A middle to late Pleistocene sedimentary sequence in the upper Las Vegas Wash, north of Las Vegas, Nevada, has yielded the largest open-site Rancholabrean vertebrate fossil assemblage in the southern Great Basin and Mojave Deserts. Recent paleontologic field studies have led to the discovery of hundreds of fossil localities and specimens, greatly extending the geographic and temporal footprint of original investigations in the early 1960s. The significance of the deposits and their entombed fossils led to the preservation of 22,650 acres of the upper Las Vegas Wash as Tule Springs Fossil Beds National Monument. These discoveries also warrant designation of the assemblage as a local fauna, named for the site of the original paleontologic studies at Tule Springs.
The large mammal component of the Tule Springs local fauna is dominated by remains of Mammuthus columbi as well as Camelops hesternus, along with less common remains of Equus (including E. scotti) and Bison. Large carnivorans including Canis dirus, Smilodon fatalis, and Panthera atrox are also recorded. Micromammals, amphibians, lizards, snakes, birds, invertebrates, plant macrofossils, and pollen also occur in the deposits and provide important and complementary paleoenvironmental information. The fauna occurs within the Las Vegas Formation, an extensive and stratigraphically complex sequence of groundwater discharge deposits that represent a mosaic of desert wetland environments. Radiometric and luminescence dating indicates the sequence spans the last ∼570 ka, and records hydrologic changes in a dynamic and temporally congruent response to northern hemispheric abrupt climatic oscillations. The vertebrate fauna occurs in multiple stratigraphic horizons in this sequence, with ages of the fossils spanning from ∼100 to ∼12.5 ka.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2017.06.001","usgsCitation":"Scott, E., Springer, K.B., and Sagebiel, J.C., 2017, The Tule Springs local fauna: Rancholabrean vertebrates from the Las Vegas Formation, Nevada: Quaternary International, v. 443, no. A, p. 105-121, https://doi.org/10.1016/j.quaint.2017.06.001.","productDescription":"17 p.","startPage":"105","endPage":"121","ipdsId":"IP-081590","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":345014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"443","issue":"A","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"599bf11fe4b0b589267ed32d","contributors":{"authors":[{"text":"Scott, Eric","contributorId":127422,"corporation":false,"usgs":false,"family":"Scott","given":"Eric","email":"","affiliations":[],"preferred":false,"id":708145,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Springer, Kathleen B. 0000-0002-2404-0264 kspringer@usgs.gov","orcid":"https://orcid.org/0000-0002-2404-0264","contributorId":149826,"corporation":false,"usgs":true,"family":"Springer","given":"Kathleen","email":"kspringer@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":708144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sagebiel, James C.","contributorId":195775,"corporation":false,"usgs":false,"family":"Sagebiel","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":708146,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190205,"text":"70190205 - 2017 - Moving forward in circles: Challenges and opportunities in modeling population cycles","interactions":[],"lastModifiedDate":"2017-08-21T11:38:36","indexId":"70190205","displayToPublicDate":"2017-08-21T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Moving forward in circles: Challenges and opportunities in modeling population cycles","docAbstract":"Population cycling is a widespread phenomenon, observed across a multitude of taxa in both laboratory and natural conditions. Historically, the theory associated with population cycles was tightly linked to pairwise consumer–resource interactions and studied via deterministic models, but current empirical and theoretical research reveals a much richer basis for ecological cycles. Stochasticity and seasonality can modulate or create cyclic behaviour in non-intuitive ways, the high-dimensionality in ecological systems can profoundly influence cycling, and so can demographic structure and eco-evolutionary dynamics. An inclusive theory for population cycles, ranging from ecosystem-level to demographic modelling, grounded in observational or experimental data, is therefore necessary to better understand observed cyclical patterns. In turn, by gaining better insight into the drivers of population cycles, we can begin to understand the causes of cycle gain and loss, how biodiversity interacts with population cycling, and how to effectively manage wildly fluctuating populations, all of which are growing domains of ecological research.","language":"English","publisher":"Wiley","doi":"10.1111/ele.12789","usgsCitation":"Barraquand, F., Louca, S., Abbott, K.C., Cobbold, C.A., Cordoleani, F., DeAngelis, D.L., Elderd, B.D., Fox, J.W., Greenwood, P., Hilker, F., Murray, D., Stieha, C.R., Taylor, R.C., Vitense, K., Wolkowicz, G., and Tyson, R., 2017, Moving forward in circles: Challenges and opportunities in modeling population cycles: Ecology Letters, v. 20, no. 8, p. 1074-1092, https://doi.org/10.1111/ele.12789.","productDescription":"19 p.","startPage":"1074","endPage":"1092","ipdsId":"IP-073202","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research 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0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":707949,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Elderd, Bret D","contributorId":195712,"corporation":false,"usgs":false,"family":"Elderd","given":"Bret","email":"","middleInitial":"D","affiliations":[],"preferred":false,"id":707955,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fox, Jeremy 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R","contributorId":195718,"corporation":false,"usgs":false,"family":"Stieha","given":"Christopher","email":"","middleInitial":"R","affiliations":[],"preferred":false,"id":707961,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Taylor, Rachel C.","contributorId":195719,"corporation":false,"usgs":false,"family":"Taylor","given":"Rachel","middleInitial":"C.","affiliations":[],"preferred":false,"id":707962,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Vitense, Kelsey","contributorId":195720,"corporation":false,"usgs":false,"family":"Vitense","given":"Kelsey","email":"","affiliations":[],"preferred":false,"id":707963,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wolkowicz, Gail","contributorId":195721,"corporation":false,"usgs":false,"family":"Wolkowicz","given":"Gail","email":"","affiliations":[],"preferred":false,"id":707964,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tyson, Rebecca 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of structure I gas hydrate stability, top of gas hydrate occurrence, sulfate-methane transition depth, pressure (water depth), and geothermal gradients. The motivation of this study is to provide first-order estimates of the top of gas hydrate occurrence and associated thickness of the gas hydrate occurrence zone for climate-change scenarios, global carbon budget analyses, or gas hydrate resource assessments. Results from publicly available drilling campaigns (21 expeditions and 52 drill sites) off Cascadia, Blake Ridge, India, Korea, South China Sea, Japan, Chile, Peru, Costa Rica, Gulf of Mexico, and Borneo reveal a first-order linear relationship between the depth to the top and base of gas hydrate occurrence. The reason for these nearly linear relationships is believed to be the strong pressure and temperature dependence of methane solubility in the absence of large difference in thermal gradients between the various sites assessed. In addition, a statistically robust relationship was defined between the thickness of the gas hydrate occurrence zone and the base of gas hydrate stability (in meters below seafloor). The relationship developed is able to predict the depth of the top of gas hydrate occurrence zone using observed depths of the base of gas hydrate stability within less than 50 m at most locations examined in this study. No clear correlation of the depth to the top and base of gas hydrate occurrences with geothermal gradient and sulfate-methane transition depth was identified.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GC006805","usgsCitation":"Riedel, M., and Collett, T.S., 2017, Observed correlation between the depth to base and top of gas hydrate occurrence from review of global drilling data: Geochemistry, Geophysics, Geosystems, v. 18, no. 7, p. 2543-2561, https://doi.org/10.1002/2017GC006805.","productDescription":"19 p.","startPage":"2543","endPage":"2561","ipdsId":"IP-082912","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gc006805","text":"Publisher Index Page"},{"id":344997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-13","publicationStatus":"PW","scienceBaseUri":"599bf122e4b0b589267ed33b","contributors":{"authors":[{"text":"Riedel, Michael","contributorId":7518,"corporation":false,"usgs":true,"family":"Riedel","given":"Michael","email":"","affiliations":[],"preferred":false,"id":707874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":707873,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190211,"text":"70190211 - 2017 - Seasonal variability in particulate matter source and composition to the depositional zone of Baltimore Canyon, U.S. Mid-Atlantic Bight","interactions":[],"lastModifiedDate":"2017-09-25T13:45:06","indexId":"70190211","displayToPublicDate":"2017-08-21T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1370,"text":"Deep-Sea Research Part I: Oceanographic Research Papers","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal variability in particulate matter source and composition to the depositional zone of Baltimore Canyon, U.S. Mid-Atlantic Bight","docAbstract":"Submarine canyons are often hotspots of biomass and productivity in the deep sea. However, the majority of deep-sea canyons remain poorly sampled. Using a multi-tracer approach, results from a detailed geochemical investigation from a year-long sediment trap deployment reveals details concerning the source, transport, and fate of particulate matter to the depositional zone (1318 m) of Baltimore Canyon on the US Mid-Atlantic Bight (MAB). Both organic biomarker composition (sterol and n-alkanes) and bulk characteristics (δ13C, Δ14C, Chl-a) suggest that on an annual basis particulate matter from marine and terrestrially-derived organic matter are equally important. However, elevated Chlorophyll-a and sterol concentrations during the spring sampling period highlight the seasonal influx of relatively fresh phytodetritus. In addition, the contemporaneous increase in the particle reactive elements cadmium (Cd) and molybdenum (Mo) in the spring suggest increased scavenging, aggregation, and sinking of biomass during seasonal blooms in response to enhanced surface production within the nutricline. While internal waves within the canyon resuspend sediment between 200 and 600 m, creating a nepheloid layer rich in lithogenic material, near-bed sediment remobilization in the canyon depositional zone is minimal. Instead, vertical transport and lateral transport across the continental margin are the dominant processes driving seasonal input of particulate matter. In turn, seasonal variability in deposited particulate organic matter may be linked to benthic faunal composition and ecosystem scale carbon cycling.","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr.2017.08.004","usgsCitation":"Prouty, N.G., Mienis, F., Campbell, P., Roark, E.B., Davies, A., Robertson, C.M., Duineveld, G., Ross, S., Rhodes, M., and Demopoulos, A.W., 2017, Seasonal variability in particulate matter source and composition to the depositional zone of Baltimore Canyon, U.S. Mid-Atlantic Bight: Deep-Sea Research Part I: Oceanographic Research Papers, v. 127, p. 77-89, https://doi.org/10.1016/j.dsr.2017.08.004.","productDescription":"13 p.","startPage":"77","endPage":"89","ipdsId":"IP-083494","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469599,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://repository.library.noaa.gov/view/noaa/57259","text":"Publisher Index Page"},{"id":344991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74,\n 38\n ],\n [\n -73,\n 38\n ],\n [\n -73,\n 39\n ],\n [\n -74,\n 39\n ],\n [\n -74,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"599bf121e4b0b589267ed331","contributors":{"authors":[{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":707994,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mienis, Furu","contributorId":20255,"corporation":false,"usgs":true,"family":"Mienis","given":"Furu","affiliations":[],"preferred":false,"id":707995,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, P.","contributorId":99249,"corporation":false,"usgs":true,"family":"Campbell","given":"P.","email":"","affiliations":[],"preferred":false,"id":708139,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roark, E. Brendan","contributorId":195726,"corporation":false,"usgs":false,"family":"Roark","given":"E.","email":"","middleInitial":"Brendan","affiliations":[],"preferred":false,"id":707997,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davies, Andrew","contributorId":71394,"corporation":false,"usgs":true,"family":"Davies","given":"Andrew","affiliations":[],"preferred":false,"id":707998,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robertson, Craig M.","contributorId":169050,"corporation":false,"usgs":false,"family":"Robertson","given":"Craig","email":"","middleInitial":"M.","affiliations":[{"id":25399,"text":"Bangor University, Wales, UK","active":true,"usgs":false}],"preferred":false,"id":708140,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duineveld, Gerard","contributorId":195725,"corporation":false,"usgs":false,"family":"Duineveld","given":"Gerard","affiliations":[],"preferred":false,"id":707999,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ross, Steve W.","contributorId":41134,"corporation":false,"usgs":false,"family":"Ross","given":"Steve W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":708000,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rhodes, M.","contributorId":6328,"corporation":false,"usgs":true,"family":"Rhodes","given":"M.","affiliations":[],"preferred":false,"id":708001,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":708002,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70190209,"text":"70190209 - 2017 - Frequencies of decision making and monitoring in adaptive resource management","interactions":[],"lastModifiedDate":"2017-08-21T11:30:54","indexId":"70190209","displayToPublicDate":"2017-08-21T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Frequencies of decision making and monitoring in adaptive resource management","docAbstract":"Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management implications and extensions.","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0182934","usgsCitation":"Williams, B.K., and Johnson, F.A., 2017, Frequencies of decision making and monitoring in adaptive resource management: PLoS ONE, v. 12, no. 8, e0182934; 18 p., https://doi.org/10.1371/journal.pone.0182934.","productDescription":"e0182934; 18 p.","ipdsId":"IP-080475","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469601,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0182934","text":"Publisher Index Page"},{"id":344992,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-11","publicationStatus":"PW","scienceBaseUri":"599bf121e4b0b589267ed333","contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":707990,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":707989,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190180,"text":"70190180 - 2017 - Cross-species transmission potential between wild pigs, livestock, poultry, wildlife, and humans: Implications for disease risk management in North America","interactions":[],"lastModifiedDate":"2017-12-19T16:01:29","indexId":"70190180","displayToPublicDate":"2017-08-21T00:00:00","publicationYear":"2017","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":"Cross-species transmission potential between wild pigs, livestock, poultry, wildlife, and humans: Implications for disease risk management in North America","docAbstract":"Cross-species disease transmission between wildlife, domestic animals and humans is an increasing threat to public and veterinary health. Wild pigs are increasingly a potential veterinary and public health threat. Here we investigate 84 pathogens and the host species most at risk for transmission with wild pigs using a network approach. We assess the risk to agricultural and human health by evaluating the status of these pathogens and the co-occurrence of wild pigs, agriculture and humans. We identified 34 (87%) OIE listed swine pathogens that cause clinical disease in livestock, poultry, wildlife, and humans. On average 73% of bacterial, 39% of viral, and 63% of parasitic pathogens caused clinical disease in other species. Non-porcine livestock in the family Bovidae shared the most pathogens with swine (82%). Only 49% of currently listed OIE domestic swine diseases had published wild pig surveillance studies. The co-occurrence of wild pigs and farms increased annually at a rate of 1.2% with as much as 57% of all farms and 77% of all agricultural animals co-occurring with wild pigs. The increasing co-occurrence of wild pigs with livestock and humans along with the large number of pathogens shared is a growing risk for cross-species transmission.","language":"English","publisher":"Nature","doi":"10.1038/s41598-017-07336-z","usgsCitation":"Miller, R.S., Sweeney, S.J., Slootmaker, C., Grear, D.A., DiSalvo, P.A., Kiser, D., and Shwiff, S.A., 2017, Cross-species transmission potential between wild pigs, livestock, poultry, wildlife, and humans: Implications for disease risk management in North America: Scientific Reports, v. 7, p. 1-14, https://doi.org/10.1038/s41598-017-07336-z.","productDescription":"Article 7821; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-086787","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":469600,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-017-07336-z","text":"Publisher Index Page"},{"id":344998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-10","publicationStatus":"PW","scienceBaseUri":"599bf123e4b0b589267ed33d","contributors":{"authors":[{"text":"Miller, Ryan S.","contributorId":49005,"corporation":false,"usgs":false,"family":"Miller","given":"Ryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":707843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweeney, Steven J.","contributorId":195672,"corporation":false,"usgs":false,"family":"Sweeney","given":"Steven","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":707844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slootmaker, Chris","contributorId":195673,"corporation":false,"usgs":false,"family":"Slootmaker","given":"Chris","email":"","affiliations":[],"preferred":false,"id":707845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":707842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DiSalvo, Paul A.","contributorId":195674,"corporation":false,"usgs":false,"family":"DiSalvo","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":707846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kiser, Deborah","contributorId":195675,"corporation":false,"usgs":false,"family":"Kiser","given":"Deborah","email":"","affiliations":[],"preferred":false,"id":707847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shwiff, Stephanie A.","contributorId":195676,"corporation":false,"usgs":false,"family":"Shwiff","given":"Stephanie","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":707848,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70190200,"text":"70190200 - 2017 - Life histories and conservation of long-lived reptiles, an illustration with the American crocodile (Crocodylus acutus)","interactions":[],"lastModifiedDate":"2017-08-20T10:51:17","indexId":"70190200","displayToPublicDate":"2017-08-20T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Life histories and conservation of long-lived reptiles, an illustration with the American crocodile (Crocodylus acutus)","title":"Life histories and conservation of long-lived reptiles, an illustration with the American crocodile (Crocodylus acutus)","docAbstract":"Management interest in North American birds has increasingly focused on species that breed in Alaska, USA, and Canada, where habitats are changing rapidly in response to climatic and anthropogenic factors. We used a series of hierarchical models to estimate rates of population change in 2 forested Bird Conservation Regions (BCRs) in Alaska based on data from the roadside North American Breeding Bird Survey (BBS) and the Alaska Landbird Monitoring Survey, which samples off-road areas on public resource lands. We estimated long-term (1993–2015) population trends for 84 bird species from the BBS and short-term (2003–2015) trends for 31 species from both surveys. Among the 84 species with long-term estimates, 11 had positive trends and 17 had negative trends in 1 or both BCRs; negative trends were primarily found among aerial insectivores and wetland-associated species, confirming range-wide negative continental trends for many of these birds. Three species with negative trends in the contiguous United States and southern Canada had positive trends in Alaska, suggesting different population dynamics at the northern edges of their ranges. Regional population trends within Alaska differed for several species, particularly those represented by different subspecies in the 2 BCRs, which are separated by rugged, glaciated mountain ranges. Analysis of the roadside and off-road data in a joint hierarchical model with shared parameters resulted in improved precision of trend estimates and suggested a roadside-related difference in underlying population trends for several species, particularly within the Northwestern Interior Forest BCR. The combined analysis highlights the importance of considering population structure, physiographic barriers, and spatial heterogeneity in habitat change when assessing patterns of population change across a landscape as broad as Alaska. Combined analysis of roadside and off-road survey data in a hierarchical framework may be particularly useful for evaluating patterns of population change in relatively undeveloped regions with sparse roadside BBS coverage.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-67.1","usgsCitation":"Handel, C.M., and Sauer, J.R., 2017, Combined analysis of roadside and off-road breeding bird survey data to assess population change in Alaska: Condor, v. 119, no. 3, p. 557-575, https://doi.org/10.1650/CONDOR-17-67.1.","productDescription":"19 p.","startPage":"557","endPage":"575","ipdsId":"IP-085966","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":461428,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-17-67.1","text":"Publisher Index Page"},{"id":438244,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SCO7AN","text":"USGS data release","linkHelpText":"Alaska Landbird Monitoring Survey Dataset"},{"id":344972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"599a9fb1e4b0b589267d58b3","contributors":{"authors":[{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":708029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":708030,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190187,"text":"70190187 - 2017 - The role of the North American Breeding Bird Survey in conservation","interactions":[],"lastModifiedDate":"2017-08-20T10:47:06","indexId":"70190187","displayToPublicDate":"2017-08-20T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"The role of the North American Breeding Bird Survey in conservation","docAbstract":"The North American Breeding Bird Survey (BBS) was established in 1966 in response to a lack of quantitative data on changes in the populations of many bird species at a continental scale, especially songbirds. The BBS now provides the most reliable regional and continental trends and annual indices of abundance available for >500 bird species. This paper reviews some of the ways in which BBS data have contributed to bird conservation in North America over the past 50 yr, and highlights future program enhancement opportunities. BBS data have contributed to the listing of species under the Canadian Species at Risk Act and, in a few cases, have informed species assessments under the U.S. Endangered Species Act. By raising awareness of population changes, the BBS has helped to motivate bird conservation efforts through the creation of Partners in Flight. BBS data have been used to determine priority species and locations for conservation action at regional and national scales through Bird Conservation Region strategies and Joint Ventures. Data from the BBS have provided the quantitative foundation for North American State of the Birds reports, and have informed the public with regard to environmental health through multiple indicators, such as the Canadian Environmental Sustainability Indicators and the U.S. Environmental Protection Agency's Report on the Environment. BBS data have been analyzed with other data (e.g., environmental, land cover, and demographic) to evaluate potential drivers of population change, which have then informed conservation actions. In a few cases, BBS data have contributed to the evaluation of management actions, including informing the management of Mourning Doves (Zenaida macroura), Wood Ducks (Aix sponsa), and Golden Eagles (Aquila chrysaetos). Improving geographic coverage in northern Canada and in Mexico, improving the analytical approaches required to integrate data from other sources and to address variation in detectability, and completing the database, by adding historical bird data at each point count location and pinpointing the current point count locations would further enhance the survey's value.
","language":"English","publisher":"Cooper Ornithological Society","doi":"10.1650/CONDOR-17-62.1","usgsCitation":"Hudson, M.R., Francis, C.M., Campbell, K., Downes, C.M., Smith, A.C., and Pardieck, K.L., 2017, The role of the North American Breeding Bird Survey in conservation: Condor, v. 119, no. 3, p. 526-545, https://doi.org/10.1650/CONDOR-17-62.1.","productDescription":"20 p.","startPage":"526","endPage":"545","ipdsId":"IP-085807","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-17-62.1","text":"Publisher Index Page"},{"id":344979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"599a9fb6e4b0b589267d58b7","contributors":{"authors":[{"text":"Hudson, Marie-Anne R.","contributorId":195235,"corporation":false,"usgs":false,"family":"Hudson","given":"Marie-Anne","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":707868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Francis, Charles M.","contributorId":195680,"corporation":false,"usgs":false,"family":"Francis","given":"Charles","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":707869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, Kate J.","contributorId":191414,"corporation":false,"usgs":false,"family":"Campbell","given":"Kate J.","affiliations":[],"preferred":false,"id":707870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downes, Constance M.","contributorId":195681,"corporation":false,"usgs":false,"family":"Downes","given":"Constance","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":707871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Adam C.","contributorId":195234,"corporation":false,"usgs":false,"family":"Smith","given":"Adam","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":707872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":707867,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187860,"text":"ds1052 - 2017 - The State Geologic Map Compilation (SGMC) geodatabase of the conterminous United States","interactions":[],"lastModifiedDate":"2017-11-27T12:29:07","indexId":"ds1052","displayToPublicDate":"2017-08-18T15:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1052","title":"The State Geologic Map Compilation (SGMC) geodatabase of the conterminous United States","docAbstract":"The State Geologic Map Compilation (SGMC) geodatabase of the conterminous United States (https://doi. org/10.5066/F7WH2N65) represents a seamless, spatial database of 48 State geologic maps that range from 1:50,000 to 1:1,000,000 scale. A national digital geologic map database is essential in interpreting other datasets that support numerous types of national-scale studies and assessments, such as those that provide geochemistry, remote sensing, or geophysical data. The SGMC is a compilation of the individual U.S. Geological Survey releases of the Preliminary Integrated Geologic Map Databases for the United States. The SGMC geodatabase also contains updated data for seven States and seven entirely new State geologic maps that have been added since the preliminary databases were published. Numerous errors have been corrected and enhancements added to the preliminary datasets using thorough quality assurance/quality control procedures. The SGMC is not a truly integrated geologic map database because geologic units have not been reconciled across State boundaries. However, the geologic data contained in each State geologic map have been standardized to allow spatial analyses of lithology, age, and stratigraphy at a national scale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1052","usgsCitation":"Horton, J.D., San Juan, C.A., and Stoeser, D.B., 2017, The State Geologic Map Compilation (SGMC) geodatabase of the conterminous United States (ver. 1.1, August 2017): U.S. Geological Survey Data Series 1052, 46 p., https://doi.org/10.3133/ds1052. ","productDescription":"Report: v, 46 p.; Appendixes 1-9; Data Release","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-076804","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":342653,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WH2N65","text":"USGS Data Release","description":"USGS data release","linkHelpText":"The State Geologic Map Compilation (SGMC) Geodatabase of the Conterminous United States"},{"id":342917,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1052/ds20171052_appendix6.pdf","text":"Appendix 6. LITH_FORM (Lithology Table) Data Dictionary","size":"192 kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1052 Appendix 6"},{"id":342913,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1052/ds20171052_appendix2_v1_1.pdf","text":"Appendix 2. State Geologic Map Compilation Attribute Field Definitions for All Feature Classes and Tables","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1052 Appendix 2"},{"id":342922,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1052/ds20171052_appendix9.pdf ","text":"Appendix 9. State Abbreviations","size":"120kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1052 Appendix 9 6"},{"id":342916,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1052/ds20171052_appendix5.pdf","text":"Appendix 5. DESCRIPTION (SGMC_Structure Feature Class) Data Dictionary","size":"156 kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1052 Appendix5"},{"id":342921,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1052/ds20171052_appendix8.pdf ","text":"Appendix 8. GENERALIZED_LITH (SGMC_Geology Feature Class) Data Dictionary","size":"148 kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1052 Appendix 8"},{"id":342914,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1052/ds20171052_appendix3.pdf","text":"Appendix 3. Age Table Data Dictionary","size":"196 kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1052 Appendix 3"},{"id":344904,"rank":13,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/1052/versionHist.txt","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1052 Version History"},{"id":342900,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1052/ds20171052_appendix1_v1_1.pdf","text":"Appendix 1. State Geologic Maps Bibliography","size":"172 kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1052 Appendix 1"},{"id":342651,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1052/coverthb2.jpg"},{"id":342915,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1052/ds20171052_appendix4.pdf","text":"Appendix 4. LITH1–LITH5 (Lithology Table) Data Dictionary","size":"220 kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1052 Appendix 4"},{"id":342920,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1052/ds20171052_appendix7.pdf","text":"Appendix 7. 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\"}}]}\n","edition":"Version 1.0: Originally posted on June 30, 2017; Version 1.1: August 2017","contact":"Central Mineral and Environmental Resources Science Center
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
The last 2500 years of activity at Kīlauea Volcano (Hawai‘i) have been characterized by centuries-long periods dominated by either effusive or explosive eruptions. The most recent period of explosive activity produced the Keanakāko‘i Tephra (KT; ca. 1500–1820 C.E.) and occurred after the collapse of the summit caldera (1470–1510 C.E.). Previous studies suggest that KT magmas may have ascended rapidly to the surface, bypassing storage in crustal reservoirs. The storage conditions and rapid ascent hypothesis are tested here using chemical zoning in olivine crystals and thermodynamic modeling. Forsterite contents (Fo; [Mg/(Mg + Fe) × 100]) of olivine core and rim populations are used to identify melt components in Kīlauea’s prehistoric (i.e., pre-1823) plumbing system. Primitive (≥Fo88) cores occur throughout the 300+ years of the KT period; they originated from mantle-derived magmas that were first mixed and stored in a deep crustal reservoir. Bimodal olivine populations (≥Fo88 and Fo83–84) record repeated mixing of primitive magmas and more differentiated reservoir components shallower in the system, producing a hybrid composition (Fo85–87). Phase equilibria modeling using MELTS shows that liquidus olivine is not stable at depths >17 km. Thus, calculated timescales likely record mixing and storage within the crust. Modeling of Fe–Mg and Ni zoning patterns (normal, reverse, complex) reveal that KT magmas were mixed and stored for a few weeks to several years before eruption, illustrating a more complex storage history than direct and rapid ascent from the mantle as previously inferred for KT magmas. Complexly zoned crystals also have smoothed compositional reversals in the outer 5–20 µm rims that are out of Fe–Mg equilibrium with surrounding glasses. Diffusion models suggest that these rims formed within a few hours to a few days, indicating that at least one additional, late-stage mixing event may have occurred shortly prior to eruption. Our study illustrates that the lifetimes of KT magmas are more complex than previously proposed, and that most KT magmas did not rise rapidly from the mantle without modification during shallow crustal storage.
","language":"English","publisher":"Springer","doi":"10.1007/s00410-017-1395-4","usgsCitation":"Lynn, K., Garcia, M.O., Shea, T., Costa, F., and Swanson, D., 2017, Timescales of mixing and storage for Keanakāko‘i Tephra magmas (1500-1823 C.E.), Kīlauea Volcano, Hawai‘i: Contributions to Mineralogy and Petrology, v. 172, 76, 20 p., https://doi.org/10.1007/s00410-017-1395-4.","productDescription":"76, 20 p.","ipdsId":"IP-084826","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":464613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.33339726285445,\n 19.47218468157476\n ],\n [\n -155.33339726285445,\n 19.36470404669582\n ],\n [\n -155.18967274036802,\n 19.36470404669582\n ],\n [\n -155.18967274036802,\n 19.47218468157476\n ],\n [\n -155.33339726285445,\n 19.47218468157476\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"172","noUsgsAuthors":false,"publicationDate":"2017-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynn, Kendra J.","contributorId":346804,"corporation":false,"usgs":false,"family":"Lynn","given":"Kendra J.","affiliations":[{"id":82969,"text":"iversity of Delaware","active":true,"usgs":false}],"preferred":false,"id":919929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Michael O.","contributorId":225524,"corporation":false,"usgs":false,"family":"Garcia","given":"Michael","email":"","middleInitial":"O.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":919930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shea, Thomas","contributorId":236886,"corporation":false,"usgs":false,"family":"Shea","given":"Thomas","affiliations":[{"id":47560,"text":"University of Hawaii Manoa","active":true,"usgs":false}],"preferred":false,"id":919931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Costa, Fidel","contributorId":184169,"corporation":false,"usgs":false,"family":"Costa","given":"Fidel","email":"","affiliations":[],"preferred":false,"id":919932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swanson, Donald A. 0000-0002-1680-3591","orcid":"https://orcid.org/0000-0002-1680-3591","contributorId":229682,"corporation":false,"usgs":true,"family":"Swanson","given":"Donald A.","affiliations":[],"preferred":true,"id":919933,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189955,"text":"sir20175022K3 - 2017 - Geologic field-trip guide to Mount Shasta Volcano, northern California","interactions":[{"subject":{"id":70189955,"text":"sir20175022K3 - 2017 - Geologic field-trip guide to Mount Shasta Volcano, northern California","indexId":"sir20175022K3","publicationYear":"2017","noYear":false,"chapter":"K3","title":"Geologic field-trip guide to Mount Shasta Volcano, northern California"},"predicate":"IS_PART_OF","object":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"id":1}],"isPartOf":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"lastModifiedDate":"2019-05-28T12:27:50","indexId":"sir20175022K3","displayToPublicDate":"2017-08-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5022","chapter":"K3","title":"Geologic field-trip guide to Mount Shasta Volcano, northern California","docAbstract":"The southern part of the Cascades Arc formed in two distinct, extended periods of activity: “High Cascades” volcanoes erupted during about the past 6 million years and were built on a wider platform of Tertiary volcanoes and shallow plutons as old as about 30 Ma, generally called the “Western Cascades.” For the most part, the Shasta segment (for example, Hildreth, 2007; segment 4 of Guffanti and Weaver, 1988) of the arc forms a distinct, fairly narrow axis of short-lived small- to moderate-sized High Cascades volcanoes that erupted lavas, mainly of basaltic-andesite or low-silica-andesite compositions. Western Cascades rocks crop out only sparsely in the Shasta segment; almost all of the following descriptions are of High Cascades features except for a few unusual localities where older, Western Cascades rocks are exposed to view along the route of the field trip.
The High Cascades arc axis in this segment of the arc is mainly a relatively narrow band of either monogenetic or short-lived shield volcanoes. The belt generally averages about 15 km wide and traverses the length of the Shasta segment, roughly 100 km between about the Klamath River drainage on the north, near the Oregon-California border, and the McCloud River drainage on the south (fig. 1). Superposed across this axis are two major long-lived stratovolcanoes and the large rear-arc Medicine Lake volcano. One of the stratovolcanoes, the Rainbow Mountain volcano of about 1.5–0.8 Ma, straddles the arc near the midpoint of the Shasta segment. The other, Mount Shasta itself, which ranges from about 700 ka to 0 ka, lies distinctly west of the High Cascades axis. It is notable that Mount Shasta and Medicine Lake volcanoes, although volcanologically and petrologically quite different, span about the same range of ages and bracket the High Cascades axis on the west and east, respectively.
The field trip begins near the southern end of the Shasta segment, where the Lassen Volcanic Center field trip leaves off, in a field of high-alumina olivine tholeiite lavas (HAOTs, referred to elsewhere in this guide as low-potassium olivine tholeiites, LKOTs). It proceeds around the southern, western, and northern flanks of Mount Shasta and onto a part of the arc axis. The stops feature elements of the Mount Shasta area in an approximately chronological order, from oldest to youngest.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022K3","usgsCitation":"Christiansen, R.L., Calvert, A.T., and Grove T.L., 2017, Geologic field-trip guide to Mount Shasta volcano, northern California: U.S. Geological Survey Scientific Investigations Report 2017-5022-K3, 33 p., https://doi.org/10.3133/sir20175022K3.","productDescription":"ix, 33 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-089120","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344950,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K","text":"Scientific Investigations Report 2017-5022-K","description":"SIR 2017-5022-K","linkHelpText":" - Chapter K: Overview for geologic field-trip guides to volcanoes of the Cascades Arc in northern California"},{"id":364156,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k3/sir20175022_k3_geopdf.pdf","text":"Map of field-trip stops at Mount Shasta Volcano","size":"2.5 MB GeoPDF","description":"SIR 2017-5022-K3 GeoPDF","linkHelpText":" - To use the map, users need to download and install a mapping application for smartphone or tablet such as Avenza or Terra Go Toolbar."},{"id":344949,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k3/sir20175022_k3.pdf","text":"Report","size":"25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-K3"},{"id":344952,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K2","text":"Scientific Investigations Report 2017-5022-K2","description":"SIR 2017-5022-K2","linkHelpText":" - Chapter K2: Geologic Field-Trip Guide to the Lassen Segment of the Cascades Arc, Northern California"},{"id":344951,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K1","text":"Scientific Investigations Report 2017-5022-K1","description":"SIR 2017-5022-K1","linkHelpText":" - Chapter K1: Geologic Field-Trip Guide to Medicine Lake Volcano, Northern California, Including Lava Beds National Monument"},{"id":344948,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/k3/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mount Shasta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.40,\n 41\n ],\n [\n -121.92626953124999,\n 41\n ],\n [\n -121.92626953124999,\n 41.5\n ],\n [\n -122.40,\n 41.5\n ],\n [\n -122.40,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered, technically recoverable continuous resources of 35.1 trillion cubic feet of gas in the Amu Darya Basin Province of Turkmenistan, Uzbekistan, Iran, and Afghanistan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173058","usgsCitation":"Schenk, C.J., Tennyson, M.E., Mercier, T.J., Hawkins, S.J., Gaswirth, S.B., Marra, K.R., Klett, T.R., Le, P.A., Brownfield, M.E., and Woodall, C.A., 2017, Assessment of undiscovered continuous gas resources in the Amu Darya Basin Province of Turkmenistan, Uzbekistan, Iran, and Afghanistan, 2017: U.S. Geological Survey Fact Sheet 2017–3058, 2 p., https://doi.org/10.3133/fs20173058.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-087377","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":344910,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20113154","text":"Fact Sheet 2011–3154:","linkHelpText":"Assessment of Undiscovered Oil and Gas Resources of the Amu Darya Basin and Afghan–Tajik Basin Provinces, Afghanistan, Iran, Tajikistan, Turkmenistan, and Uzbekistan, 2011"},{"id":344909,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3058/fs20173058.pdf ","text":"Report","size":"384 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3058"},{"id":344908,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3058/coverthb.jpg"}],"country":"Afghanistan, Iran, Turkmenistan, Uzbekistan","otherGeospatial":" Amu Darya Basin Province ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {\n \"stroke\": \"#555555\",\n \"stroke-width\": 2,\n \"stroke-opacity\": 1,\n \"fill\": \"#555555\",\n \"fill-opacity\": 0.5\n },\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 56.920654296875,\n 32.72355492704221\n ],\n [\n 68.6650390625,\n 32.72355492704221\n ],\n [\n 68.6650390625,\n 42.28606238749825\n ],\n [\n 56.920654296875,\n 42.28606238749825\n ],\n [\n 56.920654296875,\n 32.72355492704221\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
This field-trip guide provides an overview of Quaternary volcanism in and around Lassen Volcanic National Park, California, emphasizing the stratigraphy of the Lassen Volcanic Center. The guide is designed to be self-guided and to focus on geologic features and stratigraphy that can be seen easily from the road network.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022K2","usgsCitation":"Clynne, M.A., and Muffler, L.J.P., 2017, Geologic field-trip guide to the Lassen segment of the Cascades Arc, northern California: U.S. Geological Survey Scientific Investigations Report 2017–5022–K2, 65 p., https://doi.org/10.3133/sir20175022K2.","productDescription":"Report: ix, 65 p.; 4 Related Works","numberOfPages":"78","onlineOnly":"Y","ipdsId":"IP-089119","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344955,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K3","text":"Scientific Investigations Report 2017-5022-K3","description":"SIR 2017-5022-K3","linkHelpText":" - Chapter K3: Geologic Field-Trip Guide to Mount Shasta Volcano, Northern California"},{"id":344933,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k2/sir20175022k2.pdf","text":"Report","size":"45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-K2"},{"id":344936,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K","text":"Scientific Investigations Report 2017-5022-K","description":"SIR 2017-5022-K","linkHelpText":" - Chapter K: Overview for geologic field-trip guides to volcanoes of the Cascades Arc in northern California"},{"id":344940,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K1","text":"Scientific Investigations Report 2017-5022-K1","description":"SIR 2017-5022-K1","linkHelpText":" - Chapter K1: Geologic Field-Trip Guide to Medicine Lake Volcano, Northern California, Including Lava Beds National Monument"},{"id":344932,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/k2/coverthb.jpg"},{"id":362964,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k2/sir20175022k2_lassen_geopdf.pdf","text":"Map of field-trip stops in the Lassen segment of the Cascades Arc","size":"3 MB GeoPDF","description":"SIR 2017-5022-K2","linkHelpText":" - To use the map, users need to download and install a mapping application for smartphone or tablet such as Avenza or Terra Go Toolbar."}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 40\n ],\n [\n -120,\n 40\n ],\n [\n -120,\n 41\n ],\n [\n -122,\n 41\n ],\n [\n -122,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
We examined the relationship between local- (wetland) and landscape-level factors and breeding bird abundances on 1,190 depressional wetlands in the Prairie Pothole Region of North and South Dakota during the breeding seasons in 1995–97. The surveyed wetlands were selected from five wetland classes (alkali, permanent, semipermanent, seasonal, or temporary), two wetland types (natural or restored), and two landowner groups (private or Federal). We recorded 133 species of birds in the surveyed wetlands during the 3 years. We analyzed the nine most common (or focal) species (that is, species that were present in 25 percent or more of the 1,190 wetlands): the Red-winged Blackbird (Agelaius phoeniceus), Blue-winged Teal (Anas discors), Mallard (Anas platyrhynchos), American Coot (Fulica americana), Gadwall (Anas strepera), Common Yellowthroat (Geothlypis trichas), Yellow-headed Blackbird (Xanthocephalus xanthocephalus), Northern Shoveler (Anas clypeata), and Savannah Sparrow (Passerculus sandwichensis). Our results emphasize the ecological value of all wetland classes, natural and restored wetlands, and publicly and privately owned wetlands in this region, including wetlands that are generally smaller and shallower (that is, temporary and seasonal wetlands) and thus most vulnerable to drainage. Blue-winged Teal, Northern Shoveler, Gadwall, Common Yellowthroat, and Red-winged Blackbird had higher abundances on Federal than on private wetlands. Abundances differed among wetland classes for seven of the nine focal species: Blue-winged Teal, Northern Shoveler, Mallard, American Coot, Common Yellowthroat, Yellow-headed Blackbird, Red-winged Blackbird. American Coot had higher abundances on restored wetlands than on natural wetlands overall, and Gadwall and Common Yellowthroat had higher abundances on private restored wetlands than on private natural wetlands. The Common Yellowthroat was the only species that had higher abundances on restored private wetlands than on restored Federal wetlands. After adjusting for wetland size and the date and location of the surveys, our results demonstrated that incorporating wetland- and landscape-level factors in models can improve our ability to predict abundances of wetland birds in this region. The top model for eight of the nine focal species included wetland- and landscape-level factors, whereas the best model for Blue-winged Teal included only wetland-level attributes. Although local factors (for example, percent open water or emergent vegetation) in individual wetlands are important factors for some wetland breeding birds, it is important that natural resource managers consider landscape-level factors beyond the local factors in their conservation plans for wetland birds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171096","usgsCitation":"Igl, L.D., Shaffer, J.A., Johnson, D.H., and Buhl, D.A., 2017, The influence of local- and landscape-level factors on wetland breeding birds in the Prairie Pothole Region of North and South Dakota: U.S. Geological Survey Open-File Report 2017–1096, 65 p., https://doi.org/10.3133/ofr20171096.","productDescription":"Report: vii, 65 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-086062","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":344903,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FX77XM","text":"USGS Data Release","linkHelpText":"The influence of local- and landscape-level factors on wetland breeding birds in the Prairie Pothole Region of North and South Dakota 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U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Medicine Lake volcano is among the very best places in the United States to see and walk on a variety of well-exposed young lava flows that range in composition from basalt to rhyolite. This field-trip guide to the volcano and to Lava Beds National Monument, which occupies part of the north flank, directs visitors to a wide range of lava flow compositions and volcanic phenomena, many of them well exposed and Holocene in age. The writing of the guide was prompted by a field trip to the California Cascades Arc organized in conjunction with the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI) quadrennial meeting in Portland, Oregon, in August of 2017. This report is one of a group of three guides describing the three major volcanic centers of the southern Cascades Volcanic Arc. The guides describing the Mount Shasta and Lassen Volcanic Center parts of the trip share an introduction, written as an overview to the IAVCEI field trip. However, this guide to Medicine Lake volcano has descriptions of many more stops than are included in the 2017 field trip. The 23 stops described here feature a range of compositions and volcanic phenomena. Many other stops are possible and some have been previously described, but these 23 have been selected to highlight the variety of volcanic phenomena at this rear-arc center, the range of compositions, and for the practical reason that they are readily accessible. Open ground cracks, various vent features, tuffs, lava-tube caves, evidence for glaciation, and lava flows that contain inclusions and show visible evidence of compositional zonation are described and visited along the route.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022K1","usgsCitation":"Donnelly-Nolan, J.M., and Grove, T.L., 2017, Geologic field-trip guide to Medicine Lake Volcano, northern California, including Lava Beds National Monument: U.S. Geological Survey Scientific Investigations Report 2017–5022–K1, 53 p., https://doi.org/10.3133/sir20175022K1.","productDescription":"Report: ix, 53 p.; 3 Related Works","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-089118","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344930,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K","text":"Scientific Investigations Report 2017-5022-K","description":"SIR 2017-5022-K","linkHelpText":" - Chapter K: Overview for geologic field-trip guides to volcanoes of the Cascades Arc in northern California"},{"id":344914,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k1/sir20175022k1.pdf","text":"Report","size":"41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-K1"},{"id":344913,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/k1/coverthb.jpg"},{"id":362962,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k1/sir20175022k1_medlake_geopdf.pdf","text":"Map of field-trip stops near Medicine Lake ","size":"11 MB GeoPDF","description":"SIR-20175022-K1","linkHelpText":" - To use the map, users need to download and install a mapping application for smartphone or tablet such as Avenza or Terra Go Toolbar."},{"id":344939,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K2","text":"Scientific Investigations Report 2017-5022-K2","description":"SIR 2017-5022-K2","linkHelpText":" - Chapter K2: Geologic Field-Trip Guide to the Lassen Segment of the Cascades Arc, Northern California"},{"id":362963,"rank":7,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k1/sir20175022k1_lavabeds_geopdf.pdf","text":"Map of field-trip stops in Lava Beds National Monument","size":"6 MB GeoPDF","description":"SIR-20175022-K1","linkHelpText":" - To use the map, users need to download and install a mapping application for smartphone or tablet such as Avenza or Terra Go Toolbar."},{"id":344954,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K3","text":"Scientific Investigations Report 2017-5022-K3","description":"SIR 2017-5022-K3","linkHelpText":" - Chapter K3: Geologic Field-Trip Guide to Mount Shasta Volcano, Northern California"}],"country":"United States","state":"California","otherGeospatial":"Medicine Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.7401885986328,\n 41.43140151372244\n ],\n [\n -121.41815185546875,\n 41.43140151372244\n ],\n [\n -121.41815185546875,\n 41.68163038712496\n ],\n [\n -121.7401885986328,\n 41.68163038712496\n ],\n [\n -121.7401885986328,\n 41.43140151372244\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
Solar photovoltaic (PV) and wind turbine technologies are projected to make up an increasing proportion of electricity generation capacity in the United States in the coming decades. By 2050, they will account for 36 percent (or 566 gigawatts) of capacity compared with about 11 percent (or 118 gigawatts) in 2016 (fig. 1; EIA, 2017).
There are several different types of commercial solar PV and wind turbine technologies, and each type makes use of different minor metals. “Minor metal” is the term used for metals for which world production is small compared with the more widely produced base metals, and they are often produced as byproducts of the mining or processing of base metals. Minor metals used in renewable energy technologies often have complex supply chains, are often produced primarily outside of the United States, and are also used in many other applications. A larger amount of minor metals will be needed in the future to support the projected increases in solar PV and wind energy production capacity (Nassar and others, 2016).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173061","usgsCitation":"Singerling, S.A., and Nassar, N.T., 2017, Minor metals and renewable energy—Diversifying America’s energy sources: U.S. Geological Survey Fact Sheet 2017–3061, 2 p., https://doi.org/10.3133/fs20173061.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-086064","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":344580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3061/coverthb2.jpg"},{"id":344585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3061/fs20173061.pdf","text":"Report","size":"453 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3061"}],"country":"United States","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
An accurate inventory of irrigated crop acreage is not available at the level of resolution needed to better estimate agricultural water use or to project future water demands in many Florida counties. A detailed digital map and summary of irrigated acreage was developed for Polk County, Florida, during the 2016 growing season. This cooperative project between the U.S. Geological Survey and the Office of Agricultural Water Policy of the Florida Department of Agriculture and Consumer Services is part of an effort to improve estimates of water use and projections of future demands across all counties in the State. The irrigated areas were delineated by using land-use data provided by the Florida Department of Agriculture and Consumer Services, along with information obtained from the South and Southwest Florida Water Management Districts consumptive water-use permits. Delineations were field verified between April and December 2016. Attribute data such as crop type, primary water source, and type of irrigation system were assigned to the irrigated areas.
The results of this inventory and field verification indicate that during the 2016 growing seasons (spring, summer, fall, and winter), an estimated 88,652 acres were irrigated within Polk County. Of the total field-verified crops, 83,995 acres were in citrus; 2,893 acres were in other non-citrus fruit crops (blueberries, grapes, peaches, and strawberries); 621 acres were in row crops (primarily beans and watermelons); 1,117 acres were in nursery (container and tree farms) and sod production; and 26 acres were in field crops including hay and pasture. Of the total inventoried irrigated acreage within Polk County, 98 percent (86,566 acres) was in the Southwest Florida Water Management District, and the remaining 2 percent (2,086 acres) was in the South Florida Water Management District.
About 85,788 acres (96.8 percent of the acreage inventoried) were irrigated by a microirrigation system, including drip, bubblers, and spray emitters. The remaining 3.2 percent of the irrigated acreage was irrigated by a sprinkler system (2,360 acres) or subsurface flood systems (504 acres). Groundwater was the primary source of water used on irrigated acreage (88 percent, or 78,050 acres); the remaining 10,602 acres (12 percent) used groundwater combined with surface water as the irrigation source.
The irrigated acreage estimated by the U.S. Geological Survey (USGS) for this 2016 inventory (88,652 acres) is about 11 percent higher than the 79,869 acres estimated by the U.S. Department of Agriculture (USDA) for 2012. Citrus and pasture in Polk County show the biggest difference in irrigated acreage between the USGS and USDA totals. Irrigated citrus acreage inventoried in 2016 by the USGS totaled 83,996 acres, whereas the USDA reported 78,305 acres of citrus in 2012. The USGS identified 6 acres of irrigated pasture and 20 acres of hay, whereas the USDA reported 6,631 acres of irrigated pasture and 1,349 acres of hay for 2012. In general, differences between the 2016 USGS field-verified acreage totals and acreage published by the USDA for 2012 could be due to (1) irrigated acreage for some specific crops increased or decreased substantially during the 4-year interval between 2012 and 2016 because of production or economic changes, (2) the assumption that if an irrigation system was present, it was used in 2016, when in fact some landowners may not have used their irrigation systems during this growing period even if they had a crop in the field, or (3) the amount of irrigated acreage published by the USDA for selected crops may be underestimated as a result of how information is obtained and formulated by the agency during census compilations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171082","collaboration":"Prepared in cooperation with the Florida Department of Agriculture and Consumer Services Office of Agricultural Water Policy","usgsCitation":"Marella, R.L., Berry, D.R., and Dixon, J.F., 2017, Agricultural irrigated land-use inventory for Polk County, Florida, 2016: U.S. Geological Survey Open-File Report 2017–1082, 14 p., https://doi.org/10.3133/ofr20171082.","productDescription":"14 p.","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080915","costCenters":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"links":[{"id":344885,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1082/coverthb.jpg"},{"id":344888,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76W98BN","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"GIS data and tables associated with irrigated agricultural land use survey in Polk County, Florida, 2016"},{"id":344886,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1082/ofr20171082.pdf","text":"Report","size":"823 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1082"},{"id":344887,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1082/ofr20171082_Appendix01.pdf","text":"Appendix 1","size":"1.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1082 Appendix 1"}],"country":"United 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Caribbean-Florida Science Center
U.S. Geological Survey
12703 Research Parkway
Orlando, Florida 32826
Historical data for six selected U.S. Geological Survey streamgages along Soldier Creek in northeast Kansas were used in an assessment of streamflow characteristics and trends. This information is required by the Prairie Band Potawatomi Nation for the effective management of tribal water resources, including drought contingency planning. Streamflow data for the period of record at each streamgage were used to assess annual mean streamflow, annual mean base flow, mean monthly flow, annual peak flow, and annual minimum flow.
Annual mean streamflows along Soldier Creek were characterized by substantial year-to-year variability with no pronounced long-term trends. On average, annual mean base flow accounted for about 20 percent of annual mean streamflow. Mean monthly flows followed a general seasonal pattern that included peak values in spring and low values in winter. Annual peak flows, which were characterized by considerable year-to-year variability, were most likely to occur in May and June and least likely to occur during November through February. With the exception of a weak yet statistically significant increasing trend at the Soldier Creek near Topeka, Kansas, streamgage, there were no pronounced long-term trends in annual peak flows. Annual 1-day, 30-day, and 90-day mean minimum flows were characterized by considerable year-to-year variability with no pronounced long-term trend. During an extreme drought, as was the case in the mid-1950s, there may be zero flow in Soldier Creek continuously for a period of one to several months.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175061","collaboration":"Prepared in cooperation with the Prairie Band Potawatomi Nation","usgsCitation":"Juracek, K.E., 2017, Streamflow characteristics and trends along Soldier Creek, northeast Kansas: U.S. Geological Survey Scientific Investigations Report 2017–5061, 30 p., https://doi.org/10.3133/sir20175061.","productDescription":"v, 30 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-084908","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":344845,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5061/coverthb.jpg"},{"id":344846,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5061/sir20175061.pdf","text":"Report","size":"5.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5061"}],"country":"United States","state":"Kansas","otherGeospatial":"Soldier Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.2896728515625,\n 38.94018471320357\n ],\n [\n -95.2734375,\n 38.94018471320357\n ],\n [\n -95.2734375,\n 39.8928799002948\n ],\n [\n -96.2896728515625,\n 39.8928799002948\n ],\n [\n -96.2896728515625,\n 38.94018471320357\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
Most of the land-surface subsidence in the Houston-Galveston region, Texas, has occurred as a direct result of groundwater withdrawals for municipal supply, commercial and industrial use, and irrigation that depressured and dewatered the Chicot and Evangeline aquifers, thereby causing compaction of the aquifer sediments, mostly in the fine-grained silt and clay layers. This report, prepared by the U.S. Geological Survey in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District, is one in an annual series of reports depicting water-level altitudes and water-level changes in the Chicot, Evangeline, and Jasper aquifers and measured cumulative compaction of subsurface sediments in the Chicot and Evangeline aquifers in the Houston-Galveston region. This report contains regional-scale maps depicting approximate 2017 water-level altitudes (represented by measurements made during December 2016 through March 2017) and long-term water-level changes for the Chicot, Evangeline, and Jasper aquifers; a map depicting locations of borehole-extensometer (hereinafter referred to as “extensometer”) sites; and graphs depicting measured long-term cumulative compaction of subsurface sediments at the extensometers during 1973–2016.
In 2017, water-level-altitude contours for the Chicot aquifer ranged from 200 feet (ft) below the North American Vertical Datum of 1988 (hereinafter referred to as “datum”) in two localized areas in southwestern and northwestern Harris County to 200 ft above datum in west-central Montgomery County. The largest water-level-altitude decline (120 ft) depicted by the 1977–2017 water-level-change contours for the Chicot aquifer was in northwestern Harris County. A broad area where water-level altitudes declined in the Chicot aquifer extends from northwestern, north-central, and southwestern Harris County across parts of north-central, eastern, and south-central Fort Bend County into southeastern Waller County. Adjacent to the areas where water levels declined was a broad area where water levels rose in central, eastern, and southeastern Harris County, most of Galveston County, eastern and northernmost Brazoria County, and northeastern Fort Bend County. The largest rise (200 ft) in water-level altitudes in the Chicot aquifer from 1977 to 2017 was in southeastern Harris County.
The water-level-altitude contours for the Evangeline aquifer in 2017 indicated two areas where the water-level altitudes were 250 ft below datum—one area extending from south-central Montgomery County into north-central Harris County and another area in western Harris County. Water-level altitudes in the Evangeline aquifer ranged from 50 to 200 ft below datum throughout most of Harris County in 2017. In Montgomery County, water-level altitudes in the Evangeline aquifer in 2017 ranged from the aforementioned area where they were 250 ft below datum to an area where they were 200 ft above datum in the northwestern part of the county. The 1977–2017 water-level-change contours for the Evangeline aquifer depict a broad area where water-level altitudes declined in north-central Harris and south-central Montgomery Counties, extending through north-central, northwestern, and southwestern Harris County into western Liberty, southeastern and northeastern Waller, and northeastern and east-central Fort Bend Counties. The largest water-level-altitude decline (280 ft) was in north-central Harris and south-central Montgomery Counties. Water-level altitudes rose in a broad area from central, east-central, and southern Harris County extending into the northernmost part of Brazoria County, the northernmost part of Galveston County, and the southwestern area of Liberty County. The largest rise in water-level altitudes in the Evangeline aquifer from 1977 to 2017 (240 ft) was in southeastern Harris County.
Water-level-altitude contours for the Jasper aquifer in 2017 ranged from 200 ft below datum in three isolated areas of south-central Montgomery County (the westernmost of these areas extended slightly into north-central Harris County) to 250 ft above datum in extreme northwestern Montgomery County, northeastern Grimes County, and southwestern Walker County. The 2000–17 water-level-change contours for the Jasper aquifer depict water-level declines in a broad area throughout most of Montgomery County and in parts of Waller, Grimes, and Harris Counties, with the largest decline (220 ft) in an isolated area in south-central Montgomery County.
Compaction of subsurface sediments (mostly in the fine-grained silt and clay layers) in the Chicot and Evangeline aquifers was recorded continuously by using 13 extensometers at 11 sites that were either activated or installed between 1973 and 1980. During the period of record beginning in 1973 (or later depending on activation or installation date) and ending in late November or December 2016, measured cumulative compaction at the 13 extensometers ranged from 0.096 ft at the Texas City-Moses Lake extensometer to 3.700 ft at the Addicks extensometer. From January through late November or December 2016, the Addicks, Lake Houston, Southwest, and Northeast extensometers recorded net decreases in land-surface elevation, but the Baytown C–1 (shallow), Baytown C–2 (deep), Clear Lake (shallow), Clear Lake (deep), East End, Johnson Space Center, Pasadena, Seabrook, and Texas City-Moses Lake extensometers recorded net increases in land-surface elevation.
The rate of compaction varies from site to site because of differences in rates of groundwater withdrawal in the areas adjacent to each extensometer site; differences among sites in the ratios of sand, silt, and clay and their corresponding compressibilities; and previously established preconsolidation heads. It is not appropriate, therefore, to extrapolate or infer a rate of compaction for an adjacent area on the basis of the rate of compaction recorded by proximal extensometers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175080","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District","usgsCitation":"Kasmarek, M.C., and Ramage, J.K., 2017, Water-level altitudes 2017 and water-level changes in the Chicot, Evangeline, and Jasper aquifers and compaction 1973–2016 in the Chicot and Evangeline aquifers, Houston-Galveston region, Texas: U.S. Geological Survey Scientific Investigations Report 2017–5080, 32 p., https://doi.org/10.3133/sir20175080. ","productDescription":"Report: vii, 32 p.; Data Releases","numberOfPages":"44","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-083843","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":344822,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77S7M18","text":"USGS - Data Release","description":"USGS Data Release","linkHelpText":"Water-level measurement data, water-level altitude and long-term water-level altitude change contours (2017) in the Chicot, Evangeline, and Jasper aquifers, Houston-Galveston region, Texas"},{"id":344820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5080/coverthb.jpg"},{"id":344823,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PC30KC","text":"USGS - Data Release","description":"USGS Data Release","linkHelpText":"Cumulative compaction of subsurface sediments (2016) in 13 extensometers completed in the Chicot and Evangeline aquifers in the Houston-Galveston region, Texas"},{"id":344821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5080/sir20175080.pdf","text":"Report","size":"16.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5080"}],"country":"United States","state":"Texas","city":"Galveston, Houston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.339111328125,\n 28.372068829631633\n ],\n [\n -96.21826171874999,\n 28.44937385955666\n ],\n [\n -95.965576171875,\n 28.58452171937042\n ],\n [\n -95.77880859375,\n 28.65203063036226\n ],\n [\n -95.592041015625,\n 28.719496107557465\n ],\n [\n -95.4052734375,\n 28.825425374477224\n ],\n [\n -95.185546875,\n 28.950475674848008\n ],\n [\n -95.00976562499999,\n 29.094577077511826\n ],\n [\n -94.833984375,\n 29.23847708592805\n ],\n [\n -94.68017578125,\n 29.401319510041485\n ],\n [\n -94.482421875,\n 29.477861195816843\n ],\n [\n -94.19677734375,\n 29.611670115197377\n ],\n [\n -93.966064453125,\n 29.6594160549124\n ],\n [\n -93.80126953124999,\n 29.707139348134145\n ],\n [\n -93.900146484375,\n 29.850173125689896\n ],\n [\n -93.89465332031249,\n 29.888280933159265\n ],\n [\n -93.88916015625,\n 29.92637417863576\n ],\n [\n -93.768310546875,\n 29.964452850852005\n ],\n [\n -93.75732421875,\n 30.021543509740027\n ],\n [\n -93.74633789062499,\n 30.088107753367257\n ],\n [\n -93.724365234375,\n 30.287531589298727\n ],\n [\n -93.74633789062499,\n 30.391830328088137\n ],\n [\n -93.75732421875,\n 30.56226095049944\n ],\n [\n -93.66943359374999,\n 30.675715404167743\n ],\n [\n -93.592529296875,\n 30.826780904779774\n ],\n [\n -93.53759765625,\n 31.015278981711266\n ],\n [\n -93.53759765625,\n 31.147006308556566\n ],\n [\n -93.62548828125,\n 31.27855085894653\n ],\n [\n -93.7353515625,\n 31.512995857454676\n ],\n [\n -93.779296875,\n 31.606609719226917\n ],\n [\n -93.812255859375,\n 31.774877618507386\n ],\n [\n -93.900146484375,\n 31.87755764334002\n ],\n [\n -93.98803710937499,\n 31.952162238024975\n ],\n [\n -94.053955078125,\n 31.99875937194732\n ],\n [\n -94.053955078125,\n 32.32427558887655\n ],\n [\n -95.416259765625,\n 32.16631295696736\n ],\n [\n -96.580810546875,\n 32.03602003973755\n ],\n [\n -96.96533203125,\n 31.970803930433096\n ],\n [\n -96.339111328125,\n 28.372068829631633\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
Human perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research.
Mapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models.
Challenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.
These field-trip guides were written for the occasion of the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI) quadrennial scientific assembly in Portland, Oregon, in August 2017. The guide to Mount Mazama and Crater Lake caldera is an updated and expanded version of the guide (Bacon, 1989) for part of an earlier IAVCEI trip to the southern Cascade Range. The guide to Newberry Volcano describes the stops included in the 2017 field trip. Crater Lake and Newberry are the two best-preserved and most recent calderas in the Cascades Volcanic Arc. Although located in different settings in the arc, with Crater Lake on the arc axis and Newberry in the rear-arc, both volcanoes are located at the intersection of the arc and the northwest corner region of the extensional Basin and Range Province.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022J","usgsCitation":"Bacon, C.R., Donnelly-Nolan, J.M., Jensen, R.A., and Wright, H.M., 2017, Overview for Geologic Field-Trip Guides to Mount Mazama, Crater Lake Caldera, and Newberry Volcano, Oregon: U.S. Geological Survey Scientific Investigations Report 2017–5022–J, 3 p., https://doi.org/10.3133/sir20175022J.","productDescription":"vii, 3 p.","numberOfPages":"5","onlineOnly":"Y","ipdsId":"IP-089109","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344907,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/j/sir2017-5022j.pdf","text":"Report","size":"5.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-J"},{"id":344906,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/j/coverthb.jpg"},{"id":344956,"rank":3,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/sir20175022J1","text":"Scientific Investigations Report 2017-5022-J1","description":"SIR 2017-5022-J1","linkHelpText":" - Chapter J1: Geologic field trip guide to Mount Mazama and Crater Lake Caldera, Oregon"},{"id":344957,"rank":4,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/sir20175022J2","text":"Scientific Investigations Report 2017-5022-J2","description":"SIR 2017-5022-J2","linkHelpText":" - Chapter J2: Field-trip guide to the geologic highlights of Newberry Volcano, Oregon"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.21716308593749,\n 42.23665188032057\n ],\n [\n -120.08056640625,\n 42.25291778330197\n ],\n [\n -120.047607421875,\n 44.82860426955568\n ],\n [\n -123.21716308593749,\n 44.83249999349062\n ],\n [\n -123.21716308593749,\n 42.23665188032057\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025