1. The recovery of piscivorous birds around the world is touted as one of the great conservation successes of the 21st century, but for some species, this success was short-lived. Bald eagles, ospreys, and great blue herons began repatriating Voyageurs National Park, USA, in the mid-20th century. However, after 1990, only eagles continued their recovery, while osprey and heron recovery failed for unknown reasons.
2. We aimed to evaluate whether top-down effects of bald eagles, and bottom-up effects of inclement weather, habitat quality, and fish resources contributed to the failed recovery of ospreys and herons in a protected area.
3. We quantified the relative influence of top-down and bottom-up factors on nest colonization, persistence (i.e., nest reuse) and success for ospreys, and occurrence and size of heronries using 26 years (1986-2012) of spatially-explicit monitoring data coupled with multi-response hierarchical models and Bayesian variable selection approaches.
4. Bald eagles were previously shown to recover faster due to intensive nest protection and management. Increased numbers of eagles were associated with a reduction in the numbers of osprey nests, their nesting success, and heronry size; while higher local densities of nesting eagles deterred heronries nearby. We found little evidence of bottom-up limitations on the failed recovery of herons and ospreys.
5. We present a conservation conundrum: bald eagles are top predators and a flagship species of conservation that have benefited from intensive protection, but this likely hindered the recovery of ospreys and herons. Returning top predators, or rewilding, is widely promoted as a conservation strategy for top-down ecosystem recovery, but managing top predators in isolation of jointly recovering species can halt or reverse ecosystem recovery. Previous studies warn of the potential consequences of ignoring biotic interactions amongst recovering species, but we go further by quantifying how these interactions contributed to failed recoveries via impacts on the nesting demography of jointly recovering species. Multi-species management is paramount to realizing the ecosystem benefits of top predator recovery.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.12990","usgsCitation":"Cruz, J., Windels, S.K., Thogmartin, W.E., Crimmins, S., Grim, L.H., Larson, J.H., and Zuckerberg, B., 2019, Top-down effect of repatriating bald eagles hinder jointly recovering competitors: Journal of Animal Ecology, v. 88, no. 7, p. 1054-1065, https://doi.org/10.1111/1365-2656.12990.","productDescription":"12 p.","startPage":"1054","endPage":"1065","ipdsId":"IP-101998","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467726,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12990","text":"Publisher Index Page"},{"id":367533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Voyageurs National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.22586059570312,\n 48.10743118848039\n ],\n [\n -92.50350952148438,\n 48.10743118848039\n ],\n [\n -92.50350952148438,\n 48.608397925562606\n ],\n [\n -93.22586059570312,\n 48.608397925562606\n ],\n [\n -93.22586059570312,\n 48.10743118848039\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","issue":"7","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Cruz, Jennyffer","contributorId":202194,"corporation":false,"usgs":false,"family":"Cruz","given":"Jennyffer","email":"","affiliations":[{"id":36365,"text":"Department of Forest and Wildlife Ecology, University of Wisconsin – Madison","active":true,"usgs":false}],"preferred":false,"id":771177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Windels, Steve K.","contributorId":182422,"corporation":false,"usgs":false,"family":"Windels","given":"Steve","email":"","middleInitial":"K.","affiliations":[{"id":18939,"text":"Voyageurs National Park","active":true,"usgs":false}],"preferred":false,"id":771178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":771176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crimmins, Shawn M.","contributorId":202196,"corporation":false,"usgs":false,"family":"Crimmins","given":"Shawn M.","affiliations":[{"id":36367,"text":"College of Natural Resources, University of Wisconsin – Stevens Point","active":true,"usgs":false}],"preferred":false,"id":771179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grim, Leland H.","contributorId":219062,"corporation":false,"usgs":false,"family":"Grim","given":"Leland","email":"","middleInitial":"H.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":771180,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":771181,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zuckerberg, Benjamin","contributorId":200298,"corporation":false,"usgs":false,"family":"Zuckerberg","given":"Benjamin","email":"","affiliations":[{"id":13562,"text":"University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":771182,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202935,"text":"70202935 - 2019 - A stratigraphic approach to inferring depositional ages from detrital geochronology data","interactions":[],"lastModifiedDate":"2019-04-08T15:28:08","indexId":"70202935","displayToPublicDate":"2019-04-05T13:56:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"A stratigraphic approach to inferring depositional ages from detrital geochronology data","docAbstract":"With the increasing use of detrital geochronology data for provenance analyses, we have also developed new constraints on the age of otherwise undateable sedimentary deposits. Because a deposit can be no older than its youngest mineral constituent, the youngest defensible detrital mineral age defines the maximum depositional age of the sampled bed. Defining the youngest `defensible' age in the face of uncertainty (e.g., analytical and geological uncertainty, or sample contamination) is challenging. The current standard practice of finding multiple detrital minerals with indistinguishable ages provides confidence that a given age is not an artifact; however, we show how requiring this overlap reduces the probability of identifying the true youngest component age. Barring unusual complications, the principle of superposition dictates that sedimentary deposits must get younger upsection. This fundamental constraint can be incoporated into the analysis of depositional ages in sedimentary sections through the use of Bayesian statistics, allowing for the inference of bounded estimates of true depositional ages and uncertainties from detrital geochronology so long as some minimum age constraints are present. We present two approaches for constructing a Bayesian model of deposit ages, first solving directly for the ages of deposits with the prior constraint that the ages of units must obey stratigraphic ordering, and second describing the evolution of ages with a curve that represents the sediment accumulation rate. Using synthetic examples we highlight how this method preforms in less-than-ideal circumstances. In an example from the Magallanes Basin of Patagonia, we demonstrate how introducing other age information from the stratigraphic section (e.g., fossil assemblages or radiometric dates) and formalizing the stratigraphic context of samples provides additional constraints on and information regarding depositional ages or derived quantities (e.g., sediment accumulation rates) compared to isolated analysis of individual samples.","language":"English","publisher":"Frontiers of Earth Science","doi":"10.3389/feart.2019.00057","usgsCitation":"Johnstone, S., Schwartz, T.M., and Holm-Denoma, C.S., 2019, A stratigraphic approach to inferring depositional ages from detrital geochronology data: Frontiers in Earth Science, v. 7, Article 57; 19 p., https://doi.org/10.3389/feart.2019.00057.","productDescription":"Article 57; 19 p.","ipdsId":"IP-102542","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":460413,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2019.00057","text":"Publisher Index Page"},{"id":362843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":760541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwartz, Theresa M.","contributorId":214678,"corporation":false,"usgs":false,"family":"Schwartz","given":"Theresa","email":"","middleInitial":"M.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":760542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440 cholm-denoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":2442,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher","email":"cholm-denoma@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":760543,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202931,"text":"70202931 - 2019 - Multi-scale preferential flow processes in an urban streambed under variable hydraulic conditions","interactions":[],"lastModifiedDate":"2019-04-05T12:54:14","indexId":"70202931","displayToPublicDate":"2019-04-05T08:59:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale preferential flow processes in an urban streambed under variable hydraulic conditions","docAbstract":"Spatially preferential flow processes occur at nested scales at the sediment-water interface (SWI), due in part to sediment heterogeneities, which may be enhanced in flashy urban streams with heavy road sand influence. However, several factors, including the flow-rate dependence of preferential hyporheic flow and discrete groundwater discharge zones are commonly overlooked in reach-scale models of groundwater/surface water exchange. Using a series of controlled-head tracer-injection experiments coupled with cm-scale geophysics within the highly reactive upper 30 cm of the hyporheic zone of an urban stream, we quantified the flow dependence of local less-mobile porosity volume, mass-transfer rate coefficient, and the resulting local residence time in the less-mobile pore space at three controlled downward fluid fluxes (0.8, 2, and 3 m/d). Experiments were performed in two adjacent streambed locations, representing different sediment bulk vertical permeability. Less-mobile porosity parameters were generally substantial and similar between the two streambed locations; though a more competent, thin, organic layer at ∼15 cm depth in one location strongly impacted tracer loading, flushing dynamics, and local residence times. Increased downward flux led to (1) a decrease in less-mobile porosity residence time in all experiments, and (2) an increase in less-mobile porosity fraction for most experiments. Additionally, at the larger stream reach-scale, surface electrodes for electrical resistivity measurement were installed along 22 m of the wetted stream channel. These surface electrode measurements were collected during a natural storm flow event, which revealed widespread, short-term, flushing (e.g. <3 h) of the hyporheic zone with stream water, followed by longer-term (e.g. >60 h) flushing of the SWI with riparian zone groundwater. Flow dependence of preferential hyporheic zone flowpaths, like in the controlled tracer experiments, was also observed in these reach-scale electrical resistivity tomography measurements. Our findings reveal that the spatial and temporal dependence of preferential flow processes create highly dynamic SWI conditions that will affect the physical and coupled biogeochemical functions of the SWI in urbanized, sand-impacted streams.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.03.022","usgsCitation":"Dehkordy, F.M., Briggs, M.A., Day-Lewis, F.D., Singha, K., Krajnovich, A., Hampton, T.B., Zarnetske, J.P., Scruggs, C.R., and Bagtzoglou, A.C., 2019, Multi-scale preferential flow processes in an urban streambed under variable hydraulic conditions: Journal of Hydrology, v. 573, p. 168-179, https://doi.org/10.1016/j.jhydrol.2019.03.022.","productDescription":"12 p.","startPage":"168","endPage":"179","ipdsId":"IP-104970","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2019.03.022","text":"Publisher Index Page"},{"id":362811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"573","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dehkordy, Farzaneh MahmoodPoor","contributorId":214661,"corporation":false,"usgs":false,"family":"Dehkordy","given":"Farzaneh","email":"","middleInitial":"MahmoodPoor","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":760524,"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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":760523,"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":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":760525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":760526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krajnovich, Ashton","contributorId":214671,"corporation":false,"usgs":false,"family":"Krajnovich","given":"Ashton","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":760527,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hampton, Tyler B.","contributorId":210072,"corporation":false,"usgs":false,"family":"Hampton","given":"Tyler","email":"","middleInitial":"B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":760528,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zarnetske, Jay P.","contributorId":210073,"corporation":false,"usgs":false,"family":"Zarnetske","given":"Jay","email":"","middleInitial":"P.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":760529,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":760530,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bagtzoglou, Amvrossios C.","contributorId":211518,"corporation":false,"usgs":false,"family":"Bagtzoglou","given":"Amvrossios","email":"","middleInitial":"C.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":760531,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70252905,"text":"70252905 - 2019 - Factors affecting 1,2,3-trichloropropane contamination in groundwater in California","interactions":[],"lastModifiedDate":"2025-01-28T15:31:22.559551","indexId":"70252905","displayToPublicDate":"2019-04-05T07:08:51","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17043,"text":"Science of the Total Envionrment","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Factors Affecting 1,2,3-trichloropropane Contamination in Groundwater in California","title":"Factors affecting 1,2,3-trichloropropane contamination in groundwater in California","docAbstract":"1,2,3-Trichloropropane (1,2,3-TCP) is a volatile organic chemical of eminent concern due to its carcinogenic, mutagenic, and reproductive effects, and its frequent occurrence at concentrations of concern worldwide. In California, 1,2,3-TCP was detected in 6.5% of 1237 wells sampled by the U. S. Geological Survey (USGS). About 8% of domestic wells had a detection of 1,2,3-TCP, compared to 5% of public-supply wells. 1,2,3-TCP was detected in 5.5% of most recent samples from 7787 public-supply well sources of the California State Water Resources Control Board Division of Drinking Water (DDW). Concentrations ranged from <0.005 to 2.7 μg/L. The California maximum contaminant level (MCL) is 0.005 μg/L. Most of the detections occurred in the San Joaquin Valley, where 1,2,3-TCP was detected above the MCL in 16% of USGS sampled wells and 18% of DDW wells. 1,2,3-TCP occurrence and concentrations are related to legacy fumigant use and hydrogeologic factors. Understanding factors affecting 1,2,3-TCP will aid in determining vulnerability and long term persistence in the San Joaquin Valley, which can help focus efforts to manage drinking water resources on the most vulnerable areas and also inform efforts in other areas of the state and worldwide. Widespread occurrence of 1,2,3-TCP is related to nonpoint source agricultural contaminant inputs. High concentrations of 1,2,3-TCP are in young, shallow, oxic groundwater beneath primarily orchard/vineyard crops. These areas are in coarse-grained sediments that promote rapid recharge, related to proximal alluvial fan sediments deposited by large streams that drain glaciated watersheds of the Sierra Nevada. 1,2,3-TCP co-occurs with 1,2-dibromo-3-chloropropane (DBCP) and 1,2-dichloropropane (1,2-DCP) throughout modern age groundwater, indicating its long term persistence with little degradation. The highest concentrations of 1,2,3-TCP were observed at point source cleanup sites in urban areas; depending on the age and source of groundwater to nearby public-supply wells, these areas may see increasing concentrations of 1,2,3-TCP.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.03.420","usgsCitation":"Burow, K.R., Floyd, W.D., and Landon, M.K., 2019, Factors affecting 1,2,3-trichloropropane contamination in groundwater in California: Science of the Total Envionrment, v. 672, no. 1 July 2019, p. 324-334, https://doi.org/10.1016/j.scitotenv.2019.03.420.","productDescription":"11 p.","startPage":"324","endPage":"334","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":487474,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.03.420","text":"Publisher Index Page"},{"id":427698,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427783,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70252905/70252905.pdf","text":"USGS open-access version of article","size":"5 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\"}}]}","volume":"672","issue":"1 July 2019","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burow, Karen R. 0000-0001-6006-6667 krburow@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-6667","contributorId":1504,"corporation":false,"usgs":true,"family":"Burow","given":"Karen","email":"krburow@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":898681,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Floyd, Walter D.","contributorId":335551,"corporation":false,"usgs":false,"family":"Floyd","given":"Walter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":898682,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landon, Matthew K. 0000-0002-5766-0494 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quantitative estimation of the quick-flow runoff component of streamflow is required for many hydrologic applications. Estimation at the monthly timescale and national spatial scale would be particularly useful for national water availability modeling. This paper reviews a sample of commonly used equations for quick-flow runoff, including several currently in use in continental-scale models. The review shows the wide range of equation forms or heuristics currently in use to predict quick-flow runoff, the limited spatial scale over which these equations are often developed or calibrated, and the scarcity of well-tested equations available for quick-flow runoff at the monthly timescale. Data were gathered from a set of 1301 gaged watersheds across the United States to test a range of equations from the literature, along with several alternative equations, to assess and compare their performance in predicting quick-flow runoff at the monthly timescale. The highest-performing equation was selected for application to monthly maps of explanatory variables to produce monthly quick-flow runoff water budget contribution maps. This equation is a regression against precipitation, soil saturated hydraulic conductivity, surficial geology type, and slope data. Its application indicates that average quick-flow runoff across the conterminous United States in the winter exceeds that in the summer by up to a factor of three. The monthly maps were explored and evaluated for the timespan of 2000-2015. The comparison of equation forms and produced monthly maps will be useful for a variety of hydrologic modeling and monitoring applications.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.04.010","usgsCitation":"Reitz, M., and Sanford, W.E., 2019, Estimating quick-flow runoff at the monthly timescale for the conterminous United States: Journal of Hydrology, v. 573, p. 841-854, https://doi.org/10.1016/j.jhydrol.2019.04.010.","productDescription":"14 p.","startPage":"841","endPage":"854","ipdsId":"IP-102672","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":467732,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2019.04.010","text":"Publisher Index Page"},{"id":437509,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y1RP02","text":"USGS data release","linkHelpText":"Monthly timescale quick-flow runoff maps for 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,{"id":70202719,"text":"ofr20191025 - 2019 - Annual wastewater nutrient data preparation and load estimation using the Point Source Load Estimation Tool (PSLoadEsT)","interactions":[],"lastModifiedDate":"2019-04-08T08:53:56","indexId":"ofr20191025","displayToPublicDate":"2019-04-04T07:00:28","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1025","displayTitle":"Annual Wastewater Nutrient Data Preparation and Load Estimation Using the Point-Source Load Estimation Tool (PSLoadEsT)","title":"Annual wastewater nutrient data preparation and load estimation using the Point Source Load Estimation Tool (PSLoadEsT)","docAbstract":"The Point-Source Load Estimation Tool (PSLoadEsT) provides a user-friendly interface for generating reproducible load calculations for point source dischargers while managing common data challenges including duplicates, incompatible input tables, and incomplete or missing nutrient concentration or effluent flow data. Maintaining a consistent method across an entire study area is important when estimating loads to be used as calibration data for regional water-quality models. PSLoadEsT is written using the open-source programming language R and has an easy-to-use interface written in Visual Basic for Applications® within a Microsoft Access® database file that guides the user through the necessary steps to estimate point source loads. The purpose of this report is to provide a detailed user guide for PSLoadEsT.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191025","collaboration":"National Water Quality Assessment Program","usgsCitation":"Gorman Sanisaca, L.E., Skinner, K.D., and Maupin, M.A., 2019, Annual wastewater nutrient data preparation and load estimation using the Point Source Load Estimation Tool (PSLoadEsT): U.S. Geological Survey Open-File Report 2019-1025, 48 p., https://doi.org/10.3133/ofr20191025.","productDescription":"Report: vi, 48 p.; Additional Report Piece","onlineOnly":"Y","ipdsId":"IP-099356","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":437510,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QWVZ4L","text":"USGS data release","linkHelpText":"Point-Source Load Estimation Tool (PSLoadEsT)"},{"id":362728,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1025/coverthb.jpg"},{"id":362733,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P9QWVZ4L","text":"PSLoadEsT Software release","description":"PSLoadEsT Software release"},{"id":362729,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1025/ofr20191025.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1025"},{"id":362732,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1101","text":"Data Series 1101","description":"Data Series 1101","linkHelpText":"Point-Source Nutrient Loads to Streams of the Conterminous United States, 2012"}],"contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228
Paleoseismic and historical earthquake records used to quantify earthquake recurrence rates can also be used to test the likelihood of seismically quiescent periods. At principal paleoseismic sites in California on the San Andreas, San Jacinto, Elsinore, and Hayward faults, no ground‐rupturing earthquake has occurred in the last 100 yr, yet this interval is about three times the average interearthquake period for the ensemble of sites. We examine long paleoseismic records from these faults, as they carry most of the transform fault slip on the plate boundary, to see if the current hiatus has any precedent in the last 1000 yr. The selection of sites is designed to sample fault sections unlikely to have ruptured together, so their conditional probabilities of a hiatus can be combined as independent events. We find a 100‐yr hiatus is not predicted by common time‐dependent or time‐independent recurrence models. Paleoearthquake dating uncertainties can allow long open intervals at individual sites or subsets of sites, but do not explain the observed gap in the ensemble. After approximately removing redundancies in the full paleoearthquake record, the time‐independent probability of the current 100‐yr gap is of order 0.3%. This raises several questions. Do we live in a statistically exceptional time? Or does some wide‐scale effect modulate earthquake occurrence among sites over longer timescales? Finally, how should we understand seismic hazard estimates in California if the recurrence models on which they rely seem, at minimum, incomplete? Whether due to a statistical anomaly, some longer‐term modulation of earthquake occurrence, or another cause, our results emphasize that the hiatus of the last century has been exceptional.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220180244","usgsCitation":"Biasi, G., and Scharer, K., 2019, The current unlikely earthquake hiatus at California’s transform boundary paleoseismic sites: Seismological Research Letters, v. 90, no. 3, p. 1168-1176, https://doi.org/10.1785/0220180244.","productDescription":"9 p.","startPage":"1168","endPage":"1176","ipdsId":"IP-099541","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":377371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Elsinore Fault, Hayward Fault, San Andreas Fault, San Jacinto Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.20214843749999,\n 32.509761735919426\n ],\n [\n -115.20263671874999,\n 32.65787573695528\n ],\n [\n -114.67529296874999,\n 32.80574473290688\n ],\n [\n -115.09277343749999,\n 34.19817309627726\n ],\n [\n -118.7841796875,\n 37.68382032669382\n ],\n [\n -120.9375,\n 39.774769485295465\n ],\n [\n -121.6845703125,\n 40.83043687764923\n ],\n [\n -124.5849609375,\n 40.51379915504413\n ],\n [\n -123.99169921875,\n 38.92522904714054\n ],\n [\n -122.78320312499999,\n 36.932330061503144\n ],\n [\n -121.33300781249999,\n 35.08395557927643\n ],\n [\n -120.234375,\n 33.87041555094183\n ],\n [\n -117.20214843749999,\n 32.509761735919426\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"90","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Biasi, Glenn 0000-0003-0940-5488 gbiasi@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-5488","contributorId":195946,"corporation":false,"usgs":true,"family":"Biasi","given":"Glenn","email":"gbiasi@usgs.gov","affiliations":[],"preferred":true,"id":795730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scharer, Katherine M. 0000-0003-2811-2496","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":217361,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":795731,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206425,"text":"70206425 - 2019 - Holocene thermokarst lake dynamics in northern Interior Alaska: The interplay of climate, fire, and subsurface hydrology","interactions":[],"lastModifiedDate":"2019-11-05T06:57:24","indexId":"70206425","displayToPublicDate":"2019-04-03T11:32:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Holocene thermokarst lake dynamics in northern Interior Alaska: The interplay of climate, fire, and subsurface hydrology","docAbstract":"The current state of permafrost in Alaska and meaningful expectations for its future evolution are informed by long-term perspectives of previous permafrost degradation. Thermokarst processes in permafrost landscapes often lead to widespread lake formation and the spatial and temporal evolution of thermokarst lake landscapes reflects the combined effects of climate, ground conditions, vegetation, and fire. This study provides detailed analyses of thermokarst lake sediments of Holocene age from the southern loess uplands of the Yukon Flats; including bathymetry and sediment core analyses across a water depth transect. The sediment core results, dated by radiocarbon and 210Pb, indicate the onset of finely laminated lacustrine sedimentation between ~10,000 and 9,000 cal yr BP following basin development through inferred thermokarst processes. Thermokarst expansion to modern shoreline configurations continued until ~5000 cal yr BP, which may have been influenced by increased fire. Between ~5000 and 2000 cal yr BP, the preservation of fine laminations at intermediate and deep-water depths indicate higher lake levels than present. At that time, the lake likely overflowed into an over-deepened gully system that is no longer occupied by perennial streams. By ~2000 cal yr BP, massive sedimentation at intermediate water depths indicates that lake levels lowered, which is interpreted to reflect a response to drier conditions based on correspondence with Yukon Flats regional fire and local paleoclimate reconstructions. Consideration of additional contributing mechanisms include the possible influence of catastrophic lake drainages on downgradient base flow levels that may have enhanced subsurface water loss, although this mechanism is untested. The overall consistency between the millennial lake level trends documented here with regional paleoclimate trends indicates that after lakes formed, their size and depth has likely been affected directly by North Pacific atmospheric circulation changes and indirectly through evolution of permafrost, ground ice and sub-surface hydrology. As the first detailed study of Holocene thermokarst basin expansion, stabilization and subsequent climate-driven lake level variations in a loess upland, results provide a framework for future investigations of paleoclimatic signals from similar lake systems that characterize large regions of Alaska and Siberia.","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2019.00053","usgsCitation":"Anderson, L., Edwards, M.E., Mark D. Shapley, Bruce P. Finney, and Langdon, C., 2019, Holocene thermokarst lake dynamics in northern Interior Alaska: The interplay of climate, fire, and subsurface hydrology: Frontiers in Earth Science, v. 7, p. 1-22, https://doi.org/10.3389/feart.2019.00053.","productDescription":"53, 22 p.","startPage":"1","endPage":"22","ipdsId":"IP-102292","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467736,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2019.00053","text":"Publisher Index Page"},{"id":437512,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O7255D","text":"USGS data release","linkHelpText":"Data Release for "Holocene thermokarst lake dynamics in northern Interior Alaska: the interplay of climate, fire, and subsurface hydrology""},{"id":368921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Habanero pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -146.75811767578125,\n 66.07962172153299\n ],\n [\n -146.7121124267578,\n 66.07962172153299\n ],\n [\n -146.7121124267578,\n 66.10772577267431\n ],\n [\n -146.75811767578125,\n 66.10772577267431\n ],\n [\n -146.75811767578125,\n 66.07962172153299\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":220214,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Mary E.","contributorId":220215,"corporation":false,"usgs":false,"family":"Edwards","given":"Mary","email":"","middleInitial":"E.","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":774502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mark D. Shapley","contributorId":220216,"corporation":false,"usgs":false,"family":"Mark D. Shapley","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":774503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bruce P. Finney","contributorId":220217,"corporation":false,"usgs":false,"family":"Bruce P. Finney","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":774504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Langdon, Catherine","contributorId":220218,"corporation":false,"usgs":false,"family":"Langdon","given":"Catherine","email":"","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":774505,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204115,"text":"70204115 - 2019 - Disentangling effects of invasive species and habitat while accounting for observer error in a long-term amphibian study","interactions":[],"lastModifiedDate":"2019-07-08T09:57:18","indexId":"70204115","displayToPublicDate":"2019-04-02T09:51:03","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":"Disentangling effects of invasive species and habitat while accounting for observer error in a long-term amphibian study","docAbstract":"The invasive American bullfrog (Lithobates catesbeianus) and a variety of non‐native sport fish commonly co‐occur in lowland lentic habitats of the western United States. Both invasive taxa are implicated in declines of native amphibians in this region, but few long‐term studies of communities exist. Further, field studies of invasive–native interactions are complicated by confounding habitat modifications and observation errors. We surveyed amphibians and measured habitat characteristics for 12 yr across 38 wetland sites within the Willamette Valley, Oregon, USA. We assessed the influence of invasive species, habitat, and their interactions on the distributions of five native amphibian species using a multispecies dynamic occupancy model that accounted for false‐negative and false‐positive detections. In general, habitat characteristics—such as within‐pond vegetation cover, surrounding forest, and drought severity—were important for local persistence of native species when bullfrogs co‐occurred. We also found evidence of a cumulative negative effect of bullfrogs and non‐native fish (families Centrarchidae and Ictaluridae) on northern red‐legged frog (Rana aurora) local persistence that was mediated by the dominance of invasive reed canarygrass (Phalaris arundinacea). Non‐native fish and bullfrogs had variable effects on native amphibian species, but neither invasive taxon appears to be causing declines in occupied sites within our study area. Moreover, species relationships with habitat differed when invaders were present, indicating that certain habitats may increase persistence of native amphibians in the invaded landscape.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.2674","usgsCitation":"Rowe, J., Duarte, A., Pearl, C., McCreary, B., Galvan, S., Peterson, J.T., and Adams, M.J., 2019, Disentangling effects of invasive species and habitat while accounting for observer error in a long-term amphibian study: Ecosphere, v. 10, no. 4, e02674, 22 p., https://doi.org/10.1002/ecs2.2674.","productDescription":"e02674, 22 p.","ipdsId":"IP-098966","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":460417,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2674","text":"Publisher Index Page"},{"id":365327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.431396484375,\n 44.15856343854312\n ],\n [\n -122.7447509765625,\n 44.15856343854312\n ],\n [\n -122.7447509765625,\n 45.41002023463975\n ],\n [\n -123.431396484375,\n 45.41002023463975\n ],\n [\n -123.431396484375,\n 44.15856343854312\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Rowe, Jennifer 0000-0002-5253-2223 jrowe@usgs.gov","orcid":"https://orcid.org/0000-0002-5253-2223","contributorId":172670,"corporation":false,"usgs":true,"family":"Rowe","given":"Jennifer","email":"jrowe@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":765576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duarte, Adam","contributorId":28492,"corporation":false,"usgs":false,"family":"Duarte","given":"Adam","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":765577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearl, Christopher 0000-0003-2943-7321 christopher_pearl@usgs.gov","orcid":"https://orcid.org/0000-0003-2943-7321","contributorId":172669,"corporation":false,"usgs":true,"family":"Pearl","given":"Christopher","email":"christopher_pearl@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":765578,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCreary, Brome 0000-0002-0313-7796 brome_mccreary@usgs.gov","orcid":"https://orcid.org/0000-0002-0313-7796","contributorId":3130,"corporation":false,"usgs":true,"family":"McCreary","given":"Brome","email":"brome_mccreary@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":765579,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Galvan, Stephanie 0000-0002-9864-3674 stephanie_galvan@usgs.gov","orcid":"https://orcid.org/0000-0002-9864-3674","contributorId":3135,"corporation":false,"usgs":true,"family":"Galvan","given":"Stephanie","email":"stephanie_galvan@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":765580,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, James T. 0000-0002-7709-8590","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":204948,"corporation":false,"usgs":false,"family":"Peterson","given":"James","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":765581,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":765582,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202847,"text":"ds1112 - 2019 - Terrestrial lidar data of the February 14, 2019 Sausalito Boulevard Landslide, Sausalito, California","interactions":[],"lastModifiedDate":"2019-04-05T14:46:46","indexId":"ds1112","displayToPublicDate":"2019-04-02T08:23:34","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1112","displayTitle":"Terrestrial Lidar Data of the February 14, 2019, Sausalito Boulevard Landslide, Sausalito, California","title":"Terrestrial lidar data of the February 14, 2019 Sausalito Boulevard Landslide, Sausalito, California","docAbstract":"On February 14, 2019, just before 2:56 am local time (Pacific Standard Time), a landslide initiated from the hillslopes above the Hurricane Gulch section of the City of Sausalito, Marin County, California. The landslide, specifically classified as a debris flow, overran a road (Sausalito Boulevard) immediately below the landslide source area and impacted a residential structure that subsequently toppled downslope and collided with another residential structure. The second structure then crossed a lower road (Crescent Avenue) that runs along the base of the slope before the mixture of soil and structural debris came to rest in and near the valley axis that drains the lower area of Hurricane Gulch.
The U.S. Geological Survey responded to this event within hours of the landslide and provided situational awareness of possible secondary landslide hazards associated with the unstable slope. The USGS also rapidly mobilized its topographic surveying capabilities (specifically, GPS and terrestrial lidar devices) and collected a three-dimensional point cloud model of the landslide source area and surrounding terrain to capture the as-failed condition of the slope for use in potential future studies. This report summarizes the methods and available data collected during this response.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1112","usgsCitation":"Collins, B.D. and Corbett, S.C., 2019. Terrestrial lidar data of the February 14, 2019 Sausalito Boulevard Landslide, Sausalito, California: U.S. Geological Survey Data Series 1112, 12 p., https://doi.org/10.3133/ds1112.","productDescription":"Report: iv, 12 p.; Data Release","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106637","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":362641,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AQRCTJ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Terrestrial LIDAR Data Set of the February 14, 2019 Sausalito Boulevard Landslide, Sausalito, California"},{"id":362639,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1112/coverthb.jpg"},{"id":362640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1112/ds1112_.pdf","text":"Report","size":"34.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1112"}],"country":"United States","state":"California","city":"Sausalito","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.5074291229248,\n 37.87376937332855\n ],\n [\n -122.50828742980956,\n 37.86299605572604\n ],\n [\n -122.48854637145995,\n 37.84422368363511\n ],\n [\n -122.47670173645018,\n 37.84564702731293\n ],\n [\n -122.47756004333496,\n 37.859540129644195\n ],\n [\n -122.50288009643553,\n 37.87715688349197\n ],\n [\n -122.5074291229248,\n 37.87376937332855\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
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Menlo Park, CA 94025-3591
Earthquake swarms present a challenge for operational earthquake forecasting because they are driven primarily by transient external processes, such as fluid flow, the behavior and duration of which are difficult to predict. In this study, we develop a swarm duration model to estimate how long a swarm is likely to last based on actuarial statistics of previous swarms in a given region. We demonstrate this approach using swarms that have been identified in the Salton trough in southern California, finding that swarms last an average of
Situated in the Mississippi Alluvial Plain of the Gulf Coast Prairie Landscape Conservation Cooperative (GCP LCC), the Chitimacha Tribe is one of four federally recognized tribes in Louisiana. The Tribal seat, trust lands/ reservation, and adjacent Tribal owned lands are located near Charenton, Louisiana, totaling nearly 1,000 acres. The Chitimacha, with a population of approximately 1,400 people, are currently impacted by storm surge, which is expected to increase with climate change. The additional stress from storms will likewise increase the vulnerability to catastrophic impact in the event of a breach in the Atchafalaya Basin Spillway levee. A collaborative effort between the U.S. Geological Survey (USGS) and the Chitimacha Tribe has been initiated to provide resources and expertise to increase the Tribe’s ability to prevent, plan, and prepare for these environmental challenges. By enhancing technical skills, providing access to environmental data, and increasing awareness of environmental issues, the Chitimacha will be better prepared to plan and adapt to the environmental impacts facing their lands related to land use and climate change.
For this project, USGS researchers asked how Chitimacha Tribal Lands might be impacted by future sea level rise scenario projections. These models illustrate some flooding within the northernmost boundary of Chitimacha Tribal Lands.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191030","collaboration":"Prepared in cooperation with The Chitimacha Tribe of Louisiana; Gulf Coast Prairie Landscape Conservation Cooperative","usgsCitation":"Spear, K.A., Jones, W., Griffith, K., Tirpak, B.E., and Walden, K., 2019, Potential sea level rise on Chitimacha Tribal Lands in Louisiana: U.S. Geological Survey Open-File Report 2019–1030, 1 sheet, https://doi.org/10.3133/ofr20191030.","productDescription":"1 Sheet: 24.0 x 36.0 inches","onlineOnly":"Y","ipdsId":"IP-090045","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":502765,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_108491.htm","linkFileType":{"id":5,"text":"html"}},{"id":362387,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1030/ofr20191030.pdf","text":"Report","size":"1.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1030"},{"id":362386,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1030/coverthb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Chitimacha Tribal Lands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.5833,\n 29.8167\n ],\n [\n -91.5,\n 29.8167\n ],\n [\n -91.5,\n 29.9167\n ],\n [\n -91.5833,\n 29.9167\n ],\n [\n -91.5833,\n 29.8167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
Recently introduced unmarked spatial capture–recapture (SCR), spatial mark–resight (SMR), and 2‐flank spatial partial identity models (SPIMs) extend the domain of SCR to populations or observation systems that do not always allow for individual identity to be determined with certainty. For example, some species do not have natural marks that can reliably produce individual identities from photographs, and some methods of observation produce partial identity samples as is the case with remote cameras that sometimes produce single‐flank photographs. Unmarked SCR, SMR, and SPIM share the feature that they probabilistically resolve the uncertainty in individual identity using the spatial location where samples were collected. Spatial location is informative of individual identity in spatially structured populations because a sample is more likely to have been produced by an individual living near the trap where it was recorded than an individual living further away from the trap. Further, the level of information about individual identity that a spatial location contains is related to two key ecological concepts, population density and home range size, which we quantify using a proposed Identity Diversity Index (IDI). We show that latent and partial identity SCR models produce imprecise and biased density estimates in many high IDI scenarios when data are sparse. We then extend the unmarked SCR model to incorporate categorical, partially identifying covariates, which reduce the level of uncertainty in individual identity, increasing the reliability and precision of density estimates, and allowing reliable density estimation in scenarios with higher IDI values and with more sparse data. We illustrate the performance of this “categorical SPIM” via simulations and by applying it to a black bear data set using microsatellite loci as categorical covariates, where we reproduce the full data set estimates with only slightly less precision using fewer loci than necessary for confident individual identification. We then discuss how the categorical SPIM can be applied to other wildlife sampling scenarios such as remote camera surveys, where natural or researcher‐applied partial marks can be observed in photographs. Finally, we discuss how the categorical SPIM can be added to SMR, 2‐flank SPIM, or other latent identity SCR models.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2627","usgsCitation":"Augustine, B., Royle, J.A., Murphy, S.M., Chandler, R.B., Cox, J., and Kelly, M., 2019, Spatial capture–recapture for categorically marked populations with an application to genetic capture–recapture: Ecosphere, v. 10, no. 4, e02627, 22 p., https://doi.org/10.1002/ecs2.2627.","productDescription":"e02627, 22 p.","ipdsId":"IP-095923","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467740,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2627","text":"Publisher Index Page"},{"id":377199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Augustine, Ben C.","contributorId":237797,"corporation":false,"usgs":false,"family":"Augustine","given":"Ben C.","affiliations":[{"id":38081,"text":"Cornell Univ.","active":true,"usgs":false}],"preferred":false,"id":795329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Sean M.","contributorId":140195,"corporation":false,"usgs":false,"family":"Murphy","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":795330,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chandler, Richard B. rchandler@usgs.gov","contributorId":63524,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":795332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cox, John J.","contributorId":140196,"corporation":false,"usgs":false,"family":"Cox","given":"John J.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":795334,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelly, Marcella","contributorId":237800,"corporation":false,"usgs":false,"family":"Kelly","given":"Marcella","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":795333,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70204687,"text":"70204687 - 2019 - Quaternary eolian sediments and Carolina Bays of the U.S. Atlantic Coastal Plain province","interactions":[],"lastModifiedDate":"2019-08-08T15:01:05","indexId":"70204687","displayToPublicDate":"2019-04-01T14:57:01","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Quaternary eolian sediments and Carolina Bays of the U.S. Atlantic Coastal Plain province","docAbstract":"Under modern conditions, the Atlantic Coastal Plain province of the eastern United States is not very conducive to widespread eolian sediment mobilization because of a humid and mesothermal climate, relatively low mean surface wind velocities (~1–3 m/sec), and relatively dense vegetation. LiDAR data, however, have revealed the presence of widespread eolian dunes and sand sheets (now covered by vegetation) at many inland locations throughout the U.S. Atlantic Coastal Plain (Swezey, in press). To date, a total of 89 OSL ages ranging from ~92–5 thousand years ago (ka) have been published from these eolian sediments, and 61 of these 89 OSL ages occur within or near the interval of the last glacial maximum (LGM). \nQuaternary eolian sediments have been identified in the following four inland settings of the U.S. Atlantic Coastal Plain: (1) on interfluvial upland areas of the northern coastal plain; (2) in the Carolina Sandhills region; (3) within river valleys; and (4) adjacent to low relief elliptical depressions known as Carolina Bays. Most of these eolian sediments are composed of fine to medium quartz sand, although a substantial component of silt is present in the northern coastal plain, and a substantial component of coarse sand is present in the Carolina Sandhills region. \nThe eolian sediments in interfluvial upland areas of the northern coastal plain (Delaware, Maryland) form both sand sheets and parabolic dunes (with dune tails pointing to the northwest). These eolian sediments in the northern upland areas were probably remobilized from any loose sediments that were available in the area, and the location near the southern margin of the LGM ice sheet is similar to extensive Quaternary eolian sand and loess deposits in Europe, China, and the central United States. \nThe eolian sediments in the Carolina Sandhills region form mostly sand sheets and some linear dunes of relatively short extent. These eolian sediments are thought to have been derived from sand of the immediately underlying Cretaceous fluvial strata. \nThe eolian sediments within river valleys form parabolic dunes that are located to the east of the modern river channels. The tails of these eolian dunes within river valleys point northwest in the northern coastal plain (Delaware, Maryland) and they point west in the southern coastal plain (North Carolina, South Carolina, Georgia). These eolian sediments within river valleys are thought to have been derived from fluvial sand in the nearby river channels. \n\tThe eolian sediments associated with Carolina Bays form arcuate ridges on the east and south sides of the depressions (“bays”). Some Carolina Bays show cross-cutting relations with other Carolina Bays. Other Carolina Bays show different stratigraphic relations with respect to eolian dunes within river valleys. For example, Bear Swamp (Marion County, South Carolina) is a Carolina Bay that is inset into (i.e., younger than) eolian dunes in the valley of the Great Pee Dee River. As another example, Big Bay (Sumter County, South Carolina) is a Carolina Bay that is overlain by (i.e., older than) eolian dunes in the valley at the confluence of the Congaree and Wateree Rivers. Cores in Carolina Bays and their associated ridges reveal a few meters of sand and (or) muddy sand above an unconformity on various older fine-grained substrates that do not show signs of disturbance. Most published OSL ages from Carolina Bay sand ridges range from ~45–8 ka. Some bays have multiple sand ridges, and ridges closer to individual bays yield younger OSL ages. \nIn summary, Quaternary eolian sediments are widespread throughout the U.S. Atlantic Coastal Plain province, and most of these sediments are thought to have been mobilized within or near the interval of the LGM when conditions were much colder, drier, and windier. These eolian sediments are thus interpreted as relict features that have subsequently been stabilized and degraded by vegetation and pedoge","language":"English","publisher":"Minnesota Geological Survey","usgsCitation":"Swezey, C.S., 2019, Quaternary eolian sediments and Carolina Bays of the U.S. Atlantic Coastal Plain province, p. 88-89.","productDescription":"2 p.","startPage":"88","endPage":"89","ipdsId":"IP-105444","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":366424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366412,"type":{"id":15,"text":"Index Page"},"url":"https://conservancy.umn.edu/handle/11299/202386"}],"country":"United States","state":"North Carolina, South Carolina 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Carolina\",\"nation\":\"USA \"}}]}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":768071,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70204660,"text":"70204660 - 2019 - Individual based modelling of fish migration in a 2-D river system: Model description and case study","interactions":[],"lastModifiedDate":"2019-08-09T10:27:26","indexId":"70204660","displayToPublicDate":"2019-04-01T14:32:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Individual based modelling of fish migration in a 2-D river system: Model description and case study","docAbstract":"Context: Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. These stressors complicate the prioritization of proposed management actions intended to improve conditions for migratory fishes including anadromous salmon and trout.\n\nObjectives: We describe a multi-scale hybrid mechanistic–probabilistic simulation model linking migration corridor conditions to fish fitness outcomes. We demonstrate the model’s utility using a case study of salmon and steelhead adults in the Columbia River migration corridor exposed to spatially- and temporally-varying stressors.\n\nMethods: The migration corridor simulation model is based on a behavioral decision tree that governs individual interactions with the environment, and an energetic submodel that estimates the hourly costs of migration. Emergent properties of the migration corridor simulation model include passage time, energy use, and survival.\n\nResults: We observed that the simulated fish’s initial energy density, the migration corridor temperatures they experienced, and their history of behavioral thermoregulation were the primary determinants of their fitness outcomes. Insights gained from use of the model might be exploited to identify management interventions that increase successful migration outcomes.\n\nConclusions: This paper describes new methods that extend the suite of tools available to aquatic biologists and conservation practitioners. We have developed a 2-dimensional spatially-explicit behavioral and physiological model and illustrated how it can be used to simulate fish migration within a river system. Our model can be used to evaluate trade-offs between behavioral thermoregulation and fish fitness at population scales.","language":"English","publisher":"Springer","doi":"10.1007/s10980-019-00804-z","usgsCitation":"Snyder, M.N., Schumaker, N.H., Ebersole, J., Dunham, J.B., Comeleo, R., Keefer, M., Leinenbach, P., Brookes, A., Cope, B., Wu, J., Palmer, J., and Keenan, D., 2019, Individual based modelling of fish migration in a 2-D river system: Model description and case study: Landscape Ecology, v. 34, no. 4, p. 737-754, https://doi.org/10.1007/s10980-019-00804-z.","productDescription":"18 p.","startPage":"737","endPage":"754","ipdsId":"IP-106277","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":467741,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7788051","text":"External Repository"},{"id":366419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Snyder, Marcia N. 0000-0003-2202-2668","orcid":"https://orcid.org/0000-0003-2202-2668","contributorId":217972,"corporation":false,"usgs":false,"family":"Snyder","given":"Marcia","email":"","middleInitial":"N.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":767950,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schumaker, Nathan H.","contributorId":199151,"corporation":false,"usgs":false,"family":"Schumaker","given":"Nathan","email":"","middleInitial":"H.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":767951,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebersole, Joseph E","contributorId":217973,"corporation":false,"usgs":false,"family":"Ebersole","given":"Joseph E","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":767952,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason B. 0000-0002-6268-0633 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":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":767953,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Comeleo, Randy","contributorId":217974,"corporation":false,"usgs":false,"family":"Comeleo","given":"Randy","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":767954,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keefer, Matthew","contributorId":217975,"corporation":false,"usgs":false,"family":"Keefer","given":"Matthew","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":767955,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leinenbach, P.T.","contributorId":217976,"corporation":false,"usgs":false,"family":"Leinenbach","given":"P.T.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":767956,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brookes, Allen","contributorId":217977,"corporation":false,"usgs":false,"family":"Brookes","given":"Allen","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":767957,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cope, Ben","contributorId":217978,"corporation":false,"usgs":false,"family":"Cope","given":"Ben","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":767958,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wu, Jennifer","contributorId":217979,"corporation":false,"usgs":false,"family":"Wu","given":"Jennifer","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":767959,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Palmer, John","contributorId":217980,"corporation":false,"usgs":false,"family":"Palmer","given":"John","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":767960,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Keenan, Druscilla","contributorId":217981,"corporation":false,"usgs":false,"family":"Keenan","given":"Druscilla","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":767961,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70203084,"text":"70203084 - 2019 - Early career climate communications and networking","interactions":[],"lastModifiedDate":"2020-07-27T19:03:54.947508","indexId":"70203084","displayToPublicDate":"2019-04-01T14:07:29","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Early career climate communications and networking","docAbstract":"The Department of the Interior and the U.S. Geological Survey have made it a priority to train the next generation of scientists and resource managers. The Climate Adaptation Science Centers (CSC) and consortium institutions are working to contribute to this initiative by supporting and building a network of students across the U.S. interested in the climate sciences and climate adaptation. The purpose of this project was to support the development of a national early career communication platform to facilitate and increase information sharing and networking across the CASCs and consortium institutions. This was accomplished by working with the Early Career Climate Forum (ECCF), a CASC-supported science network dedicated to improving research practice through communication and collaboration. Project goals included the redesign and expansion of a pilot website that was originally developed by early career scientists in attendance of the 2012 Northwest Climate Science Bootcamp as well as adding services such as a regular blog, email list-serve, database of members, training modules for CASC retreats and bootcamps, all directed towards the advancement of early career scientists in the field of climate change science and adaptation.","language":"English","usgsCitation":"Ezra Markowitz, and Staudinger, M., 2019, Early career climate communications and networking, 19 p.","productDescription":"19 p.","ipdsId":"IP-107130","costCenters":[{"id":41705,"text":"Northeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":363907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363906,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://necsc.umass.edu/sites/default/files/Final%20Report%20-Early%20Career%20Climate%20Communications%20and%20Networking.pdf"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ezra Markowitz","contributorId":214892,"corporation":false,"usgs":false,"family":"Ezra Markowitz","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":761096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Staudinger, Michelle D. 0000-0002-4535-2005","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":207908,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle D.","affiliations":[{"id":484,"text":"Northwest Climate Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":761095,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203376,"text":"70203376 - 2019 - Energetic costs of aquatic locomotion in a subadult polar bear","interactions":[],"lastModifiedDate":"2019-05-09T13:53:06","indexId":"70203376","displayToPublicDate":"2019-04-01T13:48:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2671,"text":"Marine Mammal Science","active":true,"publicationSubtype":{"id":10}},"title":"Energetic costs of aquatic locomotion in a subadult polar bear","docAbstract":"Most marine mammals rely on swimming as their primary form of locomotion. These animals have evolved specialized morphologies, physiologies, and behaviors that have enabled them to efficiently move through an aquatic environment (Williams 1999). Such adaptations include body streamlining, modified plantar surfaces for propulsion, and abilities to remain submerged for extended durations (Williams 1989). As a result of these adaptations, many marine mammal species exhibit minimal increases in metabolism at routine swim speeds relative to resting rates (Williams et al. 1992, 2017; Yazdi et al. 1999). Contrary to most marine mammals, polar bears (Ursus maritimus) rely on walking as their primary form of locomotion. As a consequence, they exhibit little evidence of body streamlining or abilities to remain submerged for extended durations. The longest dive recorded for a polar bear is 3 min and 10 s (Stirling and van Meurs 2015), a relatively brief period compared to other marine mammals (Ponganis 2015). Nevertheless, polar bears do exhibit large forepaws (DeMaster and Stirling 1981), lower and flatter heads (Slater et al. 2010), and more dense forelimb bones (Wall 1983) relative to other bear species, potentially as adaptations for swimming. Polar bears further exhibit some distinct physiological and behavioral adaptations from other bear species likely as a consequence of their marine existence (Pagano et al. 2018a).
","language":"English","publisher":"Society for Marine Mammalogy","doi":"10.1111/mms.12556","usgsCitation":"Pagano, A.M., Cutting, A., Nicassio-Hiskey, N., Hash, A., and Williams, T.M., 2019, Energetic costs of aquatic locomotion in a subadult polar bear: Marine Mammal Science, v. 35, no. 2, p. 649-659, https://doi.org/10.1111/mms.12556.","productDescription":"11 p.","startPage":"649","endPage":"659","ipdsId":"IP-098029","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":437516,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98IQWT4","text":"USGS data release","linkHelpText":"Measures of oxygen consumption and stroke frequency of a captive subadult polar bear (Ursus maritimus) while resting in water and swimming and diving in a metabolic water flume, Oregon Zoo, 2017"},{"id":363649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"35","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":762382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cutting, Amy","contributorId":200751,"corporation":false,"usgs":false,"family":"Cutting","given":"Amy","email":"","affiliations":[],"preferred":false,"id":762383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nicassio-Hiskey, Nicole","contributorId":150616,"corporation":false,"usgs":false,"family":"Nicassio-Hiskey","given":"Nicole","email":"","affiliations":[{"id":18050,"text":"Oregon Zoo","active":true,"usgs":false}],"preferred":false,"id":762384,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hash, Amy","contributorId":200755,"corporation":false,"usgs":false,"family":"Hash","given":"Amy","email":"","affiliations":[],"preferred":false,"id":762385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Terrie M.","contributorId":191735,"corporation":false,"usgs":false,"family":"Williams","given":"Terrie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":762386,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203001,"text":"70203001 - 2019 - Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data","interactions":[],"lastModifiedDate":"2019-04-11T13:46:12","indexId":"70203001","displayToPublicDate":"2019-04-01T13:45:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data","docAbstract":"Fine scale maps of soil properties enable efficient land management and inform earth system models. Recent efforts to create soil property maps from field observations tend to use similar tree-based machine learning interpolation approaches, but often deal with depth of predictions, validation, and uncertainty differently. One of the main differences in approaches is whether to model individual depths of interest separately as ‘2D’ models, or to create models that incorporate depth as a predictor variable creating a ‘3D’ model that can make pre-dictions for all depths. It is unclear how choice of 2D or 3D approach influences model accuracy and uncertainty due to lack of direct comparison and inconsistent presentation of results in past studies. This study compares 2D and 3D methods for mapping soil electrical conductivity (salinity), pH, sum of fine and very fine sands, and organic carbon at 30 m resolution for the upper 432,000 km 2 of the Colorado River Watershed of the United States of America. A new, simple, model-agnostic relative prediction interval (RPI) approach to report un-certainty is presented that scales prediction interval width to the 95% interquantile width of the original training sample distribution. The RPI approach enables direct comparison of uncertainty between properties and depths and is easily interpretable by end users. Results indicate that 3D mapping of soil properties with strong variation with depth can result in substantial areas with much higher uncertainty that coincide with unrealistic predictions relative to 2D models, even though 3D models had slightly better global cross-validation scores. Maps and global model summaries of RPI proved helpful in identifying these issues with 3D models. These results suggest that the use of RPI or similar approaches to evaluate models can identify accuracy problems not evident in global va-lidation diagnostics.","language":"English","publisher":"ELsevier","doi":"10.1016/j.geoderma.2019.03.037","usgsCitation":"Nauman, T., and Duniway, M.C., 2019, Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data: Geoderma, v. 347, p. 170-184, https://doi.org/10.1016/j.geoderma.2019.03.037.","productDescription":"15 p.","startPage":"170","endPage":"184","ipdsId":"IP-102589","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":467743,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geoderma.2019.03.037","text":"Publisher Index Page"},{"id":437517,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YBAKC2","text":"USGS data release","linkHelpText":"Predictive maps of 2D and 3D surface soil properties and associated uncertainty for the Upper Colorado River Basin, USA"},{"id":362917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"347","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nauman, Travis","contributorId":214769,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":760737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":760738,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202936,"text":"70202936 - 2019 - Using the value of information to improve conservation decision making","interactions":[],"lastModifiedDate":"2019-04-08T15:25:35","indexId":"70202936","displayToPublicDate":"2019-04-01T13:41:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1023,"text":"Biological Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Using the value of information to improve conservation decision making","docAbstract":"Conservation decisions are challenging, not only because they often involve difficult conflicts among outcomes that people value, but because our understanding of the natural world and our effects on it is fraught with uncertainty. Value of Information (VoI) methods provide an approach for understanding and managing uncertainty from the standpoint of the decision maker. These methods are commonly used in other fields (e.g., economics, public health) and are increasingly used in biodiversity conservation. This decision analytical approach can identify the best management alternative to select where the effectiveness of interventions is uncertain, and can help to decide when to act and when to delay action until after further research. We review the use of VoI in the environmental domain, reflect on the need for greater uptake of VoI, particularly for strategic conservation planning, and suggest promising areas for new research. We also suggest common reporting standards as a means of increasing the leverage of this powerful tool.\n\nThe environmental science, ecology and biodiversity categories of the Web of Knowledge were searched using the terms ‘Value of Information,’ ‘Expected Value of Perfect Information,’ and the abbreviation ‘EVPI.’ Google Scholar was searched with the same terms, and additionally the terms decision and biology, biodiversity conservation, fish, or ecology. We identified 1225 papers from these searches. Included studies were limited to those that show an application of VoI in biodiversity conservation rather than simply describing the method. All examples of use of VOI were summarised regarding the application of VoI, the management objectives, the uncertainties, models used, how the objectives were measured, and the type of VoI.\n\nWhile the use of VoI appears to be on the increase in biodiversity conservation, the reporting of results is highly variable, which can make it difficult to understand the decision context and which uncertainties were considered. Moreover, it was unclear if, and how, the papers informed management and policy interventions, which is why we suggest a range of reporting standards that would aid the use of VoI.\n\nThe use of VoI in conservation settings is at an early stage. There are opportunities for broader applications, not only for species-focussed management problems, but also for setting local or global research priorities for biodiversity conservation, making funding decisions, or designing or improving protected area networks and management. The long-term benefits of applying VoI methods to biodiversity conservation include a more structured and decision-focused allocation of resources to research.","language":"English","publisher":"Wiley","doi":"10.1111/brv.12471","usgsCitation":"Bolam, F.C., Grainger, M.J., Mengerson, K.L., Stewart, G.B., Sutherland, W.J., Runge, M.C., and McGowan, P., 2019, Using the value of information to improve conservation decision making: Biological Reviews, v. 94, no. 2, p. 629-647, https://doi.org/10.1111/brv.12471.","productDescription":"19 p.","startPage":"629","endPage":"647","ipdsId":"IP-092321","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467744,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.repository.cam.ac.uk/handle/1810/286798","text":"External Repository"},{"id":362842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Bolam, Friederike C.","contributorId":214679,"corporation":false,"usgs":false,"family":"Bolam","given":"Friederike","email":"","middleInitial":"C.","affiliations":[{"id":33636,"text":"Newcastle University","active":true,"usgs":false}],"preferred":false,"id":760545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grainger, Matthew J.","contributorId":214680,"corporation":false,"usgs":false,"family":"Grainger","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":33636,"text":"Newcastle University","active":true,"usgs":false}],"preferred":false,"id":760546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mengerson, Kerrie L.","contributorId":214681,"corporation":false,"usgs":false,"family":"Mengerson","given":"Kerrie","email":"","middleInitial":"L.","affiliations":[{"id":37600,"text":"Queensland University of Technology","active":true,"usgs":false}],"preferred":false,"id":760547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stewart, Gavin B.","contributorId":214682,"corporation":false,"usgs":false,"family":"Stewart","given":"Gavin","email":"","middleInitial":"B.","affiliations":[{"id":33636,"text":"Newcastle University","active":true,"usgs":false}],"preferred":false,"id":760548,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sutherland, William J.","contributorId":204319,"corporation":false,"usgs":false,"family":"Sutherland","given":"William","email":"","middleInitial":"J.","affiliations":[{"id":36918,"text":"Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge CB2 3QZ, UK","active":true,"usgs":false}],"preferred":false,"id":760549,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":760544,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGowan, Philip J. K.","contributorId":214683,"corporation":false,"usgs":false,"family":"McGowan","given":"Philip J. K.","affiliations":[{"id":33636,"text":"Newcastle University","active":true,"usgs":false}],"preferred":false,"id":760550,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203428,"text":"70203428 - 2019 - Offshore landslide hazard curves from mapped landslide size distributions","interactions":[],"lastModifiedDate":"2019-06-18T12:05:49","indexId":"70203428","displayToPublicDate":"2019-04-01T12:06:16","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Offshore landslide hazard curves from mapped landslide size distributions","docAbstract":"We present a method to calculate landslide hazard curves along offshore margins based on size distributions of submarine landslides. The method analyzes ten different continental margins, that were mapped by high-resolution multibeam sonar with landslide scar areas measured by a consistent GIS procedure. Statistical tests of several different probability distribution models indicate that the lognormal model is most appropriate for these siliciclastic environments, consistent with an earlier study of the U.S. Atlantic margin [Chaytor et al., 2009]. Parameter estimation is performed using the maximum likelihood technique and confidence intervals are determined using likelihood profiles. Pairwise comparison of size distributions for the ten margins indicates that the U.S. Atlantic and Queen Charlotte margins are different than most other margins. These margins represent end members, with the U.S. Atlantic margin having the highest mean scar area and the Queen Charlotte margin, the lowest. We demonstrate that empirical, offshore landslide hazard curves can be developed from the landslide size distributions, if the duration of mapped landslide activity is known. This study indicates that the shape parameter of the size distribution is similar among all ten margins and thus the shape of the hazard curves is also similar. Significant differences in hazard curves among the margins are therefore related to differences in mean sizes and, potentially, differences in the duration of landslide activity.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JB017236","usgsCitation":"Geist, E.L., and ten Brink, U., 2019, Offshore landslide hazard curves from mapped landslide size distributions: Journal of Geophysical Research B: Solid Earth, v. 124, no. 4, p. 3320-3334, https://doi.org/10.1029/2018JB017236.","productDescription":"15 p.","startPage":"3320","endPage":"3334","ipdsId":"IP-103389","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460421,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/24319","text":"External Repository"},{"id":363766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":762670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":762671,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}