High-resolution light detection and ranging (lidar) data are used in energy infrastructure siting, design, permitting, construction, and monitoring to promote public safety through the reduction of risks. For example, lidar data are used to identify safe locations for energy infrastructure by analyzing terrain parameters and identifying and evaluating geologic hazards (for example, landslide and fault locations) and their potential public safety effects on the location or design of infrastructure. Increasingly, engineering companies and regulatory agencies are using lidar and other remote sensing techniques as an efficient method to collect accurate, comprehensive data while reducing risks to field personnel.
The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) is collecting lidar data nationwide (interferometric synthetic aperture radar [IfSAR] data in Alaska) to support a wide range of applications, including projects related to energy infrastructure construction and safety. Renewable energy resources, resource mining, and oil and gas resources were identified by the National Enhanced Elevation Assessment as business uses requiring three-dimensional (3D) elevation data.
Elevation data are critical in assessing potential sites for energy infrastructure, such as pipelines, refineries and other facilities, to mitigate risks from natural hazards. For example, the Federal Energy Regulatory Commission (FERC), an independent agency that regulates the interstate transmission of electricity, natural gas, and oil, uses enhanced elevation data to conduct National Environmental Policy Act (NEPA) compliance assessments. The acquisition of high-resolution lidar data by the USGS 3DEP initiative helps the FERC and NEPA permit applicants by providing accurate and consistent data for hazards analysis. The use of these data accelerates the application and review process and avoids the much higher costs of acquiring elevation data along proposed energy facility locations and pipeline corridors.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193051","usgsCitation":"Thatcher, C.A., Lukas, Vicki, and Stoker, J.M., 2020, The 3D Elevation Program and energy for the Nation: U.S. Geological Survey Fact Sheet 2019–3051, 2 p., https://doi.org/10.3133/fs20193051.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-107266","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":372745,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3051/coverthb.jpg"},{"id":372746,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3051/fs20193051.pdf","text":"Report","size":"566 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3051"}],"contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 511
Reston, VA 20192
Dauphin Island, Alabama, located in the Northern Gulf of Mexico just outside of Mobile Bay, is Alabama’s only barrier island and provides an array of historical, natural, and economic resources. The dynamic island shoreline of Dauphin Island evolved across time scales while constantly acted upon by waves and currents during both storms and calm periods. Reductions in the vulnerability and enhancements to the resiliency of Dauphin Island—through offshore sand placement, breach closure, berm construction, and other means—have been used to protect the island and its vital resources. Planning for a resilient Dauphin Island requires predicting the long-term evolution of the barrier island system and the dominant, temporally varying processes that influence it, including littoral alongshore sediment transport under typical wave conditions, beach and dune erosion, the island overwash and breaching that occur rapidly during storm events, and the recovery of primary sand dunes through Aeolian transport over decadal time scales. Littoral sediment transport within the Dauphin Island decadal-scale framework was simulated using the Delft-3D modeling software suite. The influences of wind, waves, water levels, and sediment transport are incorporated into the model. Model skill in the prediction of waves, water levels, currents, volumetric flow rates through inlets, and shoreline position was assessed by using a set of deterministic and statistical hindcast simulations. The Delft-3D modeling application described here can be coupled with validated models of storm-response and dune recovery to predict the evolution of Dauphin Island on decadal time scales.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201011","usgsCitation":"Jenkins, R.L., III, Long, J.W., Dalyander, P.S., Thompson, D.M., and Mickey, R.C., 2020, Development of a process-based littoral sediment transport model for Dauphin Island, Alabama: U.S. Geological Survey Open-File Report 2020–1011, 43 p., https://doi.org/10.3133/ofr20201011.","productDescription":"vii, 43 p.","numberOfPages":"51","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-109477","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":399455,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109731.htm"},{"id":372743,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1011/ofr20201011.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1011"},{"id":372742,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1011/coverthb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.36715698242186,\n 30.210421455819937\n ],\n [\n -88.06640625,\n 30.210421455819937\n ],\n [\n -88.06640625,\n 30.26974231529823\n ],\n [\n -88.36715698242186,\n 30.26974231529823\n ],\n [\n -88.36715698242186,\n 30.210421455819937\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
A study was conducted by the U.S. Geological Survey (USGS) in cooperation with the Washington, D.C., Department of Energy & Environment to estimate the loads of suspended-sediment-bound chemical compounds in five gaged tributaries and four ungaged tributaries of the Anacostia River (known locally as “Lower Anacostia River”) in Washington, D.C. Tributaries whose discharge is measured by the USGS are the Northeast and Northwest Branches of the Anacostia River, referred to in this report as “Northeast Branch” (NEB) and “Northwest Branch” (NWB), respectively; Watts Branch (WB); and Hickey Run (HR). A USGS streamflow-gaging station was established in 2016 on Beaverdam Creek (known locally as “Lower Beaverdam Creek” [LBDC]) to support this study. The ungaged streams studied include Nash Run; Pope Branch; an unnamed stream at Fort DuPont, referred to in this report as “Fort DuPont Creek”; and an unnamed stream at Fort Stanton, referred to in this report as “Fort Stanton Creek.” The gaged streams were sampled during four to five storms and two low-flow events during January, March, May, and July 2017. The ungaged streams were sampled during one storm and one low-flow event during July 2017. Storm sampling involved collecting large-volume (60- to 70-liter) composite samples, then removing sediment by filtration in the laboratory. Low-flow samples were obtained by filtering streamwater directly in the field. Continuously recording data sondes were deployed throughout the study to measure turbidity and other water-quality characteristics. During sampling, multiple discrete samples of streamwater were collected to determine suspended-sediment concentration (SSC) and particulate organic carbon (POC) concentration. Shortly after each storm, bed sediment was collected for chemical analysis.
Sediment samples were analyzed for 209 polychlorinated biphenyl (PCB) congeners; 35 polyaromatic hydrocarbon (PAH) compounds, including 20 nonalkylated and 15 alkylated species; and 20 organochlorine pesticide (OP) compounds. Sediment from one storm was analyzed for 23 metals.
Relations were developed among turbidity, discharge, and measured SSC by using multiple linear regression of log-transformed data. These relations were used to estimate SSC from continuous records of discharge and turbidity and were subsequently used to estimate sediment loads for the 2017 calendar year. USGS continuous records of turbidity in NEB, NWB, Watts Branch, and Hickey Run were available for 2013–17, which allowed sediment loads to be calculated for these years. Sediment loads for the ungaged streams were estimated by using loads measured in Watts Branch adjusted on the basis of stream-basin areas.
Sediment loads for 2017 total 3.10×107 kilograms (kg), with 1.02×107 kg (33 percent of total) from the NEB, 1.55×107 kg (50 percent) from the NWB, 4.45×106 kg (14 percent) from LBDC, 5.62×105 kg (2 percent) from Watts Branch, and 2.82×105 kg (1 percent) from Hickey Run. Sediment yields were highest from NWB and LBDC (3.13×105 kilograms per year per square mile [kg/yr/mi2] and 3.01 kg/yr/mi2, respectively). As a result of gaps in turbidity and discharge data, the load for LBDC reported here was calculated from measurements representing only 88 percent of the year (2017), and thus underestimates the actual load. All other gaged tributaries had datasets covering 100 percent of the year and are considered to fully represent actual loads. Estimated sediment loads for the ungaged streams during 2017 total 3.5×105 kg, with 1.2×105 kg from Nash Run, 6.2×104 kg from Pope Branch, 1.1×105 kg from Fort DuPont Creek, and 5.6×104 kg from Fort Stanton Creek.
Concentrations of PCBs, PAHs, and chlorinated pesticides in streamwater are presented for stormflow and low-flow conditions. Average concentrations (in stormflow and low-flow samples) of total PCBs (sum of all congeners, including coelutions) are 5.9 micrograms per kilogram (µg/kg) for NEB, 6.6 µg/kg for NWB, 130 µg/kg for LBDC, 34 µg/kg for Watts Branch, and 69 µg/kg for Hickey Run. Average concentrations of total PAHs (tPAH) (total of nonalkylated and alkylated species) are 2,000 µg/kg for NEB, 3,300 µg/kg for NWB, 2,200 µg/kg for LBDC, 2,400 µg/kg for Watts Branch, and 18,000 µg/kg for Hickey Run. tPAH concentrations among the ungaged streams were highest in Nash Run (5,500 µg/kg); concentrations in the other ungaged streams were less than (<) 700 µg/kg.
The general magnitude of tPCB and tPAH concentrations in streamwater samples was low-flow samples greater than (>) stormflow samples greater than or equal to (≥) bed-sediment samples. PCB congener profiles in the three types of samples were nearly identical in each stream and were similar in all streams except for LBDC, where the dominant PCBs shifted to the lighter di- through tetra- homologs. LBDC showed higher tPCB concentrations and a distinct congener profile from the other streams. The similarity in congener makeup supported that averaging PCB concentrations in stormflow and low-flow samples was appropriate for calculating chemical loads.
Loads of tPCB, tPAH (total of alkylated and nonalkylated forms), and pesticides were estimated for each stream by multiplying average contaminant concentrations by the respective sediment loads. Total PCB loads for 2017 were estimated to be 820 grams (g) with 8 percent (60 g) from NEB, 12 percent (95 g) from NWB, 75 percent (590 g) from LBDC, 3 percent (25 g) from Watts Branch, and 2.5 percent (19 g) from Hickey Run. PCB toxicity totaled 3.8×10−3 µg/kg, with the largest contribution (47 percent) derived from LBDC. Total PAH loads (sum of alkylated and nonalkylated forms) for 2017 were estimated to be 89,000 g, with 23 percent (20,000 g) from NEB, 59 percent (52,000 g) from NWB, 11 percent (9,800 g) from LBDC, 2 percent (1,400 g) from Watts Branch, and 6 percent (5,200 g) from Hickey Run. These results indicate that the largest contributor (75 percent) of PCBs to the Anacostia River is LBDC, although it contributes only 15 percent of the sediment and its basin area represents only 10 percent of the area of the Anacostia River watershed. The majority of the PAH load originates from NWB (59 percent of total) and NEB (22 percent). The ungaged tributaries contribute extremely small loads of PCBs and PAHs, totaling 8.1 g and 765 kg, respectively. More than 94 percent of the total load from the ungaged tributaries is derived from the Nash Run Basin.
Various organochlorine pesticides were present in suspended and bed sediment from all gaged and ungaged tributaries; however, elevated detection levels associated with the analytical methods resulted in numerous unquantifiable concentrations in the suspended-sediment samples. Only the pesticide chlordane was found in measurable concentrations in all gaged tributaries. As a result, in this report, a combination of analytical data from suspended-sediment and bed-sediment samples was used to estimate the maximum pesticide loading for each tributary. Chlordane was the principal compound present in the gaged tributaries; the highest average concentration (average of stormflow and low-flow samples from each stream) was 62 µg/kg in sediment from Watts Branch. Chlordane loads for 2017 totaled 1,100 g, of which 7 percent (430 g) was from NEB, 28 percent (320 g) was from NWB, 28 percent (310 g) was from LBDC, 5 percent (56 g) was from Watts Branch, and 1 percent (11 g) was from Hickey Run. Chlordane was not present in suspended or bed sediment from any of the ungaged tributaries. Loads of the other pesticides were estimated by using the highest concentration measured in the combined suspended-sediment and bed-sediment data for each stream. Notable loads include dieldrin (860 g from NWB), methoxychlor (205 g from LBDC), endrin aldehyde (150 g from NWB), and 4,4-DDT (79 g from Watts Branch). Compared with pesticide loads from the gaged streams, those from the ungaged streams were minimal, with only the Pope Branch contribution exceeding 1 gram per year for 4,4-DDE (1.05 g) and 4,4’-DDT (1.3 g).
The results of this study show that the dominant source of PCBs and chlordane is LBDC, despite its relatively small basin area. PAHs are ubiquitous throughout the study area, with the largest sources being NEB and NWB; this finding is a result of the large sediment load originating from these basins. The small, ungaged streams supply only minimal PCB and PAH loads, with Nash Run being the largest contributor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195092","collaboration":"Prepared in cooperation with the Washington, D.C., Department of Energy & Environment","usgsCitation":"Wilson, T.P., 2019, Sediment and chemical contaminant loads in tributaries to the Anacostia River, Washington, District of Columbia, 2016–17: U.S. Geological Survey Scientific Investigations Report 2019–5092, 146 p., https://doi.org/10.3133/sir20195092.","productDescription":"Report: x, 146 p.; Data Release","numberOfPages":"160","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-099743","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":399540,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109730.htm"},{"id":372690,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RUZSMV","text":"USGS data release","linkHelpText":"Discharge and sediment data for selected tributaries to the Anacostia River, Washington, District of Columbia, 2003–18"},{"id":372692,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5092/sir20195092.pdf","text":"Report","size":"5.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5092"},{"id":372691,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5092/coverthb.jpg"}],"country":"United States","state":"District of Columbia","county":"Washington","otherGeospatial":"Anacostia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.0797,\n 38.8447\n ],\n [\n -76.7689,\n 38.8447\n ],\n [\n -76.7689,\n 39.1611\n ],\n [\n -77.0797,\n 39.1611\n ],\n [\n -77.0797,\n 38.8447\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
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A fully worked example of decision-support-scale uncertainty quantification (UQ) and parameter estimation (PE) is presented. The analyses are implemented for an existing groundwater flow model of the Edwards aquifer, Texas, USA, and are completed in a script-based workflow that strives to be transparent and reproducible. High-dimensional PE is used to history-match simulated outputs to corresponding state observations of spring flow and groundwater level. Then a hindcast of a historical drought is made. Using available state observations recorded during drought conditions, the combined UQ and PE analyses are shown to yield an ensemble of model results that bracket the observed hydrologic responses. All files and scripts used for the analyses are placed in the public domain to serve as a template for other practitioners who are interested in undertaking these types of analyses.
","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2020.00050","usgsCitation":"White, J.T., Foster, L.K., Fienen, M., Knowling, M.J., Hemmings, B., and Winterle, J.R., 2020, Towards reproducible environmental modeling for decision support: A worked example: Frontiers in Earth Science, Hydrosphere, v. 28, 50, 11 p., https://doi.org/10.3389/feart.2020.00050.","productDescription":"50, 11 p.","ipdsId":"IP-115342","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":457567,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2020.00050","text":"Publisher Index Page"},{"id":437084,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AUZMI7","text":"USGS data release","linkHelpText":"Towards reproducible environmental modeling for decision support: a worked example"},{"id":386114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"southern-central Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.96435546875,\n 28.76765910569123\n ],\n [\n -96.83349609375,\n 28.76765910569123\n ],\n [\n -96.83349609375,\n 30.14512718337613\n ],\n [\n -100.96435546875,\n 30.14512718337613\n ],\n [\n -100.96435546875,\n 28.76765910569123\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationDate":"2020-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, Linzy K. 0000-0002-7373-7017","orcid":"https://orcid.org/0000-0002-7373-7017","contributorId":259186,"corporation":false,"usgs":true,"family":"Foster","given":"Linzy","email":"","middleInitial":"K.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knowling, Matthew J.","contributorId":251909,"corporation":false,"usgs":false,"family":"Knowling","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":816775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hemmings, Brioch","contributorId":259187,"corporation":false,"usgs":false,"family":"Hemmings","given":"Brioch","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":816776,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Winterle, James R.","contributorId":259189,"corporation":false,"usgs":false,"family":"Winterle","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":52328,"text":"Edwards Aquifer Authority","active":true,"usgs":false}],"preferred":false,"id":816777,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208796,"text":"70208796 - 2020 - Spatial epidemiological patterns suggest mechanisms of land-sea transmission for Sarcocystis neurona in a coastal marine mammal","interactions":[],"lastModifiedDate":"2020-03-02T06:48:31","indexId":"70208796","displayToPublicDate":"2020-02-28T06:45:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Spatial epidemiological patterns suggest mechanisms of land-sea transmission for Sarcocystis neurona in a coastal marine mammal","docAbstract":"Sarcocystis neurona was recognised as an important cause of mortality in southern sea otters (Enhydra lutris nereis) after an outbreak in April 2004 and has since been detected in many marine mammal species in the Northeast Pacific Ocean. Risk of S. neurona exposure in sea otters is associated with consumption of clams and soft-sediment prey and is temporally associated with runoff events. We examined the spatial distribution of S. neurona exposure risk based on serum antibody testing and assessed risk factors for exposure in animals from California, Washington, British Columbia and Alaska. Significant spatial clustering of seropositive animals was observed in California and Washington, compared with British Columbia and Alaska. Adult males were at greatest risk for exposure to S. neurona, and there were strong associations with terrestrial features (wetlands, cropland, high human housing-unit density). In California, habitats containing soft sediment exhibited greater risk than hard substrate or kelp beds. Consuming a diet rich in clams was also associated with increased exposure risk. These findings suggest a transmission pathway analogous to that described for Toxoplasma gondii, with infectious stages traveling in freshwater runoff and being concentrated in particular locations by marine habitat features, ocean physical processes, and invertebrate bioconcentration.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-020-60254-5","usgsCitation":"Burgess, T., Tinker, M., Miller, M.A., Smith, W.A., Bodkin, J.L., Murray, M.J., Nichol, L.M., Saarinen, J.A., Larson, S.E., Tomoleoni, J.A., Conrad, P.A., and Johnson, C., 2020, Spatial epidemiological patterns suggest mechanisms of land-sea transmission for Sarcocystis neurona in a coastal marine mammal: Scientific Reports, v. 10, 3683, 9 p., https://doi.org/10.1038/s41598-020-60254-5.","productDescription":"3683, 9 p.","ipdsId":"IP-114629","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":457569,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-60254-5","text":"Publisher Index Page"},{"id":372757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","state":"California, Washington, British Columbia, Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.71874999999999,\n 33.578014746143985\n ],\n [\n -121.9921875,\n 39.639537564366684\n ],\n [\n -122.6953125,\n 47.15984001304432\n ],\n [\n -122.6953125,\n 48.45835188280866\n ],\n [\n -127.265625,\n 54.57206165565852\n ],\n [\n -135.703125,\n 60.58696734225869\n ],\n [\n -143.7890625,\n 62.67414334669093\n ],\n [\n -152.2265625,\n 62.59334083012024\n ],\n [\n -156.97265625,\n 58.99531118795094\n ],\n [\n -160.48828125,\n 55.57834467218206\n ],\n [\n -158.37890625,\n 54.87660665410869\n ],\n [\n -145.01953124999997,\n 59.17592824927136\n ],\n [\n -142.20703125,\n 55.87531083569679\n ],\n [\n -138.33984375,\n 48.10743118848039\n ],\n [\n -128.671875,\n 38.54816542304656\n ],\n [\n -117.94921874999999,\n 31.952162238024975\n ],\n [\n -116.71874999999999,\n 33.578014746143985\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Burgess, Tristan","contributorId":214303,"corporation":false,"usgs":false,"family":"Burgess","given":"Tristan","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":783410,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. 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David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":936775,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70208828,"text":"70208828 - 2020 - Egg counts of Southern Leopard Frog, Lithobates sphenocephalus, egg masses from southern Louisiana, USA","interactions":[],"lastModifiedDate":"2020-03-03T09:00:25","indexId":"70208828","displayToPublicDate":"2020-02-27T08:58:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1899,"text":"Herpetology Notes","active":true,"publicationSubtype":{"id":10}},"title":"Egg counts of Southern Leopard Frog, Lithobates sphenocephalus, egg masses from southern Louisiana, USA","docAbstract":"Southern Leopard Frogs, Lithobates sphenocephalus (Cope, 1889), lay eggs year-round in their southern range, including Louisiana, but their peak breeding season is the cooler months from late fall through early spring (Mount, 1975; Caldwell, 1986; Dundee and Rossman, 1989). Double-enveloped eggs in globular masses are typically deposited in shallow water, but deeper waters are used when temperatures are warmer (Dodd, 2013). Egg masses are often attached to vegetation when present but may also lie free on the substrate (Dundee and Rossman, 1989; Dodd, 2013). Egg masses may be deposited singly, but are often found communally, with hundreds of egg masses in a small area (Dundee and Rossman, 1989; Trauth, 1989). Communal laying in Southern Leopard Frogs may be an adaptative response to cold temperatures (Caldwell, 1986), as has been noted in congeners (Waldman and Ryan, 1983).","language":"English","publisher":"Societas Europaea Herpetologica","usgsCitation":"Glorioso, B.M., Muse, L.J., and Waddle, J.H., 2020, Egg counts of Southern Leopard Frog, Lithobates sphenocephalus, egg masses from southern Louisiana, USA: Herpetology Notes, v. 13, p. 187-189.","productDescription":"3 p.","startPage":"187","endPage":"189","ipdsId":"IP-111582","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":372793,"type":{"id":15,"text":"Index Page"},"url":"https://www.biotaxa.org/hn/article/view/57036/60009"},{"id":372837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.71337890625,\n 29.621221113784504\n ],\n [\n -92.6806640625,\n 29.420460341013133\n ],\n [\n -90.615234375,\n 28.786918085420226\n ],\n [\n -88.846435546875,\n 28.748396571187406\n ],\n [\n -88.53881835937499,\n 29.5830116903775\n ],\n [\n -89.09912109375,\n 30.088107753367257\n ],\n [\n -89.571533203125,\n 30.211608223816906\n ],\n [\n -89.84619140625,\n 30.65681556429287\n ],\n [\n -89.725341796875,\n 31.005862904624205\n ],\n [\n -91.64794921875,\n 30.996445897426373\n ],\n [\n -93.58154296875,\n 30.817346256492073\n ],\n [\n -93.80126953124999,\n 30.315987718557867\n ],\n [\n -93.944091796875,\n 29.81205076752506\n ],\n [\n -93.71337890625,\n 29.621221113784504\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glorioso, Brad M. 0000-0002-5400-7414 gloriosob@usgs.gov","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":4241,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","email":"gloriosob@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":783512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muse, Lindy J.","contributorId":172438,"corporation":false,"usgs":false,"family":"Muse","given":"Lindy","email":"","middleInitial":"J.","affiliations":[{"id":27041,"text":"Cherokee at USGS-WARC Lafayette","active":true,"usgs":false}],"preferred":false,"id":783513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waddle, J. 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Estimated ages for samples that contain a mixture of young and old groundwater will be particularly sensitive to model parametrization as relatively small additions of modern 14C from recent recharge can mask the presence and amount of old groundwater. A novel multi-model approach based on inverse geochemical modeling and lumped parameter modeling of age tracers (3H, 3Hetrit, and SF6) was used to better constrain 14C dilution caused by dissolution of carbonates in the unsaturated zone or shallow parts of the Glacial aquifer, which extends over 2000 miles across the northern contiguous United States. Calibration of 14C inverse geochemical models to LPM computed 14C concentrations in modern water indicated that 14C of soil zone and shallow aquifer carbonates were not 14C-dead (0 pmC), as is typically assumed for 14C correction models. 14C of such carbonates was on average about 53 pmC (ranged 0-110 pmC, n = 72). This information was used to correct 14C concentrations for water recharged entirely before 1950 and water that is a mixture of pre- and post-1950 water. The multi-model approach developed here was compared to an analytical 14C-adjustment model (Revised Fontes and Garnier) that assumed solid carbonates were 14C-dead. 14C corrections using the analytical adjustment model tended to over-correct final 14C concentrations by 21 pmC and underestimates mean ages by 40% for groundwater mixtures. In fact, 14C corrections based on analytical model yielded negative ages (14C > 120 pmC) in nearly 36% of mixed samples. This work presents a new approach to constraining 14C corrections and age estimates of mixtures of young and old groundwater. The new method is applied to three well networks distributed across the spatially expansive Glacial aquifer.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.124766","usgsCitation":"Solder, J.E., and Jurgens, B., 2020, Evaluation of soil zone processes and a novel radiocarbon correction approach for groundwater with mixed sources: Journal of Hydrology, v. 588, 124766, 14 p., https://doi.org/10.1016/j.jhydrol.2020.124766.","productDescription":"124766, 14 p.","ipdsId":"IP-098920","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":376259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Glacier aquifer system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.3544921875,\n 49.15296965617039\n ],\n [\n -123.79394531249999,\n 47.517200697839414\n ],\n [\n -122.16796875,\n 46.800059446787316\n ],\n [\n -120.234375,\n 48.019324184801185\n ],\n [\n -114.3896484375,\n 47.249406957888446\n ],\n [\n -108.984375,\n 47.931066347509756\n ],\n [\n -107.75390625,\n 48.268569112964336\n ],\n [\n -105.64453125,\n 48.28319289548347\n ],\n [\n -102.1728515625,\n 46.830133640447386\n ],\n [\n -101.3818359375,\n 43.739352079154706\n ],\n [\n -99.66796875,\n 42.87596410238256\n ],\n [\n -98.5693359375,\n 40.83043687764923\n ],\n [\n -96.9873046875,\n 38.99357205820944\n ],\n [\n -94.76806640625,\n 38.27268853598095\n ],\n [\n -92.2412109375,\n 38.5825261593533\n ],\n [\n -90,\n 38.41055825094609\n ],\n [\n -86.39648437499999,\n 38.65119833229951\n ],\n [\n -82.705078125,\n 39.36827914916011\n ],\n [\n -82.001953125,\n 40.54720023441049\n ],\n [\n -81.07910156249999,\n 41.11246878918086\n ],\n [\n -80.2001953125,\n 41.40977583200954\n ],\n [\n -77.87109375,\n 41.343824581185686\n ],\n [\n -74.7509765625,\n 40.68063802521456\n ],\n [\n -73.5205078125,\n 41.07935114946896\n ],\n [\n -71.1474609375,\n 41.54147766679026\n ],\n [\n -69.9169921875,\n 41.83682786072712\n ],\n [\n -70.9716796875,\n 42.35854391749705\n ],\n [\n -70.8837890625,\n 43.67581809328341\n ],\n [\n -67.03857421875,\n 44.88701247981298\n ],\n [\n -67.82958984375,\n 45.75219336063106\n ],\n [\n -68.4228515625,\n 47.398349200359235\n ],\n [\n -69.4775390625,\n 47.487513008956554\n ],\n [\n -70.9716796875,\n 45.38301927899063\n ],\n [\n -75.322265625,\n 45.10454630976873\n ],\n [\n -76.4208984375,\n 44.18220395771563\n ],\n [\n -76.376953125,\n 43.64402584769947\n ],\n [\n -79.453125,\n 43.389081939117496\n ],\n [\n -79.0576171875,\n 42.84375132629018\n ],\n [\n -83.4521484375,\n 42.00032514831621\n ],\n [\n -82.265625,\n 44.3709869629717\n ],\n [\n -84.6826171875,\n 46.649436163350245\n ],\n [\n -88.1982421875,\n 47.487513008956554\n ],\n [\n -91.9775390625,\n 46.89023157359399\n ],\n [\n -91.318359375,\n 48.166085419012504\n ],\n [\n -94.6142578125,\n 48.777912755501845\n ],\n [\n -95.3173828125,\n 49.468124067331615\n ],\n [\n -95.44921875,\n 49.03786794532641\n ],\n [\n -123.3544921875,\n 49.15296965617039\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"588","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Solder, John E. 0000-0002-0660-3326","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":201953,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203430,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792357,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211043,"text":"70211043 - 2020 - Food and temperature stressors have opposing effects in determining flexible migration decisions in brown trout (Salmo trutta )","interactions":[],"lastModifiedDate":"2020-07-13T13:54:48.113896","indexId":"70211043","displayToPublicDate":"2020-02-27T08:48:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Food and temperature stressors have opposing effects in determining flexible migration decisions in brown trout (Salmo trutta)","title":"Food and temperature stressors have opposing effects in determining flexible migration decisions in brown trout (Salmo trutta )","docAbstract":"With rapid global change, organisms in natural systems are exposed to a multitude of stressors that likely co‐occur, with uncertain impacts. We explored individual and cumulative effects of co‐occurring environmental stressors on the striking, yet poorly understood, phenomenon of facultative migration. We reared offspring of a brown trout population that naturally demonstrates facultative anadromy (sea migration), under different environmental stressor treatments and measured life history responses in terms of migratory tactics and freshwater maturation rates. Juvenile fish were exposed to reduced food availability, temperatures elevated to 1.8°C above natural conditions or both treatments in combination over 18 months of experimental tank rearing. When considered in isolation, reduced food had negative effects on the size, mass and condition of fish across the experiment. We detected variable effects of warm temperatures (negative effects on size and mass, but positive effect on lipids). When combined with food restriction, temperature effects on these traits were less pronounced, implying antagonistic stressor effects on morphological traits. Stressors combined additively, but had opposing effects on life history tactics: migration increased and maturation rates decreased under low food conditions, whereas the opposite occurred in the warm temperature treatment. Not all fish had expressed maturation or migration tactics by the end of the study, and the frequency of these ‘unassigned’ fish was higher in food deprivation treatments, but lower in warm treatments. Fish showing migration tactics were smaller and in poorer condition than fish showing maturation tactics, but were similar in size to unassigned fish. We further detected effects of food restriction on hypo‐osmoregulatory function of migrants that may influence the fitness benefits of the migratory tactic at sea. We also highlight that responses to multiple stressors may vary depending on the response considered. Collectively, our results indicate contrasting effects of environmental stressors on life history trajectories in a facultatively migratory species.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14990","usgsCitation":"Archer, L., Hutton, S.A., Harman, L., McCormick, S.D., O’Grady, M.N., Kerry, J.P., Poole, W., Gargan, P., McGinnity, P., and Reed, T.E., 2020, Food and temperature stressors have opposing effects in determining flexible migration decisions in brown trout (Salmo trutta ): Global Change Biology, v. 26, no. 5, p. 2878-2896, https://doi.org/10.1111/gcb.14990.","productDescription":"19 p.","startPage":"2878","endPage":"2896","ipdsId":"IP-109996","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":457575,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.14990","text":"External Repository"},{"id":376303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Archer, Louise C","contributorId":228950,"corporation":false,"usgs":false,"family":"Archer","given":"Louise C","affiliations":[{"id":41530,"text":"University College Cork","active":true,"usgs":false}],"preferred":false,"id":792577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hutton, Stephen A.","contributorId":228963,"corporation":false,"usgs":false,"family":"Hutton","given":"Stephen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":792578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harman, Luke","contributorId":228952,"corporation":false,"usgs":false,"family":"Harman","given":"Luke","email":"","affiliations":[{"id":41530,"text":"University College Cork","active":true,"usgs":false}],"preferred":false,"id":792579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":792580,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Grady, Michael N","contributorId":228953,"corporation":false,"usgs":false,"family":"O’Grady","given":"Michael","email":"","middleInitial":"N","affiliations":[{"id":41530,"text":"University College Cork","active":true,"usgs":false}],"preferred":false,"id":792581,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kerry, Joseph P.","contributorId":228964,"corporation":false,"usgs":false,"family":"Kerry","given":"Joseph","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":792619,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Poole, W Russel","contributorId":228954,"corporation":false,"usgs":false,"family":"Poole","given":"W Russel","affiliations":[{"id":41530,"text":"University College Cork","active":true,"usgs":false}],"preferred":false,"id":792582,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gargan, Patrick","contributorId":228955,"corporation":false,"usgs":false,"family":"Gargan","given":"Patrick","email":"","affiliations":[{"id":41531,"text":"Marine Inst","active":true,"usgs":false}],"preferred":false,"id":792583,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McGinnity, Philip","contributorId":224809,"corporation":false,"usgs":false,"family":"McGinnity","given":"Philip","email":"","affiliations":[],"preferred":false,"id":792584,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reed, Thomas E","contributorId":228956,"corporation":false,"usgs":false,"family":"Reed","given":"Thomas","email":"","middleInitial":"E","affiliations":[{"id":41530,"text":"University College Cork","active":true,"usgs":false}],"preferred":false,"id":792585,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70208763,"text":"70208763 - 2020 - Increased prespawning mortality threatens an integrated natural- and hatchery-origin sockeye salmon population in the Lake Washington Basin","interactions":[],"lastModifiedDate":"2020-03-02T06:23:12","indexId":"70208763","displayToPublicDate":"2020-02-27T06:44:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Increased prespawning mortality threatens an integrated natural- and hatchery-origin sockeye salmon population in the Lake Washington Basin","docAbstract":"The life cycle of diadromous fishes such as salmonids involves natural mortality in a series of distinct life history stages, occurring sequentially in different habitats. Decades of research have emphasized mortality at the embryo, juvenile, and sub-adult stages but it is increasingly clear that some adults that survive and return to freshwater habitats die during the final homeward migration or after they reach the spawning grounds, prior to breeding. These are termed “en route” and “prespawning” mortality, respectively, and can threaten populations depleted by mortality at previous stages. In this study, we present evidence that the sockeye salmon, Oncorhynchus nerka, population that returns to the Lake Washington Basin, in Washington State, USA, is experiencing both forms of adult mortality. Counts of the salmon entering the basin on their return migration in June and July were compared to counts in the major spawning grounds in September through November for 1995–2018. The disparity has increased markedly in recent years. The counts on the spawning grounds have decreased as a proportion of the number entering the system with an average 49 % of sockeye unaccounted for, consistent with increased en route mortality. In addition, prespawning mortality rates have increased in salmon that reach the Cedar River, the main spawning tributary, both at a hatchery holding adult fish in 1995–2018, and in the naturally spawning populations when monitored in the last five years. Hatchery records indicated <10 % prespawning mortality for 1995–2010, increasing to an average 43 % for 2014 – 2018. Recent carcass surveys in the Cedar River documented that 33.6% (2014), 22.3% (2015), 30.3% (2016) and 50.0% (2018) of female sockeye died before completing spawning. These recent increases in prespawning mortality have been associated with warm water during entry to freshwater, but comparably warm water in past decades had no such effect. Steady warming of river temperatures around the median run completion date from < 8.0 °C to > 13.0 °C was correlated with increased prespawning mortality rates at the hatchery from 1995–2018. We conclude that warming conditions during migration and spawning, in concert with other factors such as infections with pathogens, are responsible for the increased prespawning mortality of adult sockeye salmon that are high enough to threaten the population’s viability.","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2020.105527","usgsCitation":"Barnett, H.K., Quinn, T.P., Bhuthimethee, M., and Winton, J., 2020, Increased prespawning mortality threatens an integrated natural- and hatchery-origin sockeye salmon population in the Lake Washington Basin: Fisheries Research, v. 227, 105527, 10 p., https://doi.org/10.1016/j.fishres.2020.105527.","productDescription":"105527, 10 p.","ipdsId":"IP-115029","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":372723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Washington Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.29980468749999,\n 47.49772004565105\n ],\n [\n -122.18238830566406,\n 47.49772004565105\n ],\n [\n -122.18238830566406,\n 47.758714187846294\n ],\n [\n -122.29980468749999,\n 47.758714187846294\n ],\n [\n -122.29980468749999,\n 47.49772004565105\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"227","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barnett, Heidy K","contributorId":222835,"corporation":false,"usgs":false,"family":"Barnett","given":"Heidy","email":"","middleInitial":"K","affiliations":[{"id":40608,"text":"West Fork Environmental, Tumwater, WA","active":true,"usgs":false}],"preferred":false,"id":783313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quinn, Thomas P.","contributorId":167272,"corporation":false,"usgs":false,"family":"Quinn","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24671,"text":"School of Aquatic and Fsiery Sciences, UW, Box 355020, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":783314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bhuthimethee, Mary","contributorId":222836,"corporation":false,"usgs":false,"family":"Bhuthimethee","given":"Mary","email":"","affiliations":[{"id":40609,"text":"Seattle Public Utilities, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":783315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winton, James 0000-0002-3505-5509 jwinton@usgs.gov","orcid":"https://orcid.org/0000-0002-3505-5509","contributorId":179330,"corporation":false,"usgs":true,"family":"Winton","given":"James","email":"jwinton@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":783316,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208725,"text":"70208725 - 2020 - Evidence for a growing population of eastern migratory monarch butterflies is currently insufficient","interactions":[],"lastModifiedDate":"2020-06-19T16:25:57.924581","indexId":"70208725","displayToPublicDate":"2020-02-26T15:31:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for a growing population of eastern migratory monarch butterflies is currently insufficient","docAbstract":"The eastern migratory population of monarch butterflies has experienced a multi-decadal decline, but a recent increase in abundance (to 6.05 ha in winter 2018) has led some observers to question whether the population has reversed its long-standing decline and embarked on a trajectory of increasing abundance. We examined this possibility through changepoint analyses, first assessing whether a change in trajectory existed and whether that change was sufficient to alter our estimated risk for the population. We found evidence of a change in trajectory in 2014, but insufficient statistical support for a significantly increasing population since that time (β = 0.285, 95% CI = -0.127, 0.697). If the population estimate for winter 2019 is ≥4.0 ha, we will then be able to credibly assert the population has been increasing since 2014. However, given estimated levels of time series variability, presumed habitat capacity and no recent change in status or trend, there was a 13.5% probability of observing a population estimate as large or larger than was reported for winter 2018. Despite insufficient evidence for an increasing population, near-term risk of quasi-extinction by 2023 has declined (mean risk declining from 43% to 20%) because of higher abundance estimates since 2014. Our analyses highlight the incredible difficulty in drawing robust conclusions from annual changes in abundance over a short time series, especially for an insect that commonly exhibits considerable year-to-year variation. Thus, we urge caution when drawing conclusions regarding species status and trends for any species for which limited data are available.","language":"English","publisher":"Frontiers Media SA","doi":"10.3389/fevo.2020.00043","usgsCitation":"Thogmartin, W.E., Szymanski, J.A., and Weiser, E.L., 2020, Evidence for a growing population of eastern migratory monarch butterflies is currently insufficient: Frontiers in Ecology and Evolution, v. 8, 43, 5 p., https://doi.org/10.3389/fevo.2020.00043.","productDescription":"43, 5 p.","ipdsId":"IP-106927","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":457579,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2020.00043","text":"Publisher Index Page"},{"id":437085,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94OWFSM","text":"USGS data release","linkHelpText":"R code Evidence for a growing population of eastern migratory monarch butterflies is currently insufficient"},{"id":372656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":783179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szymanski, Jennifer A","contributorId":222787,"corporation":false,"usgs":false,"family":"Szymanski","given":"Jennifer","email":"","middleInitial":"A","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":783180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":213770,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":783181,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208985,"text":"70208985 - 2020 - Non-freezing cold event stresses can cause significant damage to mangrove seedlings: Assessing the role of warming and nitrogen enrichment in a mesocosm study","interactions":[],"lastModifiedDate":"2020-06-22T11:43:36.060529","indexId":"70208985","displayToPublicDate":"2020-02-26T14:25:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1561,"text":"Environmental Research","active":true,"publicationSubtype":{"id":10}},"title":"Non-freezing cold event stresses can cause significant damage to mangrove seedlings: Assessing the role of warming and nitrogen enrichment in a mesocosm study","docAbstract":"Mangroves are expanding poleward along coastlines globally as a response to rising temperatures and reduced incidence of freezing under climate change. Yet, knowledge of mangrove responses to infrequent cold events in the context of future global and regional environmental changes is limited. We initiated a mesocosm experiment in which the seedlings of two mangrove species were grown either at ambient temperature or under warming with and without nitrogen (N) loading. During a short winter period, an unusually severe cold event occurred with the lowest temperature of 2°C. We assessed the possible response of these two mangrove species to the cold stress. We found that the cold event caused various degrees of damage to the seedlings of both mangrove species, with the warming treatment seemingly protecting leaves and branches from the cold damage. However, warming did not buffer mangroves to mortality from those low temperatures in either species. The cold event resulted in a significant decrease in seedling growth rates and net ecosystem CO2 uptake in the post-cold period relative to the pre-cold period, though the cold event did not alter the effects of warming on these parameters of both mangrove species. The cold event differentially altered physiological responses of the two species growing under N loading, with A. marina growing in higher N concentrations having a reduced growth response after the cold event, whereas B. gymnorrhiza displayed no change in post-cold period versus pre-cold period growth. Our findings suggest the pivotal role of cold events, versus freeze events, in regulating mangrove survival and growth even under future warming scenarios. Two mangrove species exhibited differential survival and growth responses to the cold event at different N concentrations, which has implications for how we can restore and conserve mangroves among the world's eutrophied sub-tropical estuaries and with future warming.","language":"English","publisher":"IOPScience","doi":"10.1088/2515-7620/ab7a77","usgsCitation":"Song, W., Feng, J., Krauss, K.W., Zhao, Y., Wang, Z., Luo, Y., and Lin, G., 2020, Non-freezing cold event stresses can cause significant damage to mangrove seedlings: Assessing the role of warming and nitrogen enrichment in a mesocosm study: Environmental Research, v. 2, 031003, 13 p., https://doi.org/10.1088/2515-7620/ab7a77.","productDescription":"031003, 13 p.","ipdsId":"IP-107849","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":457581,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/2515-7620/ab7a77","text":"Publisher Index Page"},{"id":373075,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Song, Weimin","contributorId":223168,"corporation":false,"usgs":false,"family":"Song","given":"Weimin","email":"","affiliations":[{"id":40681,"text":"Department of Earth System Science, Tsinghua University, Beijing","active":true,"usgs":false}],"preferred":false,"id":784416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feng, Jianxiang","contributorId":223169,"corporation":false,"usgs":false,"family":"Feng","given":"Jianxiang","email":"","affiliations":[{"id":40682,"text":"Graduate School at Shenzhen, Tsinghua University, Shenzhen","active":true,"usgs":false}],"preferred":false,"id":784417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":784415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhao, Yan","contributorId":220290,"corporation":false,"usgs":false,"family":"Zhao","given":"Yan","email":"","affiliations":[],"preferred":false,"id":784418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Zhonglei","contributorId":223170,"corporation":false,"usgs":false,"family":"Wang","given":"Zhonglei","email":"","affiliations":[{"id":40682,"text":"Graduate School at Shenzhen, Tsinghua University, Shenzhen","active":true,"usgs":false}],"preferred":false,"id":784419,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luo, Yiqi","contributorId":177420,"corporation":false,"usgs":false,"family":"Luo","given":"Yiqi","email":"","affiliations":[],"preferred":false,"id":784420,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lin, Guanghui","contributorId":177296,"corporation":false,"usgs":false,"family":"Lin","given":"Guanghui","email":"","affiliations":[{"id":25577,"text":"Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":784421,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209424,"text":"70209424 - 2020 - Geology of the Trout Rock caves (Hamilton Cave, Trout Cave, New Trout Cave) in Pendleton County, West Virginia (USA), and implications regarding the origin of maze caves","interactions":[],"lastModifiedDate":"2020-04-09T17:51:25.200543","indexId":"70209424","displayToPublicDate":"2020-02-26T12:26:03","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geology of the Trout Rock caves (Hamilton Cave, Trout Cave, New Trout Cave) in Pendleton County, West Virginia (USA), and implications regarding the origin of maze caves","docAbstract":"The Trout Rock caves (Hamilton Cave, Trout Cave, New Trout Cave) are located in a hill named Cave Knob that overlooks the South Branch of the Potomac River in Pendleton County, West Virginia (U.S.A). The geologic structure of this hill is a northeasttrending anticline, and the caves are located at different elevations primarily along the contact between the Devonian New Creek Limestone (Helderberg Group) and the overlying Devonian Corriganville Limestone (Helderberg Group). The entrance to New Trout Cave (Stop 1) is located on the east flank of Cave Knob anticline at an elevation of 585 m (1,920 ft) relative to sea level, or 39 m (128 ft) above the modern river. Much of the cave consists of passages that extend to the northeast along strike, and many of these passages have developed along primary joints that trend N40E or secondary joints that trend N40W. Sediments in New Trout Cave include mud and sand (some of which was mined for nitrate during the American Civil War), as well as large boulders in the front part of the cave. Gypsum crusts are present in a maze section of the cave ~213 to 305 m (700 to 1,000 ft) from the cave entrance. Excavations in New Trout Cave have produced vertebrate fossils of Rancholabrean age, ~300,000 to 10,000 years Before Present (BP). The entrance to Trout Cave (Stop 2) is located on the east flank of Cave Knob anticline ~100 m (328 ft) northwest of the New Trout Cave entrance at an elevation of 622 m (2,040 ft) relative to sea level, or 76 m (249 ft) above the modern river. Much of the cave consists of passages that extend to the northeast along strike, although a small area of network maze passages is present in the western portion of Trout Cave that is closest to Hamilton Cave. Many of the passages of Trout Cave have developed along primary joints that trend N40E or secondary joints that trend N40W. Sediments in Trout Cave include mud (also mined for nitrate during the American Civil War), as well as large boulders in the front part of the cave. Excavations in the upper levels of Trout Cave have produced vertebrate fossils of Rancholabrean age (~300,000 to 10,000 years BP), whereas excavations in the lower levels of the cave have produced vertebrate fossils of Irvingtonian age (~1,810,000 to 300,000 years BP). The entrance to Hamilton Cave (Stop 3) is located along the axis of Cave Knob anticline ~165 m (540 ft) northwest of the Trout Cave entrance at an elevation of 640 m (2,100 ft) relative to sea level, or 94 m (308 ft) above the modern river. The front (upper) part of Hamilton Cave has a classic network maze pattern that is an angular grid of relatively horizontal passages, most of which follow vertical or near-vertical primary joints that trend N40W and N50W and secondary joints that trend N60W and N80E. This part of the cave lies along the axis of Cave Knob anticline. In contrast, the passages in the back (lower) part of Hamilton Cave lie along the west flank of Cave Knob anticline at ~58 to 85 m (190 to 279 ft) above the modern river. These passages do not display a classic maze pattern, and instead they may be divided into the following two categories: (1) longer northeast-trending passages that are relatively horizontal and follow the strike of the beds; and (2) shorter northwest-trending passages that descend steeply to the west and follow the dip of the beds. Sediments in Hamilton Cave include mud (which was apparently not mined for nitrate during the American Civil War), as well as large boulders in the front part of the cave. Gypsum crusts are present along passage walls of the New Creek Limestone from the Slab Room to the Airblower. Excavations in the front part of Hamilton Cave (maze section) have produced vertebrate fossils of Irvingtonian age (~1,810,000 to 300,000 years BP). The network maze portions of Hamilton Cave are interpreted as having developed at or near the water table where water did not have a free surface in contact with air and where the following conditions were present: (1) Location on or near the axis of an anticline (the location of the greatest amount of flexure); (2) Abundant vertical or near vertical joints, which are favored by location in the area of greatest flexure and by a lithologic unit (chert-rich limestone) that is more likely to experience brittle rather than ductile deformation; (3) Widening of joints to enhance ease of water infiltration, favored by location in area of greatest amount of flexure; and (4) Dissolution along nearly all major joints to produce cave passages of approximately the same size (which would most likely occur via water without a free surface in contact with air). The cave passages that are located along anticline axes and along strike at the New Creek-Corriganville contact are interpreted as having formed initially during times of base level stillstand at or near the water table where water did not have a free surface in contact with air and where the water flowed along the hydraulic gradient at gentle slopes. Under such conditions, dissolution occurred in all directions to produce cave passages with relatively linear wall morphologies. In the lower portions of some of the along-strike passages, the cave walls have a more sinuous (meandering) morphology, which is interpreted as having formed during subsequent initial base level fall as cave development continued under vadose conditions where the water had a free surface in contact with air, and where water flow was governed primarily by gravitational processes. Steeply inclined cave passages that are located along dip at the New Creek-Corriganville contact are interpreted as having formed during subsequent true vadose conditions (after base level fall). This chronology of base level stasis (with cave development in the phreatic zone a short distance below top of water table) followed by base level fall (with cave development in the vadose or epiphreatic zone) has repeated multiple times at Cave Knob during the past ~4 to 3 million years, resulting in multiple cave passages at different elevations, with different passage morphologies, and at different passage locations with respect to strike and dip.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geological Society of America Field Guide","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2020.0057(03)","collaboration":"","usgsCitation":"Swezey, C.S., and Brent, E.L., 2020, Geology of the Trout Rock caves (Hamilton Cave, Trout Cave, New Trout Cave) in Pendleton County, West Virginia (USA), and implications regarding the origin of maze caves, chap. of Geological Society of America Field Guide, v. 57, p. 43-77, https://doi.org/10.1130/2020.0057(03).","productDescription":"35 p.","startPage":"43","endPage":"77","ipdsId":"IP-113405","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":457583,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2020.0057(03)","text":"Publisher Index Page"},{"id":373863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","county":"Pendleton County","otherGeospatial":"Trout Rock Caves","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.06036376953125,\n 38.768004230175954\n ],\n [\n -79.37759399414062,\n 38.975424875431436\n ],\n [\n -79.4586181640625,\n 38.932707274379595\n ],\n [\n -79.53826904296875,\n 38.839707613545144\n ],\n [\n -79.66323852539062,\n 38.59970036588819\n ],\n [\n -79.53414916992186,\n 38.543869175876154\n ],\n [\n -79.47509765625,\n 38.460041065720446\n ],\n [\n -79.33364868164062,\n 38.415938460513274\n ],\n [\n -79.27322387695312,\n 38.41486245064945\n ],\n [\n -79.20867919921875,\n 38.50304202775689\n ],\n [\n -79.21005249023438,\n 38.515937313413474\n ],\n [\n -79.12216186523438,\n 38.66299474019031\n ],\n [\n -79.1015625,\n 38.659777730712534\n ],\n [\n -79.08233642578124,\n 38.6897975322717\n ],\n [\n -79.06036376953125,\n 38.768004230175954\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":786454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brent, Emily L","contributorId":223860,"corporation":false,"usgs":false,"family":"Brent","given":"Emily","email":"","middleInitial":"L","affiliations":[],"preferred":false,"id":786455,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209422,"text":"70209422 - 2020 - Foreward: Geology Field Trips in and around the U.S. Capital","interactions":[],"lastModifiedDate":"2020-04-28T20:30:35.335374","indexId":"70209422","displayToPublicDate":"2020-02-26T12:11:17","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Foreward: Geology Field Trips in and around the U.S. Capital","docAbstract":"The first annual meeting of the Geological Society of America (GSA) was held in 1888 in Ithaca, New York (Fairchild, 1932), but official Sections of GSA formed much later. During the spring of 1949, a symposium in Knoxville, Tennessee, on mineral resources of the southeastern United States became the catalyst for the creation of the Southeastern Section of the Geological Society of America (King, 1964), and the first annual meeting of the Southeastern Section was held in 1952 in Roanoke, Virginia (Wilson, 1954). The Northeastern Section formed much later, and its first annual meeting was held in 1966 in Philadelphia, Pennsylvania (Socolow, 1968). At all of these section meetings, field trips have been important venues for geologists and especially students to gather together, examine rocks in the field, and discuss ideas. These field trips have been especially important at combined section meetings because they provide settings for geologists who are experienced in one geographic region to examine and compare the geology of other regions. The first combined meeting of the Southeastern and Northeastern sections occurred in 1976 in Arlington, Virginia. Since then, the Southeastern and Northeastern sections have met together on numerous occasions, including 1982 in Washington, DC; 1991 in Baltimore, Maryland; 2004 in Tysons Corner, Virginia; and 2010 in Baltimore, Maryland. \n Since the first combined section meeting in 1976, there has been a gradual increase in the role of technology in geology field studies. In fact, during the past several decades there has been an increase in emphasis in our society on the instrumental component of science, the goal of which is operational techniques to do or control things, and a corresponding decrease in emphasis on the natural philosophy component of science, the goal of which is a greater understanding of the natural world (Dear, 2006). The modern education acronym STEM (Science, Technology, Engineering, and Mathematics), for example, is often used as a catch-all term that implies that science and technology are relatively synonymous, and implies that greater technology leads automatically to greater understanding of the natural world. This assumption, however, is not always valid (Dear, 2006), and technology should not be promoted as a substitute for field experiences. Technology can be a tool that leads to greater understanding of the natural world, but not all Science uses technology as a means of providing greater understanding. The benefits of new technologies include: (1) data of greater resolution; and (2) greater efficiency of capturing, storing, and visualizing data. The risks of new technologies include: (1) an overabundance of data, some of which may be of little value; (2) less time available for analysis of data, if geologists become occupied primarily with capturing and storing data; and (3) errors that arise from complacency and the perception that field-checking may not be necessary. In other words, there is a risk that a glut of data and vast amounts of time devoted to the capturing and storing of data may result in a reduced interest and (or) willingness to field-check data. \nIn the spirit of the early GSA section meetings, we feel that there are still enormous advantages to conducting geology field trips in conjunction with traditional meeting presentations and posters. In 2020, with this current combined Southeastern and Northeastern section meeting in Reston, Virginia, we have assembled eight different field trips that cover a wide range of territory in and around the Nation’s capital. These field trip localities include the immediate vicinity of Washington, DC, as well as various locations in nearby areas of Virginia, Maryland, and West Virginia. The physiographic provinces include Mesozoic Rift Basins, the Piedmont, the Blue Ridge, the Valley and Ridge, and the Allegheny Plateau of the Appalachian Basin. The field trip sites exhibit a wide range of igneous, metamorphic, and sedimentary rocks, as well as rocks with a wide range of geologic ages from the Mesoproterozoic to the Holocene. We hope that this guidebook provides new motivation for geologists to examine rocks in the field, to discuss ideas with colleagues in the field, and to avoid becoming complacent. \n The editors of this volume would like to thank the authors of the different field trip guides, the field trip leaders, and all of the reviewers who made suggestions for improving the field trip manuscripts. The editors would also like to thank Elle Derwent of GSA for her logistical help and guidance regarding the field trips, and April Leo and the staff of the GSA Publications Department for seeing this book through to publication.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geological Society of America Field Guide","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2020.0057(00)","collaboration":"","usgsCitation":"Swezey, C.S., and Carter, M.W., 2020, Foreward: Geology Field Trips in and around the U.S. Capital, chap. of Geological Society of America Field Guide, v. 57, p. v-vi, https://doi.org/10.1130/2020.0057(00).","productDescription":"2 p.","startPage":"v","endPage":"vi","ipdsId":"IP-113973","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":373862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.870361328125,\n 36.84006462037767\n ],\n [\n -75.8056640625,\n 36.84006462037767\n ],\n [\n -75.8056640625,\n 39.65222681530652\n ],\n [\n -80.870361328125,\n 39.65222681530652\n ],\n [\n -80.870361328125,\n 36.84006462037767\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":786450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":786451,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211287,"text":"70211287 - 2020 - The role of Northeast Pacific meltwater events in deglacial climate change","interactions":[],"lastModifiedDate":"2020-07-22T15:13:57.928397","indexId":"70211287","displayToPublicDate":"2020-02-26T10:11:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"The role of Northeast Pacific meltwater events in deglacial climate change","docAbstract":"Columbia River megafloods occurred repeatedly during the last deglaciation, but the impacts of this fresh water on Pacific hydrography are largely unknown. To reconstruct changes in ocean circulation during this period, we used a numerical model to simulate the flow trajectory of Columbia River megafloods and compiled records of sea surface temperature, paleo-salinity, and deep-water radiocarbon from marine sediment cores in the Northeast Pacific. The North Pacific sea surface cooled and freshened during the early deglacial (19.0-16.5 ka) and Younger Dryas (12.9-11.7 ka) intervals, coincident with the appearance of subsurface water masses depleted in radiocarbon relative to the sea surface. We infer that Pacific meltwater fluxes contributed to net Northern Hemisphere cooling prior to North Atlantic Heinrich Events, and again during the Younger Dryas stadial. Abrupt warming in the Northeast Pacific similarly contributed to hemispheric warming during the Bølling and Holocene transitions. These findings underscore the importance of changes in North Pacific freshwater fluxes and circulation in deglacial climate events.","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.aay2915","usgsCitation":"Praetorius, S.K., Condron, A., Mix, A., Walczak, M., McKay, J., and Du, J., 2020, The role of Northeast Pacific meltwater events in deglacial climate change: Science Advances, v. 6, no. 9, eaay2915, 18 p., https://doi.org/10.1126/sciadv.aay2915.","productDescription":"eaay2915, 18 p.","ipdsId":"IP-093675","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":457590,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aay2915","text":"Publisher Index Page"},{"id":376636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Praetorius, Summer K. 0000-0003-2683-3652","orcid":"https://orcid.org/0000-0003-2683-3652","contributorId":206966,"corporation":false,"usgs":true,"family":"Praetorius","given":"Summer","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":793519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Condron, Alan 0000-0002-7337-1713","orcid":"https://orcid.org/0000-0002-7337-1713","contributorId":229547,"corporation":false,"usgs":false,"family":"Condron","given":"Alan","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":793520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mix, Alan","contributorId":184163,"corporation":false,"usgs":false,"family":"Mix","given":"Alan","affiliations":[],"preferred":false,"id":793521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walczak, Maureen 0000-0002-4123-6998","orcid":"https://orcid.org/0000-0002-4123-6998","contributorId":206972,"corporation":false,"usgs":false,"family":"Walczak","given":"Maureen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":793522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKay, Jennifer","contributorId":229548,"corporation":false,"usgs":false,"family":"McKay","given":"Jennifer","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":793523,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Du, Jianghui 0000-0002-3386-9314","orcid":"https://orcid.org/0000-0002-3386-9314","contributorId":206970,"corporation":false,"usgs":false,"family":"Du","given":"Jianghui","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":793524,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263647,"text":"70263647 - 2020 - Near-field ground motions from the July, 2019 Ridgecrest, California, earthquake sequence","interactions":[],"lastModifiedDate":"2025-02-19T14:20:57.140542","indexId":"70263647","displayToPublicDate":"2020-02-26T09:53:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Near-field ground motions from the July, 2019 Ridgecrest, California, earthquake sequence","docAbstract":"The 2019 Ridgecrest, California, earthquake sequence, including an Mw 6.4 event on 4 July and an Mw 7.1 approximately 34 hr later, was recorded by 15 instruments within 55 km nearest‐fault distance. To characterize and explore near‐field ground motions from the Mw 6.4 foreshock and Mw 7.1 mainshock, we augment these records with available macroseismic information, including conventional intensities and displaced rocks. We conclude that near‐field shaking intensities were generally below modified Mercalli intensity 9, with concentrations of locally high values toward the northern and southern termini of the mainshock rupture. We further show that, relative to near‐field ground motions at hard‐rock sites, instrumental ground motions at alluvial near‐field sites for both the Mw 6.4 foreshock and Mw 7.1 mainshock were depleted in energy at frequencies higher than 2–3 Hz, as expected from ground‐motion models. Both the macroseismic and instrumental observations suggest that sediments in the Indian Wells Valley experienced a pervasively nonlinear response, which helps explain why shaking intensities and damage in the closest population center, Ridgecrest, were relatively modest given its proximity to the earthquakes.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190279","usgsCitation":"Hough, S.E., Thompson, E.M., Parker, G., Graves, R., Hudnut, K.W., Patton, J., Dawson, T., Ladinsky, T.C., Oskin, M., Sirorattanakul, K., Blake, K., Baltay Sundstrom, A.S., and Cochran, E.S., 2020, Near-field ground motions from the July, 2019 Ridgecrest, California, earthquake sequence: Seismological Research Letters, v. 91, no. 3, p. 1542-1555, https://doi.org/10.1785/0220190279.","productDescription":"14 p.","startPage":"1542","endPage":"1555","ipdsId":"IP-112076","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482164,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.50916574226079,\n 36.688337109123\n ],\n [\n -119.50916574226079,\n 33.93284050953977\n ],\n [\n -115.58563079978865,\n 33.93284050953977\n ],\n [\n -115.58563079978865,\n 36.688337109123\n ],\n [\n -119.50916574226079,\n 36.688337109123\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"91","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parker, Grace A.","contributorId":350992,"corporation":false,"usgs":false,"family":"Parker","given":"Grace A.","affiliations":[],"preferred":false,"id":927655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudnut, Kenneth W. 0000-0002-3168-4797 hudnut@usgs.gov","orcid":"https://orcid.org/0000-0002-3168-4797","contributorId":2550,"corporation":false,"usgs":true,"family":"Hudnut","given":"Kenneth","email":"hudnut@usgs.gov","middleInitial":"W.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":927657,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Patton, Jason","contributorId":225602,"corporation":false,"usgs":false,"family":"Patton","given":"Jason","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":927658,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dawson, Timothy E.","contributorId":304669,"corporation":false,"usgs":false,"family":"Dawson","given":"Timothy E.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":927659,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ladinsky, Tyler C.","contributorId":201083,"corporation":false,"usgs":false,"family":"Ladinsky","given":"Tyler","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":927660,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Oskin, Michael","contributorId":140301,"corporation":false,"usgs":false,"family":"Oskin","given":"Michael","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":927661,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sirorattanakul, Krittanon","contributorId":350993,"corporation":false,"usgs":false,"family":"Sirorattanakul","given":"Krittanon","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":927662,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Blake, Kelly","contributorId":344574,"corporation":false,"usgs":false,"family":"Blake","given":"Kelly","affiliations":[{"id":82392,"text":"U.S. Navy Geothermal Program office","active":true,"usgs":false}],"preferred":false,"id":927663,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927664,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927665,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70223337,"text":"70223337 - 2020 - Trends in cheetah Acinonyx jubatus density in north-central Namibia","interactions":[],"lastModifiedDate":"2021-08-24T13:13:40.57478","indexId":"70223337","displayToPublicDate":"2020-02-26T08:09:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Trends in cheetah Acinonyx jubatus density in north-central Namibia","title":"Trends in cheetah Acinonyx jubatus density in north-central Namibia","docAbstract":"Assessing trends in abundance and density of species of conservation concern is vital to inform conservation and management strategies. The remaining population of the cheetah (Acinonyx jubatus) largely exists outside of protected areas, where they are often in conflict with humans. Despite this, the population status and dynamics of cheetah outside of protected areas have received relatively limited attention across its range. We analyzed remote camera trapping data of nine surveys conducted from 2005 to 2014 in the Waterberg Conservancy, north-central Namibia, which included detections of 74 individuals (52 adult males, 7 adult females and 15 dependents). Using spatial capture–recapture methods, we assessed annual and seasonal trends in cheetah density. We found evidence of a stable trend in cheetah density over the study period, with an average density of 1.94/100 km2 (95% confidence interval 1.33–2.84). This apparent stability of cheetah density is likely the result of stable and abundant prey availability, a high tolerance to carnivores by farmers and low turnover rates in home range tenure. This study highlights the importance of promoting long-term surveys that capture a broad range of environmental variation that may influence species density and the importance of nonprotected areas for cheetah conservation.
In 2015, the total amount of water withdrawn in Florida was estimated to be 15,319 million gallons per day (Mgal/d). Saline water accounted for 9,598 Mgal/d (63 percent) and freshwater accounted for 5,721 Mgal/d (37 percent) of the total. Groundwater accounted for 3,604 Mgal/d (63 percent) of freshwater withdrawals and surface water accounted for the remaining 2,117 Mgal/d (37 percent). Surface-water sources accounted for 9,401 Mgal/d (98 percent) of the saline-water withdrawals, and groundwater sources accounted for the remaining 198 Mgal/d (2 percent). The majority of groundwater withdrawals (almost 62 percent) in 2015 were from the Floridan aquifer system, which is used throughout most of the State while the majority of fresh surface-water withdrawals (52 percent) occurred in the Southern Florida Subregion, a hydrologic unit that includes Lake Okeechobee and canals in the Everglades Agricultural Area. Groundwater provided drinking water (public supplied and self-supplied) for 18.324 million people (92 percent of Florida’s population), and fresh surface water provided drinking water for 1.491 million people (8 percent).
Overall, public supply accounted for 39 percent of the total freshwater withdrawals (ground and surface) and 53 percent of groundwater withdrawals, followed by agricultural self-supplied uses, which accounted for 37 percent of the total freshwater withdrawals and 28 percent of groundwater withdrawals. Other self-supplied groundwater withdrawals include commercial-industrial-mining self-supplied (8 percent), recreational-landscape irrigation and domestic self-supplied (5 percent each), and power generation (less than 1 percent). Agricultural self-supplied withdrawals accounted for 51 percent of fresh surface-water withdrawals, followed by power generation (19 percent), public supply (15 percent), recreational-landscape irrigation (10 percent), and commercial-industrial-mining self-supplied (5 percent).
In 1975, agricultural water withdrawals accounted for 43 percent of the total freshwater withdrawals, followed by power generation (24 percent) and public supply (17 percent). By 2000, agricultural withdrawals increased to 48 percent of the total freshwater withdrawals, followed by public supply (30 percent). For 2015, agricultural self-supplied decreased to 37 percent of total freshwater withdrawals, and was surpassed by public supply at 39 percent. Over the 40-year period between 1975 and 2015, increases in freshwater withdrawals caused by large gains in population and the expansion of irrigated acreage were offset by decreases in water used for power generation and commercial-industrial-mining withdrawals. Since 2000, however, irrigated acreage has decreased statewide because of crop disease, storm damage, and urbanization. This decline, coupled with large gains in water conservation measures in the farming industry, has led to agricultural withdrawals in Florida being less than public-supply withdrawals for the first time since water-use data were first reported in 1965.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195147","collaboration":"Prepared in cooperation with the Florida Department of Agricultural and Consumer Services","usgsCitation":"Marella, R.L., 2020, Water withdrawals, uses, and trends in Florida, 2015: U.S. Geological Survey Scientific Investigations Report 2019–5147, 52 p., https://doi.org/10.3133/sir20195147.","productDescription":"Report: vii, 52 p.; Data Release","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-093230","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":372545,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5147/sir20195147.pdf","text":"Report","size":"2.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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\"}}]}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The behavior of wildlife varies seasonally, and that variation can have substantial demographic consequences. This is especially true for long‐distance migrants where the use of landscapes varies by season and, sometimes, age cohort. We tested the hypothesis that distributional patterns of Golden Eagles (Aquila chrysaetos) wintering in eastern North America are age‐structured (i.e., birds of similar ages winter together) through the analysis of 370,307 images collected by motion‐sensitive trail cameras set over bait during the winters of 2012–2013 and 2013–2014. At nine sites with sufficient data for analysis, we documented 145 eagle visits in 2012–2013 and 146 in 2013–2014. We found significant between‐year variation in age structure of wintering eastern Golden Eagles, driven largely by annual differences in the proportion of first‐winter birds. However, although many other species show spatial structure in wintering behavior, our analysis revealed no latitudinal organization among age cohorts of wintering eastern Golden Eagles. The lack of age‐related latitudinal segregation in wintering behavior does not exclude the possibility that these eagles have sex‐based or other types of dominance hierarchies that could result in spatial or temporal segregation. Alternatively, other mechanisms such as food availability or habitat structure may determine the distribution and abundance of Golden Eagles in winter.