The hazards posed by infrequent major floods to communities along the Susquehanna River and the ecological health of Chesapeake Bay remain largely unconstrained due to the short length of streamgage records. Here we develop a history of high‐flow events on the Susquehanna River during the late Holocene from flood deposits contained in MD99‐2209, a sediment core recovered in 26 m of water from Chesapeake Bay near Annapolis, Maryland, United States. We identify coarse‐grained deposits left by Hurricane Agnes (1972) and the Great Flood of 1936, as well as during three intervals that predate instrumental flood records (~1800–1500, 1300–1100, and 400–0 CE). Comparison to sedimentary proxy data (pollen and ostracode Mg/Ca ratios) from the same core site indicates that prehistoric flooding on the Susquehanna often accompanied cooler‐than‐usual winter/spring temperatures near Chesapeake Bay—typical of negative phases of the North Atlantic Oscillation and conditions thought to foster hurricane landfalls along the East Coast.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GL080890","usgsCitation":"Toomey, M., Cantwell, M., Colman, S., Cronin, T.M., Donnelly, J.P., Giosan, L., Heil, C., Korty, R.L., Marot, M.E., and Willard, D.A., 2019, The mighty Susquehanna—extreme floods in Eastern North America during the past two millennia: Geophysical Research Letters, v. 46, no. 6, p. 3398-3407, https://doi.org/10.1029/2018GL080890.","productDescription":"10 p.","startPage":"3398","endPage":"3407","ipdsId":"IP-104701","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":467896,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gl080890","text":"Publisher Index Page"},{"id":362903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Chesapeake Bay, Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.398681640625,\n 36.78289206199065\n ],\n [\n -75.443115234375,\n 36.78289206199065\n ],\n [\n -75.443115234375,\n 39.816975090490004\n ],\n [\n -77.398681640625,\n 39.816975090490004\n ],\n [\n -77.398681640625,\n 36.78289206199065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience 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Long-term capture–recapture datasets provide valuable ecological insights and baselines for conservation and management, but where such studies rely on noninvasive re-encounters, such as field-readable color bands, there is the potential to accumulate detection errors as the length of the study and number of tags deployed increases. We investigated the prevalence and effects of misreads in a 10-yr dataset of Red Knots (Calidris canutus rufa) marked with field-readable leg flags in Delaware, USA. We quantified the effects of misreads on survival estimation via a simulation study and evaluated whether removal of individuals only reported once in a year (potential misreads) influenced survival estimation from both simulated datasets and our case study data. We found overall apparent error rates of 0.31% (minimum) to 6.6% (maximum). Observer-specific error rates and the variation among observers both decreased with the number of flags an observer recorded. Our simulation study showed that misreads lead to spurious negative trends in survival over time, particularly for long-term studies. Removing all records in which a flag was only recorded once in a sampling occasion reduced bias and eliminated spurious negative trends in survival but also reduced precision in survival estimates. Without data filtering, we found a slight decrease in Red Knot annual survival probability from 2008 to 2018 (β = −0.043 ± 0.03), but removing all single-observation records resulted in no apparent trend (β = −0.0074 ± 0.02). Spurious trends in demographic rates could influence inference about population trajectories and resultant conservation decision-making. Data filtering could eliminate errors, but researchers should carefully consider the tradeoff between precision obtained by larger sample sizes and potential bias due to misreads in their data.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duy017","usgsCitation":"Tucker, A.M., McGowan, C.P., Robinson, R.A., Clark, J.A., Lyons, J.E., Derose-Wilson, A., Du Feu, R., Austin, G.E., Atkinson, P.W., and Clark, N.A., 2019, Effects of individual misidentification on estimates of survival in long-term mark–resight studies: Condor, v. 121, no. 1, duy017, 13 p., https://doi.org/10.1093/condor/duy017.","productDescription":"duy017, 13 p.","ipdsId":"IP-095982","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware","otherGeospatial":"Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.4705810546875,\n 39.71986348549764\n ],\n [\n -75.6243896484375,\n 39.63530729658601\n ],\n [\n -75.574951171875,\n 39.2492708462234\n ],\n [\n -75.322265625,\n 38.79690830348427\n ],\n [\n -75.12451171875,\n 38.453588708941375\n ],\n [\n -74.970703125,\n 38.42347008084991\n ],\n [\n -75.0531005859375,\n 38.80118939192329\n ],\n [\n -75.135498046875,\n 39.13006024213511\n ],\n [\n -75.4925537109375,\n 39.42346418978382\n ],\n [\n -75.5474853515625,\n 39.50827899034114\n ],\n [\n -75.55847167968749,\n 39.63530729658601\n ],\n [\n -75.4705810546875,\n 39.71986348549764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Tucker, A. 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A.","contributorId":274222,"corporation":false,"usgs":false,"family":"Clark","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":38864,"text":"British Trust for Ornithology","active":true,"usgs":false}],"preferred":false,"id":832817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":832818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Derose-Wilson, A.","contributorId":243204,"corporation":false,"usgs":false,"family":"Derose-Wilson","given":"A.","email":"","affiliations":[{"id":36379,"text":"Delaware Division of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":832819,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Du Feu, R.","contributorId":274224,"corporation":false,"usgs":false,"family":"Du Feu","given":"R.","email":"","affiliations":[{"id":33563,"text":"Lancaster University","active":true,"usgs":false}],"preferred":false,"id":832820,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Austin, G. E.","contributorId":274226,"corporation":false,"usgs":false,"family":"Austin","given":"G.","email":"","middleInitial":"E.","affiliations":[{"id":38864,"text":"British Trust for Ornithology","active":true,"usgs":false}],"preferred":false,"id":832821,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Atkinson, P. W.","contributorId":274227,"corporation":false,"usgs":false,"family":"Atkinson","given":"P.","email":"","middleInitial":"W.","affiliations":[{"id":38864,"text":"British Trust for Ornithology","active":true,"usgs":false}],"preferred":false,"id":832822,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Clark, N. A.","contributorId":274229,"corporation":false,"usgs":false,"family":"Clark","given":"N.","email":"","middleInitial":"A.","affiliations":[{"id":38864,"text":"British Trust for Ornithology","active":true,"usgs":false}],"preferred":false,"id":832823,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70204432,"text":"70204432 - 2019 - Impact of prey occupancy and other ecological and anthropogenic factors on Tiger distribution in Thailand’s Western Forest Complex","interactions":[],"lastModifiedDate":"2019-07-23T15:18:08","indexId":"70204432","displayToPublicDate":"2019-02-18T15:17:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Impact of prey occupancy and other ecological and anthropogenic factors on Tiger distribution in Thailand’s Western Forest Complex","docAbstract":"Despite conservation efforts, large mammals such as tigers (Panthera tigris) and their main prey, gaur (Bos gaurus), banteng (Bos javanicus), and sambar (Rusa unicolor), are highly threatened and declining across their entire range. The only large viable source population of tigers in mainland Southeast Asia occurs in Thailand's Western Forest Complex (WEFCOM), an approximately 19,000 km 2 landscape of 17 contiguous protected areas. We used an occupancy modeling framework, which accounts for imperfect detection, to identify the factors that affect tiger distribution at the approximate scale of a female tiger's home range, 64 km 2 , and site use at a scale of 1-km 2 . At the larger scale, we estimated the proportion of sites at WEFCOM that were occupied by tigers; at the finer scale, we identified the key variables that influence site-use and developed a predictive distribution map. At both scales, we examined key anthropogenic and ecological factors that help explain tiger distribution and habitat use, including probabilities of gaur, banteng, and sambar occurrence from a companion study. Occupancy estimated at the 64-km 2 scale was primarily influenced by the combined presence of all three large prey species, and 37% or 5,858 km 2 of the landscape was predicted to be occupied by tigers. In contrast, site use estimated at the scale of 1 km 2 was most strongly influenced by the presence of sambar. By modeling occupancy while accounting for imperfect probability of detection, we established reliable benchmark data on the distribution of tigers in WEFCOM. This study also identified factors that limit tiger distributions; which managers can then target to expand tiger distribution and guide recovery elsewhere in Southeast Asia.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4845","usgsCitation":"Duangchatrasiri, S., Jornburom, P., Jinamoy, S., Pattanvibool, A., Hines, J.E., Arnold, T.W., Fieberg, J., and Smith, J.L., 2019, Impact of prey occupancy and other ecological and anthropogenic factors on Tiger distribution in Thailand’s Western Forest Complex: Ecology and Evolution, v. 9, no. 5, p. 2449-2458, https://doi.org/10.1002/ece3.4845.","productDescription":"10 p.","startPage":"2449","endPage":"2458","ipdsId":"IP-098845","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467897,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4845","text":"Publisher Index Page"},{"id":365886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365866,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/full/10.1002/ece3.4845"}],"country":"Thailand","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[102.58493,12.18659],[101.68716,12.64574],[100.83181,12.62708],[100.97847,13.41272],[100.0978,13.40686],[100.01873,12.307],[99.47892,10.84637],[99.15377,9.96306],[99.2224,9.23926],[99.87383,9.20786],[100.27965,8.29515],[100.45927,7.42957],[101.01733,6.85687],[101.62308,6.74062],[102.14119,6.22164],[101.81428,5.81081],[101.15422,5.69138],[101.07552,6.20487],[100.2596,6.64282],[100.08576,6.46449],[99.69069,6.84821],[99.51964,7.34345],[98.98825,7.90799],[98.50379,8.38231],[98.33966,7.79451],[98.15001,8.35001],[98.25915,8.97392],[98.55355,9.93296],[99.03812,10.96055],[99.58729,11.89276],[99.19635,12.80475],[99.21201,13.26929],[99.09776,13.8275],[98.43082,14.62203],[98.19207,15.1237],[98.53738,15.3085],[98.90335,16.17782],[98.49376,16.83784],[97.85912,17.56795],[97.3759,18.44544],[97.79778,18.62708],[98.25372,19.7082],[98.95968,19.75298],[99.54331,20.1866],[100.11599,20.41785],[100.54888,20.10924],[100.60629,19.50834],[101.28201,19.46258],[101.03593,18.40893],[101.05955,17.5125],[102.11359,18.1091],[102.413,17.93278],[102.99871,17.96169],[103.20019,18.30963],[103.95648,18.24095],[104.71695,17.42886],[104.77932,16.44186],[105.58904,15.57032],[105.54434,14.72393],[105.21878,14.27321],[104.28142,14.41674],[102.98842,14.22572],[102.3481,13.39425],[102.58493,12.18659]]]},\"properties\":{\"name\":\"Thailand\"}}]}","volume":"9","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Duangchatrasiri, Somphot","contributorId":217487,"corporation":false,"usgs":false,"family":"Duangchatrasiri","given":"Somphot","email":"","affiliations":[{"id":39649,"text":"Wildlife Research Division, Department of National Parks, Thailand","active":true,"usgs":false}],"preferred":false,"id":766888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jornburom, Pornkamol","contributorId":217488,"corporation":false,"usgs":false,"family":"Jornburom","given":"Pornkamol","email":"","affiliations":[{"id":39650,"text":"Univ. of MN, WCS Thailand","active":true,"usgs":false}],"preferred":false,"id":766889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jinamoy, Sitthichai","contributorId":217489,"corporation":false,"usgs":false,"family":"Jinamoy","given":"Sitthichai","email":"","affiliations":[{"id":39651,"text":"WCS, Thailand","active":true,"usgs":false}],"preferred":false,"id":766890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pattanvibool, Anak","contributorId":217490,"corporation":false,"usgs":false,"family":"Pattanvibool","given":"Anak","email":"","affiliations":[{"id":39651,"text":"WCS, Thailand","active":true,"usgs":false}],"preferred":false,"id":766891,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":766887,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arnold, Todd W.","contributorId":36058,"corporation":false,"usgs":false,"family":"Arnold","given":"Todd","email":"","middleInitial":"W.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":766892,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fieberg, John","contributorId":44804,"corporation":false,"usgs":false,"family":"Fieberg","given":"John","affiliations":[{"id":7201,"text":"University of Minnesota-St. Paul","active":true,"usgs":false}],"preferred":false,"id":766893,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smith, James L D","contributorId":217491,"corporation":false,"usgs":false,"family":"Smith","given":"James","email":"","middleInitial":"L D","affiliations":[{"id":39652,"text":"Univ. of MN","active":true,"usgs":false}],"preferred":false,"id":766894,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202288,"text":"70202288 - 2019 - The potential role of very high-resolution imagery to characterise lake, wetland and stream systems across the Prairie Pothole Region, United States","interactions":[],"lastModifiedDate":"2019-06-13T14:18:43","indexId":"70202288","displayToPublicDate":"2019-02-18T10:47:14","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The potential role of very high-resolution imagery to characterise lake, wetland and stream systems across the Prairie Pothole Region, United States","docAbstract":"Aquatic features critical to watershed hydrology range widely in size from narrow, shallow streams to large, deep lakes. In this study we evaluated wetland, lake, and river systems across the Prairie Pothole Region to explore where pan-sharpened high-resolution (PSHR) imagery, relative to Landsat imagery, could provide additional data on surface water distribution and movement, missed by Landsat. We used the monthly Global Surface Water (GSW) Landsat product as well as surface water derived from Landsat imagery using a matched filtering algorithm (MF Landsat) to help consider how including partially inundated Landsat pixels as water influenced our findings. The PSHR outputs (and MF Landsat) were able to identify ~60–90% more surface water interactions between waterbodies, relative to the GSW Landsat product. However, regardless of Landsat source, by documenting many smaller (<0.2 ha), inundated wetlands, the PSHR outputs modified our interpretation of wetland size distribution across the Prairie Pothole Region.
The General Lake Model (GLM) is a one-dimensional open-source code designed to simulate the hydrodynamics of lakes, reservoirs, and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice cover dynamics, vertical mixing, and inflow–outflow dynamics. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-12-473-2019","usgsCitation":"Hipsey, M.R., Bruce, L.C., Boon, C., Busch, B., Carey, C.C., Hamilton, D., Hanson, P.C., Read, J.S., de Sousa, E., Weber, M., and Winslow, L., 2019, A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON): Geoscientific Model Development, v. 12, p. 473-523, https://doi.org/10.5194/gmd-12-473-2019.","productDescription":"51 p.","startPage":"473","endPage":"523","ipdsId":"IP-091920","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":467899,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-12-473-2019","text":"Publisher Index 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California","interactions":[],"lastModifiedDate":"2019-03-25T09:16:40","indexId":"70202737","displayToPublicDate":"2019-02-15T10:56:13","publicationYear":"2019","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":"Human-induced and natural carbon storage in floodplains of the Central Valley of California","docAbstract":"Active floodplains can putatively store large amounts of organic carbon (SOC) in subsoils originating from catchment erosion processes with subsequent floodplain deposition. Our study focussed on the assessment of SOC pools associated with alluvial floodplain soils that are affected by human-induced changes in floodplain deposition and in situ SOC mineralisation due to land use change and drainage. We evaluated depth-dependent SOC contents based on 23 soil cores down to 3 m and 10 drillings down to 7 m in a floodplain area of the lower Cosumnes River. An estimate of 266 Mg C ha−1 or about 59% of the entire SOC stored within the 7 m profiles was found in the upper 2 m. Most profiles (n = 25) contained discrete buried A horizons at depths of approximately 0.8 m. These profiles had up to 130% higher SOC stocks. The mean δ13C of all deep soil profiles clearly indicated that arable land use has already altered the stable isotopic signature in the first meter of the profile. Radiocarbon dating showed that the 14C age in the buried horizon was younger than in overlaying soils indicating a substantial sedimentation phase for the overlaying soils. An additional analysis of total mercury contents in the soil profiles indicated that this sedimentation was associated with upstream hydraulic gold mining after the 1850s. In summary, deep alluvial soils in floodplains store large amounts of SOC not yet accounted for in global carbon models. Historic data give evidence that large amounts of sediment were transported into the floodplains of most rivers of the Central Valley and deposited over organically rich topsoil, which promoted the stabilization of SOC, and needs to be considered to improve our understanding of the human-induced interference with C cycling.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.09.205","usgsCitation":"Steger, K., Fiener, P., Marvin-DiPasquale, M.C., Viers, J.H., and Smart, D.R., 2019, Human-induced and natural carbon storage in floodplains of the Central Valley of California: Science of the Total Environment, v. 651, no. 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The goal of the NESQA was to assess the health of wadeable streams in the region by characterizing multiple water-quality factors that are stressors to aquatic life and by evaluating the relation between these stressors and the condition of biological communities. Urbanization, agriculture, and human modifications to streamflow are anthropogenic changes that greatly affect water quality in the region; consequently, the study design primarily selected sites and targeted stressors associated with these activities. The NESQA built on a prior NAWQA study conducted in the region in 2014, the Atlantic Highlands flow-ecology study, which investigated the effects of anthropogenically modified flows on aquatic biological communities in primarily forested watersheds. Land-cover data for the NESQA were used to identify and select sites within the region that had watersheds ranging in levels of urban and agricultural development. A total of 95 sites were selected: 67 on streams in watersheds representing a range of urban land use, 13 on streams in watersheds with some degree of agricultural land use, and 15 on streams in predominantly forested watersheds with little development. Depending on land-cover characteristics, sites were sampled weekly for metal and organic contaminants, nutrients, and sediment for either a 9-week period that began the week of June 6, 2016, or a 4-week period that begin the week of July 11, 2016. Beginning August 1, 2016, and for about 2 weeks, an ecological survey was conducted at every site to assess stream habitat, and algal, benthic invertebrate, and fish communities. Additional samples collected during the ecological surveys were streambed sediment for chemical analysis and toxicity testing, and fish tissue for mercury analysis. This report describes the various study components and methods of the NESQA and describes a precursor effort for the Atlantic Highlands flow-ecology study. Details are presented for measurements of water quality, sediment chemistry, streamflow, and ecological surveys of stream biota and habitat, as well as processes of sample analysis, quality assurance and quality control, and data management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181183","collaboration":"National Water Quality Program","usgsCitation":"Coles, J.F., Riva-Murray, K., Van Metre, P.C., Button, D.T., Bell, A.H., Qi, S.L., Journey, C.A., and Sheibley, R.W., 2019, Design and methods of the U.S. Geological Survey Northeast Stream Quality Assessment (NESQA), 2016: U.S. Geological Survey Open-File Report 2018–1183, 46 p., https://doi.org/10.3133/ofr20181183.","productDescription":"Report: vii, 46 p.; Appendixes 1 and 2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095438","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":361093,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1183/ofr20181183_appendix2.xlsx","text":"Appendix 2, tables 2.1 through 2.10: Excel ","size":"119 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":361094,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1183/ofr20181183_appendixes.zip","text":"Appendixes 1 and 2, all tables in CSV format","size":"5.45 GB","linkFileType":{"id":6,"text":"zip"}},{"id":361095,"rank":6,"type":{"id":18,"text":"Project Site"},"url":"https://webapps.usgs.gov/rsqa/#!/"},{"id":361090,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1183/coverthb.jpg"},{"id":361091,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1183/ofr20181183.pdf","text":"Report","size":"2.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1183"},{"id":361092,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1183/ofr20181183_appendix1.xlsx","text":"Appendix 1, tables 1.1 through 1.4: Excel","size":"777 KB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.9365234375,\n 40.17887331434696\n ],\n [\n -68.291015625,\n 40.17887331434696\n ],\n [\n -68.291015625,\n 47.60616304386874\n ],\n [\n -79.9365234375,\n 47.60616304386874\n ],\n [\n -79.9365234375,\n 40.17887331434696\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The effectiveness of Integrated Water Resource Management (IWRM) modeling hinges on the quality of practices employed through the process, starting from early problem definition all the way through to using the model in a way that serves its intended purpose. The adoption and implementation of effective modeling practices need to be guided by a practical understanding of the variety of decisions that modelers make, and the information considered in making these choices. There is still limited documented knowledge on the modeling workflow, and the role of contextual factors in determining this workflow and which practices to employ. This paper attempts to contribute to this knowledge gap by providing systematic guidance of the modeling practices through the phases (Planning, Development, Application, and Perpetuation) and steps that comprise the modeling process, positing questions that should be addressed. Practice-focused guidance helps explain the detailed process of conducting IWRM modeling, including the role of contextual factors in shaping practices. We draw on findings from literature and the authors’ collective experience to articulate what and how contextual factors play out in employing those practices. In order to accelerate our learning about how to improve IWRM modeling, the paper concludes with five key areas for future practice-related research: knowledge sharing, overcoming data limitations, informed stakeholder involvement, social equity and uncertainty management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2019.02.013","usgsCitation":"Badham, J., Elsawah, S., Guillaume, J., Hamilton, S.H., Hunt, R., Jakeman, A.J., Pierce, S.A., Babbar-Sebens, M., Fu, B., Gober, P., Hill, M.C., Iwanaga, T., Loucks, D.P., Merritt, W.S., Peckham, S.D., Richmond, A.K., Zare, F., Ames, D.P., and Bammer, G., 2019, Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities: Environmental Modelling & Software, v. 116, 17 p., https://doi.org/10.1016/j.envsoft.2019.02.013.","productDescription":"17 p.","ipdsId":"IP-098737","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":467903,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://ro.ecu.edu.au/ecuworkspost2013/5935","text":"Publisher Index Page"},{"id":383145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"116","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Badham, J.","contributorId":248842,"corporation":false,"usgs":false,"family":"Badham","given":"J.","affiliations":[{"id":36943,"text":"Queens University","active":true,"usgs":false}],"preferred":false,"id":810046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elsawah, Sondoss","contributorId":146686,"corporation":false,"usgs":false,"family":"Elsawah","given":"Sondoss","affiliations":[],"preferred":false,"id":810047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guillaume, Joseph H. 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Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Simulating demography, genetics, and spatially explicit processes to inform reintroduction of a threatened char","docAbstract":"The success of species reintroductions can depend on a combination of environmental, demographic, and genetic factors. Although the importance of these factors in the success of reintroductions is well‐accepted, they are typically evaluated independently, which can miss important interactions. For species that persist in metapopulations, movement through and interaction with the landscape is predicted to be a vital component of persistence. Simulation‐based approaches are a promising technique for evaluating the independent and combined effects of these factors on the outcome of various reintroduction and associated management actions. We report results from a simulation study of bull trout (Salvelinus confluentus) reintroduction to three watersheds of the Pend Oreille River system in northeastern Washington State, USA. We used an individual‐based, spatially explicit simulation model to evaluate how reintroduction strategies, life history variation, and riverscape structure (e.g., network topology) interact to influence the demographic and genetic characteristics of reintroduced bull trout populations in three watersheds. Simulation scenarios included a range of initial genetic stocks (informed by empirical bull trout genetic data), variation in migratory tendency and life history, and two landscape connectivity alternatives representing a connected network (isolation‐by‐distance) and a fragmented network (isolation‐by‐barrier, using the known existing barriers). A novel feature of these simulations was the ability to consider the interaction of both demographic and genetic (i.e., demogenetic) factors in riverscapes with implicit asymmetric movement probabilities across the barriers. We found that connectivity (presence or absence of barriers) had the largest effect on demographic and genetic outcomes over 200 yr, with a greater effect than both initial genetic diversity and life history variation. We also identified regions of the study system in which bull trout populations persisted across a wide range of demographic, life history, and environmental connectivity parameters. Finally, we found no evidence that initial neutral genetic diversity influenced genetic diversity and structure after 200 yr; instead, genetic drift due to stray rate and population isolation dominated and erased any initial differences in genetic diversity. Our results highlight the utility of spatially explicit demogenetic approaches in exploring and understanding population dynamics—and their implications for management strategies—in fresh waters.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2589","usgsCitation":"Mims, M.C., Day, C.C., Burkhart, J.J., Fuller, M.R., Hinkle, J., Bearlin, A., Dunham, J.B., DeHaan, P.W., Holden, Z.A., and Landguth, E.L., 2019, Simulating demography, genetics, and spatially explicit processes to inform reintroduction of a threatened char: Ecosphere, v. 10, no. 2, p. 1-24, https://doi.org/10.1002/ecs2.2589.","productDescription":"Article e02589; 24 p.","startPage":"1","endPage":"24","ipdsId":"IP-103940","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":467904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2589","text":"Publisher Index Page"},{"id":361262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Pend Oreille River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.51113891601561,\n 48.179822811961785\n ],\n [\n -117.02911376953124,\n 48.179822811961785\n ],\n [\n -117.02911376953124,\n 48.9991410647952\n ],\n [\n -117.51113891601561,\n 48.9991410647952\n ],\n [\n -117.51113891601561,\n 48.179822811961785\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Mims, Meryl C. 0000-0003-0570-988X","orcid":"https://orcid.org/0000-0003-0570-988X","contributorId":209951,"corporation":false,"usgs":false,"family":"Mims","given":"Meryl","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":757283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Casey C.","contributorId":213259,"corporation":false,"usgs":false,"family":"Day","given":"Casey","email":"","middleInitial":"C.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":757284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burkhart, Jacob J.","contributorId":213260,"corporation":false,"usgs":false,"family":"Burkhart","given":"Jacob","email":"","middleInitial":"J.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":757285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuller, Matthew 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jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":757289,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"DeHaan, Patrick W.","contributorId":145918,"corporation":false,"usgs":false,"family":"DeHaan","given":"Patrick","email":"","middleInitial":"W.","affiliations":[{"id":16297,"text":"USFWS Abernathy Fish Technology Center, Longview, WA 98632","active":true,"usgs":false}],"preferred":false,"id":757290,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Holden, Zachary A.","contributorId":213263,"corporation":false,"usgs":false,"family":"Holden","given":"Zachary","email":"","middleInitial":"A.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":757291,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Landguth, Erin L.","contributorId":190821,"corporation":false,"usgs":false,"family":"Landguth","given":"Erin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":757292,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70202209,"text":"70202209 - 2019 - River‐valley morphology, basin size, and flow‐event magnitude interact to produce wide variation in flooding dynamics","interactions":[],"lastModifiedDate":"2019-02-14T12:37:40","indexId":"70202209","displayToPublicDate":"2019-02-14T12:37:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"River‐valley morphology, basin size, and flow‐event magnitude interact to produce wide variation in flooding dynamics","docAbstract":"Inundation dynamics are a key driver of ecosystem form and function in river‐valley bottoms. Inundation itself is an outcome of multi‐scalar interactions and can vary strongly within and among river reaches. As a result, establishing to what degree and how inundation dynamics vary spatially both within and among river reaches can be challenging. The objective of this study was to understand how river‐valley morphology, basin size, and flow‐event magnitude interact to affect inundation dynamics in river‐valley bottoms. We used 2D hydraulic models to simulate inundation in four river reaches from Maryland's Piedmont physiographic province, and qualitatively and quantitatively summarized within‐ and among‐reach patterns of inundation extent, duration, depth, shear stress, and wetting frequencies. On average, reaches from confined valley settings experienced less extensive flooding, shorter durations and shallower depths, stronger gradients of maximum shear stress, and relatively infrequent wetting compared to reaches from unconfined settings. These patterns were generally consistent across flow‐event magnitudes. Patterns of within‐reach flooding across event magnitudes revealed complex interactions between hydrology and surface topography. We concluded that valley morphology had a greater impact on flooding patterns than basin size: Inundation patterns were more consistent across reaches of similar morphology than similar basin size, but absolute values of inundation characteristics varied between large and small basins. Our results showed that the manifestation of out‐of‐bank flows in valley floors can vary widely depending on geomorphic context, even within a single physiographic province, which suggests that hydrologic and hydraulic conditions experienced on the valley floor may not be well represented by existing hydrologic metrics derived from discharge data alone. We thus support the notion that 2D hydraulic models can be useful hydrometric tools for cross‐scale investigations of floodplain ecosystems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2546","usgsCitation":"Van Appledorn, M., Baker, M.E., and Miller, A.J., 2019, River‐valley morphology, basin size, and flow‐event magnitude interact to produce wide variation in flooding dynamics: Ecosphere, v. 10, no. 1, p. 1-25, https://doi.org/10.1002/ecs2.2546.","productDescription":"Article e02546; 25 p.","startPage":"1","endPage":"25","ipdsId":"IP-096187","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467905,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2546","text":"Publisher Index Page"},{"id":437572,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ITQTNQ","text":"USGS data release","linkHelpText":"Complex interactions among river-valley morphology, basin size, and flow-event magnitude structure the physical template of floodplain ecosystems. Data"},{"id":361256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Chesapeake Bay Watershed","volume":"10","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":757248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Matthew E.","contributorId":149189,"corporation":false,"usgs":false,"family":"Baker","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":17665,"text":"Department of Geography and Environmental Systems, University of Maryland, Baltimore County, Baltimore, Maryland, US","active":true,"usgs":false}],"preferred":false,"id":757249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Andrew J.","contributorId":207595,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":15309,"text":"University of Maryland Baltimore County","active":true,"usgs":false}],"preferred":false,"id":757250,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202196,"text":"70202196 - 2019 - Factors affecting the occurrence of lead and manganese in untreated drinking water from Atlantic and Gulf Coastal Plain aquifers, eastern United States—Dissolved oxygen and pH framework for evaluating risk of elevated concentrations","interactions":[],"lastModifiedDate":"2019-02-14T10:19:07","indexId":"70202196","displayToPublicDate":"2019-02-14T10:19:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting the occurrence of lead and manganese in untreated drinking water from Atlantic and Gulf Coastal Plain aquifers, eastern United States—Dissolved oxygen and pH framework for evaluating risk of elevated concentrations","docAbstract":"Groundwater samples collected during 2012 and 2013 from public-supply wells screened in the Atlantic and Gulf Coastal Plain aquifers of the eastern and southeastern U.S. rarely contained lead or manganese concentrations that exceeded drinking-water limits, despite having corrosive characteristics. Data indicate that the occurrence of dissolved lead and manganese in sampled groundwater, prior to its distribution or treatment, was related to several explanatory factors including the presence of source minerals, hydrologic position along the flow path, water-rock interactions, and associated geochemical conditions such as pH and dissolved oxygen (DO) concentrations. Elevated concentrations of lead compared to health-based benchmarks were associated with groundwater that is acidic (pH ≤ 6.5), oxygenated (DO ≥ 2 mg/L), and closer to recharge zones (relatively young water). Elevated concentrations of manganese were associated with groundwater that is acidic to neutral (pH ≤ 7.5), has low DO (<2 mg/L), and further from recharge zones (relatively old). Under these geochemical conditions, minerals that could sequester lead or manganese tended to be undersaturated, and adsorption by hydrous ferric oxide was limited. Under neutral to alkaline pH conditions, precipitation of impure calcium carbonate or phosphate compounds containing traces of lead or manganese (solid solutions) could maintain low concentrations of the trace elements. Additionally, adsorption of lead or manganese cations by hydrous ferric oxides (HFO) could be another attenuating factor where conditions are oxidizing and dissolved inorganic carbon concentrations are relatively low. A DO/pH framework was developed as a screening tool for evaluating risk of elevated lead or manganese, based on the occurrence of elevated lead and manganese concentrations and the corresponding distributions of DO and pH in the Atlantic and Gulf Coastal Plain aquifers. Validation of the DO/pH framework was accomplished using an independent national dataset that showed consistent results for elevated lead (pH ≤ 6.5; DO ≥ 2 mg/L) and manganese (pH ≤ 7.5; DO < 2 mg/L).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2018.10.017","usgsCitation":"Brown, C., Barlow, J.R., Cravotta, C., and Lindsey, B.D., 2019, Factors affecting the occurrence of lead and manganese in untreated drinking water from Atlantic and Gulf Coastal Plain aquifers, eastern United States—Dissolved oxygen and pH framework for evaluating risk of elevated concentrations: Applied Geochemistry, v. 101, p. 88-102, https://doi.org/10.1016/j.apgeochem.2018.10.017.","productDescription":"15 p.","startPage":"88","endPage":"102","ipdsId":"IP-086334","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":437574,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MK6BCD","text":"USGS data release","linkHelpText":"Inventory of well-construction data, water-quality and quality control data, statistical data, and geochemical modeling data for wells in Atlantic and Gulf Coastal Plain aquifers, eastern United States, 2012 and 2013"},{"id":361243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Atlantic and Gulf Coastal Plain aquifers","volume":"101","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Craig J. 0000-0002-3858-3964","orcid":"https://orcid.org/0000-0002-3858-3964","contributorId":210450,"corporation":false,"usgs":true,"family":"Brown","given":"Craig J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barlow, Jeannie R. B. 0000-0002-0799-4656 jbarlow@usgs.gov","orcid":"https://orcid.org/0000-0002-0799-4656","contributorId":3701,"corporation":false,"usgs":true,"family":"Barlow","given":"Jeannie","email":"jbarlow@usgs.gov","middleInitial":"R. B.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":757190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":207249,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757193,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757191,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70005455,"text":"tm11B2 - 2019 - US Topo Product Standard","interactions":[],"lastModifiedDate":"2019-02-14T10:58:54","indexId":"tm11B2","displayToPublicDate":"2019-02-13T15:30:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"11-B2","title":"US Topo Product Standard","docAbstract":"This document defines a U.S. Geological Survey (USGS) digital topographic map. This map product series, named “US Topo,” is modeled on the now historical USGS 7.5-minute (1:24,000 scale) topographic map series produced and printed by the USGS from 1947 to 2006. US Topo maps have the same extent, scale, and general layout as the historical topographic maps. US Topo maps incorporate an orthorectified image (hereinafter referred to as “orthoimage”) and shaded relief image along with a selection of data that were included in the historical 7.5-minute topographic maps. Between June and September of 2017, the USGS transitioned the format of US Topo maps to be published, by using a geospatial extension, in an International Organization for Standardization (ISO) 32000-compliant Adobe® portable document format (PDF) that is called a “geospatial PDF.” Previously, US Topo maps were published, by using geospatial extensions patented by TerraGo® Technologies, in PDF in a format called a “GeoPDF®.” The geospatial PDF design allows a user to zoom in and out in a georeferenced environment, turn layers on and off, view or print any combination of layers, and print any portion of the map at the published scale. US Topo maps are intended to serve conventional map users by providing geographic information system (GIS) information in symbolized form in the customary topographic map layout. The maps are not intended for advanced GIS analysis applications. These products are built on standard coordinate systems and include full U.S. National Grid (USNG) lines, making US Topo maps particularly useful for emergency first-response operations. These maps are also used by traditional topographic map users, such as resource managers, planners, and recreational users who continue to have a need for the symbolized feature data contained in the 7.5-minute quadrangle maps. Full-size style sheet templates in PDF defining the placement of map elements, marginalia, and font sizes and styles accompany this standard. US Topo maps published as geospatial PDFs are fashioned to conform to these style sheets so that a user can print out a map at the 1:24,000, 1:25,000, or 1:20,000 scale using the dimensions of the traditional standard 7.5-minute quadrangle. Symbology and type specifications for feature content and detailed requirements for geospatial content will be published separately. This document is an update of the US Topo Product Standard published in 2011 (Cooley and others, 2011). It is applicable to all US Topo maps. Updates in this version include
|
Director, National Geospatial Technical Operations Center
U.S. Geological Survey
Box 25046, MS 510
Denver Federal Center
Denver, CO 80225-0046
Maintenance of genetic diversity is important for conserving species, especially those with fragmented habitats or ranges. In the absence of natural dispersal, translocation can be used to achieve this goal, although the success of translocation can be difficult to measure. Here we evaluate genetic change following translocation in Gunnison Sage-Grouse (Centrocercus minimus), a species reduced to 7 discrete populations with low levels of gene flow and high levels of genetic differentiation. Between 2000 and 2014, 306 birds from the largest and most genetically diverse population (Gunnison Basin) were translocated to 5 much smaller satellite populations to augment local population size and increase genetic diversity. Although the magnitude of the effect varied by population, we found evidence of increased genetic variation, decreased genetic differentiation from Gunnison Basin, and reproduction between translocated individuals and resident birds. These results suggest that translocations are impacting satellite populations, with current data providing a new baseline for genetic diversity among populations of this imperiled species.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duy006","usgsCitation":"Zimmerman, S., Aldridge, C., Apa, A.D., and Oyler-McCance, S.J., 2019, Evaluation of genetic change from translocation among Gunnison Sage-Grouse (Centrocercus minimus) populations: Ornithological Applications, v. 121, no. 1, duy006, 14 p., https://doi.org/10.1093/condor/duy006.","productDescription":"duy006, 14 p.","ipdsId":"IP-100802","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":398630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.64355468749999,\n 37.3002752813443\n ],\n [\n -106.3916015625,\n 37.3002752813443\n ],\n [\n -106.3916015625,\n 38.92522904714054\n ],\n [\n -109.64355468749999,\n 38.92522904714054\n ],\n [\n -109.64355468749999,\n 37.3002752813443\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Zimmerman, Shawna J","contributorId":139402,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Shawna J","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":840426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":213471,"corporation":false,"usgs":false,"family":"Aldridge","given":"Cameron L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":840427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Apa, Anthony D.","contributorId":272966,"corporation":false,"usgs":false,"family":"Apa","given":"Anthony","email":"","middleInitial":"D.","affiliations":[{"id":40103,"text":"cdpw","active":true,"usgs":false}],"preferred":false,"id":840428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":840429,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202178,"text":"70202178 - 2019 - The dual‐domain porosity apparatus: Characterizing dual porosity at the sediment/water interface","interactions":[],"lastModifiedDate":"2019-07-23T12:21:29","indexId":"70202178","displayToPublicDate":"2019-02-12T16:49:16","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"The dual‐domain porosity apparatus: Characterizing dual porosity at the sediment/water interface","docAbstract":"The characterization of pore-space connectivity in porous media at the sediment/water interface is critical to understanding contaminant transport and reactive biogeochemical processes in zones of groundwater and surface-water exchange. Previous in situ studies of dual-domain (i.e., \nmobile/less-mobile porosity) studies have been limited to solute tracer injections at scales of meters to 100s of meters and subsequent numerical model parameterization using fluid concentration histories. Pairing fine-scale (e.g., sub-meter) geoelectrical measurements with fluid tracer data over time alleviates dependence on flowpath-scale experiments, enabling spatially targeted characterization of shallow sediment/water interface media where biogeochemical reactivity is often high. The Dual-Domain Porosity Apparatus is a field-tested device capable of variable rate-controlled downward flow experiments. The Dual-Domain Porosity Apparatus facilitates meter-scale inference of dual-domain parameters, i.e., mobile/less-mobile exchange rate coefficient and the ratio of less mobile to mobile porosity. The Dual-Domain Porosity Apparatus experimental procedure uses water electrical conductivity as a conservative tracer of differential loading and flushing of pore spaces within the region of measurement. Variable injection rates permit the direct quantification of the flow-dependence of dual-domain parameters, which has been theorized for decades but remains challenging to assess using existing experimental methodologies.","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12846","usgsCitation":"Scruggs, C.R., Briggs, M.A., Day-Lewis, F.D., Werkema, D.D., and Lane, J., 2019, The dual‐domain porosity apparatus: Characterizing dual porosity at the sediment/water interface: Groundwater, v. 57, no. 4, p. 640-646, https://doi.org/10.1111/gwat.12846.","productDescription":"7 p.","startPage":"640","endPage":"646","ipdsId":"IP-102223","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467908,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7028363","text":"External Repository"},{"id":361214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Scruggs, Courtney R. 0000-0002-1744-3233 cscruggs@usgs.gov","orcid":"https://orcid.org/0000-0002-1744-3233","contributorId":190406,"corporation":false,"usgs":true,"family":"Scruggs","given":"Courtney","email":"cscruggs@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":757117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":757118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":757119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Werkema, Dale D.","contributorId":190401,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":757120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":757121,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202167,"text":"70202167 - 2019 - Three-dimensional geologic mapping to assess geothermal potential: Examples from Nevada and Oregon","interactions":[],"lastModifiedDate":"2019-02-12T16:21:46","indexId":"70202167","displayToPublicDate":"2019-02-12T16:21:43","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5804,"text":"Geothermal Energy – Science, Society and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Three-dimensional geologic mapping to assess geothermal potential: Examples from Nevada and Oregon","docAbstract":"Geologic structure plays an important role in controlling fluid flow in geothermal systems. In particular, very complex structural settings, consisting of many closely spaced and intersecting faults, host many geothermal systems. To elucidate the key geologic factors that affect fault-controlled geothermal circulation, it is critical to precisely characterize the structural and stratigraphic geometries in these complex settings. Here, we present a methodology and the results of 3D geologic analyses of two geothermal systems in the Basin and Range, USA. This methodology is a quantitative and geologically focused technique that can be used to precisely characterize geothermal areas, in a time when future geothermal growth demands increased exploration precision and efficiency. Surficial and subsurface geologic and geophysical data are synthesized in the construction of detailed 3D geologic maps of geothermal areas. Based on these 3D geologic maps, we examine several geologic attributes that control permeability development and geothermal fluid flow along faults. We use the stress state of faults and the distribution of structural discontinuities (i.e., fault intersections and fault terminations) to identify locations of upflow along faults in these geothermal systems. These results and the methodology presented herein are directly applicable to structurally controlled geothermal fields in the Basin and Range and worldwide. As development focus shifts toward blind geothermal resources, integration of precisely characterized subsurface structural information into exploration methods will be increasingly critical to continued growth in geothermal exploration and development.
","language":"English","publisher":"Springer","doi":"10.1186/s40517-018-0117-0","usgsCitation":"Siler, D.L., Faulds, J., Hinz, N.H., Dering, G.M., Edwards, J.H., and Mayhew, B., 2019, Three-dimensional geologic mapping to assess geothermal potential: Examples from Nevada and Oregon: Geothermal Energy – Science, Society and Technology, v. 7, no. 2, p. 1-32, https://doi.org/10.1186/s40517-018-0117-0.","productDescription":"32 p.","startPage":"1","endPage":"32","ipdsId":"IP-102990","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467910,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40517-018-0117-0","text":"Publisher Index Page"},{"id":361208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","volume":"7","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":757063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faulds, James E.","contributorId":184258,"corporation":false,"usgs":false,"family":"Faulds","given":"James E.","affiliations":[],"preferred":false,"id":757064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hinz, Nicholas H.","contributorId":211979,"corporation":false,"usgs":false,"family":"Hinz","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":757065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dering, Gregory M.","contributorId":213188,"corporation":false,"usgs":false,"family":"Dering","given":"Gregory","email":"","middleInitial":"M.","affiliations":[{"id":38377,"text":"University of Nevada, Reno, Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":757066,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Joel H.","contributorId":202599,"corporation":false,"usgs":false,"family":"Edwards","given":"Joel","email":"","middleInitial":"H.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":757067,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mayhew, Brett","contributorId":213189,"corporation":false,"usgs":false,"family":"Mayhew","given":"Brett","email":"","affiliations":[{"id":38377,"text":"University of Nevada, Reno, Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":757068,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203224,"text":"70203224 - 2019 - Stratification of reactivity determines nitrate removal in groundwater","interactions":[],"lastModifiedDate":"2019-05-01T07:53:36","indexId":"70203224","displayToPublicDate":"2019-02-12T07:52:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Stratification of reactivity determines nitrate removal in groundwater","docAbstract":"Biogeochemical reactions occur unevenly in space and time, but this heterogeneity is often simplified as a linear average due to sparse data, especially in subsurface environments where access is limited. For example, little is known about the spatial variability of groundwater denitrification, an important process in removing nitrate originating from agriculture and land use conversion. Information about the rate, arrangement, and extent of denitrification is needed to determine sustainable limits of human activity and to predict recovery time frames. Here, we developed and validated a method for inferring the spatial organization of sequential biogeochemical reactions in an aquifer in France. We applied it to five other aquifers in different geological settings located in the United States and compared results among 44 locations across the six aquifers to assess the generality of reactivity trends. Of the sampling locations, 79% showed pronounced increases of reactivity with depth. This suggests that previous estimates of denitrification have underestimated the capacity of deep aquifers to remove nitrate, while overestimating nitrate removal in shallow flow paths. Oxygen and nitrate reduction likely increases with depth because there is relatively little organic carbon in agricultural soils and because excess nitrate input has depleted solid phase electron donors near the surface. Our findings explain the long-standing conundrum of why apparent reaction rates of oxygen in aquifers are typically smaller than those of nitrate, which is energetically less favorable. This stratified reactivity framework is promising for mapping vertical reactivity trends in aquifers, generating new understanding of subsurface ecosystems and their capacity to remove contaminants.
The timing and extent of international crossings by billfishes, tunas, and sharks in the Cuba-Mexico-United States (U.S.) triangle was investigated using electronic tagging data from eight species that resulted in >22,000 tracking days. Transnational movements of these highly mobile marine predators were pronounced with varying levels of bi- or tri-national population connectivity displayed by each species. Billfishes and tunas moved throughout the Gulf of Mexico and all species investigated (blue marlin, white marlin, Atlantic bluefin tuna, yellowfin tuna) frequently crossed international boundaries and entered the territorial waters of Cuba and/or Mexico. Certain sharks (tiger shark, scalloped hammerhead) displayed prolonged periods of residency in U.S. waters with more limited displacements, while whale sharks and to a lesser degree shortfin mako moved through multiple jurisdictions. The spatial extent of associated movements was generally associated with their differential use of coastal and open ocean pelagic ecosystems. Species with the majority of daily positions in oceanic waters off the continental shelf showed the greatest tendency for transnational movements and typically traveled farther from initial tagging locations. Several species converged on a common seasonal movement pattern between territorial waters of the U.S. (summer) and Mexico (winter).
","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-38144-8","usgsCitation":"Rooker, J.R., Dance, M.A., Wells, R.J., Ajemian, M.J., Block, B.A., Castleton, M.R., Drymon, J.M., Falterman, B.J., Franks, J.S., Hammerschlag, N., Hendon, J.M., Hoffmayer, E.R., Kraus, R.T., McKinney, J.A., Secor, D.H., Stunz, G.W., and Walter, J.F., 2019, Population connectivity of pelagic megafauna in the Cuba-Mexico-United States triangle: Scientific Reports, v. 9, no. 1, p. 1-13, https://doi.org/10.1038/s41598-018-38144-8.","productDescription":"Article number: 1663; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-098137","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467918,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-38144-8","text":"Publisher Index Page"},{"id":361124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Cuba-Mexico-United States triangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99,\n 15\n ],\n [\n -73,\n 15\n ],\n [\n -73,\n 31\n ],\n [\n -99,\n 31\n ],\n [\n -99,\n 15\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Rooker, Jay R.","contributorId":213048,"corporation":false,"usgs":false,"family":"Rooker","given":"Jay","email":"","middleInitial":"R.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":756843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dance, Michael A.","contributorId":213049,"corporation":false,"usgs":false,"family":"Dance","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":756844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wells, R. J. David","contributorId":213050,"corporation":false,"usgs":false,"family":"Wells","given":"R.","email":"","middleInitial":"J. David","affiliations":[{"id":38696,"text":"Texas A&M Univeristy","active":true,"usgs":false}],"preferred":false,"id":756845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ajemian, Matthew J.","contributorId":177080,"corporation":false,"usgs":false,"family":"Ajemian","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":756846,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Block, Barbara A.","contributorId":150815,"corporation":false,"usgs":false,"family":"Block","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":18108,"text":"Tuna Research and Conservation Center, Stanford University, Hopkins Marine Station, Pacific Grove, California 93950, U.S.A","active":true,"usgs":false}],"preferred":false,"id":756847,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Castleton, Michael R.","contributorId":213051,"corporation":false,"usgs":false,"family":"Castleton","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":756848,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Drymon, J. Marcus","contributorId":213052,"corporation":false,"usgs":false,"family":"Drymon","given":"J.","email":"","middleInitial":"Marcus","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":756849,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Falterman, Brett J.","contributorId":213053,"corporation":false,"usgs":false,"family":"Falterman","given":"Brett","email":"","middleInitial":"J.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":756850,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Franks, James S.","contributorId":213054,"corporation":false,"usgs":false,"family":"Franks","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":38697,"text":"University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":756851,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hammerschlag, Neil","contributorId":213059,"corporation":false,"usgs":false,"family":"Hammerschlag","given":"Neil","email":"","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":756857,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hendon, Jill M.","contributorId":213060,"corporation":false,"usgs":false,"family":"Hendon","given":"Jill","email":"","middleInitial":"M.","affiliations":[{"id":38697,"text":"University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":756858,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hoffmayer, Eric R.","contributorId":213055,"corporation":false,"usgs":false,"family":"Hoffmayer","given":"Eric","email":"","middleInitial":"R.","affiliations":[{"id":38698,"text":"NOAA Fisheries","active":true,"usgs":false}],"preferred":false,"id":756852,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":756842,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McKinney, Jennifer A.","contributorId":213056,"corporation":false,"usgs":false,"family":"McKinney","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":756853,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Secor, David H.","contributorId":179379,"corporation":false,"usgs":false,"family":"Secor","given":"David","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":756854,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Stunz, Gregory W.","contributorId":213057,"corporation":false,"usgs":false,"family":"Stunz","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":38699,"text":"Texas A&M University - Corpus Christi","active":true,"usgs":false}],"preferred":false,"id":756855,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Walter, John F.","contributorId":213058,"corporation":false,"usgs":false,"family":"Walter","given":"John","email":"","middleInitial":"F.","affiliations":[{"id":38698,"text":"NOAA Fisheries","active":true,"usgs":false}],"preferred":false,"id":756856,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70203003,"text":"70203003 - 2019 - Groundwater inflow toward a preheated volcanic conduit: Application to the 2018 eruption at Kīlauea Volcano, Hawai’i","interactions":[],"lastModifiedDate":"2019-04-11T10:25:06","indexId":"70203003","displayToPublicDate":"2019-02-08T10:23:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater inflow toward a preheated volcanic conduit: Application to the 2018 eruption at Kīlauea Volcano, Hawai’i","docAbstract":"The many successes in volcano forecasting over the past several decades owe mainly to pattern recognition, both in monitoring data and the geologic record. During the early stages of the 2018 Kīlauea eruption, the conceptual model of Stearns (1925), based on the explosive 1924 Kīlauea eruption, was highly influential. This model postulates that explosions are triggered by liquid-water inflow into a recently vacated magma conduit. Modern quantitative modeling approaches, supplemented by hydrogeologic data unavailable in 1925, yield a more nuanced view. Results demonstrate that liquid-water inflow would likely be delayed by months to years, owing to the inability of liquid water to transit a zone of very hot rock surrounding the conduit. The exercise demonstrates the use of physically based modeling to supplement traditional volcano-forecasting approaches during an ongoing event.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JB017133","usgsCitation":"Hsieh, P.A., and Ingebritsen, S.E., 2019, Groundwater inflow toward a preheated volcanic conduit: Application to the 2018 eruption at Kīlauea Volcano, Hawai’i: Journal of Geophysical Research, v. 124, no. 2, p. 1498-1506, https://doi.org/10.1029/2018JB017133.","productDescription":"9 p.","startPage":"1498","endPage":"1506","ipdsId":"IP-103531","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":362911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.30393600463867,\n 19.39050559875186\n ],\n [\n -155.30393600463867,\n 19.44296062654318\n ],\n [\n -155.23029327392578,\n 19.44296062654318\n ],\n [\n -155.23029327392578,\n 19.39050559875186\n ],\n [\n -155.30393600463867,\n 19.39050559875186\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hsieh, Paul A. 0000-0003-4873-4874 pahsieh@usgs.gov","orcid":"https://orcid.org/0000-0003-4873-4874","contributorId":1634,"corporation":false,"usgs":true,"family":"Hsieh","given":"Paul","email":"pahsieh@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":39113,"text":"WMA - Office of Quality Assurance","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":760743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":760742,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201218,"text":"sir20185165 - 2019 - Using acoustic Doppler velocity meters to estimate suspended sediment along the lower Minnesota and Mississippi Rivers","interactions":[],"lastModifiedDate":"2019-02-08T12:35:57","indexId":"sir20185165","displayToPublicDate":"2019-02-08T07:23:13","publicationYear":"2019","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":"2018-5165","displayTitle":"Using Acoustic Doppler Velocity Meters to Estimate Suspended Sediment along the Lower Minnesota and Mississippi Rivers","title":"Using acoustic Doppler velocity meters to estimate suspended sediment along the lower Minnesota and Mississippi Rivers","docAbstract":"Lake Pepin is the largest naturally formed lake on the Mississippi River and has complex management needs to satisfy economic, environmental, and cultural demands. Lake Pepin is filling in with sediment at a rapid rate compared to conditions before settlement by European immigrants and intense agricultural cultivation. Accordingly, the Minnesota Pollution Control Agency has developed aggressive plans to prioritize sediment sources, understand transport mechanisms, and implement large-scale strategies to reduce sedimentation in Lake Pepin.
The Minnesota River is the primary sediment source to Lake Pepin, and reductions in sediment loading from the Minnesota River are needed to reduce sedimentation in Lake Pepin. Current loading estimates were calculated from grab sampling and total suspended solids laboratory methods that greatly underestimate the actual concentrations in the rivers when compared to U.S. Geological Survey width and depth integrated sampling and laboratory methods for determining suspended-sediment concentration (SSC). Therefore, the U.S. Geological Survey, with funding from the Environment and Natural Resources Trust Fund and in cooperation with the U.S. Army Corps of Engineers, Lower Minnesota River Watershed District, Minnesota Pollution Control Agency, and Minnesota Department of Natural Resources, collected SSCs and acoustic backscatter data from acoustic Doppler velocity meters over a 2-year period at nine sites. The purpose of the study was to improve understanding of sediment-transport processes and increase accuracy of estimating SSCs and suspended-sediment loads for the lower Minnesota River and the Mississippi River compared to traditional measures.
The study results indicated that acoustic backscatter worked well in estimating SSCs at sites not regulated by locks, dams, and lakes. The results also confirmed previous studies that determined most of the suspended-sediment loading into the Mississippi River is from the Minnesota River and the largest sediment sink is Lake Pepin. Suspended-sediment loading from site to site and year to year was often variable when compared to streamflow, which has been traditionally used to estimate SSC. As a result, this study demonstrates the value in having high temporal and spatial resolution of continuous sediment monitoring from acoustic devices to help manage the sources of sediment into Lake Pepin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185165","collaboration":"Prepared in cooperation with Environment and Natural Resources Trust Fund, U.S. Army Corps of Engineers, Lower Minnesota River Watershed District, Minnesota Pollution Control Agency, and Minnesota Department of Natural Resources","usgsCitation":"Groten, J.T., Ziegeweid, J.R., Lund, J.W., Ellison, C.A., Costa, S.B., Coenen, E.N., and Kessler, E.W., 2019, Using acoustic Doppler velocity meters to estimate suspended sediment along the lower Minnesota and Mississippi Rivers: U.S. Geological Survey Scientific Investigations Report 2018–5165, 30 p., https://doi.org/10.3133/sir20185165.","productDescription":"Report: viii, 30 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-096837","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":361062,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7542MXV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Suspended-sediment concentrations, acoustic data, and linear regression models for the Lower Minnesota River, Mississippi River, and Lake Pepin, 2015–2017"},{"id":361061,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5165/sir20185165.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5165"},{"id":361060,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5165/coverthb3.jpg"}],"country":"United States","otherGeospatial":"Minnesota River, Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"GeometryCollection\",\n \"geometries\": [\n {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.36792373657227,\n 44.036269809534616\n ],\n [\n -94.36792373657227,\n 45.089035564831036\n ],\n [\n -92.02783584594725,\n 45.089035564831036\n ],\n [\n -92.02783584594725,\n 44.036269809534616\n ],\n [\n -94.36792373657227,\n 44.036269809534616\n ]\n ]\n ]\n }\n ]\n },\n \"properties\": {\n \"name\": \"footprint.3216965\",\n \"description\": \"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
The health and function of northern peatlands, particularly for fens, are strongly affected by fire and hydrology. Fens are important to several avian species of conservation interest, notably the yellow rail (Coturnicops noveboracensis). Fire suppression and altered hydrology often result in woody encroachment, altering the plant community and structure. Woody encroachment and its effects on biodiversity have become an increasing concern in the conservation and management of plant communities. This study evaluated the effects of spring and summer prescribed burns on the plant community, cover, and structure in open and partially wooded fens at Seney National Wildlife Refuge, Michigan, using a before-after-control-impact design. Paired, 1-hectare blocks were established in two fen areas, C3 and Marsh Creek, and data were collected for 2 years before burning (2006–7) and 3 years after burning (2008–10). We used generalized linear mixed models and ordination to assess differences among four treatments: C3 control, C3 spring burn (May 2008), Marsh Creek control, and Marsh Creek summer burn (July 2008); results from a block burned under drier conditions in July 2007 also are reported. Variables include water depth; litter depth; graminoid height; species richness and diversity; percent cover of plant taxa, mosses, and open area; shrub height, number of patches, and cover; and visual obstruction readings. The 2008 prescribed burns were done under moderate fire conditions, whereas the 2007 summer burn on one block was done under high fire conditions because of prolonged drought. We identified 104 plant taxa over the 5 years and noted differences between C3 and Marsh Creek communities. We examined data for effects of treatment, year, and year × treatment interactions for percent open and the 28 most common taxa. Most differences among treatments were related to natural differences in the plant community and hydrology between the two areas rather than fire effects; year effects were likely related to annual differences in water conditions. We detected few effects of spring burning in C3, even in the same year of burning. In Marsh Creek, most treatment effects were in 2008, when data were collected within 3 weeks of burning. Some fire effects there, however, persisted one to two growing seasons (2009, 2010) and two to three growing seasons in the block burned in the more intense summer 2007 fire. Effects of burning on shrub measures were more apparent on summer-burned blocks, but most measures returned to preburn conditions by 2010. Our results demonstrate the heterogeneity of plant community and environmental conditions of fens within and among years and the interactions of water conditions with burning. The results also demonstrate that neither single spring nor summer burning under moderate fire conditions are effective in setting back woody cover. Maintaining more open conditions in fens may require different approaches to water management, more frequent fires, more aggressive fire management, or a combination of tools to control woody cover.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185168","usgsCitation":"Austin, J.E., and Newton, W.E., 2019, Response of vegetation in open and partially wooded fens to prescribed burning at Seney National Wildlife Refuge: U.S. Geological Survey Scientific Investigations Report 2018–5168, 62 p., https://doi.org/10.3133/sir20185168.","productDescription":"Report: viii, 62 p.; Data Release","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-098588","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":361081,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5168/coverthb.jpg"},{"id":361083,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90P8VWJ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Effects of fire on vegetation in fens at Seney National Wildlife Refuge"},{"id":361082,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5168/sir20185168.pdf","text":"Report","size":"5.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5168"}],"country":"United States","state":"Michigan","otherGeospatial":"Seney National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.26121520996094,\n 46.15724277677564\n ],\n [\n -85.92681884765624,\n 46.15724277677564\n ],\n [\n -85.92681884765624,\n 46.34289859337118\n ],\n [\n -86.26121520996094,\n 46.34289859337118\n ],\n [\n -86.26121520996094,\n 46.15724277677564\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Habitat loss and fragmentation are primary threats to biodiversity worldwide. We studied the impacts of habitat loss and fragmentation on genetic connectivity and diversity among local aggregations of the California gnatcatcher (Polioptila californica californica) across its U.S. range. With a dataset of 268 individuals genotyped at 19 microsatellite loci, we analyzed genetic structure across the range using clustering analyses, exact tests for population differentiation, and a pedigree analysis to examine the spatial distribution of first-order relatives throughout the study area. In addition, we developed a habitat suitability model and related percent suitable habitat to genetic diversity indices within aggregations at two spatial scales. We detected a single genetic cluster across the range, with weak genetic structure among recently geographically isolated aggregations in the northern part of the range. The pedigree analysis detected closely related individuals across disparate aggregations and across large geographic distances in the majority of the sampled range, demonstrating that recent long-distance dispersal has occurred within this species. Genetic diversity was independent of suitable habitat at a local 5-km scale, but increased in a non-linear fashion with habitat availability at a broader, 30-km scale. Diversity declined steeply when suitable habitat within 30-km fell below 10%. Together, our results suggest that California gnatcatchers retain genetic connectivity across the majority of the current distribution of coastal sage scrub fragments, with the exception of some outlying aggregations. Connectivity may help support long-term persistence under current conservation and management strategies. However, emerging structure among more remote aggregations and associations between available habitat and genetic diversity also suggest that continued loss of habitat could threaten diversity and connectivity in the future.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-37712-2","usgsCitation":"Vandergast, A.G., Kus, B., Preston, K.L., and Barr, K., 2019, Distinguishing recent dispersal from historical genetic connectivity in the coastal California gnatcatcher: Scientific Reports, v. 9, p. 1-12, https://doi.org/10.1038/s41598-018-37712-2.","productDescription":"Article number 1355; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-099518","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":467924,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-37712-2","text":"Publisher Index Page"},{"id":437577,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SJRU51","text":"USGS data release","linkHelpText":"Coastal California Gnatcatcher Habitat Suitability Model for Southern California (2015)"},{"id":437576,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77D2SBP","text":"USGS data release","linkHelpText":"Genetic Structure of California Gnatcatcher Populations in Southern California from 2012 through 2013"},{"id":361071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.24560546875001,\n 32.565333160841035\n ],\n [\n -116.4715576171875,\n 32.565333160841035\n ],\n [\n -116.4715576171875,\n 34.6060845921693\n ],\n [\n -119.24560546875001,\n 34.6060845921693\n ],\n [\n -119.24560546875001,\n 32.565333160841035\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":756773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":756774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Preston, Kristine L. 0000-0002-6958-1128 kpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-6958-1128","contributorId":207765,"corporation":false,"usgs":true,"family":"Preston","given":"Kristine","email":"kpreston@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":756775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barr, Kelly R.","contributorId":212860,"corporation":false,"usgs":false,"family":"Barr","given":"Kelly R.","affiliations":[{"id":38694,"text":"former USGS employee; current affiliation UCLA","active":true,"usgs":false}],"preferred":false,"id":756776,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218277,"text":"70218277 - 2019 - Monitoring landscape dynamics in central U.S. grasslands with harmonized Landsat-8 and Sentinel-2 time series data","interactions":[],"lastModifiedDate":"2021-02-24T13:13:25.614595","indexId":"70218277","displayToPublicDate":"2019-02-07T07:08:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring landscape dynamics in central U.S. grasslands with harmonized Landsat-8 and Sentinel-2 time series data","docAbstract":"Remotely monitoring changes in central U.S. grasslands is challenging because these landscapes tend to respond quickly to disturbances and changes in weather. Such dynamic responses influence nutrient cycling, greenhouse gas contributions, habitat availability for wildlife, and other ecosystem processes and services. Traditionally, coarse-resolution satellite data acquired at daily intervals have been used for monitoring. Recently, the harmonized Landsat-8 and Sentinel-2 (HLS) data increased the temporal frequency of the data. Here we investigated if the increased data frequency provided adequate observations to characterize highly dynamic grassland processes. We evaluated HLS data available for 2016 to (1) determine if data from Sentinel-2 contributed to an improvement in characterizing landscape processes over Landsat-8 data alone, and (2) quantify how observation frequency impacted results. Specifically, we investigated into estimating annual vegetation phenology, detecting burn scars from fire, and modeling within-season wetland hydroperiod and growth of aquatic vegetation. We observed increased sensitivity to the start of the growing season (SOST) with the HLS data. Our estimates of the grassland SOST compared well with ground estimates collected at a phenological camera site. We used the Continuous Change Detection and Classification (CCDC) algorithm to assess if the HLS data improved our detection of burn scars following grassland fires and found that detection was considerably influenced by the seasonal timing of the fires. The grassland burned in early spring recovered too quickly to be detected as change events by CCDC; instead, the spectral characteristics following these fires were incorporated as part of the ongoing time-series models. In contrast, the spectral effects from late-season fires were detected both by Landsat-8 data and HLS data. For wetland-rich areas, we used a modified version of the CCDC algorithm to track within-season dynamics of water and aquatic vegetation. The addition of Sentinel-2 data provided the potential to build full time series models to better distinguish different wetland types, suggesting that the temporal density of data was sufficient for within-season characterization of wetland dynamics. Although the different data frequency, in both the spatial and temporal dimensions, could cause inconsistent model estimation or sensitivity sometimes; overall, the temporal frequency of the HLS data improved our ability to track within-season grassland dynamics and improved results for areas prone to cloud contamination. The results suggest a greater frequency of observations, such as from harmonizing data across all comparable Landsat and Sentinel sensors, is still needed. For our study areas, at least a 3-day revisit interval during the early growing season (weeks 14–17) is required to provide a >50% probability of obtaining weekly clear observations.
","language":"English","publisher":"MDPI","doi":"10.3390/rs11030328","usgsCitation":"Zhou, Q., Rover, J., Brown, J.F., Worstell, B.B., Howard, D., Wu, Z., Gallant, A.L., Rundquist, B., and Burke, M., 2019, Monitoring landscape dynamics in central U.S. grasslands with harmonized Landsat-8 and Sentinel-2 time series data: Remote Sensing, v. 11, no. 3, 328, 23 p., https://doi.org/10.3390/rs11030328.","productDescription":"328, 23 p.","ipdsId":"IP-104526","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467926,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11030328","text":"Publisher Index Page"},{"id":383590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.2509765625,\n 47.90161354142077\n ],\n [\n -96.3720703125,\n 47.90161354142077\n ],\n [\n -96.3720703125,\n 49.009050809382046\n ],\n [\n -97.2509765625,\n 49.009050809382046\n ],\n [\n -97.2509765625,\n 47.90161354142077\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhou, Qiang 0000-0002-1282-8177","orcid":"https://orcid.org/0000-0002-1282-8177","contributorId":223103,"corporation":false,"usgs":true,"family":"Zhou","given":"Qiang","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":810803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rover, Jennifer 0000-0002-3437-4030","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":211850,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":810877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":810876,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Worstell, Bruce B. 0000-0001-8927-3336 worstell@usgs.gov","orcid":"https://orcid.org/0000-0001-8927-3336","contributorId":1815,"corporation":false,"usgs":true,"family":"Worstell","given":"Bruce","email":"worstell@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":810804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Howard, Danny 0000-0002-7563-7538 danny.howard.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":176973,"corporation":false,"usgs":true,"family":"Howard","given":"Danny","email":"danny.howard.ctr@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":810878,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":810880,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":810881,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rundquist, Bradley 0000-0002-2572-9792","orcid":"https://orcid.org/0000-0002-2572-9792","contributorId":251983,"corporation":false,"usgs":false,"family":"Rundquist","given":"Bradley","email":"","affiliations":[],"preferred":false,"id":810888,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Burke, Morgan","contributorId":251990,"corporation":false,"usgs":false,"family":"Burke","given":"Morgan","email":"","affiliations":[],"preferred":false,"id":810889,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70202020,"text":"70202020 - 2019 - Predicting the initial spread of novel Asian origin influenza A viruses in the continental USA by wild waterfowl","interactions":[],"lastModifiedDate":"2019-03-15T12:36:43","indexId":"70202020","displayToPublicDate":"2019-02-06T16:20:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3849,"text":"Transboundary and Emerging Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the initial spread of novel Asian origin influenza A viruses in the continental USA by wild waterfowl","docAbstract":"Using data on waterfowl band recoveries, we identified spatially explicit hotspots of concentrated waterfowl movement to predict occurrence and spatial spread of a novel influenza A virus (clade 2.3.4.4) introduced from Asia by waterfowl from an initial outbreak in North America in November 2014. In response to the outbreak, the hotspots of waterfowl movement were used to help guide sampling for clade 2.3.4.4 viruses in waterfowl as an early warning for the US poultry industry during the outbreak . After surveillance sampling of waterfowl, we tested whether there was greater detection of clade 2.3.4.4 viruses inside hotspots. We found that hotspots defined using kernel density estimates of waterfowl band recoveries worked well in predicting areas with higher prevalence of the viruses in waterfowl. This approach exemplifies the value of ecological knowledge in predicting risk to agricultural security.
","language":"English","publisher":"Wiley","doi":"10.1111/tbed.13070","usgsCitation":"Franklin, A.B., Bevins, S.N., Ellis, J.W., Miller, R.S., Shriner, S.A., Root, J.J., Walsh, D.P., and DeLiberto, T.J., 2019, Predicting the initial spread of novel Asian origin influenza A viruses in the continental USA by wild waterfowl: Transboundary and Emerging Diseases, v. 66, no. 2, p. 705-714, https://doi.org/10.1111/tbed.13070.","productDescription":"10 p.","startPage":"705","endPage":"714","ipdsId":"IP-090306","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":361065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Franklin, Alan B.","contributorId":101999,"corporation":false,"usgs":false,"family":"Franklin","given":"Alan","email":"","middleInitial":"B.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":756726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bevins, Sarah N.","contributorId":212845,"corporation":false,"usgs":false,"family":"Bevins","given":"Sarah","email":"","middleInitial":"N.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":756727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Jeremy W.","contributorId":212846,"corporation":false,"usgs":false,"family":"Ellis","given":"Jeremy","email":"","middleInitial":"W.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":756728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ryan S.","contributorId":49005,"corporation":false,"usgs":false,"family":"Miller","given":"Ryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":756729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shriner, Susan A.","contributorId":168690,"corporation":false,"usgs":false,"family":"Shriner","given":"Susan","email":"","middleInitial":"A.","affiliations":[{"id":13407,"text":"Colorado State Univ.","active":true,"usgs":false}],"preferred":false,"id":756730,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Root, J. 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The number of landslides that occurred during this event was two orders of magnitude greater than those reported from previous hurricanes. Landslide source areas were commonly limited to surficial soils but also extended into underlying saprolite and bedrock. Slope failures occurred before, during, and after flooding, and many transitioned into long runout debris flows. Steep slopes in hilly and mountainous regions were particularly impacted by landslides due to antecedent soil moisture levels that were 11%–13% higher than average and rainfall totals of at least 250 mm within a 48 h period. High landslide densities were especially widespread across some geologic formations (e.g., granodiorite of the Utuado batholith); however, bedrock geology alone did not determine the location and distribution of landslides caused by Hurricane Maria. While rainfall data collected during Hurricane Maria were inconsistent, satellite-based soil moisture data were correlated with the distribution of landslides. In the future, the use of soil moisture data could enable assessments of regional landslide susceptibility prior to hurricanes or extreme precipitation events.","language":"English","publisher":"Geological Society of America","doi":"10.1130/GSATG383A.1","usgsCitation":"Bessette-Kirton, E., Cerovski-Darriau, C., Schulz, W.H., Coe, J.A., Kean, J.W., Godt, J.W., Thomas, M.A., and Hughes, K.S., 2019, Landslides triggered by Hurricane Maria: Assessment of an extreme event in Puerto Rico: GSA Today, v. 29, no. 6, p. 4-10, https://doi.org/10.1130/GSATG383A.1.","productDescription":"7 p.","startPage":"4","endPage":"10","ipdsId":"IP-103814","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":467927,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/gsatg383a.1","text":"Publisher Index Page"},{"id":370181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.4725341796875,\n 17.84283252904802\n ],\n [\n -65.4510498046875,\n 17.84283252904802\n ],\n [\n -65.4510498046875,\n 18.60460138845525\n ],\n [\n -67.4725341796875,\n 18.60460138845525\n ],\n [\n -67.4725341796875,\n 17.84283252904802\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bessette-Kirton, Erin 0000-0002-2797-0694 ebessette-kirton@usgs.gov","orcid":"https://orcid.org/0000-0002-2797-0694","contributorId":177153,"corporation":false,"usgs":true,"family":"Bessette-Kirton","given":"Erin","email":"ebessette-kirton@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cerovski-Darriau, Corina 0000-0002-0543-0902","orcid":"https://orcid.org/0000-0002-0543-0902","contributorId":221159,"corporation":false,"usgs":true,"family":"Cerovski-Darriau","given":"Corina","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":777239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulz, William H. 0000-0001-9980-3580 wschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-9980-3580","contributorId":942,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"wschulz@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":777241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777242,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":777243,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777244,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hughes, K. 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Clinical signs of SFD include dermal lesions, including regional and local edema, crusts, and ulcers. Snake fungal disease is widespread in the Eastern United States, yet there are limited data on how clinical signs of SFD compare with laboratory diagnostics. We compared two sampling methods for O. ophiodiicola, scale clip collection and swabbing, to evaluate whether collection method impacted the results of polymerase chain reaction (PCR). In addition, we evaluated the use of clinical signs to predict the presence of O. ophiodiicola across seasons, snake habitat affiliation (aquatic or terrestrial) and study sites. We found no significant difference in PCR results between sampling methods. Clinical signs were a strong predictor of O. ophiodiicola presence in spring and summer seasons. Snakes occupying terrestrial environments had a lower overall probability of testing positive for O. ophiodiicolacompared to snakes occupying aquatic environments. Although our study indicates that both clinical signs of SFD and prevalence of O. ophiodiicola vary seasonally and based on habitat preferences of the host, our analysis suggests that clinical signs can serve as a reliable indicator of O. ophiodiicola presence, especially during spring and summer.
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