{"pageNumber":"232","pageRowStart":"5775","pageSize":"25","recordCount":41062,"records":[{"id":70228994,"text":"70228994 - 2021 - Harvest as a tool to manage populations of undesirable or overabundant fish and wildlife","interactions":[],"lastModifiedDate":"2022-02-25T14:20:08.753662","indexId":"70228994","displayToPublicDate":"2021-06-07T08:10:32","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"18","title":"Harvest as a tool to manage populations of undesirable or overabundant fish and wildlife","docAbstract":"

Harvest is a common management tool for fish and game species and can also be used for overabundant populations when stakeholders want to reduce populations reduced and still provide recreational opportunities. The authors propose a framework to determine if harvest can be used to control populations when overabundance is an issue, stakeholders support harvest, information is available to set harvest goals and evaluate impacts of harvest, and assessments are conducted to evaluate unintended consequences of harvest. The chapter provides two case examples of mid-continent light geese and blue catfish in the Chesapeake Bay watershed, for which overabundance was a problem and stakeholders had interest in harvest. Substantial data existed to set goals for light geese whereas blue catfish data were limited. For both light geese and blue catfish, desired outcomes have not yet been achieved, but hunting and fishing opportunities generated societal benefits despite existing barriers to increasing harvest. Harvest to control overabundant populations can be a useful tool, but consideration of stakeholder support, the data require to establish and monitor goals, and unintended consequences should be considered for an effective harvest plan.

Harvest is a common management tool used for centuries to limit populations of game species (Caughley 1977, Redmond 1986). Managing populations using harvest regulations allow certain sizes, numbers, sex, and species to be harvested, and often include open or closed seasons. Regulated hunting opportunity and harvest are cornerstones of the North American Model of Wildlife Conservation, which developed gradually following unregulated harvest of wildlife populations that often were at risk of overharvest or extinction (Geist et al. 2001). Since then, many populations have recovered and expanded to the point where harvest regulations are now often used to limit or even reduce populations of some species. In general, harvest regulations have been well established as an effective way to control animal populations in many aquatic and terrestrial systems and are broadly accepted among the hunting and fishing public. For example, harvest regulations have been established or adapted to reduce or control populations of feral hogs (Sus scrofa; Hanson et al. 2009), white-tailed deer (Odocoileus virginianus; Simard et al. 2013) and cougar (Puma concolor; Cooley et al. 2009), overabundant small black bass (Micropertus spp.; Isermann and Paukert 2010), northern pike (Esox lucius; Pierce 2010) or non-native species (Arlinghaus et al. 2016b).

Harvest has also been employed as a tool for controlling populations of invasive species. However, in many cases invasive species are so overabundant that a substantial commitment to harvest is necessary, which may exceed recreational harvest capacity and require commercial harvest or an active lethal control program by management agencies. Often removal of invasive species is challenging because the ultimate goal may be to eliminate the entire population, which may require impractical efforts. For example, controlling Asian carp in the Illinois River may require harvest rates of at least 70% (Tsehaye et al. 2013), whereas in the Great Smoky Mountains, an annual harvest rate of 40% would be necessary to decrease feral hog populations (Salinas et al. 2015). Many invasive species are known to negatively impact native species and ecosystems; thus, eradication is an ideal outcome. However, there may be opportunity to use harvest to control populations of native (or non-native) species that have some value yet are still overabundant. In this chapter, we explore the process of using harvest to control overabundant populations that have some recreational value, provide two examples to control overabundant populations using harvest, and describe the challenges and effectiveness associated with these efforts and some of the unintended effects of using harvest to control populations.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Harvest of fish and wildlife: New paradigms for sustainable management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","usgsCitation":"Paukert, C.P., Webb, E.B., Fowler, D.N., and Hilling, C.D., 2021, Harvest as a tool to manage populations of undesirable or overabundant fish and wildlife, chap. 18 of Harvest of fish and wildlife: New paradigms for sustainable management, p. 249-261.","productDescription":"13 p.","startPage":"249","endPage":"261","ipdsId":"IP-119950","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":836089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":836090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fowler, Drew N.","contributorId":205356,"corporation":false,"usgs":false,"family":"Fowler","given":"Drew","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":836091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hilling, Corbin D. 0000-0003-4040-9516","orcid":"https://orcid.org/0000-0003-4040-9516","contributorId":257754,"corporation":false,"usgs":false,"family":"Hilling","given":"Corbin","email":"","middleInitial":"D.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":836092,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221293,"text":"70221293 - 2021 - Direct and size-mediated effects of temperature and ration-dependent growth rates on energy reserves in juvenile anadromous alewives (Alosa pseudoharengus)","interactions":[],"lastModifiedDate":"2021-10-18T14:04:00.020978","indexId":"70221293","displayToPublicDate":"2021-06-07T07:27:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Direct and size-mediated effects of temperature and ration-dependent growth rates on energy reserves in juvenile anadromous alewives (Alosa pseudoharengus)","title":"Direct and size-mediated effects of temperature and ration-dependent growth rates on energy reserves in juvenile anadromous alewives (Alosa pseudoharengus)","docAbstract":"

Growth rate and energy reserves are important determinants of fitness and are governed by endogenous and exogenous factors. Thus, examining the influence of individual and multiple stressors on growth and energy reserves can help estimate population health under current and future conditions. In young anadromous fishes, freshwater habitat quality determines physiological state and fitness of juveniles emigrating to marine habitats. We tested how temperature and food availability affect survival, growth, and energy reserves in juvenile anadromous alewives (Alosa pseudoharengus), a forage fish distributed along the eastern North American continent. Field-collected juvenile anadromous A. pseudoharengus were exposed for 21 days to one of two temperatures (21°C and 25°C) and one of two levels of food rations (1% or 2% tank biomass daily) and compared for differences in final size, fat mass-at-length, lean mass-at-length, and energy density. Increased temperature and reduced ration both led to lower growth rates and the effect of reduced ration was greater at higher temperature. Fat mass-at-length decreased with dry mass and energy density increased with total length, suggesting size-based endogenous influences on energy reserves. Lower ration also directly decreased fat mass-at-length, lean mass-at-length and energy density. Given the fitness implications of size and energy reserves, temperature and food availability should be considered important indicators of nursery habitat quality and incorporated in A. pseudoharengus life history models to improve forecasting of population health under climate change.

","language":"English","publisher":"Wiley","doi":"10.1111/jfb.14824","usgsCitation":"Guo, L., McCormick, S.D., Schultz, E., and Jordaan, A., 2021, Direct and size-mediated effects of temperature and ration-dependent growth rates on energy reserves in juvenile anadromous alewives (Alosa pseudoharengus): Journal of Fish Biology, v. 99, no. 4, p. 1236-1246, https://doi.org/10.1111/jfb.14824.","productDescription":"11 p.","startPage":"1236","endPage":"1246","ipdsId":"IP-125451","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":386341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Guo, Liang 0000-0001-5454-6330","orcid":"https://orcid.org/0000-0001-5454-6330","contributorId":210404,"corporation":false,"usgs":false,"family":"Guo","given":"Liang","email":"","affiliations":[],"preferred":false,"id":817253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":817254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schultz, Eric T.","contributorId":260102,"corporation":false,"usgs":false,"family":"Schultz","given":"Eric T.","affiliations":[],"preferred":false,"id":817255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jordaan, Adrian","contributorId":257709,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":817256,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221478,"text":"70221478 - 2021 - Integrating wildlife habitat models with state-and-transitions models to enhance the management of rangelands for multiple objectives","interactions":[],"lastModifiedDate":"2021-06-17T11:51:14.687819","indexId":"70221478","displayToPublicDate":"2021-06-07T06:49:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Integrating wildlife habitat models with state-and-transitions models to enhance the management of rangelands for multiple objectives","docAbstract":"

State-and-transition models (STMs) are tools used in rangeland management to describe linear and nonlinear vegetation dynamics as conceptual models. STMs can be improved by including additional ecosystem services, such as wildlife habitat, so that managers can predict how local populations might respond to state changes and to illustrate the tradeoffs in managing for different ecosystem services. Our objective was to incorporate songbird density into an STM developed for sagebrush rangelands in northwest Colorado to guide local management of sagebrush birds. The STM included two shrub-dominated community phases, a native grassland state, and a shrubland and grassland phase within an exotic-dominated state. We surveyed plots for songbirds, collected a suite of vegetation indicators at each plot, and quantified songbird habitat relationships with count-based regression models. We then used the estimated models to predict songbird density based on average vegetation conditions per state or community phase. Moderate or increasing shrub cover were important predictors for shrubland-associated species, and responses to understory components varied by species. In the STM, we predicted higher densities of shrubland-associated bird species in the shrub-dominated phases and higher densities of grassland-associated bird species in the state and phase lacking shrub cover. No single state or phase captured the highest density for all songbirds, illustrating the value of alternative states. Our results also demonstrate the utility of displaying traditional wildlife count models against the range of vegetation conditions associated with each state or phase to understand how wildlife density can vary within states and phases. Our approach can assist land managers to gauge the potential impacts of land-use decisions and natural vegetation variability on wildlife, especially for species of conservation concern.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2021.04.005","usgsCitation":"Timmer, J.M., Tipton, C.Y., Bruegger, R.A., Augustine, D.J., Dickey, C.P., Fernandez-Gimenez, M.E., and Aldridge, C.L., 2021, Integrating wildlife habitat models with state-and-transitions models to enhance the management of rangelands for multiple objectives: Rangeland Ecology and Management, v. 78, p. 15-25, https://doi.org/10.1016/j.rama.2021.04.005.","productDescription":"11 p.","startPage":"15","endPage":"25","ipdsId":"IP-121879","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":452000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2021.04.005","text":"Publisher Index Page"},{"id":386565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Timmer, Jennifer M.","contributorId":140717,"corporation":false,"usgs":false,"family":"Timmer","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":817794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tipton, Crystal Y.","contributorId":260364,"corporation":false,"usgs":false,"family":"Tipton","given":"Crystal","email":"","middleInitial":"Y.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":817795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bruegger, Retta A.","contributorId":260365,"corporation":false,"usgs":false,"family":"Bruegger","given":"Retta","email":"","middleInitial":"A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":817796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Augustine, David J.","contributorId":189957,"corporation":false,"usgs":false,"family":"Augustine","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":817797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dickey, Christopher P.K.","contributorId":260367,"corporation":false,"usgs":false,"family":"Dickey","given":"Christopher","email":"","middleInitial":"P.K.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":817798,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fernandez-Gimenez, Maria E.","contributorId":260369,"corporation":false,"usgs":false,"family":"Fernandez-Gimenez","given":"Maria","email":"","middleInitial":"E.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":817799,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":817800,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70222615,"text":"70222615 - 2021 - NGA-East ground-motion characterization model Part II: Implementation and hazard implications","interactions":[],"lastModifiedDate":"2021-08-09T13:14:26.676694","indexId":"70222615","displayToPublicDate":"2021-06-06T08:11:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"NGA-East ground-motion characterization model Part II: Implementation and hazard implications","docAbstract":"

As a companion article to Goulet et al., we describe implementation of the NGA-East ground motion characterization (GMC) model in probabilistic seismic hazard analysis (PSHA) for sites in the Central and Eastern United States (CEUS). We present extensions to the EPRI/DOE/NRC seismic source characterization (SSC) model for the CEUS needed for full implementation of NGA-East. Comparisons are presented to the EPRI GMC, the currently accepted model by the U.S. Nuclear Regulatory Commission for hazard assessment at nuclear facilities. Comparisons are presented both in terms of GMC model components and in the resulting seismic hazard assessments for a range of site locations in the CEUS. Illustrations of the effect of various components of the NGA-East GMC on seismic hazard results are also presented. Finally, we present recommendations for application of the NGA-East GMC in PSHA.

","language":"English","publisher":"Earthquake Engineering Research Institute (EERI)","doi":"10.1177/87552930211007503","usgsCitation":"Youngs, R., Goulet, C.A., Bozorgnia, Y., Kuehn, N., Al Atik, L., Graves, R., and Atkinson, G.M., 2021, NGA-East ground-motion characterization model Part II: Implementation and hazard implications: Earthquake Spectra, v. 37, no. 1, p. 1283-1330, https://doi.org/10.1177/87552930211007503.","productDescription":"48 p.","startPage":"1283","endPage":"1330","ipdsId":"IP-124999","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":387773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.6328125,\n 31.57853542647338\n ],\n [\n -105.205078125,\n 29.458731185355344\n ],\n [\n -102.919921875,\n 29.152161283318915\n ],\n [\n -97.646484375,\n 25.48295117535531\n ],\n [\n -93.779296875,\n 26.27371402440643\n ],\n [\n -81.298828125,\n 24.367113562651262\n ],\n [\n -77.34374999999999,\n 27.371767300523047\n ],\n [\n -72.24609375,\n 33.94335994657882\n ],\n [\n -57.65624999999999,\n 45.089035564831036\n ],\n [\n -61.787109375,\n 51.23440735163459\n ],\n [\n -71.630859375,\n 50.401515322782366\n ],\n [\n -75.9375,\n 47.635783590864854\n ],\n [\n -86.1328125,\n 50.28933925329178\n ],\n [\n -100.283203125,\n 52.696361078274485\n ],\n [\n -108.896484375,\n 51.83577752045248\n ],\n [\n -108.720703125,\n 48.86471476180277\n ],\n [\n -109.3359375,\n 40.44694705960048\n ],\n [\n -108.6328125,\n 31.57853542647338\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Youngs, Robert","contributorId":140544,"corporation":false,"usgs":false,"family":"Youngs","given":"Robert","affiliations":[],"preferred":false,"id":820761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goulet, Christine A. 0000-0002-7643-357X","orcid":"https://orcid.org/0000-0002-7643-357X","contributorId":194805,"corporation":false,"usgs":false,"family":"Goulet","given":"Christine","email":"","middleInitial":"A.","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":820762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bozorgnia, Yousef","contributorId":40101,"corporation":false,"usgs":false,"family":"Bozorgnia","given":"Yousef","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":820763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuehn, Nicolas","contributorId":229633,"corporation":false,"usgs":false,"family":"Kuehn","given":"Nicolas","email":"","affiliations":[{"id":6772,"text":"UC Los Angeles","active":true,"usgs":false}],"preferred":false,"id":820764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Al Atik, Linda","contributorId":140526,"corporation":false,"usgs":false,"family":"Al Atik","given":"Linda","email":"","affiliations":[],"preferred":false,"id":820765,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":820766,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Atkinson, Gail M.","contributorId":60515,"corporation":false,"usgs":false,"family":"Atkinson","given":"Gail","email":"","middleInitial":"M.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":820767,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70225672,"text":"70225672 - 2021 - A hidden Markov model for estimating age-specific survival when age and size are uncertain","interactions":[],"lastModifiedDate":"2021-11-02T11:56:59.846688","indexId":"70225672","displayToPublicDate":"2021-06-05T06:55:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A hidden Markov model for estimating age-specific survival when age and size are uncertain","docAbstract":"

Estimates of age-specific survival probabilities are needed for age-structured population models and to inform conservation decisions. However, determining the age of individuals in wildlife populations is often problematic. We present a hidden Markov model for estimating age-specific survival from capture–recapture or capture–recapture–recovery data when age is unknown and indicators of age, such as size and growth layer counts, are imprecise. The model is evaluated through simulations, and its implementation is illustrated with maximum likelihood and Bayesian approaches in commonly used software. The model is then applied to genetic capture–recapture data of Florida manatees to estimate age- and time-variant survival probabilities. The approach is broadly applicable to studies aiming to quantify age-specific effects of environmental change and management actions on population dynamics, including studies that rely on minimally invasive methods such as genetic and photo identification.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3426","usgsCitation":"Gowan, T.A., Tringali, M.D., Hostetler, J.A., Martin, J., Ward-Geiger, L.I., and Johnson, J.M., 2021, A hidden Markov model for estimating age-specific survival when age and size are uncertain: Ecology, v. 102, no. 8, e03426, 7 p., https://doi.org/10.1002/ecy.3426.","productDescription":"e03426, 7 p.","ipdsId":"IP-121258","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":452006,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecy.3426","text":"External Repository"},{"id":436327,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TPN4F3","text":"USGS data release","linkHelpText":"Data from: A hidden Markov model for estimating age-specific survival when age and size are uncertain"},{"id":391263,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"102","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Gowan, Timothy A.","contributorId":138595,"corporation":false,"usgs":false,"family":"Gowan","given":"Timothy","email":"","middleInitial":"A.","affiliations":[{"id":12456,"text":"former USGS scientist","active":true,"usgs":false}],"preferred":false,"id":826163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tringali, Michael D.","contributorId":191189,"corporation":false,"usgs":false,"family":"Tringali","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":826164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hostetler, Jeffrey A. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":190248,"corporation":false,"usgs":false,"family":"Hostetler","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":826165,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":218445,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":826166,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ward-Geiger, Leslie I.","contributorId":190250,"corporation":false,"usgs":false,"family":"Ward-Geiger","given":"Leslie","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":826167,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Jennifer M","contributorId":268201,"corporation":false,"usgs":false,"family":"Johnson","given":"Jennifer","email":"","middleInitial":"M","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":826168,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70221475,"text":"70221475 - 2021 - Relative risk of groundwater-quality degradation near California (USA) oil fields estimated from 3H, 14C, and 4He","interactions":[],"lastModifiedDate":"2021-06-17T11:56:09.830879","indexId":"70221475","displayToPublicDate":"2021-06-05T06:52:07","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Relative risk of groundwater-quality degradation near California (USA) oil fields estimated from 3H, 14C, and 4He","docAbstract":"

Relative risks of groundwater-quality degradation near selected California oil fields are estimated by examining spatial and temporal patterns in chemical and isotopic data in the context of groundwater-age categories defined by tritium and carbon-14. In the Coastal basins, western San Joaquin Valley (SJV), and eastern SJV; 82, 76, and 0% of samples are premodern (pre-1953 recharge), respectively; and 3, 0, and 31% are modern (recharged during or after 1953), respectively. Carbon-14 and helium-4 data indicate most premodern samples are 1000 to 10,000 (33%) or >10,000 (50%) years old. Organic chemicals that could be associated with deeper hydrocarbon reservoirs (e.g. thermogenic gases and benzene) occur most frequently in premodern groundwater, suggesting premodern groundwater has a higher risk of degradation from upward migration of hydrocarbons than modern and mixed-age groundwater. Low sulfate concentrations in some premodern groundwater containing high thermogenic-methane concentrations (>28 mg/L) indicate methane attenuation associated with sulfate reduction can be limited in premodern groundwater. The more common occurrence of manufactured compounds, like tetrachloroethene, in modern and mixed-age groundwater than in premodern groundwater indicates modern and mixed-age groundwater has a higher risk of degradation from land-surface sources than premodern groundwater. Time-series data for chloride in groundwater affected by disposal of oil-field water in unlined ponds indicate some modern and mixed-age groundwater are susceptible to chemical migration within 2–3 km of surface sources. Timescales for diluting chloride concentrations in groundwater with fresh recharge once disposal ponds are decommissioned are shorter in mixed-age groundwater with large fractions of modern water (9–14 years in one example) than in mixed-age groundwater with large fractions of premodern water (no evidence of dilution after 12 years of monitoring in one example). The presence of predominantly premodern groundwater in the Coastal basins and western SJV indicates these areas have relatively high risk from upward migration of hydrocarbons, reduced methane attenuation capacity, and long dilution times, whereas predominantly modern- and mixed-age groundwater in the eastern SJV indicates this area has relatively high risk from chemical migration from land-surface sources and subsequent extensive spreading. Age-based characterizations of relative risk could inform the design of groundwater-monitoring programs near oil fields in terms of the spatial distribution of monitoring points relative to source areas and monitoring frequency and duration.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2021.105024","usgsCitation":"McMahon, P.B., Landon, M.K., Davis, T., Wright, M., Rosecrans, C.Z., Anders, R., Land, M., Kulongoski, J.T., and Hunt, A., 2021, Relative risk of groundwater-quality degradation near California (USA) oil fields estimated from 3H, 14C, and 4He: Applied Geochemistry, v. 131, 105024, 15 p., https://doi.org/10.1016/j.apgeochem.2021.105024.","productDescription":"105024, 15 p.","ipdsId":"IP-120473","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":452009,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2021.105024","text":"Publisher Index Page"},{"id":386566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.95947265624999,\n 33.96158628979907\n ],\n [\n -117.99316406249999,\n 33.96158628979907\n ],\n [\n -117.99316406249999,\n 35.30840140169162\n ],\n [\n -120.95947265624999,\n 35.30840140169162\n ],\n [\n -120.95947265624999,\n 33.96158628979907\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"131","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Tracy 0000-0003-0253-6661 tadavis@usgs.gov","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":176921,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy","email":"tadavis@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, Michael 0000-0003-0653-6466 mtwright@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":151031,"corporation":false,"usgs":true,"family":"Wright","given":"Michael","email":"mtwright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817788,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosecrans, Celia Z. 0000-0003-1456-4360 crosecrans@usgs.gov","orcid":"https://orcid.org/0000-0003-1456-4360","contributorId":187542,"corporation":false,"usgs":true,"family":"Rosecrans","given":"Celia","email":"crosecrans@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":817789,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anders, Robert 0000-0002-2363-9072 randers@usgs.gov","orcid":"https://orcid.org/0000-0002-2363-9072","contributorId":1210,"corporation":false,"usgs":true,"family":"Anders","given":"Robert","email":"randers@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817790,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Land, Michael 0000-0001-5141-0307 mtland@usgs.gov","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":171938,"corporation":false,"usgs":true,"family":"Land","given":"Michael","email":"mtland@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817791,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817792,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hunt, Andrew G. 0000-0002-3810-8610","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":206197,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":817793,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70221174,"text":"ofr20211049 - 2021 - Deposit classification scheme for the Critical Minerals Mapping Initiative Global Geochemical Database","interactions":[],"lastModifiedDate":"2021-06-07T11:43:05.163242","indexId":"ofr20211049","displayToPublicDate":"2021-06-04T16:00:00","publicationYear":"2021","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":"2021-1049","displayTitle":"Deposit Classification Scheme for the Critical Minerals Mapping Initiative Global Geochemical Database","title":"Deposit classification scheme for the Critical Minerals Mapping Initiative Global Geochemical Database","docAbstract":"

A challenge for the global economy is to meet the growing demand for commodities used in today’s advanced technologies. Critical minerals are commodities (for example, elements, compounds, minerals) deemed vital to the economic and national security of individual countries that are vulnerable to supply disruption. The national geological agencies of Australia, Canada, and the United States recently joined forces to advance understanding and foster development of critical mineral resources in their respective countries through the Critical Minerals Mapping Initiative (CMMI). An initial goal of the CMMI is to fill the knowledge gap on the abundance of critical minerals in ores. To do this, the CMMI compiled modern multielement geochemical data generated by each agency on ore samples collected from historical and active mines and prospects from around the world. To identify relationships between critical minerals, deposit types, deposit environments, and mineral systems, a unified deposit classification scheme was needed. This report describes the scheme developed by the CMMI to classify the initial release of geochemical data. In 2021, the resulting database—along with basic query, statistical analysis, and display tools—will be served to the public through a web-based portal managed by Geoscience Australia. The database will enable users to trace critical minerals through mineral systems and identify individual deposits or deposit types that are potential sources of critical minerals.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211049","issn":"2331-1258","collaboration":"Prepared as part of a joint research program between the U.S. Geological Survey, Geological Survey of Canada, Geological Survey of Queensland, and Geoscience Australia","usgsCitation":"Hofstra, A., Lisitsin, V., Corriveau, L., Paradis, S., Peter, J., Lauzière, K., Lawley, C., Gadd, M., Pilote, J., Honsberger, I., Bastrakov, E., Champion, D., Czarnota, K., Doublier, M., Huston, D., Raymond, O., VanDerWielen, S., Emsbo, P., Granitto, M., and Kreiner, D., 2021, Deposit classification scheme for the Critical Minerals Mapping Initiative Global Geochemical Database: U.S. Geological Survey Open-File Report 2021–1049, 60 p., https://doi.org/10.3133/ofr20211049.","productDescription":"Report: v, 60 p.; 1 Table","onlineOnly":"Y","ipdsId":"IP-127680","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":386206,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2021/1049/ofr20211049_table2.pdf","text":"Table 2—Deposit classification scheme","size":"224 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1049 Table 1"},{"id":386204,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1049/coverthb.jpg"},{"id":386205,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1049/ofr20211049.pdf","text":"Report","size":"1.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1049"}],"contact":"

Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
MS 973, Box 25046
Denver, CO 80225

","tableOfContents":"","publishedDate":"2021-06-04","noUsgsAuthors":false,"publicationDate":"2021-06-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":816952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lisitsin, Vladimir","contributorId":259280,"corporation":false,"usgs":false,"family":"Lisitsin","given":"Vladimir","email":"","affiliations":[{"id":52346,"text":"Geological Survey of Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":816953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corriveau, Louise","contributorId":259281,"corporation":false,"usgs":false,"family":"Corriveau","given":"Louise","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":816954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paradis, Suzanne","contributorId":259282,"corporation":false,"usgs":false,"family":"Paradis","given":"Suzanne","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":816955,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peter, Jan","contributorId":259283,"corporation":false,"usgs":false,"family":"Peter","given":"Jan","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":816956,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lauziere, Kathleen","contributorId":259284,"corporation":false,"usgs":false,"family":"Lauziere","given":"Kathleen","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":816957,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lawley, Christopher","contributorId":259285,"corporation":false,"usgs":false,"family":"Lawley","given":"Christopher","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":816958,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gadd, Michael","contributorId":259286,"corporation":false,"usgs":false,"family":"Gadd","given":"Michael","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":816959,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pilote, Jean-Luc","contributorId":259287,"corporation":false,"usgs":false,"family":"Pilote","given":"Jean-Luc","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":816960,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Honsberger, Ian","contributorId":259288,"corporation":false,"usgs":false,"family":"Honsberger","given":"Ian","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":816961,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bastrakov, Evgeniy","contributorId":259289,"corporation":false,"usgs":false,"family":"Bastrakov","given":"Evgeniy","email":"","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":816962,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Champion, David C.","contributorId":259290,"corporation":false,"usgs":false,"family":"Champion","given":"David","middleInitial":"C.","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":816963,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Czarnota, Karol","contributorId":259291,"corporation":false,"usgs":false,"family":"Czarnota","given":"Karol","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":816964,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Doublier, Michael P.","contributorId":259292,"corporation":false,"usgs":false,"family":"Doublier","given":"Michael","middleInitial":"P.","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":816965,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Huston, David L.","contributorId":259293,"corporation":false,"usgs":false,"family":"Huston","given":"David","middleInitial":"L.","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":816966,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Raymond, Oliver","contributorId":259294,"corporation":false,"usgs":false,"family":"Raymond","given":"Oliver","email":"","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":816967,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"VanDerWielen, Simon","contributorId":259295,"corporation":false,"usgs":false,"family":"VanDerWielen","given":"Simon","email":"","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":816968,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Emsbo, Poul 0000-0001-9421-201X pemsbo@usgs.gov","orcid":"https://orcid.org/0000-0001-9421-201X","contributorId":997,"corporation":false,"usgs":true,"family":"Emsbo","given":"Poul","email":"pemsbo@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":816969,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Granitto, Matthew 0000-0003-3445-4863 granitto@usgs.gov","orcid":"https://orcid.org/0000-0003-3445-4863","contributorId":1224,"corporation":false,"usgs":true,"family":"Granitto","given":"Matthew","email":"granitto@usgs.gov","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":816972,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Kreiner, Douglas C. 0000-0002-4405-1403","orcid":"https://orcid.org/0000-0002-4405-1403","contributorId":220474,"corporation":false,"usgs":true,"family":"Kreiner","given":"Douglas","email":"","middleInitial":"C.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":816973,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70221330,"text":"70221330 - 2021 - Oxygen-controlled recirculating seepage meter reveals extent of nitrogen transformation in discharging coastal groundwater at the aquifer–estuary interface","interactions":[],"lastModifiedDate":"2021-08-17T15:20:14.841712","indexId":"70221330","displayToPublicDate":"2021-06-04T07:30:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Oxygen-controlled recirculating seepage meter reveals extent of nitrogen transformation in discharging coastal groundwater at the aquifer–estuary interface","docAbstract":"

Nutrient loads delivered to estuaries via submarine groundwater discharge (SGD) play an important role in the nitrogen (N) budget and eutrophication status. However, accurate and reliable quantification of the chemical flux across the final decimeters and centimeters at the sediment–estuary interface remains a challenge, because there is significant potential for biogeochemical alteration due to contrasting conditions in the coastal aquifer and surface sediment. Here, a novel, oxygen- and light-regulated ultrasonic seepage meter, and a standard seepage meter, were used to measure SGD and calculate N species fluxes across the sediment–estuary interface. Coupling the measurements to an endmember approach based on subsurface N concentrations and an assumption of conservative transport enabled estimation of the extent of transformation occurring in discharging groundwater within the benthic zone. Biogeochemical transformation within reactive estuarine surface sediment was a dominant driver in modifying the N flux carried upward by SGD, and resulted in a similar percentage of N removal (~ 42–52%) as did transformations occurring deeper within the coastal aquifer salinity mixing zone (~ 42–47%). Seasonal shifts in the relative importance of biogeochemical processes including denitrification, nitrification, dissimilatory nitrate reduction, and assimilation altered the composition of the flux to estuarine surface water, which was dominated by ammonium in June and by nitrate in August, despite the endmember-based observation that fixed N in discharging groundwater was strongly dominated by nitrate. This may have important ramifications for the ecology and management of estuaries, since past N loading estimates have generally assumed conservative transport from the nearshore aquifer to estuary.

","language":"English","publisher":"Wiley","doi":"10.1002/lno.11858","usgsCitation":"Brooks, T.W., Kroeger, K.D., Michael, H.A., and York, J.K., 2021, Oxygen-controlled recirculating seepage meter reveals extent of nitrogen transformation in discharging coastal groundwater at the aquifer–estuary interface: Limnology and Oceanography, v. 66, no. 8, p. 3055-3069, https://doi.org/10.1002/lno.11858.","productDescription":"15 p.","startPage":"3055","endPage":"3069","ipdsId":"IP-124776","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"links":[{"id":452017,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/lno.11858","text":"External Repository"},{"id":386388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-06-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Brooks, Thomas W. 0000-0002-0555-3398 wallybrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-0555-3398","contributorId":5989,"corporation":false,"usgs":true,"family":"Brooks","given":"Thomas","email":"wallybrooks@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":817339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michael, Holly A.","contributorId":190224,"corporation":false,"usgs":false,"family":"Michael","given":"Holly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":817340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"York, Joanna K.","contributorId":140023,"corporation":false,"usgs":false,"family":"York","given":"Joanna","email":"","middleInitial":"K.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":817341,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221708,"text":"70221708 - 2021 - Online-coupling of widely-ranged timescales to model coral reef development","interactions":[],"lastModifiedDate":"2021-06-29T14:46:51.786211","indexId":"70221708","displayToPublicDate":"2021-06-03T09:44:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7599,"text":"Environmental Modeling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Online-coupling of widely-ranged timescales to model coral reef development","docAbstract":"

The increasing pressure on Earth's ecosystems due to climate change is becoming more and more evident and the impacts of climate change are especially visible on coral reefs. Understanding how climate change interacts with the physical environment of reefs to impact coral growth and reef development is critically important to predicting the persistence of reefs into the future. In this study, a biophysical model was developed including four environmental factors in a feedback loop with the coral's biology: (1) light; (2) hydrodynamics; (3) temperature; and (4) pH. The submodels are online coupled, i.e. regularly exchanging information and feedbacks while the model runs. This ensures computational efficiency despite the widely-ranged timescales. The composed biophysical model provides a significant step forward in understanding the processes that modulate the evolution of coral reefs, as it is the first construction of a model in which the hydrodynamics are included in the feedback loop.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105103","usgsCitation":"Hendrickx, G., Herman, P.M., Dijkstra, J.T., Storlazzi, C.D., and Toth, L., 2021, Online-coupling of widely-ranged timescales to model coral reef development: Environmental Modeling and Software, v. 143, 105103, 12 p., https://doi.org/10.1016/j.envsoft.2021.105103.","productDescription":"105103, 12 p.","ipdsId":"IP-121545","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":452022,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105103","text":"Publisher Index Page"},{"id":386863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hendrickx, Gijs","contributorId":260697,"corporation":false,"usgs":false,"family":"Hendrickx","given":"Gijs","email":"","affiliations":[{"id":27619,"text":"TU Delft","active":true,"usgs":false}],"preferred":false,"id":818489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herman, Peter M. J.","contributorId":207157,"corporation":false,"usgs":false,"family":"Herman","given":"Peter","email":"","middleInitial":"M. J.","affiliations":[{"id":37466,"text":"Department of Estuarine and Delta Systems, Royal Netherlands Institute for Sea Research (NIOZ) and Utrecht University, PO Box 140, Yerseke NL-4400 AC, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":818490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dijkstra, Jasper T.","contributorId":260698,"corporation":false,"usgs":false,"family":"Dijkstra","given":"Jasper","email":"","middleInitial":"T.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":818491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818492,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818493,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254573,"text":"70254573 - 2021 - Effects of climate and irrigation on GRACE-based estimates of water storage changes in major US aquifers","interactions":[],"lastModifiedDate":"2024-06-03T11:50:37.905478","indexId":"70254573","displayToPublicDate":"2021-06-03T06:45:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Effects of climate and irrigation on GRACE-based estimates of water storage changes in major US aquifers","docAbstract":"

Understanding climate and human impacts on water storage is critical for sustainable water-resources management. Here we assessed climate and human drivers of total water storage (TWS) variability from Gravity Recovery and Climate Experiment (GRACE) satellites compared with drought severity and irrigation water use in 14 major aquifers in the United States. Results show that long-term variability in TWS tracked by GRACE satellites is dominated by interannual variability in most of the 14 major US aquifers. Low TWS trends in the humid eastern U.S. are linked to low drought intensity. Although irrigation pumpage in the humid Mississippi Embayment aquifer exceeded that in the semi-arid California Central Valley, a surprising lack of TWS depletion in the Mississippi Embayment aquifer is attributed to extensive streamflow capture. Marked storage depletion in the semi-arid southwestern Central Valley and south-central High Plains totaled ∼90 km3, about three times greater than the capacity of Lake Mead, the largest U.S. reservoir. Depletion in the Central Valley was driven by long-term droughts (⩽5 yr) amplified by switching from mostly surface water to groundwater irrigation. Low or slightly rising TWS trends in the northwestern (Columbia and Snake Basins) US are attributed to dampening drought impacts by mostly surface water irrigation. GRACE satellite data highlight synergies between climate and irrigation, resulting in little impact on TWS in the humid east, amplified TWS depletion in the semi-arid southwest and southcentral US, and dampened TWS deletion in the northwest and north central US Sustainable groundwater management benefits from conjunctive use of surface water and groundwater, inefficient surface water irrigation promoting groundwater recharge, efficient groundwater irrigation minimizing depletion, and increasing managed aquifer recharge. This study has important implications for sustainable water development in many regions globally.

","language":"English","publisher":"IOPScience","doi":"10.1088/1748-9326/ac16ff","usgsCitation":"Scanlon, B.R., Rateb, A., Pool, D., Sanford, W.E., Save, H., Sun, A.Y., Long, D., and Fuchs, B., 2021, Effects of climate and irrigation on GRACE-based estimates of water storage changes in major US aquifers: Environmental Research Letters, v. 16, no. 9, 094009, 14 p., https://doi.org/10.1088/1748-9326/ac16ff.","productDescription":"094009, 14 p.","ipdsId":"IP-130369","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":452025,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac16ff","text":"Publisher Index Page"},{"id":429443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n 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Pickle Research Campus, Bldg. 130, 10100 Burnet Rd., Austin, TX 78758-4445","active":true,"usgs":false}],"preferred":false,"id":901930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rateb, Ahsraf 0000-0002-8875-1508","orcid":"https://orcid.org/0000-0002-8875-1508","contributorId":337082,"corporation":false,"usgs":false,"family":"Rateb","given":"Ahsraf","affiliations":[{"id":80965,"text":"Bureau of Economic Geology, University of Texas","active":true,"usgs":false}],"preferred":false,"id":901931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pool, Donald R. 0001-1234-4321-0505","orcid":"https://orcid.org/0001-1234-4321-0505","contributorId":337083,"corporation":false,"usgs":false,"family":"Pool","given":"Donald R.","affiliations":[{"id":80967,"text":"Retired USGS, Arizona Water Science Center","active":true,"usgs":false}],"preferred":false,"id":901932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":337084,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":901933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Save, Himanshu","contributorId":187510,"corporation":false,"usgs":false,"family":"Save","given":"Himanshu","email":"","affiliations":[],"preferred":false,"id":902001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sun, Alexander Y. 0000-0002-6365-8526","orcid":"https://orcid.org/0000-0002-6365-8526","contributorId":302987,"corporation":false,"usgs":false,"family":"Sun","given":"Alexander","email":"","middleInitial":"Y.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":902002,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Long, Di","contributorId":187511,"corporation":false,"usgs":false,"family":"Long","given":"Di","email":"","affiliations":[],"preferred":false,"id":902003,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fuchs, Brian","contributorId":192359,"corporation":false,"usgs":false,"family":"Fuchs","given":"Brian","email":"","affiliations":[],"preferred":false,"id":902004,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70229459,"text":"70229459 - 2021 - The roles of environmental variation and parasite survival in virulence–transmission relationships","interactions":[],"lastModifiedDate":"2022-03-09T15:44:13.307405","indexId":"70229459","displayToPublicDate":"2021-06-02T09:39:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3908,"text":"Royal Society Open Science","active":true,"publicationSubtype":{"id":10}},"title":"The roles of environmental variation and parasite survival in virulence–transmission relationships","docAbstract":"

Disease outbreaks are a consequence of interactions among the three components of a host–parasite system: the infectious agent, the host and the environment. While virulence and transmission are widely investigated, most studies of parasite life-history trade-offs are conducted with theoretical models or tractable experimental systems where transmission is standardized and the environment controlled. Yet, biotic and abiotic environmental factors can strongly affect disease dynamics, and ultimately, host–parasite coevolution. Here, we review research on how environmental context alters virulence–transmission relationships, focusing on the off-host portion of the parasite life cycle, and how variation in parasite survival affects the evolution of virulence and transmission. We review three inter-related ‘approaches’ that have dominated the study of the evolution of virulence and transmission for different host–parasite systems: (i) evolutionary trade-off theory, (ii) parasite local adaptation and (iii) parasite phylodynamics. These approaches consider the role of the environment in virulence and transmission evolution from different angles, which entail different advantages and potential biases. We suggest improvements to how to investigate virulence–transmission relationships, through conceptual and methodological developments and taking environmental context into consideration. By combining developments in life-history evolution, phylogenetics, adaptive dynamics and comparative genomics, we can improve our understanding of virulence–transmission relationships across a diversity of host–parasite systems that have eluded experimental study of parasite life history.

","language":"English","publisher":"Royal Society Publishing","doi":"10.1098/rsos.210088","usgsCitation":"Turner, W.C., Kamath, P., van Heerden, H., Huang, Y., Barandongo, Z., Bruce, S.A., and Kausrud, K., 2021, The roles of environmental variation and parasite survival in virulence–transmission relationships: Royal Society Open Science, v. 8, no. 6, 210088, 21 p., https://doi.org/10.1098/rsos.210088.","productDescription":"210088, 21 p.","ipdsId":"IP-125282","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":452029,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsos.210088","text":"Publisher Index Page"},{"id":396918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Turner, Wendy Christine 0000-0002-0302-1646","orcid":"https://orcid.org/0000-0002-0302-1646","contributorId":287053,"corporation":false,"usgs":true,"family":"Turner","given":"Wendy","email":"","middleInitial":"Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":837533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kamath, Pauline L.","contributorId":288151,"corporation":false,"usgs":false,"family":"Kamath","given":"Pauline L.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":837534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Heerden, Henriette","contributorId":288152,"corporation":false,"usgs":false,"family":"van Heerden","given":"Henriette","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":837535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huang, Yen-Hua","contributorId":288153,"corporation":false,"usgs":false,"family":"Huang","given":"Yen-Hua","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":837536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barandongo, Zoe R.","contributorId":288154,"corporation":false,"usgs":false,"family":"Barandongo","given":"Zoe R.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":837537,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bruce, Spencer A.","contributorId":288155,"corporation":false,"usgs":false,"family":"Bruce","given":"Spencer","email":"","middleInitial":"A.","affiliations":[{"id":61712,"text":"University of Albany SUNY","active":true,"usgs":false}],"preferred":false,"id":837538,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kausrud, Kyrre","contributorId":288159,"corporation":false,"usgs":false,"family":"Kausrud","given":"Kyrre","affiliations":[{"id":61713,"text":"Norwegian Veterinary Institute","active":true,"usgs":false}],"preferred":false,"id":837539,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70221076,"text":"sir20215024 - 2021 - Use of dissolved oxygen monitoring to evaluate phosphorus loading in Connecticut streams, 2015–18","interactions":[],"lastModifiedDate":"2021-06-02T17:25:11.979978","indexId":"sir20215024","displayToPublicDate":"2021-06-02T08:11:17","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5024","displayTitle":"Use of Dissolved Oxygen Monitoring to Evaluate Phosphorus Loading in Connecticut Streams, 2015–18","title":"Use of dissolved oxygen monitoring to evaluate phosphorus loading in Connecticut streams, 2015–18","docAbstract":"

The Connecticut Department of Energy and Environmental Protection (CT DEEP) has developed an interim phosphorus reduction strategy to establish water-quality-based phosphorus limits in nontidal freshwaters for industrial and municipal water pollution control facilities. A recommendation in the strategy included the addition of diurnal dissolved oxygen (DO) sampling to the sampling of diatom communities collected by CT DEEP. The chemistry data coupled with biological data will help to examine the effects of phosphorus loading in streams. The U.S. Geological Survey (USGS), in cooperation with the CT DEEP and New England Interstate Water Pollution Control Commission, implemented a summer DO monitoring program from 2015 to 2018 to examine the effects of phosphorus loading in streams. Continuous DO data were collected at 18 sites in streams with varying concentrations of phosphorus throughout the State of Connecticut. Discrete water-quality nutrient data were collected by the USGS at 11 of the 18 sites. All continuous and discrete data collected from June to September for the 4 years were examined for all sites. This report documents a pattern of diurnal DO for monitoring sites across 4 years and presents estimated daily gross primary productivity (GPP), ecosystem respiration (ER), and a standardized rate coefficient for gas exchange for selected streams. Relations of phosphorus concentrations to the diurnal DO response and stream metabolism are described. Interannual variability in average annual total phosphorus (TP) concentrations and maximum daily DO concentrations were evaluated among sites in years of the study. Streams identified as impaired by CT DEEP such as Naugatuck River at Beacon Falls (USGS station 01208500), Still River at Route 7 at Brookfield Center (USGS station 01201487), and Quinnipiac River at Wallingford (USGS station 01196500) had higher TP concentrations (greater than 0.10 milligram per liter [mg/L]) throughout the study. Reference streams considered unimpaired had lower concentrations of TP (less than 0.10 mg/L). The range in daily DO concentrations remained less than 4 mg/L for most of the sites during the study except for Naugatuck River at Beacon Falls and Still River at Route 7 at Brookfield Center. Daily GPP and ER were summarized for 11 sites using the maximum likelihood estimation model of the streamMetabolizer package in the R statistical program. The models indicated that most sites had an estimated negative net primary productivity, based on the daily estimates of GPP and ER, which indicates the systems are heterotrophic and dominated by respiration. The high variation of GPP and ER reported for several sites can be affected by many physical, chemical, and biological factors, including the abundance and community composition of phytoplankton, periphyton, and macrophyte algae present. The variability in mean GPP was similar to the variability in maximum DO concentrations when plotted against annual average TP concentrations for the maximum likelihood estimation model in streamMetabolizer. The concept that phosphorus loading can affect the stream metabolism requires more detailed knowledge of stream geomorphic variables (canopy cover, stream velocity, water depth) and algal communities to help improve the scientific basis for managing phosphorus loading.

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Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-06-02","noUsgsAuthors":false,"publicationDate":"2021-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Izbicki, Brittney 0000-0002-9161-0415 bizbicki@usgs.gov","orcid":"https://orcid.org/0000-0002-9161-0415","contributorId":207391,"corporation":false,"usgs":true,"family":"Izbicki","given":"Brittney","email":"bizbicki@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":816705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morrison, Jonathan 0000-0002-1756-4609 jmorriso@usgs.gov","orcid":"https://orcid.org/0000-0002-1756-4609","contributorId":2274,"corporation":false,"usgs":true,"family":"Morrison","given":"Jonathan","email":"jmorriso@usgs.gov","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816706,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221164,"text":"70221164 - 2021 - Short‐period surface‐wave tomography in the continental United States— A resource for research","interactions":[],"lastModifiedDate":"2021-11-01T15:22:56.646029","indexId":"70221164","displayToPublicDate":"2021-06-02T07:32:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Short‐period surface‐wave tomography in the continental United States— A resource for research","docAbstract":"

The variation of phase and group velocity dispersion of Love and Rayleigh waves was determined for the continental United States and adjacent Canada. By processing ambient noise from the broadband channels of the Transportable Array (TA) of USArray and several Program for the Array Seismic Studies of the Continental Lithosphere experiments and using some earthquake recordings, the effort was focused on determining dispersion down to periods as short as 2 s. The relatively short distances between TA stations permitted the use of a 25  km×25  km\">25  km×25  km grid for the four independent tomographic inversions (Love and Rayleigh and phase and group velocity). One reason for trying to obtain short‐period dispersion was to have a data set capable of constraining upper crust velocity models for use in determining regional moment tensors. The benefit of focusing on short‐period dispersion is apparent in the tomography maps—shallow geologic structures such as the Mid‐Continent Rift, and the Michigan, Illinois, Anadarko, Arkoma, and Appalachian basins are imaged. In our processing, we noted that the phase velocities were more robustly determined than the group velocities. We also noted that the inability to obtain dispersion at short periods shows distinct regional patterns that may be related to the local upper crust structure.

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J.","affiliations":[{"id":52339,"text":"Department of Geosciences, Penn State, 440 Deike Building, University Park, PA 16802","active":true,"usgs":false}],"preferred":false,"id":816918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":816919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aziz-Zanjani, A.","contributorId":259272,"corporation":false,"usgs":false,"family":"Aziz-Zanjani","given":"A.","email":"","affiliations":[{"id":52342,"text":"Department of Earth and Atmospheric Sciences, Saint Louis University, 3642 Lindell Boulevard, St. Louis, MO 63108 USA","active":true,"usgs":false}],"preferred":false,"id":816920,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boschelli, J.","contributorId":259273,"corporation":false,"usgs":false,"family":"Boschelli","given":"J.","affiliations":[{"id":52342,"text":"Department of Earth and Atmospheric Sciences, Saint Louis University, 3642 Lindell Boulevard, St. Louis, MO 63108 USA","active":true,"usgs":false}],"preferred":false,"id":816921,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221082,"text":"sir20215037 - 2021 - Sediment concentrations and loads upstream from and through John Redmond Reservoir, east-central Kansas, 2010–19","interactions":[],"lastModifiedDate":"2021-06-02T13:05:23.095316","indexId":"sir20215037","displayToPublicDate":"2021-06-02T06:12:32","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5037","displayTitle":"Sediment Concentrations and Loads Upstream from and through John Redmond Reservoir, East-Central Kansas, 2010–19","title":"Sediment concentrations and loads upstream from and through John Redmond Reservoir, east-central Kansas, 2010–19","docAbstract":"

Streambank erosion and reservoir sedimentation are primary concerns of resource managers in Kansas and throughout many regions of the United States and negatively affect flood control, water supply, and recreation. The Cottonwood and upper Neosho Rivers drain into John Redmond Reservoir, and since reservoir completion in 1964, there has been substantial conservation-pool sedimentation and storage loss in John Redmond Reservoir, causing storage capacity losses more rapidly than most other Federal reservoirs in Kansas. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office, has monitored water quality (temperature, specific conductance, and turbidity) on the Cottonwood River (upstream from the reservoir) and Neosho River (upstream and downstream from the reservoir) since 2007 with additional sites added in 2009. The purpose of this report is to quantify suspended-sediment concentrations, loads, and yields entering and exiting John Redmond Reservoir during January 1, 2010, through December 31, 2019.

Three water-quality monitoring sites were upstream from the reservoir (Cottonwood River near Plymouth, Kansas [USGS site 07182250; hereinafter referred to as “Cottonwood”]; Neosho River at Burlingame Road near Emporia, Kans. [USGS site 07179750; hereinafter referred to as “Burlingame”]; and Neosho River at Neosho Rapids, Kans. [USGS site 07182390; hereinafter referred to as “Neosho Rapids”]), and one water-quality monitoring site was downstream from the reservoir (Neosho River at Burlington, Kans. [USGS site 07182510; hereinafter referred to as “Burlington”]). The Neosho Rapids streamgage is downstream from the confluence of the Cottonwood and upper Neosho Rivers and has a contributing drainage area accounting for 91 percent of the total contributing drainage area to John Redmond Reservoir.

Continuously measured streamflow, water quality, and discrete water-quality data were used to develop updated regression models to compute suspended-sediment concentrations, loads, and yields upstream and downstream from John Redmond Reservoir in east-central Kansas. Several turbidity sensors were deployed during the analysis period, and there are no established relations between the sensors; therefore, individual models for each sensor were developed. Model statistics for the turbidity and suspended-sediment concentration linear regression models were better (based on the coefficient of determination, root mean square error, and model standard percentage error) than the streamflow and suspended-sediment concentration linear regression models, indicating better model performance. Computed concentrations, loads, and yields do not account for the ungaged 9 percent of the drainage basin downstream from the Neosho Rapids streamgage.

Mean daily suspended-sediment loads upstream from the reservoir were largest at Neosho Rapids (2,250 tons), second largest at Cottonwood (2,180 tons), and smallest at Burlingame (624 tons). Streamflow at Burlington was predominately regulated by reservoir releases, and mean daily suspended-sediment loads were smaller (286 tons) than at upstream sites. Among the upstream sites, Cottonwood had the largest mean daily suspended-sediment concentration (179 milligrams per liter [mg/L]), followed by Neosho Rapids (162 mg/L), and Burlingame (108 mg/L). Burlington had the smallest mean daily suspended-sediment concentration of all sites (46 mg/L).

Annual reservoir trapping efficiency ranged from 82 to 94 percent, and the largest sediment mass trapped was during 2019 (2,230,000 tons). Reservoir storage decreased an estimated 7,750 acre-feet during 2010 and 2014–19. Using the mean trapping efficiency to estimate suspended-sediment loads during years with missing data (2011–13), the total estimated reservoir storage lost to sedimentation for the analysis period (2010–19) was 8,690 acre-feet, about 17 percent of the remaining storage space reported in 2007. The mean annual sedimentation rate during the analysis period (747 acre-feet per year) was about 85 percent larger than the design sedimentation rate (404 acre-feet per year) originally projected during construction. Different reservoir outflow management strategies, including operating near normal capacity as opposed to higher flood pool levels, could reduce the total reservoir storage lost by 3 percent (about 261 acre-feet), which is equal to 14 percent of the total sediment removed during the dredging operation in 2016.

During the study period, about 56 percent of the total suspended-sediment load was transported during streamflows greater than the National Weather Service flood action stage at the upstream sites (0.1–5 percent of the record; Cottonwood mean: 48 percent; Burlingame mean: 40 percent; Neosho Rapids mean: 78 percent). Disproportionately large sediment loads were delivered during short periods of time, and localized efforts of stream erosion protection (streambank stabilization, riparian buffers) were likely to be overwhelmed. Precipitation frequency and intensity are projected to continue to increase in this region; therefore, future sediment reduction strategies that account for extreme episodic events may be beneficial. Changes to reservoir outflow management could also minimize sediment accumulation while still preserving flood control. Continued investigation of sediment reduction measures is necessary for future mitigation with the understanding that sedimentation rate is largely driven by high flows. Results from this study can be used to calibrate sediment models, explore sediment reduction strategies, highlight the importance of continued water-quality monitoring to determine effectiveness and changes in sediment transport, and assess the ability of John Redmond Reservoir to support designated uses into the future.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215037","collaboration":"Prepared in cooperation with the Kansas Water Office","usgsCitation":"Kramer, A.R., Peterman-Phipps, C.L., Mahoney, M.D., and Lukasz, B.S., 2021, Sediment concentrations and loads upstream from and through John Redmond Reservoir, east-central Kansas, 2010–19: U.S. Geological Survey Scientific Investigations Report 2021–5037, 49 p., https://doi.org/10.3133/sir20215037.","productDescription":"Report: ix, 50 p; Appendixes: 12; Dataset","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-119997","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":386084,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix09.pdf","text":"Appendix 9","size":"457 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 9","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182250, Cottonwood River near Plymouth, Kansas, during January 1, 2010, through December 31, 2019"},{"id":386074,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5037/coverthb.jpg"},{"id":386075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037"},{"id":386076,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix01.pdf","text":"Appendix 1","size":"408 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 1","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182250, Cottonwood River near Plymouth, Kansas, during January 1, 2010, through April 22, 2015"},{"id":386078,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix03.pdf","text":"Appendix 3","size":"432 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 3","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182390, Neosho River at Neosho Rapids, Kansas, during January 1, 2010, through September 24, 2015"},{"id":386079,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix04.pdf","text":"Appendix 4","size":"455 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 4","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182510, Neosho River at Burlington, Kansas, during January 1, 2010, through October 16, 2015"},{"id":386088,"rank":15,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":386087,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix12.pdf","text":"Appendix 12","size":"451 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 12","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182510, Neosho River at Burlington, Kansas, during January 1, 2010, through December 31, 2019"},{"id":386086,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix11.pdf","text":"Appendix 11","size":"449 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 11","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182390, Neosho River at Neosho Rapids, Kansas, during January 1, 2010, through December 31, 2019"},{"id":386083,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix08.pdf","text":"Appendix 8","size":"427 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 8","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182510, Neosho River at Burlington, Kansas, during October 23, 2015, through December 31, 2019"},{"id":386082,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix07.pdf","text":"Appendix 7","size":"391 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 7","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182390, Neosho River at Neosho Rapids, Kansas, during November 13, 2015, through December 31, 2019"},{"id":386085,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix10.pdf","text":"Appendix 10","size":"418 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 10","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07179750, Neosho River at Burlingame Road near Emporia, Kansas, during January 1, 2010, through December 31, 2019"},{"id":386080,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix05.pdf","text":"Appendix 5","size":"376 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 5","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182250, Cottonwood River near Plymouth, Kansas, during April 22, 2015, through December 31, 2019"},{"id":386081,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix06.pdf","text":"Appendix 6","size":"399 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 6","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07179750, Neosho River at Burlingame Road near Emporia, Kansas, during May 2, 2015, through December 31, 2019"},{"id":386077,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix02.pdf","text":"Appendix 2","size":"414 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 2","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07179750, Neosho River at Burlingame Road near Emporia, Kansas, during January 1, 2010, through December 16, 2012"}],"country":"United States","state":"Kansas","otherGeospatial":"John Redmond Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.52838134765624,\n 38.01131226070673\n ],\n [\n -95.49041748046875,\n 38.01131226070673\n ],\n [\n -95.49041748046875,\n 39.27266344858914\n ],\n [\n -97.52838134765624,\n 39.27266344858914\n ],\n [\n -97.52838134765624,\n 38.01131226070673\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-06-02","noUsgsAuthors":false,"publicationDate":"2021-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Kramer, Ariele R. 0000-0002-7075-3310 akramer@usgs.gov","orcid":"https://orcid.org/0000-0002-7075-3310","contributorId":185245,"corporation":false,"usgs":true,"family":"Kramer","given":"Ariele","email":"akramer@usgs.gov","middleInitial":"R.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":816715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterman-Phipps, Cara L. 0000-0003-1822-2552","orcid":"https://orcid.org/0000-0003-1822-2552","contributorId":259166,"corporation":false,"usgs":true,"family":"Peterman-Phipps","given":"Cara","email":"","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":816716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahoney, Matthew D. 0000-0002-9008-7132","orcid":"https://orcid.org/0000-0002-9008-7132","contributorId":206054,"corporation":false,"usgs":true,"family":"Mahoney","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":816717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lukasz, Bradley S. 0000-0001-5438-5901","orcid":"https://orcid.org/0000-0001-5438-5901","contributorId":225021,"corporation":false,"usgs":true,"family":"Lukasz","given":"Bradley","email":"","middleInitial":"S.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":816718,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221885,"text":"70221885 - 2021 - Multivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers","interactions":[],"lastModifiedDate":"2021-07-13T18:57:42.166406","indexId":"70221885","displayToPublicDate":"2021-06-01T13:53:23","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Multivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers","docAbstract":"

Chemically, petroleum is an extraordinarily complex mixture of different types of hydrocarbons that are now possible to isolate and identify because of advances in geochemistry. Here, we use biomarkers and carbon isotopes to establish genetic differences and similarities among oil samples. Conventional approaches for evaluating biomarker and carbon isotope relative abundances include statistical techniques such as principal component and cluster analysis. Considering that proportions of the different hydrocarbon molecules are relative parts of a laboratory sample, the data are compositional in nature, thus requiring the use of log-ratio approaches for adequate mathematical modeling. We apply both traditional and compositional modeling approaches to crude oil samples from an onshore area of about 50,000 square miles in southeast Texas. The data comprise 177 crude oil samples from producing oil fields that include key biomarkers, elemental, and isotopic values commonly used in source rock correlation studies. Our results indicate that compositional modeling has higher discriminating power and lower uncertainty than the traditional approach, allowing the identification of up to 16 clusters. Each cluster represents one oil family from a source rock organofacies ranging from Carboniferous to Paleogene. The families provide new insights into important petroleum systems in the Texas onshore region of the Gulf of Mexico sedimentary basin.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Advances in compositional data analysis—Festschrift in honor of Vera-Pawlowsky-Glahn","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-71175-7_16","usgsCitation":"Olea, R., Martin-Fernandez, J.A., and Craddock, W.H., 2021, Multivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers, chap. of Advances in compositional data analysis—Festschrift in honor of Vera-Pawlowsky-Glahn, p. 303-307, https://doi.org/10.1007/978-3-030-71175-7_16.","productDescription":"5 p.","startPage":"303","endPage":"307","ipdsId":"IP-112995","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":387163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.119140625,\n 25.97779895546436\n ],\n [\n -96.767578125,\n 27.68352808378776\n ],\n [\n -95.11962890625,\n 28.497660832963472\n ],\n [\n -93.8232421875,\n 29.49698759653577\n ],\n [\n -93.97705078125,\n 30.20211367909724\n ],\n [\n -95.55908203125,\n 30.240086360983426\n ],\n [\n -97.3388671875,\n 28.9600886880068\n ],\n [\n -98.23974609375,\n 27.586197857692664\n ],\n [\n -97.91015624999999,\n 26.13571361317392\n ],\n [\n -97.119140625,\n 25.97779895546436\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-06-02","publicationStatus":"PW","contributors":{"editors":[{"text":"Fitzmoser, Peter","contributorId":261055,"corporation":false,"usgs":false,"family":"Fitzmoser","given":"Peter","email":"","affiliations":[],"preferred":false,"id":819247,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Hron, Karel","contributorId":261056,"corporation":false,"usgs":false,"family":"Hron","given":"Karel","email":"","affiliations":[],"preferred":false,"id":819248,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Martin-Fernandez, Josep Antoni","contributorId":208528,"corporation":false,"usgs":false,"family":"Martin-Fernandez","given":" Josep Antoni","affiliations":[],"preferred":false,"id":819249,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Palarea-Albaladejo, Javier","contributorId":120518,"corporation":false,"usgs":true,"family":"Palarea-Albaladejo","given":"Javier","email":"","affiliations":[],"preferred":false,"id":819250,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":224285,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":819213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin-Fernandez, J. A 0000-0003-2366-1592","orcid":"https://orcid.org/0000-0003-2366-1592","contributorId":260957,"corporation":false,"usgs":false,"family":"Martin-Fernandez","given":"J.","email":"","middleInitial":"A","affiliations":[{"id":28183,"text":"University of Girona","active":true,"usgs":false}],"preferred":false,"id":819214,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":819215,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70255078,"text":"70255078 - 2021 - Modeling opportunistic exploitation: Increased extinction risk when targeting more than one species","interactions":[],"lastModifiedDate":"2024-06-12T16:51:25.835725","indexId":"70255078","displayToPublicDate":"2021-06-01T11:48:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling opportunistic exploitation: Increased extinction risk when targeting more than one species","docAbstract":"

Extinction rates are increasing globally, and direct exploitation is an important driver. Many pathways have been proposed to explain how exploitation can lead to extinction. One of these proposed but understudied multispecies pathways is opportunistic exploitation, which occurs when a highly valuable but rare species is encountered and targeted during exploitation of a less valuable, but more common, target species. Using individual-based simulations of exploiters in a two-species spatial model, we contribute evidence which supports that opportunistic exploitation increases depletion when compared to single-species exploitation, and is as detrimental to the more valuable, rare species as the anthropogenic Allee effect (where price increases with rarity) and the Allee effect (where population growth declines at low abundance). The most important factors affecting the impact of opportunistic exploitation are gross revenue and abundance of the more common, less valuable species, while ease of capture and growth rate of the more common, less valuable species are less important. Thus, valuable but rare species are most at risk when harvested alongside low-value abundant species; this information is relevant for managers focused on protection of rare species in multispecies systems.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2021.109611","usgsCitation":"Thurner, S., Converse, S.J., and Branch, T., 2021, Modeling opportunistic exploitation: Increased extinction risk when targeting more than one species: Ecological Modelling, v. 454, 109611, 12 p., https://doi.org/10.1016/j.ecolmodel.2021.109611.","productDescription":"109611, 12 p.","ipdsId":"IP-126753","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":452034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2021.109611","text":"Publisher Index Page"},{"id":430024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"454","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thurner, S.","contributorId":338523,"corporation":false,"usgs":false,"family":"Thurner","given":"S.","email":"","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":903328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903329,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Branch, Trevor A.","contributorId":172088,"corporation":false,"usgs":false,"family":"Branch","given":"Trevor A.","affiliations":[],"preferred":false,"id":903330,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221396,"text":"70221396 - 2021 - A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons","interactions":[],"lastModifiedDate":"2021-06-14T12:56:49.325445","indexId":"70221396","displayToPublicDate":"2021-06-01T07:54:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8932,"text":"Shore and Beach","active":true,"publicationSubtype":{"id":10}},"title":"A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons","docAbstract":"Hurricanes are known to play a critical role in reshaping coastlines, but often only impacts on the open ocean coast are considered, ignoring seaward-directed forces and responses. The identification of subaerial evidence for storm-induced seaward transport is a critical step towards understanding its impact on coastal resiliency. The visual features, found in the National Oceanic and Atmospheric Administration, National Geodetic Survey Emergency Response Imagery (ERI) collected after recent hurricanes on the U.S. East Atlantic and Gulf of Mexico coasts, include scours and channelized erosion, but also deposition on the shoreface or in the nearshore as deltas and fans of various sizes. We catalog all available ERI and describe recently formed features found on the North Core Banks, North Carolina, after Hurricane Dorian (2019); the Carolina coasts after Hurricane Isaias (2020); the Isles Dernieres, Louisiana, after Hurricane Zeta (2020); and the southwest coast of Louisiana, after Hurricanes Laura and Delta (2020). Hundreds of features were identified over nearly 200 km of coastline with the density of features exceeding 20 per km in some areas. Individual features range in size from 5 m to 500 m in the alongshore, with similar dimensions in the cross-shore direction, including the formation or reactivation of outlets. The extensive occurrence of these storm-induced return-flow and seawardflow morphologic features demonstrates that their role in coastal evolution and resilience may be more prominent than previously thought. Based on these observations we propose clarifying terms for return- and seaward-flow features to distinguish them from more frequently documented landward-flow features and advocate for their inclusion in coastal change hazards classification schemes and coastal evolution morphodynamic models.","language":"English","publisher":"American Shore & Beach Preservation Association","doi":"10.34237/1008924","usgsCitation":"Over, J.R., Brown, J., Sherwood, C.R., Hegermiller, C., Wernette, P., Ritchie, A.C., and Warrick, J.A., 2021, A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons: Shore and Beach, v. 89, no. 2, p. 31-40, https://doi.org/10.34237/1008924.","productDescription":"10 p.","startPage":"31","endPage":"40","ipdsId":"IP-126879","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":452060,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.31223/x5dp69","text":"External Repository"},{"id":386467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"southeast United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.306640625,\n 25.005972656239187\n ],\n [\n -75.146484375,\n 25.005972656239187\n ],\n [\n -75.146484375,\n 36.59788913307022\n ],\n [\n -94.306640625,\n 36.59788913307022\n ],\n [\n -94.306640625,\n 25.005972656239187\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"89","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Over, Jin-Si R. 0000-0001-6753-7185 jover@usgs.gov","orcid":"https://orcid.org/0000-0001-6753-7185","contributorId":260178,"corporation":false,"usgs":true,"family":"Over","given":"Jin-Si","email":"jover@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Jenna A. 0000-0003-3137-7073","orcid":"https://orcid.org/0000-0003-3137-7073","contributorId":208564,"corporation":false,"usgs":true,"family":"Brown","given":"Jenna A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hegermiller, Christie 0000-0002-6383-7508 chegermiller@usgs.gov","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":149010,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","email":"chegermiller@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wernette, Phillipe Alan 0000-0002-8902-5575","orcid":"https://orcid.org/0000-0002-8902-5575","contributorId":259274,"corporation":false,"usgs":true,"family":"Wernette","given":"Phillipe Alan","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ritchie, Andrew C. aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817515,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817516,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70221599,"text":"70221599 - 2021 - Watersheds and drainage networks","interactions":[],"lastModifiedDate":"2021-06-25T12:49:28.165348","indexId":"70221599","displayToPublicDate":"2021-06-01T07:47:23","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Watersheds and drainage networks","docAbstract":"

This topic is an overview of basic concepts about how the distribution of water on the Earth, with specific regard to watersheds, stream and river networks, and waterbodies are represented by geographic data. The flowing and non-flowing bodies of water on the earth’s surface vary in extent largely due to seasonal and annual changes in climate and precipitation. Consequently, modeling the detailed representation of surface water using geographic information is important. The area of land that collects surface runoff and other flowing water and drains to a common outlet location defines a watershed. Terrain and surface features can be naturally divided into watersheds of various sizes. Drainage networks are important data structures for modeling the distribution and movement of surface water over the terrain.  Numerous tools and methods exist to extract drainage networks and watersheds from digital elevation models (DEMs). The cartographic representations of surface water are referred to as hydrographic features and consist of a snapshot at a specific time. Hydrographic features can be assigned general feature types, such as lake, pond, river, and ocean. Hydrographic features can be stored, maintained, and distributed for use through vector geospatial databases, such as the National Hydrography Dataset (NHD) for the United States.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The geographic information science & technology body of knowledge","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University Consortium for Geographic Information Science","doi":"10.22224/gistbok/2021.2.1","usgsCitation":"Stanislawski, L., and Shavers, E.J., 2021, Watersheds and drainage networks, chap. of The geographic information science & technology body of knowledge, https://doi.org/10.22224/gistbok/2021.2.1.","ipdsId":"IP-125926","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":452062,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.22224/gistbok/2021.2.1","text":"Publisher Index Page"},{"id":386732,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":818251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":818252,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70243820,"text":"70243820 - 2021 - New interpretations of the ages and origins of the Hawkeye Granite Gneiss and Lyon Mountain Granite Gneiss, Adirondack Mountains, NY: Implications for the nature and timing of Mesoproterozoic plutonism, metamorphism, and deformation","interactions":[],"lastModifiedDate":"2023-05-22T12:43:37.935818","indexId":"70243820","displayToPublicDate":"2021-06-01T07:11:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"New interpretations of the ages and origins of the Hawkeye Granite Gneiss and Lyon Mountain Granite Gneiss, Adirondack Mountains, NY: Implications for the nature and timing of Mesoproterozoic plutonism, metamorphism, and deformation","docAbstract":"The Hawkeye Granite Gneiss and Lyon Mountain Granite Gneiss are widespread Mesoproterozoic plutonic rocks that occur in the amphibolite- to granulite-facies Adirondack Highlands of northern New York, USA. The strongly deformed Hawkeye Granite Gneiss, previously dated by zircon multi-grain thermal ionization mass spectrometry (TIMS) U-Pb analyses at about 1100 Ma, was intruded by the weakly deformed Lyon Mountain Granite Gneiss. Previous sensitive high resolution ion microprobe (SHRIMP) analyses of Lyon Mountain Granite Gneiss zircon rims were considered to record the time of igneous emplacement at about 1.05 Ga, whereas the ages of zircon cores (~1.15 Ga) were interpreted as being inherited from nearby metaigneous country rocks. This interpretation has formed the basis of numerous models for the Mesoproterozoic structural and tectonic evolution of the Adirondacks Highlands.\nNew U-Pb spot analyses (~15-20 µm diameter) by SHRIMP from four samples of Hawkeye Granite Gneiss and eight samples of Lyon Mountain Granite Gneiss challenge the historically accepted ages of the rocks. Using a combination of high-resolution CL imagery of oscillatory zoned cores and weakly zoned to unzoned rims, SHRIMP U-Pb geochronology, SHRIMP trace element geochemistry, and SEM petrography, we conclude that: (1) the Hawkeye Granite Gneiss was emplaced at about 1160 to 1155 Ma; (2) the vast majority of Lyon Mountain Granite Gneiss zircon cores yield ages of 1150 to 1145 Ma and are mainly primary, not inherited; and (3) the Hawkeye Granite Gneiss and Lyon Mountain Granite Gneiss zircon rims (~1080 to 1000 Ma) are metamorphic in origin, not igneous. Thus, both the Hawkeye Granite Gneiss and Lyon Mountain Granite Gneiss are considered herein to be late members of the mangerite-charnockite-granite (MCG) plutonic suite, emplaced during the waning stages of the Shawinigan orogeny. Zircon cores from two small plutons of largely undeformed fayalite granite of the Lyon Mountain Granite Gneiss are about 1142 Ma, providing a minimum age constraint for the termination of the Shawinigan. Zircon rim ages can be deconvoluted into multiple metamorphic events of the Ottawan and Rigolet tectonothermal events. These new interpretations have profound implications for structural, tectonic, and ore deposit models of the Adirondacks Highlands.","language":"English","publisher":"Elsevier","doi":"10.1016/j.precamres.2021.106112","usgsCitation":"Aleinikoff, J.N., Walsh, G., and McAleer, R.J., 2021, New interpretations of the ages and origins of the Hawkeye Granite Gneiss and Lyon Mountain Granite Gneiss, Adirondack Mountains, NY: Implications for the nature and timing of Mesoproterozoic plutonism, metamorphism, and deformation: Precambrian Research, v. 358, 106112, 37 p., https://doi.org/10.1016/j.precamres.2021.106112.","productDescription":"106112, 37 p.","ipdsId":"IP-125459","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":452063,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.precamres.2021.106112","text":"Publisher Index Page"},{"id":417288,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Mountains, Lyon Mountain Granite, Hawkeye Granite","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.48797761630235,\n 44.84476019334153\n ],\n [\n -74.48797761630235,\n 44.35760977189841\n ],\n [\n -73.42439482753956,\n 44.35760977189841\n ],\n [\n -73.42439482753956,\n 44.84476019334153\n ],\n [\n -74.48797761630235,\n 44.84476019334153\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"358","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":873381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Gregory J. 0000-0003-4264-8836","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":265307,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":873382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":873383,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219918,"text":"70219918 - 2021 - 3-D Modeling of the Duluth Complex from geophysical data","interactions":[],"lastModifiedDate":"2021-09-17T15:49:58.370459","indexId":"70219918","displayToPublicDate":"2021-05-31T10:43:45","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"3-D Modeling of the Duluth Complex from geophysical data","docAbstract":"The Mesoproterozoic Duluth Complex in northeastern Minnesota is one of the major plutonic components of the Midcontinent Rift System and hosts a variety of copper-nickel sulfide and platinum-group element deposits. The Duluth Complex is composed of a series of individual mafic and felsic intrusions emplaced 1110-1098 Ma within Paleoproterozoic sedimentary rocks of the Animikie basin and volcanic flows of the Midcontinent Rift. Prior work has included 2-D modeling and qualitative geologic interpretations of gravity and magnetic data (e.g., Chandler, 1990; Chandler and Ferderer, 1989), much of which is still preliminary (V. Chandler, written commun., 2020). Three-dimensional modeling has been limited, with only one 3-D model created using Bouguer gravity data constrained by seismic-reflection interpretations as part of a PhD thesis (Allen, 1994). Given the complex geology of the area, 3-D modeling is useful for providing a complete picture of the variable densities, susceptibilities, and electrical resistivities throughout the Duluth Complex and associated volcanic rocks as well as their depth extent beneath sedimentary cover. Models of these geophysical properties at depth enable more accurate geologic mapping in the subsurface which can lead to an improved understanding of the formation history of the Duluth Complex. \nIn this study, we use aeromagnetic data acquired between 1979-1991 (Chandler, 2007), Bouguer gravity data collected since 1950 (Chandler and Lively, 2019), and magnetotelluric data collected in 2019 to create new 2-D and 3-D geophysical models of the Duluth Complex constrained by seismic reflection, geologic, and rock property data. An inversion of the Bouguer gravity data for thickness of the Duluth Complex using constant densities of 3110 kg/m3 and 2670 kg/m3 for the Duluth Complex and surrounding crustal rocks, respectively, results in thicknesses ranging from ~3-28 km for the Duluth Complex and related intrusions and volcanic rocks (Figure 1A). A 3-D model of the magnetotelluric data reveals low resistivity anomalies at ~5-10 km depth below the northern margin of the Duluth Complex and below the Greenwood Lake intrusion (Figure 1B). We expect to encounter low resistivities at depth associated with the Paleoproterozoic Animikie basin, which makes up the floor of the Duluth Complex, and therefore interpret these anomalies as either the base of the complex or as fragments of Animikie sediments interfingered with igneous intrusive rocks. Finally, 3-D voxel models of density and susceptibility illuminate the subsurface distribution of rock properties below the Duluth Complex which, in combination with resistivity and thickness models, can be used to create a 3-D geologic map of this area.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"67th Institute on Lake Superior Geology Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Institute on Lake Superior Geology","usgsCitation":"Peterson, D.E., Bedrosian, P.A., and Finn, C., 2021, 3-D Modeling of the Duluth Complex from geophysical data, in 67th Institute on Lake Superior Geology Proceedings, p. 52-53.","productDescription":"2 p.","startPage":"52","endPage":"53","ipdsId":"IP-128596","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":389395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":389394,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.lakesuperiorgeology.org/Virtual2021/index.html"}],"country":"United States","state":"Minnesota","otherGeospatial":"Duluth Complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.31787109374999,\n 47.29413372501023\n ],\n [\n -88.48388671874999,\n 47.29413372501023\n ],\n [\n -88.48388671874999,\n 48.46563710044979\n ],\n [\n -93.31787109374999,\n 48.46563710044979\n ],\n [\n -93.31787109374999,\n 47.29413372501023\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, Dana E. 0000-0002-1941-265X","orcid":"https://orcid.org/0000-0002-1941-265X","contributorId":225536,"corporation":false,"usgs":true,"family":"Peterson","given":"Dana","email":"","middleInitial":"E.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":814394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":814395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finn, Carol A. 0000-0002-6178-0405","orcid":"https://orcid.org/0000-0002-6178-0405","contributorId":205010,"corporation":false,"usgs":true,"family":"Finn","given":"Carol A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":814396,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70222361,"text":"70222361 - 2021 - Integration of geophysical evidence suggests that anorthosite composes a significant portion of Grand Marais ridge, an inferred basement high in western Lake Superior","interactions":[],"lastModifiedDate":"2021-07-26T11:46:26.615466","indexId":"70222361","displayToPublicDate":"2021-05-31T10:03:36","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Integration of geophysical evidence suggests that anorthosite composes a significant portion of Grand Marais ridge, an inferred basement high in western Lake Superior","docAbstract":"

The Midcontinent Rift System (MRS) is expressed geophysically by a semi-linear, regional gravity high that trends across the Midcontinent and Great Lakes region of North America. The gravity high is interrupted by two prominent, semi-circular gravity lows, which have been interpreted from modeling and seismic-reflection sections as basement highs of Archean granite (Allen et al., 1997). One is centered southwest of Isle Royale in western Lake Superior (Grand Marais ridge) and the other over Bayfield Peninsula (White’s Ridge). Allen et al. (1997) suggest that the Archean granite highs were pre-rift features that remained high while lava basins of the MRS subsided adjacent to them. Hart et al. (1994) questioned the presence of granitic rocks underlying Grand Marais ridge (GMR) because heat flow measurements there are much lower than is typical for Archean granitic upper crust. They argued that the region must instead be underlain by rocks of low radiogenic heat production, such as gabbro, extending to at least 15 km depth. However, gabbro has high densities and would not produce the observed gravity low. Thus, the geophysical observations appear contradictory. 

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Institute on Lake Superior Geology: Proceedings 2021","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Institute of Lake Superior Geology","usgsCitation":"Grauch, V.J., and Heller, S.J., 2021, Integration of geophysical evidence suggests that anorthosite composes a significant portion of Grand Marais ridge, an inferred basement high in western Lake Superior, in Institute on Lake Superior Geology: Proceedings 2021, v. 67, p. 29-30.","productDescription":"2 p.","startPage":"29","endPage":"30","ipdsId":"IP-128430","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":387398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387391,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcollections.lakeheadu.ca/items/show/3063"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.340576171875,\n 47.56170075451973\n ],\n [\n -89.26391601562499,\n 47.56170075451973\n ],\n [\n -89.26391601562499,\n 47.96785877999251\n ],\n [\n -90.340576171875,\n 47.96785877999251\n ],\n [\n -90.340576171875,\n 47.56170075451973\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.01074218749999,\n 46.76244305208004\n ],\n [\n -90.28564453124999,\n 46.76244305208004\n ],\n [\n -90.28564453124999,\n 47.249406957888446\n ],\n [\n -91.01074218749999,\n 47.249406957888446\n ],\n [\n -91.01074218749999,\n 46.76244305208004\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Grauch, V. J. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":152256,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":819754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heller, Samuel J. 0000-0002-6579-5620 sheller@usgs.gov","orcid":"https://orcid.org/0000-0002-6579-5620","contributorId":201350,"corporation":false,"usgs":true,"family":"Heller","given":"Samuel","email":"sheller@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819755,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222466,"text":"70222466 - 2021 - Field evaluation of an improved solid TFM formulation for use in treating small tributary streams","interactions":[],"lastModifiedDate":"2021-07-30T14:22:37.638537","indexId":"70222466","displayToPublicDate":"2021-05-31T09:21:11","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"Field Evaluation of an Improved Solid TFM Formulation for Use in Treating Small Tributary Streams","title":"Field evaluation of an improved solid TFM formulation for use in treating small tributary streams","docAbstract":"A solid lampricide formulation containing 23% 3-trifluoromethyl-4-nitrophenol (TFM) as the active ingredient was developed in the mid-1980s for use in small tributaries of dendritic streams during routine treatments to kill larval sea lamprey. This TFM bar formulation was designed to use a matrix of commercially prepared surfactants that would dissolve and slowly release their TFM payload over an 8–10-hour period. Although this formulation has proven useful, several matrix surfactants have been discontinued, resulting in the need to reformulate the TFM bar multiple times. Maintaining acceptable performance of the TFM bars while reformulating has been challenging. As a result, an experimental surfactant-free tableted TFM formulation was developed as a potential TFM bar replacement. Release of TFM from the tablet formulation was evaluated in four independent experimental applications made over varied substrates in three small tributaries of the Ford River (Delta County, Michigan). For each tributary, TFM release from tablets was modeled using exponential decay curves and the time required to release 25, 50, 75 and 90% of the TFM tablets was calculated. Differences in water-quality properties were detected using one-way analysis of variance tests, and post-hoc Tukey Honest Significant Difference tests were used to determine which water-quality properties differed among the trials. The influences of water temperature and water velocity on the release of TFM from the tablets has been previously reported; however, in this study substrate type also appeared to be an indicator of TFM release. In this study the performance of the TFM tablets appeared acceptable; however, it may be beneficial to conduct additional investigations to determine storage stability and handling durability as well as to identify potential challenges with mass production.","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Luoma, J.A., Robertson, N., Schueller, J., Schloesser, N., Johnson, T., Severson, T.J., Meulemans, M.J., and Muelemans, E., 2021, Field evaluation of an improved solid TFM formulation for use in treating small tributary streams, 21 p.","productDescription":"21 p.","ipdsId":"IP-127807","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":387600,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387559,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/pubs/pdfs/research/reports/2020_LUO_760150.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Luoma, James A. 0000-0003-3556-0190 jluoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3556-0190","contributorId":4449,"corporation":false,"usgs":true,"family":"Luoma","given":"James","email":"jluoma@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Nicholas","contributorId":237024,"corporation":false,"usgs":false,"family":"Robertson","given":"Nicholas","email":"","affiliations":[{"id":18886,"text":"Northland College","active":true,"usgs":false}],"preferred":false,"id":820121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schueller, Justin R. 0000-0002-7102-3889","orcid":"https://orcid.org/0000-0002-7102-3889","contributorId":213527,"corporation":false,"usgs":true,"family":"Schueller","given":"Justin","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schloesser, Nicholas 0000-0002-3815-5302","orcid":"https://orcid.org/0000-0002-3815-5302","contributorId":237025,"corporation":false,"usgs":true,"family":"Schloesser","given":"Nicholas","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Todd 0000-0003-2152-8528","orcid":"https://orcid.org/0000-0003-2152-8528","contributorId":261519,"corporation":false,"usgs":true,"family":"Johnson","given":"Todd","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Severson, Todd J. 0000-0001-5282-3779 tseverson@usgs.gov","orcid":"https://orcid.org/0000-0001-5282-3779","contributorId":4749,"corporation":false,"usgs":true,"family":"Severson","given":"Todd","email":"tseverson@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meulemans, Matthew J. 0000-0003-4584-8737","orcid":"https://orcid.org/0000-0003-4584-8737","contributorId":261521,"corporation":false,"usgs":true,"family":"Meulemans","given":"Matthew J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820126,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Muelemans, Erica","contributorId":261523,"corporation":false,"usgs":false,"family":"Muelemans","given":"Erica","email":"","affiliations":[{"id":52865,"text":"Northland College, Ashland, WI","active":true,"usgs":false}],"preferred":false,"id":820127,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223180,"text":"70223180 - 2021 - Alaska landbird montoring survey: Alaska regional protocol framework for monitoring landbirds using point counts","interactions":[],"lastModifiedDate":"2021-08-17T14:13:12.185743","indexId":"70223180","displayToPublicDate":"2021-05-31T09:03:14","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5856,"text":"Regional Protocol Framework","active":true,"publicationSubtype":{"id":1}},"title":"Alaska landbird montoring survey: Alaska regional protocol framework for monitoring landbirds using point counts","docAbstract":"

Alaska provides habitat for 143 species of landbirds that occur regularly in the state, about half of which breed predominantly north of the border between the contiguous United States and Canada. The road-based North American Breeding Bird Survey (BBS) provides some data on population trends in Alaska, but most northern populations are inadequately monitored by this program because of a paucity of roads. To remedy this deficiency, Boreal Partners in Flight developed the Alaska Landbird Monitoring Survey (ALMS) to monitor breeding populations of landbirds in off-road areas of Alaska in tandem with data collected from the roadside BBS. The primary objective of ALMS is to monitor long-term population trends of landbirds and other species that can be monitored by diurnal point counts during the breeding season, including many shorebirds and aquatic birds. A secondary objective is to estimate landbird densities by habitat, which can be used to model avian distribution and abundance across Alaska. ALMS is a collaborative program whereby agencies and other entities conduct standardized surveys of breeding birds and their habitats on the lands they manage and then contribute the data to the U.S. Geological Survey Alaska Science Center for storage and analysis.

The short-term implementation goal of ALMS is to monitor birds systematically within each of 100 randomly selected survey blocks, thereby matching the number of BBS surveys conducted in each of Alaska's five Bird Conservation Regions (BCRs). Each block has a mini-grid of 15−25 points that are surveyed biennially, with half of the blocks surveyed in alternating years. Survey blocks are stratified by accessibility and cost-effectiveness. Refuges may opt to limit sites to those accessible by foot, vehicle, boat, or fixed-wing aircraft, as these can be surveyed more inexpensively and reliably over time. Observers survey each point within a survey block for birds using a 10-min point count once per summer on a biennial basis. They collect corresponding habitat data during the first visit and at subsequent 10-year intervals or whenever a disturbance (e.g., fire, wind) has caused a significant change. USGS analyzes ALMS data jointly with BBS data to test for differences between off-road and roadside areas and to increase power to detect statewide trends. Additional blocks can be surveyed in areas that are more difficult and expensive to access as resources become available in the future. Long-term monitoring enables detection of change in bird populations in relation to fire, disease and insect damage, resource development, climate-related change, and other landscape-level disturbances across Alaska. Results from ALMS can also help prioritize conservation and research towards species before they become endangered and require expensive recovery programs.

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Despite its successes, the U.S. Endangered Species Act (ESA) has proven challenging to implement due to funding limitations, workload backlog, and other problems. As threats to species survival intensify and as more species come under threat, the need for the ESA and similar conservation laws and policies in other countries to function efficiently has grown. Attempts by the U.S. Fish and Wildlife Service (USFWS) to streamline ESA decisions include multispecies recovery plans and habitat conservation plans. We address species status assessment (SSA), a USFWS process to inform ESA decisions from listing to recovery, within the context of multispecies and ecosystem planning. Although existing SSAs have a single-species focus, ecosystem-based research can efficiently inform multiple SSAs within a region and provide a foundation for transition to multispecies SSAs in the future. We considered at-risk grassland species and ecosystems within the southeastern United States, where a disproportionate number of rare and endemic species are associated with grasslands. To initiate our ecosystem-based approach, we used a combined literature-based and structured World Café workshop format to identify science needs for SSAs. Discussions concentrated on 5 categories of threats to grassland species and ecosystems, consistent with recommendations to make shared threats a focus of planning under the ESA: (1) habitat loss, fragmentation, and disruption of functional connectivity; (2) climate change; (3) altered disturbance regimes; (4) invasive species; and (5) localized impacts. For each threat, workshop participants identified science and information needs, including database availability, research priorities, and modeling and mapping needs. Grouping species by habitat and shared threats can make the SSA process and other planning processes for conservation of at-risk species worldwide more efficient and useful. We found a combination of literature review and structured discussion effective for identifying the scientific information and analysis needed to support the development of multiple SSAs.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.13777","usgsCitation":"Noss, R., Cartwright, J.M., Estes, D., Witsell, T., Elliott, G., Adams, D.S., Albrecht, M.A., Boyles, R., Comer, P., Doffitt, C., Hill, J.G., Hunter, W.C., Knapp, W.M., Marshall, M., Singhurst, J.R., Tracey, C., Walck, J.L., and Weakley, A., 2021, Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide: Conservation Biology, v. 35, no. 6, p. 1715-1724, https://doi.org/10.1111/cobi.13777.","productDescription":"10 p.","startPage":"1715","endPage":"1724","ipdsId":"IP-122143","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":452069,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/cobi.13777","text":"External 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Center","active":true,"usgs":true}],"preferred":true,"id":818520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Estes, Dwayne","contributorId":260711,"corporation":false,"usgs":false,"family":"Estes","given":"Dwayne","affiliations":[{"id":52648,"text":"Southeastern Grasslands Initiative","active":true,"usgs":false}],"preferred":false,"id":818521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witsell, Theo","contributorId":258187,"corporation":false,"usgs":false,"family":"Witsell","given":"Theo","email":"","affiliations":[],"preferred":false,"id":818522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elliott, Gregg","contributorId":260712,"corporation":false,"usgs":false,"family":"Elliott","given":"Gregg","email":"","affiliations":[{"id":52648,"text":"Southeastern Grasslands Initiative","active":true,"usgs":false}],"preferred":false,"id":818523,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Daniel S. 0000-0001-9695-0577","orcid":"https://orcid.org/0000-0001-9695-0577","contributorId":258189,"corporation":false,"usgs":false,"family":"Adams","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":818524,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Albrecht, Matthew A. 0000-0002-1079-1630","orcid":"https://orcid.org/0000-0002-1079-1630","contributorId":213559,"corporation":false,"usgs":false,"family":"Albrecht","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":38790,"text":"Missouri Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":818525,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boyles, Ryan 0000-0001-9272-867X","orcid":"https://orcid.org/0000-0001-9272-867X","contributorId":221983,"corporation":false,"usgs":true,"family":"Boyles","given":"Ryan","affiliations":[{"id":565,"text":"Southeast Climate Science 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R.","contributorId":258196,"corporation":false,"usgs":false,"family":"Singhurst","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":818533,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tracey, Christopher","contributorId":260714,"corporation":false,"usgs":false,"family":"Tracey","given":"Christopher","affiliations":[{"id":52650,"text":"Pennsylvania Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":818534,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Walck, Jeffrey L. 0000-0002-8518-9900","orcid":"https://orcid.org/0000-0002-8518-9900","contributorId":258197,"corporation":false,"usgs":false,"family":"Walck","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":818535,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Weakley, Alan 0000-0003-2093-3767","orcid":"https://orcid.org/0000-0003-2093-3767","contributorId":197982,"corporation":false,"usgs":false,"family":"Weakley","given":"Alan","email":"","affiliations":[],"preferred":false,"id":818536,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70239001,"text":"70239001 - 2021 - Quantification of manganese for ChemCam Mars and laboratory spectra using a multivariate model","interactions":[],"lastModifiedDate":"2022-12-20T13:15:41.956204","indexId":"70239001","displayToPublicDate":"2021-05-31T07:14:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12986,"text":"Spectrochimica Acta B","active":true,"publicationSubtype":{"id":10}},"title":"Quantification of manganese for ChemCam Mars and laboratory spectra using a multivariate model","docAbstract":"

We report a new calibration model for manganese using the laser-induced breakdown spectroscopy instrument that is part of the ChemCam instrument suite onboard the NASA Curiosity rover. The model has been trained using an expanded set of 523 manganese-bearing rock, mineral, metal ore, and synthetic standards. The optimal calibration model uses the Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO) multivariate techniques, with a novel “double blending” technique. We determined the detection limit for manganese is 82 ppm using a method blank procedure and is possibly as low as 27 ppm based on visual inspection of the spectra. Based on a representative test set consisting of measurements on 93 standards, the double blended multivariate model shows a Root Mean Squared Error of Prediction (RMSEP) accuracy of 1.39 wt% MnO for the full blended model. Employing a local RMSEP estimate where the model performance is evaluated based on nearby test samples, the accuracy is 0.03 wt% at the quantification limit (0.05 wt% MnO), 0.4 wt% accuracy at 1.0 wt% MnO, and 4.4 wt% accuracy at 100 wt% MnO. Precision is estimated using the standard deviation of the test set measurements, and is ±0.01 wt% MnO at the quantification limit, ±0.09 wt% MnO at 1.0 wt% MnO, and ± 2.1 wt% MnO at 100 wt% MnO (all 1 standard deviation). This new calibration is important for understanding the variation of manganese in the bedrock with the Curiosity rover on Mars, which provides insight into past redox conditions on Mars.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.sab.2021.106223","usgsCitation":"Gasda, P.J., Anderson, R.B., Cousin, A., Forni, O., Clegg, S.M., Ollila, A., Lanza, N.L., Lamm, S., Wiens, R.C., Maurice, S., Gasnault, O., Beal, R., Reyes-Newell, A., and Delapp, D., 2021, Quantification of manganese for ChemCam Mars and laboratory spectra using a multivariate model: Spectrochimica Acta B, v. 181, 106223, https://doi.org/10.1016/j.sab.2021.106223.","productDescription":"106223","ipdsId":"IP-127445","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":452071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hal.science/hal-03449982","text":"Publisher Index Page"},{"id":410785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"181","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gasda, Patrick J.","contributorId":196313,"corporation":false,"usgs":false,"family":"Gasda","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":859645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Ryan B. 0000-0003-4465-2871 rbanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-4465-2871","contributorId":170054,"corporation":false,"usgs":true,"family":"Anderson","given":"Ryan","email":"rbanderson@usgs.gov","middleInitial":"B.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":859646,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cousin, A.","contributorId":290035,"corporation":false,"usgs":false,"family":"Cousin","given":"A.","affiliations":[{"id":62314,"text":"Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":859647,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forni, O.","contributorId":290037,"corporation":false,"usgs":false,"family":"Forni","given":"O.","affiliations":[{"id":62314,"text":"Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":859648,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clegg, S. 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