Epigenetic mechanisms such as DNA methylation may vary in response to environmental stressors and introduce adaptive or maladaptive gene expression within and among wild bird populations. We examined the association between DNA methylation and demographic characteristics of the Louisiana Waterthrush Parkesia motacilla in territories with and without disturbance from shale gas development in a Central Appalachian watershed during 2013–2015. We also evaluated the degree to which an individual’s methylated state was subject to change across years in individuals that returned over the course of more than one breeding season (i.e. recaptures). Overall, population methylation differed between adult male and female Waterthrush where adult males generally had fewer methylated restriction sites. Methylation also differed between adult females and nestlings. Age influenced methylation in both adult males and females with a decrease in methylation with age, although adult female recaptures had increased methylation with age. Adult males were variably methylated between shale gas undisturbed and disturbed areas at a population and restriction site (i.e. loci) level, where restriction sites were predominately less methylated in shale gas-disturbed areas. Barium (Ba) and strontium (Sr) data from 2013 feather samples showed adult males had fewer methylated sites at higher concentrations of Ba and Sr, whereas nestlings displayed no correlation of methylation to Ba and Sr concentrations. Adult females displayed increased methylation with increased Sr, a trend also seen year to year in adult female recaptures. Overall, results of our study suggest sex-specific influences of shale gas development on gene expression that may affect long-term population survival and fitness.
Recent research has highlighted that the relationship between species interactions and latitude can differ between native and invasive plant taxa, generating biogeographical heterogeneity in community resistance to plant invasions. In the first study with foliar pathogens, we tested whether co‐occurring native and invasive lineages of common reed (Phragmites australis ) exhibit non‐parallel latitudinal gradients in foliar fungal communities, pathogen susceptibility and damage, and whether these biogeographical patterns can influence the success of invasion.
North America.
2015–2017.
Perennial grass P. australis .
We surveyed 35 P. australis field populations, spanning 17° latitude and comprising four phylogeographical lineages, including one endemic to North America and one invasive from Europe. For each population, we quantified the percentage of leaf pathogen damage and cultured fungi from diseased leaves, which we identified using molecular tools. To assess whether latitudinal gradients in pathogen damage had a genetic basis, we inoculated plants from 73 populations with four putative pathogens in a complementary common garden experiment and measured P. australis susceptibility (i.e., diseased leaf area).
We isolated 84 foliar fungal taxa. Phragmites australis lineage influenced fungal community composition but not diversity. Despite the invasive European P. australis lineage being the least susceptible to three of the four pathogens tested in the common garden experiment, pathogen damage in the field was similar between native and invasive lineages, providing no evidence that release from foliar pathogens contributes to the success of invasion. Genetically based latitudinal gradients in pathogen susceptibility observed in the common garden were isolate specific and obscured by local environmental conditions in the field, where pathogen damage was threefold higher for northern compared with southern populations, regardless of lineage.
Our results highlight that host plant lineage and genetically based biogeographical gradients strongly influence foliar fungal communities and pathogen susceptibility, but do not translate to patterns of pathogen damage observed in the field.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.13097","usgsCitation":"Allen, W.J., Devries, A., Bologna, N.J., Bickford, W.A., Kowalski, K., Meyerson, L., and Cronin, J.T., 2020, Intraspecific and biogeographical variation in foliar fungal communities and pathogen damage of native and invasive Phragmites australis: Global Ecology and Biogeography, v. 29, no. 7, p. 1199-1211, https://doi.org/10.1111/geb.13097.","productDescription":"13 p.","startPage":"1199","endPage":"1211","ipdsId":"IP-113518","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":457261,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/geb.13097","text":"External Repository"},{"id":376479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Warwick J.","contributorId":229451,"corporation":false,"usgs":false,"family":"Allen","given":"Warwick","email":"","middleInitial":"J.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":793209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devries, Aaron","contributorId":229452,"corporation":false,"usgs":false,"family":"Devries","given":"Aaron","affiliations":[{"id":37768,"text":"USGS Contractor","active":true,"usgs":false}],"preferred":false,"id":793210,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bologna, Nicholas J.","contributorId":229453,"corporation":false,"usgs":false,"family":"Bologna","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":793211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bickford, Wesley A. 0000-0001-7612-1325 wbickford@usgs.gov","orcid":"https://orcid.org/0000-0001-7612-1325","contributorId":5687,"corporation":false,"usgs":true,"family":"Bickford","given":"Wesley","email":"wbickford@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":793212,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":793213,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meyerson, Laura A.","contributorId":229454,"corporation":false,"usgs":false,"family":"Meyerson","given":"Laura A.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":793214,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cronin, James T.","contributorId":229455,"corporation":false,"usgs":false,"family":"Cronin","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":793215,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209092,"text":"fs20203017 - 2020 - Pyrrhotite distribution in the conterminous United States, 2020","interactions":[],"lastModifiedDate":"2022-04-20T18:44:59.3731","indexId":"fs20203017","displayToPublicDate":"2020-03-26T11:45:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3017","displayTitle":"Pyrrhotite Distribution in the Conterminous United States, 2020","title":"Pyrrhotite distribution in the conterminous United States, 2020","docAbstract":"In parts of Connecticut and Massachusetts, foundations of some homes are cracking and crumbling. Failing foundations can reduce the market value of a home and lifting a house to replace and repour a foundation is an expensive undertaking. In response, some homeowners are defaulting on their mortgages and abandoning their homes. The culprit is pyrrhotite, which occurs in construction aggregate (crushed stone) that was used as a filler in concrete. When pyrrhotite is naturally exposed to water and oxygen, it breaks down to produce sulfuric acid and secondary minerals, including gypsum, which have larger volumes than the pyrrhotite they replace. The expanded volume of the secondary minerals cracks and degrades concrete.
Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS-973
Denver, CO 80225-0046
We used odds ratios and a hurdle model to analyze parasite co-infections over 25 years on >20,000 young-of-the year of endangered Shortnose and Lost River Suckers. Host ecologies differed as did parasite infections. Shortnose Suckers were more likely to be caught inshore and 3–5 times more likely to have Bolbophorus spp. and Contracaecum sp. infections, and Lost River Suckers were more likely to be caught offshore and approximately three times more likely to have Lernaea cyprinacea infections. An observed peak shift seems likely to be due to a lower host size limit for Bolbophorus spp. (13.6 mm) compared with L. cyprinacea (23.4 mm). The large data set allowed us to generate strong hypotheses: (i) that a major marsh restoration project had unintended consequences that resulted in an increase in infections; (ii) that co-infection with Bolbophorus spp. increased the odds of infection by L. cyprinacea and Contracaecum sp.; (iii) that significant declines in the odds of infection over approximately 25 days were due to parasite-induced host mortality; (iv) that the fish’s small size relative to L. cyprinacea and Contracaecum sp. might be directly lethal; (v) that the absence of L. cyprinacea infections in the early 1990s was associated with good year-class production of the suckers; and (vi) that parasites might increase the odds of vagrancy from the nursery ground.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijpara.2020.02.001","usgsCitation":"Markle, D.F., Janik, A., Peterson, J., Choudhury, A., Simon, D., Tkach, V., Terwilliger, M.R., Sanders, J.L., and Kent, M.L., 2020, Odds ratios and hurdle models: a long-term analysis of parasite infection patterns in endangered young-of-the-year suckers from Upper Klamath Lake, Oregon, USA: International Journal for Parasitology, v. 50, no. 4, p. 315-330, https://doi.org/10.1016/j.ijpara.2020.02.001.","productDescription":"16 p.","startPage":"315","endPage":"330","ipdsId":"IP-115203","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457263,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijpara.2020.02.001","text":"Publisher Index Page"},{"id":395785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.7889404296875,\n 42.22648356137063\n ],\n [\n -121.79443359375,\n 42.409262623071186\n ],\n [\n -121.93588256835938,\n 42.603641609996586\n ],\n [\n -122.12265014648438,\n 42.48222557002593\n ],\n [\n -122.02377319335938,\n 42.379850764344134\n ],\n [\n -121.92626953124999,\n 42.2752765520868\n ],\n [\n -121.81503295898436,\n 42.20207291264876\n ],\n [\n -121.7889404296875,\n 42.22648356137063\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Markle, Douglas F.","contributorId":14530,"corporation":false,"usgs":true,"family":"Markle","given":"Douglas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":834165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janik, Andrew","contributorId":275600,"corporation":false,"usgs":false,"family":"Janik","given":"Andrew","email":"","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":834166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834164,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Choudhury, Anindo","contributorId":275601,"corporation":false,"usgs":false,"family":"Choudhury","given":"Anindo","affiliations":[{"id":56865,"text":"nsc","active":true,"usgs":false}],"preferred":false,"id":834167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simon, David C.","contributorId":275602,"corporation":false,"usgs":false,"family":"Simon","given":"David C.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":834168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tkach, Vasyl V.","contributorId":275603,"corporation":false,"usgs":false,"family":"Tkach","given":"Vasyl V.","affiliations":[{"id":40486,"text":"UND","active":true,"usgs":false}],"preferred":false,"id":834169,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Terwilliger, Mark R.","contributorId":275604,"corporation":false,"usgs":false,"family":"Terwilliger","given":"Mark","email":"","middleInitial":"R.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":834170,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sanders, Justin L.","contributorId":275605,"corporation":false,"usgs":false,"family":"Sanders","given":"Justin","email":"","middleInitial":"L.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":834171,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kent, Michael L.","contributorId":275606,"corporation":false,"usgs":false,"family":"Kent","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":834172,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70208684,"text":"sir20205008 - 2020 - Effects of huisache removal on rangeland evapotranspiration in Victoria County, south-central Texas, 2015–18","interactions":[],"lastModifiedDate":"2022-04-25T21:19:00.19189","indexId":"sir20205008","displayToPublicDate":"2020-03-26T09:18:33","publicationYear":"2020","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":"2020-5008","displayTitle":"Effects of Huisache Removal on Rangeland Evapotranspiration in Victoria County, South-Central Texas, 2015–18","title":"Effects of huisache removal on rangeland evapotranspiration in Victoria County, south-central Texas, 2015–18","docAbstract":"The U.S. Geological Survey and Desert Research Institute, in cooperation with the Natural Resources Conservation Service, Texas State Soil and Water Conservation Board, Victoria County Groundwater Conservation District, Victoria Soil and Water Conservation District, and the San Antonio River Authority, evaluated the hydrologic effects of Vachellia farnesiana var. farnesiana (huisache) removal on rangeland evapotranspiration in Victoria County, Texas. Measurements of evapotranspiration, rainfall, and related properties were made at two sites during March 2015 through August 2018. One site was predominantly grassland. The other site was dominated by dense huisache vegetation that was removed about halfway through the study period. The resulting evapotranspiration data were examined for differences between the locations and differences between the pre-removal (2015–16) and post-removal (2017–18) periods to assess the effects of huisache removal on evapotranspiration. Evapotranspiration measurements were made using the eddy-covariance technique and were supplemented by remote-sensing estimates of evapotranspiration derived from thermal and optical satellite images. A map of remotely sensed evapotranspiration was generated for the area surrounding the study sites for 2015 and demonstrates the capability of remote sensing to evaluate land-management effects on evapotranspiration for larger scale areas, such as a county or stream-basin area.
During the pre-removal period (March 2015–December 2016), evapotranspiration was greater at the huisache site than at the grassland site. Evapotranspiration at the grassland site (average of the eddy-covariance evapotranspiration and average remotely sensed evapotranspiration) was 87.6 millimeters per month (mm/mo) and at the huisache site was 100.8 mm/mo, with the differences in evapotranspiration rates being attributed to the difference in site vegetation. After huisache was removed in January 2017, evapotranspiration at the huisache site was substantially lower than at the grassland site, the changes in evapotranspiration rates being attributed not only to removal of huisache vegetation but also to possible disruption of soil runoff and infiltration characteristics. During the post-removal period (February 2017–August 2018), evapotranspiration was 88.5 mm/mo at the grassland site and 72.9 mm/mo at the huisache site (average of the eddy-covariance and average remotely sensed evapotranspiration).
The monthly differences in evapotranspiration between the grassland and huisache sites, determined by eddy-covariance and remote-sensing methods, were statistically significant between the pre-removal and post-removal periods. Also, the pre-removal period provided the best conditions to evaluate the differences between huisache site and grassland site evapotranspiration. During the pre-removal period, evapotranspiration from the huisache site as measured by the eddy-covariance method was, on average, 10.7 mm/mo greater than evapotranspiration measured at the grassland site. As determined by the average of the remotely sensed methods, huisache site evapotranspiration was 15.8 mm/mo greater than grassland site evapotranspiration. These average differences in evapotranspiration rates by the two methods indicate that evapotranspiration at the grassland site was, on average, 13.2 mm/mo less than that at the huisache site during the pre-removal period. This average difference in evapotranspiration rates also indicates potential increased groundwater recharge and (or) surface-water runoff at the grassland site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205008","collaboration":"Prepared in cooperation with the Natural Resources Conservation Service, Texas State Soil and Water Conservation Board, Victoria County Groundwater Conservation District, Victoria Soil and Water Conservation District, and the San Antonio River Authority","usgsCitation":"Slattery, R.N., Ockerman, D.J., Bromley, M., Huntington, J., and Banta, J.R., 2020, Effects of huisache removal on rangeland evapotranspiration in Victoria County, south-central Texas, 2015–18: U.S. Geological Survey Scientific Investigations Report 2020–5008, 27 p., https://doi.org/10.3133/sir20205008.","productDescription":"Report: ix, 27 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-113663","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":399630,"rank":4,"type":{"id":36,"text":"NGMDB Index 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Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
The Boone and Roubidoux aquifers (or their equivalents) are the main sources of fresh groundwater in northeastern Oklahoma. Projected total water demand of both surface water and groundwater in northeastern Oklahoma is expected to increase approximately 56 percent from 2010 to 2060. This report provides an overview of the hydrogeology of northeastern Oklahoma, with an emphasis on the hydrogeologic units composing and surrounding the Boone and Roubidoux aquifers (the Western Interior Plains confining unit, the Boone aquifer, the Ozark confining unit, and the Roubidoux aquifer). This report also provides the hydrogeologic framework for an ongoing (as of 2020) hydrologic investigation to aid the Oklahoma Water Resources Board in determining the maximum annual yields of the Boone and Roubidoux aquifers. As a first step of this ongoing hydrologic investigation, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board and U.S. Army Corps of Engineers, developed hydrogeologic-unit maps, contour maps for the bases of the four hydrogeologic units, and generalized cross sections to further characterize the hydrogeologic framework of the Boone and Roubidoux aquifers. The contour maps illustrate the altitudes of the bases of each hydrogeologic unit. The altitude of the base of the Western Interior Plains confining unit ranged from 1,316 to −6,437 feet (ft) relative to North American Vertical Datum of 1988. The altitude of the base of the Boone aquifer ranged from 1,327 to −6,681 ft. The altitude of the base of the Ozark confining unit ranged from 1,275 to −6,720 ft. The altitude of the base of the Roubidoux aquifer ranged from 403 to −9,488 ft.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3452","collaboration":"Prepared in cooperation with Oklahoma Water Resources Board and U.S. Army Corps of Engineers","usgsCitation":"Russell, C.A., and Stivers, J.W., 2020, Hydrogeologic units, contour maps, and cross sections of the Boone and Roubidoux aquifers, northeastern Oklahoma, 2020: U.S. Geological Survey Scientific Investigations Map 3452, 2 sheets, https://dx.doi.org/10.3133/sim3452.","productDescription":"2 Sheets: 36.00 x 45.00 inches; Data Releases","onlineOnly":"Y","ipdsId":"IP-109561","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":399522,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109802.htm"},{"id":373495,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3452/sim3452_sheet02.pdf","text":"Sheet 2","size":"17.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3452 Sheet 2"},{"id":373494,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3452/sim3452_sheet01.pdf","text":"Sheet 1","size":"8.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3452 Sheet 1"},{"id":373493,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3452/coverthb.jpg"},{"id":373496,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P967BVQL","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data used to describe hydrogeologic units and create contour maps and cross sections of the Boone and Roubidoux Aquifers, northeastern Oklahoma"}],"scale":"583000","country":"United States","state":"Oklahoma","otherGeospatial":"Boone Aquifer, Roubidoux Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.85,\n 35.2342\n ],\n [\n -93.9256,\n 35.2342\n ],\n [\n -93.9256,\n 37.3669\n ],\n [\n -95.85,\n 37.3669\n ],\n [\n -95.85,\n 35.2342\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Areas of improving and degrading groundwater-quality conditions in the State of California were assessed using spatial weighting of a new metric for scoring wells based on constituent concentrations and the direction and magnitude of a trend slope (Sen). Individual well scores were aggregated across 2135 equal-area grid cells covering the entire groundwater resource used for public supply in the state. Spatial weighting allows results to be aggregated locally (well or grid cell), regionally (groundwater basin), provincially, or statewide. Results differentiate degrading (increasing concentration trends) areas with low to moderate concentrations (unimpaired) from degrading areas with moderate to high concentrations (impaired). Results also differentiate improving areas (decreasing concentration trends) in the same manner. Multi-year to decadal groundwater-quality trends were computed from periodic, inorganic water-quality data for 38 constituents collected between 1974 and 2014 for compliance monitoring of nearly 13,000 public-supply wells (PSWs) in the State of California. Mann-Kendall (MK) rank correlations and Sen’s slope estimator were used to detect statistically significant trends for the entire period of recorded data (long-term trend), for the period since 2000 (recent trend), for different pumping seasons (seasonal trend), and for reversals of trends. Statewide, the most frequently detected trends since 2000 were for nitrate (36%), gross alpha/uranium (10%), arsenic (14%), total dissolved solids (TDS) (23%), and the major ions that contribute to TDS (19–28%). The Transverse and Selected Peninsular Ranges (TSPR) and the San Joaquin Valley (SJV) hydrogeologic provinces had the largest percentage of areas with moderate to high nitrate concentrations and groundwater quality trends. Improving nitrate concentrations in parts of the TSPR is associated with long-term managed aquifer recharge that has replaced historical, agriculturally affected groundwater with low-nitrate recharge in parts of the TSPR. This example suggests that application of dilute, excess surface water to agricultural fields during the winter could improve groundwater-quality in the SJV over the long term.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-020-8180-y","usgsCitation":"Jurgens, B., Fram, M.S., Rutledge, J., and Bennett, G.L., 2020, Identifying areas of degrading and improving groundwater-quality conditions in the State of California, USA, 1974-2014: Environmental Monitoring and Assessment (https://www.springer.com/journal/10661), v. 192, 250, 23 p., https://doi.org/10.1007/s10661-020-8180-y.","productDescription":"250, 23 p.","ipdsId":"IP-083518","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":457269,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-020-8180-y","text":"Publisher Index Page"},{"id":376498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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This public version, with CVO names and contact information removed, may be useful to other agencies developing their own protocols and templates. This guide evolved from a smaller document hastily assembled out of necessity during the complex and overwhelming news media interest in the 2004–2008 Mount St. Helens eruption. News media interest exceeded the need for life-saving crisis communication and foretold of the need for future multi-faceted and well-coordinated news media and social media responses during future volcanic events.
This guide accompanies the USGS Volcano Science Center’s (VSC’s) general guidelines and protocols for how communications staff at all VSC observatories will work together to respond to news media requests. The protocols and templates are applicable to (1) normal conditions when CVO has an opportunity to be proactive with its messages and to raise general awareness, (2) general responses to news media and TV documentary inquiries, (3) intense news media interest where the responsibility to communicate information and hazards rests primarily with staff at CVO, and (4) intense and overwhelming news media interest that requires a multiagency response. This guide reflects general protocols in effect at the time of publication. The information will be modified as conditions change. Although “news media” generally refers to traditional outlets such as TV, radio, and newspapers, the protocols used to engage these traditional outlets apply also when responding to bloggers, online news services, and social media comments.
Volcano Science Center
Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, WA, 98683
In an effort to determine whether fish populations in an area affected by wood tar waste exhibited health effects, fish were collected and analyzed with histopathology. Multiple species, including Mottled Sculpin (Cottus bairdii), Creek Chub (Semotilus atromaculatus), White Sucker (Catostumus commersonii), Redside Dace (Clinostomus elongatus), Common Shiner (Luxilus cornutus), and Western Blacknose Dace (Rhinichthys obtusus) were sampled from a reference site, Meade Run, and potentially affected streams, Kinzua Creek and Threemile Run, in northwestern Pennsylvania. A full histopathological evaluation was conducted to identify microscopic abnormalities potentially associated with wood tar exposure. The evaluation identified primarily parasites associated with tissue changes. These included microsporidian parasites in the ovaries of Common Shiner and Western Blacknose Dace; myxozoan cysts in the muscle of Common Shiner, Creek Chub, and Western Blacknose Dace; trematode cysts in the muscle of Creek Chub, Redside Dace and Common Shiner; and coccidia in spleen or pancreas of Creek Chub and Common Shiner. Microscopic abnormalities potentially associated with chemical exposure included ceroid/lipofuscin deposits in the meninges of the olfactory lobe of the brain in Common Shiner, Western Blacknose Dace, and Creek Chub, as well as bile duct proliferation and a biliary tumor in Creek Chub. Overall, the findings did not reveal significant microscopic pathology consistent with exposure to wood tar waste.
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\"}}]}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
In 1943, Aldo Leopold observed that the real problem of wildlife management is not how to handle wildlife, but how to manage humans. As with any other aspect of wildlife management, social sciences can improve understanding the human dimensions of wildlife disease management (WDM). Human activities have accelerated the emergence of wildlife diseases, and human concerns about the ecological, social, and economic impacts of wildlife diseases and their management have led to diseases becoming headline-worthy public issues. This chapter provides guidance to help front-line professionals understand and address the public’s perspectives and behaviors relevant to WDM. This chapter focuses on practical needs of wildlife disease managers who have to consider and interact with specific stakeholders and the broader public. The chapter does not dive deeply into social science; instead it briefly reviews some concepts that are most relevant to WDM. The chapter also suggests where to look for assistance and additional resources for further reading. Following brief introductory comments, the chapter is organized around a simple model of the general process for WDM. It addresses three key areas where social science can assist in WDM—audience research to understand stakeholders; engaging stakeholders in wildlife disease management; and using risk communication about wildlife diseases and disease management to inspire risk-wise behavior.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Techniques in disease surveillance and investigation in Book 15: Field Manual of Wildlife Diseases","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm15C8","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service and National Park Service","usgsCitation":"Leong, K.M, and Decker, D.J., 2020, Human dimensions considerations in wildlife disease management: U.S. Geological Survey Techniques and Methods, book 15, chap. C8, 21 p., https://doi.org/10.3133/tm15C8.","productDescription":"iv, 21 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-101578","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":373455,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/15/c08/coverthb3.jpg"},{"id":373456,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/15/c08/tm15c8.pdf","text":"Report","size":"1.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T&M 15–C8"}],"publicComments":"This report is Chapter 8 of Section C: Techniques in disease surveillance and investigation in Book 15: Field Manual of Wildlife Diseases\n","contact":"Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711–6223
To better understand the streamflow trends at the streamgages in the Elkhorn River Basin in Nebraska, the U.S. Geological Survey (USGS) in cooperation with the Lower Elkhorn Natural Resources District further investigated streamflow trends at the eight streamgages on the Elkhorn River, Salt Creek, and the Lower Platte River that indicated a positive trend in streamflow characteristics and analyzed precipitation trends in the four basins upstream from the Elkhorn River Basin streamgages. An analysis of four streamgages in the Elkhorn River Basin, one streamgage in Salt Creek Basin, and three streamgages in the Lower Platte River Basin that had previously indicated trends in selected annual mean streamflow, annual low flows, fall low flows, and growing season monthly mean streamflows metrics were analyzed for the period from 1961 to 2011. A streamgage in the Upper Elkhorn River Basin (Elkhorn River at Neligh, Nebraska [USGS station 06798500; maintained by USGS from water years 1930 to 1993, maintained by Nebraska Department of Natural Resources from water years 1994 to 2019]) had significant positive trends in annual mean streamflow and insignificant trends for other streamflow metrics whereas the lower three sites (Logan Creek near Uehling, Nebr. [USGS station 06799500]; Maple Creek at Nickerson, Nebr. [USGS station 06800000]; and Elkhorn River at Waterloo, Nebr. [USGS station 06800500]) had significant positive trends for annual mean streamflow, for all durations of the annual low-flow periods (1-day, 2-day, 3-day, 7-day, 14-day, 30-day, 60-day, 90-day, and 183-day periods), for all durations of the low-flow periods in October–November (1-day, 2-day, 3-day, 7-day, 14-day, 30-day, and 60-day periods), and for monthly mean streamflow for July, August, and September. Upstream from the confluence of the Elkhorn River and the Platte River, the Platte River at North Bend, Nebr. (USGS station 06796000), streamgage indicated insignificant trends for most streamflow metrics. A streamgage in the Salt Creek Basin (Salt Creek at Greenwood, Nebr. [USGS station 06803555]) also indicated positive trends in some low-flows metrics. Streamflow at the Platte River at Louisville, Nebr. (USGS station 06805500), streamgage, downstream from the Salt Creek and Elkhorn River inflows, indicated significant positive trends in most annual and all October–November low flows and August mean streamflow but insignificant trends in annual mean streamflow and June, July, and September monthly mean streamflows. Streamflow records for the Platte River near Duncan, Nebr. (USGS station 06774000), streamgage only indicated a significant trend in the August mean streamflow; no other metrics had significant trends at the streamgage.
The trend analyses are sensitive to the period that is analyzed for trends. Sites with the most significant trends for low-flow metrics for the period 1961–2011 have fewer significant trends for low-flow metrics for the period after 1980–2011.
The results indicate that positive trends in low flows at the Salt Creek and Elkhorn River streamgages may be contributing to positive trends in low flows for the Platte River at Louisville, Nebr., streamgage. Likewise, streamflow in the Salt Creek and Elkhorn River Basins may be contributing to the positive trend in August mean streamflow for the Platte River at Louisville, Nebr., streamgage, three lower Elkhorn River streamgages, and the Salt Creek streamgage.
Precipitation was also examined as a primary cause for streamflow trends in the Elkhorn River Basin. For the four streamgages in the Elkhorn River Basin, relations between precipitation and streamflow were examined on an annual and monthly basis using linear regression. In general, the goodness of fit for the linear relations was poor with coefficient of determination values of less than or equal to 0.10 for four of the eight relations. Only one significant increase in annual precipitation upstream from the four streamgages and the frequent detection of significant increases in streamflow after removing the effect of precipitation indicate that other factors besides precipitation may have played a role in the significant positive trends in low-flow periods in the lower Elkhorn River and its tributaries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205016","collaboration":"Prepared in cooperation with the Lower Elkhorn Natural Resources District","usgsCitation":"Dietsch, B.J., and Strauch, K.R., 2020, Trends in streamflow and precipitation for selected sites in the Elkhorn River Basin and in streamflow in the Salt Creek and Platte River Basins, Nebraska, 1961–2011: U.S. Geological Survey Scientific Investigations Report 2020–5016, 20 p., https://doi.org/10.3133/sir20205016.","productDescription":"iv, 20 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-102970","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":373469,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5016/sir20205016.pdf","text":"Report","size":"2.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5016"},{"id":373468,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5016/coverthb.jpg"},{"id":399636,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109799.htm"}],"country":"United States","state":"Nebraska","otherGeospatial":"Elkhorn River Basin, Salt Creek Basin, Platte River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.7283,\n 40.9667\n ],\n [\n -96,\n 40.9667\n ],\n [\n -96,\n 42.7\n ],\n [\n -99.7283,\n 42.7\n ],\n [\n -99.7283,\n 40.9667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
The key to Merlin (Falco columbarius) management is maintaining an interspersion of groves of deciduous or coniferous trees for nesting and open grasslands for hunting. Merlins do not build their own nests but rather use former nests of other bird species, including those of corvids (crows, ravens, and magpies) and accipitrids (hawks). In recent decades, Merlins have established breeding populations in urban and residential areas in the northern Great Plains.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842R","usgsCitation":"Konrad, P.M., Shaffer, J.A., and Igl, L.D., 2020, The effects of management practices on grassland birds—Merlin (Falco columbarius), chap. R of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 21 p., https://doi.org/10.3133/pp1842R.","productDescription":"iv, 12 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-093874","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":373441,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/r/coverthb.jpg"},{"id":373442,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/r/pp1842r.pdf","text":"Report","size":"2.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–R"}],"otherGeospatial":"North America","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Keys to Sprague’s Pipit (Anthus spragueii) management include providing suitable grassland habitat, especially native prairie, with intermediate vegetation height and low visual obstruction, and controlling succession therein. Sprague’s Pipits have been reported to use habitats with no more than 49 centimeters (cm) average vegetation height, 4–14 cm visual obstruction reading, 15–53 percent grass cover, less than (<) 21 percent forb cover, <18 percent shrub cover, <44 percent bare ground, 10–63 percent litter cover, and less than or equal to 11 cm litter depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842W","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Nenneman, M.P., Wooten, T.L., Thiele, J.P.,and Euliss, B.R., 2020, The effects of management practices on grassland birds—Sprague’s Pipit (Anthus spragueii), chap. W of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 21 p., https://doi.org/10.3133/pp1842W.","productDescription":"v, 21 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-096448","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":373440,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/w/pp1842w.pdf","text":"Report","size":"2.10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–W"},{"id":373439,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/w/coverthb.jpg"}],"country":"United States, Canada","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Numerous studies have documented the linkages between agricultural nitrogen loads and surface water degradation. In contrast, potential water quality improvements due to agricultural best management practices are difficult to detect because of the confounding effect of background nitrate removal rates, as well as the groundwater-driven delay between land surface action and stream response. To characterize background controls on nitrate removal in two agricultural catchments, we calibrated groundwater travel time distributions with subsurface environmental tracer data to quantify the lag time between historic agricultural inputs and measured baseflow nitrate. We then estimated spatially distributed loading to the water table from nitrate measurements at monitoring wells, using machine learning techniques to extrapolate the loading to unmonitored portions of the catchment to subsequently estimate catchment removal controls. Multiple models agree that in-stream processes remove as much as 75% of incoming loads for one subcatchment while removing <20% of incoming loads for the other. The use of a spatially variable loading field did not result in meaningfully different optimized parameter estimates or model performance when compared with spatially constant loading derived directly from a county-scale agricultural nitrogen budget. Although previous studies using individual well measurements have shown that subsurface denitrification due to contact with a reducing argillaceous confining unit plays an important role in nitrate removal, the catchment-scale contribution of this process is difficult to quantify given the available data. Nonetheless, the study provides a baseline characterization of nitrate transport timescales and removal mechanisms that will support future efforts to detect water quality benefits from ongoing best management practice implementation.
","language":"English","publisher":"American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America","doi":"10.1002/jeq2.20049","usgsCitation":"Zell, W.O., Culver, T., Sanford, W.E., and Goodall, J.L., 2020, Quantifying background nitrate removal mechanisms in an agricultural watershed with contrasting subcatchment baseflow concentrations: Journal of Environmental Quality, v. 49, no. 2, p. 392-403, https://doi.org/10.1002/jeq2.20049.","productDescription":"12 p.","startPage":"392","endPage":"403","ipdsId":"IP-110824","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":437051,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VWY11M","text":"USGS data release","linkHelpText":"MODFLOW-2005 and MODPATH6 models used to simulate groundwater flow and nitrate transport in two tributaries to the Upper Chester River, Maryland"},{"id":430521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Upper Chester study area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76,\n 39.333\n ],\n [\n -76,\n 39.25\n ],\n [\n -75.916667,\n 39.25\n ],\n [\n -75.916667,\n 39.333\n ],\n [\n -76,\n 39.333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Zell, Wesley O. 0000-0002-8782-6627","orcid":"https://orcid.org/0000-0002-8782-6627","contributorId":339721,"corporation":false,"usgs":true,"family":"Zell","given":"Wesley","email":"","middleInitial":"O.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":904929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Culver, Teresa B","contributorId":339722,"corporation":false,"usgs":false,"family":"Culver","given":"Teresa B","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":904930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":904931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goodall, Jonathan L","contributorId":339724,"corporation":false,"usgs":false,"family":"Goodall","given":"Jonathan","email":"","middleInitial":"L","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":904932,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209617,"text":"70209617 - 2020 - Well predictive performance of play-wide and Subarea Random Forest models for Bakken productivity","interactions":[],"lastModifiedDate":"2020-08-06T19:34:08.003257","indexId":"70209617","displayToPublicDate":"2020-03-25T08:07:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2419,"text":"Journal of Petroleum Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Well predictive performance of play-wide and Subarea Random Forest models for Bakken productivity","docAbstract":"In recent years, geologists and petroleum engineers have struggled to clearly identify the mechanisms that drive productivity in horizontal, hydraulically-fractured oil wells producing from the middle member of the Bakken formation. This paper fills a gap in the literature by showing how this play’s heterogeneity affects factors that drive well productivity. It is important because understanding the relative strength of productivity drivers and how predictors vary spatially facilitates best-practices for well site selection and well completion design. The paper describes an application of the Random Forest (RF) machine learning technique to identify these mechanisms and to evaluate their importance across 9 subareas of the North Dakota portion of the Bakken play. The study examined productivity of 7311 wells initiating production from 2010 through 2017. Well productivity varied considerably across the 9 subareas within the play, so it was not surprising that the dominant predictors, the initial 180-day water cut and the 30-day initial gas production, vary spatially to mirror local conditions that strongly affect well productivity. The relative importance of well completion predictor variables, that is, the numbers of fractures stages per well, volume of injected proppant per stage, volume of injected fluids per stage, and lateral length, varied considerably across the subareas. Statistical permutation tests are presented that generally confirm the importance rankings. Subarea Random Forest models explained from 50 percent to 82 percent of the variation in productivity test samples while the play-wide model explained 73 percent of the test sample well productivity. Weakness in the predictive ability of the Random Forest models are traced to the limited variability in the training data. Implications of the empirical findings regarding the Bakken play for operators and for research and government institutions are discussed in the concluding section.","language":"English","publisher":"Elsevier","doi":"10.1016/j.petrol.2020.107150","usgsCitation":"Attanasi, E., Freeman, P., and Coburn, T., 2020, Well predictive performance of play-wide and Subarea Random Forest models for Bakken productivity: Journal of Petroleum Science and Engineering, v. 191, 107150, 12 p., https://doi.org/10.1016/j.petrol.2020.107150.","productDescription":"107150, 12 p.","ipdsId":"IP-109805","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":457284,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.petrol.2020.107150","text":"Publisher Index Page"},{"id":374051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.80859375,\n 47.931066347509784\n ],\n [\n -107.2705078125,\n 46.5286346952717\n ],\n [\n -103.5791015625,\n 45.02695045318546\n ],\n [\n -101.689453125,\n 45.30580259943578\n ],\n [\n -99.84374999999999,\n 46.89023157359399\n ],\n [\n -98.701171875,\n 48.951366470947725\n ],\n [\n -108.10546875,\n 48.951366470947725\n ],\n [\n -109.072265625,\n 48.980216985374994\n ],\n [\n -108.80859375,\n 47.931066347509784\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"191","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":198728,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil D.","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":787187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Philip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":224150,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":787188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coburn, Tim","contributorId":224151,"corporation":false,"usgs":false,"family":"Coburn","given":"Tim","email":"","affiliations":[{"id":38022,"text":"University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":787189,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209556,"text":"70209556 - 2020 - Sequential biodegradation of 1,2,4-trichlorobenzene at oxic-anoxic groundwater interfaces in model laboratory columns","interactions":[],"lastModifiedDate":"2020-08-06T19:17:57.204399","indexId":"70209556","displayToPublicDate":"2020-03-25T07:32:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Sequential biodegradation of 1,2,4-trichlorobenzene at oxic-anoxic groundwater interfaces in model laboratory columns","docAbstract":"Halogenated organic solvents such as chlorobenzenes (CBs) are frequent groundwater contaminants due to legacy spills. When contaminated anaerobic groundwater discharges into surface water through wetlands and other transition zones, aeration can occur from various physical and biological processes at shallow depths, resulting in oxic-anoxic interfaces (OAIs). This study investigated the potential for 1,2,4-trichlorobenzene (1,2,4-TCB) biodegradation at OAIs. A novel upflow column system was developed to create stable anaerobic and aerobic zones, simulating a natural groundwater OAI. Two columns containing (1) sand and (2) a mixture of wetland sediment and sand were operated continuously for 295 days with varied doses of 0.14-1.4 mM sodium lactate (NaLac) as a model electron donor. Both column matrices supported anaerobic reductive dechlorination and aerobic degradation of 1,2,4-TCB spatially separated between anaerobic and aerobic zones. Reductive dechlorination produced a mixture of di- and monochlorobenzene daughter products, with estimated zero-order dechlorination rates up to 31.3 µM/hr. Aerobic CB degradation, limited by available dissolved oxygen, occurred for 1,2,4-TCB and all dechlorinated daughter products. Initial reductive dechlorination did not enhance the overall observed extent or rate of subsequent aerobic CB degradation. Increasing NaLac dose increased the extent of reductive dechlorination, but suppressed aerobic CB degradation at 1.4 mM NaLac due to increased oxygen demand. 16S-rRNA sequencing of biofilm microbial communities revealed strong stratification of functional anaerobic and aerobic organisms between redox zones including the sole putative reductive dechlorinator detected in the columns, Dehalobacter. The sediment mixture column supported enhanced reductive dechlorination compared to the sand column at all tested NaLac doses and growth of Dehalobacter populations up to 4.1×108 copies/g (51% relative abundance), highlighting the potential benefit of sediments in reductive dechlorination processes. Results from these model systems suggest both substantial anaerobic and aerobic CB degradation can co-occur along the OAI at contaminated sites where bioavailable electron donors and oxygen are both present.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2020.103639","usgsCitation":"Chow, S.J., Lorah, M.M., Wadhawan, A.R., Durant, N.D., and Bouwer, E.J., 2020, Sequential biodegradation of 1,2,4-trichlorobenzene at oxic-anoxic groundwater interfaces in model laboratory columns: Journal of Contaminant Hydrology, v. 231, 103639, 13 p., https://doi.org/10.1016/j.jconhyd.2020.103639.","productDescription":"103639, 13 p.","ipdsId":"IP-111522","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":457286,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7217665","text":"External Repository"},{"id":373945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"231","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chow, Steven J.","contributorId":224063,"corporation":false,"usgs":false,"family":"Chow","given":"Steven","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":786947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lorah, Michelle M. 0000-0002-9236-587X","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":224040,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","middleInitial":"M.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wadhawan, Amar R.","contributorId":224041,"corporation":false,"usgs":false,"family":"Wadhawan","given":"Amar","email":"","middleInitial":"R.","affiliations":[{"id":40822,"text":"Arcadis U.S. Inc.","active":true,"usgs":false}],"preferred":false,"id":786844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Durant, Neal D.","contributorId":224042,"corporation":false,"usgs":false,"family":"Durant","given":"Neal","email":"","middleInitial":"D.","affiliations":[{"id":36571,"text":"Geosyntec Consultants","active":true,"usgs":false}],"preferred":false,"id":786845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bouwer, Edward J.","contributorId":224043,"corporation":false,"usgs":false,"family":"Bouwer","given":"Edward","email":"","middleInitial":"J.","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":786846,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70209126,"text":"ofr20201025 - 2020 - Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon and Clear Lake Reservoir, California—2017 Monitoring Report","interactions":[],"lastModifiedDate":"2020-03-25T11:48:27","indexId":"ofr20201025","displayToPublicDate":"2020-03-24T16:15:59","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1025","displayTitle":"Juvenile Lost River and Shortnose Sucker Year-Class Formation, Survival, and Growth in Upper Klamath Lake, Oregon and Clear Lake Reservoir, California—2017 Monitoring Report","title":"Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon and Clear Lake Reservoir, California—2017 Monitoring Report","docAbstract":"Populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir (hereinafter referred to as Clear Lake; fig. 1), California, are experiencing long-term declines in abundance. Upper Klamath Lake populations are decreasing because juvenile suckers are not surviving and recruiting into the adult population. Most juvenile sucker mortality occurs within the first year of life in Upper Klamath Lake. Annual production of juvenile suckers in Clear Lake appear to be highly variable and may not occur at all in very dry years. However, juvenile sucker survival is much higher in Clear Lake, with some suckers surviving to join spawning aggregations. Long-term monitoring of juvenile sucker populations is needed to 1) determine if there are annual and species-specific differences in production, survival, and growth; 2) better understand when juvenile sucker mortality is greatest; 3) help identify potential causes of high juvenile sucker mortality particularly in Upper Klamath Lake; and 4) monitor for successful juvenile survival in Upper Klamath Lake.
The U.S. Geological Survey (USGS) began a summer juvenile sucker monitoring program in 2015 to track cohorts over time in Upper Klamath and Clear Lakes. The juvenile sucker monitoring program involved using trap net data at fixed sites to determine the status of juvenile suckers. Annual variability in apparent age-0 sucker production, juvenile sucker survival, and growth were tracked. Using genetic markers, suckers were classified as one of three taxa; shortnose (combinations of shortnose and Klamath largescale suckers), Lost River, or suckers with genetic markers of both species (Intermediate [Prob]). By using catch data, we generated taxa-specific indices of year-class strength, August–September apparent survival, and overwinter apparent survival. We also examined the prevalence and severity of afflictions such as parasites, wounds, and deformities.
The Upper Klamath Lake year-class strength indices for both Lost River and shortnose suckers were slightly lower in 2015 and 2017 than in 2016. The ratios of age-0 Lost River suckers to age-0 shortnose suckers captured in August in Upper Klamath Lake were low in 2015 and 2017, given that adult Lost River suckers are more abundant and more fecund than adult shortnose suckers. This may indicate lower egg, larval, or juvenile survival or poorer spawning success for Lost River suckers than shortnose suckers in these two years. Apparent relative age-0 survival indices for Lost River suckers from August to September in Upper Klamath Lake were greater in 2015 (0.29) than in 2016 (0.16) or 2017 (0.14). Age-0 shortnose sucker catch rates increased between August and September in 2015, possibly indicating new individuals of this species were still recruiting to the lake between the two sampling periods. August to September relative survival indices for Upper Klamath Lake shortnose suckers were 0.35 in 2016 and 0.00 in 2017.
We predicted year-class strength would be greater in Clear Lake in years when high spring-time lake elevations and instream flow allowed adult suckers access to spawning habitat in the Willow Creek drainage. Instream flows and lake elevations were sufficient to allow adult suckers to access Willow Creek during the 2016 and 2017 spawning seasons, and age-0 suckers were detected in Clear Lake both years. Higher lake surface elevations and instream flows in 2017 than in 2016 were not associated with higher year-class strength indices in 2017 than in 2016. Low lake surface elevations appeared to limit access by adults to Willow Creek during the 2014 and 2015 spawning seasons and age-0 suckers were not detected in Clear Lake during these years. Nineteen shortnose suckers from the 2014 cohort were captured in Clear Lake in 2017. A 2015 cohort of shortnose suckers was captured as age-1 in 2016 and as age-2 in 2017. The most likely explanation for increasing catch rates of the 2015 cohort is that the higher Willow Creek flows in 2016 and 2017 facilitated the movement of stream-resident suckers, spawned in 2014 and 2015 downstream into Clear Lake. Due to uncertainty in the genetic identification of non-Lost River suckers, these fish are equally likely to be Klamath largescale or shortnose suckers (Hoy and Ostberg, 2015).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201025","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Bart, R.J., Burdick, S.M., Hoy, M.S., and Ostberg, C.O., 2020, Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon and Clear Lake Reservoir, California—2017 Monitoring Report: U.S. Geological Survey Open-File Report 2020–1025, 36 p., https://doi.org/10.3133/ofr20201025.","productDescription":"v, 36 p.","onlineOnly":"Y","ipdsId":"IP-112875","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":373492,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1025/ofr20201025.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1025"},{"id":373491,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1025/coverthb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Clear Lake Reservoir, Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.77197265625,\n 40.763901280945866\n ],\n [\n -121.22314453124999,\n 40.763901280945866\n ],\n [\n -121.22314453124999,\n 43.08493742707592\n ],\n [\n -123.77197265625,\n 43.08493742707592\n ],\n [\n -123.77197265625,\n 40.763901280945866\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Recent work on cores and outcrops of the Middle-Upper Triassic Shublik Formation has facilitated surface to subsurface correlation of depositional sequences across the Alaska North Slope. Five transgressive-regressive depositional sequences have been defined within three large-scale stratigraphic units. Outcrop spectral gamma-ray (GR) profiles were used to correlate observed stacking patterns with nearby exploration wells, and GR logs from 161 exploration wells were used to correlate the three large-scale stratigraphic units across the North Slope and nearby offshore. Interpretations of depositional facies and sequence stratigraphy in cores from 26 wells were used to corroborate regional correlations. Isochore maps constructed for each of the three stratigraphic units illustrate the influence of accommodation on depositional patterns and suggest reactivation of several older tectonic elements during Shublik deposition. An isochore map of the richest, oil-prone interval of the Shublik Formation reveals a thick pod south of Harrison Bay, the eastern part of which lies beneath a recent giant Shublik-sourced oil discovery in the Cretaceous Nanushuk Formation. In addition, when integrated with thermal maturity, this isochore map may provide leads for areas that are optimal for unconventional resource exploration.
","language":"English","publisher":"Society of Exploration Geophysicists, American Association of Petroleum Geologists","doi":"10.1190/INT-2019-0195.1","usgsCitation":"Rouse, W.A., Whidden, K.J., Dumoulin, J.A., and Houseknecht, D.W., 2020, Surface to subsurface correlation of the Middle-Upper Triassic Shublik Formation within a revised sequence stratigraphic framework: Interpretation, v. 8, no. 2, p. SJ1-SJ16, https://doi.org/10.1190/INT-2019-0195.1.","productDescription":"16 p.","startPage":"SJ1","endPage":"SJ16","ipdsId":"IP-111994","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":377207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.5654296875,\n 66.96447630005638\n ],\n [\n -140.9765625,\n 66.96447630005638\n ],\n [\n -140.9765625,\n 71.31487666166718\n ],\n [\n -159.5654296875,\n 71.31487666166718\n ],\n [\n -159.5654296875,\n 66.96447630005638\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rouse, William A. 0000-0002-0790-370X wrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0790-370X","contributorId":4172,"corporation":false,"usgs":true,"family":"Rouse","given":"William","email":"wrouse@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":795306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":795307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":795308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":795309,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}