Habitat loss and fragmentation are considered the main causes of species extinctions, particularly in tropical ecosystems. The objective of this work was to evaluate the temporal dynamics of tropical bird communities in landscapes with different levels of fragmentation in eastern Guatemala. We evaluated five bird community dynamic parameters for forest specialists and generalists: (1) species extinction, (2) species turnover, (3) number of colonizing species, (4) relative species richness, and (5) a homogeneity index. For each of 24 landscapes, community dynamic parameters were estimated from bird point count data, for the 1998–1999 and 2008–2009 periods, accounting for species’ detection probability. Forest specialists had higher extinction rates and a smaller number of colonizing species in landscapes with higher fragmentation, thus having lower species richness in both time periods. Alternatively, forest generalists elicited a completely different pattern, showing a curvilinear association to forest fragmentation for most parameters. Thus, greater community dynamism for forest generalists was shown in landscapes with intermediate levels of fragmentation. Our study supports general theory regarding the expected negative effects of habitat loss and fragmentation on the temporal dynamics of biotic communities, particularly for forest specialists, providing strong evidence from understudied tropical bird communities.
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\n• Hydrologic climate-response data (initiating or expanding long-term hydrologic climate-response data collection networks to detect and monitor climate-related changes in hydrology)
• Relations between historical climatic and hydrologic variation (investigating historic relations between long-term climatic variation and hydrologic variation and connecting these relations to future conditions as forecasted by the Interagency Panel on Climate Change (Nakićenović and others, 2000)
• Hydrologic change on natural and human (incorporating climate change scenarios into assessments of how flows in streams or water levels in aquifers may change)
• Relations between climatic and hydrologic variation (characterizing impacts of climate change on floods and droughts, the long-term availability of water supplies for societal and natural uses in response to climate changes)
• Developing tools to forecast ecosystem change and water resources management (developing regionally consistent tools for forecasting ecosystem change and resource management)
This fact sheet presents recent climate change investigations of the USGS in New England using selected recent publications. These publications highlight the broad spectrum of expertise and commitment to understanding the relations of climate change and water resources in New England.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163011","usgsCitation":"U.S. Geological Survey, 2016, Climate change science activities of the U.S. Geological Survey in New England: U.S. Geological Survey Fact Sheet 2016–3011, 4 p., https://dx.doi.org/10.3133/fs20163011.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-070470","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":319052,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/fs20163012","text":"Fact Sheet 2016-3012","size":"1 MB","description":"FS2016-3011"},{"id":319051,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/fs20163010","text":"Fact Sheet 2016-3010","size":"871 KB","description":"FS2016-3011"},{"id":319050,"rank":4,"type":{"id":7,"text":"Companion 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
The U.S. Geological Survey (USGS) collaborates with a variety of Federal, State, local, and tribal partners on scientific projects to provide reliable and impartial water-quality data and interpretation to resource managers, planners, stakeholders, and the general public. The themes related to surface water quality include the following:
\n• Water quality monitoring networks
• Effects of best management practices and low impact development on water quality
• Load estimation techniques and total maximum daily load assistance
• Mercury studies
• Toxics and emerging contaminants
• Eutrophication and nuisance algal blooms
Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
Aquifers in New England provide water for human needs and natural ecosystems. In some areas, however, aquifers have been degraded by contaminants from geologic and human sources. In recent decades, the U.S. Geological Survey has been a leader in describing contaminant occurrence in the bedrock and surficial aquifers of New England. In cooperation with Federal, State, and local agencies, the U.S. Geological Survey has also studied the vulnerability of groundwater to contaminants, the factors affecting the geographic distribution of contaminants, and the geochemical processes controlling contaminant transport and fate. This fact sheet describes some of the major science needs in the region related to groundwater contaminants and highlights recent U.S. Geological Survey studies that provide a foundation for future investigations.
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U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
The U.S. Geological Survey (USGS) has many ongoing and recent water-related natural hazard activities in New England that can be used to help mitigate the effects of natural hazards in cooperation with other agencies. The themes related to potential hazards and the tools and science to better understand and address them include the following:
\nErosion and landslides
• Fluvial erosion (sediment transport, bridge scour, and bankfull channel geometry characterization)
• Current and historic landslide mapping
Flood documentation and assessment
• Flood high-water marks
• Flood modeling and frequency analysis
• Flood inundation mapping
• Peak-flow regression equations
Drought documentation and assessment
• Drought frequency analysis
• Low-flow frequency and flow duration statistics
• Water use and availability during drought
Hydrologic monitoring
• Streamflow monitoring network
• Groundwater monitoring network
• Tidal monitoring network
• Snow surveys and ice jam monitoring
Tools for natural hazard assessment and mitigation
• Light detection and ranging (lidar) remote sensing technology
• StreamStats Web-based tool for streamflow statistics
• Flood inundation mapper
Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
The U.S. Geological Survey (USGS) has a long history of working with the Federal Highway Administration (FHWA) and State transportation agencies to provide data and information to address various issues related to water resources and the Nation’s transportation infrastructure. These issues include the following:
\n• Streamgaging data networks
• Flow frequencies and flow statistics
• Water-quality investigations
• Bridge scour and sediment transport
• Hydrologic and hydraulic flood modeling
In New England, the USGS is conducting investigations to improve flood flow estimation techniques, to define channel characteristics at bankfull discharge, and to document storm tide as a result of major coastal storms. Current locally focused investigations include examination of flow frequency in rural, urban, and small watersheds; documentation of extreme inland floods along with flood-frequency updates; examination of the effects of roadway blasting on groundwater quality; and determinations of the effects of road salting on the quality of runoff and receiving waters.
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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
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Using water column temperature records collected since 1968, we analyzed the impacts of climate change on thermal properties, stability intensity, length of stratification, and deep mixing dynamics of Lake Tahoe using a modified stability index (SI). This new SI is easier to produce and is a more informative measure of deep lake stability than commonly used stability indices. The annual average SI increased at 16.62 kg/m2/decade although the summer (May–October) average SI increased at a higher rate (25.42 kg/m2/decade) during the period 1968–2014. This resulted in the lengthening of the stratification season by approximately 24 d. We simulated the lake thermal structure over a future 100 yr period using a lake hydrodynamic model driven by statistically downscaled outputs of the Geophysical Fluid Dynamics Laboratory Model (GFDL) for two different green house gas emission scenarios (the A2 in which greenhouse-gas emissions increase rapidly throughout the 21st Century, and the B1 in which emissions slow and then level off by the late 21st Century). The results suggest a continuation and intensification of the already observed trends. The length of stratification duration and the annual average lake stability are projected to increase by 38 d and 12 d and 30.25 kg/m2/decade and 8.66 kg/m2/decade, respectively for GFDLA2 and GFDLB1, respectively during 2014–2098. The consequences of this change bear the hallmarks of climate change induced lake warming and possible exacerbation of existing water quality, quantity and ecosystem changes. The developed methodology could be extended and applied to other lakes as a tool to predict changes in stratification and mixing dynamics.
","language":"English","publisher":"Wiley & Sons Ltd.","doi":"10.1002/lno.10228","usgsCitation":"Sahoo, G.B., Forrest, A.L., Schladow, S., Reuter, J.E., Coats, R., and Dettinger, M.D., 2016, Climate change impacts on lake thermal dynamics and ecosystem vulnerabilities: Limnology and Oceanography, v. 61, p. 496-507, https://doi.org/10.1002/lno.10228.","productDescription":"11 p.","startPage":"496","endPage":"507","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057124","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471128,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10228","text":"Publisher Index Page"},{"id":325694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Lake 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E","contributorId":173178,"corporation":false,"usgs":false,"family":"Reuter","given":"J.","email":"","middleInitial":"E","affiliations":[{"id":27174,"text":"UC Davis, Tahoe Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":643558,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coats, R.","contributorId":9540,"corporation":false,"usgs":true,"family":"Coats","given":"R.","email":"","affiliations":[],"preferred":false,"id":643559,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":643554,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160548,"text":"sir20105090AA - 2016 - Geology and undiscovered resource assessment of the potash-bearing Central Asia Salt Basin, Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan: Chapter AA in Global mineral resource assessment","interactions":[{"subject":{"id":70160548,"text":"sir20105090AA - 2016 - Geology and undiscovered resource assessment of the potash-bearing Central Asia Salt Basin, Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan: Chapter AA in Global mineral resource assessment","indexId":"sir20105090AA","publicationYear":"2016","noYear":false,"chapter":"AA","title":"Geology and undiscovered resource assessment of the potash-bearing Central Asia Salt Basin, Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan: Chapter AA in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2016-03-23T15:14:43","indexId":"sir20105090AA","displayToPublicDate":"2016-03-23T09:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"AA","title":"Geology and undiscovered resource assessment of the potash-bearing Central Asia Salt Basin, Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan: Chapter AA in Global mineral resource assessment","docAbstract":"Undiscovered potash resources in the Central Asia Salt Basin (CASB) of Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan were assessed as part of a global mineral resource assessment led by the U.S. Geological Survey. The term “potash” refers to potassium-bearing, water-soluble salts derived from evaporite basins, where seawater dried up and precipitated various salt compounds; the word for the element “potassium” is derived from potash. Potash is produced worldwide at amounts exceeding 30 million metric tons per year, mostly for use in fertilizers. The term “potash” is used by industry to refer to potassium chloride, as well as potassium in sulfate, nitrate, and oxide forms. For the purposes of this assessment, the term “potash” refers to potassium ores and minerals and potash ore grades. Resource and production values are usually expressed by industry in terms of K2O (potassium oxide) or muriate of potash (KCl, potassium chloride).
\nThe CASB hosts significant discovered potash resources and originated in an inland sea during Late Jurassic time. Seawater flowed into the CASB, mostly from its extreme northwestern margin near the modern Caspian Sea, during several evaporation episodes that deposited at least five different packages of evaporites, with virtually all potash in the second and fourth packages. In this study, the CASB was subdivided into three tracts (permissive areas) for evaluation: the Amu Darya tract in the west, the Gissar tract in the center, and the Afghan-Tajik tract in the east. The Gissar and Amu Darya tracts were quantitatively assessed, whereas the Afghan‑Tajik tract was only qualitatively assessed because of the commonly extreme depth (as deep as 7 km) of the Jurassic salt, extensive deformation, and a lack of known potash deposits.
\nTwo approaches were used to estimate amounts of undiscovered potash in the CASB. Stratabound evaporite deposits in the Amu Darya tract were evaluated using an Adaptive Geometric Estimation (AGE) approach, which estimates in-place potash volumes and tonnages. The Gissar tract was evaluated by using the AGE approach for stratabound deposits and the three-part form of assessment of Singer and Menzie (2005) for discrete halokinetic deposits. In the three-part form of assessment, numbers of undiscovered deposits were estimated and combined with grade and tonnage models to probabilistically forecast the amount of undiscovered potash. The Amu Darya tract is estimated to contain 38 billion metric tons of undiscovered potash as K2O by using the AGE approach for stratabound deposits. The hybrid stratabound-halokinetic Gissar tract is estimated to contain between 1 and 16 billion metric tons of undiscovered potash as K2O.
\nChapter 1 of this report provides an overview of the history of the CASB and summarizes evaporite potash deposition, halokinesis, and dissolution processes that have affected the current distribution of potash-bearing salt in the CASB. Chapter 2 describes the Gissar tract, an uplifted region that contains a mix of stratabound and halokinetic potash deposits and all of the discovered and exploited potash deposits of the CASB. Chapter 3 describes the Amu Darya tract, where evaporite deposits remain flat-lying and undeformed since their original deposition. Chapter 4 describes the highly deformed and compressed Afghan-Tajik tract and what is known of the deeply-buried Jurassic salt. Chapter 5 describes the spatial databases included with this report, which contain a collection of CASB potash information. Appendixes A and B summarize descriptive models for stratabound and halokinetic potash-bearing salt deposits, respectively. Appendix C summarizes the AGE method used to evaluate the Gissar and Amu Darya tracts. Appendixes D and E contain grade and thickness data for the Gissar and Amu Darya tracts. Appendix F provides the SYSTAT script used to estimate undiscovered K2 O in a CASB tract. Appendix G provides a potash glossary, and appendix H provides biographies of assessment participants.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090AA","usgsCitation":"Wynn, Jeff, Orris, G.J., Dunlap, Pamela, Cocker, M.D., and Bliss, J.D., 2016, Geology and undiscovered resource assessment of the potash-bearing Central Asia Salt Basin, Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan: U.S. Geological Survey Scientific Investigations Report SIR 2010–5090–AA, 106 p., and spatial data, https://dx.doi.org/10.3133/sir20105090AA.","productDescription":"Report: xi, 106 p.; GIS Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053583","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":318376,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/aa/sir20105090aa.pdf","text":"Report","size":"7.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090-AA report PDF"},{"id":318377,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/aa/sir20105090aa_gis.zip","text":"GIS Data","size":"4.1 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2010-5090-AA GIS Data"},{"id":318375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5090/aa/coverthb.jpg"}],"country":"Afghanistan, Tajikistan, Turkmenistan, Uzbekistan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 62.38037109374999,\n 40.094882122321174\n ],\n [\n 60.3369140625,\n 40.01078714046552\n ],\n [\n 61.14990234374999,\n 36.89719446989036\n ],\n [\n 70.07080078125,\n 35.94243575255426\n ],\n [\n 70.24658203125,\n 37.94419750075404\n ],\n [\n 70.9716796875,\n 38.94232097947902\n ],\n [\n 62.38037109374999,\n 40.094882122321174\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Mineral Resources Program
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This report describes two software tools that, when used as front ends for the three-dimensional backward Monte Carlo atmospheric-radiative-transfer model (RTM) McArtim, facilitate the generation of lookup tables of volcanic-plume optical-transmittance characteristics in the ultraviolet/visible-spectral region. In particular, the differential optical depth and derivatives thereof (that is, weighting functions), with regard to a change in SO2 column density or aerosol optical thickness, can be simulated for a specific measurement geometry and a representative range of plume conditions. These tables are required for the retrieval of SO2 column density in volcanic plumes, using the simulated radiative-transfer/differential optical-absorption spectroscopic (SRT-DOAS) approach outlined by Kern and others (2012). This report, together with the software tools published online, is intended to make this sophisticated SRT-DOAS technique available to volcanologists and gas geochemists in an operational environment, without the need for an indepth treatment of the underlying principles or the low-level interface of the RTM McArtim.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161045","usgsCitation":"Kern, Christoph, 2016, An interface for simulating radiative transfer in and around volcanic plumes with the Monte Carlo radiative transfer model McArtim: U.S. Geological Survey Open-File Report 2016–1045, 18 p., https://dx.doi.org/10.3133/ofr20161045.","productDescription":"iv, 18 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046306","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":319193,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1045/coverthb.jpg"},{"id":319194,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1045/ofr20161045.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1045"}],"contact":"Contact CVO
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Since 2012, a multi-agency initiative to restore these native forage species has been under way. Evaluating the restoration success of Cisco Coregonus artedi and Bloater C. hoyi in Lake Ontario waters requires methods to identify stocked fish. However, juvenile Cisco and Bloater are fragile; thus, mass marking techniques that reduce the handling of individual fish are required and have not previously been evaluated. In 2014–2015 we evaluated the usefulness of calcein (SE-MARK) as a marker on bony structures, including the otolith. Juvenile Bloater and Cisco (14, 100, 128 d old) were immersed in a calcein bath at 5,000 mg/L of water for 4 min to apply the chemical marker. Observations of the marking retention were evaluated 8 d following the treatment. All fish immersed in calcein had strong brilliant marks (rating scale 3) on all bony structures including scales, fin rays, jaw bones, and vertebrate. The otolith was the only hard structure that did not show a brilliant marking due to the opaque nature of the structure. Our results suggest that calcein produces a strong discernable mark on hard bony structures of Cisco and Bloater; however, long-term retention needs further study.
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Thomas","contributorId":168583,"corporation":false,"usgs":false,"family":"Kehler","given":"Thomas","email":"","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":642951,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ringler, Neil H.","contributorId":28936,"corporation":false,"usgs":true,"family":"Ringler","given":"Neil","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":642952,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70175025,"text":"70175025 - 2016 - Integrating subsistence practice and species distribution modeling: assessing invasive elodea’s potential impact on Native Alaskan subsistence of Chinook salmon and whitefish","interactions":[],"lastModifiedDate":"2016-07-27T11:31:40","indexId":"70175025","displayToPublicDate":"2016-03-22T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Integrating subsistence practice and species distribution modeling: assessing invasive elodea’s potential impact on Native Alaskan subsistence of Chinook salmon and whitefish","docAbstract":"Alaska has one of the most rapidly changing climates on earth and is experiencing an accelerated rate of human disturbance, including resource extraction and transportation infrastructure development. Combined, these factors increase the state’s vulnerability to biological invasion, which can have acute negative impacts on ecological integrity and subsistence practices. Of growing concern is the spread of Alaska’s first documented freshwater aquatic invasive plant Elodea spp. (elodea). In this study, we modeled the suitable habitat of elodea using global and state-specific species occurrence records and environmental variables, in concert with an ensemble of model algorithms. Furthermore, we sought to incorporate local subsistence concerns by using Native Alaskan knowledge and available statewide subsistence harvest data to assess the potential threat posed by elodea to Chinook salmon (Oncorhynchus tshawytscha) and whitefish (Coregonus nelsonii) subsistence. State models were applied to future climate (2040–2059) using five general circulation models best suited for Alaska. Model evaluations indicated that our results had moderate to strong predictability, with area under the receiver-operating characteristic curve values above 0.80 and classification accuracies ranging from 66 to 89 %. State models provided a more robust assessment of elodea habitat suitability. These ensembles revealed different levels of management concern statewide, based on the interaction of fish subsistence patterns, known spawning and rearing sites, and elodea habitat suitability, thus highlighting regions with additional need for targeted monitoring. Our results suggest that this approach can hold great utility for invasion risk assessments and better facilitate the inclusion of local stakeholder concerns in conservation planning and management.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-016-0692-4","usgsCitation":"Luizza, M., Evangelista, P., Jarnevich, C.S., West, A., and Stewart, H., 2016, Integrating subsistence practice and species distribution modeling: assessing invasive elodea’s potential impact on Native Alaskan subsistence of Chinook salmon and whitefish: Environmental Management, v. 58, no. 1, p. 144-163, https://doi.org/10.1007/s00267-016-0692-4.","productDescription":"19 p.","startPage":"144","endPage":"163","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067317","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":325696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":643639,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"West, Amanda M.","contributorId":139058,"corporation":false,"usgs":false,"family":"West","given":"Amanda M.","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":643642,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stewart, Heather","contributorId":173199,"corporation":false,"usgs":false,"family":"Stewart","given":"Heather","affiliations":[{"id":27188,"text":"Alaska Department of Natural Resources Division of Agriculture","active":true,"usgs":false}],"preferred":false,"id":643643,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169145,"text":"70169145 - 2016 - Enhancing and restoring habitat for the desert tortoise","interactions":[],"lastModifiedDate":"2016-12-16T11:17:02","indexId":"70169145","displayToPublicDate":"2016-03-22T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Enhancing and restoring habitat for the desert tortoise","docAbstract":"Habitat has changed unfavorably during the past 150 y for the desert tortoise Gopherus agassizii, a federally threatened species with declining populations in the Mojave Desert and western Sonoran Desert. To support recovery efforts, we synthesized published information on relationships of desert tortoises with three habitat features (cover sites, forage, and soil) and candidate management practices for improving these features for tortoises. In addition to their role in soil health and facilitating recruitment of annual forage plants, shrubs are used by desert tortoises for cover and as sites for burrows. Outplanting greenhouse-grown seedlings, protected from herbivory, has successfully restored (>50% survival) a variety of shrubs on disturbed desert soils. Additionally, salvaging and reapplying topsoil using effective techniques is among the more ecologically beneficial ways to initiate plant recovery after severe disturbance. Through differences in biochemical composition and digestibility, some plant species provide better-quality forage than others. Desert tortoises selectively forage on particular annual and herbaceous perennial species (e.g., legumes), and forage selection shifts during the year as different plants grow or mature. Nonnative grasses provide low-quality forage and contribute fuel to spreading wildfires, which damage or kill shrubs that tortoises use for cover. Maintaining a diverse “menu” of native annual forbs and decreasing nonnative grasses are priorities for restoring most desert tortoise habitats. Reducing herbivory by nonnative animals, carefully timing herbicide applications, and strategically augmenting annual forage plants via seeding show promise for improving tortoise forage quality. Roads, another disturbance, negatively affect habitat in numerous ways (e.g., compacting soil, altering hydrology). Techniques such as recontouring road berms to reestablish drainage patterns, vertical mulching (“planting” dead plant material), and creating barriers to prevent trespasses can assist natural recovery on decommissioned backcountry roads. Most habitat enhancement efforts to date have focused on only one factor at a time (e.g., providing fencing) and have not included proactive restoration activities (e.g., planting native species on disturbed soils). A research and management priority in recovering desert tortoise habitats is implementing an integrated set of restorative habitat enhancements (e.g., reducing nonnative plants, improving forage quality, augmenting native perennial plants, and ameliorating altered hydrology) and monitoring short- and long-term indicators of habitat condition and the responses of desert tortoises to habitat restoration.
","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington, D.C.","doi":"10.3996/052015-JFWM-046","usgsCitation":"Abella, S.R., and Berry, K.H., 2016, Enhancing and restoring habitat for the desert tortoise: Journal of Fish and Wildlife Management, v. 7, no. 1, p. 255-279, https://doi.org/10.3996/052015-JFWM-046.","productDescription":"25 p.","startPage":"255","endPage":"279","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066485","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488430,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/052015-jfwm-046","text":"Publisher Index Page"},{"id":319189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.027099609375,\n 37.32648861334206\n ],\n [\n -113.75244140624999,\n 37.42252593456307\n ],\n [\n -113.521728515625,\n 37.33522435930641\n ],\n [\n -113.48876953125,\n 37.055177106660814\n ],\n [\n -113.5986328125,\n 36.4566360115962\n ],\n [\n -113.73046875,\n 36.1822249804225\n ],\n [\n -113.79638671875,\n 35.951329861522666\n ],\n [\n -113.895263671875,\n 35.60371874069731\n ],\n [\n -113.675537109375,\n 35.23664622093195\n ],\n [\n -113.51074218749999,\n 35.074964853989556\n ],\n [\n -113.44482421875,\n 34.97600151317591\n ],\n [\n -113.18115234375,\n 34.66032236481892\n ],\n [\n -113.203125,\n 34.379712580462204\n ],\n [\n -113.466796875,\n 34.19817309627726\n ],\n [\n -113.88427734374999,\n 34.125447565116126\n ],\n [\n -114.36767578124999,\n 34.03445260967645\n ],\n [\n -115.13671875,\n 34.17090836352573\n ],\n [\n -115.15869140624999,\n 33.8430453147447\n ],\n [\n -114.664306640625,\n 33.486435450999885\n ],\n [\n -114.81811523437501,\n 33.14675022877648\n ],\n [\n -115.04882812499999,\n 32.94414888814148\n ],\n [\n -115.3564453125,\n 33.119150226768866\n ],\n [\n -115.521240234375,\n 33.330528249028085\n ],\n [\n -116.114501953125,\n 33.779147331286474\n ],\n [\n -116.38916015624999,\n 33.90689555128866\n ],\n [\n -117.22412109375,\n 34.19817309627726\n ],\n [\n -117.630615234375,\n 34.15272698011818\n ],\n [\n -118.02612304687499,\n 34.14363482031264\n ],\n [\n -118.38867187500001,\n 34.288991865037524\n ],\n [\n -118.65234374999999,\n 34.52466147177172\n ],\n [\n -118.80615234374999,\n 34.75966612466248\n ],\n [\n -118.223876953125,\n 35.16482750605027\n ],\n [\n -118.487548828125,\n 35.39800594715108\n ],\n [\n -118.443603515625,\n 35.6126508187567\n ],\n [\n -118.14697265625,\n 35.7286770448517\n ],\n [\n -117.98217773437499,\n 35.639441068973916\n ],\n [\n -117.850341796875,\n 35.64836915737426\n ],\n [\n -117.98217773437499,\n 36.05798104702501\n ],\n [\n -118.048095703125,\n 36.38591277287651\n ],\n [\n -118.21289062499999,\n 36.5978891330702\n ],\n [\n -118.333740234375,\n 37.02886944696474\n ],\n [\n -118.35571289062499,\n 37.25656608611523\n ],\n [\n -118.0810546875,\n 37.23907530202184\n ],\n [\n -117.938232421875,\n 37.448696585910376\n ],\n [\n -117.740478515625,\n 37.56199695314352\n ],\n [\n -117.57568359374999,\n 37.49229399862877\n ],\n [\n -117.2900390625,\n 37.26530995561875\n ],\n [\n -116.79565429687499,\n 37.274052809979054\n ],\n [\n -116.5869140625,\n 37.25656608611523\n ],\n [\n -116.49902343749999,\n 37.204081555898526\n ],\n [\n -116.15844726562501,\n 37.16907157713011\n ],\n [\n -115.927734375,\n 37.142803443716836\n ],\n [\n -115.51025390625,\n 37.38761749978395\n ],\n [\n -114.993896484375,\n 37.24782120155428\n ],\n [\n -114.54345703125,\n 37.25656608611523\n ],\n [\n -114.3017578125,\n 37.212831514455964\n ],\n [\n -114.027099609375,\n 37.32648861334206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-01","publicationStatus":"PW","scienceBaseUri":"56f25e98e4b0f59b85de6ff1","contributors":{"authors":[{"text":"Abella, Scott R.","contributorId":103940,"corporation":false,"usgs":true,"family":"Abella","given":"Scott","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":623207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":623206,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169017,"text":"fs20163007 - 2016 - Landscape ecology of the Upper Mississippi River System: Lessons learned, challenges and opportunities","interactions":[],"lastModifiedDate":"2016-06-24T09:07:49","indexId":"fs20163007","displayToPublicDate":"2016-03-22T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3007","title":"Landscape ecology of the Upper Mississippi River System: Lessons learned, challenges and opportunities","docAbstract":"The Upper Mississippi River System (UMRS) is a mosaic of river channels, backwater lakes, floodplain forests, and emergent marshes. This complex mosaic supports diverse aquatic and terrestrial plant communities, over 150 fish species; 40 freshwater mussel species; 50 amphibian and reptile species; and over 360 bird species, many of which use the UMRS as a critical migratory route. The river and floodplain are also hotspots for biogeochemical activity as the river-floodplain collects and processes nutrients derived from the UMR basin. These features qualify the UMRS as a Ramsar wetland of international significance.
Two centuries of land-use change, including construction for navigation and conversion of large areas to agriculture, has altered the broad-scale structure of the river and changed local environmental conditions in many areas. Such changes have affected rates of nutrient processing and transport, as well as the abundance of various fish, mussel, plant, and bird species. However, the magnitude and spatial scale of these effects are not well quantified, especially in regards to the best methods and locations for restoring various aspects of the river ecosystem.
The U.S. Congress declared the navigable portions of the Upper Mississippi River System (UMRS) a “nationally significant ecosystem and nationally significant commercial navigation system” in the Water Resources Development Act of 1986 (Public Law 99-662) and launched the Upper Mississippi River Restoration (UMRR) Program, the first comprehensive program for ecosystem restoration, monitoring, and research on a large river system. This fact sheet focuses on landscape ecological studies conducted by the U.S. Geological Survey to support decision making by the UMRR with respect to ecosystem restoration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163007","collaboration":"A Product of the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration (UMRR) Program","usgsCitation":"De Jager, N., 2016, Landscape Ecology of the Upper Mississippi River System: Lessons learned, challenges and opportunities. U.S. Geological Survey Fact Sheet 2016–3007, 4 p., https://dx.doi.org/10.3133/fs20163007.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041434","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":318908,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3007/coverthb.jpg"},{"id":318909,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3007/fs20163007.pdf","text":"Report","size":"6.58 MB","description":"FS 2016-3007"}],"country":"United States","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.62646484375,\n 36.4566360115962\n ],\n [\n -91.47216796875,\n 38.41055825094609\n ],\n [\n -93.93310546875,\n 39.7240885773337\n ],\n [\n -95.44921875,\n 40.48038142908172\n ],\n [\n -96.328125,\n 42.391008609205045\n ],\n [\n -96.50390625,\n 44.26093725039923\n ],\n [\n -96.52587890625,\n 45.19752230305685\n ],\n [\n -95.108642578125,\n 46.21785176740299\n ],\n [\n -94.09790039062499,\n 46.39998810407942\n ],\n [\n -92.735595703125,\n 46.51351558059737\n ],\n [\n -92.17529296875,\n 46.44542749723387\n ],\n [\n -90.3076171875,\n 44.94924926661153\n ],\n [\n -89.197998046875,\n 43.40504748787035\n ],\n [\n -88.22021484375,\n 42.706659563510385\n ],\n [\n -87.791748046875,\n 42.439674178149424\n ],\n [\n -87.60498046875,\n 40.830436877649255\n ],\n [\n -88.187255859375,\n 38.993572058209466\n ],\n [\n -88.53881835937499,\n 37.52715361723378\n ],\n [\n -89.527587890625,\n 36.5184659896759\n ],\n [\n -89.62646484375,\n 36.4566360115962\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
Phone: (608) 783-6451
http://www.umesc.usgs.gov/ltrmp.html
Bioremediation strategies, including bioaugmentation with chlorinated ethene-degrading enrichment cultures, have been successfully applied in the cleanup of subsurface environments contaminated with tetrachloroethene (PCE) and/or trichloroethene (TCE). However, these compounds are frequently found in the environment as components of mixtures that may also contain chlorinated ethanes and methanes. Under these conditions, the implementation of bioremediation may be complicated by inhibition effects, particularly when multiple dehalorespirers are present. We investigated the ability of the 1,1,2,2-tetrachloroethane (TeCA)-dechlorinating culture WBC-2 to biotransform TeCA alone, or a mixture of TeCA plus PCE and carbon tetrachloride (CT), in microcosms. The microcosms contained electron donors provided to biostimulate the added culture and sediment collected from a wetland where numerous “hotspots” of contamination with chlorinated solvent mixtures exist. The dominant TeCA biodegradation mechanism mediated by the WBC-2 culture in the microcosms was different in the presence of these wetland sediments than in the sediment-free enrichment culture or in previous WBC-2 bioaugmented microcosms and column tests conducted with wetland sediment collected at nearby sites. The co-contaminants and their daughter products also inhibited TeCA biodegradation by WBC-2. These results highlight the need to conduct biodegradability assays at new sites, particularly when multiple contaminants and dehalorespiring populations are present.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2015.12.033","collaboration":"U.S. Army, Aberdeen Proving Ground (Maryland)","usgsCitation":"Lorah, M.M., Schiffmacher, E.N., Becker, J.G., and Voytek, M.A., 2016, The effects of co-contaminants and native wetland sediments on the activity and dominant transformation mechanisms of a 1,1,2,2-tetrachloroethane (TeCA)-degrading enrichment culture: Chemosphere, v. 147, p. 239-247, https://doi.org/10.1016/j.chemosphere.2015.12.033.","productDescription":"9 p.","startPage":"239","endPage":"247","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069806","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":488787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemosphere.2015.12.033","text":"Publisher Index Page"},{"id":324363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576e59b6e4b07657d1a43caf","chorus":{"doi":"10.1016/j.chemosphere.2015.12.033","url":"http://dx.doi.org/10.1016/j.chemosphere.2015.12.033","publisher":"Elsevier BV","authors":"Schiffmacher Emily N., Becker Jennifer G., Lorah Michelle M., Voytek Mary A.","journalName":"Chemosphere","publicationDate":"3/2016","publiclyAccessibleDate":"1/13/2017"},"contributors":{"authors":[{"text":"Lorah, Michelle M. 0000-0002-9236-587X mmlorah@usgs.gov","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":1437,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","email":"mmlorah@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schiffmacher, Emily N.","contributorId":172429,"corporation":false,"usgs":false,"family":"Schiffmacher","given":"Emily","email":"","middleInitial":"N.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":640694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Becker, Jennifer G.","contributorId":172430,"corporation":false,"usgs":false,"family":"Becker","given":"Jennifer","email":"","middleInitial":"G.","affiliations":[{"id":27038,"text":"Michigan Technological University and University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":640696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voytek, Mary A.","contributorId":91943,"corporation":false,"usgs":true,"family":"Voytek","given":"Mary","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":640695,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169158,"text":"70169158 - 2016 - Spatial genetic structure of Long-tailed Ducks (Clangula hyemalis) among Alaskan, Canadian, and Russian breeding populations","interactions":[],"lastModifiedDate":"2021-08-27T16:20:37.812591","indexId":"70169158","displayToPublicDate":"2016-03-22T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":894,"text":"Arctic","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatial genetic structure of Long-tailed Ducks (Clangula hyemalis) among Alaskan, Canadian, and Russian breeding populations","title":"Spatial genetic structure of Long-tailed Ducks (Clangula hyemalis) among Alaskan, Canadian, and Russian breeding populations","docAbstract":"Arctic ecosystems are changing at an unprecedented rate. How Arctic species are able to respond to such environmental change is partially dependent on the connections between local and broadly distributed populations. For species like the Long-tailed Duck (Clangula hyemalis), we have limited telemetry and band-recovery information from which to infer population structure and migratory connectivity; however, genetic analyses can offer additional insights. To examine population structure in the Long-tailed Duck, we characterized variation at mtDNA control region and microsatellite loci among four breeding areas in Alaska, Canada, and Russia. We observed significant differences in the variance of mtDNA haplotype frequencies between the Yukon-Kuskokwim Delta (YKD) and the three Arctic locations (Arctic Coastal Plain in Alaska, eastern Siberia, and central Canadian Arctic). However, like most sea duck genetic assessments, our study found no evidence of population structure based on autosomal microsatellite loci. Long-tailed Ducks use multiple wintering areas where pair formation occurs with some populations using both the Pacific and Atlantic Oceans. This situation provides a greater opportunity for admixture across breeding locales, which would likely homogenize the nuclear genome even in the presence of female philopatry. The observed mtDNA differentiation was largely due to the presence of two divergent clades: (A) a clade showing signs of admixture among all breeding locales and (B) a clade primarily composed of YKD samples. We hypothesize that the pattern of mtDNA differentiation reflects some degree of philopatry to the YKD and isolation of two refugial populations with subsequent expansion and admixture. We recommend additional genetic assessments throughout the circumpolar range of Long-tailed Ducks to further quantify aspects of genetic diversity and migratory connectivity in this species.
","language":"English","publisher":"Arctic Institute of North America","publisherLocation":"Montreal","doi":"10.14430/arctic4548","usgsCitation":"Wilson, R.E., Gust, J., Petersen, M.R., and Talbot, S.L., 2016, Spatial genetic structure of Long-tailed Ducks (Clangula hyemalis) among Alaskan, Canadian, and Russian breeding populations: Arctic, v. 69, no. 1, p. 65-78, https://doi.org/10.14430/arctic4548.","productDescription":"Article: 14 p.; Data Release","startPage":"65","endPage":"78","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058269","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438629,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HX19RJ","text":"USGS data release","linkHelpText":"Long-tailed Duck (Clangula hyemalis) Microsatellite DNA Data, Alaska, Canada, Russia, 1994-2002"},{"id":319212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335474,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7HX19RJ"}],"country":"Canada, Russia, United States","otherGeospatial":"Arctic Coastal Plain, central Canadian Arctic, eastern Siberia, Yukon-Kuskokwim Delta","volume":"69","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-01","publicationStatus":"PW","scienceBaseUri":"56f3be4fe4b0f59b85e02f08","contributors":{"authors":[{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":623264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gust, J. R.","contributorId":167730,"corporation":false,"usgs":false,"family":"Gust","given":"J. R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":623267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petersen, Margaret R. 0000-0001-6082-3189 mrpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-6082-3189","contributorId":167729,"corporation":false,"usgs":true,"family":"Petersen","given":"Margaret","email":"mrpetersen@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":623265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":623266,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169142,"text":"ds983 - 2016 - Water temperature profiles for reaches of the Raging River during summer baseflow, King County, western Washington, July 2015","interactions":[],"lastModifiedDate":"2016-03-23T08:58:18","indexId":"ds983","displayToPublicDate":"2016-03-22T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"983","title":"Water temperature profiles for reaches of the Raging River during summer baseflow, King County, western Washington, July 2015","docAbstract":"Re-introducing wood into rivers where it was historically removed is one approach to improving habitat conditions in rivers of the Pacific Northwest. The Raging River drainage basin, which flows into the Snoqualmie River at Fall City, western Washington, was largely logged during the 20th century and wood was removed from its channel. To improve habitat conditions for several species of anadromous salmonids that spawn and rear in the Raging River, King County Department of Transportation placed untethered log jams in a 250-meter reach where wood was historically removed. The U.S. Geological Survey measured longitudinal profiles of near-streambed temperature during summer baseflow along 1,026 meters of channel upstream, downstream, and within the area of wood placements. These measurements were part of an effort by King County to monitor the geomorphic and biological responses to these wood placements. Near-streambed temperatures averaged over about 1-meter intervals were measured with a fiber‑optic distributed temperature sensor every 30 minutes for 7 days between July 7 and 13, 2015. Vertical temperature profiles were measured coincident with the longitudinal temperature profile at four locations at 0 centimeters (cm) (at the streambed), and 35 and 70 cm beneath the streambed to document thermal dynamics of the hyporheic zone and surface water in the study reach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds983","collaboration":"Prepared in cooperation with King County Department of Natural Resource and Parks","usgsCitation":"Gendaszek, A.S., and Opatz, C.C., 2016, Water temperature profiles for reaches of the Raging River during summer baseflow, King County, western Washington, July 2015: U.S. Geological Survey Data Series 983, 8 p.,\nhttps://dx.doi.org/10.3133/ds983.","productDescription":"Report: iii, 8 p.; Tables 1-3","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070544","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":319142,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0983/coverthb.jpg"},{"id":319143,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0983/ds983.pdf","text":"Report","size":"4.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 983"},{"id":319144,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0983/ds983_table01.xlsx","text":"Table 1","size":"1.2 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 983 Table 1"},{"id":319145,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0983/ds983_table02.xlsx","text":"Table 2","size":"56 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 983 Table 2"},{"id":319146,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0983/ds983_table03.xlsx","text":"Table 3","size":"70 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 983 Table 3"}],"country":"United States","state":"Washington","county":"King County","otherGeospatial":"Raging River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.8639,\n 47.45\n ],\n [\n -121.8639,\n 47.4569\n ],\n [\n -121.8583,\n 47.4569\n ],\n [\n -121.8583,\n 47.45\n ],\n [\n -121.8639,\n 47.45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.
","language":"English","publisher":"Kluwer Academic Publishers","doi":"10.1007/s10661-016-5228-0","usgsCitation":"Cooke, S., Martins, E.G., Struthers, D.P., Gutowsky, L.F., Powers, M.H., Doka, S.E., Dettmers, J.M., Crook, D.A., Lucas, M.C., Holbrook, C., and Krueger, C., 2016, A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations: Environmental Monitoring and Assessment, v. 188, no. 239, 18 p., https://doi.org/10.1007/s10661-016-5228-0.","productDescription":"18 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073964","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471130,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/file/1387959/1/Accepted%20Journal%20Article","text":"External Repository"},{"id":326047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"188","issue":"239","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-22","publicationStatus":"PW","scienceBaseUri":"57a315b9e4b006cb45558a20","contributors":{"authors":[{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":644582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martins, Eduardo G","contributorId":173417,"corporation":false,"usgs":false,"family":"Martins","given":"Eduardo","email":"","middleInitial":"G","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":644583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Struthers, Daniel P","contributorId":173418,"corporation":false,"usgs":false,"family":"Struthers","given":"Daniel","email":"","middleInitial":"P","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":644584,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gutowsky, Lee F G","contributorId":149696,"corporation":false,"usgs":false,"family":"Gutowsky","given":"Lee","email":"","middleInitial":"F G","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":644585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":644586,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doka, Susan E.","contributorId":173419,"corporation":false,"usgs":false,"family":"Doka","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":644587,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dettmers, John M.","contributorId":27395,"corporation":false,"usgs":true,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":644588,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crook, David A","contributorId":173420,"corporation":false,"usgs":false,"family":"Crook","given":"David","email":"","middleInitial":"A","affiliations":[{"id":12877,"text":"Charles Darwin University","active":true,"usgs":false}],"preferred":false,"id":644589,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lucas, Martyn C.","contributorId":18725,"corporation":false,"usgs":true,"family":"Lucas","given":"Martyn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":644590,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":644581,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Krueger, Charles C.","contributorId":73131,"corporation":false,"usgs":true,"family":"Krueger","given":"Charles C.","affiliations":[],"preferred":false,"id":644591,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70169299,"text":"70169299 - 2016 - Permissible Home Range Estimation (PHRE) in restricted habitats: A new algorithm and an evaluation for sea otters","interactions":[],"lastModifiedDate":"2016-03-24T08:44:05","indexId":"70169299","displayToPublicDate":"2016-03-22T09:45:00","publicationYear":"2016","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":"Permissible Home Range Estimation (PHRE) in restricted habitats: A new algorithm and an evaluation for sea otters","docAbstract":"Parametric and nonparametric kernel methods dominate studies of animal home ranges and space use. Most existing methods are unable to incorporate information about the underlying physical environment, leading to poor performance in excluding areas that are not used. Using radio-telemetry data from sea otters, we developed and evaluated a new algorithm for estimating home ranges (hereafter Permissible Home Range Estimation, or “PHRE”) that reflects habitat suitability. We began by transforming sighting locations into relevant landscape features (for sea otters, coastal position and distance from shore). Then, we generated a bivariate kernel probability density function in landscape space and back-transformed this to geographic space in order to define a permissible home range. Compared to two commonly used home range estimation methods, kernel densities and local convex hulls, PHRE better excluded unused areas and required a smaller sample size. Our PHRE method is applicable to species whose ranges are restricted by complex physical boundaries or environmental gradients and will improve understanding of habitat-use requirements and, ultimately, aid in conservation efforts.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0150547","collaboration":"USFWS","usgsCitation":"Tarjan, L.M., and Tinker, M.T., 2016, Permissible Home Range Estimation (PHRE) in restricted habitats: A new algorithm and an evaluation for sea otters: PLoS ONE, v. 11, no. 3, https://doi.org/10.1371/journal.pone.0150547.","productDescription":"20 p.","startPage":"e0150547","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072967","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471131,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0150547","text":"Publisher Index Page"},{"id":438630,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76H4FH8","text":"USGS data release","linkHelpText":"Geospatial data collected from tagged sea otters in central California, 1998-2012"},{"id":319336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-22","publicationStatus":"PW","scienceBaseUri":"56f50fcce4b0f59b85e1eb77","contributors":{"authors":[{"text":"Tarjan, Lily M","contributorId":167782,"corporation":false,"usgs":false,"family":"Tarjan","given":"Lily","email":"","middleInitial":"M","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":623488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":623487,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159388,"text":"sir20155152 - 2016 - Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska","interactions":[],"lastModifiedDate":"2016-03-22T10:17:15","indexId":"sir20155152","displayToPublicDate":"2016-03-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5152","title":"Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska","docAbstract":"Digital flood-inundation maps for a 12.5-mile reach of the Big Papillion Creek from 0.6 mile upstream from the State Street Bridge to the 72nd Street Bridge in Omaha, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the Papio-Missouri River Natural Resources District. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Big Papillion Creek at Fort Street at Omaha, Nebraska (station 06610732). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at this site.
\nFlood profiles were computed for the 12.5-mile reach by means of a one-dimensional step-backwater model. The model was calibrated by using the current (2015) stage-discharge relation at streamgages for the Big Papillion Creek at Fort Street at Omaha, Nebraska, and the Big Papillion Creek at Q Street at Omaha, Nebraska. The hydraulic model was then used to compute 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum for the Big Papillion Creek at Fort Street and ranging from 18 ft (or near bankfull) to 32 ft, which exceeds the “major flood stage” as defined by the National Weather Service. The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging data having a 1.18-ft vertical accuracy and 3.28-ft horizontal resolution) to delineate the area flooded at each flood stage (water level).
\nThe availability of these flood-inundation maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155152","collaboration":"Prepared in cooperation with the Papio-Missouri River Natural Resources District","usgsCitation":"Strauch, K.R., Dietsch, B.J., and Anderson, K.J., 2016, Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska: U.S. Geological Survey Scientific Investigations Report 2015–5152, 11 p., https://dx.doi.org/10.3133/sir20155152.","productDescription":"Report: v, 11 p.; Datasets; Metadata","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066029","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":314625,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_river_areas_GRIDS.zip","text":"River area GRIDS","size":"52.9 MB","description":"SIR 2015–5152 River area GRIDS"},{"id":314626,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_river_areas_shapefiles.zip","text":"River area shapefiles","size":"2.2 MB","description":"SIR 2015–5152 River area shapefiles"},{"id":314628,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_metadata_BigPapio_at_Fort_FIM_GRID.txt","text":"GRID metadata","size":"20.0 kb","description":"SIR 2015–5152 GRID metadata"},{"id":314629,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_metadata_BigPapio_at_Fort_FIM_shapefile.txt","text":"Shapefile metadata","size":"20.0 kb","description":"SIR 2015–5152 Shapefile metadata"},{"id":314466,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152.pdf","text":"Report","size":"2.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5152"},{"id":314622,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_levee_areas_GRIDS.zip","text":"Levee area GRIDS","size":"1.6 MB","description":"SIR 2015–5152 Levee area GRIDS"},{"id":314623,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_levee_areas_shapefiles.zip","text":"Levee area shapefiles","size":"144 kb","description":"SIR 2015–5152 Levee area shapefiles"},{"id":314465,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5152/coverthb.jpg"}],"country":"United States","state":"Nebraska","city":"Omaha","otherGeospatial":"Big Papillion Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.16676330566406,\n 41.23702755320388\n ],\n [\n -96.16676330566406,\n 41.35052580597025\n ],\n [\n -96.01020812988281,\n 41.35052580597025\n ],\n [\n -96.01020812988281,\n 41.23702755320388\n ],\n [\n -96.16676330566406,\n 41.23702755320388\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
This report, prepared by the U.S. Geological Survey in cooperation with the Kansas Department of Agriculture, Division of Water Resources, presents derivative statistics of 2013 irrigation water use in Kansas. The published regional and county-level statistics from the previous 4 years (2009–12) are shown with the 2013 statistics and are used to calculate a 5-year average. An overall Kansas average and regional averages also are calculated and presented. Total reported irrigation water use in 2013 was 3.3 million acre-feet of water applied to 3.0 million irrigated acres.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds981","collaboration":"Prepared in cooperation with the Kansas Department of Agriculture, Division of Water Resources","usgsCitation":"Lanning-Rush, J.L., 2016, Irrigation water use in Kansas, 2013: U.S. Geological Survey Data Series 981, 12 p., https://dx.doi.org/10.3133/ds981.","productDescription":"Report: iv, 12 p.; Tables 6-12; Appendix: 2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070156","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":318889,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0981/ds981.pdf","text":"Report","size":"617 kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 981"},{"id":318890,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0981/downloads/ds981_tables6to12.xlsx","text":"Tables 6–12","size":"80 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 981 Tables "},{"id":318888,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0981/coverthb_new.jpg"},{"id":318893,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0981/downloads/ds981_appendix.pdf","text":"Water-Use Report","size":"1.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 981 Appendix"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.29541015625,\n 39.99395569397331\n ],\n [\n -102.06298828125,\n 40.01078714046552\n ],\n [\n -102.052001953125,\n 36.98500309285596\n ],\n [\n -94.603271484375,\n 36.99377838872517\n ],\n [\n -94.6142578125,\n 39.13006024213511\n ],\n [\n -94.76806640624999,\n 39.172658670429946\n ],\n [\n -94.82299804687499,\n 39.2407625100131\n ],\n [\n -94.910888671875,\n 39.29179704377487\n ],\n [\n -94.8779296875,\n 39.38526381099777\n ],\n [\n -94.976806640625,\n 39.436192999314095\n ],\n [\n -95.086669921875,\n 39.53793974517628\n ],\n [\n -95.042724609375,\n 39.57182223734374\n ],\n [\n -95.042724609375,\n 39.63953756436671\n ],\n [\n -94.9658203125,\n 39.73253798438173\n ],\n [\n -94.910888671875,\n 39.73253798438173\n ],\n [\n -94.888916015625,\n 39.78321267821705\n ],\n [\n -94.910888671875,\n 39.842286020743394\n ],\n [\n -94.95483398437499,\n 39.8928799002948\n ],\n [\n -95.03173828125,\n 39.90973623453719\n ],\n [\n -95.06469726562499,\n 39.87601941962116\n ],\n [\n -95.174560546875,\n 39.926588421909436\n ],\n [\n -95.29541015625,\n 39.99395569397331\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
Seepage investigations have been conducted annually by the U.S. Geological Survey from 1988 to 1998 and from 2004 to the present (2015) along a 64-mile reach of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, as part of the Mesilla Basin monitoring program. Results of the investigation conducted in 2015 are presented in this report. The 2015 seepage investigation was conducted on February 10, 2015, during the low-flow conditions of the non-irrigation season. During the 2015 investigation, discharge was measured at 23 sites along the main-stem Rio Grande and 19 inflow sites within the study reach. Because of extended drought conditions affecting the basin, many sites along the Rio Grande (17 main-stem and 10 inflow) were observed to be dry in February 2015.
\nNet seepage gain or loss was computed for each subreach (the interval between two adjacent measurement locations along the river) by subtracting the discharge measured at the upstream location from the discharge measured at the closest downstream location along the river and then subtracting any inflow to the river within the subreach. An estimated gain or loss was determined to be meaningful when it exceeded the cumulative measurement uncertainty associated with the net seepage computation. The cumulative seepage loss in the 64-mile study reach in 2015 was 17.3 plus or minus 2.6 cubic feet per second. Gaining and losing reaches identified in this investigation generally correspond to seepage patterns observed in previous investigations conducted during dry years, with the gaining reaches occurring primarily at the southern (downstream) end of the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165011","usgsCitation":"Briody, A.C., Robertson, A.J., and Thomas, Nicole, 2016, Seepage investigation of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5011, 15 p., https://dx.doi.org/10.3133/sir20165011.","productDescription":"vi., 15 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069688","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":319125,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5011/sir20165011.pdf","text":"Report","size":"3.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5011"},{"id":319124,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5011/coverthb.jpg"}],"country":"United States","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.85302734374999,\n 31.728167146023935\n ],\n [\n -106.85302734374999,\n 32.41706632846282\n ],\n [\n -106.3970947265625,\n 32.41706632846282\n ],\n [\n -106.3970947265625,\n 31.728167146023935\n ],\n [\n -106.85302734374999,\n 31.728167146023935\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montogmery Blvd., NE Suite 400
Albuquerque, NM 87109–1311
Seepage investigations have been conducted annually by the U.S. Geological Survey from 1988 to 1998 and from 2004 to the present (2014) along a 64-mile reach of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, as part of the Mesilla Basin monitoring program. Results of the investigation conducted in 2014 are presented in this report. The 2014 seepage investigation was conducted on February 11, 2014, during the low-flow conditions of the non-irrigation season. During the 2014 investigation, discharge was measured at 23 sites along the main-stem Rio Grande and 19 inflow sites within the study reach. Because of extended drought conditions affecting the basin, many sites along the Rio Grande (17 main-stem and 9 inflow) were observed to be dry in February 2014. Water-quality samples were collected during the seepage investigation at sites with flowing water as part of a long-term monitoring effort in the region.
Net seepage gain or loss was computed for each subreach (the interval between two adjacent measurement locations along the river) by subtracting the discharge measured at the upstream location from the discharge measured at the closest downstream location along the river and then subtracting any inflow to the river within the subreach. An estimated gain or loss was determined to be meaningful when it exceeded the cumulative measurement uncertainty associated with the net seepage computation. The cumulative seepage loss in the 64-mile study reach in 2014 was 16.0 plus or minus 2.9 cubic feet per second.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165010","usgsCitation":"Briody, A.C., Robertson, A.J., and Thomas, Nicole, 2016, Seepage investigation of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, 2014: U.S. Geological Survey Scientific Investigations Report 2016–5010, 15 p., https://dx.doi.org/10.3133/sir20165010.","productDescription":"Report: vi, 12 p., Appendix: 3 p.","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068494","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":319116,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5010/coverthb.jpg"},{"id":319117,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5010/sir20165010.pdf","text":"Report","size":"3.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5010"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.9,\n 32.5\n ],\n [\n -106.9,\n 31.75\n ],\n [\n -106.5,\n 31.75\n ],\n [\n -106.5,\n 32.5\n ],\n [\n -106.9,\n 32.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montogmery Blvd., NE Suite 400
Albuquerque, NM 87109–1311
Non-native fish introductions are a major threat to biodiversity and fisheries, and occur through numerous pathways that vary regionally in importance. A key strategy for managing invasions is to focus prevention efforts on pathways posing the greatest risk of future introductions. We identified high-risk pathways for fish establishment in the Mid-Atlantic region of the United States based on estimates of probability of establishment and records of previous introductions, which were considered in the context of emerging socioeconomic trends. We used estimates of propagule pressure, species’ environmental tolerance, and size of species pool to assess the risk of establishment by pathway. Pathways varied considerably in historic importance and species composition, with the majority of species introduced intentionally via stocking (primarily for sport, forage, or biocontrol) or bait release. Bait release, private stocking, illegal introductions intended to establish reproducing populations (e.g., of sport fish), aquaculture, and the sale of live organisms all create risks for future invasions in the Mid-Atlantic region. Of these pathways, bait release probably poses the greatest risk of introductions for the Mid-Atlantic region because propagule pressure is moderate, most released species are tolerant of local environmental conditions, and the pool of species available for transplantation is large. Our findings differ considerably from studies in other regions (e.g., bait release is a dominant pathway in the Mid-Atlantic region, whereas illegal introduction of sport fish is dominant in the western US and aquarium releases are dominant in Florida), demonstrating the need for regional-scale assessments of, and management strategies for, introduction pathways.
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The monarch’s multi-generational migration between overwintering grounds in central Mexico and the summer breeding grounds in the northern U.S. and southern Canada is celebrated in all three countries and creates shared management responsibilities across North America. Here we present a novel Bayesian multivariate auto-regressive state-space model to assess quasi-extinction risk and aid in the establishment of a target population size for monarch conservation planning. We find that, given a range of plausible quasi-extinction thresholds, the population has a substantial probability of quasi-extinction, from 11–57% over 20 years, although uncertainty in these estimates is large. Exceptionally high population stochasticity, declining numbers, and a small current population size act in concert to drive this risk. An approximately 5-fold increase of the monarch population size (relative to the winter of 2014–15) is necessary to halve the current risk of quasi-extinction across all thresholds considered. Conserving the monarch migration thus requires active management to reverse population declines, and the establishment of an ambitious target population size goal to buffer against future environmentally driven variability.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/srep23265","usgsCitation":"Semmens, B.X., Semmens, D.J., Thogmartin, W.E., Wiederholt, R., Lopez-Hoffman, L., Diffendorfer, J., Pleasants, J., Oberhauser, K.S., and Taylor, O.R., 2016, Quasi-extinction risk and population targets for the Eastern, migratory population of monarch butterflies (Danaus plexippus): Scientific Reports, v. 6, Article number 23265; 7 p., https://doi.org/10.1038/srep23265.","productDescription":"Article number 23265; 7 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066835","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":471134,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep23265","text":"Publisher Index Page"},{"id":320161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-21","publicationStatus":"PW","scienceBaseUri":"571756e6e4b0ef3b7caa62a9","contributors":{"authors":[{"text":"Semmens, Brice X.","contributorId":149775,"corporation":false,"usgs":false,"family":"Semmens","given":"Brice","email":"","middleInitial":"X.","affiliations":[{"id":17820,"text":"Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":626766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":626765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":626767,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiederholt, Ruscena","contributorId":149125,"corporation":false,"usgs":false,"family":"Wiederholt","given":"Ruscena","affiliations":[{"id":17653,"text":"School of Natural Resources & the Environment, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":626768,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":626769,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":626770,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pleasants, John M.","contributorId":168616,"corporation":false,"usgs":false,"family":"Pleasants","given":"John M.","affiliations":[{"id":25341,"text":"Department of Ecology, Evolution, and Organismal Biology, Iowa State University","active":true,"usgs":false}],"preferred":false,"id":626771,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oberhauser, Karen S.","contributorId":27737,"corporation":false,"usgs":true,"family":"Oberhauser","given":"Karen","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":626772,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Taylor, Orley R.","contributorId":168617,"corporation":false,"usgs":false,"family":"Taylor","given":"Orley","email":"","middleInitial":"R.","affiliations":[{"id":25342,"text":"Department of Ecology and Evolutionary Biology, University of Kansas","active":true,"usgs":false}],"preferred":false,"id":626773,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}