Many plants resprout from basal buds after disturbance, and this is common in shrublands subjected to high-intensity fires. However, resprouting after fire from epicormic (stem) buds is globally far less common. Unlike basal resprouting, post-fire epicormic resprouting is a key plant adaptation for retention of the arborescent skeleton after fire, allowing rapid recovery of the forest or woodland and leading to greater ecosystem resilience under recurrent high-intensity fires. Here we review the biogeography of epicormic resprouting, the mechanisms of protection, the fire regimes where it occurs, and the evolutionary drivers that shaped this trait. We propose that epicormic resprouting is adaptive in ecosystems with high fire frequency and relatively high productivity, at moderate–high fire intensities.
","language":"English","publisher":"Cell Press","doi":"10.1016/j.tplants.2017.08.010","usgsCitation":"Pausas, J.G., and Keeley, J.E., 2017, Epicormic resprouting in fire-prone ecosystems: Trends in Plant Science, v. 22, no. 12, p. 1008-1015, https://doi.org/10.1016/j.tplants.2017.08.010.","productDescription":"8 p.","startPage":"1008","endPage":"1015","ipdsId":"IP-088237","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469427,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10261/183556","text":"External Repository"},{"id":346896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"12","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e8682fe4b05fe04cd4d1ae","contributors":{"authors":[{"text":"Pausas, Juli G.","contributorId":197439,"corporation":false,"usgs":false,"family":"Pausas","given":"Juli","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":713504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":713503,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191837,"text":"70191837 - 2017 - Multistressor predictive models of invertebrate condition in the Corn Belt, USA","interactions":[],"lastModifiedDate":"2017-11-29T16:22:43","indexId":"70191837","displayToPublicDate":"2017-10-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Multistressor predictive models of invertebrate condition in the Corn Belt, USA","docAbstract":"Understanding the complex relations between multiple environmental stressors and ecological conditions in streams can help guide resource-management decisions. During 14 weeks in spring/summer 2013, personnel from the US Geological Survey and the US Environmental Protection Agency sampled 98 wadeable streams across the Midwest Corn Belt region of the USA for water and sediment quality, physical and habitat characteristics, and ecological communities. We used these data to develop independent predictive disturbance models for 3 macroinvertebrate metrics and a multimetric index. We developed the models based on boosted regression trees (BRT) for 3 stressor categories, land use/land cover (geographic information system [GIS]), all in-stream stressors combined (nutrients, habitat, and contaminants), and for GIS plus in-stream stressors. The GIS plus in-stream stressor models had the best overall performance with an average cross-validation R2 across all models of 0.41. The models were generally consistent in the explanatory variables selected within each stressor group across the 4 invertebrate metrics modeled. Variables related to riparian condition, substrate size or embeddedness, velocity and channel shape, nutrients (primarily NH3), and contaminants (pyrethroid degradates) were important descriptors of the invertebrate metrics. Models based on all measured in-stream stressors performed comparably to models based on GIS landscape variables, suggesting that the in-stream stressor characterization reasonably represents the dominant factors affecting invertebrate communities and that GIS variables are acting as surrogates for in-stream stressors that directly affect in-stream biota.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/694894","usgsCitation":"Waite, I.R., and Van Metre, P., 2017, Multistressor predictive models of invertebrate condition in the Corn Belt, USA: Freshwater Science, v. 36, no. 4, p. 901-914, https://doi.org/10.1086/694894.","productDescription":"14 p.","startPage":"901","endPage":"914","ipdsId":"IP-069783","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":346921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Kansas, Kentucky, Minnesota, Missouri, Nebraska, Ohio, South Dakota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.41552734375,\n 37.61423141542417\n ],\n [\n -82.30957031249999,\n 37.61423141542417\n ],\n [\n -82.30957031249999,\n 44.77793589631623\n ],\n [\n -98.41552734375,\n 44.77793589631623\n ],\n [\n -98.41552734375,\n 37.61423141542417\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e86831e4b05fe04cd4d1c5","contributors":{"authors":[{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Metre, Peter C. 0000-0001-7564-9814 pcvanmet@usgs.gov","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":197363,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":false,"id":713307,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191857,"text":"70191857 - 2017 - U.S. Geological Survey experience with the residual absolutes method","interactions":[],"lastModifiedDate":"2017-10-18T14:02:39","indexId":"70191857","displayToPublicDate":"2017-10-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5518,"text":"Geoscientific Instrumentation, Methods and Data Systems","active":true,"publicationSubtype":{"id":10}},"title":"U.S. Geological Survey experience with the residual absolutes method","docAbstract":"The U.S. Geological Survey (USGS) Geomagnetism Program has developed and tested the residual method of absolutes, with the assistance of the Danish Technical University's (DTU) Geomagnetism Program. Three years of testing were performed at College Magnetic Observatory (CMO), Fairbanks, Alaska, to compare the residual method with the null method. Results show that the two methods compare very well with each other and both sets of baseline data were used to process the 2015 definitive data. The residual method will be implemented at the other USGS high-latitude geomagnetic observatories in the summer of 2017 and 2018.
","language":"English","publisher":"EGU","doi":"10.5194/gi-6-419-2017","usgsCitation":"Worthington, E.W., and Matzka, J., 2017, U.S. Geological Survey experience with the residual absolutes method: Geoscientific Instrumentation, Methods and Data Systems, v. 6, p. 419-427, https://doi.org/10.5194/gi-6-419-2017.","productDescription":"9 p.","startPage":"419","endPage":"427","ipdsId":"IP-085974","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469431,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gi-6-419-2017","text":"Publisher Index Page"},{"id":346870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-17","publicationStatus":"PW","scienceBaseUri":"59e86830e4b05fe04cd4d1b7","contributors":{"authors":[{"text":"Worthington, E. William 0000-0002-5879-0477 bworth@usgs.gov","orcid":"https://orcid.org/0000-0002-5879-0477","contributorId":2570,"corporation":false,"usgs":true,"family":"Worthington","given":"E.","email":"bworth@usgs.gov","middleInitial":"William","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":713419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matzka, Jurgen","contributorId":197403,"corporation":false,"usgs":false,"family":"Matzka","given":"Jurgen","email":"","affiliations":[],"preferred":false,"id":713420,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226533,"text":"70226533 - 2017 - Bedrock geology of DFDP-2B, central Alpine Fault, New Zealand","interactions":[],"lastModifiedDate":"2021-11-23T14:11:41.867427","indexId":"70226533","displayToPublicDate":"2017-10-17T07:26:31","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2869,"text":"New Zealand Journal of Geology and Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Bedrock geology of DFDP-2B, central Alpine Fault, New Zealand","docAbstract":"During the second phase of the Alpine Fault, Deep Fault Drilling Project (DFDP) in the Whataroa River, South Westland, New Zealand, bedrock was encountered in the DFDP-2B borehole from 238.5–893.2 m Measured Depth (MD). Continuous sampling and meso- to microscale characterisation of whole rock cuttings established that, in sequence, the borehole sampled amphibolite facies, Torlesse Composite Terrane-derived schists, protomylonites and mylonites, terminating 200–400 m above an Alpine Fault Principal Slip Zone (PSZ) with a maximum dip of 62°. The most diagnostic structural features of increasing PSZ proximity were the occurrence of shear bands and reduction in mean quartz grain sizes. A change in composition to greater mica:quartz + feldspar, most markedly below c. 700 m MD, is inferred to result from either heterogeneous sampling or a change in lithology related to alteration. Major oxide variations suggest the fault-proximal Alpine Fault alteration zone, as previously defined in DFDP-1 core, was not sampled.
Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral
in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.
On 7 May 2015, a Mw 4.0 earthquake occurred near Venus, northeast Johnson County, Texas, in an area of the Bend Arch-Fort Worth Basin that reports long-term, high-volume wastewater disposal and that has hosted felt earthquakes since 2009. In the weeks following the Mw 4.0 earthquake, we deployed a local seismic network and purchased nearby active-source seismic reflection data to capture additional events, characterize the causative fault, and explore potential links between ongoing industry activity and seismicity. Hypocenter relocations of the resulting local earthquake catalog span ~4–6 km depth and indicate a fault striking ~230°, dipping to the west, consistent with a nodal plane of the Mw 4.0 regional moment tensor. Fault plane solutions indicate normal faulting, with B axes striking parallel to maximum horizontal compressive stress. Seismic reflection data image the reactivated basement fault penetrating the Ordovician disposal layer and Mississippian production layer, but not displacing post-Lower Pennsylvanian units. Template matching at regional seismic stations indicates that low-magnitude earthquakes with similar waveforms began in April 2008, with increasing magnitude over time. Pressure data from five saltwater disposal wells within 5 km of the active fault indicate a disposal formation that is 0.9–4.8 MPa above hydrostatic. We suggest that the injection of 28,000,000 m3 of wastewater between 2006 and 2015 at these wells led to an increase in subsurface pore fluid pressure that contributed to inducing this long-lived earthquake sequence. The 2015 Mw 4.0 event represents the largest event in the continuing evolution of slip on the causative fault.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014460","usgsCitation":"Scales, M.M., DeShon, H.R., Magnani, M., Walter, J., Quinones, L., Pratt, T.L., and Hornbach, M.J., 2017, A decade of induced slip on the causative fault of the 2015 Mw 4.0 Venus earthquake, northeast Johnson County, Texas: Journal of Geophysical Research B: Solid Earth, v. 122, no. 10, p. 7879-7894, https://doi.org/10.1002/2017JB014460.","productDescription":"16 p.","startPage":"7879","endPage":"7894","ipdsId":"IP-088408","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":346739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Johnson County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.4,\n 32.1\n ],\n [\n -96.8,\n 32.1\n ],\n [\n -96.8,\n 32.6\n ],\n [\n -97.4,\n 32.6\n ],\n [\n -97.4,\n 32.1\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-07","publicationStatus":"PW","scienceBaseUri":"59e7168de4b05fe04cd33165","contributors":{"authors":[{"text":"Scales, Monique M.","contributorId":197229,"corporation":false,"usgs":false,"family":"Scales","given":"Monique","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":712997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeShon, Heather R.","contributorId":48540,"corporation":false,"usgs":true,"family":"DeShon","given":"Heather","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":712998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magnani, M. Beatrice","contributorId":197231,"corporation":false,"usgs":false,"family":"Magnani","given":"M. Beatrice","affiliations":[],"preferred":false,"id":712999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walter, Jacob I.","contributorId":147406,"corporation":false,"usgs":false,"family":"Walter","given":"Jacob I.","affiliations":[{"id":16842,"text":"U Texas Austin","active":true,"usgs":false}],"preferred":false,"id":713000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quinones, Louis","contributorId":197233,"corporation":false,"usgs":false,"family":"Quinones","given":"Louis","email":"","affiliations":[],"preferred":false,"id":713001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":713002,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hornbach, Matthew J.","contributorId":14258,"corporation":false,"usgs":true,"family":"Hornbach","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":713003,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70191552,"text":"70191552 - 2017 - Forecast first: An argument for groundwater modeling in reverse","interactions":[],"lastModifiedDate":"2017-10-17T10:24:51","indexId":"70191552","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Forecast first: An argument for groundwater modeling in reverse","docAbstract":"Numerical groundwater models are important compo-nents of groundwater analyses that are used for makingcritical decisions related to the management of ground-water resources. In this support role, models are oftenconstructed to serve a specific purpose that is to provideinsights, through simulation, related to a specific func-tion of a complex aquifer system that cannot be observeddirectly (Anderson et al. 2015).
For any given modeling analysis, several modelinput datasets must be prepared. Herein, the datasetsrequired to simulate the historical conditions are referredto as the calibration model, and the datasets requiredto simulate the model’s purpose are referred to as theforecast model. Future groundwater conditions or otherunobserved aspects of the groundwater system may besimulated by the forecast model—the outputs of interestfrom the forecast model represent the purpose of themodeling analysis. Unfortunately, the forecast model,needed to simulate the purpose of the modeling analysis,is seemingly an afterthought—calibration is where themajority of time and effort are expended and calibrationis usually completed before the forecast model is evenconstructed. Herein, I am proposing a new groundwatermodeling workflow, referred to as the “forecast first”workflow, where the forecast model is constructed at anearlier stage in the modeling analysis and the outputsof interest from the forecast model are evaluated duringsubsequent tasks in the workflow.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12558","usgsCitation":"White, J.T., 2017, Forecast first: An argument for groundwater modeling in reverse: Groundwater, v. 55, no. 5, p. 660-664, https://doi.org/10.1111/gwat.12558.","productDescription":"5 p.","startPage":"660","endPage":"664","ipdsId":"IP-085148","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":346670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-03","publicationStatus":"PW","scienceBaseUri":"59e7168ee4b05fe04cd33174","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712742,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70263401,"text":"70263401 - 2017 - FinDer v.2: Improved real-time ground-motion predictions for M2-M9 with seismic finite-source characterization","interactions":[],"lastModifiedDate":"2025-02-10T15:32:10.488528","indexId":"70263401","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"FinDer v.2: Improved real-time ground-motion predictions for M2-M9 with seismic finite-source characterization","docAbstract":"Recent studies suggest that small and large earthquakes nucleate similarly, and that they often have indistinguishable seismic waveform onsets. The characterization of earthquakes in real time, such as for earthquake early warning, therefore requires a flexible modeling approach that allows a small earthquake to become large as fault rupture evolves over time. Here, we present a modeling approach that generates a set of output parameters and uncertainty estimates that are consistent with both small/moderate (≤M6.5) and large earthquakes (>M6.5) as is required for a robust parameter interpretation and shaking forecast. Our approach treats earthquakes over the entire range of magnitudes (>M2) as finite line-source ruptures, with the dimensions of small earthquakes being very small (<100 m) and those of large earthquakes exceeding several tens to hundreds of kilometres in length. The extent of the assumed line source is estimated from the level and distribution of high-frequency peak acceleration amplitudes observed in a local seismic network. High-frequency motions are well suited for this approach, because they are mainly controlled by the distance to the rupturing fault. Observed ground-motion patterns are compared with theoretical templates modeled from empirical ground-motion prediction equations to determine the best line source and uncertainties. Our algorithm extends earlier work by Böse et al. for large finite-fault ruptures. This paper gives a detailed summary of the new algorithm and its offline performance for the 2016 M7.0 Kumamoto, Japan and 2014 M6.0 South Napa, California earthquakes, as well as its performance for about 100 real-time detected local earthquakes (2.2 ≤ M ≤ 5.1) in California. For most events, both the rupture length and the strike are well constrained within a few seconds (<10 s) of the event origin. In large earthquakes, this could allow for providing warnings of up to several tens of seconds. The algorithm could also be useful for resolving fault plane ambiguities of focal mechanisms and identification of rupturing faults for earthquakes as small as M2.5.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggx430","usgsCitation":"Boese, M., Smith, D., Felizardo, C., Meier, M., Heaton, T.H., and Clinton, J., 2017, FinDer v.2: Improved real-time ground-motion predictions for M2-M9 with seismic finite-source characterization: Geophysical Journal International, v. 212, no. 1, p. 725-742, https://doi.org/10.1093/gji/ggx430.","productDescription":"18 p.","startPage":"725","endPage":"742","ipdsId":"IP-087811","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482056,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggx430","text":"Publisher Index Page"},{"id":481858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan, United 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Maren","contributorId":350745,"corporation":false,"usgs":false,"family":"Boese","given":"Maren","affiliations":[{"id":80868,"text":"ETH","active":true,"usgs":false}],"preferred":false,"id":926851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Deborah 0000-0002-8317-7762","orcid":"https://orcid.org/0000-0002-8317-7762","contributorId":201885,"corporation":false,"usgs":true,"family":"Smith","given":"Deborah","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Felizardo, Claude","contributorId":201876,"corporation":false,"usgs":false,"family":"Felizardo","given":"Claude","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":926853,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meier, Men-Andrin 0000-0002-2949-8602","orcid":"https://orcid.org/0000-0002-2949-8602","contributorId":293577,"corporation":false,"usgs":false,"family":"Meier","given":"Men-Andrin","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":926854,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heaton, Thomas H.","contributorId":187505,"corporation":false,"usgs":false,"family":"Heaton","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":926855,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clinton, J.F.","contributorId":350746,"corporation":false,"usgs":false,"family":"Clinton","given":"J.F.","affiliations":[{"id":80868,"text":"ETH","active":true,"usgs":false}],"preferred":false,"id":926856,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191659,"text":"70191659 - 2017 - Protected areas as social-ecological systems: perspectives from resilience and social-ecological systems theory","interactions":[],"lastModifiedDate":"2017-10-17T16:08:31","indexId":"70191659","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Protected areas as social-ecological systems: perspectives from resilience and social-ecological systems theory","docAbstract":"Conservation biology and applied ecology increasingly recognize that natural resource management is both an outcome and a driver of social, economic, and ecological dynamics. Protected areas offer a fundamental approach to conserving ecosystems, but they are also social-ecological systems whose ecological management and sustainability are heavily influenced by people. This editorial, and the papers in the invited feature that it introduces, discuss three emerging themes in social-ecological systems approaches to understanding protected areas: (1) the resilience and sustainability of protected areas, including analyses of their internal dynamics, their effectiveness, and the resilience of the landscapes within which they occur; (2) the relevance of spatial context and scale for protected areas, including such factors as geographic connectivity, context, exchanges between protected areas and their surrounding landscapes, and scale dependency in the provision of ecosystem services; and (3) efforts to reframe what protected areas are and how they both define and are defined by the relationships of people and nature. These emerging themes have the potential to transform management and policy approaches for protected areas and have important implications for conservation, in both theory and practice.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1584","usgsCitation":"Cumming, G.S., and Allen, C.R., 2017, Protected areas as social-ecological systems: perspectives from resilience and social-ecological systems theory: Ecological Applications, v. 27, no. 6, p. 1709-1717, https://doi.org/10.1002/eap.1584.","productDescription":"9 p.","startPage":"1709","endPage":"1717","ipdsId":"IP-066373","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-17","publicationStatus":"PW","scienceBaseUri":"59e7168de4b05fe04cd3316d","contributors":{"authors":[{"text":"Cumming, Graeme S.","contributorId":39191,"corporation":false,"usgs":true,"family":"Cumming","given":"Graeme","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":713010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":712975,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191542,"text":"70191542 - 2017 - Influence of pore pressure change on coseismic volumetric strain","interactions":[],"lastModifiedDate":"2017-10-17T11:00:00","indexId":"70191542","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Influence of pore pressure change on coseismic volumetric strain","docAbstract":"Coseismic strain is fundamentally important for understanding crustal response to changes of stress after earthquakes. The elastic dislocation model has been widely applied to interpreting observed shear deformation caused by earthquakes. The application of the same theory to interpreting volumetric strain, however, has met with difficulty, especially in the far field of earthquakes. Predicted volumetric strain with dislocation model often differs substantially, and sometimes of opposite signs, from observed coseismic volumetric strains. The disagreement suggests that some processes unaccounted for by the dislocation model may occur during earthquakes. Several hypotheses have been suggested, but none have been tested quantitatively. In this paper we first examine published data to highlight the difference between the measured and calculated static coseismic volumetric strains; we then use these data to provide quantitative test of the model that the disagreement may be explained by the change of pore pressure in the shallow crust. The test allows us to conclude that coseismic change of pore pressure may be an important mechanism for coseismic crustal strain and, in the far field, may even be the dominant mechanism. Thus in the interpretation of observed coseismic crustal strain, one needs to account not only for the elastic strain due to fault rupture but also for the strain due to coseismic change of pore pressure.
","language":"English","publisher":"Springer","doi":"10.1016/j.epsl.2017.07.034","usgsCitation":"Wang, C., and Barbour, A., 2017, Influence of pore pressure change on coseismic volumetric strain: Earth and Planetary Science Letters, v. 475, p. 152-159, https://doi.org/10.1016/j.epsl.2017.07.034.","productDescription":"8 p.","startPage":"152","endPage":"159","ipdsId":"IP-085682","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469434,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2017.07.034","text":"Publisher Index Page"},{"id":346678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"475","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e7168ee4b05fe04cd3317d","contributors":{"authors":[{"text":"Wang, Chi-Yuen","contributorId":20001,"corporation":false,"usgs":true,"family":"Wang","given":"Chi-Yuen","affiliations":[],"preferred":false,"id":712711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barbour, Andrew J. 0000-0002-6890-2452 abarbour@usgs.gov","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":140443,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew J.","email":"abarbour@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":712710,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191662,"text":"70191662 - 2017 - Defining ecological drought for the 21st century","interactions":[],"lastModifiedDate":"2018-04-24T12:10:02","indexId":"70191662","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"Defining ecological drought for the 21st century","docAbstract":"No abstract available.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-16-0292.1","usgsCitation":"Crausbay, S.D., Ramirez, A.R., Carter, S.L., Cross, M.S., Hall, K.R., Bathke, D.J., Betancourt, J.L., Colt, S., Cravens, A.E., Dalton, M.S., Dunham, J.B., Hay, L.E., Hayes, M., McEvoy, J., McNutt, C.A., Moritz, M.A., Nislow, K.H., Raheem, N., and Sanford, T., 2017, Defining ecological drought for the 21st century: Bulletin of the American Meteorological Society, v. 98, p. 2543-2550, https://doi.org/10.1175/BAMS-D-16-0292.1.","productDescription":"8 p.","startPage":"2543","endPage":"2550","ipdsId":"IP-077088","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":469433,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.montana.edu/xmlui/handle/1/17158","text":"External Repository"},{"id":346740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e7168de4b05fe04cd33169","contributors":{"authors":[{"text":"Crausbay, Shelley D.","contributorId":197220,"corporation":false,"usgs":false,"family":"Crausbay","given":"Shelley","email":"","middleInitial":"D.","affiliations":[{"id":54831,"text":"Conservation Science Partners, Inc","active":true,"usgs":false}],"preferred":false,"id":712980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramirez, Aaron R.","contributorId":149780,"corporation":false,"usgs":false,"family":"Ramirez","given":"Aaron","email":"","middleInitial":"R.","affiliations":[{"id":17824,"text":"UC Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":712979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Shawn L. 0000-0002-0045-4681 scarter@usgs.gov","orcid":"https://orcid.org/0000-0002-0045-4681","contributorId":3110,"corporation":false,"usgs":true,"family":"Carter","given":"Shawn","email":"scarter@usgs.gov","middleInitial":"L.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":712978,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cross, Molly S. 0000-0002-4238-9208","orcid":"https://orcid.org/0000-0002-4238-9208","contributorId":149216,"corporation":false,"usgs":false,"family":"Cross","given":"Molly","middleInitial":"S.","affiliations":[{"id":17674,"text":"Wildlife Conservation Society, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":712981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Kimberly R.","contributorId":197221,"corporation":false,"usgs":false,"family":"Hall","given":"Kimberly","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":712982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bathke, Deborah J.","contributorId":197224,"corporation":false,"usgs":false,"family":"Bathke","given":"Deborah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712991,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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Central Branch","active":true,"usgs":true}],"preferred":true,"id":712988,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hayes, Michael J.","contributorId":197222,"corporation":false,"usgs":false,"family":"Hayes","given":"Michael J.","affiliations":[{"id":34856,"text":"National Drought Mitigation Center, Unversity of Nebraska","active":true,"usgs":false}],"preferred":false,"id":712989,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McEvoy, Jamie","contributorId":197223,"corporation":false,"usgs":false,"family":"McEvoy","given":"Jamie","affiliations":[],"preferred":false,"id":712990,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"McNutt, Chad A.","contributorId":197225,"corporation":false,"usgs":false,"family":"McNutt","given":"Chad","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712992,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Moritz, Max A.","contributorId":182434,"corporation":false,"usgs":false,"family":"Moritz","given":"Max","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712993,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Nislow, Keith H.","contributorId":197226,"corporation":false,"usgs":false,"family":"Nislow","given":"Keith","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":712994,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Raheem, Nejem","contributorId":197227,"corporation":false,"usgs":false,"family":"Raheem","given":"Nejem","email":"","affiliations":[],"preferred":false,"id":712995,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Sanford, Todd","contributorId":197228,"corporation":false,"usgs":false,"family":"Sanford","given":"Todd","email":"","affiliations":[],"preferred":false,"id":712996,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70191549,"text":"70191549 - 2017 - Millennial-scale variability in the local radiocarbon reservoir age of south Florida during the Holocene","interactions":[],"lastModifiedDate":"2017-10-17T10:34:50","indexId":"70191549","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3216,"text":"Quaternary Geochronology","active":true,"publicationSubtype":{"id":10}},"title":"Millennial-scale variability in the local radiocarbon reservoir age of south Florida during the Holocene","docAbstract":"A growing body of research suggests that the marine environments of south Florida provide a critical link between the tropical and high-latitude Atlantic. Changes in the characteristics of water masses off south Florida may therefore have important implications for our understanding of climatic and oceanographic variability over a broad spatial scale; however, the sources of variability within this oceanic corridor remain poorly understood. Measurements of ΔR, the local offset of the radiocarbon reservoir age, from shallow-water marine environments can serve as a powerful tracer of water-mass sources that can be used to reconstruct variability in local-to regional-scale oceanography and hydrology. We combined radiocarbon and U-series measurements of Holocene-aged corals from the shallow-water environments of the Florida Keys reef tract (FKRT) with robust statistical modeling to quantify the millennial-scale variability in ΔR at locations with (“nearshore”) and without (“open ocean”) substantial terrestrial influence. Our reconstructions demonstrate that there was significant spatial and temporal variability in ΔR on the FKRT during the Holocene. Whereas ΔR was similar throughout the region after ∼4000 years ago, nearshore ΔR was significantly higher than in the open ocean during the middle Holocene. We suggest that the elevated nearshore ΔR from ∼8000 to 5000 years ago was most likely the result of greater groundwater influence associated with lower sea level at this time. In the open ocean, which would have been isolated from the influence of groundwater, ΔR was lowest ∼7000 years ago, and was highest ∼3000 years ago. We evaluated our open-ocean model of ΔR variability against records of local-to regional-scale oceanography and conclude that local upwelling was not a significant driver of open-ocean radiocarbon variability in this region. Instead, the millennial-scale trends in open-ocean ΔR were more likely a result of broader-scale changes in western Atlantic circulation associated with an increase in the supply of equatorial South Atlantic water to the Caribbean and shifts in the character of South Atlantic waters resulting from variation in the intensity of upwelling off the southwest coast of Africa. Because accurate estimates of ΔR are critical to precise calibrations of radiocarbon dates from marine samples, we also developed models of nearshore and open-ocean ΔR versus conventional 14C ages that can be used for regional radiocarbon calibrations for the Holocene. Our study provides new insights into the patterns and drivers of oceanographic and hydrologic variability in the Straits of Florida and highlights the value of the paleoceanographic records from south Florida to our understanding of Holocene changes in climate and ocean circulation throughout the Atlantic.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quageo.2017.07.005","usgsCitation":"Toth, L., Cheng, H., Edwards, R., Ashe, E., and Richey, J.N., 2017, Millennial-scale variability in the local radiocarbon reservoir age of south Florida during the Holocene: Quaternary Geochronology, v. 42, p. 130-143, https://doi.org/10.1016/j.quageo.2017.07.005.","productDescription":"14 p.","startPage":"130","endPage":"143","ipdsId":"IP-084508","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":461385,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quageo.2017.07.005","text":"Publisher Index Page"},{"id":438188,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P8492Q","text":"USGS data release","linkHelpText":"Local Radiocarbon Reservoir Age (Delta-R) Variability from the Nearshore and Open-Ocean Environments of the Florida Keys Reef Tract During the Holocene and Associated U-Series and Radiocarbon Data"},{"id":346672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.04290771484374,\n 24.492147541216028\n ],\n [\n -80.15625,\n 24.492147541216028\n ],\n [\n -80.15625,\n 25.535006795752302\n ],\n [\n -83.04290771484374,\n 25.535006795752302\n ],\n [\n -83.04290771484374,\n 24.492147541216028\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e7168ee4b05fe04cd33178","contributors":{"authors":[{"text":"Toth, Lauren T. ltoth@usgs.gov","contributorId":149483,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren T.","email":"ltoth@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":712730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheng, Hai","contributorId":85896,"corporation":false,"usgs":true,"family":"Cheng","given":"Hai","affiliations":[],"preferred":false,"id":712743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, R. 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Many migratory species provide ecosystem service benefits to society. For example, insectivorous bats prey on crop pests and reduce the need for pesticides; birds and insects pollinate food plants; and birds afford recreational opportunities to hunters and birdwatchers. Migration is driven by the seasonal availability of resources; as resources in one area become seasonally scarce, individuals move to locations where resources have become seasonally abundant. The separation of the annual lifecycle means that species management and governance is often fractured across international borders. Because migratory species depend on habitat in different locations, their ability to provide ecosystem services in one area depends on the spatial subsidies, or support, provided by habitat and ecological processes in other areas. This creates telecouplings, or interconnections across geographic space, of areas such that impacts to the habitat of a migratory species in one location will affect the benefits enjoyed by people in other locations. Information about telecoupling and spatial subsidies can be used to craft new governance arrangements such as Payment for Ecosystem Services programs that target specific stakeholder groups and locations. We illustrate these challenges and opportunities with three North American case studies: the Duck Stamp Program, Mexican free-tailed bats (Tadarida brasiliensis mexicana), and monarch butterflies (Danaus plexippus).
","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-environ-110615-090119","usgsCitation":"Lopez-Hoffman, L., Chester, C.C., Semmens, D.J., Thogmartin, W.E., Rodriguez-McGoffin, M.S., Merideth, R.W., and Diffendorfer, J.E., 2017, Ecosystem services from transborder migratory species: Implications for conservation governance: Annual Review of Environment and Resources, v. 42, p. 509-539, https://doi.org/10.1146/annurev-environ-110615-090119.","productDescription":"31 p.","startPage":"509","endPage":"539","ipdsId":"IP-084535","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":469436,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1146/annurev-environ-110615-090119","text":"Publisher Index Page"},{"id":346718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e7168ee4b05fe04cd33171","contributors":{"authors":[{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":712926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chester, Charles C.","contributorId":197202,"corporation":false,"usgs":false,"family":"Chester","given":"Charles","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":712927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":712925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":712928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodriguez-McGoffin, M. 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To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the Cascade Mountains, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous Change Detection and Classification (CCDC) algorithm to Landsat satellite imagery collected from 1985 to 2014. We calculated metrics of landscape pattern using patches of intact and harvested forest in each annual layer to identify changes throughout the time series. Patch dynamics revealed four distinct eras of logging trends that align with prevailing regulations and economic conditions. We used multiple logistic regression to determine the biophysical and anthropogenic factors that influence fine-scale selection of harvest stands in each time period. Results show that private lands forest cover became significantly reduced and more fragmented from 1985 to 2014. Variables linked to parameters of site conditions, location, climate, and vegetation greenness consistently distinguished harvest selection for each distinct era. This study demonstrates the utility of annual LULC data for investigating the underlying factors that influence land cover change.
","language":"English","publisher":"MDPI","doi":"10.3390/f8100383","usgsCitation":"Soulard, C.E., Walker, J.J., and Griffith, G.E., 2017, Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA: Forests, v. 8, no. 10, p. 1-18, https://doi.org/10.3390/f8100383.","productDescription":"Article 383; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-090964","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469435,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f8100383","text":"Publisher Index Page"},{"id":438189,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X63KWW","text":"USGS data release","linkHelpText":"Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA"},{"id":347269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Cascade Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.33276367187499,\n 45.767522962149876\n ],\n [\n -119.80590820312499,\n 45.767522962149876\n ],\n [\n -119.80590820312499,\n 49.009050809382046\n ],\n [\n -122.33276367187499,\n 49.009050809382046\n ],\n [\n -122.33276367187499,\n 45.767522962149876\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-07","publicationStatus":"PW","scienceBaseUri":"59f05120e4b0220bbd9a1d79","contributors":{"authors":[{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":714098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Jessica J. 0000-0002-3225-0317 jjwalker@usgs.gov","orcid":"https://orcid.org/0000-0002-3225-0317","contributorId":169458,"corporation":false,"usgs":true,"family":"Walker","given":"Jessica","email":"jjwalker@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":714099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griffith, Glenn E. 0000-0001-7966-4720 ggriffith@usgs.gov","orcid":"https://orcid.org/0000-0001-7966-4720","contributorId":4053,"corporation":false,"usgs":true,"family":"Griffith","given":"Glenn","email":"ggriffith@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":714100,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191368,"text":"ofr20171130 - 2017 - Conceptual modeling framework to support development of site-specific selenium criteria for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada","interactions":[],"lastModifiedDate":"2017-10-17T10:08:39","indexId":"ofr20171130","displayToPublicDate":"2017-10-16T17:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1130","title":"Conceptual modeling framework to support development of site-specific selenium criteria for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada","docAbstract":"The U.S. Geological Survey, working with the Montana Department of Environmental Quality and the British Columbia Ministry of the Environment and Climate Change Strategy, has developed a conceptual modeling framework that can be used to provide structured and scientifically based input to the Lake Koocanusa Monitoring and Research Working Group as they consider potential site-specific selenium criteria for Lake Koocanusa, a transboundary reservoir located in Montana and British Columbia. This report describes that modeling framework, provides an example of how it can be applied, and outlines possible next steps for implementing the framework.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171130","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality","usgsCitation":"Jenni, K.E., Naftz, D.L., and Presser, T.S., 2017, Conceptual modeling framework to support development of site-specific selenium criteria for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada: U.S. Geological Survey Open-File Report 2017–1130, 14 p., https://doi.org/10.3133/ofr20171130.","productDescription":"Report: iv, 14 p.; Data Release","numberOfPages":"22","onlineOnly":"N","ipdsId":"IP-091389","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":346538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1130/coverthb.jpg"},{"id":346541,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/F7ZP44C9","text":"USGS Data Release – ","description":"USGS Data Release","linkHelpText":"USGS Measurements of Dissolved and Suspended Particulate Material Selenium in Lake Koocanusa in the Vicinity of Libby Dam (MT), 2015–2016"},{"id":346539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1130/ofr20171130.pdf","text":"Report","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1130"}],"country":"Canada, United States","state":"British Columbia, Montana","otherGeospatial":" Lake Koocanusa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.98266601562499,\n 48.356249029540734\n ],\n [\n -114.8565673828125,\n 48.356249029540734\n ],\n [\n -114.8565673828125,\n 50.42601852427907\n ],\n [\n -115.98266601562499,\n 50.42601852427907\n ],\n [\n -115.98266601562499,\n 48.356249029540734\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Thermal regimes are fundamental determinants of aquatic ecosystems, which makes description and prediction of temperatures critical during a period of rapid global change. The advent of inexpensive temperature sensors dramatically increased monitoring in recent decades, and although most monitoring is done by individuals for agency‐specific purposes, collectively these efforts constitute a massive distributed sensing array that generates an untapped wealth of data. Using the framework provided by the National Hydrography Dataset, we organized temperature records from dozens of agencies in the western U.S. to create the NorWeST database that hosts >220,000,000 temperature recordings from >22,700 stream and river sites. Spatial‐stream‐network models were fit to a subset of those data that described mean August water temperatures (AugTw) during 63,641 monitoring site‐years to develop accurate temperature models (r2 = 0.91; RMSPE = 1.10°C; MAPE = 0.72°C), assess covariate effects, and make predictions at 1 km intervals to create summer climate scenarios. AugTw averaged 14.2°C (SD = 4.0°C) during the baseline period of 1993–2011 in 343,000 km of western perennial streams but trend reconstructions also indicated warming had occurred at the rate of 0.17°C/decade (SD = 0.067°C/decade) during the 40 year period of 1976–2015. Future scenarios suggest continued warming, although variation will occur within and among river networks due to differences in local climate forcing and stream responsiveness. NorWeST scenarios and data are available online in user‐friendly digital formats and are widely used to coordinate monitoring efforts among agencies, for new research, and for conservation planning.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017WR020969","usgsCitation":"Isaak, D.J., Wenger, S.J., Peterson, E.E., Ver Hoef, J.M., Nagel, D., Luce, C.H., Hostetler, S.W., Dunham, J.B., Roper, B.B., Wollrab, S., Chandler, G.L., Horan, D., and Parkes-Payne, S., 2017, The NorWeST summer stream temperature model and scenarios for the western U.S.: A crowd-sourced database and new geospatial tools foster a user-community and predict broad climate warming of rivers and streams: Water Resources Research, v. 53, no. 11, p. 9181-9205, https://doi.org/10.1002/2017WR020969.","productDescription":"25 p.","startPage":"9181","endPage":"9205","ipdsId":"IP-090157","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":438,"text":"National Research 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\"}}]}","volume":"53","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Isaak, Daniel J.","contributorId":177835,"corporation":false,"usgs":false,"family":"Isaak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":766575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wenger, Seth J.","contributorId":64786,"corporation":false,"usgs":true,"family":"Wenger","given":"Seth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":766576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Erin E.","contributorId":177839,"corporation":false,"usgs":false,"family":"Peterson","given":"Erin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":766577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ver Hoef, Jay 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0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":766581,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science 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volcano","interactions":[],"lastModifiedDate":"2024-10-29T14:37:03.70833","indexId":"70260163","displayToPublicDate":"2017-10-16T09:33:03","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7602,"text":"Eos, American Geophysical Union","active":true,"publicationSubtype":{"id":10}},"title":"Volcanic unrest at Mauna Loa, Earth's largest active volcano","docAbstract":"Mauna Loa is showing persistent signs of volcanic unrest. Since 2014, increased seismicity and deformation indicate that Mauna Loa, the volcano that dominates more than half of the island of Hawaiʻi, may be building toward its first eruption since 1984.
Thousands of residents and key infrastructure are potentially at risk from lava flows, so a critical question is whether the volcano will follow patterns of previous eruptions or return to its now historically unprecedented 33-year slumber.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2017EO083937","usgsCitation":"Thelen, W., Mikijus, A., and Neal, C.A., 2017, Volcanic unrest at Mauna Loa, Earth's largest active volcano: Eos, American Geophysical Union, HTML Document, https://doi.org/10.1029/2017EO083937.","productDescription":"HTML Document","ipdsId":"IP-085728","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469438,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017eo083937","text":"Publisher Index Page"},{"id":463336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.77507649188428,\n 19.686539008086896\n ],\n [\n -155.77507649188428,\n 19.20945444941283\n ],\n [\n -155.34842869991644,\n 19.20945444941283\n ],\n [\n -155.34842869991644,\n 19.686539008086896\n ],\n [\n -155.77507649188428,\n 19.686539008086896\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thelen, Weston 0000-0003-2534-5577","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":215530,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mikijus, Asta 0000-0002-2286-1886","orcid":"https://orcid.org/0000-0002-2286-1886","contributorId":80431,"corporation":false,"usgs":true,"family":"Mikijus","given":"Asta","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":917278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neal, Christina A. 0000-0002-7697-7825 tneal@usgs.gov","orcid":"https://orcid.org/0000-0002-7697-7825","contributorId":131135,"corporation":false,"usgs":true,"family":"Neal","given":"Christina","email":"tneal@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917279,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191508,"text":"70191508 - 2017 - Increasing floodplain connectivity through urban stream restoration increases nutrient and sediment retention","interactions":[],"lastModifiedDate":"2017-10-16T09:50:37","indexId":"70191508","displayToPublicDate":"2017-10-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Increasing floodplain connectivity through urban stream restoration increases nutrient and sediment retention","docAbstract":"Stream restoration practices frequently aim to increase connectivity between the stream channel and its floodplain to improve channel stability and enhance water quality through sediment trapping and nutrient retention. To measure the effectiveness of restoration and to understand the drivers of these functional responses, we monitored five restored urban streams that represent a range of channel morphology and restoration ages. High and low elevation floodplain plots were established in triplicate in each stream to capture variation in floodplain connectivity. We measured ecosystem geomorphic and soil attributes, sediment and nutrient loading, and rates of soil nutrient biogeochemistry processes (denitrification; N and P mineralization) then used boosted regression trees (BRT) to identify controls on sedimentation and nutrient processing. Local channel and floodplain morphology and position within the river network controlled connectivity with increased sedimentation at sites downstream of impaired reaches and at floodplain plots near the stream channel and at low elevations. We observed that nitrogen loading (both dissolved and particulate) was positively correlated with denitrification and N mineralization and dissolved phosphate loading positively influenced P mineralization; however, none of these input rates or transformations differed between floodplain elevation categories. Instead, continuous gradients of connectivity were observed rather than categorical shifts between inset and high floodplains. Organic matter and nutrient content in floodplain soils increased with the time since restoration, which highlights the importance of recovery time after construction that is needed for restored systems to increase ecosystem functions. Our results highlight the importance of restoring floodplains downstream of sources of impairment and building them at lower elevations so they flood frequently, not just during bankfull events. This integrated approach has the greatest potential for increasing trapping of sediment, nutrients, and associated pollutants in restored streams and thereby improving water quality in urban watersheds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2017.08.006","usgsCitation":"McMillan, S., and Noe, G.E., 2017, Increasing floodplain connectivity through urban stream restoration increases nutrient and sediment retention: Ecological Engineering, v. 108, no. A, p. 284-295, https://doi.org/10.1016/j.ecoleng.2017.08.006.","productDescription":"12 p.","startPage":"284","endPage":"295","ipdsId":"IP-088155","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":346621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","county":"Mecklenburg County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-80.7823,35.5113],[-80.7867,35.5031],[-80.7889,35.4949],[-80.7831,35.4836],[-80.7819,35.475],[-80.7779,35.4668],[-80.7778,35.4614],[-80.7744,35.4578],[-80.7549,35.423],[-80.7525,35.4148],[-80.7553,35.4125],[-80.7638,35.4134],[-80.7693,35.402],[-80.7551,35.3944],[-80.7364,35.3786],[-80.7187,35.3624],[-80.704,35.3552],[-80.6983,35.3507],[-80.6822,35.3131],[-80.6677,35.2705],[-80.6214,35.2499],[-80.5954,35.2369],[-80.5485,35.2108],[-80.6245,35.1487],[-80.7328,35.0627],[-80.7645,35.0375],[-80.7684,35.0348],[-80.7746,35.0329],[-80.7858,35.0315],[-80.7892,35.0314],[-80.8009,35.0286],[-80.8155,35.0204],[-80.8194,35.019],[-80.8216,35.018],[-80.8216,35.0167],[-80.8288,35.0098],[-80.835,35.0061],[-80.8405,35.0016],[-80.8604,35.0246],[-80.8854,35.0535],[-80.9016,35.0716],[-80.9312,35.1049],[-80.9373,35.1018],[-81.0383,35.0452],[-81.0419,35.0432],[-81.0447,35.0468],[-81.0464,35.0482],[-81.0483,35.0507],[-81.0503,35.0527],[-81.0528,35.0557],[-81.0548,35.0582],[-81.0568,35.0611],[-81.0577,35.0636],[-81.0586,35.067],[-81.0582,35.0722],[-81.0577,35.0788],[-81.0566,35.0834],[-81.0554,35.0868],[-81.0541,35.0904],[-81.0533,35.0927],[-81.0523,35.0956],[-81.0503,35.0975],[-81.0487,35.099],[-81.0462,35.1003],[-81.0437,35.1014],[-81.042,35.1022],[-81.0391,35.1027],[-81.0369,35.1036],[-81.0352,35.1054],[-81.0344,35.1072],[-81.0341,35.1095],[-81.0341,35.1136],[-81.0358,35.1186],[-81.0363,35.1213],[-81.038,35.124],[-81.0408,35.1267],[-81.0425,35.1281],[-81.0454,35.1289],[-81.0476,35.1295],[-81.0499,35.1302],[-81.051,35.1313],[-81.0521,35.1335],[-81.0523,35.1365],[-81.0517,35.1392],[-81.0501,35.142],[-81.0476,35.1463],[-81.0448,35.1494],[-81.0238,35.1486],[-81.0176,35.1536],[-81.0109,35.1532],[-81.0076,35.1569],[-81.0088,35.165],[-81.0049,35.1728],[-81.0045,35.1814],[-81.0046,35.1864],[-81.0063,35.1923],[-81.0064,35.1973],[-81.0054,35.2055],[-81.0071,35.2109],[-81.0129,35.2231],[-81.0113,35.2309],[-81.012,35.2349],[-81.0082,35.2509],[-81.0139,35.2585],[-81.0152,35.2685],[-81.0143,35.2876],[-81.0133,35.293],[-81.0105,35.2944],[-81.0033,35.3017],[-81.0022,35.3045],[-80.9961,35.3113],[-80.9938,35.3132],[-80.9894,35.3205],[-80.9844,35.3237],[-80.9805,35.3287],[-80.9823,35.3341],[-80.984,35.3373],[-80.9818,35.3446],[-80.9706,35.3501],[-80.9656,35.3506],[-80.9593,35.3489],[-80.9537,35.3521],[-80.9442,35.3521],[-80.9374,35.3572],[-80.9285,35.3614],[-80.9268,35.3627],[-80.9296,35.3636],[-80.9432,35.3658],[-80.9505,35.3675],[-80.9563,35.3738],[-80.9597,35.3756],[-80.9625,35.3756],[-80.9647,35.3738],[-80.9669,35.3688],[-80.9697,35.3669],[-80.9742,35.3642],[-80.9776,35.3646],[-80.9844,35.3695],[-80.9868,35.38],[-80.9846,35.3822],[-80.9806,35.3823],[-80.9761,35.3828],[-80.9632,35.3901],[-80.9554,35.3925],[-80.9549,35.4006],[-80.959,35.4133],[-80.9569,35.4288],[-80.9587,35.436],[-80.9527,35.446],[-80.9465,35.4524],[-80.9421,35.457],[-80.9432,35.4602],[-80.9506,35.4656],[-80.9518,35.4701],[-80.948,35.481],[-80.947,35.486],[-80.951,35.4942],[-80.9612,35.4986],[-80.9664,35.509],[-80.9637,35.5131],[-80.9586,35.5163],[-80.9569,35.5177],[-80.7823,35.5113]]]},\"properties\":{\"name\":\"Mecklenburg\",\"state\":\"NC\"}}]}","volume":"108","issue":"A","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e5c519e4b05fe04cd1c9c6","contributors":{"authors":[{"text":"McMillan, Sara K.","contributorId":197089,"corporation":false,"usgs":false,"family":"McMillan","given":"Sara K.","affiliations":[],"preferred":false,"id":712530,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":712529,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191491,"text":"70191491 - 2017 - Evaluating upstream passage and timing of approach by adult bigheaded carps at a gated dam on the Illinois River","interactions":[],"lastModifiedDate":"2017-10-16T10:09:52","indexId":"70191491","displayToPublicDate":"2017-10-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating upstream passage and timing of approach by adult bigheaded carps at a gated dam on the Illinois River","docAbstract":"Dams are a conservation threat because they function as barriers to native fish movement; however, they may prevent the spread of invasive species. Invasive bigheaded carps (Hypophthalmichthys spp.) threaten the Great Lakes ecosystem and are advancing towards Lake Michigan via the Illinois River. Navigation dams on the Illinois River may deter bigheaded carps' upstream movement. We investigated the permeability of the Starved Rock Lock and Dam (SRLD), the most downstream gated Illinois River dam, to bigheaded carps' migration by examining the timing of individuals approaching and passing through SRLD in relation to gate openness, tailwater elevation, and water temperature. Using acoustic telemetry of (N = ~104 per year) tagged fish, 13 upstream passages of bigheaded carps occurred through SRLD between 2013 and 2016. Eleven passages occurred through the dam gates and 2 through the lock chamber, indicating deterrents (e.g., CO2) placed in SRLD lock chamber may only limit passage of a small proportion of all fish passing through the lock-and-dam structure. Passages were documented only in 2013 and 2015. Most of the dam gate passages occurred during high water when gates were completely out of the water. Timing of bigheaded carps approaching SRLD was positively correlated with rising water temperature and high tailwater elevation, and all fish approached during late March through mid-September. Movement through dams is rare; modifying gate operations to reduce gate openness during late spring and summer could further reduce the permeability of gated dams such as SRLD to bigheaded carps, slowing their upstream advance.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3180","usgsCitation":"Lubejko, M., Whitledge, G., Coulter, A.A., Brey, M.K., Oliver, D., and Garvey, J.E., 2017, Evaluating upstream passage and timing of approach by adult bigheaded carps at a gated dam on the Illinois River: River Research and Applications, v. 33, no. 8, p. 1268-1278, https://doi.org/10.1002/rra.3180.","productDescription":"11 p.","startPage":"1268","endPage":"1278","ipdsId":"IP-084443","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":346624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River, Starved Rock Lock and Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.04041290283203,\n 41.308502890261764\n ],\n [\n -88.94634246826172,\n 41.308502890261764\n ],\n [\n -88.94634246826172,\n 41.333513657873205\n ],\n [\n -89.04041290283203,\n 41.333513657873205\n ],\n [\n -89.04041290283203,\n 41.308502890261764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"8","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-21","publicationStatus":"PW","scienceBaseUri":"59e5c51ae4b05fe04cd1c9ca","contributors":{"authors":[{"text":"Lubejko, Matthew","contributorId":195897,"corporation":false,"usgs":false,"family":"Lubejko","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":712426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitledge, Greg","contributorId":195898,"corporation":false,"usgs":false,"family":"Whitledge","given":"Greg","affiliations":[],"preferred":false,"id":712427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coulter, Alison A.","contributorId":187652,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":712425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oliver, Devon","contributorId":195899,"corporation":false,"usgs":false,"family":"Oliver","given":"Devon","affiliations":[],"preferred":false,"id":712429,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garvey, James E.","contributorId":178007,"corporation":false,"usgs":false,"family":"Garvey","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":712430,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191492,"text":"70191492 - 2017 - Effects of flood inundation and invasion by Phalaris arundinacea on nitrogen cycling in an Upper Mississippi River floodplain forest","interactions":[],"lastModifiedDate":"2022-11-02T13:53:22.124712","indexId":"70191492","displayToPublicDate":"2017-10-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effects of flood inundation and invasion by Phalaris arundinacea on nitrogen cycling in an Upper Mississippi River floodplain forest","title":"Effects of flood inundation and invasion by Phalaris arundinacea on nitrogen cycling in an Upper Mississippi River floodplain forest","docAbstract":"Although floodplains are thought to serve as important buffers against nitrogen (N) transport to aquatic systems, frequent flooding and high levels of nutrient availability also make these systems prone to invasion by exotic plant species. Invasive plants could modify the cycling and availability of nutrients within floodplains, with effects that could feedback to promote the persistence of the invasive species and impact N export to riverine and coastal areas. We examined the effect of flooding on soil properties and N cycling at a floodplain site in Pool 8 of the Upper Mississippi River with 2 plant communities: mature native forest (Acer saccharinum) and patches of an invasive grass (Phalaris arundinacea). Plots were established within each vegetation type along an elevation gradient and sampled throughout the summers of 2013 and 2014. Spatial trends in flooding resulted in higher soil organic matter, porosity, and total nitrogen and carbon in low elevations. Nutrient processes and NH4+ and NO3− availability, however, were best explained by vegetation type and time after flooding. Phalaris plots maintained higher rates of nitrification and higher concentrations of available NH4+ and NO3−. These results suggest that invasion by Phalarismay make nitrogen more readily available and could help to reinforce this species' persistence in floodplain wetlands. They also raise the possibility that Phalaris may decrease floodplain N storage capacity and influence downstream transport of N to coastal zones.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1877","usgsCitation":"Swanson, W., De Jager, N.R., Strauss, E.A., and Thomsen, M., 2017, Effects of flood inundation and invasion by Phalaris arundinacea on nitrogen cycling in an Upper Mississippi River floodplain forest: Ecohydrology, v. 10, no. 7, e1877; 12 p., https://doi.org/10.1002/eco.1877.","productDescription":"e1877; 12 p.","ipdsId":"IP-076663","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":346623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.2547981144141,\n 43.78463269677704\n ],\n [\n -91.2547981144141,\n 43.674577852975204\n ],\n [\n -91.18842801676165,\n 43.674577852975204\n ],\n [\n -91.18842801676165,\n 43.78463269677704\n ],\n [\n -91.2547981144141,\n 43.78463269677704\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"7","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-05","publicationStatus":"PW","scienceBaseUri":"59e5c51ae4b05fe04cd1c9c8","contributors":{"authors":[{"text":"Swanson, Whitney","contributorId":194558,"corporation":false,"usgs":false,"family":"Swanson","given":"Whitney","affiliations":[],"preferred":false,"id":712432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":712431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strauss, Eric A.","contributorId":190148,"corporation":false,"usgs":false,"family":"Strauss","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomsen, Meredith","contributorId":197064,"corporation":false,"usgs":false,"family":"Thomsen","given":"Meredith","affiliations":[],"preferred":false,"id":712434,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194633,"text":"70194633 - 2017 - A revised list of the freshwater mussels (Mollusca: Bivalvia: Unionida) of the United States and Canada","interactions":[],"lastModifiedDate":"2020-12-16T16:59:11.151556","indexId":"70194633","displayToPublicDate":"2017-10-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5254,"text":"Freshwater Mollusk Biology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A revised list of the freshwater mussels (Mollusca: Bivalvia: Unionida) of the United States and Canada","docAbstract":"We present a revised list of freshwater mussels (order Unionida, families Margaritiferidae and Unionidae) of the United States and Canada, incorporating changes in nomenclature and systematic taxonomy since publication of the most recent checklist in 1998. We recognize a total of 298 species in 55 genera in the families Margaritiferidae (one genus, five species) and Unionidae (54 genera, 293 species). We propose one change in the Margaritiferidae: the placement of the formerly monotypic genus Cumberlandia in the synonymy of Margaritifera. In the Unionidae, we recognize three new genera, elevate four genera from synonymy, and place three previously recognized genera in synonymy. We recognize for the first time two species (one native and one nonindigenous) in the Asian genus Sinanodonta as occurring in North America. We recognize four new species and one subspecies and elevate 21 species from synonymy. We elevate 10 subspecies to species status and no longer recognize four subspecies. We change common names for five taxa, correct spelling for eight species, and correct the date of publication of original descriptions for four species.
","language":"English","publisher":"Freshwater Mollusk Conservation Society","doi":"10.31931/fmbc.v20i2.2017.33-58","usgsCitation":"Williams, J.D., Bogan, A.E., Butler, R., Cummings, K.S., Garner, J.T., Harris, J.L., Johnson, N.A., and Watters, G.T., 2017, A revised list of the freshwater mussels (Mollusca: Bivalvia: Unionida) of the United States and Canada: Freshwater Mollusk Biology and Conservation, v. 20, no. 2, p. 33-58, https://doi.org/10.31931/fmbc.v20i2.2017.33-58.","productDescription":"26 p.","startPage":"33","endPage":"58","ipdsId":"IP-086632","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469440,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc.v20i2.2017.33-58","text":"Publisher Index Page"},{"id":349849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, 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Hepatic, pancreatic, splenic, and intestinal necrosis were observed in dead eiders. We inoculated 6-week-old common eider ducklings with WFBV in an attempt to recreate the naturally occurring disease. Approximately 25% of inoculated eiders had onset of clinical disease and required euthanasia; an additional 18.75% were adversely affected based on net weight loss during the trial. Control ducklings did not become infected and did not have clinical disease. Infected ducklings with clinical disease had pathologic lesions consistent with those observed during natural mortality events. WFBV was re-isolated from 37.5% of the inoculated ducklings. Ducklings surviving to 5 days postinoculation developed serum antibody titers to WFBV.
","language":"English","publisher":"CDC","doi":"10.3201/eid2312.160366","usgsCitation":"Shearn-Bochsler, V.I., Ip, S., Ballmann, A., Hall, J.S., Allison, A.B., Ballard, J.R., Ellis, J.C., Cook, R., Gibbs, S., and Dwyer, C.P., 2017, Experimental infection of common eider ducklings with Wellfleet Bay virus, a newly characterized orthomyxovirus: Emerging Infectious Diseases, v. 23, no. 12, p. 1974-1981, https://doi.org/10.3201/eid2312.160366.","productDescription":"8 p.","startPage":"1974","endPage":"1981","ipdsId":"IP-087219","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":469439,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3201/eid2312.160366","text":"Publisher Index Page"},{"id":346628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"12","publishingServiceCenter":{"id":6,"text":"Columbus 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aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":712555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":712556,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allison, Andrew B.","contributorId":83011,"corporation":false,"usgs":false,"family":"Allison","given":"Andrew","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":712557,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ballard, Jennifer R.","contributorId":127726,"corporation":false,"usgs":false,"family":"Ballard","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":712558,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ellis, Julie C.","contributorId":127731,"corporation":false,"usgs":false,"family":"Ellis","given":"Julie","email":"","middleInitial":"C.","affiliations":[{"id":7128,"text":"Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA 01536, USA.","active":true,"usgs":false}],"preferred":false,"id":712559,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cook, Robert","contributorId":176416,"corporation":false,"usgs":false,"family":"Cook","given":"Robert","affiliations":[],"preferred":false,"id":712560,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gibbs, Samantha E.J.","contributorId":127739,"corporation":false,"usgs":false,"family":"Gibbs","given":"Samantha E.J.","affiliations":[{"id":7128,"text":"Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA 01536, USA.","active":true,"usgs":false}],"preferred":false,"id":712561,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dwyer, Chris P.","contributorId":127734,"corporation":false,"usgs":false,"family":"Dwyer","given":"Chris","email":"","middleInitial":"P.","affiliations":[{"id":7131,"text":"United States Department of the Interior, United States Fish and 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wildfire is critical for restoring the ecosystem services of protecting of human lives and infrastructure from hazards and delivering water supply of sufficient quality and quantity. Recovery of soil-hydraulic properties, such as field-saturated hydraulic conductivity (Kfs), is a key factor for assessing the duration of watershed-scale flash flood and debris flow risks after wildfire. Despite the crucial role of Kfs in parameterizing numerical hydrologic models to predict the magnitude of postwildfire run-off and erosion, existing quantitative relations to predict Kfsrecovery with time since wildfire are lacking. Here, we conduct meta-analyses of 5 datasets from the literature that measure or estimate Kfs with time since wildfire for longer than 3-year duration. The meta-analyses focus on fitting 2 quantitative relations (linear and non-linear logistic) to explain trends in Kfs temporal recovery. The 2 relations adequately described temporal recovery except for 1 site where macropore flow dominated infiltration and Kfs recovery. This work also suggests that Kfs can have low hydrologic resistance (large postfire changes), and moderate to high hydrologic stability (recovery time relative to disturbance recurrence interval) and resilience (recovery of hydrologic function and provision of ecosystem services). Future Kfs relations could more explicitly incorporate processes such as soil-water repellency, ground cover and soil structure regeneration, macropore recovery, and vegetation regrowth.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11288","usgsCitation":"Ebel, B.A., and Martin, D.A., 2017, Meta-analysis of field-saturated hydraulic conductivity recovery following wildland fire: Applications for hydrologic model parameterization and resilience assessment: Hydrological Processes, v. 31, no. 21, p. 3682-3696, https://doi.org/10.1002/hyp.11288.","productDescription":"15 p.","startPage":"3682","endPage":"3696","ipdsId":"IP-084869","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":347327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"21","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-30","publicationStatus":"PW","scienceBaseUri":"59f1a2a4e4b0220bbd9d9f34","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":714984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":168662,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"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":714985,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193775,"text":"70193775 - 2017 - Sex difference in PCB concentrations of a catostomid fish","interactions":[],"lastModifiedDate":"2025-05-21T14:43:00.473932","indexId":"70193775","displayToPublicDate":"2017-10-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5543,"text":"Journal of Environmental & Analytical Toxicology","onlineIssn":"2161-0525","active":true,"publicationSubtype":{"id":10}},"title":"Sex difference in PCB concentrations of a catostomid fish","docAbstract":"Unraveling the complexities associated with the relative differences in contaminant concentrations between the sexes of mature fish may provide insights into important behavioral and physiological differences between the sexes of not just fish but higher vertebrates as well. Whole-fish polychlorinated biphenyl (PCB) concentrations were determined in 25 mature female white suckers (Catostomus commersoni) and 26 mature male white suckers caught during their spawning run in the Kewaunee River, a tributary to Lake Michigan. Total length and weight were measured for each fish, and age of each fish was estimated from thin-sectioned otoliths. PCB concentration significantly increased with increasing total length, weight, and age. Consequently, three analysis of covariance (ANCOVA) models were fitted to the data to assess the effect of sex on white sucker PCB concentration. Based on model averaging, estimates of mean PCB concentrations in female and male white suckers were 185 and 219 ng/g, respectively. Thus, males were 18% greater in PCB concentration than females. We conclude that this difference between the sexes was most likely mainly driven by a higher rate of energy expenditure in males compared with females. Greater energy expenditure, owing to greater swimming activity and a higher resting metabolic rate, resulted in a higher rate of food consumption, which in turn led to a greater rate of PCB accumulation. Higher whole-fish PCB concentration in males compared with females has now been shown in nine different fish species. Our study represented the first documentation of this type of sex difference in a catostomid fish.
","language":"English","publisher":"OMICS International","doi":"10.4172/2161-0525.1000515","usgsCitation":"Madenjian, C.P., Stevens, A.L., Stapanian, M.A., Batterman, S.A., Chernyak, S.M., Menczer, J.E., and McIntyre, P.B., 2017, Sex difference in PCB concentrations of a catostomid fish: Journal of Environmental & Analytical Toxicology, v. 7, no. 6, 1000515, 6 p., https://doi.org/10.4172/2161-0525.1000515.","productDescription":"1000515, 6 p.","ipdsId":"IP-090486","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":348466,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":469441,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4172/2161-0525.1000515","text":"Publisher Index Page"}],"country":"United States","otherGeospatial":"Kewaunee River, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.55987644195555,\n 44.454981738717876\n ],\n [\n -87.53923416137695,\n 44.454981738717876\n ],\n [\n -87.53923416137695,\n 44.46380338011975\n ],\n [\n -87.55987644195555,\n 44.46380338011975\n ],\n [\n -87.55987644195555,\n 44.454981738717876\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425b3e4b0dc0b45b4531a","contributors":{"authors":[{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":720379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevens, Andrew L.","contributorId":199914,"corporation":false,"usgs":false,"family":"Stevens","given":"Andrew","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":720380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":720385,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Batterman, Stuart A.","contributorId":199915,"corporation":false,"usgs":false,"family":"Batterman","given":"Stuart","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chernyak, Sergei M.","contributorId":199916,"corporation":false,"usgs":false,"family":"Chernyak","given":"Sergei","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":720382,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Menczer, Jordan E.","contributorId":199917,"corporation":false,"usgs":false,"family":"Menczer","given":"Jordan","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":720383,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McIntyre, Peter B.","contributorId":166828,"corporation":false,"usgs":false,"family":"McIntyre","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":24540,"text":"Center for Limnology, University of Wisconsin, Madison, Wisconsin, 53706, USA.","active":true,"usgs":false}],"preferred":false,"id":720384,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204370,"text":"70204370 - 2017 - Viability analysis for multiple populations","interactions":[],"lastModifiedDate":"2019-07-22T13:39:20","indexId":"70204370","displayToPublicDate":"2017-10-13T13:35:43","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Viability analysis for multiple populations","docAbstract":"Many species of conservation interest exist solely or largely in isolated populations. Ideally, prioritization of management actions among such populations would be guided by quantitative estimates of extinction risk, but conventional methods of demographic population viability analysis (PVA) model each population separately and require temporally extensive datasets that are rarely available in practice. We introduce a general class of statistical PVA that can be applied to many populations at once, which we term multiple population viability analysis or MPVA. The approach combines models of abundance at multiple spatial locations with temporal models of population dynamics, effectively borrowing information from more data-rich populations to inform inferences for data-poor populations. Covariates are used to explain population variability in space and time. Using Bayesian analysis, we illustrate the method with a dataset of Lahontan cutthroat trout (Oncorhynchus clarkii henshawi) observations that previously had been analyzed with conventional PVA. We find that MPVA predictions are similar in bias and higher in precision than predictions from simple PVA models that treat each population individually; moreover, the use of covariates in MPVA allows for predictions in minimally-sampled and unsampled populations. The basic MPVA model can be extended in multiple ways, such as by linking to a sampling and observation model to provide a full accounting of uncertainty. We conclude that the approach has great potential to expand the use of PVA for species that exist in multiple, isolated populations.
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