Large-scale computational investigations of groundwater levels are proposed to accelerate science delivery through a workflow spanning database assembly, statistics, and information synthesis and packaging. A water-availability study of the Mississippi River alluvial plain, and particularly the Mississippi River Valley alluvial aquifer (MRVA), is ongoing. Software (visGWDBmrva) has been released as part of the study that demonstrates groundwater informatics for the aquifer. Considerable water-level data collected by multiple agencies over a seven-state area exist (18,903 wells; 287,272 measurements [April 22, 2019]). Data and metadata quality assurance methods, basic statistics, hydrograph visualization, outlier identification, hypothesis testing, and time-series modeling are described. Two approaches (generalized additive models [GAMs] and support vector machines [SVMs]) are used for data interpolation and extension to monthly water-level estimates. Numerical congruence between GAM and SVM estimates will be useful to limit inclusion of monthly estimates from subsequent science activities.
Tribal communities may benefit from land management activities that enhance their use of resources on tribal lands. The Bureau of Indian Affairs is implementing a 5-year vegetation management program to provide support for projects that develop and use natural and cultural resources and improve opportunities for agricultural activities to benefit 20 Indian Tribes and Nations in the Eastern Oklahoma Region of the Bureau of Indian Affairs. The bureau is working with individual Tribes to identify project objectives and design treatments, which include prescribed burning, timber removal, thinning, and reduction of hazardous fuels. The total action area for the vegetation management program is estimated to be 236,575 acres, representing approximately 1 percent of the region.
A biological assessment was prepared, in cooperation with the bureau and U.S. Fish and Wildlife Service, to evaluate the potential effects of the proposed vegetation management program on 22 federally threatened, endangered, and candidate species that may occur within the Eastern Oklahoma Region. The species evaluated included one plant, two insects, one reptile, five fresh-water mussels, four fishes, five birds, and four bats. Because the proposed treatments will be largely restricted to terrestrial systems, it is expected that there will be no adverse effects on the 15 species associated with aquatic habitats, provided that best management practices are followed. The proposed treatments may affect but are unlikely to adversely affect six of the primarily terrestrial species (the Papaipema eryngii [rattlesnake master borer], Picoides borealis [red-cockaded woodpecker], Myotis grisescens [gray bat], Myotis sodalis [Indiana bat], Myotis septentrionalis [northern long-eared bat], and Corynorhinus townsendii ingens [Ozark big-eared bat]), provided that best management practices are followed, including avoidance of critical habitat features.
The only species likely to be adversely affected by the proposed treatments is Nicrophorus americanus (American burying beetle) as a consequence of short-term disturbances to soils and vegetation. Most adverse effects of the treatments (such as soil compaction and decreased cover in the forest understory) are expected to be short term (habitat will recover or be restored within 5 years of treatments). Less than 1 percent of the action area is expected to result in long-term adverse effects to the American burying beetle as a result of permanent cover changes that persist for more than 5 years. It is expected that the primary treatments will be largely beneficial to the American burying beetle population in the region by reducing the risk of high-severity fires and expansion of invasive woody shrubs, such as Juniperus virginiana (eastern redcedar) within potential beetle habitat and the surrounding landscape. Overall, the proposed management program is expected to provide long-term benefits to American burying beetle habitat across 91 percent of the action area.
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The US Geological Survey (USGS) is currently (2020) integrating its water science programs to better address the nation’s greatest water resource challenges now and into the future. This integration will rely, in part, on data from 10 or more intensively monitored river basins from across the USA. A team of USGS scientists was convened to develop a systematic, quantitative approach to prioritize candidate basins for this monitoring investment to ensure that, as a group, the 10 basins will support the assessment and forecasting objectives of the major USGS water science programs. Candidate basins were the level-4 hydrologic units (HUC04) with some of the smaller HUC04s being combined; median candidate-basin area is 46,600 km2. Candidate basins for the contiguous United States (CONUS) were grouped into 18 hydrologic regions. Ten geospatial variables representing land use, climate change, water use, water-balance components, streamflow alteration, fire risk, and ecosystem sensitivity were selected to rank candidate basins within each of the 18 hydrologic regions. The two highest ranking candidate basins in each of the 18 regions were identified as finalists for selection as “Integrated Water Science Basins”; final selection will consider input from a variety of stakeholders. The regional framework, with only one basin selected per region, ensures that as a group, the basins represent the range in major drivers of the hydrologic cycle. Ranking within each region, primarily based on anthropogenic stressors of water resources, ensures that settings representing important water-resource challenges for the nation will be studied.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-020-08403-1","usgsCitation":"Van Metre, P.C., Qi, S.L., Deacon, J.R., Dieter, C., Driscoll, J.M., Fienen, M.N., Kenney, T.A., Lambert, P.M., Lesmes, D.P., Mason, C., Mueller-Solger, A., Musgrove, M., Painter, J.A., Rosenberry, D.O., Sprague, L.A., Tesoriero, A.J., Windham-Myers, L., and Wolock, D.M., 2020, Prioritizing river basins for intensive monitoring and assessment by the US Geological Survey: Environmental Modeling & Assessment, v. 192, 458, 17 p., https://doi.org/10.1007/s10661-020-08403-1.","productDescription":"458, 17 p.","ipdsId":"IP-114496","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456145,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-020-08403-1","text":"Publisher Index Page"},{"id":436898,"rank":0,"type":{"id":30,"text":"Data 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Hedvig","contributorId":225727,"corporation":false,"usgs":false,"family":"Nenzen","given":"Hedvig","email":"","affiliations":[{"id":13584,"text":"Natural Resources Canada, Canadian Forest Service","active":true,"usgs":false}],"preferred":false,"id":792000,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Nielsen, Scott","contributorId":225729,"corporation":false,"usgs":false,"family":"Nielsen","given":"Scott","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":792002,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Parisien, Marc-André","contributorId":225730,"corporation":false,"usgs":false,"family":"Parisien","given":"Marc-André","affiliations":[{"id":13584,"text":"Natural Resources Canada, Canadian Forest Service","active":true,"usgs":false}],"preferred":false,"id":792003,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Pedlar, John","contributorId":225731,"corporation":false,"usgs":false,"family":"Pedlar","given":"John","email":"","affiliations":[{"id":13584,"text":"Natural Resources Canada, Canadian Forest Service","active":true,"usgs":false}],"preferred":false,"id":792004,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Price, David","contributorId":225732,"corporation":false,"usgs":false,"family":"Price","given":"David","affiliations":[{"id":13584,"text":"Natural Resources Canada, Canadian Forest Service","active":true,"usgs":false}],"preferred":false,"id":792005,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Schmiegelow, Fiona","contributorId":225733,"corporation":false,"usgs":false,"family":"Schmiegelow","given":"Fiona","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":792006,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Slattery, Stuart","contributorId":225734,"corporation":false,"usgs":false,"family":"Slattery","given":"Stuart","affiliations":[{"id":7182,"text":"Ducks Unlimited Canada","active":true,"usgs":false}],"preferred":false,"id":792007,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Sonnentag, Oliver 0000-0001-9333-9721","orcid":"https://orcid.org/0000-0001-9333-9721","contributorId":225735,"corporation":false,"usgs":false,"family":"Sonnentag","given":"Oliver","email":"","affiliations":[{"id":41192,"text":"Université de Montreal","active":true,"usgs":false}],"preferred":false,"id":792008,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Thompson, Daniel","contributorId":225736,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","affiliations":[{"id":13584,"text":"Natural Resources Canada, Canadian Forest Service","active":true,"usgs":false}],"preferred":false,"id":792009,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Whitman, Ellen","contributorId":225737,"corporation":false,"usgs":false,"family":"Whitman","given":"Ellen","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":792010,"contributorType":{"id":1,"text":"Authors"},"rank":31}]}} ,{"id":70211044,"text":"70211044 - 2020 - Wildfire-driven changes in hydrology mobilize arsenic and metals from legacy mine waste","interactions":[],"lastModifiedDate":"2020-07-13T13:47:04.995291","indexId":"70211044","displayToPublicDate":"2020-07-02T08:27:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire-driven changes in hydrology mobilize arsenic and metals from legacy mine waste","docAbstract":"Wildfires burning in watersheds that have been mined and since revegetated pose unique risks to downstream water supplies. A wildfire near Boulder, Colorado that burned a forested watershed recovering from mining disturbance that occurred 80-160 years ago allowed us to 1) assess arsenic and metal contamination in streams draining the burned area for a five-year period after the wildfire and 2) determine the fire-affected hydrologic drivers that convey arsenic and metals to surface water. Most metal concentrations were low in the circumneutral waters draining the burned area. Water and sediment collected from streams downstream of the burned area had elevated arsenic concentrations during and after post-fire storms. Mining-related deposits were the main source of arsenic to streams. An increased proportion of overland flow relative to infiltration after the fire mobilized arsenic- and metal- rich surface deposits and wildfire ash into streams within and downstream of the burned area. The deposition of this sediment into stream channels resulted in the remobilization of arsenic for the five-year post-fire study period. It is also possible that enhanced subsurface flow after the fire increased contact of water with arsenic-bearing minerals exposed in underground mine workings. Other studies have reported that wildfire ash can be an important source of arsenic and metals to surface waters, but wildfire ash was not an important source of arsenic in this study. Predicted increases in frequency, size, and intensity of wildfires in the western U.S., a region with widely dispersed historical mines, suggest that the intersection of legacy mining and post-wildfire hydrologic response poses an increasing risk for water supplies.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.140635","usgsCitation":"Murphy, S.F., McCleskey, R., Martin, D.A., Holloway, J.M., and Writer, J., 2020, Wildfire-driven changes in hydrology mobilize arsenic and metals from legacy mine waste: Science of the Total Environment, v. 743, 140635, 15 p., https://doi.org/10.1016/j.scitotenv.2020.140635.","productDescription":"140635, 15 p.","ipdsId":"IP-118726","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456160,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.140635","text":"Publisher Index Page"},{"id":436899,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P941BIYS","text":"USGS data release","linkHelpText":"Chemistry of water, stream sediment, wildfire ash, soil, dust, and mine waste for Fourmile Creek Watershed, Colorado, 2010-2019"},{"id":376298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Boulder","otherGeospatial":"Four Mile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.45948028564453,\n 39.98211859887411\n ],\n [\n -105.33416748046875,\n 39.98211859887411\n ],\n [\n -105.33416748046875,\n 40.04049503186035\n ],\n [\n -105.45948028564453,\n 40.04049503186035\n ],\n [\n -105.45948028564453,\n 39.98211859887411\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"743","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":792586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. Blaine","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":792587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":168662,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":792588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holloway, JoAnn M. 0000-0003-3603-7668","orcid":"https://orcid.org/0000-0003-3603-7668","contributorId":201855,"corporation":false,"usgs":true,"family":"Holloway","given":"JoAnn","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":792589,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Writer, Jeffrey H.","contributorId":203440,"corporation":false,"usgs":false,"family":"Writer","given":"Jeffrey H.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":792590,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70219051,"text":"70219051 - 2020 - Fish growth rates and lake sulphate explain variation in mercury levels in ninespine stickleback (Pungitius pungitius) on the Arctic Coastal Plain of Alaska","interactions":[],"lastModifiedDate":"2021-03-22T13:16:14.021201","indexId":"70219051","displayToPublicDate":"2020-07-02T08:11:09","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Fish growth rates and lake sulphate explain variation in mercury levels in ninespine stickleback (Pungitius pungitius) on the Arctic Coastal Plain of Alaska","docAbstract":"Mercury concentrations in freshwater food webs are governed by complex biogeochemical and ecological interactions that spatially vary and are often mediated by climate. The Arctic Coastal Plain of Alaska (ACP) is a heterogeneous, lake-rich landscape where variability in mercury accumulation is poorly understood. Earlier research indicated that the level of catchment influence on lakes varied spatially on the ACP, and affected mercury accumulation in lake sediments. This work sought to determine drivers of spatial variation in mercury accumulation in lake food webs on the ACP. Three lakes that were a priori identified as “high catchment influence” (Reindeer Camp region) and three lakes that were a priori identified as “low catchment influence” (Atqasuk region) were sampled, and variability in water chemistry, food web ecology, and mercury accumulation was investigated. Among-lake differences in ninespine stickleback (Pungitius pungitius) length-adjusted methylmercury concentrations were significantly explained by sulphate concentration in lake water, a tracer of catchment runoff input. This effect was mediated by fish growth, which had no pattern between regions. Together, lake water sulphate concentration and fish age-at-size (proxy for growth) accounted for nearly all of the among-lake variability in length-adjusted methylmercury concentrations in stickleback (R2adj = 0.94, p < 0.01). The percentage of total mercury as methylmercury (a proxy for net Hg methylation) was higher in sediments of more autochthonous, “low catchment influence” lakes (p < 0.05), and in the periphyton of more allochthonous, “high catchment influence” lakes (p < 0.05). The results indicate that dominant sources of primary production (littoral macrophyte/biofilm vs. pelagic phytoplankton) and food web structure (detrital vs. grazing) are regulated by catchment characteristics on the ACP, and that this ultimately influences the amount of methylmercury in the aquatic food web. These results have important implications for predicting future mercury concentrations in fish in lakes where fish growth rates and catchment inputs may change in response to a changing climate.
The Biological Condition Gradient (BCG) is a conceptual model that describes changes in aquatic communities under increasing levels of anthropogenic stress. The BCG helps decision-makers connect narrative water quality goals (e.g., maintenance of natural structure and function) to quantitative measures of ecological condition by linking index thresholds based on statistical distributions (e.g., percentiles of reference distributions) to expert descriptions of changes in biological condition along disturbance gradients. As a result, the BCG may be more meaningful to managers and the public than indices alone. To develop a BCG model, biological response to stress is divided into 6 levels of condition, represented as changes in biological structure (abundance and diversity of pollution sensitive versus tolerant taxa) and function. We developed benthic macroinvertebrate (BMI) and algal BCG models for California perennial wadeable streams to support interpretation of percentiles of reference-based thresholds for bioassessment indices (i.e., the California Stream Condition Index [CSCI] for BMI and the Algal Stream Condition Index [ASCI] for diatoms and soft-bodied algae). Two panels (one of BMI ecologists and the other of algal ecologists) each calibrated a general BCG model to California wadeable streams by first assigning taxa to specific tolerance and sensitivity attributes, and then independently assigning test samples (264 BMI and 248 algae samples) to BCG Levels 1–6. Consensus on the assignments was developed within each assemblage panel using a modified Delphi method. Panels then developed detailed narratives of changes in BMI and algal taxa that correspond to the 6 BCG levels. Consensus among experts was high, with 81% and 82% expert agreement within 0.5 units of assigned BCG level for BMIs and algae, respectively. According to both BCG models, the 10th percentiles index scores at reference sites corresponded to a BCG Level 3, suggesting that this type of threshold would protect against moderate changes in structure and function while allowing loss of some sensitive taxa. The BCG provides a framework to interpret changes in aquatic biological condition along a gradient of stress. The resulting relationship between index scores and BCG levels and narratives can help decision-makers select thresholds and communicate how these values protect aquatic life use goals.
The Planchón Peteroa Volcanic Complex (PPVC) is located on the border of Chile and Argentina, and is one of the most active volcanic systems in the Andes. Holocene activity has included magma-water interaction with an evolving series of crater lakes, mainly sourced from Peteroa volcano. This study examines data from the 2018/19 eruption, together with the volcanic history of the PPVC, to elucidate the complex interplay between magmatic activity and summit water and ice. From February 2016 to mid-2019, three seismic swarms occurred in the PPVC, preceding the explosive eruption from September 2018 to April 2019. The activity originated from a small vent nested within the easternmost crater, the most active portion of the complex (Peteroa). The explosions interacted with a crater lake, producing ash plumes up to 2 km above the crater and building a small tephra cone. To investigate the eruption mechanisms, we performed remote sensing analysis of plume dispersal, thermal anomalies and ground deformation, and characterized the volcanic products, including grain size, componentry, morphology, internal textures, composition and mineralogy. Our results suggest that the precursory seismicity beginning in 2016 was related to the intrusion of a new magma batch that reached the surface during the 2018/19 eruption. The eruption was also preceded by thermal anomalies, geomorphic changes and increased hydrothermal activity at the surface, though without any ground deformation recognized through radar interferometry (InSAR). The eruption initially produced predominantly recycled ash (phreatic activity), then evolved to increasing proportions of juvenile magma (phreatomagmatic) by April 2019. The juvenile clasts had a trachyandesite composition (~59 wt% SiO2), with vesicular and dense scoria containing plagioclase and pyroxene. The ash surfaces show external quenching cracks and step fractures consistent with phreatomagmatic fragmentation within the active crater lake. Textural characteristics also point to a slowly ascending batch of magma that was relatively viscous by the time it interacted with water in the crater lake. Notably, these juvenile particles are distinctive from the pre-2018 products. Ash erupted from 2010/11 did not contain recognizable juvenile material, and is inferred to have been a mainly phreatic eruption. Our findings suggest that the interplay between phreatic and phreatomagmatic eruptions fed by small magma batches intruding at shallow levels characterize much of the eruptive behavior of the PPVC during the last three decades. Multi-parametric assessment is a powerful tool to discriminate between phreatic and phreatomagmatic eruptions.
Coastal marsh loss, combined with expected sea-level rise, will cause inundation and extensive shifts to vegetation and salinity regimes that may affect the bird species dependent on coastal ecosystems worldwide. Within coastal marsh habitats, birds provide key targets for coastal management goals. However, limited information on bird-habitat relationships within coastal marshes inhibits the development of restoration projects targeted to bird species. We surveyed birds bi-monthly within Barataria Basin, LA from July 2014 to December 2015 to compare their use between fresh and saline coastal marshes. Additionally, we examined habitat use at finer spatial scales to assess preference for marsh edge microhabitats. Edge habitat supported 1.8 times more bird species (guild) richness than emergent and open water habitat. We concluded that future modelling efforts would be improved if models incorporate edge effects for birds in coastal marshes that extend 20 m from emergent vegetation into open water, with a reduced effect if marsh types convert from fresh to saline. Our data will be useful to simulate the effects of changes in marsh type, area, and edge on habitat quality for birds in coastal Louisiana and will inform habitat restoration and management decisions aimed at optimizing bird use.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-020-01324-2","usgsCitation":"Patton, B., Nyman, J.A., and La Peyre, M., 2020, Living on the edge: Multi-scale analyses of bird habitat use in coastal marshes of Barataria Basin, Louisiana, USA: Wetlands, v. 40, p. 2041-2054, https://doi.org/10.1007/s13157-020-01324-2.","productDescription":"14 p.","startPage":"2041","endPage":"2054","ipdsId":"IP-098169","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499826,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/agrnr_pubs/602","text":"External Repository"},{"id":395743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Barataria Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.8349609375,\n 28.714678586705976\n ],\n [\n -89.033203125,\n 28.714678586705976\n ],\n [\n -89.033203125,\n 30.32547125932808\n ],\n [\n -90.8349609375,\n 30.32547125932808\n ],\n [\n -90.8349609375,\n 28.714678586705976\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2020-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Patton, Brett 0000-0002-7396-3452 pattonb@usgs.gov","orcid":"https://orcid.org/0000-0002-7396-3452","contributorId":5458,"corporation":false,"usgs":true,"family":"Patton","given":"Brett","email":"pattonb@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":833827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nyman, J. A.","contributorId":275213,"corporation":false,"usgs":false,"family":"Nyman","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":833828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833829,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211872,"text":"70211872 - 2020 - Regionally continuous Miocene rhyolites beneath the eastern Snake River Plain reveal localized flexure at its western margin: Idaho National Laboratory and vicinity","interactions":[],"lastModifiedDate":"2020-12-15T20:23:40.067951","indexId":"70211872","displayToPublicDate":"2020-07-01T16:07:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6000,"text":"The Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Regionally continuous Miocene rhyolites beneath the eastern Snake River Plain reveal localized flexure at its western margin: Idaho National Laboratory and vicinity","docAbstract":"The eastern Snake River Plain (ESRP) is a northeast-trending topographic basin interpreted to be the result of the time-transgressive track of the North American plate above the Yellowstone hotspot. The track is defined by the age progression of silicic volcanic rocks exposed along the margins of the ESRP. However, the bulk of these silicic rocks are buried under 1 to 3 kilometers of younger basalts. Here, silicic volcanic rocks recovered from boreholes that penetrate below the basalts, including INEL-1, WO-2 and new deep borehole USGS-142, are correlated with one another and to surface exposures to assess various models for ESRP subsidence. These correlations are established on U/Pb zircon and 40Ar/39Ar sanidine age determinations, phenocryst assemblages, major and trace element geochemistry, δ18O isotopic data from selected phenocrysts, and initial εHf values of zircon. These data suggest a correlation of: (1) the newly documented 8.1 ± 0.2 Ma rhyolite of Butte Quarry (sample 17KS03), exposed near Arco, Idaho to the upper-most Picabo volcanic field rhyolites found in borehole INEL-1; (2) the 6.73 ± 0.02 Ma East Arco Hills rhyolite (sample 16KS02) to the Blacktail Creek Tuff, which was also encountered at the bottom of borehole WO-2; and (3) the 6.42 ± 0.07 Ma rhyolite of borehole USGS-142 to the Walcott Tuff B encountered in deep borehole WO-2. These results show that rhyolites found along the western margin of the ESRP dip ~20º south-southeast toward the basin axis, and then gradually tilt less steeply in the subsurface as the axis is approached. This subsurface pattern of tilting is consistent with a previously proposed crustal flexural model of subsidence based only on surface exposures, but is inconsistent with subsidence models that require accommodation of ESRP subsidence on either a major normal fault or strike-slip fault.","language":"English","publisher":"Rocky Mountain Association of Geologists","doi":"10.31582/rmag.mg.57.3.241","usgsCitation":"Schusler, K.L., Pearson, D.M., McCurry, M.J., Bartholomay, R.C., and Anders, M.H., 2020, Regionally continuous Miocene rhyolites beneath the eastern Snake River Plain reveal localized flexure at its western margin: Idaho National Laboratory and vicinity: The Mountain Geologist, v. 57, no. 3, p. 241-270, https://doi.org/10.31582/rmag.mg.57.3.241.","productDescription":"30 p.","startPage":"241","endPage":"270","ipdsId":"IP-112371","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":377936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.18002319335938,\n 43.41302868475145\n ],\n [\n -111.93145751953125,\n 43.41302868475145\n ],\n [\n -111.93145751953125,\n 43.55651037504758\n ],\n [\n -112.18002319335938,\n 43.55651037504758\n ],\n [\n -112.18002319335938,\n 43.41302868475145\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Schusler, Kyle L.","contributorId":237858,"corporation":false,"usgs":false,"family":"Schusler","given":"Kyle","email":"","middleInitial":"L.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":795484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearson, David M.","contributorId":237860,"corporation":false,"usgs":false,"family":"Pearson","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":795485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCurry, Michael J.","contributorId":237861,"corporation":false,"usgs":false,"family":"McCurry","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":795486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":795487,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anders, Mark H.","contributorId":237862,"corporation":false,"usgs":false,"family":"Anders","given":"Mark","email":"","middleInitial":"H.","affiliations":[{"id":39266,"text":"St. Lawrence University","active":true,"usgs":false}],"preferred":false,"id":795488,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210894,"text":"sir20205064 - 2020 - A summary of water-quality monitoring in San Francisco Bay in water year 2017","interactions":[],"lastModifiedDate":"2020-07-01T21:11:28.152523","indexId":"sir20205064","displayToPublicDate":"2020-07-01T12:33:01","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":"2020-5064","displayTitle":"A Summary of Water-Quality Monitoring in San Francisco Bay in Water Year 2017","title":"A summary of water-quality monitoring in San Francisco Bay in water year 2017","docAbstract":"This report summarizes the activities of the U.S. Geological Survey (USGS) San Francisco Bay Water-Quality Monitoring and Sediment Transport Project during water year 2017, including an explanation of methods employed, stations operated, and a graphical summary of data for the period of record for stations operational in water year 2017. In cooperation with partner agencies, the USGS maintains a network of sensors that continuously and autonomously measures water-quality parameters in San Francisco Bay including water temperature, specific conductance, turbidity, and suspended-sediment concentration. Data are collected at several locations in the estuary by a network of water-quality sondes sampled at 15-minute intervals. Methods of data collection are presented along with documentation of the regression models utilized to estimate suspended-sediment concentration from observed turbidity, a commonly utilized surrogate to estimate suspended-sediment concentration. The goals of the data collection effort are to (1) obtain long-term, high-frequency, and high-quality data to describe San Francisco Bay water quality; (2) make the data publicly available on the USGS National Water Information System data portal; and (3) help improve understanding of the spatial and temporal variability of water quality in the estuary, informing management decisions regarding restoration, water supply, navigation, and ecology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205064","usgsCitation":"Livsey, D., and Downing-Kunz, M., 2020, A summary of water-quality monitoring in San Francisco Bay in water year 2017: U.S. Geological Survey Scientific Investigations Report 2020–5064, 78 p., https://doi.org/10.3133/sir20205064.","productDescription":"Report: vi, 78 p.; Data Release","numberOfPages":"78","onlineOnly":"Y","ipdsId":"IP-104269","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":376068,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","linkHelpText":"National Water Information System"},{"id":376066,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5064/coverthb.jpg"},{"id":376067,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5064/sir20205064.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.62390136718749,\n 37.35050947036205\n ],\n [\n -121.7340087890625,\n 37.35050947036205\n ],\n [\n -121.7340087890625,\n 38.22307753495298\n ],\n [\n -122.62390136718749,\n 38.22307753495298\n ],\n [\n -122.62390136718749,\n 37.35050947036205\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Playa wetlands in the Great Plains, USA support a wide variety of plant species not found elsewhere in this agriculturally-dominated region due to the ephemeral presence of standing water and hydric soils within playas. If longer dry periods occur due to climate change or if changes in surrounding land use alter sediment accumulation rates and water storage capacity in playas, plant communities could experience decreased diversity, with lasting effects on ecosystem services provided by playas in the Great Plains and at a continental-level in North America. We quantified potential changes in playa wetland plant community composition associated with predicted changes in precipitation and land use in the Great Plains through the end of the 21st century. We conducted two six-month greenhouse experiments mimicking field conditions using intact mesocosms collected from playas in Nebraska and Texas. In the precipitation experiment, treatments derived from historical precipitation observations and three future moderate emissions (CMIP5 RCP4.5) downscaled climate projections were applied to mesocosms. For the land use experiment, treatments were simulated by nitrogen (N) applications to soil ranging from 0 to 100 mg-N L-1 with each precipitation event under historical rainfall patterns, representing increasing and decreasing area in agricultural use in playa watersheds. Plant communities tended to shift toward more native species under projected future climate conditions, but as N runoff increased, native species richness decreased. Agricultural land-use surrounding playas may have a greater effect on wetland plant communities than future alterations to hydrology based on climate change in the Great Plains; thus, efforts to reduce nutrient runoff into playas would likely mitigate loss in ecosystem function in the coming decades.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envexpbot.2020.104039","usgsCitation":"Owen, R.K., Webb, E.B., Haukos, D.A., and Goyne, K.W., 2020, Projected climate and land use changes drive plant community composition in agricultural wetlands: Environmental and Experimental Botany, v. 175, p. 1-12, https://doi.org/10.1016/j.envexpbot.2020.104039.","productDescription":"104039, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-111000","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":456171,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envexpbot.2020.104039","text":"Publisher Index Page"},{"id":395691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska, Texas","otherGeospatial":"Rainwater Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.01953125,\n 40.01078714046552\n ],\n [\n -96.51489257812499,\n 40.01078714046552\n ],\n [\n -96.51489257812499,\n 41.77950486590359\n ],\n [\n -100.01953125,\n 41.77950486590359\n ],\n [\n -100.01953125,\n 40.01078714046552\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.07373046875,\n 32.02670629333614\n ],\n [\n -103.040771484375,\n 31.44741029142872\n ],\n [\n -98.668212890625,\n 31.475524020001806\n ],\n [\n -98.7451171875,\n 34.15272698011818\n ],\n [\n -98.85498046875,\n 34.19817309627726\n ],\n [\n -99.041748046875,\n 34.252676117101515\n ],\n [\n -99.151611328125,\n 34.20725938207231\n ],\n [\n -99.283447265625,\n 34.42503613021332\n ],\n [\n -99.42626953125,\n 34.46127728843705\n ],\n [\n -99.42626953125,\n 34.38877925439021\n ],\n [\n -99.60205078124999,\n 34.42503613021332\n ],\n [\n -99.66796875,\n 34.38877925439021\n ],\n [\n -99.986572265625,\n 34.58799745550482\n ],\n [\n -99.97558593749999,\n 36.518465989675875\n ],\n [\n -103.062744140625,\n 36.50963615733049\n ],\n [\n -103.07373046875,\n 32.02670629333614\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"175","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Owen, Rachel K.","contributorId":273204,"corporation":false,"usgs":false,"family":"Owen","given":"Rachel","email":"","middleInitial":"K.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goyne, Keith W.","contributorId":204931,"corporation":false,"usgs":false,"family":"Goyne","given":"Keith","email":"","middleInitial":"W.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833948,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211508,"text":"70211508 - 2020 - Leachable phosphorus from senesced green ash and Norway mapleleaves in urban watersheds","interactions":[],"lastModifiedDate":"2020-08-03T14:49:50.385993","indexId":"70211508","displayToPublicDate":"2020-07-01T09:29:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Leachable phosphorus from senesced green ash and Norway mapleleaves in urban watersheds","docAbstract":"In urban watersheds, street tree leaf litter is a critical biogenic source of phosphorus (P) in stormwater runoff.\nStormwater extracts P from leaf litter and transports it, through the storm sewer network, to a receiving\nwaterbody potentially causing downstream eutrophication. The goal of this study is to understand P leaching dynamics of two prevalent tree species (Norway maple (Acer platanoides) and green ash (Fraxinus pennsylvanica))\nin three urban residential watersheds in Madison, Wisconsin, USA. Leaf litter was collected from the three basins\nduring Fall 2017 and 2018. Laboratory experiments showed an initial rapid total dissolved phosphorus (TDP) release that gradually plateaued over a 48-hour period. The total TDP released from Norway maple (2.10 mg g−1\n)\nwas greater than from green ash (1.60 mg g−1\n).Within the same species, increased fragmentation of leaves led to\nmore rapid initial TDP release, but not greater total TDP release. Increased aging of senescent leaves decreased\ntotal TDP release. Incubation temperature and volume of water in contact with leaves may not be critical factors\naffecting TDP leaching dynamics. Predictive equations were derived to characterize time-variable TDP release of\nboth Norway maple and green ash leaves. Potential TDP release from leaf litter estimated using these equations\nwas compared with field-measured end-of-pipe TDP loads in one of the study watersheds. Our results indicate\nthat preventing leaf litter from accumulating in streets is an important stormwater quality control measure.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.140662","usgsCitation":"Wang, Y., Thompson, A., and Selbig, W.R., 2020, Leachable phosphorus from senesced green ash and Norway mapleleaves in urban watersheds: Science of the Total Environment, v. 743, 140662, 10 p., https://doi.org/10.1016/j.scitotenv.2020.140662.","productDescription":"140662, 10 p.","ipdsId":"IP-117466","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":456181,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.140662","text":"Publisher Index Page"},{"id":436901,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UF3III","text":"USGS data release","linkHelpText":"Total phosphorus and total dissolved phosphorous released from Green Ash (Fraxinus pennsylvanica) and Norway Maple (Acer platanoides) as they contribute to leachable phosphorus in leaf litter and impact phosphorus loads in urban stormwater"},{"id":376837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"743","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Yi 0000-0003-3638-7940","orcid":"https://orcid.org/0000-0003-3638-7940","contributorId":236843,"corporation":false,"usgs":false,"family":"Wang","given":"Yi","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":794406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Anita 0000-0002-6202-1742","orcid":"https://orcid.org/0000-0002-6202-1742","contributorId":236844,"corporation":false,"usgs":false,"family":"Thompson","given":"Anita","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":794407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794408,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263280,"text":"70263280 - 2020 - Genetic structure of Smallmouth Bass in the Lake Michigan and Upper Mississippi River drainages relates to habitat, distance, and drainage boundaries: Smallmouth bass population genetic structure","interactions":[],"lastModifiedDate":"2025-02-05T14:21:54.170799","indexId":"70263280","displayToPublicDate":"2020-07-01T09:05:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12982,"text":"Transaction of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Genetic structure of Smallmouth Bass in the Lake Michigan and Upper Mississippi River drainages relates to habitat, distance, and drainage boundaries: Smallmouth bass population genetic structure","docAbstract":"Analysis of genetic connectivity helps to define stock boundaries and provides information on interpopulation dynamics, such as migration and spawning site fidelity. We used 16 microsatellite loci to describe the genetic population structure of 1,215 Smallmouth Bass Micropterus dolomieu from 32 sites throughout the upper Mississippi River and Lake Michigan watersheds. We found that Smallmouth Bass populations formed two genetically distinct units separated by the Mississippi River–Lake Michigan drainage boundary. Smallmouth Bass from the Lake Michigan drainage could be parsimoniously grouped into two or six genetically distinct units that largely corresponded with either river or lake habitats, while fish from the Mississippi River drainage grouped into two, six, or nine genetic units that were mostly associated with watershed boundaries. In the Lake Michigan and Mississippi River drainages, relative migration was limited between lake and river sites, suggesting that gene flow between neighboring sites with different habitat attributes can be low. Our research provides a higher‐resolution assessment of Smallmouth Bass genetic structure in a core portion of the species’ range and provides strong evidence that Smallmouth Bass populations are structured at small spatial scales that are potentially associated with habitat type. These results demonstrate the importance of evaluating genetic structure at small spatial scales and adopting management strategies that preserve genetic diversity of black bass populations at both the watershed level and the habitat level.
","language":"English","publisher":"Oxford Academic","doi":"10.1002/tafs.10238","usgsCitation":"Euclide, P., Ruzich, J., Hansen, S., Rowe, D., Zorn, T., and Larson, W., 2020, Genetic structure of Smallmouth Bass in the Lake Michigan and Upper Mississippi River drainages relates to habitat, distance, and drainage boundaries: Smallmouth bass population genetic structure: Transaction of the American Fisheries Society, v. 149, no. 4, p. 383-397, https://doi.org/10.1002/tafs.10238.","productDescription":"15 p.","startPage":"383","endPage":"397","ipdsId":"IP-110080","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","otherGeospatial":"Lake Michigan, Upper Mississippi River drainages","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.47157655214929,\n 46.23506584980677\n ],\n [\n -92.21749036091056,\n 46.23506584980677\n ],\n [\n -91.22368843327665,\n 42.54628056314354\n ],\n [\n -84.47157655214929,\n 42.61230188495793\n ],\n [\n -84.47157655214929,\n 46.23506584980677\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"149","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-06-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Euclide, Peter T.","contributorId":348493,"corporation":false,"usgs":false,"family":"Euclide","given":"Peter T.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":926141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruzich, Jenna","contributorId":244568,"corporation":false,"usgs":false,"family":"Ruzich","given":"Jenna","email":"","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":926142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Scott P.","contributorId":348684,"corporation":false,"usgs":false,"family":"Hansen","given":"Scott P.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":926143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rowe, David","contributorId":244571,"corporation":false,"usgs":false,"family":"Rowe","given":"David","email":"","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":926144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zorn, Troy G.","contributorId":348692,"corporation":false,"usgs":false,"family":"Zorn","given":"Troy G.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":926145,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Larson, Wesley 0000-0003-4473-3401 wlarson@usgs.gov","orcid":"https://orcid.org/0000-0003-4473-3401","contributorId":199509,"corporation":false,"usgs":true,"family":"Larson","given":"Wesley","email":"wlarson@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":926140,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70243722,"text":"70243722 - 2020 - Substantially greater carbon emissions estimated based on annual land-use transition data","interactions":[],"lastModifiedDate":"2023-05-18T11:48:21.304527","indexId":"70243722","displayToPublicDate":"2020-07-01T06:40:15","publicationYear":"2020","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":"Substantially greater carbon emissions estimated based on annual land-use transition data","docAbstract":"Quantifying land-use and land-cover change (LULCC) effects on carbon sources and sinks has been very challenging because of the availability and quality of LULCC data. As the largest estuary in the United States, Chesapeake Bay is a rapidly changing region and is affected by human activities. A new annual land-use and land-cover (LULC) data product developed by the U.S. Geological Survey Land Change Monitoring and Analysis Program (LCMAP) from 2001 to 2011 was analyzed for transitions between agricultural land, developed land, grassland, forest land and wetland. The Land Use and Carbon Scenario Simulator was used to simulate effects of LULCC and ecosystem disturbance in the south of the Chesapeake Bay Watershed (CBW) on carbon storage and fluxes, with carbon parameters derived from the Integrated Biosphere Simulator. We found that during the study period: (1) areas of forest land, disturbed land, agricultural land and wetland decreased by 90, 82, 57, and 65 km2, respectively, but developed lands gained 293 km2 (29 km2 annually); (2) total ecosystem carbon stock in the CBW increased by 13 Tg C from 2001 to 2011, mainly due to carbon sequestration of the forest ecosystem; (3) carbon loss was primarily attributed to urbanization (0.224 Tg C·yr−1) and agricultural expansion (0.046 Tg C·yr−1); and (4) estimated carbon emissions and harvest wood products were greater when estimated with the annual LULC input. We conclude that a dense time series of LULCC, such as that of the LCMAP program, may provide a more accurate accounting of the effects of land use change on ecosystem carbon, which is critical to understanding long-term ecosystem carbon dynamics.
","language":"English","publisher":"MDPI","doi":"10.3390/rs12071126","usgsCitation":"Diao, J., Liu, J., Zhu, Z., Li, M., and Sleeter, B.M., 2020, Substantially greater carbon emissions estimated based on annual land-use transition data: Remote Sensing, v. 12, no. 7, 15 p., https://doi.org/10.3390/rs12071126.","productDescription":"15 p.","ipdsId":"IP-105541","costCenters":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":456187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12071126","text":"Publisher Index Page"},{"id":417197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Chesapeake Bay Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.76743643889431,\n 39.33891670961805\n ],\n [\n -77.39396479275541,\n 38.21620000341724\n ],\n [\n -75.61512040539517,\n 37.61260838958307\n ],\n [\n -75.0537501361022,\n 38.83411126864999\n ],\n [\n -76.76743643889431,\n 39.33891670961805\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-04-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Diao, Jiaojiao","contributorId":305505,"corporation":false,"usgs":false,"family":"Diao","given":"Jiaojiao","email":"","affiliations":[{"id":33416,"text":"Nanjing Forestry University, China","active":true,"usgs":false}],"preferred":false,"id":873061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":873063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Mingshi","contributorId":202731,"corporation":false,"usgs":false,"family":"Li","given":"Mingshi","email":"","affiliations":[],"preferred":false,"id":873065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873066,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70214075,"text":"70214075 - 2020 - Planetary science decadal survey planetary mission concept study report: Ceres: Exploration of Ceres’ habitability","interactions":[],"lastModifiedDate":"2020-09-22T15:59:04.00305","indexId":"70214075","displayToPublicDate":"2020-06-30T10:41:56","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5883,"text":"Cooperator Report","active":true,"publicationSubtype":{"id":1}},"title":"Planetary science decadal survey planetary mission concept study report: Ceres: Exploration of Ceres’ habitability","docAbstract":"Dwarf planet Ceres is a compelling target as an evolved ocean world with, at least, regional brine reservoirs and potentially ongoing geological activity. As the most water-rich body in the inner solar system (in relative abundance), it is a representative of the population of planetesimals that brought volatiles and organics to the inner solar system. Situated in the Main Belt of asteroids, Ceres is accessible enough for a sample return with the resources of a typical medium-class (New Frontiers) NASA mission. Under the Discovery program, Dawn explored Ceres from 2015 to 2018. The extensive dataset revealed the presence of liquid, brine-driven activity, organic matter, and a rich salt chemistry. With this evidence, the overarching goals of the mission concept presented herein are to quantify Ceres’ current habitability potential and origin.
","language":"English","publisher":"NASA","usgsCitation":"Castillo-Rogez, J.C., Brody, J., Bland, M.T., Buczkowski, D., Grimm, R., Hendrix, A., Miller, K., Prettyman, T., Quick, L., Raymond, C., Scully, J., Sori, M.M., Sekine, Y., Williams, D., and Zolensky, M., 2020, Planetary science decadal survey planetary mission concept study report: Ceres: Exploration of Ceres’ habitability: Cooperator Report, 360 p.","productDescription":"360 p.","ipdsId":"IP-120108","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":378672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378651,"type":{"id":15,"text":"Index Page"},"url":"https://science.nasa.gov/science-red/s3fs-public/atoms/files/Exploration%20of%20Ceres%20Habitability.pdf"}],"otherGeospatial":"Ceres","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":799381,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Castillo-Rogez, J. C.","contributorId":177375,"corporation":false,"usgs":false,"family":"Castillo-Rogez","given":"J.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":799378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brody, John","contributorId":241031,"corporation":false,"usgs":false,"family":"Brody","given":"John","email":"","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":799379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":799380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buczkowski, Debra","contributorId":177352,"corporation":false,"usgs":false,"family":"Buczkowski","given":"Debra","affiliations":[],"preferred":false,"id":799428,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grimm, Robert","contributorId":241052,"corporation":false,"usgs":false,"family":"Grimm","given":"Robert","affiliations":[],"preferred":false,"id":799429,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hendrix, A.","contributorId":88218,"corporation":false,"usgs":true,"family":"Hendrix","given":"A.","affiliations":[],"preferred":false,"id":799430,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Kelly","contributorId":241053,"corporation":false,"usgs":false,"family":"Miller","given":"Kelly","email":"","affiliations":[],"preferred":false,"id":799431,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prettyman, Thomas","contributorId":196620,"corporation":false,"usgs":false,"family":"Prettyman","given":"Thomas","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":799432,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Quick, Lynnae","contributorId":238473,"corporation":false,"usgs":false,"family":"Quick","given":"Lynnae","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":799433,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Raymond, Carol","contributorId":113907,"corporation":false,"usgs":true,"family":"Raymond","given":"Carol","affiliations":[],"preferred":false,"id":799434,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Scully, Jennifer","contributorId":241054,"corporation":false,"usgs":false,"family":"Scully","given":"Jennifer","affiliations":[],"preferred":false,"id":799435,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sori, Michael M.","contributorId":173342,"corporation":false,"usgs":false,"family":"Sori","given":"Michael","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":799436,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sekine, Yasuhito","contributorId":241055,"corporation":false,"usgs":false,"family":"Sekine","given":"Yasuhito","email":"","affiliations":[],"preferred":false,"id":799437,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Williams, David","contributorId":33989,"corporation":false,"usgs":true,"family":"Williams","given":"David","affiliations":[],"preferred":false,"id":799438,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Zolensky, Michael","contributorId":241056,"corporation":false,"usgs":false,"family":"Zolensky","given":"Michael","email":"","affiliations":[],"preferred":false,"id":799439,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70211312,"text":"70211312 - 2020 - Quality Assurance Project Plan: Status and trends monitoring of small streams in the Puget Lowlands ecoregion for Stormwater Action Monitoring (SAM)","interactions":[],"lastModifiedDate":"2020-07-23T15:38:49.303701","indexId":"70211312","displayToPublicDate":"2020-06-30T10:30:57","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"Quality Assurance Project Plan: Status and Trends Monitoring of Small Streams in the Puget Lowlands Ecoregion for Stormwater Action Monitoring (SAM)","title":"Quality Assurance Project Plan: Status and trends monitoring of small streams in the Puget Lowlands ecoregion for Stormwater Action Monitoring (SAM)","docAbstract":"This Quality Assurance Project Plan (QAPP) details a long term status and trends monitoring study for small streams in the Puget Lowland as part of Stormwater Action Monitoring (SAM) program. SAM is the regional stormwater monitoring program funded by the Phase I Municipal Stormwater permit and the Western Washington Phase II Municipal Stormwater permit permittees.\n\nThis study of small streams in the Puget Lowland Ecoregion (called Puget Small Streams, PSS study, or SAM_PSS study hereafter) is designed to answer the question, “Are regional conditions in receiving water quality and biota improving in concert with broad implementation of required stormwater management practices?”\n\nIn 2015, the first round of monitoring evaluated the condition (status) of streams (DeGasperi et al., 2018). Beginning in 2020 and thereafter this study will monitor streams’ changes over time in\nurban, urbanizing and rural areas of the Puget Lowland. \n\nThe PSS will follow the protocols developed for the on-going statewide stream health monitoring\nprogram-Status and Trends Monitoring for Watershed Health and Salmon Recovery (WHSR) for\nphysical habitat, biological measurements, except for minor changes to water quality parameters\nto better capture the stormwater-related chemistry signals. In addition this effort will sample\nsieved sediments for stormwater-related chemistry signals.\n\nThis QAPP ensures quality data collection, analysis, reporting and management of the SAM PSS monitoring study","language":"English","publisher":"Washington State Department of Ecology","collaboration":"Washington State Department of Ecology","usgsCitation":"Song, K., and Sheibley, R.W., 2020, Quality Assurance Project Plan: Status and trends monitoring of small streams in the Puget Lowlands ecoregion for Stormwater Action Monitoring (SAM), 58 p.","productDescription":"58 p.","ipdsId":"IP-119398","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":376671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":376656,"type":{"id":15,"text":"Index Page"},"url":"https://fortress.wa.gov/ecy/publications/SummaryPages/2010015.html"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.98046874999999,\n 46.97275640318636\n ],\n [\n -121.9482421875,\n 46.97275640318636\n ],\n [\n -121.9482421875,\n 49.0306652257167\n ],\n [\n -124.98046874999999,\n 49.0306652257167\n ],\n [\n -124.98046874999999,\n 46.97275640318636\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Song, Keunyea 0000-0002-0538-7991","orcid":"https://orcid.org/0000-0002-0538-7991","contributorId":229632,"corporation":false,"usgs":false,"family":"Song","given":"Keunyea","email":"","affiliations":[{"id":25353,"text":"Washington State Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":793729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheibley, Rich W. 0000-0003-1627-8536 sheibley@usgs.gov","orcid":"https://orcid.org/0000-0003-1627-8536","contributorId":3044,"corporation":false,"usgs":true,"family":"Sheibley","given":"Rich","email":"sheibley@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793730,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70213133,"text":"70213133 - 2020 - Petrophysical and geomechanical properties of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well","interactions":[],"lastModifiedDate":"2020-09-10T15:01:33.235696","indexId":"70213133","displayToPublicDate":"2020-06-30T09:48:59","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Petrophysical and geomechanical properties of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well","docAbstract":"Knowledge of petrophysical and geomechanical properties of gas hydrate-bearing sediments are essential for predicting reservoir responses to gas production. The same information is also needed for the designing of production well completions such as specifications for artificial lift, test site water storage capacity, and mesh size for the sand control systems. In December 2018, the Stratigraphic Test Well Hydrate-01 was drilled in the western part of the Prudhoe Bay Unit on the Alaska North Slope as part of the technical planning effort for a future long-term production test being planned and led by a collaborative team from the U.S. Department of Energy - National Energy Technology Laboratory (DOE-NETL), U.S. Geological Survey (USGS), and Japan’s Research and Development Consortium for Pore Filling Hydrate in Sand (MH21-S) (Boswell et al., 2020, Collett et al., 2020, Okinaka et al., 2020). Logging-while-drilling (LWD) data were acquired (Haines et al., 2020, Suzuki et al., 2019) and sidewall core sampling depths were selected from the LWD logs. Sidewall pressure coring was conducted to recover gas hydrate-bearing sediments from two reservoir sections named Unit B and Unit D. A total of 34 cores were successfully recovered by 5 runs of a wireline deployed pressure coring system (CoreVault® System - Halliburton). The core analysis plan for this project is shown in Figure 1. Upon recovery, the pressure core autoclaves were transported from the Alaska North Slope to the Stratum Reservoir laboratory in Anchorage Alaska. To access the cores, they were first quenched in liquid nitrogen while still at high pressure in the core system autoclaves (Figure 1a). The cores were next removed from the pressure corer autoclaves with temperature control support from dry ice and stored under liquid nitrogen at atmospheric pressure. A total of 19 disturbed low-quality cores were processed for index property measurements, which included grain size and grain density analysis. Another 4 core samples were depressurized, trimmed, and core plugs were cut from each core and used to measure intrinsic permeabilities of host sediments (Figure 1). Unsteady-state permeability measurements were conducted on two samples to obtain relative water permeability (Rel.-Perm.) to gas and core scale Nuclear Magnetic Resonance (NMR) transverse relaxation time (T2) distribution measurements were performed to evaluate pore size distribution (Figure 1b). A total of 13 remaining high-quality cores with significant gas hydrate concentrations were preserved for advanced laboratory analysis. The National Institute of Advanced Industrial Science and Technology, as a part of the Japanese National Hydrate Research Program (MH21-S, funded by Ministry of Economy, Trade and Industry), received the 13 remaining high-quality core samples at their laboratories in Sapporo, Japan for advanced core analysis. High-resolution X-ray computed tomography (CT) was used to analyze the physical characteristics of the samples, which showed for the most part undisturbed lithological layers. Cores were lathed into cylindrical shapes and prepared for multi property measurements (Figure 1c). As a result, sediment from Unit D was characterized as silty-sand at ~37% porosity with ~80% gas hydrate saturation. An average hydration number n = 6.16 was measured for the recovered gas hydrate samples by Raman spectroscopy. An average intrinsic permeability of ~400 mD and in situ effective permeability (with hydrate) on the order of ~10 mD was measured for a total of five core samples. The Unit B recovered cores consisted of well sorted sand at ~40% porosity with ~95% gas hydrate saturation. An average intrinsic permeability of ~1 Darcy and in situ effective permeability on the order of ~30 mD was measured for the Unit B cores. Additional laboratory measurements yielded small permeability reductions due to porosity loss with increasing effective stress that simulated sediment consolidation along with depressurization in the highly permeable sandy sediment. The apparent limited change in porosity and permeability may be caused by the low compressibility of quartz sand grains in the recovered cores. X-ray diffraction (XRD) and thermal conductivity analysis also indicated a high quartz content within the recovered cores. Completed triaxial compression tests established internal friction angles based on the Mohr-Coulomb's failure criterion, which were calculated at 40° for hydrate-bearing sediment and 29.8° for hydrate free sediment.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 10th international conference on gas hydrates (ICGH10)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"10th International Conference on Gas Hydrates (ICGH10)","conferenceDate":"Jun 21-26, 2020","conferenceLocation":"Singapore","language":"English","publisher":"US Department of Energy – NETL Program","usgsCitation":"Yoneda, J., Jin, Y., Muraoka, M., Oshima, M., Suzuki, K., Walker, M., Westacott, D., Otsuki, S., Kumagai, K., Collett, T., Boswell, R., and Okinaka, N., 2020, Petrophysical and geomechanical properties of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well, in Proceedings of the 10th international conference on gas hydrates (ICGH10), Singapore, Jun 21-26, 2020, 2 p.","productDescription":"2 p.","ipdsId":"IP-115398","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":378313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378292,"type":{"id":15,"text":"Index Page"},"url":"https://www.netl.doe.gov/node/10037"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.69873046875,\n 68.2042121888185\n ],\n [\n -146.18408203125,\n 68.2042121888185\n ],\n [\n -146.18408203125,\n 71.4900625291139\n ],\n [\n -153.69873046875,\n 71.4900625291139\n ],\n [\n -153.69873046875,\n 68.2042121888185\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Yoneda, Jun","contributorId":240044,"corporation":false,"usgs":false,"family":"Yoneda","given":"Jun","email":"","affiliations":[{"id":40273,"text":"National Institute of Advanced Industrial Science and Technology","active":true,"usgs":false}],"preferred":false,"id":798354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jin, Yusuke","contributorId":240045,"corporation":false,"usgs":false,"family":"Jin","given":"Yusuke","affiliations":[{"id":40273,"text":"National Institute of Advanced Industrial Science and Technology","active":true,"usgs":false}],"preferred":false,"id":798355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muraoka, Michihiro","contributorId":240046,"corporation":false,"usgs":false,"family":"Muraoka","given":"Michihiro","email":"","affiliations":[{"id":40273,"text":"National Institute of Advanced Industrial Science and 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LLC","active":true,"usgs":false}],"preferred":false,"id":798359,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Westacott, Donald","contributorId":240050,"corporation":false,"usgs":false,"family":"Westacott","given":"Donald","email":"","affiliations":[{"id":34662,"text":"Halliburton","active":true,"usgs":false}],"preferred":false,"id":798360,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Otsuki, Satoshi","contributorId":240051,"corporation":false,"usgs":false,"family":"Otsuki","given":"Satoshi","email":"","affiliations":[{"id":17917,"text":"Japan Oil, Gas and Metals National Corporation","active":true,"usgs":false}],"preferred":false,"id":798361,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kumagai, Kenichi","contributorId":240052,"corporation":false,"usgs":false,"family":"Kumagai","given":"Kenichi","email":"","affiliations":[{"id":17917,"text":"Japan Oil, Gas and Metals National Corporation","active":true,"usgs":false}],"preferred":false,"id":798362,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Collett, Timothy 0000-0002-7598-4708","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":220806,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","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":798363,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Boswell, Ray","contributorId":240053,"corporation":false,"usgs":false,"family":"Boswell","given":"Ray","affiliations":[{"id":40277,"text":"U.S. Department of Energy","active":true,"usgs":false}],"preferred":false,"id":798364,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Okinaka, Norihiro","contributorId":240054,"corporation":false,"usgs":false,"family":"Okinaka","given":"Norihiro","email":"","affiliations":[{"id":17917,"text":"Japan Oil, Gas and Metals National Corporation","active":true,"usgs":false}],"preferred":false,"id":798365,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70210993,"text":"70210993 - 2020 - Rethinking groundwater flow on the South Rim of the Grand Canyon, USA: Characterizing recharge sources and flow paths with environmental tracers","interactions":[],"lastModifiedDate":"2020-08-04T14:24:42.736989","indexId":"70210993","displayToPublicDate":"2020-06-30T08:41:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Rethinking groundwater flow on the South Rim of the Grand Canyon, USA: Characterizing recharge sources and flow paths with environmental tracers","docAbstract":"In the arid landscape south of the Grand Canyon, natural springs and seeps are a critical resource for endemic species and Native American tribes. Groundwater is potentially threatened by expanding populations, visitations, and mineral extraction activities. Environmental tracers including noble gases, stable isotopes of hydrogen and oxygen in water, tritium, and carbon-14 were used to characterize recharge sources and flow paths in South Rim aquifers. Results confirm the regional Redwall-Muav Aquifer as the primary groundwater source to springs. However, a second local recharge source is required to explain the detection of tritium. Two probable sources are identified as: low-elevation infiltration of surface run-off with warm noble gas recharge temperatures, high excess air, and relatively low fractions of winter recharge, and high-elevation plateau recharge with cool recharge temperatures, low excess air, and fraction of winter recharge of ~ 1. Previous investigators have linked spring occurrence with regional faults and fractures. We show such features are also the likely control chemical mixing between the regional and local groundwater sources, the transport of deeply sourced and local recharge fluids, groundwater age, and thus the relative vulnerability of groundwater to depletion and contamination. The new conceptual model of groundwater sources and flow paths suggest many South Rim springs may respond on the order of 10s to 100s of years to groundwater depletion and contamination, even though the majority of groundwater flow is along longer flow paths with longer lag times. The magnitude of response to short term changes in the flow system remains unclear.","language":"English","publisher":"Springer","doi":"10.1007/s10040-020-02193-z","usgsCitation":"Solder, J.E., Beisner, K.R., Anderson, J.R., and Bills, D.J., 2020, Rethinking groundwater flow on the South Rim of the Grand Canyon, USA: Characterizing recharge sources and flow paths with environmental tracers: Hydrogeology Journal, v. 28, p. 1593-1613, https://doi.org/10.1007/s10040-020-02193-z.","productDescription":"21 p.","startPage":"1593","endPage":"1613","ipdsId":"IP-110439","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":456198,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-020-02193-z","text":"Publisher Index Page"},{"id":436904,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WX8N0L","text":"USGS data release","linkHelpText":"Noble gas isotopes and lumped parameter model results for environmental tracer based groundwater ages, South Rim Grand Canyon, Arizona, USA"},{"id":376255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"South Rim of the Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.4835205078125,\n 35.7019167328534\n ],\n [\n -111.65679931640625,\n 35.7019167328534\n ],\n [\n -111.65679931640625,\n 36.18000806322456\n ],\n [\n -112.4835205078125,\n 36.18000806322456\n ],\n [\n -112.4835205078125,\n 35.7019167328534\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationDate":"2020-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Solder, John E. 0000-0002-0660-3326","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":201953,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beisner, Kimberly R. 0000-0002-2077-6899 kbeisner@usgs.gov","orcid":"https://orcid.org/0000-0002-2077-6899","contributorId":2733,"corporation":false,"usgs":true,"family":"Beisner","given":"Kimberly","email":"kbeisner@usgs.gov","middleInitial":"R.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Jessica R. 0000-0002-3286-7552 jranderson@usgs.gov","orcid":"https://orcid.org/0000-0002-3286-7552","contributorId":193158,"corporation":false,"usgs":true,"family":"Anderson","given":"Jessica","email":"jranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bills, Donald J. 0000-0001-8955-3370 djbills@usgs.gov","orcid":"https://orcid.org/0000-0001-8955-3370","contributorId":177439,"corporation":false,"usgs":true,"family":"Bills","given":"Donald","email":"djbills@usgs.gov","middleInitial":"J.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792366,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217072,"text":"70217072 - 2020 - Machine-learning models to map pH and redox conditions in groundwater in a layered aquifer system, Northern Atlantic Coastal Plain, eastern USA","interactions":[],"lastModifiedDate":"2021-01-04T13:17:05.281621","indexId":"70217072","displayToPublicDate":"2020-06-30T07:12:49","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Machine-learning models to map pH and redox conditions in groundwater in a layered aquifer system, Northern Atlantic Coastal Plain, eastern USA","docAbstract":"The study was conducted in the Northern Atlantic Coastal Plain aquifer system, in the eastern USA.
Groundwater pH and redox conditions are fundamental chemical characteristics controlling the distribution of many contaminants of concern for drinking water or the ecological health of receiving waters. In this study, pH and redox conditions were modeled and mapped in a complex, layered aquifer system. Machine-learning methods (boosted regression trees) were applied to data from 3000 to 5000 wells. Predicted pH and the probability of anoxic conditions, defined by three thresholds of dissolved oxygen (0.5, 1, and 2 mg/L), were mapped at the 1-km2 scale for each of 10 regional aquifer layers.
Maps depict the extent of acidic groundwater and oxic conditions in the shallow, unconfined surficial aquifer and in unconfined, recharge-proximal areas of underlying aquifers, in contrast to alkaline and anoxic groundwater elsewhere. Geographic patterns and influential predictors–including elevation, overlying confining-units thickness, and simulated groundwater age and flux–are consistent with prior understanding of the processes controlling pH and redox in the aquifer system. The model-based maps support robust estimates of aquifer proportions, either areal or volumetric, likely to contain groundwater of a specified quality or be vulnerable to specific pH- or redox-sensitive contaminants. The machine-learning methods were an effective tool to map groundwater quality at the regional scale.
Climate change is expected to result in the tropicalization of coastal wetlands in the northern Gulf of Mexico, as warming winters allow tropical mangrove forests to expand their distribution poleward at the expense of temperate salt marshes. Data limitations near mangrove range limits have hindered understanding of the effects of winter temperature extremes on mangrove distribution and structure. Here, we investigated the influence of extreme freeze events on the abundance, height and coverage of black mangroves (Avicennia germinans ) near their northern range limit in Louisiana.
Coastal Louisiana, USA.
We quantified the relationships between the frequency of extreme freeze events and A. germinans abundance, height and coverage using: (a) mangrove observation points recorded via aerial surveys from a fixed‐wing aircraft; (b) 30 years of temperature data; and (c) mangrove mortality and leaf damage temperature thresholds. We used freeze frequency data and mangrove–climate relationships to evaluate and spatially depict the risk of A. germinans freeze damage across Louisiana.
We identified strong negative relationships between the frequency of extreme freeze events and A. germinans abundance, height and coverage. Avicennia germinans is most abundant, tall and continuous along the south‐eastern outer coast of Louisiana, where the frequency of extreme freeze events is reduced (i.e., lower risk of mangrove freeze damage) by the buffering effects of comparatively warm Gulf of Mexico waters. Conversely, the risk of A. germinans freeze damage has historically been very high across Louisiana's Chenier Plain and within more inland wetlands in the Deltaic Plain.
Our analyses advance understanding of how the frequency of extreme freeze events controls the distribution, height and coverage of A. germinans near its northern range limit. In addition to informing climate‐smart coastal restoration efforts, our findings can be used to better anticipate and prepare for the tropicalization of temperate wetlands due to climate change.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13119","usgsCitation":"Osland, M., Day, R., and Michot, T.C., 2020, Frequency of extreme freeze events controls the distribution and structure of black mangroves (Avicennia germinans) near their northern range limit in coastal Louisiana: Diversity and Distributions, v. 26, no. 10, p. 1366-1382, https://doi.org/10.1111/ddi.13119.","productDescription":"Article: 17 p.; Data Release","startPage":"1366","endPage":"1382","ipdsId":"IP-116815","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456209,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13119","text":"Publisher Index Page"},{"id":376104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379388,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RC8EIE"}],"country":"United States","state":"Louisiana","otherGeospatial":"Coastal Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.779296875,\n 29.152161283318915\n ],\n [\n -92.46093749999999,\n 28.998531814051795\n ],\n [\n -90.615234375,\n 28.8831596093235\n ],\n [\n -89.07714843749999,\n 29.305561325527698\n ],\n [\n -89.384765625,\n 30.29701788337205\n ],\n [\n -89.82421875,\n 30.600093873550072\n ],\n [\n -91.62597656249999,\n 30.44867367928756\n ],\n [\n -93.6474609375,\n 30.259067203213018\n ],\n [\n -94.130859375,\n 30.031055426540206\n ],\n [\n -93.779296875,\n 29.152161283318915\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":214842,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":792079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Richard 0000-0002-5959-7054","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":221895,"corporation":false,"usgs":true,"family":"Day","given":"Richard","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":792080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michot, Thomas C.","contributorId":228798,"corporation":false,"usgs":false,"family":"Michot","given":"Thomas","email":"","middleInitial":"C.","affiliations":[{"id":41511,"text":"USGS WARC (retired)","active":true,"usgs":false}],"preferred":false,"id":792081,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70220662,"text":"70220662 - 2020 - Geomorphological evidence for a dry dust avalanche origin of slope streaks on Mars","interactions":[],"lastModifiedDate":"2021-05-24T13:22:20.872996","indexId":"70220662","displayToPublicDate":"2020-06-29T08:20:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphological evidence for a dry dust avalanche origin of slope streaks on Mars","docAbstract":"Mars has several different types of slope feature that resemble aqueous flows. However, the current cold, dry conditions are inimical to liquid water, resulting in uncertainty about its role in modern surface processes. Dark slope streaks were among the first distinctive young slope features to be identified on Mars and the first with activity seen in orbital images. They form markings on steep slopes that can persist for decades, and the role of water in their formation remains a matter of debate. Here I analyse the geomorphic features of new slope streaks using high-resolution orbital images. Comparison of images before and after streak formation reveal how this process affects the surface and provides information about the cause. These observations demonstrate that slope streaks erode and deposit material in some instances. They also reveal that streaks can jump slopes and may be erosive very near their termini. These observations support a formation model where dark slope streaks form as ground-hugging, low-density avalanches of dry surface dust. Such streaks need not be treated as Special Regions for planetary protection.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41561-020-0598-x","usgsCitation":"Dundas, C.M., 2020, Geomorphological evidence for a dry dust avalanche origin of slope streaks on Mars: Nature Geoscience, v. 13, p. 473-476, https://doi.org/10.1038/s41561-020-0598-x.","productDescription":"4 p.","startPage":"473","endPage":"476","ipdsId":"IP-110925","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":456222,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8243413","text":"External Repository"},{"id":385891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":816346,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70211185,"text":"70211185 - 2020 - Energy development and production in the Great Plains: Implications and restoration opportunities","interactions":[],"lastModifiedDate":"2021-10-04T16:45:27.336205","indexId":"70211185","displayToPublicDate":"2020-06-28T10:10:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Energy development and production in the Great Plains: Implications and restoration opportunities","docAbstract":"Energy is an integral part of society. The major US energy sources of fossil fuels (coal, oil, natural gas); biofuels (ethanol); and wind are concentrated in grassland ecosystems of the Great Plains. As energy demand continues to increase, mounting pressures will be placed on North American grassland systems. In this review, we present the ecological effects of energy development and production on grassland systems. We then identify opportunities to mitigate these effects during the planning, construction, and production phases by using informed methodology and improved technology. Primary effects during energy development include small- and large-scale soil disturbance and vegetation removal as small patches of grasslands are used to host oil or gas wells, wind turbine pads, associated roadways, and pipelines or through the conversion of large grassland areas to biofuel croplands. Direct habitat loss or habitat fragmentation can affect wildlife directly through increased mortality or indirectly through reduction in habitat quantity and quality. During energy production, air and water quality can be affected through regular emissions or unplanned spills. Energy development can also affect the economy and health of local communities. During planning, energy development and production effects can be reduced by carefully considering effects on grasslands during siting and even by selecting different energy source types. During construction, effects on soil and plant systems can be minimized by eliminating weed populations before disturbance, salvaging and stockpiling topsoil for future revegetation, and harvesting native local seed for postsite restoration. During energy production operations, noise and road traffic reduction plans and atmospheric monitoring will enable more informed mitigation measures. Continued research on energy development effects and mitigation measures is necessary to establish best management practices beneficial to grassland health while providing needed energy for the United States.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2020.05.003","usgsCitation":"Ott, J.P., Hanberry, B.B., Khalil, M., Paschke, M.W., Post van der Burg, M., and Prenni, A.J., 2020, Energy development and production in the Great Plains: Implications and restoration opportunities: Rangeland Ecology and Management, v. 78, p. 257-272, https://doi.org/10.1016/j.rama.2020.05.003.","productDescription":"16 p.","startPage":"257","endPage":"272","ipdsId":"IP-109053","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":456232,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2020.05.003","text":"Publisher Index Page"},{"id":376427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Illinois, Indiana, Iowa, Kansas, Minnesota, Missouri, Montana, Nebraska, New Mexico, North Dakota, Oklahoma, South Dakota, Texas, Wisconsin, Wyoming","otherGeospatial":"Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.00976562499999,\n 49.15296965617042\n ],\n [\n -113.73046875,\n 48.86471476180277\n ],\n [\n -106.787109375,\n 40.64730356252251\n ],\n [\n -105.205078125,\n 34.016241889667015\n ],\n [\n -102.74414062499999,\n 30.675715404167743\n ],\n [\n -97.294921875,\n 30.372875188118016\n ],\n [\n -94.658203125,\n 36.73888412439431\n ],\n [\n -86.66015624999999,\n 39.639537564366684\n ],\n [\n -87.978515625,\n 42.09822241118974\n ],\n [\n -93.1640625,\n 44.276671273775186\n ],\n [\n -95.00976562499999,\n 49.15296965617042\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ott, Jacqueline P.","contributorId":229363,"corporation":false,"usgs":false,"family":"Ott","given":"Jacqueline","email":"","middleInitial":"P.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":793006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanberry, Brice B. 0000-0001-8657-9540","orcid":"https://orcid.org/0000-0001-8657-9540","contributorId":229364,"corporation":false,"usgs":false,"family":"Hanberry","given":"Brice","email":"","middleInitial":"B.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":793007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khalil, Mona 0000-0002-6046-1293","orcid":"https://orcid.org/0000-0002-6046-1293","contributorId":207187,"corporation":false,"usgs":true,"family":"Khalil","given":"Mona","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":793008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paschke, Mark W. 0000-0002-6345-5905","orcid":"https://orcid.org/0000-0002-6345-5905","contributorId":229365,"corporation":false,"usgs":false,"family":"Paschke","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":793009,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":793010,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prenni, Anthony J. 0000-0002-0256-5166","orcid":"https://orcid.org/0000-0002-0256-5166","contributorId":229366,"corporation":false,"usgs":false,"family":"Prenni","given":"Anthony","email":"","middleInitial":"J.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":793011,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}