The U.S. Geological Survey in cooperation with the Colorado Water Conservation Board and the Upper Big Sandy Groundwater Management District carried out a study in 2016 to evaluate potential groundwater storage changes within the Upper Big Sandy Designated Groundwater Basin (UBSDGB) alluvial aquifer, including groundwater flow between the UBSDGB alluvial aquifer and the Denver Basin bedrock aquifers. The UBSDGB alluvial aquifer is located along the ephemeral Big Sandy Creek on the east-central edge of the Denver Basin aquifer system and covers an area of about 66,560 acres within the UBSDGB. The UBSDGB alluvial aquifer consists of unconsolidated Quaternary sand and gravel deposits that contain an unconfined (water table) groundwater system. The western three-fourths of the UBSDGB alluvial aquifer overlies the Tertiary and Cretaceous bedrock formations that compose the Denver Basin aquifer system. The updated water budget for the UBSDGB alluvial aquifer, including annual change in groundwater storage in 2016, was determined by combining water-budget information from an existing Denver Basin model for about three-fourths of the study area with best estimates for the major water-budget components for the area outside the Denver Basin aquifer system. The western part of the UBSDGB was included in the Denver Basin model (modeled area), whereas the eastern part of the UBSDGB was not included in the Denver Basin model (unmodeled area). The water-budget components were first estimated for the modeled area using outputs from the Denver Basin model, which uses the modular finite-difference groundwater flow computer model MODFLOW-2000 with 1-mile grid cells. For this study, the Denver Basin model was updated with additional data from 2004 through 2016 to generate current (2016) estimates of water consumption in the UBSDGB alluvial aquifer. A basin-specific water budget for the UBSDGB alluvial aquifer from the Denver Basin model was computed using a modeling tool called ZONEBUDGET. The modeled area groundwater budget, along with previous studies, was used to estimate a groundwater budget for the unmodeled area, and results for the modeled and unmodeled areas were combined for an overall water-budget estimate for the entire UBSDGB alluvial aquifer.
The net groundwater flow into the basin from adjacent alluvial aquifers was positive with flow entering the UBSDGB alluvial aquifer. Combining the total inflow from adjacent alluvial and the total outflow to adjacent alluvial aquifers resulted in a net flow from adjacent alluvial aquifers to UBSDGB alluvial aquifer of 5,125 acre-feet (ac-ft) in 2016. The net flow between the underlying bedrock aquifers and the UBSDGB alluvial aquifer was positive with flow entering the UBSDGB alluvial aquifer from the bedrock aquifers. The net flow from the bedrock aquifers to the UBSDGB alluvial aquifer was 347 ac-ft in 2016. Net recharge (precipitation and irrigation return flows minus evaporation) into the UBSDGB alluvial aquifer was negative with groundwater being removed from the UBSDGB alluvial aquifer over the total area of the basin. Combining the total inflow from recharge to the UBSDGB alluvial aquifer of 11,153 ac-ft in 2016 and the total evapo-transpiration of −11,656 ac-ft from the UBSDGB alluvial aquifer in 2016 resulted in a net recharge from UBSDGB alluvial aquifer of −503 ac-ft in 2016. Combining the modeled and unmodeled well pumping resulted in a total well pumping volume of −3,735 ac-ft in 2016 from the UBSDGB alluvial aquifer. The net groundwater flow to the stream network in the basin was negative with flow discharging from the UBSDGB alluvial aquifer into streams. Combining the total inflow from streams and the total outflow to streams for the UBSDGB alluvial aquifer resulted in −1,032 ac-ft in 2016 that was lost to the stream network in the UBSDGB. The net groundwater flow out of the UBSDGB was negative with flow leaving the UBSDGB alluvial aquifer. Combining the total area inflow to the basin from upgradient areas and the total area outflow from the basin for the UBSDGB alluvial aquifer resulted in a net flow out of the basin of −2,300 ac-ft. In the annual groundwater budget for 2016, groundwater storage in the UBSDGB alluvial aquifer system was removed because annual groundwater outflows from storage exceeded groundwater inflows to storage; in other words, water was removed from storage to balance the annual water budget. Combining the net flow from storage for the modeled area of 73 ac-ft and the inflow from storage for the unmodeled area of 2,025 ac-ft resulted in a net positive flow from storage of the UBSDGB alluvial aquifer of 2,098 ac-ft.
Increased pumping since 1958 in the Denver and upper Arapahoe aquifers, not necessarily in the UBSDGB, has caused a change in flow from bedrock units, which were minor or non-contributors of inflow to the UBSDGB alluvial aquifer, to receiving outflow from the UBSDGB alluvial aquifer. Since 2000, aquifer storage has been an inflow component of the water budget, which means that outflow from the modeled area exceeded inflow for the UBSDGB alluvial aquifer. Increased recharge from wetter than average years could replenish the UBSDGB alluvial aquifer. From 2003 through 2016, 13 of the 25 observation wells completed in the UBSDGB alluvial aquifer had a decline in the groundwater-level elevation with an average decline of −2.21 feet, and 12 of the 25 observation wells had an increase in the groundwater-level elevation with an average increase of 1.54 feet. In general, wells at the eastern and western edges of the UBSDGB showed an increase in groundwater-level elevation that appears related to areas of groundwater discharge from the lower Dawson and Laramie-Fox Hills bedrock aquifers to the UBSDGB alluvial aquifer. The remaining wells exhibited water-level declines. Future work could include the development of a basin-specific model to serve as a basin management tool for modeling changes in groundwater levels and storage under various future groundwater recharge and withdrawal scenarios.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195049","collaboration":"Prepared in cooperation with the Colorado Water Conservation Board and the Upper Big Sandy Groundwater Management District","usgsCitation":"Kohn, M.S., Oden, J.H., and Arnold, L.R., 2019, Water-budget analysis of the Upper Big Sandy Designated Ground-water Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016: U.S. Geological Survey Scientific Investigations Report 2019-5049, 25 p., https://dx.doi.org/10.3133/sir20195049.","productDescription":"Report: vi, 25 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-091541","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":365584,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5049/sir20195049.pdf","text":"Report","size":"7.12 M","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5049"},{"id":365581,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5049/coverthb.jpg"},{"id":365748,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DEOYGZ","text":"USGS data release","linkHelpText":"MODFLOW2000 model and ZONEBUDGET computer program used to simulate the Upper Big Sandy Designated Groundwater Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016"}],"country":"United States","state":"Colorado","county":"Elbert County, El Paso County, Lincoln County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.054,38.523],[-104.1629,38.5215],[-104.2759,38.5204],[-104.2794,38.5205],[-104.2836,38.5201],[-104.3759,38.52],[-104.4971,38.5192],[-104.6071,38.5187],[-104.7171,38.5186],[-104.736,38.5183],[-104.8295,38.5183],[-104.943,38.5175],[-104.9432,38.5479],[-104.943,38.5624],[-104.9429,38.6041],[-104.9427,38.6186],[-104.9429,38.6467],[-104.9429,38.6503],[-104.9427,38.6621],[-104.9427,38.6648],[-104.9428,38.6938],[-104.9399,38.6938],[-104.9386,38.7808],[-104.939,38.7949],[-105.0671,38.7946],[-105.0674,38.8666],[-105.0502,38.8665],[-105.0296,38.8668],[-105.026,39.0413],[-105.032,39.1311],[-104.9371,39.1312],[-104.9175,39.131],[-104.8303,39.1311],[-104.6642,39.1308],[-104.6638,39.2165],[-104.664,39.3026],[-104.663,39.3892],[-104.6626,39.4762],[-104.6627,39.5665],[-104.6054,39.5663],[-104.5374,39.5655],[-104.4927,39.5636],[-104.4891,39.5636],[-104.4742,39.5629],[-104.3841,39.5627],[-104.3763,39.5631],[-104.2695,39.5639],[-104.2647,39.5638],[-104.1602,39.5646],[-104.1543,39.565],[-104.0468,39.5652],[-104.0427,39.5651],[-103.9305,39.5646],[-103.9293,39.5646],[-103.8189,39.5646],[-103.8129,39.5649],[-103.7126,39.5649],[-103.7066,39.5648],[-103.6004,39.5646],[-103.595,39.5645],[-103.4882,39.5647],[-103.4804,39.5645],[-103.3748,39.5651],[-103.3658,39.5654],[-103.2631,39.5659],[-103.253,39.5657],[-103.1533,39.5657],[-103.1539,39.475],[-103.1537,39.3879],[-103.1542,39.3009],[-103.154,39.2147],[-103.1527,39.1258],[-103.161,39.1255],[-103.1615,39.0376],[-103.1626,38.9492],[-103.163,38.863],[-103.1634,38.7765],[-103.1638,38.6912],[-103.1709,38.6909],[-103.1705,38.6837],[-103.1731,38.6796],[-103.1716,38.6111],[-103.1714,38.5236],[-103.2809,38.5224],[-103.3897,38.5239],[-103.5086,38.5236],[-103.5089,38.5159],[-103.6118,38.5171],[-103.6116,38.5225],[-103.7228,38.5223],[-103.8328,38.523],[-103.9411,38.523],[-104.054,38.523]]]},\"properties\":{\"name\":\"Elbert\",\"state\":\"CO\"}}]}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
The magnitude and distribution of lead contamination remain unknown in wetland systems. Anthropogenic deposition of lead may be contributing to negative population-level effects in waterfowl and other organisms that depend on dynamic wetland habitats, particularly if they are unable to detect and differentiate levels of environmental contamination by lead. Detection of lead and behavioral response to elevated lead levels by waterfowl is poorly understood, but necessary to characterize the risk of lead-contaminated habitats. We measured the relationship between lead contamination of wetland soils and habitat use by mottled ducks (Anas fulvigula) on the Upper Texas Coast, USA. Mottled ducks have historically experienced disproportionate negative effects from lead exposure, and exhibit a unique nonmigratory life history that increases risk of exposure when inhabiting contaminated areas. We used spatial interpolation to estimate lead in wetland soils of the Texas Chenier Plain National Wildlife Refuge Complex. Soil lead levels varied across the refuge complex (0.01–1085.51 ppm), but greater lead concentrations frequently corresponded to areas with high densities of transmittered mottled ducks. We used soil lead concentration data and MaxENT species distribution models to quantify relationships among various habitat factors and locations of mottled ducks. Use of habitats with greater lead concentration increased during years of a major disturbance. Because mottled ducks use habitats with high concentrations of lead during periods of stress, have greater risk of exposure following major disturbance to the coastal marsh system, and no innate mechanism for avoiding the threat of lead exposure, we suggest the potential presence of an ecological trap of quality habitat that warrants further quantification at a population scale for mottled ducks.
Polycyclic aromatic hydrocarbon contamination related to boat use is one of the most important water-quality issues affecting Lake Powell. High concentrations of polycyclic aromatic hydrocarbons in water are common around marinas and other areas with extensive motorboat activity because of releases of uncombusted or partially combusted oil and gasoline from boat engines. The fate of these compounds in Lake Powell is of serious environmental concern because of their toxicity and carcinogenicity and their moderate persistence once they enter the aquatic ecosystem. In 2016–17, the U.S. Geological Survey (USGS) assessed the presence and concentrations of polycyclic aromatic hydrocarbons in Lake Powell at seven sites where concentrations have historically been elevated and one site where concentrations have historically been relatively low. Semipermeable membrane devices were used to collect samples that represent time-weighted averages of polycyclic aromatic hydrocarbon concentrations in water over one-month deployment periods. Samples were collected from the epilimnion of the lake at each of the eight sampling sites during two periods of relatively high boat use (summer), and one period of relatively low boat use (spring). Twenty-eight out of 33 polycyclic aromatic hydrocarbons analyzed were detected in Lake Powell during the three sampling events. During the two summer sampling events, concentrations were generally higher, and more compounds were detected, than during the spring sampling event. Twenty-two of the polycyclic aromatic hydrocarbons analyzed in 2016–17 had previously been analyzed by the USGS in the summer of 2010 at the same 8 sites using the same collection method. Eleven of 22 compounds were detected in the summer 2010, summer 2016, and summer 2017 sampling events, and 1 was detected in the summer 2010 and summer 2017 samplings, but not in the summer 2016 sampling event. During both the current and previous sampling events, concentrations were generally higher, and more compounds were detected, at the high-use marina sites located most downstream on the lake. The consistent presence of a wide range of polycyclic aromatic hydrocarbons in the water of Lake Powell indicates chronic and (or) recent anthropogenic sources of contamination. The results from this study will provide the National Park Service with information necessary to determine if the current regulations on emission standards for personal watercraft used on Lake Powell are effective in lowering polycyclic aromatic hydrocarbon concentrations in the lake.
Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Runoff in steep channels is capable of transitioning into debris flows with hazardous implications for downstream communities and infrastructure, particularly in alpine landscapes with minimal vegetation and areas recently disturbed by wildfire. Here, we derive thresholds for the initiation of runoff‐generated debris flows based on critical values of dimensionless discharge and Shields stress. These thresholds are derived by using a numerical model to estimate the hydrodynamic conditions coinciding with the timing of debris flow activity in a recently burned basin. A benefit of hydrodynamic thresholds is that they can be used to assess debris flow likelihood based on measurable hydrologic and geomorphic parameters and therefore provide more universal criteria for quantifying the runoff‐to‐debris flow transition in landscape evolution studies and hazard assessments. We then demonstrate how hydrodynamic thresholds can be used to estimate rainfall intensity‐duration thresholds for runoff‐generated debris flows without the need for historic debris flow observations.
This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from −0.2 ± 0.02 g C m–2 yr–1 for an upland forest site to 114.9 ± 13.4 g C m–2 yr–1 for an estuarine freshwater marsh, with fluxes exceeding 40 g C m–2 yr–1 at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average ±1.6 g C m–2 yr–1 at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-18-0268.1","usgsCitation":"Knox, S.H., Jackson, R.B., Poulter, B., McNicol, G., Fluet-Chouinard, E., Zhang, Z., Hugelius, G., Bousquet, P., Canadell, J.G., Saunois, M., Papale, D., Chu, H., Keenan, T.F., Baldocchi, D., Torn, M.S., Mammarella, I., Trotta, C., Aurela, M., Bohrer, G., Campbell, D.I., Cescatti, A., Chamberlain, S.D., Chen, J., Chen, W., Dengel, S., Desai, A.R., Euskirchen, E.S., Friborg, T., Gasbarra, D., Goded, I., Goeckede, M., Heimann, M., Helbig, M., Hirano, T., Hollinger, D.Y., Iwata, H., Kang, M., Klatt, J., Krauss, K., Kutzbach, L., Lohila, A., Mitra, B., Morin, T., Nilsson, M.B., Niu, S., Noormets, A., Oechel, W.C., Peichl, M., Peltola, O., Reba, M.L., Richardson, A.D., Runkle, B.R., Ryu, Y., Sachs, T., Schafer, K.V., Schmid, H.P., Shurpali, N., Sonnentag, O., Tang, A., Ueyama, M., Vargas, R., Vesala, T., Ward, E., Windham-Myers, L., Wohlfahrt, G., and Zona, D., 2019, FLUXNET-CH4 synthesis activity: Objectives, observations, and future directions: Bulletin of the American Meteorological Society, v. 100, no. 12, p. 2607-2632, https://doi.org/10.1175/BAMS-D-18-0268.1.","productDescription":"26 p.","startPage":"2607","endPage":"2632","ipdsId":"IP-102319","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":467447,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hal.science/hal-02969171","text":"Publisher Index Page"},{"id":365836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"12","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Knox, Sara H. 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Subseasonal-to-seasonal forecasts of this timing are important for industry, environmental management and Arctic communities. In northern Alaska, the timing is influenced by the advection of marine air from the north Pacific by the Aleutian Low, modulated by high pressure centered in the Beaufort Sea. A new climate index that integrates their interaction could advance melt predictions. We define this index based on 850 hPa geopotential height at four fixed locations referred to as the Aleutian Low –Beaufort Sea Anticyclone (ALBSA). During positive ALBSA in May, advection of +0.5-1.5 K/day is observed through the Bering Strait. ALBSA is correlated with both snowmelt in northern Alaska and the onset of sea ice melt over the adjacent seas. 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PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":773320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dorning, Monica 0000-0002-7576-1256 mdorning@usgs.gov","orcid":"https://orcid.org/0000-0002-7576-1256","contributorId":191772,"corporation":false,"usgs":true,"family":"Dorning","given":"Monica","email":"mdorning@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":773321,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keen, Jolene 0000-0003-4962-6613","orcid":"https://orcid.org/0000-0003-4962-6613","contributorId":219835,"corporation":false,"usgs":false,"family":"Keen","given":"Jolene","email":"","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":773322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kramer, Louisa 0000-0002-6776-9768","orcid":"https://orcid.org/0000-0002-6776-9768","contributorId":204878,"corporation":false,"usgs":true,"family":"Kramer","given":"Louisa","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":773323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Robert 0000-0001-5137-6874","orcid":"https://orcid.org/0000-0001-5137-6874","contributorId":219836,"corporation":false,"usgs":true,"family":"Taylor","given":"Robert","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":773324,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248318,"text":"70248318 - 2019 - Influences of potential oil and gas development and future climate on Sage-grouse declines and redistribution","interactions":[],"lastModifiedDate":"2024-05-16T15:31:39.363715","indexId":"70248318","displayToPublicDate":"2019-07-16T06:52:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Influences of potential oil and gas development and future climate on Sage-grouse declines and redistribution","docAbstract":"Multiple environmental stressors impact wildlife populations, but we often know little about their cumulative and combined influences on population outcomes. We generally know more about past effects than potential future impacts, and direct influences such as changes of habitat footprints than indirect, long-term responses in behavior, distribution, or abundance. Yet, an understanding of all these components is needed to plan for future landscapes that include human activities and wildlife. We developed a case study to assess how spatially explicit individual-based modeling could be used to evaluate future population outcomes of gradual landscape change from multiple stressors. For Greater Sage-grouse in southwest Wyoming, USA, we projected oil and gas development footprints and climate-induced vegetation changes 50 years into the future. Using a time-series of planned oil and gas development and predicted climate-induced changes in vegetation, we recalculated habitat selection maps to dynamically modify future habitat quantity, quality, and configuration. We simulated long-term Sage-grouse responses to habitat change by allowing individuals to adjust to shifts in habitat availability and quality. The use of spatially explicit individual-based modeling offered a useful means of evaluating delayed indirect impacts of landscape change on wildlife population outcomes. The inclusion of movement and demographic responses to oil and gas infrastructure resulted in substantive changes in distribution and abundance when cumulated over several decades and throughout the regional population. When combined, additive development and climate-induced vegetation changes reduced abundance by up to half of the original size. In our example, the consideration of only a single population stressor the final possible population size by as much as 50%. Multiple stressors and their cumulative impacts need to be broadly considered through space and time to avoid underestimating the impacts of multiple gradual changes and overestimating the ability of populations to withstand change.
The U.S. Geological Survey (USGS) quantitatively assessed the potential for undiscovered, technically recoverable continuous oil and gas resources in the Eastern Great Basin Province (Anna and others, 2007) of Nevada, Utah, and Idaho (fig. 1). The assessment focused on the area of the province between the Roberts Mountains and Sevier thrust systems (Peterson, 1994). The major petroleum source rocks within this area are the Upper Devonian–Lower Mississippian Pilot Shale and the Mississippian Chainman Formation (Gutschick and Rodriquez, 1979; Poole and Claypool, 1984; Giles, 1994; Trexler and others, 1995). The geologic model applied to the Pilot Shale and shales in the Chainman Formation is for these shales to have achieved generative maturity for oil by burial to at least 8,700 feet (2,652 meters) within some of the Neogene extensional basins (Grabb, 1994; Anna and others, 2007). Areas that satisfy this depth requirement were defined using modeled gravity data that were calibrated to the petroleum system in Railroad Valley and Pine Valley in Nevada (Barker and Peterson, 1991; Ïnan and Davis, 1994; Meissner, 1995; Anna and others, 2007).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193002","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Finn, T.M., Gaswirth, S.B., Marra, K.R., Le, P.A., Brownfield, M.E., Leathers-Miller, H.M., Drake, R.M., II, and Kinney, S.A., 2019, Assessment of continuous oil resources in the Eastern Great Basin Province of Nevada, Utah, and Idaho, 2018: U.S. Geological Survey Fact Sheet 2019–3002, 2 p., https://doi.org/10.3133/fs20193002.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-101431","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":365379,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3002/coverthb.jpg"},{"id":365364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3002/fs20193002.pdf","text":"Report","size":"660 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3002"}],"country":"United States","state":"Idaho, Nevada, Utah","otherGeospatial":"Eastern Great Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.02636718749999,\n 42.00032514831621\n ],\n [\n -117.0703125,\n 36.77409249464195\n ],\n [\n -114.60937499999999,\n 34.994003757575776\n ],\n [\n -114.697265625,\n 36.10237644873644\n ],\n [\n -114.62585449218749,\n 36.14231087352999\n ],\n [\n -114.47753906249999,\n 36.146746777814364\n ],\n [\n -114.3731689453125,\n 36.13343831245866\n ],\n [\n -114.2303466796875,\n 36.01800375871416\n ],\n [\n -114.1204833984375,\n 36.04021586880111\n ],\n [\n -111.22558593749999,\n 40.94671366508002\n ],\n [\n -111.939697265625,\n 41.261291493919884\n ],\n [\n -111.76391601562499,\n 41.541477666790286\n ],\n [\n -111.456298828125,\n 42.73894375124377\n ],\n [\n -111.412353515625,\n 43.14909399920127\n ],\n [\n -112.8076171875,\n 43.15710884095329\n ],\n [\n -114.06005859375,\n 41.983994270935625\n ],\n [\n -117.02636718749999,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
This publication consists of three map sheets that display shallow geologic structure, along with sediment distribution and thickness, for an about 225-km-long offshore section of the central California coast between Point Sur and Point Arguello. Each map sheet includes three maps, at scales of either 1:150,000 or 1:200,000, as well as a set of figures that contain representative high-resolution seismic-reflection profiles. The maps and seismic-reflection surveys cover most of the continental shelf in this region. In addition, the maps show the locations of the shelf break and the 3-nautical-mile limit of California’s State Waters.
The seismic-reflection data, which are the primary dataset used to develop the maps, were collected to support the California Seafloor Mapping Program and U.S. Geological Survey Offshore Geologic Hazards projects. In addition to the three map sheets, this publication includes geographic information system data files of interpreted faults, folds, sediment thicknesses, and depths-to-base of sediment. The faults and folds shown on the maps have been locally simplified as appropriate for the map scales.
The right-lateral San Gregorio–Hosgri Fault (SGHF) is the most significant structure in the map area. On a regional scale, the SGHF is part of a 400-km-long, right-lateral fault system that extends northwestward from Point Arguello to the area offshore of San Francisco, where it merges with the San Andreas Fault. From north to south in this part of central California, the SGHF lies offshore between the south flank of Point Sur and the north flank of Point Piedras Blancas, then comes onshore at Point Piedras Blancas, before heading offshore again between the south flank of Point Piedras Blancas and Point Arguello. Cumulative fault offset along the SGHF is as much as 150 to 160 km, decreasing to the south by transferring slip on to northwest-striking faults that converge with the SGHF both onland and offshore from the east. In the map area, the offshore-converging faults include the Los Osos Fault, the Shoreline–Point Buchon Fault, the Casmalia Fault, and the Lions Head Fault.
Quaternary sediments and bedrock underlie the shelf. On the seismic-reflection profiles, we divide Quaternary shelf sediments into two units. Characterizing the younger, upper unit is a focus of this publication. This unit is inferred to have been deposited on the shelf in the last about 21,000 years during the sea-level rise that followed the last major lowstand and the Last Glacial Maximum (LGM). This upper unit overlies a transgressive surface of erosion, a commonly angular, wave-cut unconformity, and is generally characterized by low-amplitude, continuous to moderately continuous, diffuse, subparallel, generally flat reflections. Maps in this publication show both the thickness of this upper sediment unit and the depth to the base of the sediment unit. Within the map region, 11 different “domains” of post-LGM shelf sediment are delineated on the basis of sediment thickness and coastal geomorphology. Maximum sediment thickness is in the southern part of the region, offshore of the mouths of the Santa Ynez and Santa Maria Rivers. Minimum sediment thickness is found offshore of prominent rocky points, including Point Buchon and Piedras Blancas. Mean sediment thickness for the entire shelf in the map area between Point Sur and Point Arguello is 12.2 m, and total sediment volume is 24.7 million cubic meters.
Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Exhumation and landscape evolution along strike‐slip fault systems reflect tectonic processes that accommodate and partition deformation in orogenic settings. We present 17 new apatite (U‐Th)/He (He), zircon He, apatite fission‐track (FT), and zircon FT dates from the eastern Denali fault zone (EDFZ) that bounds the Kluane Ranges in Yukon, Canada. The dates elucidate patterns of deformation along the EDFZ. Mean apatite He, apatite FT, zircon He, and zircon FT sample dates range within ~26–4, ~110–12, ~94–28, and ~137–83 Ma, respectively. A new zircon U‐Pb date of 113.9 ± 1.7 Ma (2σ) complements existing geochronology and aids in interpretation of low‐temperature thermochronometry data patterns. Samples ≤2 km southwest of the EDFZ trace yield the youngest thermochronometry dates. Multimethod thermochronometry, zircon He date‐effective U patterns, and thermal history modeling reveal rapid cooling ~95–75 Ma, slow cooling ~75–30 Ma, and renewed rapid cooling ~30 Ma to present. The magnitude of net surface uplift constrained by published paleobotanical data, exhumation, and total surface uplift from ~30 Ma to present are ~1, ~2–6, and ~1–7 km, respectively. Exhumation is highest closest to the EDFZ trace but substantially lower than reported for the central Denali fault zone. We infer exhumation and elevation changes associated with ~95–75 Ma terrane accretion and EDFZ activity, relief degradation from ~75–30 Ma, and ~30 Ma to present exhumation and surface uplift as a response to flat‐slab subduction and transpressional deformation. Integrated results reveal new constraints on landscape evolution within the Kluane Ranges directly tied to the EDFZ during the last ~100 Myr.
","language":"English","publisher":"Wiley","doi":"10.1029/2019TC005545","usgsCitation":"McDermott, R.G., Ault, A.K., Caine, J.S., and Thomson, S.N., 2019, Thermotectonic history of the Kluane Ranges and evolution of the eastern Denali Fault Zone in southwestern Yukon, Canada: Tectonics, v. 38, no. 8, p. 2983-3010, https://doi.org/10.1029/2019TC005545.","productDescription":"28 p.","startPage":"2983","endPage":"3010","ipdsId":"IP-105959","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":467460,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019tc005545","text":"Publisher Index Page"},{"id":367017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, Yukon","otherGeospatial":"Denali Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.390625,\n 58.56252272853734\n ],\n [\n -135.17578125,\n 58.56252272853734\n ],\n [\n -135.17578125,\n 64.28275952823394\n ],\n [\n -155.390625,\n 64.28275952823394\n ],\n [\n -155.390625,\n 58.56252272853734\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-15","publicationStatus":"PW","contributors":{"authors":[{"text":"McDermott, Robert G. 0000-0002-2550-0322","orcid":"https://orcid.org/0000-0002-2550-0322","contributorId":218595,"corporation":false,"usgs":false,"family":"McDermott","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":769611,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ault, Alexis K. 0000-0001-6361-3179","orcid":"https://orcid.org/0000-0001-6361-3179","contributorId":218596,"corporation":false,"usgs":false,"family":"Ault","given":"Alexis","email":"","middleInitial":"K.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":769612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caine, Jonathan S. 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":1272,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan","email":"jscaine@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":769610,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomson, Stuart N. 0000-0003-4331-5654","orcid":"https://orcid.org/0000-0003-4331-5654","contributorId":218597,"corporation":false,"usgs":false,"family":"Thomson","given":"Stuart","email":"","middleInitial":"N.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":769613,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204745,"text":"70204745 - 2019 - Effects of infiltration characteristics on the spatial-temporal evolution of stability of an interstate highway embankment","interactions":[],"lastModifiedDate":"2019-08-15T10:10:23","indexId":"70204745","displayToPublicDate":"2019-07-11T09:52:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2327,"text":"Journal of Geotechnical and Geoenvironmental Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Effects of infiltration characteristics on the spatial-temporal evolution of stability of an interstate highway embankment","docAbstract":"Infiltration-induced landslides are among the most common natural disasters threatening modern civilization, but conventional methods for studying the triggering mechanisms and predicting the occurrence of these slides are limited by incomplete consideration of underlying physical processes and the lack of precision inherent in limit-equilibrium analyses. To address this problem the spatial-temporal evolution of failure is investigated in a seasonally unstable section of interstate highway embankment, known as the Straight Creek landslide, Colorado. The study includes multi-year site investigation, monitoring, and numerical simulation using a rigorous hydromechanical framework along with a field of local factor of safety method. The sensitivity of episodic landslide reactivation to infiltration characteristics is evaluated. Results indicate that annual cumulative snowmelt infiltration, which typically accounts for approximately 75% of total annual cumulative infiltration and occurs over a short period in the spring, has the most substantial impact on slide activation. The rate of snowmelt infiltration varies independently of annual cumulative snowmelt infiltration and cumulative infiltration in the previous year, but still affects antecedent soil moisture conditions at the onset of snowmelt infiltration and therefore also the level of slide activation. These findings are used to establish specific thresholds for exacerbated slide movement using annual snowpack accumulation, forecasted snowmelt rate, and the previous year’s snowmelt, an approach which may be applied for predicting movement at this and other recurring or potential slide sites.","language":"English","publisher":"ASCE","doi":"10.1061/(ASCE)GT.1943-5606.0002127","usgsCitation":"Hinds, E., Lu, N., Mirus, B.B., and Wayllace, A., 2019, Effects of infiltration characteristics on the spatial-temporal evolution of stability of an interstate highway embankment: Journal of Geotechnical and Geoenvironmental Engineering, v. 145, no. 9, 05019008, 11 p., https://doi.org/10.1061/(ASCE)GT.1943-5606.0002127.","productDescription":"05019008, 11 p.","ipdsId":"IP-102759","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":366560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Summit County","otherGeospatial":"Straight Creek Landslide","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.9666667,\n 39.67916667\n ],\n [\n -105.9666667,\n 39.67083333\n ],\n [\n -105.95833333,\n 39.67083333\n ],\n [\n -105.95833333,\n 39.67916667\n ],\n [\n -105.9666667,\n 39.67916667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hinds, Eric","contributorId":218084,"corporation":false,"usgs":false,"family":"Hinds","given":"Eric","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":768280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Ning","contributorId":191360,"corporation":false,"usgs":false,"family":"Lu","given":"Ning","email":"","affiliations":[{"id":12620,"text":"U.S. Army Corp. of Engineers","active":true,"usgs":false}],"preferred":false,"id":768281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":768282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wayllace, Alexandra","contributorId":203213,"corporation":false,"usgs":false,"family":"Wayllace","given":"Alexandra","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":768283,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228071,"text":"70228071 - 2019 - The dream and the reality: Meeting decision-making time frames while incorporating ecosystem and economic models into management strategy evaluation","interactions":[],"lastModifiedDate":"2022-02-03T15:08:46.766493","indexId":"70228071","displayToPublicDate":"2019-07-11T08:58:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The dream and the reality: Meeting decision-making time frames while incorporating ecosystem and economic models into management strategy evaluation","docAbstract":"Atlantic herring (Clupea harengus) in the Northwest Atlantic have been managed with interim harvest control rules (HCRs). A stakeholder-driven management strategy evaluation (MSE) was conducted that incorporated a broad range of objectives. The MSE process was completed within 1 year. Constant catch, conditional constant catch, and a biomass-based (BB) HCR with a 15% restriction on the interannual change in the quota could achieve more stable yields than BB HCRs without such restrictions, but could not attain as high of yields and resulted in more negative outcomes for terns (Sterna hirundo; a predator of herring). A similar range of performance could be achieved by applying a BB HCR annually every 3 years or every 5 years. Predators (i.e., dogfish (Squalus acanthias), bluefin tuna (Thunnus thynnus), and terns) were generally insensitive to the range of HCRs. While median net revenues were sensitive to some HCRs, time series analysis suggests that most HCRs produced a stable equilibrium of net revenue. To meet management needs, some aspects of the simulations were less than might be considered scientifically ideal, but using “models of intermediate complexity” were informative for managers and formed a foundation for future improvements.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0128","usgsCitation":"Deroba, J., Gaichas, S., Lee, M., Feeney, R.G., Boelke, D., and Irwin, B.J., 2019, The dream and the reality: Meeting decision-making time frames while incorporating ecosystem and economic models into management strategy evaluation: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 7, https://doi.org/10.1139/cjfas-2018-0128.","ipdsId":"IP-097206","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":460337,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/52990","text":"External Repository"},{"id":395348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northwest Atlantic","volume":"76","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Deroba, J.J.","contributorId":274471,"corporation":false,"usgs":false,"family":"Deroba","given":"J.J.","affiliations":[{"id":38698,"text":"NOAA Fisheries","active":true,"usgs":false}],"preferred":false,"id":833011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaichas, S.K.","contributorId":274472,"corporation":false,"usgs":false,"family":"Gaichas","given":"S.K.","affiliations":[{"id":38698,"text":"NOAA Fisheries","active":true,"usgs":false}],"preferred":false,"id":833012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Min-Yang","contributorId":274376,"corporation":false,"usgs":false,"family":"Lee","given":"Min-Yang","email":"","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":833063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feeney, Rachael G.","contributorId":274373,"corporation":false,"usgs":false,"family":"Feeney","given":"Rachael","email":"","middleInitial":"G.","affiliations":[{"id":40788,"text":"New England Fishery Management Council","active":true,"usgs":false}],"preferred":false,"id":833064,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boelke, D.","contributorId":274473,"corporation":false,"usgs":false,"family":"Boelke","given":"D.","affiliations":[{"id":56621,"text":"New England Fisheries Management Council","active":true,"usgs":false}],"preferred":false,"id":833015,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833016,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70225147,"text":"70225147 - 2019 - Black bears alter movements in response to anthropogenic features with time of day and season","interactions":[],"lastModifiedDate":"2021-10-14T12:48:58.830437","indexId":"70225147","displayToPublicDate":"2019-07-11T07:45:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Black bears alter movements in response to anthropogenic features with time of day and season","docAbstract":"With the growth and expansion of human development, large mammals will increasingly encounter humans, elevating the likelihood of human-wildlife conflicts. Understanding the behavior and movement of large mammals, particularly around human development, is important for crafting effective conservation and management plans for these species.
We used GPS collar data from American black bears (Ursus americanus) to determine how seasonal food resources and human development affected bear movement patterns and resource use across the Commonwealth of Massachusetts.
We found that though bears moved more and avoided human development during crepuscular and daylight hours than at night, bears preferentially moved through human dominated areas at night. This indicates bears were mitigating the risk of human development by altering their behavior to exploit these areas when human activity is low. This behavioral shift was most prominent in the spring, when natural foods are scarce, and fall, when energetic demands are high. We also observed a high degree of inter-individual variability among our sample of bears. Bears with a higher density of houses in their home ranges (~ 75 houses/km2) displayed less avoidance of human development than more rural bears. Furthermore, bear movement models had different explanatory variables, with preference or avoidance of a variable being dependent on the individual bear. To account for this individuality in our predictive surfaces, we projected the probability of movement for each season and time of day using a spatially weighted surface centered on each bear’s home range.
We found that black bears in Massachusetts are operating in a landscape of fear and are altering their movement patterns to use developed areas when human activity is low. We also found seasonal and diel differences among individual bears in resource selection during movement. Accounting for these individual, seasonal, and diel differences when assessing movement for large mammals is especially important if predictive surfaces are to be used in identifying areas for conservation and management.
","language":"English","publisher":"Springer","doi":"10.1186/s40462-019-0166-4","usgsCitation":"Zeller, K., Wattles, D., Conlee, L., and DeStefano, S., 2019, Black bears alter movements in response to anthropogenic features with time of day and season: Movement Ecology, v. 7, 19, 14 p., https://doi.org/10.1186/s40462-019-0166-4.","productDescription":"19, 14 p.","ipdsId":"IP-105931","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467465,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-019-0166-4","text":"Publisher Index Page"},{"id":390520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2019-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Zeller, Katherine A.","contributorId":267698,"corporation":false,"usgs":false,"family":"Zeller","given":"Katherine A.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":825158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wattles, David","contributorId":255402,"corporation":false,"usgs":false,"family":"Wattles","given":"David","affiliations":[{"id":51525,"text":"Massachusetts Division of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":825201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conlee, Laura","contributorId":267742,"corporation":false,"usgs":false,"family":"Conlee","given":"Laura","email":"","affiliations":[],"preferred":false,"id":825202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeStefano, Stephen 0000-0003-2472-8373 destef@usgs.gov","orcid":"https://orcid.org/0000-0003-2472-8373","contributorId":2874,"corporation":false,"usgs":true,"family":"DeStefano","given":"Stephen","email":"destef@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":825157,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204226,"text":"70204226 - 2019 - Heat flow in the Western Arctic Ocean (Amerasian Basin)","interactions":[],"lastModifiedDate":"2019-10-09T09:28:09","indexId":"70204226","displayToPublicDate":"2019-07-10T15:19:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Heat flow in the Western Arctic Ocean (Amerasian Basin)","docAbstract":"From 1963 to 1973 the U.S. Geological Survey (USGS) measured heat flow at 356 sites in the Amerasian Basin (Western Arctic Ocean) from a drifting ice island (T-3). The resulting measurements, which are unevenly distributed on Alpha-Mendeleev Ridge (AMR) and in Canada and Nautilus basins, greatly expand available heat flow data for the Arctic Ocean. Average T-3 heat flow is ~54.7 ± 11.3 mW m-2, and Nautilus Basin, including Mendeleev Plain, is the only well-surveyed area (~13% of data) with significantly higher average heat flow (63.8 mW m-2). Heat flow and bathymetry are not correlated at a large scale, and turbiditic surficial sediments (Canada and Nautilus basins) have higher heat flow than the sediments that blanket the AMR. Thermal gradients are mostly near-linear, implying that conductive heat transport dominates and that near-seafloor sediments are in thermal equilibrium with overlying bottom waters. Combining the heat flow data with modern seismic imagery suggests that some of the observed heat flow variability may be explained by local changes in sediment thickness or lithology or the presence of basement faults that channel circulating seawater. A thermal model that incorporates thermal conductivity variations along a profile from Canada Basin (thick sediment on mostly oceanic crust) to Alpha Ridge (thin sediment over thick magmatic units associated with the High Arctic Large Igneous Province) predicts heat flow lower than that observed on Alpha Ridge. This, along with other observations, implies that circulating fluids modulate conductive heat flow and contribute to high variability in the T-3 dataset. .","language":"English","publisher":"AGU","doi":"10.1029/2019JB017587","usgsCitation":"Ruppel, C.D., Lachenbruch, A., Hutchinson, D., Munroe, R., and Mosher, D., 2019, Heat flow in the Western Arctic Ocean (Amerasian Basin): Journal of Geophysical Research B: Solid Earth, v. 124, no. 8, p. 7562-7587, https://doi.org/10.1029/2019JB017587.","productDescription":"26 p.","startPage":"7562","endPage":"7587","ipdsId":"IP-104584","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467466,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2019jb017587","text":"External Repository"},{"id":437392,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91XQ3IS","text":"USGS data release","linkHelpText":"Post-expedition report for USGS T-3 Ice Island heat flow measurements in the High Arctic Ocean, 1963-1973"},{"id":437391,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97EPU2F","text":"USGS data release","linkHelpText":"Thermal Data and Navigation for T-3 (Fletcher's) Ice Island Arctic Ocean Heat Flow Studies, 1963-73 (ver. 1.1 December 2022)"},{"id":365525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"8","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":195778,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn","email":"cruppel@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":766065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lachenbruch, A.H.","contributorId":216905,"corporation":false,"usgs":false,"family":"Lachenbruch","given":"A.H.","email":"","affiliations":[{"id":39546,"text":"(retired) U.S.Geological Survey","active":true,"usgs":false}],"preferred":false,"id":766066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hutchinson, Deborah 0000-0002-2544-5466 dhutchinson@usgs.gov","orcid":"https://orcid.org/0000-0002-2544-5466","contributorId":174836,"corporation":false,"usgs":true,"family":"Hutchinson","given":"Deborah","email":"dhutchinson@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":766067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munroe, Robert","contributorId":216907,"corporation":false,"usgs":false,"family":"Munroe","given":"Robert","affiliations":[{"id":39548,"text":"(retired) U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":766068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mosher, David","contributorId":174895,"corporation":false,"usgs":false,"family":"Mosher","given":"David","affiliations":[],"preferred":false,"id":766069,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204191,"text":"70204191 - 2019 - Bundle adjustment using space based triangulation method for improving the Landsat global ground reference","interactions":[],"lastModifiedDate":"2019-07-10T12:01:42","indexId":"70204191","displayToPublicDate":"2019-07-10T11:58:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Bundle adjustment using space based triangulation method for improving the Landsat global ground reference","docAbstract":"There is an ever-increasing interest and need for accurate geo-registration of remotely sensed data products to a common global geometric reference. Although the geo-registration has improved significantly in the last decade, the lack of an accurate global ground reference dataset\nposes serious issues for data providers seeking to make geometrically stackable analysis ready data. The existing Global Land Survey 2000 (GLS2000) dataset derived from Landsat 7 images provide global coverage and can be used as a reference dataset, but its accuracy is much lower than what can be attained using the agile and precise pointing capability of the new spacecrafts. The improved position and pointing knowledge of the new spacecrafts such as Landsat 8 can be used to improve the accuracy of the existing global ground control points using a space based triangulation method. This paper discusses the theoretical basis, formulation, and application of the space based triangulation method at a continental scale to improve the accuracy of the GLS-derived ground control points.Our triangulation method involves adjusting the spacecraft position, velocity, attitude, attitude rate, and ground control point locations, iteratively, by linearizing the non-linear viewing geometry, such that the residual errors in the measured image points are minimized. The complexity of the numerical inversion and processing is dealt with in our approach by processing and eliminating the ground points one at a time. This helps to reduce the size of the normal matrix significantly, thereby making the triangulation of a continent-wide scale block feasible and efficient. One of the unique characteristics of our method is the use of a correlation model linking the attitude corrections between images of the same pass, which promotes consistency in the attitude corrections. We evaluated the performance of our triangulation method over the Australian continent using the Australian Geographic Reference Image (AGRI) dataset as a reference. Both a free adjustment, using only the pointing information of the Landsat 8 spacecraft, and a constrained adjustment, using the AGRI as external control were performed and the results compared. The Australian block’s horizontal accuracy improved from 15.4 m to 3.6 m with the use of AGRI controls, and from 15.4 m to 8.8 m without the use of AGRI controls.","language":"English","publisher":"MDPI","doi":"10.3390/rs11141640","usgsCitation":"Storey, J.C., Rengarajan, R., and Choate, M., 2019, Bundle adjustment using space based triangulation method for improving the Landsat global ground reference: Remote Sensing, v. 11, no. 14, 1640; 25 p., https://doi.org/10.3390/rs11141640.","productDescription":"1640; 25 p.","ipdsId":"IP-108480","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467468,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11141640","text":"Publisher Index Page"},{"id":365464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"14","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-10","publicationStatus":"PW","contributors":{"editors":[{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":216866,"corporation":false,"usgs":true,"family":"Choate","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":765937,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Storey, James C. 0000-0002-6664-7232 storey@usgs.gov","orcid":"https://orcid.org/0000-0002-6664-7232","contributorId":5333,"corporation":false,"usgs":true,"family":"Storey","given":"James","email":"storey@usgs.gov","middleInitial":"C.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":765936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengarajan, R. 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":56036,"corporation":false,"usgs":true,"family":"Rengarajan","given":"R.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":765935,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choate, Mike 0000-0002-8101-4994 choate@usgs.gov","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":4618,"corporation":false,"usgs":true,"family":"Choate","given":"Mike","email":"choate@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":765940,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204250,"text":"70204250 - 2019 - First examination of diet items consumed by wild-caught black carp (Mylopharyngodon piceus) in the U.S.","interactions":[],"lastModifiedDate":"2019-07-23T09:04:27","indexId":"70204250","displayToPublicDate":"2019-07-10T10:28:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5153,"text":"The American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"First examination of diet items consumed by wild-caught black carp (Mylopharyngodon piceus) in the U.S.","title":"First examination of diet items consumed by wild-caught black carp (Mylopharyngodon piceus) in the U.S.","docAbstract":"Black carp (Mylopharyngodon piceus) were imported to the U.S. in the 1970s to control snails in aquaculture ponds and have since escaped from captivity. The increase in captures of wild fish has raised concerns of risk to native and imperiled unionid mussels given previous literature classified this species a molluscivore. We acquired black carp from commercial fishers and biologists, and examined digestive contents of 109 fish captured over 8 y from lentic and lotic habitats in the central and southern U.S.A. Digestive tract contents were preserved, and diet items inventoried. We identified 59 aquatic animal taxa (21 mollusks, 27 insects, and 11 other invertebrates) and various plant material including nuts and seeds; no fish were found. Approximately 45% of stomachs examined were empty or only contained flukes (Trematoda) that had infected mollusks before they were ingested. Nonempty stomachs contained snails (16.5%), bivalve mussels (22.8%), and insect larvae (net-spinning caddisflies, 15.6%; burrowing mayflies, 6.4%; and midges, 13.7%). Fish also consumed freshwater sponges (Porifera), moss animals (Bryozoa), crustaceans (Ostracoda and Decapoda), water mites (Acarina), and three worm phyla (Nematoda, Nemertea, Annelida). Seven taxa of unionid mussels were identified from shell fragments among the fish we examined, all of which are found in habitats with soft mud or sand/silt substrates. Diet of fish captured in lentic environments contained significantly higher richness than those captured in lotic environments. Individual black carp often contained large numbers of only one or two diet items that were assumed locally abundant and did not always crush the shells of mollusks. Most fish we examined consumed benthic prey, which supports the classification of black carp as a benthic foraging species. However, the presence of other aquatic taxa associated with pelagic or subsurface zones suggests black carp are opportunistic in their consumption of diet items and flexible in their feeding modes.
","language":"English","publisher":"BioOne Complete","doi":"10.1674/0003-0031-182.1.89","usgsCitation":"Poulton, B.C., Kroboth, P., Aiken, G., Chapman, D., Bailey, J., McMurray, S.E., and Faiman, J.S., 2019, First examination of diet items consumed by wild-caught black carp (Mylopharyngodon piceus) in the U.S.: The American Midland Naturalist, v. 182, no. 1, p. 89-108, https://doi.org/10.1674/0003-0031-182.1.89.","productDescription":"20 p.","startPage":"89","endPage":"108","ipdsId":"IP-102117","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":437393,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K88CWF","text":"USGS data release","linkHelpText":"Diet items consumed by wild-caught black carp (Mylopharyngodon piceus) in the U.S."},{"id":365576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365572,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1674/0003-0031-182.1.89"}],"volume":"182","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Poulton, Barry C. 0000-0002-7219-4911 bpoulton@usgs.gov","orcid":"https://orcid.org/0000-0002-7219-4911","contributorId":2421,"corporation":false,"usgs":true,"family":"Poulton","given":"Barry","email":"bpoulton@usgs.gov","middleInitial":"C.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":766180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroboth, Patrick 0000-0002-9447-4818","orcid":"https://orcid.org/0000-0002-9447-4818","contributorId":216578,"corporation":false,"usgs":true,"family":"Kroboth","given":"Patrick","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":766181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aiken, George","contributorId":209051,"corporation":false,"usgs":true,"family":"Aiken","given":"George","affiliations":[],"preferred":true,"id":766182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":766183,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bailey, J.","contributorId":11981,"corporation":false,"usgs":true,"family":"Bailey","given":"J.","affiliations":[],"preferred":false,"id":766184,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McMurray, Stephen E.","contributorId":206918,"corporation":false,"usgs":false,"family":"McMurray","given":"Stephen","email":"","middleInitial":"E.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":766185,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Faiman, John S.","contributorId":216897,"corporation":false,"usgs":false,"family":"Faiman","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":766186,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204486,"text":"70204486 - 2019 - Precipitation regime change in Western North America: The role of atmospheric rivers","interactions":[],"lastModifiedDate":"2020-12-15T22:01:36.101171","indexId":"70204486","displayToPublicDate":"2019-07-09T15:26:45","publicationYear":"2019","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":"Precipitation regime change in Western North America: The role of atmospheric rivers","docAbstract":"Daily precipitation in California has been projected to become less frequent even as precipitation extremes intensify, leading to uncertainty in the overall response to climate warming. Precipitation extremes are historically associated with Atmospheric Rivers (ARs). Sixteen global climate models are evaluated for realism in modeled historical AR behavior and contribution of the resulting daily precipitation to annual total precipitation over Western North America. The five most realistic models display consistent changes in future AR behavior, constraining the spread of the full ensemble. They, moreover, project increasing year-to-year variability of total annual precipitation, particularly over California, where change in total annual precipitation is not projected with confidence. Focusing on three representative river basins along the West Coast, we show that, while the decrease in precipitation frequency is mostly due to non-AR events, the increase in heavy and extreme precipitation is almost entirely due to ARs. This research\ndemonstrates that examining meteorological causes of precipitation regime change can lead to better and more nuanced understanding of climate projections. It highlights the critical role of future changes in ARs to Western water resources, especially over California.","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-46169-w","usgsCitation":"Gerhunov, A., Shulgina, T., Clemesha, R., Guirguis, K., Pierce, D., Dettinger, M.D., Lavers, D.A., Cayan, D., Polade, S., Kalansky, J., and Ralph, M., 2019, Precipitation regime change in Western North America: The role of atmospheric rivers: Scientific Reports, v. 9, 9944, 11 p., https://doi.org/10.1038/s41598-019-46169-w.","productDescription":"9944, 11 p.","ipdsId":"IP-107573","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467472,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-46169-w","text":"Publisher Index Page"},{"id":366005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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