The purpose of this manual is to support use of satellite-based remote sensing for statewide lake water-quality monitoring in Maine. The authors describe step-by-step methods that combine Landsat and MODIS satellite data with field-collected Secchi disk data for statewide assessment of lake water clarity. Landsat can be simultaneously used to assess more than Maine 1,000 lakes ≥ 8 ha, whereas MODIS can be used to assess a maximum of 364 lakes ≥ 100 ha (250-m image resolution) or 83 lakes ≥ 400 ha (500-m image resolution). Although the methods were specifically developed for Maine, other states or non-Maine agencies may find these methods as useful starting points in developing their own protocols for regional remote lake monitoring.
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McCullough","affiliations":[{"id":25572,"text":"University of Maine, Orono","active":true,"usgs":false}],"preferred":false,"id":641009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":641008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sader, Steven A.","contributorId":171436,"corporation":false,"usgs":false,"family":"Sader","given":"Steven","email":"","middleInitial":"A.","affiliations":[{"id":25572,"text":"University of Maine, Orono","active":true,"usgs":false}],"preferred":false,"id":641010,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70045244,"text":"ofr20121247 - 2013 - The Shoreline Management Tool—An ArcMap tool for analyzing water depth, inundated area, volume, and selected habitats, with an example for the lower Wood River Valley, Oregon","interactions":[],"lastModifiedDate":"2020-01-13T06:18:45","indexId":"ofr20121247","displayToPublicDate":"2020-01-10T14:00:00","publicationYear":"2013","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":"2012-1247","displayTitle":"The Shoreline Management Tool—An ArcMap Tool for Analyzing Water Depth, Inundated Area, Volume, and Selected Habitats, with an Example for the Lower Wood River Valley, Oregon","title":"The Shoreline Management Tool—An ArcMap tool for analyzing water depth, inundated area, volume, and selected habitats, with an example for the lower Wood River Valley, Oregon","docAbstract":"The Shoreline Management Tool is a geographic information system (GIS) based program developed to assist water- and land-resource managers in assessing the benefits and effects of changes in surface-water stage on water depth, inundated area, and water volume. Additionally, the Shoreline Management Tool can be used to identify aquatic or terrestrial habitat areas where conditions may be suitable for specific plants or animals as defined by user-specified criteria including water depth, land-surface slope, and land-surface aspect. The tool can also be used to delineate areas for use in determining a variety of hydrologic budget components such as surface-water storage, precipitation, runoff, or evapotranspiration.
The Shoreline Management Tool consists of two parts, a graphical user interface for use with Esri™ ArcMap™ GIS software to interact with the user to define scenarios and map results, and a spreadsheet in Microsoft® Excel® developed to display tables and graphs of the results. The graphical user interface allows the user to define a scenario consisting of an inundation level (stage), land areas (parcels), and habitats (areas meeting user-specified conditions) based on water depth, slope, and aspect criteria. The tool uses data consisting of land-surface elevation, tables of stage/volume and stage/area, and delineated parcel boundaries to produce maps (data layers) of inundated areas and areas that meet the habitat criteria. The tool can be run in a Single-Time Scenario mode or in a Time-Series Scenario mode, which uses an input file of dates and associated stages. The spreadsheet part of the tool uses a macro to process the results from the graphical user interface to create tables and graphs of inundated water volume, inundated area, dry area, and mean water depth for each land parcel based on the user-specified stage. The macro also creates tables and graphs of the area, perimeter, and number of polygons comprising the user-specified habitat areas within each parcel.
The Shoreline Management Tool is highly transferable, using easily generated or readily available data. The capabilities of the tool are demonstrated using data from the lower Wood River Valley adjacent to Upper Klamath and Agency Lakes in southern Oregon.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121247","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Snyder, D.T., Haluska, T.L., and Respini-Irwin, D., 2013, The Shoreline Management Tool—An ArcMap tool for analyzing water depth, inundated area, volume, and selected habitats, with an example for the lower Wood River Valley, Oregon: U.S. Geological Survey Open-File Report 2012–1247, 86 p. (Also available at https://pubs.usgs.gov/of/2012/1247/.)","productDescription":"Report: viii, 86 p.; 2 Videos: 3 minutes; Companion File","numberOfPages":"98","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":270535,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121247.jpg","text":"Report"},{"id":371153,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1247/videos.zip","text":"Videos","size":"45.4 MB","linkFileType":{"id":6,"text":"zip"}},{"id":270531,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1247/ofr20121247.pdf","text":"Report","size":"9.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2012-1247"},{"id":371154,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1247/faq.pdf","text":"Shoreline Management Tool—Frequently Asked Questions","size":"105 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":371166,"rank":5,"type":{"id":21,"text":"Referenced Work"},"url":"https://water.usgs.gov/GIS/dsdl/ShorelineManagementTool_OFR2012-1247_v20130410.zip","text":"Generic version","size":"39 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Intended for use in any area. Required input data must be prepared by the users as described in the report. Example Python scripts are provided to assist with the data preparation. Includes all ancillary files except those specific to the lower Wood River Valley example."},{"id":371167,"rank":6,"type":{"id":21,"text":"Referenced Work"},"url":"https://water.usgs.gov/GIS/dsdl/ShorelineManagementTool_NAVD88_OFR2012-1247_v20130410.zip","text":"Example version for the Lower Wood River Valley, Oregon - NAVD88","size":"1.9 GB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Contains all required data for use in the lower Wood River Valley of southern Oregon. Ready to run. Utilizes the North American Vertical Datum of 1988 (NAVD88) for elevation reference. Useful for training purposes or examination of input datasets and output results. Includes all ancillary files."},{"id":371168,"rank":7,"type":{"id":21,"text":"Referenced Work"},"url":"https://water.usgs.gov/GIS/dsdl/ShorelineManagementTool_NGVD29_OFR2012-1247_v20130410.zip","text":"Example version for the Lower Wood River Valley, Oregon - NGVD29/UKLVD","size":"2.0 GB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Contains all required data for use in the lower Wood River Valley of southern Oregon. Ready to run. Utilizes the National Geodetic Vertical Datum of 1929 (NGVD29) for elevation reference. Also contains data for use with the Upper Klamath Lake Vertical Datum (UKLVD). Useful for training purposes or examination of input datasets and output results. Includes all ancillary files."}],"country":"United States","state":"Oregon","otherGeospatial":"Wood River Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.61,42.0 ], [ -124.61,46.29 ], [ -116.46,46.29 ], [ -116.46,42.0 ], [ -124.61,42.0 ] ] ] } } ] }","contact":"Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
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A one-dimensional diffusion analogy model for estimating tide heights in coastal marshes was developed and calibrated by using data from previous tidal-marsh studies. The method is simpler to use than other one- and two-dimensional hydrodynamic models because it does not require marsh depth and tidal prism information; however, the one-dimensional diffusion analogy model cannot be used to estimate tide heights, flow velocities, and tide arrival times for tide conditions other than the highest tide for which it is calibrated. Limited validation of the method indicates that it has an accuracy within 0.3 feet. The method can be applied with limited calibration information that is based entirely on remote sensing or geographic information system data layers. The method can be used to estimate high-tide heights in tidal wetlands drained by tide gates where tide levels cannot be observed directly by opening the gates without risk of flooding properties and structures. A geographic information system application of the method is demonstrated for Sybil Creek marsh in Branford, Connecticut. The tidal flux into this marsh is controlled by two tide gates that prevent full tidal inundation of the marsh. The method application shows reasonable tide heights for the gates-closed condition (the normal condition) and the one-gate-open condition on the basis of comparison with observed heights. The condition with all tide gates open (two gates) was simulated with the model; results indicate where several structures would be flooded if the gates were removed as part of restoration efforts or if the tide gates were to fail.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135076","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Bjerklie, D.M., O’Brien, Kevin, and Rozsa, Ron, 2013, A one-dimensional diffusion analogy model for estimation of tide heights in selected tidal marshes in Connecticut (ver. 1.1, December 2019): U.S. Geological Survey Scientific Investigations Report 2013–5076, 17 p., https://doi.org/10.3133/sir20135076.","productDescription":"iv, 17 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":273622,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5076/index.html"},{"id":370389,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2013/5076/versionhist.txt","size":"485 B","linkFileType":{"id":2,"text":"txt"}},{"id":273623,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5076/sir20135076.pdf","text":"Report","size":"3.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2013-5076"},{"id":273624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2013/5076/coverthb2.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Leetes Island, Pine Creek, Sybil Creek, Wilson Cove Marshes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.5,41 ], [ -73.5,41.6 ], [ -72.3,41.6 ], [ -72.3,41 ], [ -73.5,41 ] ] ] } } ] }","edition":"Version 1.1: December 30, 2019; Version 1.0 June 11, 2013","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Across the country, public land managers make decisions each year that influence landscapes and ecosystems within their jurisdictions. Many of these decisions involve vegetation manipulations, which often are referred to as land treatments. These treatments include removal or alteration of plant biomass, seeding of burned areas, application of herbicides, and other activities. Data documenting these land treatments usually are stored at local management offices in various formats. Therefore, anyone interested in the types and effects of land treatments across multiple jurisdictions must first assemble the information, which can be difficult if data discovery and organization involve multiple local offices. A centralized system for storing and accessing the data helps inform land managers when making policy and management considerations and assists scientists in developing sampling designs and studies.
The Land Treatment Digital Library (LTDL) was created by the U.S. Geological Survey (USGS) as a comprehensive database incorporating tabular data, documentation, photographs, and spatial data about land treatments in a single system. It was developed over a period of several years and refined based on feedback from partner agencies and stakeholders. Currently, Bureau of Land Management (BLM) land treatment data are being entered by USGS personnel as part of a memorandum of understanding between the USGS and BLM. The LTDL has a website maintained by the USGS Forest and Rangeland Ecosystem Science Center where LTDL data can be viewed https://www.usgs.gov/apps/ltdl.
The resources and information provided in this data series allow other agencies, organizations, and individuals to download an empty, stand-alone LTDL database to individual or networked computers. Data entered in these databases may be submitted to the USGS for possible inclusion in the online LTDL.
Multiple computer programs are used to accomplish the objective of the LTDL. The support of an information-technology specialist or professionals familiar with Microsoft Access™, ESRI’s ArcGIS™, Python, Adobe Acrobat Professional™, and computer settings is essential when installing and operating the LTDL. After the program is operational, a critical element for successful data entry is an understanding of the difference between database tables and forms, and how to edit data in both formats. Complete instructions accompany the program, and they should be followed carefully to ensure the setup and operation of the database goes smoothly.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds749","usgsCitation":"Welty, J.L., and Pilliod, D.S., 2013, Data entry module and manuals for the Land Treatment Digital Library: U.S. Geological Survey Data Series 749, https://pubs.usgs.gov/ds/749.","productDescription":"Pamphlet: 56 p.; 5 Companion Files; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":275362,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL%20User%20Guides%20for%20ArcGIS%2010.0.zip","size":"5.55 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Land Treatment Digital Library User Guides for ArcGIS 10.0"},{"id":275363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL%20User%27s%20Manual%20and%20Installation%20Instructions%20Arc10.1.pdf","size":"4.29 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Land Treatment Digital Library User Guides for ArcGIS 10.1"},{"id":275364,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL%20User%20Guides%20for%20ArcGIS%2010.1.zip","size":"5.55 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Land Treatment Digital Library User Guides for ArcGIS 10.1"},{"id":275360,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL%20User%27s%20Manual%20and%20Installation%20Instructions%20Arc10.0.pdf","size":"4.19 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Land Treatment Digital Library User Guides for ArcGIS 10.0"},{"id":275366,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL_metadata.zip","size":"30.1 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Land Treatment Digital Library Metadata"},{"id":275361,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL_Data_10.0.zip","size":"913 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Land Treatment Digital Library Data 10.0"},{"id":275365,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL_Data_10.1.zip","size":"942 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Land Treatment Digital Library Data 10.1"},{"id":275367,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds749.png"}],"contact":"Forest and Rangeland Ecosystem Science Center (FRESC)
U.S. Geological Survey
777 NW 9th Street
Corvallis, Oregon 97330
The economy, national security, and standard of living of the United States depend heavily on adequate and reliable supplies of energy and mineral resources. Based on population and consumption trends, the Nation’s use of energy and minerals can be expected to grow, driving the demand for ever broader scientific understanding of resource formation, location, and availability. In addition, the increasing importance of environmental stewardship, human health, and sustainable growth places further emphasis on energy and mineral resources research and understanding. Collectively, these trends in resource demand and the interconnectedness among resources will lead to new challenges and, in turn, require cutting-edge science for the next generation of societal decisions.
The long and continuing history of U.S. Geological Survey contributions to energy and mineral resources science provide a solid foundation of core capabilities upon which new research directions can grow. This science strategy provides a framework for the coming decade that capitalizes on the growth of core capabilities and leverages their application toward new or emerging challenges in energy and mineral resources research, as reflected in five interrelated goals.
Within each goal, multiple actions are identified. The level of specificity and complexity of these actions varies, consistent with the reality that even a modest refocus can yield large payoffs in the near term whereas more ambitious plans may take years to reach fruition. As such, implementation of these actions is largely dependent on available resources and the sequencing of prerequisite steps. This science strategy places an emphasis on interdisciplinary collaboration and leveraging of expertise across the U.S. Geological Survey and with external partners.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1383D","usgsCitation":"Ferrero, R.C., Kolak, J.J., Bills, D.J., Bowen, Z.H., Cordier, D.J., Gallegos, T.J., Hein, J.R., Kelley, K.D., Nelson, P.H., Nuccio, V.F., Schmidt, J.M., and Seal, R.R., 2013, U.S. Geological Survey energy and minerals science strategy— A resource lifecycle approach: U.S. Geological Survey Circular 1383–D, 37 p.","productDescription":"ix, 37 p.","numberOfPages":"52","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":260,"text":"Energy and Minerals","active":false,"usgs":true}],"links":[{"id":270894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1383d.gif"},{"id":270893,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1383d/circ1383-D.pdf","text":"Report","size":"12.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1383-D"}],"contact":"Energy and Minerals
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policymakers are faced with countless decisions each year at local, regional, and national levels on issues as diverse as renewable and nonrenewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decisionmaking is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and wellbeing of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decisionmakers as they develop policies to adapt to these changes.
This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that U.S. Geological Survey (USGS) scientists and partners can play in building scientific understanding and providing timely information to decisionmakers. The strategy underscores the connection between scientific discoveries and the application of new knowledge, and it integrates ecosystem science and decisionmaking, producing new scientific outcomes to assist resource managers and providing public benefits. We envision the USGS as a leader in integrating scientific information into decisionmaking processes that affect the Nation’s natural resources and human well-being.
The USGS is uniquely positioned to play a pivotal role in ecosystem science. With its wide range of expertise, the Bureau can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the Department of the Interior (DOI) and other partners in the natural sciences, in both conducting science and applying the results. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct.
The heart of this strategy is a framework for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected components that reinforce our vision of the USGS providing science that is at the forefront of decisionmaking:
Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy:
Following the four strategic approaches are a set of proposed actions that represent a sampling of specific USGS activities that align with this strategy and that address the Nation’s most pressing environmental needs.
The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio.
Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role in guiding sound decisionmaking during the next decade by advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1383C","usgsCitation":"Williams, B.K., Wingard, G.L., Brewer, Gary, Cloern, J.E., Gelfenbaum, Guy, Jacobson, R.B., Kershner, J.L., McGuire, A.D., Nichols, J.D., Shapiro, C.D., van Riper III, Charles, and White, R.P., 2013, U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration: U.S. Geological Survey Circular 1383–C, 43 p.","productDescription":"vii, 43 p.","numberOfPages":"56","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true}],"links":[{"id":270889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1383c.gif"},{"id":270886,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1383c/circ1383-C.pdf","text":"Report","size":"16.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1383-C"}],"contact":"Ecosystems
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Core Science Systems is a new mission of the U.S. Geological Survey (USGS) that resulted from the 2007 Science Strategy, “Facing Tomorrow’s Challenges: U.S. Geological Survey Science in the Decade 2007–2017.” This report describes the Core Science Systems vision and outlines a strategy to facilitate integrated characterization and understanding of the complex Earth system. The vision and suggested actions are bold and far-reaching, describing a conceptual model and framework to enhance the ability of the USGS to bring its core strengths to bear on pressing societal problems through data integration and scientific synthesis across the breadth of science.
The context of this report is inspired by a direction set forth in the 2007 Science Strategy. Specifically, ecosystem-based approaches provide the underpinnings for essentially all science themes that define the USGS. Every point on Earth falls within a specific ecosystem where data, other information assets, and the expertise of USGS and its many partners can be employed to quantitatively understand how that ecosystem functions and how it responds to natural and anthropogenic disturbances. Every benefit society obtains from the planet— food, water, raw materials to build infrastructure, homes and automobiles, fuel to heat homes and cities, and many others— are derived from or affect ecosystems.
The vision for Core Science Systems builds on core strengths of the USGS in characterizing and understanding complex Earth and biological systems through research, modeling, mapping, and the production of high quality data on the Nation’s natural resource infrastructure. Together, these research activities provide a foundation for ecosystem-based approaches through geologic mapping, topographic mapping, and biodiversity mapping. The vision describes a framework founded on these core mapping strengths that makes it easier for USGS scientists to discover critical information, share and publish results, and identify potential collaborations that transcend all USGS missions. The framework is designed to improve the efficiency of scientific work within USGS by establishing a means to preserve and recall data for future applications, organizing existing scientific knowledge and data to facilitate new use of older information, and establishing a future workflow that naturally integrates new data, applications, and other science products to make interdisciplinary research easier and more efficient. Given the increasing need for integrated data and interdisciplinary approaches to solve modern problems, leadership by the Core Science Systems mission will facilitate problem solving by all USGS missions in ways not formerly possible.
The report lays out a strategy to achieve this vision through three goals with accompanying objectives and actions. The first goal builds on and enhances the strengths of the Core Science Systems mission in characterizing and understanding the Earth system from the geologic framework to the topographic characteristics of the land surface and biodiversity across the Nation. The second goal enhances and develops new strengths in computer and information science to make it easier for USGS scientists to discover data and models, share and publish results, and discover connections between scientific information and knowledge. The third goal brings additional focus to research and development methods to address complex issues affecting society that require integration of knowledge and new methods for synthesizing scientific information. Collectively, the report lays out a strategy to create a seamless connection between all USGS activities to accelerate and make USGS science more efficient by fully integrating disciplinary expertise within a new and evolving science paradigm for a changing world in the 21st century.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1383B","usgsCitation":"Bristol, R.S., Euliss, N.H., Jr., Booth, N.L., Burkardt, Nina, Diffendorfer, J.E., Gesch, D.B., McCallum, B.E., Miller, D.M., Morman, S.A., Poore, B.S., Signell, R.P., and Viger, R.J., 2013, U.S. Geological Survey core science systems strategy—Characterizing, synthesizing, and understanding the critical zone through a modular science framework: U.S. Geological Survey Circular 1383–B, 33 p.","productDescription":"vi, 33 p.","numberOfPages":"44","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":270895,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1383b.gif"},{"id":270890,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1383b/circ1383-B.pdf","text":"Report","size":"16.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1383-B"}],"country":"United States","contact":"Core Science Systems
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Mineral weathering rates and a forest macronutrient uptake stoichiometry were determined for the forested, metabasaltic Hauver Branch watershed in north-central Maryland, USA. Previous studies of Hauver Branch have had an insufficient number of analytes to permit determination of rates of all the minerals involved in chemical weathering, including biomass. More equations in the mass-balance matrix were added using existing mineralogic information. The stoichiometry of a deciduous biomass term was determined using multi-year weekly to biweekly stream-water chemistry for a nearby watershed, which drains relatively unreactive quartzite bedrock.
At Hauver Branch, calcite hosts ~38 mol% of the calcium ion (Ca2+) contained in weathering minerals, but its weathering provides ~90% of the stream water Ca2+. This occurs in a landscape with a regolith residence time of more than several Ka (kiloannum). Previous studies indicate that such old regolith does not typically contain dissolving calcite that affects stream Ca2+/Na+ ratios. The relatively high calcite dissolution rate likely reflects dissolution of calcite in fractures of the deep critical zone.
Of the carbon dioxide (CO2) consumed by mineral weathering, calcite is responsible for approximately 27%, with the silicate weathering consumption rate far exceeding that of the global average. The chemical weathering of mafic terrains in decaying orogens thus may be capable of influencing global geochemical cycles, and therefore, climate, on geological timescales. Based on carbon-balance calculations, atmospheric-derived sulfuric acid is responsible for approximately 22% of the mineral weathering occurring in the watershed. Our results suggest that rising air temperatures, driven by global warming and resulting in higher precipitation, will cause the rate of chemical weathering in the Hauver Branch watershed to increase until a threshold temperature is reached. Beyond the threshold temperature, increased recharge would produce a shallower groundwater table and reduced chemical weathering rates.
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Research focused on geographical analysis to avoid, minimize and mitigate the cumulative biological effects of utility-scale solar energy development. A hierarchical logic model was created to map the compatibility of new solar energy projects with current biological conservation values. The research indicated that the extent of compatible areas is much greater than the estimated land area required to achieve 2040 greenhouse gas reduction goals. Species distribution models were produced for 65 animal and plant species that were of potential conservation significance to the Desert Renewable Energy Conservation Plan process. These models mapped historical and projected future habitat suitability using 270 meter resolution climate grids. The results were integrated into analytical frameworks to locate potential sites for offsetting project impacts and evaluating the cumulative effects of multiple solar energy projects. Examples applying these frameworks in the Western Mojave Desert ecoregion show the potential of these publicly-available tools to assist regional planning efforts. Results also highlight the necessity to explicitly consider projected land use change and climate change when prioritizing areas for conservation and mitigation offsets. 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Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Landscape-scale evaluation of asymmetric interactions between Brown Trout and Brook Trout using two-species occupancy models","docAbstract":"Predicting the distribution of native stream fishes is fundamental to the management and conservation of many species. Modeling species distributions often consists of quantifying relationships between species occurrence and abundance data at known locations with environmental data at those locations. However, it is well documented that native stream fish distributions can be altered as a result of asymmetric interactions between dominant exotic and subordinate native species. For example, the naturalized exotic Brown Trout Salmo trutta has been identified as a threat to native Brook Trout Salvelinus fontinalis in the eastern United States. To evaluate large-scale patterns of co-occurrence and to quantify the potential effects of Brown Trout presence on Brook Trout occupancy, we used data from 624 stream sites to fit two-species occupancy models. These models assumed that asymmetric interactions occurred between the two species. In addition, we examined natural and anthropogenic landscape characteristics we hypothesized would be important predictors of occurrence of both species. Estimated occupancy for Brook Trout, from a co-occurrence model with no landscape covariates, at sites with Brown Trout present was substantially lower than sites where Brown Trout were absent. We also observed opposing patterns for Brook and Brown Trout occurrence in relation to percentage forest, impervious surface, and agriculture within the network catchment. Our results are consistent with other studies and suggest that alterations to the landscape, and specifically the transition from a forested catchment to one that contains impervious surface or agriculture, reduces the occurrence probability of wild Brook Trout. Our results, however, also suggest that the presence of Brown Trout results in lower occurrence probability of Brook Trout over a range of anthropogenic landscape characteristics, compared with streams where Brown Trout were absent.
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PA","active":true,"usgs":false}],"preferred":false,"id":637156,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Detar, Jason","contributorId":171356,"corporation":false,"usgs":false,"family":"Detar","given":"Jason","email":"","affiliations":[{"id":26873,"text":"Pennsylvania Fish and Boat Commission, Bellefonte, PA","active":true,"usgs":false}],"preferred":false,"id":637155,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"John A. Sweka","contributorId":171358,"corporation":false,"usgs":false,"family":"John A. Sweka","affiliations":[{"id":26874,"text":"USFWS, Lamar, PA","active":true,"usgs":false}],"preferred":false,"id":637157,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70173470,"text":"70173470 - 2013 - Between- and within-lake responses of macrophyte richness metrics to shoreline developmen","interactions":[],"lastModifiedDate":"2016-06-17T13:52:01","indexId":"70173470","displayToPublicDate":"2015-12-07T14:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Between- and within-lake responses of macrophyte richness metrics to shoreline developmen","docAbstract":"Aquatic habitat in littoral environments can be affected by residential development of shoreline areas. We evaluated the relationship between macrophyte richness metrics and shoreline development to quantify indicator response at 2 spatial scales for Minnesota lakes. First, the response of total, submersed, and sensitive species to shoreline development was evaluated within lakes to quantify macrophyte response as a function of distance to the nearest dock. Within-lake analyses using generalized linear mixed models focused on 3 lakes of comparable size with a minimal influence of watershed land use. Survey points farther from docks had higher total species richness and presence of species sensitive to disturbance. Second, between-lake effects of shoreline development on total, submersed, emergent-floating, and sensitive species were evaluated for 1444 lakes. Generalized linear models were developed for all lakes and stratified subsets to control for lake depth and watershed land use. Between-lake analyses indicated a clear response of macrophyte richness metrics to increasing shoreline development, such that fewer emergent-floating and sensitive species were correlated with increasing density of docks. These trends were particularly evident for deeper lakes with lower watershed development. Our results provide further evidence that shoreline development is associated with degraded aquatic habitat, particularly by illustrating the response of macrophyte richness metrics across multiple lake types and different spatial scales.
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The data available for such analyses of fish and other populations are usually nonnegative integer counts of the number of organisms, often dominated by many low values with few observations of relatively high abundance. These characteristics are not well approximated by the Gaussian distribution. We present a detailed description of a negative binomial mixed-model framework that can be used to model count data and quantify temporal and spatial variability. We applied these models to data from four fishery-independent surveys of Walleyes Sander vitreus across the Great Lakes basin. Specifically, we fitted models to gill-net catches from Wisconsin waters of Lake Superior; Oneida Lake, New York; Saginaw Bay in Lake Huron, Michigan; and Ohio waters of Lake Erie. These long-term monitoring surveys varied in overall sampling intensity, the total catch of Walleyes, and the proportion of zero catches. Parameter estimation included the negative binomial scaling parameter, and we quantified the random effects as the variations among gill-net sampling sites, the variations among sampled years, and site × year interactions. This framework (i.e., the application of a mixed model appropriate for count data in a variance-partitioning context) represents a flexible approach that has implications for monitoring programs (e.g., trend detection) and for examining the potential of individual variance components to serve as response metrics to large-scale anthropogenic perturbations or ecological changes.
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Floodplains and their associated river systems are structured by four dimensional gradients of hydrogeomorphology: longitudinal, lateral, vertical, and temporal components. These four dimensions create dynamic hydrologic and geomorphologic mosaics that have a large imprint on the vegetation and nutrient biogeochemistry of floodplains. Plant physiology, population dynamics, community structure, and productivity are all very responsive to floodplain hydrogeomorphology. The strength of this relationship between vegetation and hydrogeomorphology is evident in the use of vegetation as an indicator of hydrogeomorphic processes. However, vegetation also influences hydrogeomorphology by modifying hydraulics and sediment entrainment and deposition that typically stabilize geomorphic patterns. Nitrogen and phosphorus biogeochemistry commonly influence plant productivity and community composition, although productivity is not limited by nutrient availability in all floodplains. Conversely, vegetation influences nutrient biogeochemistry through direct uptake and storage as well as production of organic matter that regulates microbial biogeochemical processes. The biogeochemistries of nitrogen and phosphorus cycling are very sensitive to spatial and temporal variation in hydrogeomorphology, in particular floodplain wetness and sedimentation. The least studied interaction is the direct effect of biogeochemistry on hydrogeomorphology, but the control of nutrient availability over organic matter decomposition and thus soil permeability and elevation is likely important. Biogeochemistry also has the more documented but indirect control of hydrogeomorphology through regulation of plant biomass. In summary, the defining characteristics of floodplain ecosystems are determined by the many interactions among physical and biological processes. Conservation and restoration of the valuable ecosystem services that floodplains provide depends on improved understanding and predictive models of interactive system controls and behavior.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecogeomorphology","language":"English","publisher":"Elsevier","publisherLocation":"Reston, VA","doi":"10.1016/B978-0-12-374739-6.00338-9","usgsCitation":"Noe, G.B., 2013, Interactions among hydrogeomorphology, vegetation, and nutrient biogeochemistry in floodplain ecosystems, chap. of Ecogeomorphology, v. 12, p. 307-321, https://doi.org/10.1016/B978-0-12-374739-6.00338-9.","productDescription":"15 p.","startPage":"307","endPage":"321","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026520","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":324307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"UNITED STATES","volume":"12","edition":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576d0832e4b07657d1a3756d","contributors":{"authors":[{"text":"Noe, G. B.","contributorId":146903,"corporation":false,"usgs":true,"family":"Noe","given":"G.","email":"","middleInitial":"B.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":640576,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159836,"text":"70159836 - 2013 - Mapping monkeypox transmission risk through time and space in the Congo Basin","interactions":[],"lastModifiedDate":"2015-12-01T11:49:37","indexId":"70159836","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Mapping monkeypox transmission risk through time and space in the Congo Basin","docAbstract":"Monkeypox is a major public health concern in the Congo Basin area, with changing patterns of human case occurrences reported in recent years. Whether this trend results from better surveillance and detection methods, reduced proportions of vaccinated vs. non-vaccinated human populations, or changing environmental conditions remains unclear. Our objective is to examine potential correlations between environment and transmission of monkeypox events in the Congo Basin. We created ecological niche models based on human cases reported in the Congo Basin by the World Health Organization at the end of the smallpox eradication campaign, in relation to remotely-sensed Normalized Difference Vegetation Index datasets from the same time period. These models predicted independent spatial subsets of monkeypox occurrences with high confidence; models were then projected onto parallel environmental datasets for the 2000s to create present-day monkeypox suitability maps. Recent trends in human monkeypox infection are associated with broad environmental changes across the Congo Basin. Our results demonstrate that ecological niche models provide useful tools for identification of areas suitable for transmission, even for poorly-known diseases like monkeypox.
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Using generalized linear models with random effects, we focus on the estimated impacts of increases in mean daily temperatures and populations in different counties on wildfire in those counties, after essentially controlling for the overall differences between counties in their overall mean temperatures and populations. We find that temperature increase appears to have a significant positive impact on both total burn area and number of observed wildfires. Population growth appears to have a much less pronounced impact on total burn area than do annual temperature increases, and population growth appears to be negatively correlated with the total number of observed wildfires. 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To explore the role of hydrogeologic heterogeneity and poorly constrained mountain hydrologic conditions on regional groundwater flow in contracted intermountain basins, a series of 3-D numerical groundwater flow models were developed using the South Park basin, Colorado, USA as a proxy. The models were used to identify the relative importance of different recharge processes to major aquifers, to estimate typical groundwater circulation depths, and to explore hydrogeologic communication between mountain and valley hydrogeologic landscapes. Modeling results show that mountain landscapes develop topographically controlled and predominantly local-scale to intermediate-scale flow systems. Permeability heterogeneity of the fold and fault belt and decreased topographic roughness led to permeability controlled flow systems in the valley. The structural position of major aquifers in the valley fold and fault belt was found to control the relative importance of different recharge mechanisms. Alternative mountain recharge model scenarios showed that higher mountain recharge rates led to higher mountain water table elevations and increasingly prominent local flow systems, primarily resulting in increased seepage within the mountain landscape and nonlinear increases in mountain block recharge to the valley. Valley aquifers were found to be relatively insensitive to changing mountain water tables, particularly in structurally isolated aquifers inside the fold and fault belt.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/2013WR014451","usgsCitation":"Ball, L.B., Caine, J.S., and Ge, S., 2013, Control on groundwater flow in a semiarid folded and faulted intermountain basin: Water Resources Research, v. 50, no. 8, p. 6788-6809, https://doi.org/10.1002/2013WR014451.","productDescription":"22 p.","startPage":"6788","endPage":"6809","ipdsId":"IP-049504","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":473350,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013wr014451","text":"Publisher Index Page"},{"id":293573,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/2013WR014451/pdf"},{"id":293583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293572,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013WR014451"}],"country":"United States","state":"Colorado","otherGeospatial":"South Park Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.0108,38.7556 ], [ -106.0108,39.3886 ], [ -105.4682,39.3886 ], [ -105.4682,38.7556 ], [ -106.0108,38.7556 ] ] ] } } ] }","volume":"50","issue":"8","noUsgsAuthors":false,"publicationDate":"2014-08-22","publicationStatus":"PW","scienceBaseUri":"541157b2e4b0fe7e184a5535","contributors":{"authors":[{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":500468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caine, Jonathan S. 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":1272,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan","email":"jscaine@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":500470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ge, Shemin","contributorId":37366,"corporation":false,"usgs":true,"family":"Ge","given":"Shemin","affiliations":[],"preferred":false,"id":500469,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70116460,"text":"70116460 - 2013 - Geomorphic characterization of four shelf-sourced submarine canyons along the U.S. Mid-Atlantic continental margin","interactions":[],"lastModifiedDate":"2017-11-18T10:19:35","indexId":"70116460","displayToPublicDate":"2014-06-01T16:03:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1371,"text":"Deep-Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic characterization of four shelf-sourced submarine canyons along the U.S. Mid-Atlantic continental margin","docAbstract":"Shelf-sourced submarine canyons are common features of continental margins and are fundamental to deep-sea sedimentary systems. Despite their geomorphic and geologic significance, relatively few passive margin shelf-breaching canyons worldwide have been mapped using modern geophysical methods. Between 2007 and 2012 a series of geophysical surveys was conducted across four major canyons of the US Mid-Atlantic margin: Wilmington, Baltimore, Washington, and Norfolk canyons. More than 5700 km2 of high-resolution multibeam bathymetry and 890 line-km of sub-bottom CHIRP profiles were collected along the outer shelf and uppermost slope (depths of 80-1200 m). The data allowed us to compare and contrast the fine-scale morphology of each canyon system. The canyons have marked differences in the morphology and orientation of canyon heads, steepness and density of sidewall gullies, and the character of the continental shelf surrounding canyon rims. Down-canyon axial profiles for Washington, Baltimore and Wilmington canyons have linear shapes, and each canyon thalweg exhibits morphological evidence for recent, relatively small-scale sediment transport. For example, Washington Canyon displays extremely steep wall gradients and contains ~100 m wide, 5–10 m deep, v-shaped incisions down the canyon axis, suggesting modern or recent sediment transport. In contrast, the convex axial thalweg profile, the absence of thalweg incision, and evidence for sediment infilling at the canyon head, suggest that depositional processes strongly influence Norfolk Canyon during the current sea-level high-stand. The north walls of Wilmington, Washington and Norfolk canyons are steeper than the south walls due to differential erosion, though the underlying cause for this asymmetry is not clear. Furthermore, we speculate that most of the geomorphic features observed within the canyons (e.g., terraces, tributary canyons, gullies, and hanging valleys) were formed during the Pleistocene, and show only subtle modification by Holocene processes active during the present sea-level high-stand.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Deep-Sea Research Part II: Topical Studies in Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2013.09.013","usgsCitation":"Obelcz, J., Brothers, D., Chaytor, J., ten Brink, U., Ross, S., and Brooke, S., 2013, Geomorphic characterization of four shelf-sourced submarine canyons along the U.S. Mid-Atlantic continental margin: Deep-Sea Research Part II: Topical Studies in Oceanography, v. 104, p. 106-119, https://doi.org/10.1016/j.dsr2.2013.09.013.","productDescription":"14 p.","startPage":"106","endPage":"119","numberOfPages":"14","ipdsId":"IP-051303","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":289824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289822,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.dsr2.2013.09.013"}],"country":"United States","otherGeospatial":"Cape Hatteras;Georges Bank;Hudson Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.0,37.0 ], [ -75.0,38.0 ], [ -72.0,38.0 ], [ -72.0,37.0 ], [ -75.0,37.0 ] ] ] } } ] }","volume":"104","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53c0ebe7e4b065ccca5fe38f","contributors":{"authors":[{"text":"Obelcz, Jeffrey jobelcz@usgs.gov","contributorId":5430,"corporation":false,"usgs":true,"family":"Obelcz","given":"Jeffrey","email":"jobelcz@usgs.gov","affiliations":[],"preferred":true,"id":495806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. dbrothers@usgs.gov","contributorId":3782,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","email":"dbrothers@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":495804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chaytor, Jason D. jchaytor@usgs.gov","contributorId":4961,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason D.","email":"jchaytor@usgs.gov","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":495805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":495808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ross, Steve W.","contributorId":41134,"corporation":false,"usgs":false,"family":"Ross","given":"Steve W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":495807,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brooke, Sandra","contributorId":101570,"corporation":false,"usgs":true,"family":"Brooke","given":"Sandra","affiliations":[],"preferred":false,"id":495809,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70128155,"text":"70128155 - 2013 - Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation","interactions":[],"lastModifiedDate":"2014-10-07T08:56:56","indexId":"70128155","displayToPublicDate":"2014-06-01T08:55:53","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation","docAbstract":"Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Climatology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Royal Meteorological Society","publisherLocation":"Chichester","doi":"10.1002/joc.3835","usgsCitation":"Alvarez, O., Guo, Q., Klinger, R.C., Li, W., and Doherty, P., 2013, Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation: International Journal of Climatology, v. 34, no. 7, p. 2258-2268, https://doi.org/10.1002/joc.3835.","productDescription":"11 p.","startPage":"2258","endPage":"2268","numberOfPages":"11","ipdsId":"IP-050933","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294953,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/joc.3835"}],"volume":"34","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-10-18","publicationStatus":"PW","scienceBaseUri":"543500a1e4b0a4f4b46a237e","contributors":{"authors":[{"text":"Alvarez, Otto","contributorId":86284,"corporation":false,"usgs":true,"family":"Alvarez","given":"Otto","affiliations":[],"preferred":false,"id":502779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guo, Qinghua","contributorId":32855,"corporation":false,"usgs":true,"family":"Guo","given":"Qinghua","affiliations":[],"preferred":false,"id":502777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klinger, Robert C. 0000-0003-3193-3199 rcklinger@usgs.gov","orcid":"https://orcid.org/0000-0003-3193-3199","contributorId":5395,"corporation":false,"usgs":true,"family":"Klinger","given":"Robert","email":"rcklinger@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":502776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Wenkai","contributorId":108044,"corporation":false,"usgs":true,"family":"Li","given":"Wenkai","affiliations":[],"preferred":false,"id":502780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, Paul","contributorId":38494,"corporation":false,"usgs":true,"family":"Doherty","given":"Paul","affiliations":[],"preferred":false,"id":502778,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70116725,"text":"70116725 - 2013 - Modeling erosion of ice-rich permafrost bluffs along the Alaskan Beaufort Sea coast","interactions":[],"lastModifiedDate":"2014-07-16T09:23:42","indexId":"70116725","displayToPublicDate":"2014-05-28T09:20:05","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Modeling erosion of ice-rich permafrost bluffs along the Alaskan Beaufort Sea coast","docAbstract":"The Arctic climate is changing, inducing accelerating retreat of ice-rich permafrost coastal\nbluffs. Along Alaska’s Beaufort Sea coast, erosion rates have increased roughly threefold from 6.8 to\n19 m yr−1 since 1955 while the sea ice-free season has increased roughly twofold from 45 to 100 days since\n1979. We develop a numerical model of bluff retreat to assess the relative roles of the length of sea ice-free\nseason, sea level, water temperature, nearshore wavefield, and permafrost temperature in controlling\nerosion rates in this setting. The model captures the processes of erosion observed in short-term\nmonitoring experiments along the Beaufort Sea coast, including evolution of melt notches, topple of ice\nwedge-bounded blocks, and degradation of these blocks. Model results agree with time-lapse imagery\nof bluff evolution and time series of ocean-based instrumentation. Erosion is highly episodic with 40% of\nerosion is accomplished during less than 5% of the sea ice-free season. Among the formulations of the\nsubmarine erosion rate we assessed, we advocate those that employ both water temperature and nearshore\nwavefield. As high water levels are a prerequisite for erosion, any future changes that increase the frequency\nwith which water levels exceed the base of the bluffs will increase rates of coastal erosion. The certain\nincreases in sea level and potential changes in storminess will both contribute to this effect. As water\ntemperature also influences erosion rates, any further expansion of the sea ice-free season into the\nmidsummer period of greatest insolation is likely to result in an additional increase in coastal retreat rates.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research F: Earth Surface","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/2013JF002845","usgsCitation":"Barnhart, K.R., Anderson, R., Overeem, I., Wobus, C., Clow, G.D., and Urban, F., 2013, Modeling erosion of ice-rich permafrost bluffs along the Alaskan Beaufort Sea coast: Journal of Geophysical Research F: Earth Surface, v. 119, no. 5, p. 1155-1179, https://doi.org/10.1002/2013JF002845.","productDescription":"25 p.","startPage":"1155","endPage":"1179","numberOfPages":"25","ipdsId":"IP-052403","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":473351,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013jf002845","text":"Publisher Index Page"},{"id":290194,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013JF002845"},{"id":290242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea Coast","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.11,68.68 ], [ -156.11,74.68 ], [ -105.1,74.68 ], [ -105.1,68.68 ], [ -156.11,68.68 ] ] ] } } ] }","volume":"119","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-05-28","publicationStatus":"PW","scienceBaseUri":"53c79f05e4b0194841642477","contributors":{"authors":[{"text":"Barnhart, Katherine R.","contributorId":42142,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":495837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Robert S.","contributorId":102396,"corporation":false,"usgs":true,"family":"Anderson","given":"Robert S.","affiliations":[],"preferred":false,"id":495839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overeem, Irina","contributorId":29320,"corporation":false,"usgs":true,"family":"Overeem","given":"Irina","affiliations":[],"preferred":false,"id":495836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wobus, Cameron","contributorId":26978,"corporation":false,"usgs":true,"family":"Wobus","given":"Cameron","email":"","affiliations":[],"preferred":false,"id":495835,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clow, Gary D. 0000-0002-2262-3853 clow@usgs.gov","orcid":"https://orcid.org/0000-0002-2262-3853","contributorId":2066,"corporation":false,"usgs":true,"family":"Clow","given":"Gary","email":"clow@usgs.gov","middleInitial":"D.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":495834,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Urban, Frank E. 0000-0002-1329-1703","orcid":"https://orcid.org/0000-0002-1329-1703","contributorId":80918,"corporation":false,"usgs":true,"family":"Urban","given":"Frank E.","affiliations":[],"preferred":false,"id":495838,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70095241,"text":"70095241 - 2013 - Desert shrub responses to experimental modification of precipitation seasonality and soil depth: relationship to the two-layer model and ecohydrological niche","interactions":[],"lastModifiedDate":"2014-06-27T13:50:25","indexId":"70095241","displayToPublicDate":"2014-05-14T13:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Desert shrub responses to experimental modification of precipitation seasonality and soil depth: relationship to the two-layer model and ecohydrological niche","docAbstract":"1. Ecohydrological niches are important for understanding plant community responses to climate shifts, particularly in dry lands. According to the two-layer hypothesis, selective use of deep-soil water increases growth or persistence of woody species during warm and dry summer periods and thereby contributes to their coexistence with shallow-rooted herbs in dry ecosystems. The resource-pool hypothesis further suggests that shallow-soil water benefits growth of all plants while deep-soil water primarily enhances physiological maintenance and survival of woody species. Few studies have directly tested these by manipulating deep-soil water availability and observing the long-term outcomes.
\n2. We predicted that factors promoting infiltration and storage of water in deep soils, specifically greater winter precipitation and soil depth, would enhance Artemisia tridentata (big sagebrush) in cold, winter-wet/summer-dry desert. Sagebrush responses to 20 years of winter irrigation were compared to summer- or no irrigation, on plots having relatively deep or shallow soils (2 m vs. 1 m depths).
\n3. Winter irrigation increased sagebrush cover, and crown and canopy volumes, but not density (individuals/plot) compared to summer or no irrigation, on deep-soil plots. On shallow-soil plots, winter irrigation surprisingly decreased shrub cover and size, and summer irrigation had no effect. Furthermore, multiple regression suggested that the variations in growth were related (i) firstly to water in shallow soils (0-0.2 m) and secondly to deeper soils (> 1 m deep) and (ii) more by springtime than by midsummer soil water. Water-use efficiency increased considerably on shallow soils without irrigation and was lowest with winter irrigation.
\n4. Synthesis. Sagebrush was more responsive to the seasonal timing of precipitation than to total annual precipitation. Factors that enhanced deep-water storage (deeper soils plus more winter precipitation) led to increases in Artemisia tridentata that were consistent with the two-layer hypothesis, and the contribution of shallow water to growth on these plots was consistent with the resource-pool hypothesis. However, shallow-soil water also had negative effects on sagebrush, suggesting an ecohydrological trade-off not considered in these or related theories. The interaction between precipitation timing and soil depth indicates that increased winter precipitation could lead to a mosaic of increases and decreases in A. tridentata across landscapes having variable soil depth.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/1365-2745.12266","usgsCitation":"Germino, M., and Reinhardt, K., 2013, Desert shrub responses to experimental modification of precipitation seasonality and soil depth: relationship to the two-layer model and ecohydrological niche: Journal of Ecology, v. 102, no. 4, p. 989-997, https://doi.org/10.1111/1365-2745.12266.","productDescription":"9 p.","startPage":"989","endPage":"997","numberOfPages":"9","ipdsId":"IP-052846","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.12266","text":"Publisher Index Page"},{"id":288083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288081,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2745.12266"}],"country":"United States","state":"Idaho","otherGeospatial":"Snake River Plain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.8726,42.4829 ], [ -116.8726,44.3356 ], [ -111.3496,44.3356 ], [ -111.3496,42.4829 ], [ -116.8726,42.4829 ] ] ] } } ] }","volume":"102","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-05-14","publicationStatus":"PW","scienceBaseUri":"53903feae4b04eea98bf8509","contributors":{"authors":[{"text":"Germino, Matthew J.","contributorId":50029,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[],"preferred":false,"id":491149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reinhardt, Keith","contributorId":11949,"corporation":false,"usgs":true,"family":"Reinhardt","given":"Keith","affiliations":[],"preferred":false,"id":491148,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70058631,"text":"70058631 - 2013 - Monitoring gray wolf populations using multiple survey methods","interactions":[],"lastModifiedDate":"2014-05-06T15:55:20","indexId":"70058631","displayToPublicDate":"2014-05-06T15:28:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring gray wolf populations using multiple survey methods","docAbstract":"The behavioral patterns and large territories of large carnivores make them challenging to monitor. Occupancy modeling provides a framework for monitoring population dynamics and distribution of territorial carnivores. We combined data from hunter surveys, howling and sign surveys conducted at predicted wolf rendezvous sites, and locations of radiocollared wolves to model occupancy and estimate the number of gray wolf (Canis lupus) packs and individuals in Idaho during 2009 and 2010. We explicitly accounted for potential misidentification of occupied cells (i.e., false positives) using an extension of the multi-state occupancy framework. We found agreement between model predictions and distribution and estimates of number of wolf packs and individual wolves reported by Idaho Department of Fish and Game and Nez Perce Tribe from intensive radiotelemetry-based monitoring. Estimates of individual wolves from occupancy models that excluded data from radiocollared wolves were within an average of 12.0% (SD = 6.0) of existing statewide minimum counts. Models using only hunter survey data generally estimated the lowest abundance, whereas models using all data generally provided the highest estimates of abundance, although only marginally higher. Precision across approaches ranged from 14% to 28% of mean estimates and models that used all data streams generally provided the most precise estimates. We demonstrated that an occupancy model based on different survey methods can yield estimates of the number and distribution of wolf packs and individual wolf abundance with reasonable measures of precision. Assumptions of the approach including that average territory size is known, average pack size is known, and territories do not overlap, must be evaluated periodically using independent field data to ensure occupancy estimates remain reliable. Use of multiple survey methods helps to ensure that occupancy estimates are robust to weaknesses or changes in any 1 survey method. Occupancy modeling may be useful for standardizing estimates across large landscapes, even if survey methods differ across regions, allowing for inferences about broad-scale population dynamics of wolves.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.654","usgsCitation":"Ausband, D., Rich, L.N., Glenn, E., Mitchell, M.S., Zager, P., Miller, D.A., Waits, L.P., Ackerman, B.B., and Mack, C.M., 2013, Monitoring gray wolf populations using multiple survey methods: Journal of Wildlife Management, v. 78, no. 2, p. 335-346, https://doi.org/10.1002/jwmg.654.","productDescription":"12 p.","startPage":"335","endPage":"346","ipdsId":"IP-048939","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":286941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286940,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.654"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.24,41.99 ], [ -117.24,49.00 ], [ -111.04,49.00 ], [ -111.04,41.99 ], [ -117.24,41.99 ] ] ] } } ] }","volume":"78","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-13","publicationStatus":"PW","scienceBaseUri":"5369f651e4b063fb73c0a9e7","contributors":{"authors":[{"text":"Ausband, David E.","contributorId":51441,"corporation":false,"usgs":true,"family":"Ausband","given":"David E.","affiliations":[],"preferred":false,"id":487207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rich, Lindsey N.","contributorId":42119,"corporation":false,"usgs":true,"family":"Rich","given":"Lindsey","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":487206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Elizabeth M.","contributorId":96568,"corporation":false,"usgs":true,"family":"Glenn","given":"Elizabeth M.","affiliations":[],"preferred":false,"id":487211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":487203,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zager, Pete","contributorId":90645,"corporation":false,"usgs":true,"family":"Zager","given":"Pete","affiliations":[],"preferred":false,"id":487210,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, David A.W. davidmiller@usgs.gov","contributorId":4043,"corporation":false,"usgs":true,"family":"Miller","given":"David","email":"davidmiller@usgs.gov","middleInitial":"A.W.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":487204,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waits, Lisette P.","contributorId":87673,"corporation":false,"usgs":true,"family":"Waits","given":"Lisette","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":487209,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ackerman, Bruce B.","contributorId":6526,"corporation":false,"usgs":true,"family":"Ackerman","given":"Bruce","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":487205,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mack, Curt M.","contributorId":58948,"corporation":false,"usgs":true,"family":"Mack","given":"Curt","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":487208,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70103281,"text":"sim3022 - 2013 - Metallogenic belt and mineral deposit maps of northeast Asia","interactions":[],"lastModifiedDate":"2023-05-26T15:56:06.537967","indexId":"sim3022","displayToPublicDate":"2014-04-30T14:11:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3022","title":"Metallogenic belt and mineral deposit maps of northeast Asia","docAbstract":"This report contains explanatory material and summary tables for lode mineral deposits and placer districts (Map A, sheet 1) and metallogenic belts of Northeast Asia (Maps B, C, and D on sheets 2, 3, and 4, respectively). The map region includes eastern Siberia, southeastern Russia, Mongolia, northeast China, and Japan. A large group of geologists—members of the joint international project, Major Mineral Deposits, Metallogenesis, and Tectonics of Northeast Asia—prepared the maps, tables, and introductory text. This is a cooperative project with the Russian Academy of Sciences, Mongolian Academy of Sciences, Mongolian National University, Ulaanbaatar, Mongolian Technical University, Mineral Resources Authority of Mongolia, Geological Research Institute, Jilin University, China Geological Survey, Korea Institute of Geoscience and Mineral Resources, Geological Survey of Japan, and U.S. Geological Survey. This report is one of a series of reports on the mineral resources, geodynamics, and metallogenesis of Northeast Asia. Companion studies include (1) a detailed geodynamics map of Northeast Asia (Parfenov and others, 2003); (2) a compilation of major mineral deposit models (Rodionov and Nokleberg, 2000; Rodionov and others, 2000); (3) a series of metallogenic belt maps (Obolenskiy and others, 2004); (4) location map of lode mineral deposits and placer districts of Northeast Asia (Ariunbileg and others, 2003b); (5) descriptions of metallogenic belts (Rodionov and others, 2004); (6) a database on significant metalliferous and selected nonmetalliferous lode deposits and selected placer districts (Ariunbileg and others, 2003a); and (7) a series of summary project publications (Ariunbileg and 74 others, 2003b).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3022","collaboration":"Prepared in collaboration with Russian Academy of Sciences, Mongolian Academy of Sciences, Jilin University, Korean Institute of Geoscience and Minerals, Geological Survey of Japan/National Institute of Advanced Industrial Science and Technology","usgsCitation":"Obolenskiy, A.A., Rodionov, S.M., Dejidmaa, G., Gerel, O., Hwang, D., Miller, R.J., Nokleberg, W.J., Ogasawara, M., Smelov, A., Yan, H., and Seminskiy, Z.V., 2013, Metallogenic belt and mineral deposit maps of northeast Asia: U.S. Geological Survey Scientific Investigations Map 3022, 4 Sheets: 46.35 x 39.53 inches and smaller; Pamphlet: i, 14 p.; Readme; Metadata; Database; 3 Tables, https://doi.org/10.3133/sim3022.","productDescription":"4 Sheets: 46.35 x 39.53 inches and smaller; Pamphlet: i, 14 p.; Readme; Metadata; Database; 3 Tables","numberOfPages":"16","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":286814,"rank":13,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3022.jpg"},{"id":286802,"rank":6,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3022/","linkFileType":{"id":5,"text":"html"}},{"id":286810,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_data.zip"},{"id":286807,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_pamphlet.pdf"},{"id":286811,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_Table%201.zip"},{"id":286812,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_Table%202.zip"},{"id":286813,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_Table%203.zip"},{"id":286808,"rank":12,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_readme.txt"},{"id":286804,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet2.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286805,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet3.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286806,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet4.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286803,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286809,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3022/downloads/metadata/"}],"scale":"7500000","projection":"Lambert Azimuthal equal-area projection","country":"China, Japan, Mongolia, Russia","otherGeospatial":"Asia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 75.0,32.0 ], [ 75.0,82.0 ], [ 144.0,82.0 ], [ 144.0,32.0 ], [ 75.0,32.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53620d52e4b0c409c6289a30","contributors":{"authors":[{"text":"Obolenskiy, Alexander A. (compiler)","contributorId":11121,"corporation":false,"usgs":true,"family":"Obolenskiy","given":"Alexander","suffix":"(compiler)","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":493232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodionov, Sergey M.","contributorId":64726,"corporation":false,"usgs":true,"family":"Rodionov","given":"Sergey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dejidmaa, Gunchin","contributorId":47865,"corporation":false,"usgs":true,"family":"Dejidmaa","given":"Gunchin","email":"","affiliations":[],"preferred":false,"id":493237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerel, Ochir","contributorId":41520,"corporation":false,"usgs":true,"family":"Gerel","given":"Ochir","email":"","affiliations":[],"preferred":false,"id":493235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hwang, Duk-Hwan","contributorId":43804,"corporation":false,"usgs":true,"family":"Hwang","given":"Duk-Hwan","email":"","affiliations":[],"preferred":false,"id":493236,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Robert J. rjmiller@usgs.gov","contributorId":2516,"corporation":false,"usgs":true,"family":"Miller","given":"Robert","email":"rjmiller@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":493231,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nokleberg, Warren J. 0000-0002-1574-8869 wnokleberg@usgs.gov","orcid":"https://orcid.org/0000-0002-1574-8869","contributorId":2077,"corporation":false,"usgs":true,"family":"Nokleberg","given":"Warren","email":"wnokleberg@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":493230,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ogasawara, Masatsugu","contributorId":17638,"corporation":false,"usgs":true,"family":"Ogasawara","given":"Masatsugu","email":"","affiliations":[],"preferred":false,"id":493233,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smelov, Alexander P.","contributorId":30685,"corporation":false,"usgs":true,"family":"Smelov","given":"Alexander P.","affiliations":[],"preferred":false,"id":493234,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yan, Hongquan","contributorId":81559,"corporation":false,"usgs":true,"family":"Yan","given":"Hongquan","email":"","affiliations":[],"preferred":false,"id":493239,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Seminskiy, Zhan V.","contributorId":102567,"corporation":false,"usgs":true,"family":"Seminskiy","given":"Zhan","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":493240,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70199974,"text":"70199974 - 2013 - Drivers of circulation in a fringing coral reef embayment: A wave-flow coupled numerical modeling study of Hanalei Bay, Hawaii","interactions":[],"lastModifiedDate":"2018-10-09T14:50:30","indexId":"70199974","displayToPublicDate":"2014-04-15T14:50:14","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of circulation in a fringing coral reef embayment: A wave-flow coupled numerical modeling study of Hanalei Bay, Hawaii","docAbstract":"A coupled wave-circulation numerical model of Hanalei Bay, Hawaii, was constructed to investigate controls on nearshore hydrodynamics and overall circulation of a bathymetrically-complex coral reef embayment that is exposed to large waves and river floods several times per annum. The model was calibrated using in situ data representative of the two conditions that dominate the region's wave climate: one associated with local trade winds and associated trade-wind waves, and the other with distant-source episodic large swells. The model results were improved by including spatially-varying hydrodynamic bed roughness and making the semi-empirical wave-breaking parameter dependent on incident wave steepness and reef slope. During trade-wind conditions, circulation was primarily wind-driven and volume flux-based flushing times of the bay were on the order of 35 h. Under the episodic swell conditions, circulation were dominated by wave-driven flows and flushing times decreased to as little as 2 h. The vigorous hydrodynamics that occur during the upper 10% most energetic swell conditions indicate that only a few (0–10) events each year are likely capable of exporting significant volumes of sediment from the bay. Like many fringing reef areas backed by steep-sided watersheds on tropical and sub-tropical high islands worldwide, Hanalei Bay receives high episodic fluvial sediment load during a similarly low number of flood events. These similarly episodic but decoupled processes of sediment delivery and removal identified here suggest that the water quality and sedimentary environment of Hanalei Bay and similar linked watershed-reef systems are sensitive to changes in annual storm frequency and intensity.