Wetlands have experienced dramatic losses in extent around the world, disrupting ecosystem function, habitat, and biodiversity. In Florida’s Greater Everglades, a massive restoration effort costing billions of dollars and spanning multiple decades is underway. As Everglades restoration is implemented in incremental projects, scientists and planners monitor the outcomes of projects. In this study, we evaluated the progress of a restoration project in the southwestern Everglades. We aimed to determine whether the presence and density of small mammals differed between areas with hydrologic restoration of the ecosystem and areas without restoration. Our three focal species were: marsh rice rat (Oryzomys palustris), hispid cotton rat (Sigmodon hispidus), and cotton mouse (Peromyscus gossypinus). Using spatially explicit capture‐recapture models, we found greater densities of cotton mouse in restored habitat and lower densities of hispid cotton rat in sites with higher water levels. Additionally, we found an increase in the presence of the marsh rice rat in restored areas compared to unrestored, but captures were too low to reliably assess significance. Our study provides evidence that ongoing restoration in the southwestern Everglades is already impacting the small mammal community.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13332","usgsCitation":"Romanach, S., D’Acunto, L., Chapman, J., and Hanson, M., 2021, Small mammal responses to wetland restoration in the Greater Everglades ecosystem: Restoration Ecology, v. 29, no. 3, e13332, 9 p., https://doi.org/10.1111/rec.13332.","productDescription":"e13332, 9 p.","ipdsId":"IP-114410","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":454216,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.13332","text":"Publisher Index Page"},{"id":436633,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BWA7RD","text":"USGS data release","linkHelpText":"Small mammal captures at the Picayune Strand State Forest, October 2014 - April 2016"},{"id":380947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.97448730468749,\n 25.035838555635017\n ],\n [\n -79.903564453125,\n 25.035838555635017\n ],\n [\n -79.903564453125,\n 26.59343927024179\n ],\n [\n -81.97448730468749,\n 26.59343927024179\n ],\n [\n -81.97448730468749,\n 25.035838555635017\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":220761,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chapman, Julia","contributorId":245353,"corporation":false,"usgs":false,"family":"Chapman","given":"Julia","affiliations":[],"preferred":false,"id":806011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Matthew R 0000-0002-2859-3878","orcid":"https://orcid.org/0000-0002-2859-3878","contributorId":245354,"corporation":false,"usgs":false,"family":"Hanson","given":"Matthew R","affiliations":[],"preferred":false,"id":806012,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216934,"text":"70216934 - 2021 - Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model","interactions":[],"lastModifiedDate":"2021-03-05T21:07:22.044536","indexId":"70216934","displayToPublicDate":"2020-11-21T12:54:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7443,"text":"Quarterly Journal of the Royal Meteorological Society","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model","docAbstract":"The importance of wind energy as an alternative energy source has increased over the latest years with more focus on offshore winds. A good estimation of the offshore winds is thus of major importance for this industry. Up to now the effect of the wind–wave (mis)alignment has not yet been taken into account in coupled atmosphere–wave models to study the vertical wind profile and power production estimations of offshore wind farms. In this study the roughness length parametrization of Drennan et al. in 2003, and its extension addressing the wind–wave (mis)alignment proposed by Porchetta et al. in 2019, are investigated in the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. This study shows that the yearly mean wind estimation at hub height (100 m) is improved by the roughness length parametrization of Porchetta et al. compared to Drennan. This is mainly due to the increased roughness of the former parametrization compare to the latter, even in aligned wind–wave conditions. This difference in roughness is caused by the dataset used to obtain the constants, deep‐water conditions versus mixed offshore conditions. Moreover, the roughness length parametrization of Porchetta et al. performs better in two of three alignment categories. Furthermore, similar model performances are obtained if we exclude the wind directions from the wind shadow zone of the measurement mast or the wind directions from the recently built Alpha Ventus wind farm, which is in close vicinity of the measurement mast. Investigating different wind conditions shows that the new roughness length parametrization of Porchetta et al. performs best for both offshore and onshore winds. Additionally, we show that the coupled model estimations of the vertical wind are only slightly affected by significant wave height estimations. Similar model performances for different accuracies of significant wave height estimations are presented. One exception is the perpendicular alignment category where the new roughness length of Porchetta et al. outperforms the roughness length of Drennan when investigating the wind estimations related to significant wave heights with a higher accuracy. The roughness length parametrization of Porchetta et al. reduced the power production overestimation of the coupled model from 5.7 to 2.8%. We also show that the standalone atmospheric model including the roughness length of Charnock in 1955 has a degraded performance compared to the coupled model including the roughness length parametrization of Porchetta et al. for yearly average wind profiles.
","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/qj.3948","usgsCitation":"Porchetta, S., Temel, O., Warner, J., Munoz-Esparza, J., Monbaliu, J., van Beeck, J., and van Lipzig, N., 2021, Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model: Quarterly Journal of the Royal Meteorological Society, v. 147, no. 735, p. 825-846, https://doi.org/10.1002/qj.3948.","productDescription":"22 p.","startPage":"825","endPage":"846","ipdsId":"IP-117950","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454221,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lirias.kuleuven.be/bitstream/123456789/685815/2/COAWST_QJRMetS_rkul.docx","text":"External Repository"},{"id":381447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","issue":"735","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Porchetta, Sara","contributorId":245775,"corporation":false,"usgs":false,"family":"Porchetta","given":"Sara","email":"","affiliations":[{"id":49315,"text":"KU Leuven, Department Earth and Environmental Sciences, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Temel, O.","contributorId":245776,"corporation":false,"usgs":false,"family":"Temel","given":"O.","email":"","affiliations":[{"id":49316,"text":"Royal Observatory of Belgium, Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":807017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munoz-Esparza, J.C.","contributorId":245777,"corporation":false,"usgs":false,"family":"Munoz-Esparza","given":"J.C.","email":"","affiliations":[{"id":16785,"text":"National Center for Atmospheric Research, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":807019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Monbaliu, J","contributorId":245778,"corporation":false,"usgs":false,"family":"Monbaliu","given":"J","email":"","affiliations":[{"id":49317,"text":"KULeuven, Department of Civil Engineering, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Beeck, J.","contributorId":245779,"corporation":false,"usgs":false,"family":"van Beeck","given":"J.","email":"","affiliations":[{"id":49319,"text":"KULeuven, Department Earth and Environmental Sciences, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van Lipzig, N.","contributorId":245780,"corporation":false,"usgs":false,"family":"van Lipzig","given":"N.","email":"","affiliations":[{"id":49321,"text":"von Karman Institute for Fluid Dynamics, Sint-Genesius-Rode, Belgium","active":true,"usgs":false}],"preferred":false,"id":807022,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219218,"text":"70219218 - 2021 - Variable seepage meter efficiency in high-permeability settings","interactions":[],"lastModifiedDate":"2021-04-01T11:25:55.835244","indexId":"70219218","displayToPublicDate":"2020-11-21T06:47:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Variable seepage meter efficiency in high-permeability settings","docAbstract":"The efficiency of seepage meters, long considered a fixed property associated with the meter design, is not constant in highly permeable sediments. Instead, efficiency varies substantially with seepage bag fullness, duration of bag attachment, depth of meter insertion into the sediments, and seepage velocity. Tests conducted in a seepage test tank filled with isotropic sand with a hydraulic conductivity of about 60 m/d indicate that seepage meter efficiency varies widely and decreases unpredictably when the volume of the seepage bag is greater than about 65 to 70 percent full or less than about 15 to 20 percent full. Seepage generally decreases with duration of bag attachment even when operated in the mid-range of bag fullness. Stopping flow through the seepage meter during bag attachment or removal also results in a decrease in meter efficiency. Numerical modeling indicates efficiency is inversely related to hydraulic conductivity in highly permeable sediments. An efficiency close to 1 for a meter installed in sediment with a hydraulic conductivity of 1 m/d decreases to about 60 and then 10 percent when hydraulic conductivity is increased to 10 and 100 m/d, respectively. These large efficiency reductions apply only to high-permeability settings, such as wave- or tidally washed coarse sand or gravel, or fluvial settings with an actively mobile sand or gravel bed, where low resistance to flow through the porous media allows bypass flow around the seepage cylinder to readily occur. In more typical settings, much greater resistance to bypass flow suppresses small changes in meter resistance during inflation or deflation of seepage bags.
","language":"English","publisher":"MPDI","doi":"10.3390/w12113267","usgsCitation":"Rosenberry, D.O., Nieto-Lopez, J.M., Webb, R.M., and Muller, S., 2021, Variable seepage meter efficiency in high-permeability settings: Water, v. 12, no. 11, 3267, 22 p., https://doi.org/10.3390/w12113267.","productDescription":"3267, 22 p.","ipdsId":"IP-119819","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454229,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12113267","text":"Publisher Index Page"},{"id":436637,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93N8B2N","text":"USGS data release","linkHelpText":"Webb and Rosenberry, 2020, MODFLOW 2005 and MODPATH 5 model data sets used to evaluate seepage-meter efficiency in high-permeability settings"},{"id":436636,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93N8B2N","text":"USGS data release","linkHelpText":"Webb and Rosenberry, 2020, MODFLOW 2005 and MODPATH 5 model data sets used to evaluate seepage-meter efficiency in high-permeability settings"},{"id":436635,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SO2FVM","text":"USGS data release","linkHelpText":"Seepage meter efficiency in highly permeable settings source data (2020)"},{"id":436634,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SO2FVM","text":"USGS data release","linkHelpText":"Seepage meter efficiency in highly permeable settings source data (2020)"},{"id":384775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":813261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nieto-Lopez, Jose M 0000-0002-2596-6368","orcid":"https://orcid.org/0000-0002-2596-6368","contributorId":256817,"corporation":false,"usgs":false,"family":"Nieto-Lopez","given":"Jose","email":"","middleInitial":"M","affiliations":[{"id":51863,"text":"University of Malaga","active":true,"usgs":false}],"preferred":false,"id":813262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muller, Sascha","contributorId":256818,"corporation":false,"usgs":false,"family":"Muller","given":"Sascha","email":"","affiliations":[{"id":12672,"text":"University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":813264,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216564,"text":"70216564 - 2021 - Systematic characterization of morphotectonic variability along the Cascadia convergent margin: Implications for shallow megathrust behavior and tsunami hazards","interactions":[],"lastModifiedDate":"2021-02-04T00:04:42.827309","indexId":"70216564","displayToPublicDate":"2020-11-20T09:17:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Systematic characterization of morphotectonic variability along the Cascadia convergent margin: Implications for shallow megathrust behavior and tsunami hazards","docAbstract":"Studies of recent destructive megathrust earthquakes and tsunamis along subduction margins in Japan, Sumatra, and Chile have linked forearc morphology and structure to megathrust behavior. This connection is based on the idea that spatial variations in the frictional behavior of the megathrust influence the tectono-morphological evolution of the upper plate. Here we present a comprehensive examination of the tectonic geomorphology, outer wedge taper, and structural vergence along the marine forearc of the Cascadia subduction zone (offshore northwestern North America). The goal is to better understand geologic controls on outer wedge strength and segmentation at spatial scales equivalent to rupture lengths of large earthquakes (≥M 6.7), and to examine potential linkages with shallow megathrust behavior.
We use cross-margin profiles, spaced 25 km apart, to characterize along-strike variation in outer wedge width, steepness, and structural vergence (measured between the toe and the outer arc high). The width of the outer wedge varies between 17 and 93 km, and the steepness ranges from 0.9° to 6.5°. Hierarchical cluster analysis of outer wedge width and steepness reveals four distinct regions that also display unique patterns of structural vergence and shape of the wedge: Vancouver Island, British Columbia, Canada (average width, linear wedge, seaward and mixed vergence); Washington, USA (higher width, concave wedge, landward and mixed vergence); northern and central Oregon, USA (average width, linear and convex wedge, mixed and seaward vergence); and southern Oregon and northern California, USA (lower width, convex wedge, seaward and mixed vergence). Variability in outer wedge morphology and structure is broadly associated with along-strike megathrust segmentation inferred from differences in oceanic asthenospheric velocities, patterns of episodic tremor and slow slip, GPS models of plate locking, and the distribution of seismicity near the plate interface. In more detail, our results appear to delineate the extent, geometry, and lithology of dynamic and static backstops along the margin. Varying backstop configurations along the Cascadia margin are interpreted to represent material-strength contrasts within the wedge that appear to regulate the along- and across-strike taper and structural vergence in the outer wedge. We argue that the morphotectonic variability in the outer wedge may reflect spatial variations in shallow megathrust behavior occurring over roughly the last few million years. Comparing outer wedge taper along the Cascadia margin to a global compilation suggests that observations in the global catalog are not accurately representing the range of heterogeneity within individual margins and highlights the need for detailed margin-wide morphotectonic analyses of subduction zones worldwide.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02178.1","usgsCitation":"Watt, J., and Brothers, D.S., 2021, Systematic characterization of morphotectonic variability along the Cascadia convergent margin: Implications for shallow megathrust behavior and tsunami hazards: Geosphere, v. 17, no. 1, p. 95-117, https://doi.org/10.1130/GES02178.1.","productDescription":"19 p.","startPage":"95","endPage":"117","ipdsId":"IP-109931","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454235,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02178.1","text":"Publisher Index Page"},{"id":380781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.01367187499999,\n 40.195659093364654\n ],\n [\n -123.50830078125,\n 41.623655390686395\n ],\n [\n -123.662109375,\n 44.6061127451739\n ],\n [\n -123.662109375,\n 47.100044694025215\n ],\n [\n -123.11279296875001,\n 48.69096039092549\n ],\n [\n -128.1005859375,\n 51.248163159055906\n ],\n [\n -128.84765625,\n 50.999928855859636\n ],\n [\n -127.46337890625001,\n 40.97989806962013\n ],\n [\n -126.03515625,\n 39.605688178320804\n ],\n [\n -124.01367187499999,\n 40.195659093364654\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Watt, Janet 0000-0002-4759-3814","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":221271,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. 0000-0001-7702-157X dbrothers@usgs.gov","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":167089,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","email":"dbrothers@usgs.gov","middleInitial":"S.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805622,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227051,"text":"70227051 - 2021 - Suspended-sediment Flux in the San Francisco Estuary; Part II: the Impact of the 2013–2016 California Drought and Controls on Sediment Flux","interactions":[],"lastModifiedDate":"2021-12-28T14:48:59.650241","indexId":"70227051","displayToPublicDate":"2020-11-20T08:46:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Suspended-sediment Flux in the San Francisco Estuary; Part II: the Impact of the 2013–2016 California Drought and Controls on Sediment Flux","docAbstract":"Recent modeling has demonstrated that sediment supply is one of the primary environmental variables that will determine the sustainability of San Francisco Estuary tidal marshes over the next century as sea level rises. Therefore, understanding the environmental controls on sediment flux within the San Francisco Estuary is crucial for optimal planning and management of tidal marsh restoration. Herein, we present suspended-sediment flux estimates from water year (WY) 2009–2016 from the San Francisco Estuary to investigate the environmental controls and impact of the record 2013–2016 California drought. During the recent drought, sediment flux into Lower South Bay, the southernmost subembayment of the San Francisco Estuary, increased by 345% from 114 kt/year from WY 2009 to 2011 to 508 kt/year from WY 2014 to 2016, while local tributary sediment flux declined from 209 to 51 kt/year. Total annual sediment flux from WY 2009 to 2011 and 2014 to 2016 can be predicted by total annual freshwater inflow from the Sacramento-San Joaquin Delta (R2 = 0.83, p < 0.01), the primary source of freshwater input into the San Francisco Estuary. The volume of freshwater inflow from the Sacramento-San Joaquin Delta is hypothesized to affect shoal-to-channel density gradients that affect sediment flux from broad, typically more saline and turbid shoals, to the main tidal-channel seaward of Lower South Bay. During the drought, freshwater inflow from the Sacramento-San Joaquin Delta decreased, and replacement of typically more saline shoal water was reduced. As a result, landward-increasing cross-channel density gradients enhanced shoal-to-channel advective flux that increased sediment available for tidal dispersion and drove an increase in net-landward sediment flux into Lower South Bay.
Geologists and petroleum engineers have struggled to identify the mechanisms that drive productivity in horizontal hydraulically fractured oil wells. The machine learning algorithms of Random Forest (RF), gradient boosting trees (GBT) and extreme gradient boosting (XGBoost) were applied to a dataset containing 7311 horizontal hydraulically fractured wells drilled into the middle member of the Bakken Formation from 2010 through 2017. The initial goal is to use these data‐driven machine learning algorithms to identify the most important explanatory predictors of well productivity within nine subareas and the composite area. Predictor variables representing initial gas production, the initial 180‐day water cut, and vertical depth vary spatially and are identified with geologically favorable areas. Well‐completion predictors include the well lateral length, number of fracture stages, volume of proppant per stage, and the volume of injected fluids per stage. The performance of methods is compared based on a common test sample. The analysis then examines the comparative predictive performance of the three algorithms for 1330 wells that had initiated production after the initial 7311 well sample had been producing. The computations of predictor importance identified the initial 180‐day water cut and the 30‐day initial gas production predictors as having a dominant influence in most subareas and for the composite area. The relative importance of well completion predictor variables, that is, the number of fracture stages per well, volume of injected proppant per stage, volume of injected fluids per stage, and lateral length, varied considerably across the subareas. For the common test or holdout sample, the models calibrated with the XGBoost algorithm had superior predictive power. The predictive power of all the algorithms trained on the data from the original sample suffered some loss when tested with a sample of wells that had started production after the end of that period. Implications of the empirical findings and strategies to mitigate loss of predictive power are discussed in the concluding section.
The U.S. Department of the Interior recently included uranium (U) on a list of mineral commodities that are considered critical to economic and national security. The uses of U for commercial and residential energy production, defense applications, medical device technologies, and energy generation for space vehicles and satellites are known, but the environmental impacts of uranium extraction are not always well quantified. We conducted a screening-level ecological risk analysis based on exposure to mining-related elements via diets and incidental soil ingestion for terrestrial biota to provide context to chemical characterization and exposures at breccia pipe U mines in northern Arizona. Relative risks, calculated as hazard quotients (HQs), were generally low for all biological receptor models. Our models screened for risk to omnivores and insectivores (HQs>1) but not herbivores and carnivores. Uranium was not the driver of ecological risk; arsenic, cadmium, copper, and zinc were of concern for biota consuming ground-dwelling invertebrates. Invertebrate species composition should be considered when applying these models to other mining locations or future sampling at the breccia pipe mine sites. Dietary concentration thresholds (DCTs) were also calculated to understand food concentrations that may lead to ecological risk. The DCTs indicated that critical concentrations were not approached in our model scenarios, as evident in the very low HQs for most models. The DCTs may be used by natural resource and land managers as well as mine operators to screen or monitor for potential risk to terrestrial receptors as mine sites are developed and remediated in the future.
1. The effects of changing climate and disturbance on mountain forest carbon stocks vary with tree species distributions and over elevational gradients. Warming can increase carbon uptake by stimulating productivity at high elevations but also enhance carbon release by increasing respiration and the frequency, intensity, and size of wildfires.
2. To understand the consequences of climate change for temperate mountain forests, we simulated interactions among climate, wildfire, tree species, and their combined effects on regional carbon stocks in forests of the Greater Yellowstone Ecosystem, USA with the LANDIS‐II landscape change model. Simulations used historical climate and future potential climate represented by downscaled projections from five general circulation models (GCMs) that bracket the range of variability under the representative concentration pathway (RCP) 8.5 emissions scenario.
3. Total ecosystem carbon increased by 67% through 2100 in simulations with historical climate, and by 38 – 69% with GCM climate. Differences in carbon uptake among GCMs resulted primarily from variation in area burned, not productivity. Warming increased productivity by extending the growing season, especially near upper treeline, but did not offset biomass losses to fire. By 2100, simulated area burned increased by 27 – 215% under GCM climate, with the largest increases after 2050. With warming >3 °C in mean annual temperature, the increased frequency of large fires reduced live carbon stocks by 4 – 36% relative to the control, historical climate scenario. However, relative losses in total carbon were delayed under GCMs with large increases in summer precipitation and buffered by carbon retained in soils and the wood of fire‐killed trees. Increasing fire size limited seed dispersal, and reductions in soil moisture limited seedling establishment; both effects will likely constrain long‐term forest regeneration and carbon uptake.
4. Synthesis.Forests in the GYE can maintain a carbon sink through the mid‐century in a warming climate but continued warming may cause the loss of forest area, live aboveground biomass, and ultimately, ecosystem carbon. Future changes in carbon stocks in similar forests throughout western North America will depend on regional thresholds for extensive wildfire and forest regeneration and therefore, changes may occur earlier in drier regions.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.13559","usgsCitation":"Henne, P., Hawbaker, T., Scheller, R.M., Zhao, F.S., He, H.S., Xu, W., and Zhu, Z., 2021, Increased burning in a warming climate reduces carbon uptake in the Greater Yellowstone Ecosystem despite productivity gains: Journal of Ecology, v. 109, no. 3801, p. 1148-1169, https://doi.org/10.1111/1365-2745.13559.","productDescription":"22 p.","startPage":"1148","endPage":"1169","ipdsId":"IP-110024","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":454241,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.13559","text":"Publisher Index Page"},{"id":436640,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94IA5B3","text":"USGS data release","linkHelpText":"Landscape inputs and simulation output for the LANDIS-II model in the Greater Yellowstone Ecosystem"},{"id":380677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.32421875,\n 42.48019996901214\n ],\n [\n -108.19335937499999,\n 42.48019996901214\n ],\n [\n -108.19335937499999,\n 45.805828539928356\n ],\n [\n -112.32421875,\n 45.805828539928356\n ],\n [\n -112.32421875,\n 42.48019996901214\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"109","issue":"3801","noUsgsAuthors":false,"publicationDate":"2020-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":805422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":805423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheller, Robert M. 0000-0002-7507-4499","orcid":"https://orcid.org/0000-0002-7507-4499","contributorId":245139,"corporation":false,"usgs":false,"family":"Scheller","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":805424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhao, Feng S 0000-0003-4534-933X","orcid":"https://orcid.org/0000-0003-4534-933X","contributorId":245140,"corporation":false,"usgs":false,"family":"Zhao","given":"Feng","email":"","middleInitial":"S","affiliations":[{"id":49091,"text":"Central China Normal University","active":true,"usgs":false}],"preferred":false,"id":805425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"He, Hong S","contributorId":218764,"corporation":false,"usgs":false,"family":"He","given":"Hong","email":"","middleInitial":"S","affiliations":[{"id":39904,"text":"University of Missouri, School of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":805426,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xu, Wenru","contributorId":245141,"corporation":false,"usgs":false,"family":"Xu","given":"Wenru","affiliations":[{"id":39904,"text":"University of Missouri, School of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":805427,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":805428,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216906,"text":"70216906 - 2021 - Small atoll fresh groundwater lenses respond to a combination of natural climatic cycles and human modified geology","interactions":[],"lastModifiedDate":"2020-12-30T14:45:53.316375","indexId":"70216906","displayToPublicDate":"2020-11-20T07:04:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Small atoll fresh groundwater lenses respond to a combination of natural climatic cycles and human modified geology","docAbstract":"Freshwater lenses underlying small ocean islands exhibit spatial variability and temporal fluctuations in volume, influencing ecologic management. For example, The Palmyra Atoll National Wildlife Refuge harbors one of the few surviving native stands of Pisonia grandis in the central Pacific Ocean, yet these trees face pressure from groundwater salinization, with little basic groundwater data to guide decision making. Adding to natural complexity, the geology of Palmyra was heavily altered by dredge and fill activities. Our study based at this atoll combines geophysical and hydrological field measurements from 2008 to 2019 with groundwater modeling to study the drivers of observed freshwater lens dynamics. Electromagnetic induction (EMI) field data were collected on the main atoll islands over repeat transects in 2008 following ‘strong’ La Niña conditions (wet) and in 2016 during ‘very strong’ El Niño conditions (dry). Shallow monitoring wells were installed adjacent to the geophysical transects in 2013 and screened within the fresh/saline groundwater transition zone. Temporal EMI and monitoring well data showed a strong contraction of the freshwater lens in response to El Niño conditions, and indicated a thicker lens toward the ocean side, an opposite spatial pattern to that observed for many other Pacific islands. On an outer islet where a stand of mature Pisonia trees exist, EMI surveys revealed only a thin (<3 m from land surface) layer of brackish groundwater during El Niño. Numerical groundwater simulations were performed for a range of permeability distributions and climate conditions at Palmyra. Results revealed that the observed atypical lens asymmetry is likely due to more efficient submarine groundwater discharge on the lagoon side as a result of lagoon dredging and filling with high-permeability material. Simulations also predict large decreases (40%) in freshwater lens volume during dry cycles and highlight threats to the Pisonia trees, yielding insight for atoll ecosystem management worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.143838","usgsCitation":"Briggs, M.A., Cantelon, J., Kurylyk, B., Kulongoski, J.T., Mills, A., and Lane, J., 2021, Small atoll fresh groundwater lenses respond to a combination of natural climatic cycles and human modified geology: Science of the Total Environment, v. 756, 143838, 14 p., https://doi.org/10.1016/j.scitotenv.2020.143838.","productDescription":"143838, 14 p.","ipdsId":"IP-124031","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454244,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.143838","text":"Publisher Index Page"},{"id":381317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Palmyra Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.11434364318848,\n 5.865525058703975\n ],\n [\n -162.04078674316406,\n 5.865525058703975\n ],\n [\n -162.04078674316406,\n 5.896261485744235\n ],\n [\n -162.11434364318848,\n 5.896261485744235\n ],\n [\n -162.11434364318848,\n 5.865525058703975\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"756","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"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":806900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cantelon, J","contributorId":245723,"corporation":false,"usgs":false,"family":"Cantelon","given":"J","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":806901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kurylyk, B.","contributorId":222758,"corporation":false,"usgs":false,"family":"Kurylyk","given":"B.","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":806902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills, Audrey","contributorId":245724,"corporation":false,"usgs":false,"family":"Mills","given":"Audrey","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":806904,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":806905,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217186,"text":"70217186 - 2021 - The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser","interactions":[],"lastModifiedDate":"2021-01-11T16:11:26.62147","indexId":"70217186","displayToPublicDate":"2020-11-18T10:00:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser","docAbstract":"Steamboat Geyser in Yellowstone National Park’s Norris Geyser Basin began a prolific sequence of eruptions in March 2018 after 34 y of sporadic activity. We analyze a wide range of datasets to explore triggering mechanisms for Steamboat’s reactivation and controls on eruption intervals and height. Prior to Steamboat’s renewed activity, Norris Geyser Basin experienced uplift, a slight increase in radiant temperature, and increased regional seismicity, which may indicate that magmatic processes promoted reactivation. However, because the geothermal reservoir temperature did not change, no other dormant geysers became active, and previous periods with greater seismic moment release did not reawaken Steamboat, the reason for reactivation remains ambiguous. Eruption intervals since 2018 (3.16 to 35.45 d) modulate seasonally, with shorter intervals in the summer. Abnormally long intervals coincide with weakening of a shallow seismic source in the geyser basin’s hydrothermal system. We find no relation between interval and erupted volume, implying unsteady heat and mass discharge. Finally, using data from geysers worldwide, we find a correlation between eruption height and inferred depth to the shallow reservoir supplying water to eruptions. Steamboat is taller because water is stored deeper there than at other geysers, and, hence, more energy is available to power the eruptions.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2020943118","usgsCitation":"Reed, M., Munoz-Saez, C., Hajimirza, S., Wu, S., Barth, A., Girona, T., Rasht-Behesht, M., Karplus, M., Hurwitz, S., and Manga, M., 2021, The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser: PNAS, v. 118, no. 2, e2020943118, 10 p., https://doi.org/10.1073/pnas.2020943118.","productDescription":"e2020943118, 10 p.","ipdsId":"IP-123913","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":454249,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2020943118","text":"Publisher Index Page"},{"id":382060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Norris Geyser Basin, Steamboat Geyser, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.71465730667114,\n 44.71879196233473\n ],\n [\n -110.6957745552063,\n 44.71879196233473\n ],\n [\n -110.6957745552063,\n 44.73068351783913\n ],\n [\n -110.71465730667114,\n 44.73068351783913\n ],\n [\n -110.71465730667114,\n 44.71879196233473\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Reed, Mara","contributorId":247557,"corporation":false,"usgs":false,"family":"Reed","given":"Mara","affiliations":[],"preferred":false,"id":807890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munoz-Saez, Carolina","contributorId":131167,"corporation":false,"usgs":false,"family":"Munoz-Saez","given":"Carolina","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":807891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hajimirza, Sahand","contributorId":247558,"corporation":false,"usgs":false,"family":"Hajimirza","given":"Sahand","email":"","affiliations":[],"preferred":false,"id":807892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Sin-Mei","contributorId":175479,"corporation":false,"usgs":false,"family":"Wu","given":"Sin-Mei","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":807893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barth, Anna","contributorId":247559,"corporation":false,"usgs":false,"family":"Barth","given":"Anna","email":"","affiliations":[],"preferred":false,"id":807894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Girona, Tarsilo","contributorId":229679,"corporation":false,"usgs":false,"family":"Girona","given":"Tarsilo","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false},{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":true,"id":807895,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rasht-Behesht, Majid","contributorId":247560,"corporation":false,"usgs":false,"family":"Rasht-Behesht","given":"Majid","email":"","affiliations":[],"preferred":false,"id":807896,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Karplus, M.S","contributorId":205767,"corporation":false,"usgs":false,"family":"Karplus","given":"M.S","email":"","affiliations":[{"id":37164,"text":"University of Texas, El Paso","active":true,"usgs":false}],"preferred":false,"id":807897,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":807898,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Manga, Michael","contributorId":131168,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":807899,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70243772,"text":"70243772 - 2021 - Behavioral responses of sea lamprey (Petromyzon marinus) and white sucker (Catostomus commersonii) to turbulent flow during fishway passage attempts","interactions":[],"lastModifiedDate":"2023-05-19T11:43:02.869837","indexId":"70243772","displayToPublicDate":"2020-11-18T06:33:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Behavioral responses of sea lamprey (Petromyzon marinus) and white sucker (Catostomus commersonii) to turbulent flow during fishway passage attempts","title":"Behavioral responses of sea lamprey (Petromyzon marinus) and white sucker (Catostomus commersonii) to turbulent flow during fishway passage attempts","docAbstract":"An understanding of how undesirable and desirable fish species respond behaviorally to turbulent flow in fishways would guide development of selective fish passage techniques. We applied high-resolution computational fluid dynamics modeling and competing risks analysis towards the development of predictive selective passage models. Sea lamprey (Petromyzon marinus; an invasive fish in the Great Lakes Basin, North America) upstream passage probability declined from 0.73 to 0.03 as flow conditions became increasingly turbulent, while declines in white sucker (Catostomus commersonii, a native fish in the region) upstream passage probability were less substantial (0.53 to 0.44). Deploying a sea lamprey trap in the fishway did not effectively reduce sea lamprey upstream passage probability, though capture rate increased during trials with cooler water temperature and low total kinetic energy. Bifurcated fishways that maintain low turbulent flow in the entrapment route and high turbulent flow in the upstream passage route could increase the effectiveness of trapping sea lamprey in fishways as a means to advance selective passage goals.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0223","usgsCitation":"Lewandoski, S.A., Hrodey, P.J., Miehls, S.M., Piszczek, P., and Zielinski, D., 2021, Behavioral responses of sea lamprey (Petromyzon marinus) and white sucker (Catostomus commersonii) to turbulent flow during fishway passage attempts: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 4, p. 409-421, https://doi.org/10.1139/cjfas-2020-0223.","productDescription":"13 p.","startPage":"409","endPage":"421","ipdsId":"IP-120067","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":417234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Bois Brule River, Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.61913799037413,\n 46.746319413615765\n ],\n [\n -91.61109265501442,\n 46.697600103611876\n ],\n [\n -91.60349428273015,\n 46.66908351070549\n ],\n [\n -91.610645691939,\n 46.6396312386392\n ],\n [\n -91.59455502121916,\n 46.61568945646317\n ],\n [\n -91.59008539046347,\n 46.5831713812953\n ],\n [\n -91.59768376274775,\n 46.54414318194961\n ],\n [\n -91.61735013807177,\n 46.5241572565657\n ],\n [\n -91.60751695040997,\n 46.48507053273994\n ],\n [\n -91.63612258724542,\n 46.45367061381313\n ],\n [\n -91.68126585787567,\n 46.44011995829479\n ],\n [\n -91.75201200283867,\n 46.40437245435308\n ],\n [\n -91.75201200283867,\n 46.39820791069087\n ],\n [\n -91.64652871700919,\n 46.43980506395201\n ],\n [\n -91.6128335861273,\n 46.45168996471648\n ],\n [\n -91.5878036538965,\n 46.483091025906276\n ],\n [\n -91.59853076771002,\n 46.527698611965775\n ],\n [\n -91.576629577008,\n 46.54522398535883\n ],\n [\n -91.57081905702584,\n 46.589166256606916\n ],\n [\n -91.57528868778131,\n 46.62048794471005\n ],\n [\n -91.59137935850114,\n 46.64381389971618\n ],\n [\n -91.58512187544464,\n 46.68098665401865\n ],\n [\n -91.59629595233312,\n 46.712255228466375\n ],\n [\n -91.5954020261823,\n 46.726657203488514\n ],\n [\n -91.60389432461741,\n 46.75361226678078\n ],\n [\n -91.61913799037413,\n 46.746319413615765\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"78","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lewandoski, Sean A.","contributorId":221007,"corporation":false,"usgs":false,"family":"Lewandoski","given":"Sean","email":"","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":873209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hrodey, Peter J.","contributorId":205578,"corporation":false,"usgs":false,"family":"Hrodey","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6599,"text":"U.S. Fish and Wildlife Service, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":873210,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":873211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piszczek, Paul","contributorId":305569,"corporation":false,"usgs":false,"family":"Piszczek","given":"Paul","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":873212,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zielinski, Daniel","contributorId":245798,"corporation":false,"usgs":false,"family":"Zielinski","given":"Daniel","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":873213,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215397,"text":"70215397 - 2021 - Sediment dynamics of a divergent bay–marsh complex","interactions":[],"lastModifiedDate":"2021-06-01T17:19:12.643911","indexId":"70215397","displayToPublicDate":"2020-11-17T12:55:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Sediment dynamics of a divergent bay–marsh complex","docAbstract":"Bay–marsh systems, composed of an embayment surrounded by fringing marsh incised by tidal channels, are widely distributed coastal environments. External sediment availability, marsh-edge erosion, and sea-level rise acting on such bay–marsh complexes may drive diverse sediment-flux regimes. These factors reinforce the ephemeral and dynamic nature of fringing marshes: material released by marsh-edge erosion becomes part of a bay–marsh exchange that fuels the geomorphic evolution of the coupled system. The dynamics of this sediment exchange determine the balance among seaward export, deposition on the embayment seabed, flux into tidal channels, and import to the marsh platform. In this work, we investigate the sediment dynamics of a transgressive bay–marsh complex and link them to larger-scale considerations of its geomorphic trajectory. Grand Bay, Alabama/Mississippi, is a shallow microtidal embayment surrounded by salt marshes with lateral erosion rates of up to 5 m year−1. We collected 6 months of oceanographic data at four moorings within Grand Bay and its tidal channels to assess hydrographic conditions and net sediment-flux patterns and augmented the observations with numerical modeling. The observations imply a divergent sedimentary system in which a majority of the suspended sediment is exported seaward, while a smaller fraction is imported landward via tidal channels, assisting in vertical marsh-plain accumulation, maintenance of channel and intertidal-flat morphologies, and landward transgression. These results describe a dynamic system that is responsive to episodic atmospheric forcing in the absence of a strong tidal signal and the presence of severe lateral marsh loss.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-020-00855-5","usgsCitation":"Nowacki, D.J., and Ganju, N., 2021, Sediment dynamics of a divergent bay–marsh complex: Estuaries and Coasts, v. 44, p. 1216-1230, https://doi.org/10.1007/s12237-020-00855-5.","productDescription":"15 p.","startPage":"1216","endPage":"1230","ipdsId":"IP-120963","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454262,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-020-00855-5","text":"Publisher Index Page"},{"id":382512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Mississippi","otherGeospatial":"Grand Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.43856811523438,\n 30.34562073484083\n ],\n [\n -88.35582733154297,\n 30.34562073484083\n ],\n [\n -88.35582733154297,\n 30.422032481449097\n ],\n [\n -88.43856811523438,\n 30.422032481449097\n ],\n [\n -88.43856811523438,\n 30.34562073484083\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2020-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Nowacki, Daniel J. 0000-0002-7015-3710 dnowacki@usgs.gov","orcid":"https://orcid.org/0000-0002-7015-3710","contributorId":174586,"corporation":false,"usgs":true,"family":"Nowacki","given":"Daniel","email":"dnowacki@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":802011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802012,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216779,"text":"70216779 - 2021 - Generalizing the inversion‐based PSHA source model for an interconnected fault system","interactions":[],"lastModifiedDate":"2023-03-27T16:59:07.467182","indexId":"70216779","displayToPublicDate":"2020-11-17T09:41:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Generalizing the inversion‐based PSHA source model for an interconnected fault system","docAbstract":"This article represents a step toward generalizing and simplifying the procedure for constructing an inversion‐based seismic hazard source model for an interconnected fault system, including the specification of adjustable segmentation constraints. A very simple example is used to maximize understandability and to counter the notion that an inversion approach is only applicable when an abundance of data is available. Also exemplified is how to construct a range of models to adequately represent epistemic uncertainties (which should be a high priority in any hazard assessment). Opportunity is also taken to address common concerns and misunderstandings associated with the third Uniform California Earthquake Rupture Forecast, including the seemingly disproportionate number of large‐magnitude events, and how well hazard is resolved given the overall problem is very underdetermined. However, the main aim of this article is to provide a general protocol for constructing such models.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200219","usgsCitation":"Field, E.H., Milner, K.R., and Page, M.T., 2021, Generalizing the inversion‐based PSHA source model for an interconnected fault system: Bulletin of the Seismological Society of America, v. 111, no. 1, p. 371-390, https://doi.org/10.1785/0120200219.","productDescription":"20 p.","startPage":"371","endPage":"390","ipdsId":"IP-122019","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":381034,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":806224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milner, Kevin R.","contributorId":194141,"corporation":false,"usgs":false,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":806225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":806226,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249204,"text":"70249204 - 2021 - Teleseismic P‐qave coda autocorrelation imaging of crustal and basin structure, Bighorn Mountains Region, Wyoming, U.S.A.","interactions":[],"lastModifiedDate":"2023-10-02T11:46:50.38526","indexId":"70249204","displayToPublicDate":"2020-11-17T06:41:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Teleseismic P‐qave coda autocorrelation imaging of crustal and basin structure, Bighorn Mountains Region, Wyoming, U.S.A.","docAbstract":"We demonstrate successful crustal imaging via teleseismic P‐wave coda autocorrelation, using data recorded on a 261 station array of vertical‐component high‐frequency geophones in the area of the Bighorn Mountains, Wyoming, U.S.A. We autocorrelate the P‐wave coda of 30 teleseismic events and use phase‐weighted stacking to yield seismic profiles comparable to low‐passed versions of those produced via controlled‐source vertical seismic reflection. Our process recovers reflections from the bottoms of the Bighorn and Powder River basins that flank the Bighorn Mountains. We also identify a mid‐crustal reflector that aligns with a region of increased reflectivity, previously interpreted as a Precambrian province boundary. Our results demonstrate the utility of crustal imaging with teleseismic P‐wave coda energy using modern large‐array seismic data, and they corroborate previous interpretations of crustal structures in the study area.
Excavation of Ptolemaic Period (ca. 309–30 BC) strata within Theban Tombs 11, 12, -399-, and UE194A by the Spanish Mission to Dra Abu el-Naga (also known as the Djehuty Project), on the west bank of the Nile River opposite Luxor, Egypt, yielded remains of at least 175 individual small mammals that include four species of shrews (Eulipotypha: Soricidae) and two species of rodents (Rodentia: Muridae). Two of the shrews (Crocidura fulvastra and Crocidura pasha) no longer occur in Egypt, and one species (Crocidura olivieri) is known in the country only from a disjunct population inhabiting the Nile delta and the Fayum. Although deposited in the tombs by humans as part of religious ceremonies, these animals probably derived originally from local wild populations. The coexistence of this diverse array of shrew species as part of the mammal community near Luxor indicates greater availability of moist floodplain habitats than occur there at present. These were probably made possible by a greater flow of the Nile, as indicated by geomorphological and palynological evidence. The mammal fauna recovered by the Spanish Mission provides a unique snapshot of the native Ptolemaic community during this time period, and it permits us to gauge community turnover in the Nile valley of Upper Egypt during the last 2000 years. It also serves as a relevant example for understanding the extinction and extirpation of mammal species as effects of future environmental changes predicted by current climatic models.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2020.89","usgsCitation":"Woodman, N., and Ikram, S., 2021, Ancient Egyptian mummified shrews (Mammalia: Eulipotyphla: Soricidae) and mice (Rodentia: Muridae) from the Spanish Mission to Dra Abu el-Naga, and their implications for environmental change in the Nile valley during the past two millennia: Quaternary Research, v. 100, p. 21-31, https://doi.org/10.1017/qua.2020.89.","productDescription":"11 p.","startPage":"21","endPage":"31","ipdsId":"IP-122070","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":380835,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Egypt","otherGeospatial":"northern Egypt","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 24.873046874999996,\n 26.78484736105119\n ],\n [\n 33.2666015625,\n 26.78484736105119\n ],\n [\n 33.2666015625,\n 31.541089879585808\n ],\n [\n 24.873046874999996,\n 31.541089879585808\n ],\n [\n 24.873046874999996,\n 26.78484736105119\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","noUsgsAuthors":false,"publicationDate":"2020-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":805702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ikram, Salima","contributorId":245249,"corporation":false,"usgs":false,"family":"Ikram","given":"Salima","affiliations":[{"id":49125,"text":"American University in Cairo","active":true,"usgs":false}],"preferred":false,"id":805703,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216698,"text":"70216698 - 2021 - Mainstems: A logical data model implementing mainstem and drainage basin feature types based on WaterML2 Part 3: HY Features concepts","interactions":[],"lastModifiedDate":"2020-12-01T13:34:28.581683","indexId":"70216698","displayToPublicDate":"2020-11-13T07:32:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Mainstems: A logical data model implementing mainstem and drainage basin feature types based on WaterML2 Part 3: HY Features concepts","docAbstract":"The Mainstems data model implements the catchment and flowpath concepts from WaterML2 Part 3: Surface Hydrology Features (HY_Features) for persistent, cross-scale, identification of hydrologic features. The data model itself provides a focused and lightweight method to describe hydrologic networks with minimum but sufficient information. The design is intended to provide a model for data integration that can be used for network navigation and persistent hydrologic indexing (hydrographic addressing) functionality. Mainstems is designed to provide long-term stability with minimal maintenance requirements. The data model is not meant to advance hydrologic process representation or uniquely represent geomorphic characteristics. The principle assumption in Mainstems is that all drainage basins have one - and only one - headwater source area and a single mainstem that flows to a single outlet. Using these base feature types, (headwater, outlet, mainstem, and drainage basin) a nested set of drainage basins - and the associated dendritic network of mainstems - can be identified.
Maximum densities of juvenile river herring (Alewife Alosa pseudoharengus and Blueback Herring A. aestivalis) vary among freshwater lakes, likely due to densities of adult spawners. Differences in habitat availability and lake water quality may also contribute to variation in juvenile river herring productivity between populations, yet these relationships have not been tested across a large geographic scope. In this study we investigated relationships between juvenile river herring densities and (1) spawning adult river herring densities, (2) lake habitat availability, and (3) lake water quality in 29 freshwater lakes in the northeastern USA. Purse seines were used at night to sample juvenile river herring monthly in June–August 2014 and 2015, with concurrent collection of lake-specific physical (e.g., lake surface area, mean depth, depth to thermocline), chemical (e.g., nitrogen, phosphorus, dissolved organic carbon [DOC]), and biological (chlorophyll a, adult spawning density) data. Spawning adult density (number of adults per surface area of lake) explained 66.6% of the variation in juvenile densities using a generalized additive model. Juvenile densities increased with increasing adult density, peaking at roughly 1,000 adults/ha, and then declined at higher adult densities, suggesting a limit to carrying capacity in juvenile production. Linear mixed-effects models revealed that differences in water quality and habitat across lakes explained additional variation in juvenile densities. Specifically, DOC was negatively related to juvenile densities, suggesting that DOC limits the amount of suitable, well-oxygenated epilimnion habitat available to juvenile river herring in late summer. Our results can be used to help understand expected juvenile production based on adult density within a lake, to inform expectations about juvenile growth and survival, and to understand the mechanisms for how changes in habitat availability and water quality affect river herring populations.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10282","usgsCitation":"Devine, M.T., Rosset, J., Roy, A.H., Gahagan, B.I., Armstrong, M.P., Whiteley, A., and Jordaan, A., 2021, Feeling the squeeze: Adult run size and habitat availability limit juvenile river herring densities in lakes: Transactions of the American Fisheries Society, v. 150, no. 2, p. 207-221, https://doi.org/10.1002/tafs.10282.","productDescription":"16 p.","startPage":"207","endPage":"221","ipdsId":"IP-120456","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":396569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.66455078125,\n 44.6061127451739\n ],\n [\n -70.927734375,\n 44.62175409623324\n ],\n [\n -72.1142578125,\n 43.723474896114794\n ],\n [\n -73.4326171875,\n 41.31082388091818\n ],\n [\n -71.103515625,\n 41.1290213474951\n ],\n [\n -70.0048828125,\n 41.32732632036622\n ],\n [\n -69.54345703125,\n 41.88592102814744\n ],\n [\n -70.400390625,\n 42.827638636242284\n ],\n [\n -69.78515625,\n 43.48481212891603\n ],\n [\n -68.84033203125,\n 44.02442151965934\n ],\n [\n -68.66455078125,\n 44.6061127451739\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Devine, Matthew T.","contributorId":204986,"corporation":false,"usgs":false,"family":"Devine","given":"Matthew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":836323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosset, Julianne","contributorId":197446,"corporation":false,"usgs":false,"family":"Rosset","given":"Julianne","email":"","affiliations":[],"preferred":false,"id":836324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":836322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gahagan, Benjamin I.","contributorId":200168,"corporation":false,"usgs":false,"family":"Gahagan","given":"Benjamin","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":836325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Armstrong, Michael P.","contributorId":286850,"corporation":false,"usgs":false,"family":"Armstrong","given":"Michael","email":"","middleInitial":"P.","affiliations":[{"id":40132,"text":"Massachusetts Division of Marine Resources","active":true,"usgs":false}],"preferred":false,"id":836326,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whiteley, Andrew R.","contributorId":286853,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew R.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":836327,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jordaan, Adrian","contributorId":210892,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":836328,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216363,"text":"70216363 - 2021 - A lagrangian-to-eulerian metric to identify estuarine pelagic habitats","interactions":[],"lastModifiedDate":"2021-06-01T17:01:46.95513","indexId":"70216363","displayToPublicDate":"2020-11-11T09:23:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"A lagrangian-to-eulerian metric to identify estuarine pelagic habitats","docAbstract":"Estuaries are among the world’s most productive ecosystems, but recent natural and anthropogenic changes have stressed these ecosystems. Tools to assess estuarine pelagic habitats are important to support and maintain healthy ecosystem function. In this work, we demonstrate that estuarine pelagic habitats can be identified by a simple ratio, termed the LE ratio, that takes into account the tidal excursion along a channel (a Lagrangian length scale) and the distance along that channel (an Eulerian length scale). To develop and assess this concept, numerical simulations of the 1D advection–dispersion equation of a conservative tracer and tidal excursion estimates based on data were used to formulize a conceptual model and to define exchange zones within a tidal channel. This conceptual model was then used to predict the extent of pelagic habitats in a terminal channel network in the Sacramento–San Joaquin Delta. Exchange zones mapped onto these channels were found to be in good agreement with independent estimates of residence time. Sensitivity analyses of the numerical model suggest that productive pelagic habitats can be expanded by a factor of 2 by either increasing dispersion or increasing spring–neap variability in mean tidal velocity. Such changes can also enhance flushing in upper channel reaches. These findings are relevant for tidal marsh restoration projects that aim to expand beneficial aquatic habitats by varying exchange or residence time over the spring–neap cycle, because this variability may interact synergistically with varying rates of phytoplankton growth due to spatiotemporal changes in environmental conditions.
In 2017 the rusty patched bumble bee (Bombus affinis) became the first bee listed under the Endangered Species Act in the continental United States due to population declines and an 87% reduction in the species’ distribution. Bombus affinis decline began in the 1990s, predating modern bee surveying initiatives, and obfuscating drivers of decline. While understood to be a highly generalist forager, little is known about the role that resource limitation or shifting floral community composition could have played in B. affinis decline. Determining which floral species support B. affinis could assist conservation efforts where B. affinis persists and identify floral species for restoration efforts. We constructed a historical foraging profile of B. affinis via DNA sequencing of pollen from museum specimens spanning seven states collected from 1913 to 2013. Molecular analysis revealed no temporal changes in the floral richness or composition of B. affinis pollen samples across our sampling period. Likewise, we found no temporal changes in the presence or proportion of native vs. introduced species in pollen samples, though we observed much greater use of introduced floral species than previously determined for B. affinis. Floral community composition was regionally dissimilar, inconsistent with patterns of B. affinis decline by state. Our results suggest B. affinis decline was unlikely to have been driven by spatial or temporal limitations of specific floral species. This work greatly expands the known forage of B. affinis and will provide managers with insight to aid the conservation of B. affinis.
Anglers face constraints that influence participation and dropout rates. Some recreational anglers may be able to negotiate constraints by altering the timing or frequency of participation, acquiring new skills, or modifying nonrecreational aspects such as family or work responsibilities. We consider data collected via a mail survey from Georgia-resident trout license holders to identify both perceived constraints and strategies used to negotiate them. To capture variation among anglers, survey responses were grouped by level of angler specialization using K-means cluster analysis, which resulted in a three-cluster solution of most, moderately, and least specialized anglers. Analyses of variance were used to detect potential differences among the three specialization clusters. Tests revealed that the least specialized anglers experienced constraints more intensely than the most or moderately specialized anglers. Likewise, least specialized anglers were less able to negotiate constraints when compared to the most or moderately specialized anglers. However, the least specialized anglers used negotiation strategies involving overcoming perceived lack of skill more intensely than their counterparts. The most intensely experienced constraints overall were lack of time due to work or family obligations and distance to Georgia’s trout waters from home. The most intensely used negotiation strategies overall were “learn to enjoy being outside and stress less about catching fish” and “encourage family or friends to go fishing with me.” This research benefits fishery managers by providing a method of identifying angling groups that perceive more constraints and are less likely to overcome these constraints through constraint negotiation strategies. With this information, managers may choose to tailor efforts towards reducing constraints for angling groups that have low participation and may drop out of the activity all together.
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J.","contributorId":276309,"corporation":false,"usgs":false,"family":"TenHarmsel","given":"H. J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boley, B. B.","contributorId":276310,"corporation":false,"usgs":false,"family":"Boley","given":"B. B.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jennings, Cecil A. 0000-0002-6159-6026 jennings@usgs.gov","orcid":"https://orcid.org/0000-0002-6159-6026","contributorId":874,"corporation":false,"usgs":true,"family":"Jennings","given":"Cecil","email":"jennings@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834734,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217679,"text":"70217679 - 2021 - Spectral inversion for seismic site response in central Oklahoma: Low-frequency resonances from the Great Unconformity","interactions":[],"lastModifiedDate":"2021-02-04T14:23:24.955134","indexId":"70217679","displayToPublicDate":"2020-11-10T07:30:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7571,"text":"Bulletin of Seismological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"Spectral inversion for seismic site response in central Oklahoma: Low-frequency resonances from the Great Unconformity","docAbstract":"We investigate seismic site response by inverting seismic ground‐motion spectra for site and source spectral properties, in a region of central Oklahoma, where previous ground‐motion studies have indicated discrepancies between observations and ground‐motion models (GMMs). The inversion is constrained by a source spectral model, which we computed from regional seismic records, using aftershocks as empirical Green’s functions to deconvolve site and path effects. Site spectra across the region exhibit multiple, strong, low‐frequency (f <2 Hz) resonances. Modeling of vertically propagating SH waves reproduces the mean amplitudes and frequencies of the site spectra and requires a deep (∼1–2 km) impedance contrast. Comparison of regional seismic velocity models and geologic profiles indicates that the seismic impedance contrast is, or is in proximity to, the Great Unconformity, which marks the interface between Precambrian basement rocks and overlying Paleozoic sedimentary rocks. Depth to Precambrian basement increases to the southwest across the study region (∼1500–4500 m), and the fundamental frequencies of the site spectra are anticorrelated with basement depth. The first higher‐mode resonance also exhibits dependence on basement depth; although modeling suggests that the second higher mode should depend on basement depth, site spectra do not support this. The low‐frequency resonances in central Oklahoma are not represented in the GMMs used in current seismic hazard analyses for tectonic earthquakes, though approaches to account for such features are under consideration in other regions of the central and eastern United States. Given the broad spatial extent of the Great Unconformity underlying eastern North America, it is likely that similar effects on seismic site response also occur in other areas. This study highlights the impact of regional geologic structure on earthquake ground motions and reiterates the need for modeling regional effects to improve ground‐motion predictions and seismic hazard assessments.
It is unknown how ungulate physiological responses to environmental perturbation influence overall population demographics. Moreover, neonatal physiological responses remain poorly studied despite the importance of neonatal survival to population growth. Glucocorticoid (GC) hormones potentially facilitate critical physiological and behavioral responses to environmental perturbations. However, elevated GC concentrations over time may compromise body condition and indirectly reduce survival. We evaluated baseline salivary cortisol (CORT; a primary GC in mammals) concentrations in 19 wild neonatal white-tailed deer (Odocoileus virginianus) in a northern (NS) and southern (SS) area in Pennsylvania. After ranking survival models consisting of variables hypothesized to influence neonate survival (i.e. weight, sex), the probability of neonate survival was best explained by CORT concentrations, where elevated CORT concentrations were associated with reduced survival probability to 12 weeks of age. Cortisol concentrations were greater in the SS where predation rates and predator densities were lower. As the first evaluation of baseline CORT concentrations in an ungulate neonate to our knowledge, this is also the first study to demonstrate CORT concentrations are negatively associated with ungulate survival at any life stage. Glucocorticoid hormones could provide a framework in which to better understand susceptibility to mortality in neonatal white-tailed deer.
","language":"English","publisher":"Wiley","doi":"10.1111/1749-4877.12499","usgsCitation":"Gingery, T.M., Diefenbach, D.R., Pritchard, C.E., Ensminger, D., Wallingford, B., and Rosenberry, C., 2021, Survival is negatively associated with glucocorticoids in a wild ungulate neonate: Integrative Zoology, v. 16, no. 2, p. 214-225, https://doi.org/10.1111/1749-4877.12499.","productDescription":"12 p.","startPage":"214","endPage":"225","ipdsId":"IP-118200","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Gingery, Tess Michelle","contributorId":276204,"corporation":false,"usgs":false,"family":"Gingery","given":"Tess","email":"","middleInitial":"Michelle","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pritchard, Catharine E.","contributorId":276205,"corporation":false,"usgs":false,"family":"Pritchard","given":"Catharine","email":"","middleInitial":"E.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ensminger, David C.","contributorId":276206,"corporation":false,"usgs":false,"family":"Ensminger","given":"David C.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallingford, Bret D.","contributorId":276207,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret D.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834660,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosenberry, Christopher S.","contributorId":276209,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834661,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228597,"text":"70228597 - 2021 - Clothianidin decomposition in Missouri wetland soils","interactions":[],"lastModifiedDate":"2022-02-14T17:58:00.120595","indexId":"70228597","displayToPublicDate":"2020-11-09T11:55:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Clothianidin decomposition in Missouri wetland soils","docAbstract":"Neonicotinoid pesticides can persist in soils for extended time periods; however, they also have a high potential to contaminate ground and surface waters. Studies have reported negative effects associated with neonicotinoids and nontarget taxa, including aquatic invertebrates, pollinating insect species, and insectivorous birds. This study evaluated factors associated with clothianidin (CTN) degradation and sorption in Missouri wetland soils to assess the potential for wetland soils to mitigate potential environmental risks associated with neonicotinoids. Solid-to-solution partition coefficients (Kd) for CTN sorption to eight wetland soils were determined via single-point sorption experiments, and sorption isotherm experiments were conducted using the two most contrasting soils. Clothianidin degradation was determined under oxic and anoxic conditions over 60 d. Degradation data were fit to zero- and first-order kinetic decay models to determine CTN half-life (t0.5). Sorption results indicated CTN sorption to wetland soil was relatively weak (average Kd, 3.58 L kg–1); thus, CTN has the potential to be mobile and bioavailable within wetland soils. However, incubation results showed anoxic conditions significantly increased CTN degradation rates in wetland soils (anoxic average t0.5, 27.2 d; oxic average t0.5, 149.1 d). A significant negative correlation was observed between anoxic half-life values and soil organic C content (r2 = .782; p = .046). Greater CTN degradation rates in wetland soils under anoxic conditions suggest that managing wetlands to facilitate anoxic conditions could mitigate CTN presence in the environment and reduce exposure to nontarget organisms.
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N.","contributorId":276298,"corporation":false,"usgs":false,"family":"Lerch","given":"R.","email":"","middleInitial":"N.","affiliations":[{"id":56949,"text":"USDA-Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":834721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mengel, D.","contributorId":244519,"corporation":false,"usgs":false,"family":"Mengel","given":"D.","email":"","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":834723,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216472,"text":"70216472 - 2021 - Stress gradients interact with disturbance to reveal alternative states in salt marsh: Multivariate resilience at the landscape scale","interactions":[],"lastModifiedDate":"2021-10-04T16:46:47.880285","indexId":"70216472","displayToPublicDate":"2020-11-09T07:45:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Stress gradients interact with disturbance to reveal alternative states in salt marsh: Multivariate resilience at the landscape scale","docAbstract":"Synthesis. Ultimately, we quantify the ball‐and‐cup conceptual model for a salt marsh ecosystem and its alternative state, mudflat. We find that increasing abiotic stress due to climate change diminishes ecosystem resilience, but the interaction with common episodic disturbances is necessary to reveal transitions to alternative states and quantify state change thresholds. Quantifying and mapping resilience and where alternative states may exist in this fashion improves ecologists’ ability to investigate the mechanisms of stress gradient control on emergent ecosystem properties, while providing spatially explicit resources for managing ecosystems according to their projected resilience.
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