Inorganic forms of nitrogen and phosphorous impact freshwater lakes by stimulating primary production and affecting water quality and ecosystem health. Communities around the world are motivated to sustain and restore freshwater resources and are interested in processes controlling nutrient inputs. We studied the environment where streams flow into lakes, referred to as the stream-lake interface (SLI), for a channelized and unmodified stream outlet. Channelization is done to protect infrastructure or recreational beach areas. We collected hydraulic and nutrient data for surface water and shallow groundwater in two SLIs to develop conceptual models that describe characteristics that are representative of these hydrologic features. Water, heat, and solute transport models were used to evaluate hydrologic conceptualizations and estimate mean residence times of water in the sediment. A nutrient mass balance model is developed to estimate net rates of adsorption and desorption, mineralization, and nitrification along subsurface flow paths. Results indicate that SLIs are dynamic sources of nutrients to lakes and that the common practice of channelizing the stream at the SLI decreases nutrient concentrations in pore water discharging along the lakeshore. This is in contrast to the unmodified SLI that forms a barrier beach that disconnects the stream from the lake and results in higher nutrient concentrations in pore water discharging to the lake. These results are significant because nutrient delivery through pore water seepage at the lakebed from the natural SLI contributes to nearshore algal communities and produces elevated concentrations of inorganic nutrients in the benthic zone where attached algae grow.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016WR019538","usgsCitation":"Niswonger, R.G., Naranjo, R.C., Smith, D., Constantz, J., Allander, K.K., Rosenberry, D.O., Neilson, B., Rosen, M.R., and Stonestrom, D.A., 2017, Nutrient processes at the stream-lake interface for a channelized versus unmodified stream mouth: Water Resources Research, v. 53, no. 1, p. 237-256, https://doi.org/10.1002/2016WR019538.","productDescription":"20 p.","startPage":"237","endPage":"256","ipdsId":"IP-077507","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":334057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-11","publicationStatus":"PW","scienceBaseUri":"588b1976e4b0ad67323f97da","contributors":{"authors":[{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":152462,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":661003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Naranjo, Ramon C. 0000-0003-4469-6831 rnaranjo@usgs.gov","orcid":"https://orcid.org/0000-0003-4469-6831","contributorId":3391,"corporation":false,"usgs":true,"family":"Naranjo","given":"Ramon","email":"rnaranjo@usgs.gov","middleInitial":"C.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":661004,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David 0000-0002-9543-800X","orcid":"https://orcid.org/0000-0002-9543-800X","contributorId":169280,"corporation":false,"usgs":true,"family":"Smith","given":"David","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":661005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Constantz, James E. 0000-0002-4062-2096 jconstan@usgs.gov","orcid":"https://orcid.org/0000-0002-4062-2096","contributorId":1962,"corporation":false,"usgs":true,"family":"Constantz","given":"James E.","email":"jconstan@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":661006,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allander, Kip K. 0000-0002-3317-298X kalland@usgs.gov","orcid":"https://orcid.org/0000-0002-3317-298X","contributorId":2290,"corporation":false,"usgs":true,"family":"Allander","given":"Kip","email":"kalland@usgs.gov","middleInitial":"K.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":661007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":661008,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neilson, Bethany","contributorId":178798,"corporation":false,"usgs":false,"family":"Neilson","given":"Bethany","affiliations":[],"preferred":false,"id":661009,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":661010,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stonestrom, David A. 0000-0001-7883-3385 dastones@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-3385","contributorId":2280,"corporation":false,"usgs":true,"family":"Stonestrom","given":"David","email":"dastones@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":661011,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70185576,"text":"70185576 - 2016 - Downstream passage and impact of turbine shutdowns on survival of silver American Eels at five hydroelectric dams on the Shenandoah River","interactions":[],"lastModifiedDate":"2017-03-24T10:26:18","indexId":"70185576","displayToPublicDate":"2017-03-24T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Downstream passage and impact of turbine shutdowns on survival of silver American Eels at five hydroelectric dams on the Shenandoah River","docAbstract":"Hydroelectric dams impact the downstream migrations of silver American Eels Anguilla rostrata via migratory delays and turbine mortality. A radiotelemetry study of American Eels was conducted to determine the impacts of five run-of-the-river hydroelectric dams located over a 195-km stretch of the Shenandoah River, Virginia–West Virginia, during fall 2007–summer 2010. Overall, 96 radio-tagged individuals (mean TL = 85.4 cm) migrated downstream past at least one dam during the study. Most American Eels passed dams relatively quickly; over half (57.9%) of the dam passage events occurred within 1 h of reaching a dam, and most (81.3%) occurred within 24 h of reaching the dam. Two-thirds of the dam passage events occurred via spill, and the remaining passage events were through turbines. Migratory delays at dams were shorter and American Eels were more likely to pass via spill over the dam during periods of high river discharge than during low river discharge. The extent of delay in migration did not differ between the passage routes (spill versus turbine). Twenty-eight American Eels suffered turbine-related mortality, which occurred at all five dams. Mortality rates for eels passing through turbines ranged from 15.8% to 40.7% at individual dams. Overall project-specific mortality rates (with all passage routes combined) ranged from 3.0% to 14.3%. To protect downstream-migrating American Eels, nighttime turbine shutdowns (1800–0600 hours) were implemented during September 15–December 15. Fifty percent of all downstream passage events in the study occurred during the turbine shutdown period. Implementation of the seasonal turbine shutdown period reduced cumulative mortality from 63.3% to 37.3% for American Eels passing all five dams. Modifying the turbine shutdown period to encompass more dates in the spring and linking the shutdowns to environmental conditions could provide greater protection to downstream-migrating American Eels.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"New York, NY","doi":"10.1080/00028487.2016.1176954","usgsCitation":"Eyler, S., Welsh, S., Smith, D.R., and Rockey, M., 2016, Downstream passage and impact of turbine shutdowns on survival of silver American Eels at five hydroelectric dams on the Shenandoah River: Transactions of the American Fisheries Society, v. 145, no. 5, p. 964-976, https://doi.org/10.1080/00028487.2016.1176954.","productDescription":"13 p.","startPage":"964","endPage":"976","ipdsId":"IP-078753","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":338259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia, West Virginia","otherGeospatial":"Shenandoah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": 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swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":686009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":686011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rockey, Mary","contributorId":189780,"corporation":false,"usgs":false,"family":"Rockey","given":"Mary","email":"","affiliations":[],"preferred":false,"id":686012,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178056,"text":"sir20165144 - 2016 - Occurrence, distribution, and volume of metals-contaminated sediment of selected streams draining the Tri-State Mining District, Missouri, Oklahoma, and Kansas, 2011–12","interactions":[],"lastModifiedDate":"2025-05-15T13:28:14.577692","indexId":"sir20165144","displayToPublicDate":"2016-12-14T00:00:00","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":"2016-5144","title":"Occurrence, distribution, and volume of metals-contaminated sediment of selected streams draining the Tri-State Mining District, Missouri, Oklahoma, and Kansas, 2011–12","docAbstract":"Lead and zinc were mined in the Tri-State Mining District (TSMD) of southwest Missouri, northeast Oklahoma, and southeast Kansas for more than 100 years. The effects of mining on the landscape are still evident, nearly 50 years after the last mine ceased operation. The legacies of mining are the mine waste and discharge of groundwater from underground mines. The mine-waste piles and underground mines are continuous sources of trace metals (primarily lead, zinc, and cadmium) to the streams that drain the TSMD. Many previous studies characterized the horizontal extent of mine-waste contamination in streams but little information exists on the depth of mine-waste contamination in these streams. Characterizing the vertical extent of contamination is difficult because of the large amount of coarse-grained material, ranging from coarse gravel to boulders, within channel sediment. The U.S. Geological Survey, in cooperation with U.S. Fish and Wildlife service, collected channel-sediment samples at depth for subsequent analyses that would allow attainment of the following goals: (1) determination of the relation between concentration and depth for lead, zinc and cadmium in channel sediments and flood-plain sediments, and (2) determination of the volume of gravel-bar sediment from the surface to the maximum depth with concentrations of these metals that exceeded sediment-quality guidelines. For the purpose of this report, volume of gravel-bar sediment is considered to be distributed in two forms, gravel bars and the wetted channel, and this study focused on gravel bars. Concentrations of lead, zinc, and cadmium in samples were compared to the consensus probable effects concentration (CPEC) and Tri-State Mining District specific probable effects concentration (TPEC) sediment-quality guidelines.
During the study, more than 700 sediment samples were collected from borings at multiple sites, including gravel bars and flood plains, along Center Creek, Turkey Creek, Shoal Creek, Tar Creek, and Spring River in order to characterize the vertical extent of mine waste in select streams in the TSMD. The largest concentrations of lead, zinc, and cadmium in gravel bar-sediment samples generally were detected in Turkey Creek and Tar Creek and the smallest concentrations were detected in Shoal Creek followed by the Spring River. Gravel bar-sediment samples from Turkey Creek exceeded the CPEC for cadmium (minimum of 70 percent of samples), lead (94 percent), and zinc (99 percent) at a slightly higher frequency than similar samples from Tar Creek (69 percent, 88 percent, and 96 percent, respectively). Gravel bar-sediment samples from Turkey Creek also contained the largest concentrations of cadmium (174 milligrams per kilogram [mg/kg]) and lead (7,520 mg/kg) detected; however, the largest zinc concentration (46,600 mg/kg) was detected in a gravel bar-sediment sample from Tar Creek. In contrast, none of the 65 gravel bar-sediment samples from Shoal Creek contained cadmium above the x-ray fluorescence reporting level of 12 mg/kg, and lead and zinc exceeded the CPEC in only 12 percent and 74 percent of samples, respectively. In most cases, concentrations of lead and zinc above the CPEC or TPEC were present at the maximum depth of boring, which indicated that nearly the entire thickness of sediment in the stream has been contaminated by mine wastes. Approximately 284,000 cubic yards of channel sediment from land surface to the maximum depth that exceeded the CPEC and approximately 236,000 cubic yards of channel sediment from land surface to the maximum depth that exceeded the TPEC were estimated along 37.6 of the 55.1 miles of Center Creek, Turkey Creek, Shoal Creek, and Tar Creek examined in this study. Mine-waste contamination reported along additional reaches of these streams is beyond the scope of this study. Flood-plain cores collected in the TSMD generally only had exceedances of the CPEC and TPEC for lead and zinc in the top 1 or 2 feet of soil with a few exceptions, such as cores in low areas near the stream or cores in areas disturbed by past mining.
Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
The Walker River is an important source of water for western Nevada. The river provides water for agriculture and recharge to local aquifers used by several communities. Farmers began diverting water from the Walker River in the 1860s to support growing agricultural development. Over time, the reduced inflows into Walker Lake from upstream reservoirs and diversions have resulted in 170 feet of lake level decline and increased dissolved-solids concentrations to levels that threaten aquatic ecosystems, including survival of Lahonton cutthroat trout, a native species listed in the Endangered Species Act. Investigations of the water-budget components in the Walker River Basin have revealed uncertainty in the recharge to aquifers from irrigation canals. To address this need, the U.S. Geological Survey conducted an extensive field study from March 2012 through October 2013 to quantify seepage losses in selected canals in the Smith Valley, Mason Valley, and Walker Lake Valley irrigation areas.
The seepage rates estimated for the 2012 and 2013 irrigation seasons in the Smith Valley transect sites (Saroni and Plymouth canals) ranged between 0.01 to 2.5 feet per day (ft/d) (0.01 to 0.68 cubic feet per second per mile [ft3/s-mi]). From 2012 to 2013, the average number of days the canals had flowing water decreased from 190 to 125 due to drier climate and lack of water available for diversion from the Walker River. The nearly 50-percent reductions in volumetric loss rates between 2012 and 2013 were associated with less than average diversions into canals from the Walker River and reductions in infiltration rates following routine canal maintenance.
Models developed for the Saroni canal in 2012 were recalibrated in 2013 to evaluate changes in seepage as a result of siltation. Just prior to the 2012 irrigation season, nearly the entire length of the canal was cleared of vegetation and debris to improve flow conveyance. In 2013, following the first year of maintenance, a 90-percent reduction in seepage was observed at one of the transect sites. The removal of sediment-clogged layers during canal maintenance may have more profound effects on seepage rates beyond what was observed at the transect sites. The seepage rates for the Saroni canal in 2012 ranged from 0.02 to 1.6 ft/d (0.03 to 0.4 ft3/s-mi). The total seepage loss in the Saroni canal for the 2012 and 2013 irrigation seasons was estimated to be 1,100 and 590 acre-feet (acre-ft), respectively.
Seepage rates on the Plymouth canal in Smith Valley in 2012 were among the lowest, ranging from 0.01 to 0.2 ft/d (0.01 to 0.1 ft3/s-mi). In 2013, the seepage rate on the Plymouth canal was similar to 2012; however, the volumetric loss was reduced by 50 percent due to the 50-percent reduction in number of canal flow days. Lower rates of seepage on the Plymouth canal for the 2012 and 2013 irrigation seasons were estimated to be 210 and 130 acre-ft, respectively.
The seepage rates estimated for the 2012 and 2013 irrigation seasons in the Mason Valley transect sites (Fox, Mickey, and Campbell ditches) ranged from 0.1 to 3.3 ft/d (0.2 to 1.3 ft3/s-mi). The influence of water-table declines on seepage was observed at the Mickey and Campbell ditches. In 2012, the estimated seepage on the Mickey ditch was 1.6 ft/d during a period when the water-table altitude was at or above the canal altitude. Following extensive declines in the water table, the hydraulic gradient increased between the canal and the shallow aquifer, thereby increasing the seepage rates to 3.2 ft/d in 2013. During the period of hydraulic disconnection, seepage rates increased to 9.5 ft/d during intermittent periods of canal flow. For the Mickey ditch, the seepage loss in 2013 was 1.5 times the rate estimated in 2012 despite the canal having 45 days less flow. Similarly, the Campbell ditch seepage loss increased slightly from 660 to 700 acre-ft, a factor of 1.1, with 49 days less flow. The seepage loss for the Fox ditch did not exhibit significant year to year variability. The annual seepage loss estimated for 2012 and 2013 in the Fox ditch was 2,100 and 2,200 acre-ft, respectively.
The seepage rates estimated for the 2013 irrigation season in the Walker Lake Valley transect sites (Schurz Lateral Canals 1A and 2A, and Canal 2) ranged from 0.7 to 0.9 ft/d (0.4 to 1.3 ft3/s-mi). In Walker Lake Valley, diversions into Lateral Canals 1A and 2A during the 2013 irrigation season were highly intermittent, a characteristic common of lateral diversions. The annual estimated seepage loss in Walker Lake Valley ranged between 50 and 725 acre-ft among the transect sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165133","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Naranjo, R.C., and Smith, D.W., 2016, Quantifying seepage using heat as a tracer in selected irrigation canals, Walker River Basin, Nevada, 2012 and 2013: U.S. Geological Survey Scientific Investigations Report 2016-5133, 169 p.,\nhttps://dx.doi.org/10.3133/sir20165133.","productDescription":"Report: viii, 169 p.; 2 Appendixes","onlineOnly":"Y","ipdsId":"IP-066495","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":331031,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5133/sir20165133_appendix_6a.xlsx","text":"Appendix 6A","size":"16.4 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5133 Appendix 6A"},{"id":331030,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5133/sir20165133.pdf","text":"Report","size":"11.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5133"},{"id":331032,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5133/sir20165133_appendix_6b.xlsx","text":"Appendix 6B","size":"13.9 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5133 Appendix 6B"},{"id":331029,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5133/coverthb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Walker River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.75,\n 38\n ],\n [\n -119.75,\n 39.25\n ],\n [\n -118.25,\n 39.25\n ],\n [\n -118.25,\n 38\n ],\n [\n -119.75,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nv.water.usgs.gov/
The city of Sioux Falls is the fastest growing community in South Dakota. In response to this continued growth and planning for future development, Sioux Falls requires a sustainable supply of municipal water. Planning and managing sustainable groundwater supplies requires a thorough understanding of local groundwater resources. The Big Sioux aquifer consists of glacial outwash sands and gravels and is hydraulically connected to the Big Sioux River, which provided about 90 percent of the city’s source-water production in 2015. Managing sustainable groundwater supplies also requires an understanding of groundwater availability. An effective mechanism to inform water management decisions is the development and utilization of a groundwater-flow model. A groundwater-flow model provides a quantitative framework for synthesizing field information and conceptualizing hydrogeologic processes. These groundwater-flow models can support decision making processes by mapping and characterizing the aquifer. Accordingly, the city of Sioux Falls partnered with the U.S. Geological Survey to construct a groundwater-flow model. Model inputs will include data from advanced geophysical techniques, specifically airborne electromagnetic methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163075","collaboration":"Prepared in cooperation with the City of Sioux Falls","usgsCitation":"Valder, J.F., Delzer, G.C., Carter, J.M., Smith, B.D., and Smith, D.V., 2016, Construction of a groundwater-flow model for the Big Sioux aquifer using airborne electromagnetic methods, Sioux Falls, South Dakota: U.S. Geological Survey Fact Sheet 2016–3075, 4 p., https://dx.doi.org/10.3133/fs20163075.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-079092","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":328947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3075/fs20163075.pdf","text":"Fact Sheet","size":"4.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3075"},{"id":328946,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3075/coverthb.jpg"}],"country":"United States","state":"South Dakota","city":"Sioux Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.79023742675781,\n 43.56098868633536\n ],\n [\n -96.79023742675781,\n 43.823133635349556\n ],\n [\n -96.69136047363281,\n 43.823133635349556\n ],\n [\n -96.69136047363281,\n 43.56098868633536\n ],\n [\n -96.79023742675781,\n 43.56098868633536\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, South Dakota 57702
The acquisition and transfer of water rights to wetland areas of Lahontan Valley, Nevada, has caused concern over the potential effects on shallow aquifer water levels. In 1992, water levels in Lahontan Valley were measured to construct a water-table map of the shallow aquifer prior to the effects of water-right transfers mandated by the Fallon Paiute-Shoshone Tribal Settlement Act of 1990 (Public Law 101-618, 104 Stat. 3289). From 1992 to 2012, approximately 11,810 water-righted acres, or 34,356 acre-feet of water, were acquired and transferred to wetland areas of Lahontan Valley. This report documents changes in water levels measured during the period of water-right transfers and presents an evaluation of five groundwater-flow model scenarios that simulated water-level changes in Lahontan Valley in response to water-right transfers and a reduction in irrigation season length by 50 percent.
Water levels measured in 98 wells from 2012 to 2013 were used to construct a water-table map. Water levels in 73 of the 98 wells were compared with water levels measured in 1992 and used to construct a water-level change map. Water-level changes in the 73 wells ranged from -16.2 to 4.1 feet over the 20-year period. Rises in water levels in Lahontan Valley may correspond to annual changes in available irrigation water, increased canal flows after the exceptionally dry and shortened irrigation season of 1992, and the increased conveyance of water rights transferred to Stillwater National Wildlife Refuge. Water-level declines generally occurred near the boundary of irrigated areas and may be associated with groundwater pumping, water-right transfers, and inactive surface-water storage reservoirs. The largest water-level declines were in the area near Carson Lake.
Groundwater-level response to water-right transfers was evaluated by comparing simulated and observed water-level changes for periods representing water-right transfers and a shortened irrigation season in areas near Fallon and Stillwater, Nevada. In the Stillwater modeled area, water rights associated with nearly 50 percent of the irrigated land were transferred from 1992 to 1998, represented by the model scenario reduction in groundwater recharge by 50 percent. The scenario resulted in a simulated average decline of 0.6 foot; average observed water-level change for the modeled area was estimated to be 0.0 foot, or no change. In the Fallon modeled area, transfers of water rights associated with 180 acres of land occurred from 1994 to 2008. The transfer is most similar to the scenario for removal of 320 acres of irrigated land. The model scenario resulted in simulated water-level declines of 0.1; water levels measured from 1994 to 2012 indicate no significant trends in water levels, or approximately zero change in water levels, for the Fallon modeled area.
The model scenarios included the simulation of a irrigation season shortened by 50 percent, which was determined to have occurred in the 1992 irrigation season in both modeled areas. The shortening of the irrigation season in the Fallon modeled area resulted in simulated water-level declines of 1.1 feet; observed declines were estimated to be 1.3 feet. The Stillwater model simulations resulted in a simulated decline of 1.4 feet, and observed water levels declined an estimated 2.3 feet for the area. The estimated difference between simulated and observed water levels are 0.2 and 0.9 foot for the Fallon and Stillwater modeled areas, respectively. Observed water-level changes were generally within one standard deviation of changes from model simulations, based on the selected periods of comparison. Simulated and observed water-level changes agree well, generally within 1 foot; however, the model scenarios were only approximately similar to the observed conditions, and periods of comparison were generally shorter for the observed periods and included additional cumulative effects of water-right transfers. Climate variability was not considered in the model scenarios.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165045","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Smith, D.W., Buto, S.G., and Welborn, T.L., 2016, Groundwater-level change and evaluation of simulated water levels for irrigated areas in Lahontan Valley, Churchill County, west-central Nevada, 1992‒2012: U.S. Geological Survey Scientific Investigations Report 2016-5045, 23 p., https://dx.doi.org/10.3133/sir20165045.","productDescription":"Report: vi, 23 p.; 1 Plate: 30.00 x 26.00 inches; 3 Appendixes; 2 Data Releases","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049203","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":438548,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7222RWF","text":"USGS data release","linkHelpText":"Go to View Manage Groundwater-level and groundwater-level change contours for the Lahontan Valley shallow aquifer near Fallon, Nevada, 2012"},{"id":328562,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5045/sir20165045_appendix2.xlsx","text":"Appendix 2","size":"11 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5045 Appendix 2"},{"id":328558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5045/coverthb.jpg"},{"id":328559,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5045/sir20165045.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5045"},{"id":328560,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5045/sir20165045_plate01.pdf","text":"Plate 1","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5045 Plate 1","linkHelpText":"Water-level Contours of Lahontan Valley"},{"id":328561,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5045/sir20165045_appendix1.xlsx","text":"Appendix 1","size":"28 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5045 Appendix 1"},{"id":328563,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5045/sir20165045_appendix3.pdf","text":"Appendix 3","size":"608 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5045 Appendix 3"},{"id":328564,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7222RWF","text":"GIS Datasets","description":"SIR 2016-5045 GIS data","linkHelpText":"Groundwater-level and groundwater-level change contours for the Lahontan Valley shallow aquifer near Fallon, Nevada, 2012"}],"country":"United States","state":"Nevada","county":"Churchill County","otherGeospatial":"Lahontan Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.25,\n 39\n ],\n [\n -119.25,\n 39.75\n ],\n [\n -118.40,\n 39.75\n ],\n [\n -118.40,\n 39\n ],\n [\n -119.25,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/
Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2016.05.016","usgsCitation":"Ellefsen, K.J., and Smith, D., 2016, Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model: Applied Geochemistry, v. 75, p. 200-210, https://doi.org/10.1016/j.apgeochem.2016.05.016.","productDescription":"11 p.","startPage":"200","endPage":"210","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073180","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":324600,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":470811,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2016.05.016","text":"Publisher Index Page"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107,\n 37\n ],\n [\n -107,\n 41\n ],\n [\n -102,\n 41\n ],\n [\n -102,\n 37\n ],\n [\n -107,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e345e4b07dd077c5fcab","contributors":{"authors":[{"text":"Ellefsen, Karl J. 0000-0003-3075-4703 ellefsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3075-4703","contributorId":789,"corporation":false,"usgs":true,"family":"Ellefsen","given":"Karl","email":"ellefsen@usgs.gov","middleInitial":"J.","affiliations":[{"id":82803,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":false}],"preferred":true,"id":629166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David 0000-0002-9543-800X","orcid":"https://orcid.org/0000-0002-9543-800X","contributorId":169280,"corporation":false,"usgs":true,"family":"Smith","given":"David","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":629167,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171109,"text":"sir20165067 - 2016 - Geologic and geophysical models for Osage County, Oklahoma, with implications for groundwater resources","interactions":[],"lastModifiedDate":"2025-05-14T18:51:50.000213","indexId":"sir20165067","displayToPublicDate":"2016-06-16T10:00:00","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":"2016-5067","title":"Geologic and geophysical models for Osage County, Oklahoma, with implications for groundwater resources","docAbstract":"This report summarizes a three-dimensional (3-D) geologic model that was constructed to provide a framework to investigate groundwater resources of the Osage Nation in northeastern Oklahoma. This report also presents an analysis of an airborne electromagnetic (AEM) survey that assessed the spatial variation of electrical resistivity to depths as great as 300 meters in the subsurface. The report and model provide support for a countywide assessment of groundwater resources, emphasizing the Upper Pennsylvanian rock units in the shallow subsurface of central and eastern Osage County having electrical resistivity properties that may indicate aquifers.
\nSurface outcrops and subsurface stratigraphic picks on wire-line geophysical logs of Upper Pennsylvanian–Lower Permian sedimentary rock were used to construct a 3-D model of the geologic subsurface as an aid for evaluating groundwater resources in Osage County. Quaternary alluvium and terraces along major streams and the Arkansas River are included in the geologic framework model. Data from the AEM survey were subjected to quality-control procedures, truncated at depth of investigation (DOI), and then used to build a 3-D electrical resistivity model making use of secondary and tertiary interpolation profiles between primary data profiles. The AEM data highlight westward-inclined resistivity gradients that parallel the shallow dip of bedrock strata; bodies have resistivity >30 ohm-meters, and extend as much as 10 kilometers (km) down the dip of host geologic units. Volume analysis and internal imaging of an integrated 3-D geology and electrical resistivity model give a proxy for likely aquifer units with large relative volumes of high resistivity: Quaternary alluvium, Elgin Sandstone Lentil in the upper part of the Vamoosa Group, Tallant Formation, and parts of a combined Wann-Iola-Chanute Formation. Less voluminous, high-resistivity bodies correspond to intervals in the lower part of the Vamoosa Group in the east-central part of the county and probable limestone intervals in the upper part of the Vanoss Group in the northwest part of the county. Northwestern and eastern troughs of potable water previously defined for central Osage County generally correspond to down-dip projections of high-resistivity bodies associated with the Elgin Sandstone Lentil of the Vamoosa Group and Tallant Formation, respectively.
\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165067","collaboration":"Prepared in cooperation with the Osage Nation","usgsCitation":"Hudson, M.R., Smith, D.V., Pantea, M.P., and Becker, C.J., 2016, Geologic and geophysical models for Osage County, Oklahoma, and implications for groundwater resources: U.S. Geological Survey Scientific Investigations Report 2016–5067, 27 p., https://dx.doi.org/10.3133/sir20165067.","productDescription":"Report: vii, 27 p.; Companion Files; Datasets; Metadata; Readme File","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071283","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":323530,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2016/5067/Data.zip","text":"Data Files","size":"22.4 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5067 Data 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Center Director, USGS Geosciences and Environmental Change Science Center
Box 25046, Mail Stop 980
Denver, CO 80225
GcClust is a software package developed by the U.S. Geological Survey for statistical clustering of regional geochemical data, and similar data such as regional mineralogical data. Functions within the software package are written in the R statistical programming language. These functions, their documentation, and a copy of the user’s guide are bundled together in R’s unit of sharable code, which is called a “package.” The user’s guide includes step-by-step instructions showing how the functions are used to cluster data and to evaluate the clustering results. These functions are demonstrated in this report using test data, which are included in the package.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer Programs in Book 7: Automated Data Processing and Computations","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C13","usgsCitation":"Ellefsen, K.J, and Smith, D.B., 2016, User's guide for GcClust—An R package for clustering of regional geochemical data: U.S. Geological Survey report Techniques and Methods 7–C13, 21 p., https://dx.doi.org/10.3133/tm7c13.","productDescription":"Report: iv, 21 p.; Installation Instructions; Example R Scripts; GcClust; Read Me File","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072334","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":320329,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://github.com/USGS-R/GcClust","text":"GcClust Source Code","description":"TM 7-C13GcClust Source Code"},{"id":319810,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c13/GcClust_1.0.tar.gz","text":"GcClust","size":"1.74 MB","linkFileType":{"id":6,"text":"zip"},"description":"TM 7-C13 GcClust"},{"id":319809,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c13/ProcessScripts.R","text":"Example R scripts","size":"6.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"TM 7-C13 Example R scripts"},{"id":319808,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c13/InstallationInstructions.txt","text":"Installation Instructions","size":"2.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"TM 7-C13 Installation Instructions"},{"id":319807,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/tm/07/c13/00ReadMe.txt","text":"Read Me File","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"TM 7-C13 Read Me"},{"id":319806,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c13/tm7c13.pdf","text":"Report","size":"2.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-C13"},{"id":319805,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c13/coverthb.jpg"}],"publicComments":"This report is Chapter 13 of Section C: Computer Programs in Book 7: Automated Data Processing and Computations.","contact":"Center Director, USGS Central Mineral and Environmental Resources
Science Center
Box 25046, Mail Stop 973
Denver, CO 80225
The terminus of a stream flowing into a larger river, pond, lake, or reservoir is referred to as the stream-mouth reach or simply the stream mouth. The terminus is often characterized by rapidly changing thermal and hydraulic conditions that result in abrupt shifts in surface water/groundwater (sw/gw) exchange patterns, creating the potential for unique biogeochemical processes and ecosystems. Worldwide shoreline development is changing stream-lake interfaces through channelization of stream mouths, i.e., channel straightening and bank stabilization to prevent natural meandering at the shoreline. In the central Sierra Nevada (USA), Lake Tahoe's shoreline has an abundance of both “unmodified” (i.e., not engineered though potentially impacted by broader watershed engineering) and channelized stream mouths. Two representative stream mouths along the lake's north shore, one channelized and one unmodified, were selected to compare and contrast water and heat exchanges. Hydraulic and thermal properties were monitored during separate campaigns in September 2012 and 2013 and sw/gw exchanges were estimated within the stream mouth-shoreline continuum. Heat-flow and water-flow patterns indicated clear differences in the channelized versus the unmodified stream mouth. For the channelized stream mouth, relatively modulated, cool-temperature, low-velocity longitudinal streambed flows discharged offshore beneath warmer buoyant lakeshore water. In contrast, a seasonal barrier bar formed across the unmodified stream mouth, creating higher-velocity subsurface flow paths and higher diurnal temperature variations relative to shoreline water. As a consequence, channelization altered sw/gw exchanges potentially altering biogeochemical processing and ecological systems in and near the stream mouth.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015WR017013","usgsCitation":"Constantz, J., Naranjo, R.C., Niswonger, R.G., Allander, K.K., Neilson, B., Rosenberry, D.O., Smith, D.W., Rosecrans, C., and Stonestrom, D.A., 2016, Groundwater exchanges near a channelized versus unmodified stream mouth discharging to a subalpine lake: Water Resources Research, v. 52, no. 3, p. 2157-2177, https://doi.org/10.1002/2015WR017013.","productDescription":"21 p.","startPage":"2157","endPage":"2177","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061592","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":319737,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":471125,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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This paper focuses on synthesizing existing surface-air Hg flux data collected throughout the Western North American region and is part of a series of geographically focused Hg synthesis projects. A database of existing Hg flux data collected using the dynamic flux chamber (DFC) approach from almost a thousand locations was created for the Western North America region. Statistical analysis was performed on the data to identify the important variables controlling Hg fluxes and to allow spatiotemporal scaling. The results indicated that most of the variability in soil-air Hg fluxes could be explained by variations in soil-Hg concentrations, solar radiation, and soil moisture. This analysis also identified that variations in DFC methodological approaches were detectable among the field studies, with the chamber material and sampling flushing flow rate influencing the magnitude of calculated emissions. The spatiotemporal scaling of soil-air Hg fluxes identified that the largest emissions occurred from irrigated agricultural landscapes in California. Vegetation was shown to have a large impact on surface-air Hg fluxes due to both a reduction in solar radiation reaching the soil as well as from direct uptake of Hg in foliage. Despite high soil Hg emissions from some forested and other heavily vegetated regions, the net ecosystem flux (soil flux + vegetation uptake) was low. Conversely, sparsely vegetated regions showed larger net ecosystem emissions, which were similar in magnitude to atmospheric Hg deposition (except for the Mediterranean California region where soil emissions were higher). The net ecosystem flux results highlight the important role of landscape characteristics in effecting the balance between Hg sequestration and (re-)emission to the atmosphere.
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California","interactions":[],"lastModifiedDate":"2025-05-14T18:41:14.173917","indexId":"ofr20161021","displayToPublicDate":"2016-02-23T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1021","title":"Ecoregions of California","docAbstract":"Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across Federal agencies, State agencies, and nongovernment organizations that are responsible for different types of resources in the same geographical areas (Omernik and others, 2000).
The approach used to compile this map is based on the premise that ecological regions are hierarchical and can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997, map revised 2006). At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions (U.S. Environmental Protection Agency, 2013). Level IV, depicted here for California, is a further refinement of level III ecoregions. Explanations of the methods used to define these ecoregions are given in Omernik (1995), Omernik and others (2000), and Omernik and Griffith (2014).
California has great ecological and biological diversity. The State contains offshore islands and coastal lowlands, large alluvial valleys, forested mountain ranges, deserts, and various aquatic habitats. There are 13 level III ecoregions and 177 level IV ecoregions in California and most continue into ecologically similar parts of adjacent States of the United States or Mexico (Bryce and others, 2003; Thorson and others, 2003; Griffith and others, 2014).
The California ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale (Omernik, 1987; U.S. Environmental Protection Agency, 2013). This poster is the result of a collaborative project primarily between U.S. Environmental Protection Agency (USEPA) Region IX, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), California Department of Fish and Wildlife (DFW), U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), U.S. Department of the Interior–Geological Survey (USGS), and other State of California agencies and universities.
The project is associated with interagency efforts to develop a common framework of ecological regions (McMahon and others, 2001). Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service (Bailey and others, 1994; Miles and Goudy, 1997; Cleland and others, 2007), the USEPA (Omernik 1987, 1995), and the NRCS (U.S. Department of Agriculture–Soil Conservation Service, 1981; U.S. Department of Agriculture–Natural Resources Conservation Service, 2006). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in California, where some agreement has been reached among multiple resource-management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161021","collaboration":"Prepared in collaboration with U.S. Environmental Protection Agency, Region IX, Regional Applied Research Effort (RARE) program.","usgsCitation":"Griffith, G.E., Omernik, J.M., Smith, D.W., Cook, T.D.,\nTallyn, E., Moseley, K., and Johnson, C.B., 2016, Ecoregions of California (poster):\nU.S. Geological Survey Open-File Report 2016–1021, with map, scale 1:1,100,000,\nhttps://dx.doi.org/10.3133/ofr20161021.","productDescription":"2 Sheets: 36.00 x 47.00 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057004","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":318343,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1021/ofr20161021_sheet1.pdf","text":"Sheet 1 - Map","size":"21 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\"}}]}","contact":"Western Geographic Science Center
U.S. Geological Survey
345 Middlefield Road, MS 531
Menlo Park, CA 94025
http://geography.wr.usgs.gov/
Quaking aspen (Populus tremuloides) is the most widespread tree species in North America and has supported a unique ecosystem for tens of thousands of years, yet is currently threatened by dramatic loss and possible local extinctions. While multiple factors such as climate change and fire suppression are thought to contribute to aspen’s decline, increased browsing by elk (Cervus elaphus), which have experienced dramatic population increases in the last ∼80 years, may severely inhibit aspen growth and regeneration. Fires are known to favor aspen recovery, but in the last several decades the spatial scale and intensity of wildfires has greatly increased, with poorly understood ramifications for aspen growth. Here, focusing on the 2000 Cerro Grande fire in central New Mexico – one of the earliest fires described as a “mega-fire” - we use three methods to examine the impact of elk browsing on aspen regeneration after a mega-fire. First, we use an exclosure experiment to show that aspen growing in the absence of elk were 3× taller than trees growing in the presence of elk. Further, aspen that were both protected from elk and experienced burning were 8.5× taller than unburned trees growing in the presence of elk, suggesting that the combination of release from herbivores and stimulation from fire creates the largest aspen growth rates. Second, using surveys at the landscape level, we found a correlation between elk browsing intensity and aspen height, such that where elk browsing was highest, aspen were shortest. This relationship between elk browsing intensity and aspen height was stronger in burned (r = −0.53) compared to unburned (r = −0.24) areas. Third, in conjunction with the landscape-level surveys, we identified possible natural refugia, microsites containing downed logs, shrubs etc. that may inhibit elk browsing by physically blocking aspen from elk or by impeding elk’s ability to move through the forest patch. We did not find any consistent patterns between refuge elements and aspen size or canopy cover suggesting that natural refugia are not aiding in aspen recruitment and that all young aspen were susceptible to browsing. In much of their normal range, aspen are not growing to large size classes, which threatens the future of this iconic species and calls into question the ability of ecosystems to recover from mega-fires. Our results highlight the importance of considering multiple interacting factors (i.e. fire and increased elk browsing) when considering aspen management and regeneration.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2015.11.020","usgsCitation":"Smith, D.S., Fettig, S.M., and Bowker, M.A., 2016, Elevated Rocky Mountain elk numbers prevent positive effects of fire on quaking aspen (Populus tremuloides) recruitment: Forest Ecology and Management, v. 362, p. 46-54, https://doi.org/10.1016/j.foreco.2015.11.020.","productDescription":"9 p.","startPage":"46","endPage":"54","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067527","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Cerro Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.42507553100586,\n 35.858309181565716\n ],\n [\n -106.42507553100586,\n 35.881122573005875\n ],\n [\n -106.38971328735352,\n 35.881122573005875\n ],\n [\n -106.38971328735352,\n 35.858309181565716\n ],\n [\n -106.42507553100586,\n 35.858309181565716\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"362","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"573ee3afe4b04a3a6a24acf8","contributors":{"authors":[{"text":"Smith, David Solance","contributorId":169498,"corporation":false,"usgs":false,"family":"Smith","given":"David","email":"","middleInitial":"Solance","affiliations":[{"id":25534,"text":"Dept. of Biological Sciences, Northern Arizona Univ, PO Box 15018, Flagstaff AZ 86011; current address: Denison Univ, Dept of Biology, PO Box 810, Granville, OH 43023. 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The study involves collaboration between the U.S. Army Corps of Engineers, the U.S. Geological Survey, and the U.S. Fish and Wildlife Service. ECALS addresses three major Action Items from the Asian Carp Regional Coordinating Committee (ACRCC) Asian Carp Control Strategy Framework, of which results to date are presented below. Initial ECALS efforts focused on eDNA vectors whereas marker development and calibration experiments received greater attention in 2013.","language":"English","publisher":"U.S. Fish and Wildlife Service & Asian Carp Regional Coordinating Committee","collaboration":"U.S. Army Corps of Engineers; U.S. Fish and Wildlife Service","usgsCitation":"Baerwaldt, K., Bartron, M.L., Schilling, K., Lee, D., Russo, E., Estes, T., Fischer, R., Fleming, B., Guilfoyle, M.P., Killgore, J., Lance, R., Perkins, E., Schultz, M., Smith, D., Amberg, J.J., Chapman, D., Gaikowski, M.P., Klymus, K.E., and Richter, C.A., 2015, Environmental DNA calibration study interim technical review report December 2014, Report: ix, ES1-3, 189 p.; Appendixes A-B.","productDescription":"Report: ix, ES1-3, 189 p.; Appendixes A-B","ipdsId":"IP-057663","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences 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management effectiveness and cost","interactions":[],"lastModifiedDate":"2017-11-29T13:52:49","indexId":"70192950","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Developing a conservation strategy to maximize persistence of an endangered freshwater mussel species while considering management effectiveness and cost","docAbstract":"We used a structured decision-making process to develop conservation strategies to increase persistence of Dwarf Wedgemussel (Alasmidonta heterodon) in North Carolina, USA, while accounting for uncertainty in management effectiveness and considering costs. Alternative conservation strategies were portfolios of management actions that differed by location of management actions on the landscape. Objectives of the conservation strategy were to maximize species persistence, maintain genetic diversity, maximize public support, and minimize management costs. We compared 4 conservation strategies: 1) the ‘status quo’ strategy represented current management, 2) the ‘protect the best’ strategy focused on protecting the best populations in the Tar River basin, 3) the ‘expand the distribution’ strategy focused on management of extant populations and establishment of new populations in the Neuse River basin, and 4) the ‘hybrid’ strategy combined elements of each strategy to balance conservation in the Tar and Neuse River basins. A population model informed requirements for population management, and experts projected performance of alternative strategies over a 20-y period. The optimal strategy depended on the relative value placed on competing objectives, which can vary among stakeholders. The protect the best and hybrid strategies were optimal across a wide range of relative values with 2 exceptions: 1) if minimizing management cost was of overriding concern, then status quo was optimal, or 2) if maximizing population persistence in the Neuse River basin was emphasized, then expand the distribution strategy was optimal. The optimal strategy was robust to uncertainty in management effectiveness. Overall, the structured decision process can help identify the most promising strategies for endangered species conservation that maximize conservation benefit given the constraint of limited funding.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/683121","usgsCitation":"Smith, D.R., McRae, S.E., Augspurger, T., Ratcliffe, J.A., Nichols, R.B., Eads, C.B., Savidge, T., and Bogan, A.E., 2015, Developing a conservation strategy to maximize persistence of an endangered freshwater mussel species while considering management effectiveness and cost: Freshwater Science, v. 34, no. 4, p. 1324-1339, https://doi.org/10.1086/683121.","productDescription":"16 p.","startPage":"1324","endPage":"1339","ipdsId":"IP-057103","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":348665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North 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,{"id":70154881,"text":"70154881 - 2015 - Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24","interactions":[],"lastModifiedDate":"2016-08-17T11:33:56","indexId":"70154881","displayToPublicDate":"2015-11-19T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24","docAbstract":"The horseshoe crab fishery on the US Atlantic coast represents a compelling fishery management story for many reasons, including ecological complexity, health and human safety ramifications, and socio-economic conflicts. Knowledge of stock status and assessment and monitoring capabilities for the species have increased greatly in the last 15 years and permitted managers to make more informed harvest recommendations. Incorporating the bioenergetics needs of migratory shorebirds, which feed on horseshoe crab eggs, into the management framework for horseshoe crabs was identified as a goal, particularly in the Delaware Bay region where the birds and horseshoe crabs exhibit an important ecological interaction. In response, significant effort was invested in studying the population dynamics, migration ecology, and the ecologic relationship of a key migratory shorebird, the Red Knot, to horseshoe crabs. A suite of models was developed that linked Red Knot populations to horseshoe crab populations through a mass gain function where female spawning crab abundance determined what proportion of the migrating Red Knot population reached a critical body mass threshold. These models were incorporated in an adaptive management framework wherein optimal harvest decisions for horseshoe crab are recommended based on several resource-based and value-based variables and thresholds. The current adaptive framework represents a true multispecies management effort where additional data over time are employed to improve the predictive models and reduce parametric uncertainty. The possibility of increasing phenologic asynchrony between the two taxa in response to climate change presents a potential challenge to their ecologic interaction in Delaware Bay.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Changing Global Perspectives on Horseshoe Crab Biology, Conservation and Management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Cham","doi":"10.1007/978-3-319-19542-1_24","usgsCitation":"Millard, M.J., Sweka, J.A., McGowan, C., and Smith, D., 2015, Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24, chap. of Changing Global Perspectives on Horseshoe Crab Biology, Conservation and Management, p. 407-431, https://doi.org/10.1007/978-3-319-19542-1_24.","startPage":"407","endPage":"431","numberOfPages":"25","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059817","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":326655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57b58abee4b03bcb0104bb5e","contributors":{"authors":[{"text":"Millard, Michael J.","contributorId":23411,"corporation":false,"usgs":false,"family":"Millard","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":645754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweka, John A.","contributorId":80945,"corporation":false,"usgs":true,"family":"Sweka","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":645755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGowan, Conor P. cmcgowan@usgs.gov","contributorId":145496,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":564308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, David R.","contributorId":173756,"corporation":false,"usgs":false,"family":"Smith","given":"David R.","affiliations":[],"preferred":false,"id":645756,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178511,"text":"70178511 - 2015 - Horseshoe crab spawning activity in Delaware Bay, USA, after harvest reduction: A mixed-model analysis","interactions":[],"lastModifiedDate":"2016-11-22T12:24:38","indexId":"70178511","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Horseshoe crab spawning activity in Delaware Bay, USA, after harvest reduction: A mixed-model analysis","docAbstract":"A Delaware Bay, USA, standardized survey of spawning horseshoe crabs, Limulus polyphemus, was carried out in 1999 − 2013 through a citizen science network. Previous trend analyses of the data were at the state (DE or NJ) or bay-wide levels. Here, an alternative mixed-model regression analysis was used to estimate trends in female and male spawning densities at the beach level (n = 26) with the objective of inferring their causes. For females, there was no overall trend and no single explanation applies to the temporal and spatial patterns in their densities. Individual beaches that initially had higher densities tended to experience a decrease, while beaches that initially had lower densities tended to experience an increase. As a result, densities of spawning females at the end of the study period were relatively similar among beaches, suggesting a redistribution of females among the beaches over the study period. For males, there was a positive overall trend in spawning abundance from 1999 to 2013, and this increase occurred broadly among beaches. Moreover, the beaches with below-average initial male density tended to have the greatest increases. Possible explanations for these patterns include harvest reduction, sampling artifact, habitat change, density-dependent habitat selection, or mate selection. The broad and significant increase in male spawning density, which occurred after enactment of harvest controls, is consistent with the harvest reduction explanation, but there is no single explanation for the temporal or spatial pattern in female densities. These results highlight the continued value of a citizen-science-based spawning survey in understanding horseshoe crab ecology and conservation.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-015-9961-3","usgsCitation":"Smith, D.R., and Robinson, T., 2015, Horseshoe crab spawning activity in Delaware Bay, USA, after harvest reduction: A mixed-model analysis: Estuaries and Coasts, v. 38, no. 6, p. 2345-2354, https://doi.org/10.1007/s12237-015-9961-3.","productDescription":"10 p.","startPage":"2345","endPage":"2354","ipdsId":"IP-057549","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":331187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-27","publicationStatus":"PW","scienceBaseUri":"5835672ce4b0070c0abfb6da","contributors":{"authors":[{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":654198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Timothy J.","contributorId":171636,"corporation":false,"usgs":false,"family":"Robinson","given":"Timothy J.","affiliations":[],"preferred":false,"id":654199,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191255,"text":"70191255 - 2015 - The distribution of selected elements and minerals in soil of the conterminous United States","interactions":[],"lastModifiedDate":"2025-05-14T19:08:03.94424","indexId":"70191255","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"The distribution of selected elements and minerals in soil of the conterminous United States","docAbstract":"In 2007, the U.S. Geological Survey initiated a low-density (1 site per 1600 km2, 4857 sites) geochemical and mineralogical survey of soil of the conterminous United States as part of the North American Soil Geochemical Landscapes Project. Three soil samples were collected, if possible, from each site; (1) a sample from a depth of 0 to 5 cm, (2) a composite of the soil A-horizon, and (3) a deeper sample from the soil C-horizon or, if the top of the C-horizon was at a depth greater than 100 cm, from a depth of approximately 80–100 cm. The < 2 mm fraction of each sample was analysed for a suite of 45 major and trace elements following near-total multi-acid digestion. The major mineralogical components in samples from the soil A- and C-horizons were determined by a quantitative X-ray diffraction method using Rietveld refinement. Sampling ended in 2010 and chemical and mineralogical analyses were completed in May 2013. Maps of the conterminous United States showing predicted element and mineral concentrations were interpolated from actual soil data for each soil sample type by an inverse distance weighted (IDW) technique using ArcGIS software. Regional- and national-scale map patterns for selected elements and minerals apparent in interpolated maps are described here in the context of soil-forming factors and possible human inputs. These patterns can be related to (1) soil parent materials, for example, in the distribution of quartz, (2) climate impacts, for example, in the distribution of feldspar and kaolinite, (3) soil age, for example, in the distribution of carbonate in young glacial deposits, and (4) possible anthropogenic loading of phosphorus (P) and lead (Pb) to surface soil. This new geochemical and mineralogical data set for the conterminous United States represents a major step forward from prior national-scale soil geochemistry data and provides a robust soil data framework for the United States now and into the future.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2015.01.006","usgsCitation":"Woodruff, L.G., Cannon, W.F., Smith, D.B., and Solano, F., 2015, The distribution of selected elements and minerals in soil of the conterminous United States: Journal of Geochemical Exploration, v. 154, p. 49-60, https://doi.org/10.1016/j.gexplo.2015.01.006.","productDescription":"12 p.","startPage":"49","endPage":"60","ipdsId":"IP-054587","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":346320,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"154","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d35029e4b05fe04cc34d6b","contributors":{"authors":[{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cannon, William F. 0000-0002-2699-8118 wcannon@usgs.gov","orcid":"https://orcid.org/0000-0002-2699-8118","contributorId":1883,"corporation":false,"usgs":true,"family":"Cannon","given":"William","email":"wcannon@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David B. 0000-0001-8396-9105 dsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8396-9105","contributorId":138565,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"dsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711699,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solano, Federico 0000-0002-0308-5850 fsolanoc@usgs.gov","orcid":"https://orcid.org/0000-0002-0308-5850","contributorId":4302,"corporation":false,"usgs":true,"family":"Solano","given":"Federico","email":"fsolanoc@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711700,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70150336,"text":"70150336 - 2015 - Developing objectives with multiple stakeholders: adaptive management of horseshoe crabs and Red Knots in the Delaware Bay","interactions":[],"lastModifiedDate":"2015-06-29T11:59:51","indexId":"70150336","displayToPublicDate":"2015-04-01T13:00:00","publicationYear":"2015","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":"Developing objectives with multiple stakeholders: adaptive management of horseshoe crabs and Red Knots in the Delaware Bay","docAbstract":"Structured decision making (SDM) is an increasingly utilized approach and set of tools for addressing complex decisions in environmental management. SDM is a value-focused thinking approach that places paramount importance on first establishing clear management objectives that reflect core values of stakeholders. To be useful for management, objectives must be transparently stated in unambiguous and measurable terms. We used these concepts to develop consensus objectives for the multiple stakeholders of horseshoe crab harvest in Delaware Bay. Participating stakeholders first agreed on a qualitative statement of fundamental objectives, and then worked to convert those objectives to specific and measurable quantities, so that management decisions could be assessed. We used a constraint-based approach where the conservation objectives for Red Knots, a species of migratory shorebird that relies on horseshoe crab eggs as a food resource during migration, constrained the utility of crab harvest. Developing utility functions to effectively reflect the management objectives allowed us to incorporate stakeholder risk aversion even though different stakeholder groups were averse to different or competing risks. While measurable objectives and quantitative utility functions seem scientific, developing these objectives was fundamentally driven by the values of the participating stakeholders.
","language":"English","publisher":"Springer-Verlag","publisherLocation":"New York, NY","doi":"10.1007/s00267-014-0422-8","usgsCitation":"McGowan, C., Lyons, J., and Smith, D., 2015, Developing objectives with multiple stakeholders: adaptive management of horseshoe crabs and Red Knots in the Delaware Bay: Environmental Management, v. 55, no. 4, p. 972-982, https://doi.org/10.1007/s00267-014-0422-8.","productDescription":"11 p.","startPage":"972","endPage":"982","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052744","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-24","publicationStatus":"PW","scienceBaseUri":"55926c95e4b0b6d21dd6775f","contributors":{"authors":[{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":556713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E.","contributorId":35461,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[],"preferred":false,"id":563937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David 0000-0001-6074-9257","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":1989,"corporation":false,"usgs":false,"family":"Smith","given":"David","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":563938,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70180672,"text":"70180672 - 2015 - Implementation of a framework for multi-species, multi-objective adaptive management in Delaware Bay","interactions":[],"lastModifiedDate":"2017-04-25T16:41:20","indexId":"70180672","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Implementation of a framework for multi-species, multi-objective adaptive management in Delaware Bay","docAbstract":"Decision analytic approaches have been widely recommended as well suited to solving disputed and ecologically complex natural resource management problems with multiple objectives and high uncertainty. However, the difference between theory and practice is substantial, as there are very few actual resource management programs that represent formal applications of decision analysis. We applied the process of structured decision making to Atlantic horseshoe crab harvest decisions in the Delaware Bay region to develop a multispecies adaptive management (AM) plan, which is currently being implemented. Horseshoe crab harvest has been a controversial management issue since the late 1990s. A largely unregulated horseshoe crab harvest caused a decline in crab spawning abundance. That decline coincided with a major decline in migratory shorebird populations that consume horseshoe crab eggs on the sandy beaches of Delaware Bay during spring migration. Our approach incorporated multiple stakeholders, including fishery and shorebird conservation advocates, to account for diverse management objectives and varied opinions on ecosystem function. Through consensus building, we devised an objective statement and quantitative objective function to evaluate alternative crab harvest policies. We developed a set of competing ecological models accounting for the leading hypotheses on the interaction between shorebirds and horseshoe crabs. The models were initially weighted based on stakeholder confidence in these hypotheses, but weights will be adjusted based on monitoring and Bayesian model weight updating. These models were used together to predict the effects of management actions on the crab and shorebird populations. Finally, we used a dynamic optimization routine to identify the state dependent optimal harvest policy for horseshoe crabs, given the possible actions, the stated objectives and our competing hypotheses about system function. The AM plan was reviewed, accepted and implemented by the Atlantic States Marine Fisheries Commission in 2012 and 2013. While disagreements among stakeholders persist, structured decision making enabled unprecedented progress towards a transparent and consensus driven management plan for crabs and shorebirds in Delaware Bay.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2015.08.038","usgsCitation":"McGowan, C., Smith, D., Nichols, J., Lyons, J.E., Sweka, J.A., Kalasz, K., Niles, L.J., Wong, R., Brust, J., Davis, M.C., and Spear, B., 2015, Implementation of a framework for multi-species, multi-objective adaptive management in Delaware Bay: Biological Conservation, v. 191, p. 759-769, https://doi.org/10.1016/j.biocon.2015.08.038.","productDescription":"11 p.","startPage":"759","endPage":"769","ipdsId":"IP-028202","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":334459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"191","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5891b0a9e4b072a7ac1298f3","contributors":{"authors":[{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":661944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David R.","contributorId":173756,"corporation":false,"usgs":false,"family":"Smith","given":"David R.","affiliations":[],"preferred":false,"id":661945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nichols, James D. jnichols@usgs.gov","contributorId":139087,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":661946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, James E. 0000-0002-9810-8751 jelyons@usgs.gov","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":177546,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"jelyons@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":661947,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sweka, John A.","contributorId":80945,"corporation":false,"usgs":true,"family":"Sweka","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":661948,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kalasz, Kevin","contributorId":7121,"corporation":false,"usgs":true,"family":"Kalasz","given":"Kevin","affiliations":[],"preferred":false,"id":661949,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Niles, Lawrence J.","contributorId":25289,"corporation":false,"usgs":true,"family":"Niles","given":"Lawrence","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":661950,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wong, Richard","contributorId":54840,"corporation":false,"usgs":true,"family":"Wong","given":"Richard","affiliations":[],"preferred":false,"id":661951,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Brust, Jeffrey","contributorId":35167,"corporation":false,"usgs":true,"family":"Brust","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":661952,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Davis, Michelle C. mcdavis@usgs.gov","contributorId":5865,"corporation":false,"usgs":true,"family":"Davis","given":"Michelle","email":"mcdavis@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":661953,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Spear, Braddock","contributorId":47220,"corporation":false,"usgs":true,"family":"Spear","given":"Braddock","email":"","affiliations":[],"preferred":false,"id":661954,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70127469,"text":"70127469 - 2015 - Threshold-dependent sample sizes for selenium assessment with stream fish tissue","interactions":[],"lastModifiedDate":"2016-12-14T11:58:43","indexId":"70127469","displayToPublicDate":"2014-09-30T09:44:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Threshold-dependent sample sizes for selenium assessment with stream fish tissue","docAbstract":"Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α = 0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased precision of composites for estimating mean conditions. However, low sample sizes (<5 fish) did not achieve 80% power to detect near-threshold values (i.e., <1 mg Se/kg) under any scenario we evaluated. This analysis can assist the sampling design and interpretation of Se assessments from fish tissue by accounting for natural variation in stream fish populations.
","language":"English","publisher":"SETAC","publisherLocation":"Pensacola, FL","doi":"10.1002/ieam.1579","usgsCitation":"Hitt, N.P., and Smith, D., 2015, Threshold-dependent sample sizes for selenium assessment with stream fish tissue: Integrated Environmental Assessment and Management, v. 11, no. 1, p. 143-149, https://doi.org/10.1002/ieam.1579.","productDescription":"7 p.","startPage":"143","endPage":"149","ipdsId":"IP-053353","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":472465,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.1579","text":"Publisher Index Page"},{"id":294605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294604,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ieam.1579"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-09-01","publicationStatus":"PW","scienceBaseUri":"542bb80ee4b0abfb4c8096b3","contributors":{"authors":[{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":502326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David R.","contributorId":173756,"corporation":false,"usgs":false,"family":"Smith","given":"David R.","affiliations":[],"preferred":false,"id":502325,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70037889,"text":"70037889 - 2014 - Environmental DNA calibration study. Interim technical review report","interactions":[],"lastModifiedDate":"2015-10-30T14:12:53","indexId":"70037889","displayToPublicDate":"2014-12-01T15:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Environmental DNA calibration study. Interim technical review report","docAbstract":"Invasive aquatic nuisance species pose a major threat to aquatic ecosystems worldwide. Invasive Asian carps, including bighead carp (Hypophthalmichthys nobilis) and silver carp (H. molitrix) have been steadily dispersing upstream through the Mississippi, Illinois, and Des Plaines Rivers since the 1990s. To prevent further movement up the Illinois River into the Chicago Area Waterway System (CAWS, see Figures 1.1.1 to 1.1.3) and possibly Lake Michigan and the Great Lakes ecosystem, an electrical barrier has been operating near Lockport to deter the advance of Asian carp. Although one adult individual has been detected in Lockport pool of the Illinois Waterway, the leading edge of the invasion of bighead and silver carp is considered to be at RM 281.5 in Dresden Island Pool, 15 miles downstream from the barrier and 55 miles from Lake Michigan, and that front has not progressed upstream since 2006. Although spawning activity has been observed in Marseilles pool in 2012, verified capture of eggs and larvae remain downstream in Peoria pool, over 140 miles from Lake Michigan (Figure 1.1.1).
\nShould a sustainable Asian carp population become established in the Great Lakes, native fish populations, as well as many threatened or endangered plant/animal species populations, could be impacted. In response to this threat, the Asian Carp Regional Control Committee (ACRCC) was formed in part to coordinate efforts to understand and organize against the Asian carp threat. The Asian Carp Control Strategy Framework (2012a) outlined major tasks to be completed for a better understanding of factors related to the advance of Asian carp populations towards the Great Lakes. In addition, the ACRCC formed the Monitoring and Rapid Response Workgroup to address Asian carp monitoring and removal (ACRCC 2012b).
","publisherLocation":"Reston, VA","usgsCitation":"Baerwaldt, K., Bartron, M.L., Schilling, K., Lee, D., Russo, E., Estes, T., Fischer, R., Fleming, B., Guilfoyle, M.P., Kilgore, K.J., Lance, R., Perkins, E., Schultz, M., Smith, D., Amberg, J., Chapman, D., Gaikowski, M.P., Klymus, K.E., and Richter, C.A., 2014, Environmental DNA calibration study. 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Although energy exploration and development have been taking place in the region since the late 1800s, the pace of development for fossil fuels and renewable energy increased significantly in the early 2000s. This and the associated urban and exurban development are leading to landscape-level environmental and socioeconomic changes that have the potential to diminish wildlife habitat and other natural resources, and the quality of human lives, in Southwest Wyoming. The potential for negative effects of these changes prompted Federal, State, and local agencies to undertake the Wyoming Landscape Conservation Initiative for Southwest Wyoming.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141093","usgsCitation":"Bowen, Z.H., Aldridge, C.L., Anderson, P.J., Assal, T.J., Bern, C., Biewick, L., Boughton, G.K., Carr, N.B., Chalfoun, A., Chong, G.W., Clark, M.L., Fedy, B.C., Foster, K., Garman, S.L., Germaine, S., Hethcoat, M.G., Homer, C.G., Kauffman, M., Keinath, D., Latysh, N., Manier, D.J., McDougal, R., Melcher, C.P., Miller, K.A., Montag, J., Potter, C.J., Schell, S., Shafer, S., Smith, D., Sweat, M.J., and Wilson, A.B., 2014, U.S. Geological Survey Science for the Wyoming Landscape Conservation Initiative: 2012 annual report: U.S. Geological Survey Open-File Report 2014-1093, viii, 71 p., https://doi.org/10.3133/ofr20141093.","productDescription":"viii, 71 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