Recent simulation modeling has shown that species can coevolve toward clusters of coexisting consumers exploiting the same limiting resource or resources, with nearly identical ratios of coefficients related to growth and mortality. This paper provides a mathematical basis for such as situation; a full analysis of the global dynamics of a new model for such a class of n-dimensional consumer–resource system, in which a set of consumers with identical growth to mortality ratios compete for the same resource and in which each consumer is mutualistic with the resource. First, we study the system of one resource and two consumers. By theoretical analysis, we demonstrate the expected result that competitive exclusion of one of the consumers can occur when the growth to mortality ratios differ. However, when these ratios are identical, the outcomes are complex. Either equilibrium coexistence or mutual extinction can occur, depending on initial conditions. When there is coexistence, interaction outcomes between the consumers can transition between effective mutualism, parasitism, competition, amensalism and neutralism. We generalize to the global dynamics of a system of one resource and multiple consumers. Changes in one factor, either a parameter or initial density, can determine whether all of the consumers either coexist or go to extinction together. New results are presented showing that multiple competing consumers can coexist on a single resource when they have coevolved toward identical growth to mortality ratios. This coexistence can occur because of feedbacks created by all of the consumers providing a mutualistic service to the resource. This is biologically relevant to the persistence of pollination–mutualisms.
","language":"English","publisher":"Springer","doi":"10.1007/s00285-018-1288-9","usgsCitation":"Wang, Y., Wu, H., and DeAngelis, D.L., 2019, Global dynamics of a mutualism–competition model with one resource and multiple consumers: Journal of Mathematical Biology, v. 78, no. 3, p. 683-710, https://doi.org/10.1007/s00285-018-1288-9.","productDescription":"28 p.","startPage":"683","endPage":"710","ipdsId":"IP-098481","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":357285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-04","publicationStatus":"PW","scienceBaseUri":"5bc02fa0e4b0fc368eb53925","contributors":{"authors":[{"text":"Wang, Yuanshi","contributorId":207814,"corporation":false,"usgs":false,"family":"Wang","given":"Yuanshi","email":"","affiliations":[{"id":37637,"text":"School of Mathematics and Computational Science Sun Yat-sen University","active":true,"usgs":false}],"preferred":false,"id":744802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Hong","contributorId":207815,"corporation":false,"usgs":false,"family":"Wu","given":"Hong","email":"","affiliations":[{"id":37637,"text":"School of Mathematics and Computational Science Sun Yat-sen University","active":true,"usgs":false}],"preferred":false,"id":744803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":744801,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70206335,"text":"70206335 - 2019 - Larger body size and earlier run timing increase alewife reproductive success in a whole lake experiment","interactions":[],"lastModifiedDate":"2019-10-31T08:07:50","indexId":"70206335","displayToPublicDate":"2018-09-06T08:04:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Larger body size and earlier run timing increase alewife reproductive success in a whole lake experiment","docAbstract":"Environmental conditions can influence biological characteristics like phenology and body size with important consequences for organismal fitness. Examining these fitness consequences under natural conditions through genetic pedigree reconstruction offers a lens into potential population responses to changing environments. Over three years (2013-2015), we introduced adult alewife (Alosa pseudoharengus), anadromous, iteroparous clupeids, into one Massachusetts (USA) lake to complete the first detailed examination of this species’ mating system and assess relationships between body size, reproductive timing, and seasonal reproductive success. We reconstructed pedigrees using 15 microsatellites and genotypes from all possible parents and samples of naturally produced offspring within four months of hatching. Within each of the three study years, spawning adults had multiple mates and spawned multiple times. Larger females that arrived earlier had higher reproductive success. Declining body size and altered migration timing over time, through an influence on reproductive success, can influence population vital rates and productivity.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0451","usgsCitation":"Roy, A.H., Marjadi, M.N., Jordaan, A., Benjamin I. Gahagan, Armstrong, M.P., and Andrew R. Whiteley, 2019, Larger body size and earlier run timing increase alewife reproductive success in a whole lake experiment: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 7, p. 1134-1146, https://doi.org/10.1139/cjfas-2017-0451.","productDescription":"13 p.","startPage":"1134","endPage":"1146","ipdsId":"IP-088556","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468099,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2017-0451","text":"External Repository"},{"id":368792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts 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\"}}]}","volume":"76","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":774189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marjadi, Meghna N.","contributorId":220123,"corporation":false,"usgs":false,"family":"Marjadi","given":"Meghna","email":"","middleInitial":"N.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":774190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jordaan, Adrian","contributorId":220124,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","email":"","affiliations":[{"id":37062,"text":"UMASS","active":true,"usgs":false}],"preferred":false,"id":774191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benjamin I. Gahagan","contributorId":220125,"corporation":false,"usgs":false,"family":"Benjamin I. Gahagan","affiliations":[{"id":40132,"text":"Massachusetts Division of Marine Resources","active":true,"usgs":false}],"preferred":false,"id":774192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Armstrong, Michael P.","contributorId":220126,"corporation":false,"usgs":false,"family":"Armstrong","given":"Michael","email":"","middleInitial":"P.","affiliations":[{"id":40132,"text":"Massachusetts Division of Marine Resources","active":true,"usgs":false}],"preferred":false,"id":774193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andrew R. Whiteley","contributorId":220127,"corporation":false,"usgs":false,"family":"Andrew R. Whiteley","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":774194,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70206189,"text":"70206189 - 2019 - Subsidies from anadromous sea lamprey (Petromyzon marinus) carcasses function as a reciprocal nutrient exchange between marine and freshwaters","interactions":[],"lastModifiedDate":"2019-10-25T07:14:32","indexId":"70206189","displayToPublicDate":"2018-09-03T07:13:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Subsidies from anadromous sea lamprey (Petromyzon marinus) carcasses function as a reciprocal nutrient exchange between marine and freshwaters","docAbstract":"Nutrient and energy flows across ecosystem boundaries subsidize recipient communities and influence bottom‐up processes in food webs. Migratory fish such as anadromous sea lamprey provide a pulse of marine‐derived nutrients and energy to Atlantic coastal streams in spring when organisms would otherwise be subject to limiting resources. We conducted sea lamprey carcass addition experiments to characterize the role of subsidies on producer and consumer trophic pathways by manipulating subsidy quantity and light exposure. We demonstrated that producer and decomposer productivity is constrained by nutrients during spring; however, these limitations were reduced in producers as light limitations intensified through riparian shading. We observed no significant effects of increasing carcass subsidies on producer and decomposer biomass. Our results suggest that high densities of carcass subsidies may stimulate primary productivity; however, these effects are mediated by the degree of riparian shading, which demonstrated a onefold to fourfold difference in biomass accrual. In addition, sea lamprey carcass nutrients were captured by larval conspecifics. Stable isotopes analysis demonstrated that adult sea lamprey carcass tissue was relatively enriched in 15N and 13C isotopes compared with larvae. We observed significant enrichment in the 13C isotope among larvae sampled after 2 and 4 weeks of exposure to adult carcass nutrients. Our work suggests that a portion of sea lamprey subsidies serve as a reciprocal exchange between freshwaters and the ocean. We highlight that this cross‐ecosystem linkage is likely influenced by subsidy quantity from donor systems and is mediated by environmental characteristics affecting the recipient system.
In most drylands, biological soil crusts (biocrusts), an assemblage of lichens, bryophytes, fungi, green algae, and cyanobacteria, are critical to healthy ecosystem function. However, they are extremely sensitive to disturbance and attempts to facilitate their recovery have had variable success. In this study, we applied soil amendments designed to improve soil surface stability and accelerate biocrust recovery on an area disturbed by oil/gas exploration vehicles. Treatments included: 1) Control (one time water only); 2) Biocrust‐only: biocrust inoculum + nutrients in water; 3) Polyacrylamide gels (PAM; which are known to stabilize soils) + biocrust inoculum + nutrients in water; 4) Gypsum + biocrust inoculum + nutrients in water; and 5) Saline (NaCl) solution + biocrust inoculum + nutrients in water. Only the NaCl treatment showed any effects on soil properties and these were only short‐term. These effects included an increase in soil strength and a reduction in soil aggregate stability, unsaturated hydraulic conductivity (Kh), and cyanobacterial biomass. The inoculated biocrust material failed to develop and even after 10 years, there was only a very low natural recolonization of the plots. These results show that inoculating soils or applying these levels of soil amendments does not guarantee recovery of soil stability or biocrust, and that some sites are unlikely to recover without assistance. Thus, there is a need for more research into ways to enhance soil stability and identify the factors limiting biocrust establishment.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.12870","usgsCitation":"Chandler, D.G., Day, N.K., Madsen, M.D., and Belnap, J., 2019, Amendments fail to hasten biocrust recovery or soil stability at a disturbed dryland sandy site: Restoration Ecology, v. 27, no. 2, p. 289-297, https://doi.org/10.1111/rec.12870.","productDescription":"9 p.","startPage":"289","endPage":"297","ipdsId":"IP-095620","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468105,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.12870","text":"Publisher Index Page"},{"id":356814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-03","publicationStatus":"PW","scienceBaseUri":"5b98a273e4b0702d0e842ee6","contributors":{"authors":[{"text":"Chandler, David G.","contributorId":207303,"corporation":false,"usgs":false,"family":"Chandler","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":37516,"text":"Syracuse University, Civil and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":743486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Madsen, Matthew D.","contributorId":191385,"corporation":false,"usgs":false,"family":"Madsen","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":743487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743485,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204094,"text":"70204094 - 2019 - Understanding how microbiomes influence the systems they inhabit","interactions":[],"lastModifiedDate":"2020-09-01T14:01:58.098487","indexId":"70204094","displayToPublicDate":"2018-08-24T16:03:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5843,"text":"Nature Microbiology","onlineIssn":"2058-5276","active":true,"publicationSubtype":{"id":10}},"title":"Understanding how microbiomes influence the systems they inhabit","docAbstract":"Translating the ever-increasing wealth of information on microbiomes (environment, host, or built environment) to advance the understanding of system-level processes is proving to be an exceptional research challenge. One reason for this challenge is that relationships between characteristics of microbiomes and the system-level processes they influence are often evaluated in the absence of a robust conceptual framework and reported without elucidating the underlying causal mechanisms. The reliance on correlative approaches limits the potential to expand the inference of a single relationship to additional systems and advance the field. We propose that research focused on how microbiomes influence the systems they inhabit should work within a common framework and target known microbial processes that contribute to the system-level processes of interest. Here we identify three distinct categories of microbiome characteristics (microbial processes, microbial community properties, and microbial membership) and propose a framework to empirically link each of these categories to each other and the broader system level processes they affect. We posit that it is particularly important to distinguish microbial community properties that can be predicted from constituent taxa (community aggregated traits) from and those properties that are currently unable to be predicted from constituent taxa (emergent properties). Existing methods in microbial ecology can be applied to more explicitly elucidate properties within each of these categories and connect these three categories of microbial characteristics with each other. We view this proposed framework, gleaned from a breadth of research on environmental microbiomes and ecosystem processes, as a promising pathway with the potential to advance discovery and understanding across a broad range of microbiome science.","language":"English","publisher":"SpringerNature","doi":"10.1038/s41564-018-0201-z","usgsCitation":"Hall, E., Bernhardt, E.S., Bier, R., Bradford, M., Boot, C., Cotner, J., del Giorgio, P., Evans, S., Graham, E., Jones, S., Lennon, J., Locey, K.J., Nemergut, D., Osborne, B., Rocca, J., Schimel, J., Waldrop, M., and Wallenstein, M., 2019, Understanding how microbiomes influence the systems they inhabit: Nature Microbiology, v. 3, no. 9, p. 977-982, https://doi.org/10.1038/s41564-018-0201-z.","productDescription":"6 p.","startPage":"977","endPage":"982","ipdsId":"IP-068241","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":365295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Hall, E.K.","contributorId":216759,"corporation":false,"usgs":false,"family":"Hall","given":"E.K.","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":765451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernhardt, E. S.","contributorId":95682,"corporation":false,"usgs":false,"family":"Bernhardt","given":"E.","email":"","middleInitial":"S.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":765452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bier, R.L.","contributorId":173735,"corporation":false,"usgs":false,"family":"Bier","given":"R.L.","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":765453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, M.A.","contributorId":216760,"corporation":false,"usgs":false,"family":"Bradford","given":"M.A.","email":"","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":765454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boot, C.M.","contributorId":173737,"corporation":false,"usgs":false,"family":"Boot","given":"C.M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":765455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cotner, J.B.","contributorId":216761,"corporation":false,"usgs":false,"family":"Cotner","given":"J.B.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":765456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"del Giorgio, P.A.","contributorId":216762,"corporation":false,"usgs":false,"family":"del Giorgio","given":"P.A.","affiliations":[{"id":24488,"text":"Universite du Quebec a Montreal","active":true,"usgs":false}],"preferred":false,"id":765457,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Evans, S.E.","contributorId":178746,"corporation":false,"usgs":false,"family":"Evans","given":"S.E.","email":"","affiliations":[],"preferred":false,"id":765458,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Graham, E.B.;","contributorId":173738,"corporation":false,"usgs":false,"family":"Graham","given":"E.B.;","email":"","affiliations":[{"id":25479,"text":"CU Boulder","active":true,"usgs":false}],"preferred":false,"id":765459,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jones, S.E.","contributorId":216763,"corporation":false,"usgs":false,"family":"Jones","given":"S.E.","email":"","affiliations":[{"id":39511,"text":"Notre Dame University","active":true,"usgs":false}],"preferred":false,"id":765460,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lennon, J.T.","contributorId":156353,"corporation":false,"usgs":false,"family":"Lennon","given":"J.T.","email":"","affiliations":[{"id":20322,"text":"Department of Biology Indiana University, Bloomington, IN","active":true,"usgs":false}],"preferred":false,"id":765461,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Locey, Kenneth J.","contributorId":216781,"corporation":false,"usgs":false,"family":"Locey","given":"Kenneth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":765490,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Nemergut, D.","contributorId":216764,"corporation":false,"usgs":false,"family":"Nemergut","given":"D.","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":765462,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Osborne, B.","contributorId":216765,"corporation":false,"usgs":false,"family":"Osborne","given":"B.","email":"","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":765463,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rocca, J.D.","contributorId":216766,"corporation":false,"usgs":false,"family":"Rocca","given":"J.D.","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":765464,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Schimel, J.S.","contributorId":216767,"corporation":false,"usgs":false,"family":"Schimel","given":"J.S.","email":"","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":765465,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216758,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[],"preferred":true,"id":765450,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Wallenstein, M.W.","contributorId":216768,"corporation":false,"usgs":false,"family":"Wallenstein","given":"M.W.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":765466,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70203655,"text":"70203655 - 2019 - Modeling golden eagle‐vehicle collisions to design mitigation strategies","interactions":[],"lastModifiedDate":"2019-05-30T15:13:10","indexId":"70203655","displayToPublicDate":"2018-08-16T15:10:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Modeling golden eagle‐vehicle collisions to design mitigation strategies","docAbstract":"The incidental take of golden eagles (Aquila chrysaetos) as a result of wind energy development requires some form of compensatory mitigation. Although several options have been proposed, only one has been formerly accepted and implemented, and the lack of options can limit the permit process for wind facilities. We developed a model to estimate numbers of golden eagles that die when struck by vehicles when eagles scavenge road kill to evaluate removal of road‐killed carcasses as an additional mitigation option. Our model estimates vehicle collision rates as a function of eagle densities, road traffic volume, and animal carcass abundance at the scale of a Wyoming, USA, county during fall‐winter, and quantifies the effects of different mitigation strategies, including estimates of uncertainty. We evaluated the plausibility of our model estimates by predicting mortality rates for each county in Wyoming and comparing overall state mortality to current estimates of mortality using derived estimates from expert judgment. We also developed a context‐dependent analysis of potential mitigation credits controlling for carcass number, traffic volume, and background carcass removals. We found that mitigation credit should be highest in areas with greatest number of carcasses. Collision mitigation is a potentially useful addition to the mitigation toolbox for wind energy development or other activities that need to offset predicted golden eagle mortality and satisfy incidental take permit requirements.
Characterizing animal space use is critical for understanding ecological relationships. Animal telemetry technology has revolutionized the fields of ecology and conservation biology by providing high quality spatial data on animal movement. Radio-telemetry with very high frequency (VHF) radio signals continues to be a useful technology because of its low cost, miniaturization, and low battery requirements. Despite a number of statistical developments synthetically integrating animal location estimation and uncertainty with spatial process models using satellite telemetry data, we are unaware of similar developments for azimuthal telemetry data. As such, there are few statistical options to handle these unique data and no synthetic framework for modeling animal location uncertainty and accounting for it in ecological models.
We developed a hierarchical modeling framework to provide robust animal location estimates from one or more intersecting or non-intersecting azimuths. We used our azimuthal telemetry model (ATM) to account for azimuthal uncertainty with covariates and propagate location uncertainty into spatial ecological models. We evaluate the ATM with commonly used estimators (Lenth (1981) maximum likelihood and M-Estimators) using simulation. We also provide illustrative empirical examples, demonstrating the impact of ignoring location uncertainty within home range and resource selection analyses. We further use simulation to better understand the relationship among location uncertainty, spatial covariate autocorrelation, and resource selection inference.
We found the ATM to have good performance in estimating locations and the only model that has appropriate measures of coverage. Ignoring animal location uncertainty when estimating resource selection or home ranges can have pernicious effects on ecological inference. Home range estimates can be overly confident and conservative when ignoring location uncertainty and resource selection coefficients can lead to incorrect inference and over confidence in the magnitude of selection. Furthermore, our simulation study clarified that incorporating location uncertainty helps reduce bias in resource selection coefficients across all levels of covariate spatial autocorrelation.
The ATM can accommodate one or more azimuths when estimating animal locations, regardless of how they intersect; this ensures that all data collected are used for ecological inference. Our findings and model development have important implications for interpreting historical analyses using this type of data and the future design of radio-telemetry studies.
","language":"English","publisher":"Springer","doi":"10.1186/s40462-018-0129-1","collaboration":"Colorado State University","usgsCitation":"Hooten, M., Brian D. Gerber, Christopher P. Peck, Mindy B. Rice, Anthony D. Apa, Gammonley, J.H., and Amy J. Davis, 2019, Accounting for location uncertainty in azimuthaltelemetry data improves ecological inference: Movement Ecology, v. 6, 14, https://doi.org/10.1186/s40462-018-0129-1.","productDescription":"14","ipdsId":"IP-086823","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468116,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-018-0129-1","text":"Publisher Index Page"},{"id":368535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":773684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brian D. Gerber","contributorId":219968,"corporation":false,"usgs":false,"family":"Brian D. Gerber","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":773685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christopher P. Peck","contributorId":219969,"corporation":false,"usgs":false,"family":"Christopher P. Peck","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":773686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mindy B. Rice","contributorId":219970,"corporation":false,"usgs":false,"family":"Mindy B. Rice","affiliations":[{"id":40103,"text":"cdpw","active":true,"usgs":false}],"preferred":false,"id":773687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anthony D. Apa","contributorId":219971,"corporation":false,"usgs":false,"family":"Anthony D. Apa","affiliations":[{"id":40103,"text":"cdpw","active":true,"usgs":false}],"preferred":false,"id":773688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gammonley, James H.","contributorId":219972,"corporation":false,"usgs":false,"family":"Gammonley","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":40103,"text":"cdpw","active":true,"usgs":false}],"preferred":false,"id":773689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amy J. Davis","contributorId":219973,"corporation":false,"usgs":false,"family":"Amy J. Davis","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":773690,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203659,"text":"70203659 - 2019 - Optimal treatment allocations in space and time for online control of anemerging infectious disease","interactions":[],"lastModifiedDate":"2019-05-30T15:07:49","indexId":"70203659","displayToPublicDate":"2018-07-18T15:02:16","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2568,"text":"Journal of the Royal Statistical Society. Series C: Applied Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Optimal treatment allocations in space and time for online control of anemerging infectious disease","docAbstract":"A key component in controlling the spread of an epidemic is deciding where, when and to whom to apply an intervention. We develop a framework for using data to inform these decisions in realtime. We formalize a treatment allocation strategy as a sequence of functions, one per treatment period, that map up‐to‐date information on the spread of an infectious disease to a subset of locations where treatment should be allocated. An optimal allocation strategy optimizes some cumulative outcome, e.g. the number of uninfected locations, the geographic footprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategy for an emerging infectious disease is challenging because spatial proximity induces interference between locations, the number of possible allocations is exponential in the number of locations, and because disease dynamics and intervention effectiveness are unknown at outbreak. We derive a Bayesian on‐line estimator of the optimal allocation strategy that combines simulation–optimization with Thompson sampling. The estimator proposed performs favourably in simulation experiments. This work is motivated by and illustrated using data on the spread of white nose syndrome, which is a highly fatal infectious disease devastating bat populations in North America.
Identifying spawning and hatching locations is vital to controlling invasive fish and conserving imperiled fish, which can be difficult for pelagically-spawning species with semi-buoyant eggs. In freshwater systems, this reproductive strategy is common among cyprinid species, such as Chinese carp species currently threatening the Great Lakes. Following the confirmation that one of these species, Grass Carp (Ctenopharyngodon idella), was spawning in a Great Lakes tributary, we developed a modeling framework to combine field data with hydraulic models to calculate the most probable spawning and hatching locations for collected eggs. Our results indicate that the estimated spawning location encompassed habitat consistent with spawning sites in Grass Carp’s native range. Additionally, all eggs were identified to have hatched in the river, increasing the likelihood of successful recruitment. This modeling framework can be used to estimate spawning and hatching locations for Chinese carp species, as well as all pelagic, riverine spawners. Spawning and hatching locations provide key information to researchers about the reproductive requirements of species and to agencies about how best to manage populations for control or restoration.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0047","usgsCitation":"Embke, H.S., Kocovsky, P., Garcia, T., Mayer, C.M., and Qian, S.S., 2019, Modeling framework to estimate spawning and hatching locations of pelagically-spawned eggs: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 4, p. 597-607, https://doi.org/10.1139/cjfas-2018-0047.","productDescription":"11 p.","startPage":"597","endPage":"607","ipdsId":"IP-087557","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":501079,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/92211","text":"External Repository"},{"id":355500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e544e4b060350a15d077","contributors":{"authors":[{"text":"Embke, Holly S. 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":173026,"corporation":false,"usgs":true,"family":"Embke","given":"Holly","email":"","middleInitial":"S.","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":false,"id":739500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":739499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garcia, Tatiana 0000-0002-1979-7246 tgarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-1979-7246","contributorId":140327,"corporation":false,"usgs":true,"family":"Garcia","given":"Tatiana","email":"tgarcia@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayer, Christine M.","contributorId":50814,"corporation":false,"usgs":true,"family":"Mayer","given":"Christine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":739502,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Qian, Song S.","contributorId":198934,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":739503,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197975,"text":"70197975 - 2019 - Diets of endangered silver chub (Macrhybopsis storeriana, Kirtland, 1844) in Lake Erie and implications for recovery","interactions":[],"lastModifiedDate":"2019-01-28T09:31:23","indexId":"70197975","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Diets of endangered silver chub (Macrhybopsis storeriana, Kirtland, 1844) in Lake Erie and implications for recovery","title":"Diets of endangered silver chub (Macrhybopsis storeriana, Kirtland, 1844) in Lake Erie and implications for recovery","docAbstract":"Silver chub (Macrhybopsis storeriana, Kirtland, 1844) is a native Cyprinid in Lake Erie, one of the Laurentian Great Lakes of North America. It is listed as endangered by the US state of New York and Canada, which has a recovery plan, and as special concern by the state of Michigan. Silver chub faces a potential threat to recovery from control efforts for invasive Grass carp (Ctenopharyngodon idella, Valenciennes 1844). Among the knowledge gaps for protection and restoration is current diet data. I describe the diet of silver chub from western Lake Erie in 2014, and I compare it to past studies to assess changes in diet through time. Silver chub captured in bottom trawls May–September 2014 were frozen in the field, and stomach contents were preserved in ethanol. Diet taxa were identified to the lowest practical taxonomic unit, then dried and weighed. Frequency of occurrence in silver chub diets was highest for Hexagenia spp. mayflies (79%). Dreissena spp. and Hexagenia spp. were both 41% of the diet by dry weight. Analysis of δ13C isotopes identified Hexagenia spp. as the primary source of carbon in silver chub. Compared to past studies, Dreissena spp. have mostly replaced Sphaeriidae and Gastropoda in silver chub diets. There also have been seasonal shifts in relative amounts of shelled organisms and Hexagenia spp. This study and past research suggest a functional link between silver chub and Hexagenia spp. abundance. Maintenance and recovery of silver chub may be dependent on maintaining Hexagenia spp. populations.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12424","usgsCitation":"Kocovsky, P., 2019, Diets of endangered silver chub (Macrhybopsis storeriana, Kirtland, 1844) in Lake Erie and implications for recovery: Ecology of Freshwater Fish, v. 28, no. 1, p. 33-40, https://doi.org/10.1111/eff.12424.","productDescription":"8 p.","startPage":"33","endPage":"40","ipdsId":"IP-096199","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":460599,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12424","text":"Publisher Index Page"},{"id":355441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.66638183593749,\n 41.35825713137813\n ],\n [\n -81.97174072265625,\n 41.35825713137813\n ],\n [\n -81.97174072265625,\n 42.20817645934742\n ],\n [\n -83.66638183593749,\n 42.20817645934742\n ],\n [\n -83.66638183593749,\n 41.35825713137813\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e546e4b060350a15d08b","contributors":{"authors":[{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":739415,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203751,"text":"70203751 - 2019 - Scale dependence of diversity in alpine tundra, Rocky Mountains, USA","interactions":[],"lastModifiedDate":"2019-06-07T15:57:50","indexId":"70203751","displayToPublicDate":"2018-06-23T15:49:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3086,"text":"Plant Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Scale dependence of diversity in alpine tundra, Rocky Mountains, USA","docAbstract":"Drivers of alpine plant community composition have been observed to vary with scale. Diversity of alpine tundra across four regions of the Rocky Mountains and among plots within one region was examined relative to temperature and precipitation variables. For regional scale analyses, averages of three metrics of plot-level species diversity relative to environmental variables and regional gamma diversity were examined for a subset of 60 plots from a stratified random sample in each region. For local scale analyses, additional soil and climate variables were included at 96 plots from one of the four regions. Correlations and visual examination of bivariate plots elucidated possible controls of cold temperatures and gamma diversity on average diversity metrics among the four regions and of precipitation and/or location on plot-level metrics within the single region. For the latter, the bivariate graph indicated a triangular distribution in which all levels of diversity exist at low precipitation but only low diversity at higher precipitation. We propose that change in drivers with scale is a general result of the relative importance of temperature and water in seed production (temperature > water) and seedling establishment (vice versa) and the logical priority of seed production over seedling establishment.","language":"English","publisher":"Springer","doi":"10.1007/s11258-018-0852-0","usgsCitation":"Malanson, G.P., Fagre, D.B., and Zimmerman, D.L., 2019, Scale dependence of diversity in alpine tundra, Rocky Mountains, USA: Plant Ecology, v. 219, no. 8, p. 999-1008, https://doi.org/10.1007/s11258-018-0852-0.","productDescription":"10 p.","startPage":"999","endPage":"1008","ipdsId":"IP-092228","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":364529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Montana, New Mexico, Wyoming","otherGeospatial":"Beartooth Range, Indian Peaks Area, Rocky Mountains, ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.16894531249999,\n 48.80686346108517\n ],\n [\n -107.22656249999999,\n 36.4566360115962\n ],\n [\n -104.94140625,\n 35.53222622770337\n ],\n [\n -105.29296874999999,\n 39.095962936305476\n ],\n [\n -107.138671875,\n 44.213709909702054\n ],\n [\n -114.9169921875,\n 48.83579746243093\n ],\n [\n -118.16894531249999,\n 48.80686346108517\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"219","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Malanson, George P.","contributorId":189162,"corporation":false,"usgs":false,"family":"Malanson","given":"George","email":"","middleInitial":"P.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":763955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":763954,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zimmerman, Dale L.","contributorId":166811,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Dale","email":"","middleInitial":"L.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":763956,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197363,"text":"70197363 - 2019 - Post-fire redistribution of soil carbon and nitrogen at a grassland-shrubland ecotone","interactions":[],"lastModifiedDate":"2019-02-21T14:59:36","indexId":"70197363","displayToPublicDate":"2018-05-31T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire redistribution of soil carbon and nitrogen at a grassland-shrubland ecotone","docAbstract":"The rapid conversion of grasslands into shrublands has been observed in many arid and semiarid regions worldwide. Studies have shown that fire can provide certain forms of reversibility for shrub-grass transition due to resource homogenization and shrub mortality, especially in the early stages of shrub encroachment. Field-level post-fire soil resource redistribution has rarely been tested. Here we used prescribed fire in a shrubland-grassland transition zone in the northern Chihuahuan Desert to test the hypothesis that fire facilitates the remobilization of nutrient-enriched soil from shrub microsites to grass and bare microsites and thereby reduces the spatial heterogeneity of soil resources. Results show that the shrub microsites had the lowest water content compared to grass and bare microsites after fire, even when rain events occurred. Significant differences of total soil carbon (TC) and total soil nitrogen (TN) among the three microsites disappeared one year after the fire. The spatial autocorrelation distance increased from 1~2 m, approximately the mean size of an individual shrub canopy, to over 5 m one year after the fire for TC and TN. Patches of high soil C and N decomposed one year after the prescribed fire. Overall, fire stimulates the transfer of soil C and N from shrub microsites to nutrient-depleted grass and bare microsites. Such a redistribution of soil C and N, coupled with the reduced soil water content under the shrub canopies, suggests that fire might influence the competition between shrubs and grasses, leading to a higher grass, compared to shrub, coverage in this ecotone.","language":"English","publisher":"Springer","doi":"10.1007/s10021-018-0260-2","usgsCitation":"Wang, G., Li, J., Ravi, S., Dukes, D., Gonzales, H.B., and Sankey, J.B., 2019, Post-fire redistribution of soil carbon and nitrogen at a grassland-shrubland ecotone: Ecosystems, v. 22, no. 1, p. 174-188, https://doi.org/10.1007/s10021-018-0260-2.","productDescription":"15 p.","startPage":"174","endPage":"188","ipdsId":"IP-091417","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":354651,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, Chihuahua, New Mexico, 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Geosciences, University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":736872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ravi, Sujith","contributorId":202738,"corporation":false,"usgs":false,"family":"Ravi","given":"Sujith","email":"","affiliations":[{"id":36520,"text":"Department of Earth and Environmental Science, Temple University","active":true,"usgs":false}],"preferred":false,"id":736873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dukes, David","contributorId":202736,"corporation":false,"usgs":false,"family":"Dukes","given":"David","email":"","affiliations":[{"id":36520,"text":"Department of Earth and Environmental Science, Temple University","active":true,"usgs":false}],"preferred":false,"id":736874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gonzales, Howell B.","contributorId":202737,"corporation":false,"usgs":false,"family":"Gonzales","given":"Howell","email":"","middleInitial":"B.","affiliations":[{"id":36520,"text":"Department of Earth and Environmental Science, Temple University","active":true,"usgs":false}],"preferred":false,"id":736875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":736870,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197333,"text":"70197333 - 2019 - Gas and ash emissions associated with the 2010–present activity of Sinabung Volcano, Indonesia","interactions":[],"lastModifiedDate":"2019-12-21T09:06:03","indexId":"70197333","displayToPublicDate":"2018-05-30T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Gas and ash emissions associated with the 2010–present activity of Sinabung Volcano, Indonesia","docAbstract":"Sinabung Volcano (Sumatra, Indonesia) awoke from over 1200 years of dormancy with multiple phreatic explosions in 2010. After a period of quiescence, Sinabung activity resumed in 2013, producing frequent explosions, lava dome extrusion, and pyroclastic flows from dome collapses, becoming one of the world's most active volcanoes and displacing over 20,000 citizens. This study presents a compilation of the geochemical datasets collected by the Indonesian Center for Volcanology and Geological Hazard Mitigation (CVGHM) from 2010 - current (2016), which provides insights into the evolution of the eruption. Based on observations of SO2 emissions, ash componentry, leachate chemistry, and bulk ash geochemistry, the eruption can be split into five distinct phases. The initial stage of phreatic summit explosions occurred from August - October 2010, during which background SO2 emissions averaged ~550 ± 180 t/d (1 s.d.). An eruptive pause (phase two) starting in October 2010 abruptly ended in September 2013 with a resumption of conduit-clearing eruptions. This third phase had a relatively modest background SO2 emission rate (avg. ~410 ± 275 t/d) and produced ash consisting entirely of accidental ejecta with high S/Cl leachate ratios (up to 30), suggestive of deep-sourced magma and the incorporation of hydrothermal sulfur-bearing phases. The most intense phase of the eruption (phase four) occurred from December 2013 to February 2014, when juvenile magma first reached the surface. This period included dozens of large eruptions per day, high SO2 emission rates (average: 1,120 ± 1,030 t/d, peak: ~3,800 t/d), the onset of lava dome extrusion, and a dramatic drop in S/Cl ash leachates to ratios < 5, all reflecting increased degassing from shallow magma and the clearing out of sulfurous phases from the old hydrothermal system. From late February 2014 through the time of writing (September 2016), Sinabung settled into a relatively steady state of lower activity (phase five). Ash emissions now consist of dominantly juvenile material, and background SO2 emission rates have been progressively decreasing to an average of ~250 - 300 t/d. Starting August 2016, SO2 emissions started being measured in a continuous manner using a network of permanent scanning DOAS instruments. We find that long-term SO2 emission rates have been gradually declining at Sinabung since early 2014, consistent with an apparent decrease in magma supply. Our degassing model suggests that large explosions and pyroclastic flows could continue in the near-term owing to conduit plugging and dome collapses, remaining a major threat until the magma supply rate decreases further and the eruption ends.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.11.018","usgsCitation":"Primulyana, S., Kern, C., Lerner, A., Saing, U., Kunrat, S., Alfianti, H., and Marlia, M., 2019, Gas and ash emissions associated with the 2010–present activity of Sinabung Volcano, Indonesia: Journal of Volcanology and Geothermal Research, v. 382, p. 184-196, https://doi.org/10.1016/j.jvolgeores.2017.11.018.","productDescription":"13 p.","startPage":"184","endPage":"196","ipdsId":"IP-080511","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468125,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2017.11.018","text":"Publisher Index Page"},{"id":354587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","state":"Sumatra","otherGeospatial":"Mount Sinabung","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 94.04296874999999,\n 6.140554782450308\n ],\n [\n 97.03125,\n -1.0546279422758742\n ],\n [\n 101.7333984375,\n -1.0546279422758742\n ],\n [\n 101.0302734375,\n 4.565473550710278\n ],\n [\n 97.03125,\n 7.885147283424331\n ],\n [\n 94.04296874999999,\n 6.140554782450308\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"382","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155df3e4b092d9651e1b92","contributors":{"authors":[{"text":"Primulyana, Sofyan","contributorId":194978,"corporation":false,"usgs":false,"family":"Primulyana","given":"Sofyan","email":"","affiliations":[],"preferred":false,"id":736704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":736703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lerner, Allan","contributorId":205264,"corporation":false,"usgs":false,"family":"Lerner","given":"Allan","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":736705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saing, Ugan","contributorId":205265,"corporation":false,"usgs":false,"family":"Saing","given":"Ugan","email":"","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":736706,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kunrat, Syegi","contributorId":205266,"corporation":false,"usgs":false,"family":"Kunrat","given":"Syegi","email":"","affiliations":[{"id":37069,"text":"CVGHM, Portland State University","active":true,"usgs":false}],"preferred":false,"id":736707,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alfianti, Hilma","contributorId":205267,"corporation":false,"usgs":false,"family":"Alfianti","given":"Hilma","email":"","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":736708,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marlia, Mitha","contributorId":205268,"corporation":false,"usgs":false,"family":"Marlia","given":"Mitha","email":"","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":736709,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196639,"text":"70196639 - 2019 - Joint 3-D tomographic imaging of Vp, Vs and Vp/Vs and hypocenter relocation at Sinabung volcano, Indonesia from November to December 2013","interactions":[],"lastModifiedDate":"2019-10-09T08:27:37","indexId":"70196639","displayToPublicDate":"2018-04-23T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Joint 3-D tomographic imaging of Vp, Vs and Vp/Vs and hypocenter relocation at Sinabung volcano, Indonesia from November to December 2013","docAbstract":"We conducted travel time tomography using P- and S-wave arrival times of volcanic-tectonic (VT) events that occurred between November and December 2013 to determine the three-dimensional (3D) seismic velocity structure (Vp, Vs, and Vp/Vs) beneath Sinabung volcano, Indonesia in order to delineate geological subsurface structure and to enhance our understanding of the volcanism itself. This was a time period when phreatic explosions became phreatomagmatic and then magma migrated to the surface forming a summit lava dome. We used 4846 VT events with 16,138 P- and 16,138 S-wave arrival time phases recorded by 6 stations for the tomographic inversion. The relocated VTs collapse into three clusters at depths from the surface to sea level, from 2 to 4 km below sea level, and from 5 to 8.5 km below sea level. The tomographic inversion results show three prominent regions of high Vp/Vs (~ 1.8) beneath Sinabung volcano at depths consistent with the relocated earthquake clusters. We interpret these anomalies as intrusives associated with previous eruptions and possibly surrounding the magma conduit, which we cannot resolve with this study. One anomalous region might contain partial melt, at sea level and below the eventual eruption site at the summit. Our results are important for the interpretation of a conceptual model of the “plumbing system” of this hazardous volcano.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.09.018","usgsCitation":"Nugraha, A.D., Indrastuti, N., Kusnandar, R., Gunawan, H., McCausland, W.A., Aulia, A.N., and Harlianti, U., 2019, Joint 3-D tomographic imaging of Vp, Vs and Vp/Vs and hypocenter relocation at Sinabung volcano, Indonesia from November to December 2013: Journal of Volcanology and Geothermal Research, v. 382, p. 210-223, https://doi.org/10.1016/j.jvolgeores.2017.09.018.","productDescription":"14 p.","startPage":"210","endPage":"223","ipdsId":"IP-084224","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468129,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2017.09.018","text":"Publisher Index Page"},{"id":353660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Sinabung Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 98.3167,\n 3.1\n ],\n [\n 98.5,\n 3.1\n ],\n [\n 98.5,\n 3.3\n ],\n [\n 98.3167,\n 3.3\n ],\n [\n 98.3167,\n 3.1\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"382","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d3e4b0da30c1bfbe70","contributors":{"authors":[{"text":"Nugraha, Andri Dian","contributorId":202043,"corporation":false,"usgs":false,"family":"Nugraha","given":"Andri","email":"","middleInitial":"Dian","affiliations":[{"id":36333,"text":"Institut Teknologi Bandung","active":true,"usgs":false}],"preferred":false,"id":733856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Indrastuti, Novianti","contributorId":204389,"corporation":false,"usgs":false,"family":"Indrastuti","given":"Novianti","email":"","affiliations":[{"id":36928,"text":"Center for Volcanology and Geological Hazard Mitigation, Bandung, Indonesia","active":true,"usgs":false}],"preferred":false,"id":733857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kusnandar, Ridwan","contributorId":204390,"corporation":false,"usgs":false,"family":"Kusnandar","given":"Ridwan","email":"","affiliations":[{"id":36929,"text":"Meteorological, Climatological, and Geophysical Agency, Denpasar, Indonesia","active":true,"usgs":false}],"preferred":false,"id":733858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunawan, Hendra","contributorId":194977,"corporation":false,"usgs":false,"family":"Gunawan","given":"Hendra","email":"","affiliations":[],"preferred":false,"id":733859,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCausland, Wendy A. 0000-0002-8683-1440","orcid":"https://orcid.org/0000-0002-8683-1440","contributorId":204380,"corporation":false,"usgs":true,"family":"McCausland","given":"Wendy","email":"","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":733855,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aulia, Atin Nur","contributorId":204391,"corporation":false,"usgs":false,"family":"Aulia","given":"Atin","email":"","middleInitial":"Nur","affiliations":[{"id":36930,"text":"Geophysical Engineering, Faculty of Mining and Petroleum Engineering, Institute of Technology Bandung, Indonesia","active":true,"usgs":false}],"preferred":false,"id":733860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harlianti, Ulvienin","contributorId":204392,"corporation":false,"usgs":false,"family":"Harlianti","given":"Ulvienin","email":"","affiliations":[{"id":36930,"text":"Geophysical Engineering, Faculty of Mining and Petroleum Engineering, Institute of Technology Bandung, Indonesia","active":true,"usgs":false}],"preferred":false,"id":733861,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205038,"text":"70205038 - 2019 - Exploring the historical earthquakes preceding the giant 1960 Chile earthquake in a time‐dependent seismogenic zone","interactions":[],"lastModifiedDate":"2019-08-29T09:25:04","indexId":"70205038","displayToPublicDate":"2017-11-07T09:23:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Exploring the historical earthquakes preceding the giant 1960 Chile earthquake in a time‐dependent seismogenic zone","docAbstract":"New documentary findings and available paleoseismological evidence provide both new insights into the historical seismic sequence that ended with the giant 1960 south-central Chile earthquake and relevant information about the region’s seismogenic zone. According to the few available written records, this region was previously struck by earthquakes of varying size in 1575, 1737, and 1837. We expanded the existing compilations of the effects of the two latter using unpublished first-hand accounts found in archives in Chile, Peru, Spain, and New England. We further investigated their sources by comparing the newly unearthed historical data and available paleoseismological evidence with the effects predicted by hypothetical dislocations. The results reveal significant differences in the along-strike and depth distribution of the ruptures in 1737, 1837, and 1960. While the 1737 rupture likely occurred in the northern half of the 1960 region, on a narrow and deep portion of the megathrust, the 1837 rupture occurred mainly in the southern half and slipped over a wide range of depth. Such a wide rupture in 1837 disagrees with the narrow and shallow seismogenic zone currently inferred along this region. If in fact there is now a narrow zone where 200 years ago there was a wider one, it means that the seismogenic zone changes with time, perhaps between seismic cycles. Such change probably explains the evident variability in both size and location of the great earthquakes that have struck this region over the last centuries, as evidenced by written history, and through millennia, as inferred from paleoseismology.","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0120170103","usgsCitation":"Cisternas, M., Carvajal, M., Wesson, R.L., Ely, L., and Gorigoitia, N., 2019, Exploring the historical earthquakes preceding the giant 1960 Chile earthquake in a time‐dependent seismogenic zone: Bulletin of the Seismological Society of America, v. 107, no. 6, p. 2664-2675, https://doi.org/10.1785/0120170103.","productDescription":"12 p.","startPage":"2664","endPage":"2675","ipdsId":"IP-091754","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":367058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-68.63401,-52.63637],[-68.63335,-54.8695],[-67.56244,-54.87001],[-66.95992,-54.89681],[-67.29103,-55.30124],[-68.14863,-55.61183],[-68.63999,-55.58002],[-69.2321,-55.49906],[-69.95809,-55.19843],[-71.00568,-55.05383],[-72.2639,-54.49514],[-73.2852,-53.95752],[-74.66253,-52.83749],[-73.8381,-53.04743],[-72.43418,-53.7154],[-71.10773,-54.07433],[-70.59178,-53.61583],[-70.26748,-52.93123],[-69.34565,-52.5183],[-68.63401,-52.63637]]],[[[-68.21991,-21.49435],[-67.82818,-22.87292],[-67.10667,-22.73592],[-66.98523,-22.98635],[-67.32844,-24.0253],[-68.41765,-24.51855],[-68.386,-26.18502],[-68.5948,-26.50691],[-68.29554,-26.89934],[-69.00123,-27.52121],[-69.65613,-28.45914],[-70.01355,-29.36792],[-69.91901,-30.33634],[-70.53507,-31.36501],[-70.0744,-33.09121],[-69.81478,-33.27389],[-69.81731,-34.19357],[-70.38805,-35.16969],[-70.36477,-36.00509],[-71.12188,-36.65812],[-71.11863,-37.57683],[-70.81466,-38.553],[-71.41352,-38.91602],[-71.68076,-39.80816],[-71.91573,-40.83234],[-71.7468,-42.05139],[-72.1489,-42.25489],[-71.91542,-43.40856],[-71.46406,-43.78761],[-71.79362,-44.20717],[-71.3298,-44.40752],[-71.22278,-44.78424],[-71.65932,-44.97369],[-71.55201,-45.56073],[-71.91726,-46.88484],[-72.44736,-47.73853],[-72.33116,-48.24424],[-72.64825,-48.87862],[-73.41544,-49.31844],[-73.32805,-50.37879],[-72.97575,-50.74145],[-72.30997,-50.67701],[-72.3294,-51.42596],[-71.9148,-52.00902],[-69.49836,-52.14276],[-68.57155,-52.29944],[-69.46128,-52.29195],[-69.94278,-52.53793],[-70.8451,-52.8992],[-71.00633,-53.83325],[-71.42979,-53.85645],[-72.55794,-53.53141],[-73.70276,-52.83507],[-74.94676,-52.26275],[-75.26003,-51.62935],[-74.97663,-51.0434],[-75.47975,-50.37837],[-75.60802,-48.67377],[-75.18277,-47.71192],[-74.12658,-46.93925],[-75.6444,-46.64764],[-74.69215,-45.76398],[-74.35171,-44.10304],[-73.24036,-44.45496],[-72.7178,-42.38336],[-73.3889,-42.11753],[-73.70134,-43.36578],[-74.33194,-43.22496],[-74.01796,-41.79481],[-73.6771,-39.94221],[-73.21759,-39.25869],[-73.50556,-38.28288],[-73.58806,-37.15628],[-73.16672,-37.12378],[-72.55314,-35.50884],[-71.86173,-33.90909],[-71.43845,-32.4189],[-71.66872,-30.92064],[-71.37008,-30.09568],[-71.48989,-28.86144],[-70.90512,-27.64038],[-70.72495,-25.70592],[-70.40397,-23.629],[-70.09125,-21.39332],[-70.16442,-19.75647],[-70.37257,-18.34798],[-69.85844,-18.09269],[-69.59042,-17.58001],[-69.10025,-18.26013],[-68.96682,-18.98168],[-68.44223,-19.40507],[-68.75717,-20.37266],[-68.21991,-21.49435]]]]},\"properties\":{\"name\":\"Chile\"}}]}","volume":"107","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Cisternas, M.","contributorId":193403,"corporation":false,"usgs":false,"family":"Cisternas","given":"M.","email":"","affiliations":[],"preferred":false,"id":769714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carvajal, M.","contributorId":197359,"corporation":false,"usgs":false,"family":"Carvajal","given":"M.","email":"","affiliations":[],"preferred":false,"id":769715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wesson, Robert L. 0000-0003-2702-0012 rwesson@usgs.gov","orcid":"https://orcid.org/0000-0003-2702-0012","contributorId":850,"corporation":false,"usgs":true,"family":"Wesson","given":"Robert","email":"rwesson@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":769716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ely, L.L","contributorId":218627,"corporation":false,"usgs":false,"family":"Ely","given":"L.L","affiliations":[{"id":26935,"text":"Central Washington University","active":true,"usgs":false}],"preferred":false,"id":769717,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gorigoitia, N","contributorId":218628,"corporation":false,"usgs":false,"family":"Gorigoitia","given":"N","email":"","affiliations":[{"id":34895,"text":"Pontificia Universidad Catolica de Valparaiso","active":true,"usgs":false}],"preferred":false,"id":769718,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202783,"text":"70202783 - 2019 - MODIS phenology-derived, multi-year distribution of conterminous U.S. crop types","interactions":[],"lastModifiedDate":"2019-03-26T11:03:41","indexId":"70202783","displayToPublicDate":"2017-09-01T11:02:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"MODIS phenology-derived, multi-year distribution of conterminous U.S. crop types","docAbstract":"Innovative, open, and rapid methods to map crop types over large areas are needed for long-term cropland monitoring. We developed two novel and automated decision tree classification approaches to map crop types across the conterminous United States (U.S.) using MODIS 250 m resolution data: 1) generalized, and 2) year-specific classification. The classification approaches use similarities and dissimilarities in crop type phenologyderived from NDVI time-series data for the two approaches. The year-specific approach uses the training samples from one year and classifies crop types for that year only, whereas the generalized classification approach uses above-average, average, and below-average precipitation years for training to produce crop type maps for one or multiple years more robustly. We produced annual crop type maps using the generalized classification approach for 2001–2014 and the year-specific approach for 2008, 2010, 2011 and 2012. The year-specific classification had overall accuracies > 78%, while the generalized classifier had accuracies > 75% for the conterminous U.S. for 2008, 2010, 2011, and 2012. The generalized classifier enables automated and routine crop type mapping without repeated and expensive ground sample collection year after year. The resulting crop type maps for years prior to 2007 are new and especially important for long-term cropland monitoring and food security analysis because no other map products are currently available for 2001–2007.
We evaluated the impact of predation on juvenile steelhead Oncorhynchus mykiss and yearling and subyearling Chinook Salmon O. tshawytscha by piscivorous waterbirds from 11 different breeding colonies in the Columbia River basin during 2012 and 2014. Fish were tagged with both acoustic tags and PIT tags and were tracked via a network of hydrophone arrays to estimate total smolt mortality (1 – survival) at various spatial and temporal scales during out‐migration. Recoveries of PIT tags on bird colonies, coupled with the last known detections of live fish passing hydrophone arrays, were used to estimate the impact of avian predation relative to total smolt mortality. Results indicated that avian predation was a substantial source of steelhead mortality, with predation probability (proportion of available fish consumed by birds) ranging from 0.06 to 0.28 for fish traveling through the lower Snake River and the lower and middle Columbia River. Predation probability estimates ranged from 0.03 to 0.09 for available tagged yearling Chinook Salmon and from 0.01 to 0.05 for subyearlings. Smolt predation by gulls Larusspp. was concentrated near hydroelectric dams, while predation by Caspian terns Hydroprogne caspia was concentrated within reservoirs. No concentrated areas of predation were identified for double‐crested cormorants Phalacrocorax auritus or American white pelicans Pelecanus erythrorhynchos. Comparisons of total smolt mortality relative to mortality from colonial waterbirds indicated that avian predation was one of the greatest sources of mortality for steelhead and yearling Chinook Salmon during out‐migration. In contrast, avian predation on subyearling Chinook Salmon was generally low and constituted a minor component of total mortality. Our results demonstrate that acoustic and PIT tag technologies can be combined to quantify where and when smolt mortality occurs and the fraction of mortality that is due to colonial waterbird predation relative to non‐avian mortality sources.
","language":"English","publisher":"Wiley","doi":"10.1080/00028487.2016.1150881","usgsCitation":"Evans, A.F., Payton, Q., Turecek, A., Cramer, B., Collis, K., Roby, D.D., Loschl, P.J., Sullivan, L., Skalski, Weiland, M., and Dotson, C., 2019, Avian predation on juvenile Salmonids: Spatial and temporal analysis based on acoustic and passive integrated transponder tags: Transactions of the American Fisheries Society, https://doi.org/10.1080/00028487.2016.1150881.","ipdsId":"IP-071908","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490058,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/dataset/Avian_Predation_on_Juvenile_Salmonids_Spatial_and_Temporal_Analysis_Based_on_Acoustic_and_Passive_Integrated_Transponder_Tags/3471605","text":"External Repository"},{"id":364261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Allen F.","contributorId":171691,"corporation":false,"usgs":false,"family":"Evans","given":"Allen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":763477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Payton, Quinn","contributorId":149990,"corporation":false,"usgs":false,"family":"Payton","given":"Quinn","email":"","affiliations":[{"id":17879,"text":"Real Time Research, Inc., 231 SW Scalehouse Loop, Suite 101, Bend, OR 97702","active":true,"usgs":false}],"preferred":false,"id":763478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turecek, Aaron aturecek@usgs.gov","contributorId":4940,"corporation":false,"usgs":true,"family":"Turecek","given":"Aaron","email":"aturecek@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":763479,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cramer, Bradley D.","contributorId":51562,"corporation":false,"usgs":true,"family":"Cramer","given":"Bradley D.","affiliations":[],"preferred":false,"id":763480,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collis, Ken","contributorId":149991,"corporation":false,"usgs":false,"family":"Collis","given":"Ken","email":"","affiliations":[{"id":17879,"text":"Real Time Research, Inc., 231 SW Scalehouse Loop, Suite 101, Bend, OR 97702","active":true,"usgs":false}],"preferred":false,"id":763481,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roby, Daniel D. 0000-0001-9844-0992 droby@usgs.gov","orcid":"https://orcid.org/0000-0001-9844-0992","contributorId":3702,"corporation":false,"usgs":true,"family":"Roby","given":"Daniel","email":"droby@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":763482,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Loschl, Peter J.","contributorId":7195,"corporation":false,"usgs":true,"family":"Loschl","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":763483,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sullivan, Leah","contributorId":215942,"corporation":false,"usgs":false,"family":"Sullivan","given":"Leah","email":"","affiliations":[],"preferred":false,"id":763484,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Skalski, John","contributorId":120021,"corporation":false,"usgs":true,"family":"Skalski","suffix":"John","affiliations":[],"preferred":false,"id":763485,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Weiland, Mark","contributorId":215944,"corporation":false,"usgs":false,"family":"Weiland","given":"Mark","email":"","affiliations":[],"preferred":false,"id":763486,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dotson, Curtis","contributorId":215945,"corporation":false,"usgs":false,"family":"Dotson","given":"Curtis","email":"","affiliations":[],"preferred":false,"id":763487,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70203619,"text":"70203619 - 2019 - Metrics for assessing the quality of groundwater used for public supply, CA, USA: Equivalent-population and area","interactions":[],"lastModifiedDate":"2019-05-28T08:46:55","indexId":"70203619","displayToPublicDate":"2015-06-26T08:46:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Metrics for assessing the quality of groundwater used for public supply, CA, USA: Equivalent-population and area","docAbstract":"Data from 11 000 public supply wells in 87 study areas were used to assess the quality of nearly all of the groundwater used for public supply in California. Two metrics were developed for quantifying groundwater quality: area with high concentrations (km2 or proportion) and equivalent-population relying upon groundwater with high concentrations (number of people or proportion). Concentrations are considered high if they are above a human-health benchmark. When expressed as proportions, the metrics are area-weighted and population-weighted detection frequencies. On a statewide-scale, about 20% of the groundwater used for public supply has high concentrations for one or more constituents (23% by area and 18% by equivalent-population). On the basis of both area and equivalent-population, trace elements are more prevalent at high concentrations than either nitrate or organic compounds at the statewide-scale, in eight of nine hydrogeologic provinces, and in about three-quarters of the study areas. At a statewide-scale, nitrate is more prevalent than organic compounds based on area, but not on the basis of equivalent-population. The approach developed for this paper, unlike many studies, recognizes the importance of appropriately weighting information when changing scales, and is broadly applicable to other areas.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.5b00265","usgsCitation":"Belitz, K., Fram, M.S., and Johnson, T., 2019, Metrics for assessing the quality of groundwater used for public supply, CA, USA: Equivalent-population and area: Environmental Science & Technology, v. 49, no. 14, p. 8830-8838, https://doi.org/10.1021/acs.est.5b00265.","productDescription":"9 p.","startPage":"8830","endPage":"8838","ipdsId":"IP-058682","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468144,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.5b00265","text":"Publisher Index 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\"}}]}","volume":"49","issue":"14","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":763298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Tyler D. 0000-0002-7334-9188","orcid":"https://orcid.org/0000-0002-7334-9188","contributorId":201888,"corporation":false,"usgs":true,"family":"Johnson","given":"Tyler D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763300,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227841,"text":"70227841 - 2018 - Predicting spatial factors associated with cattle depredations by the Mexican wolf (Canis lupus baileyi) with recommendations for depredation risk modeling","interactions":[],"lastModifiedDate":"2022-02-01T17:56:59.268014","indexId":"70227841","displayToPublicDate":"2021-06-21T11:53:14","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Predicting spatial factors associated with cattle depredations by the Mexican wolf (Canis lupus baileyi) with recommendations for depredation risk modeling","title":"Predicting spatial factors associated with cattle depredations by the Mexican wolf (Canis lupus baileyi) with recommendations for depredation risk modeling","docAbstract":"Predation on livestock is one of the primary concerns for Mexican wolf (Canis lupus baileyi) recovery because it causes economic losses and negative attitudes toward wolves. Our objectives were to develop a spatial risk model of cattle depredation by Mexican wolves in the USA portion of their recovery area to help reduce the potential for future depredations.
Arizona and New Mexico, USA.
We used a presence-only maximum entropy modeling approach (Maxent) to develop a risk model based on confirmed depredation incidents on public lands. In addition to landscape and human variables, we developed a model for annual livestock density using linear regression analysis of Animal Unit Month (AUM), and models for abundance of elk (Cervus canadensis), mule deer (Odocoileus hemionus) and white-tailed deer (Odocoileus virginiana) using Maxent, to include them as biotic variables in the risk model. We followed current recommendations for controlling model complexity and other sources of bias.
The primary factors associated with increased risk of depredation by Mexican wolf were higher canopy cover variation and higher relative abundance of elk. Additional factors with increased risk but smaller effect were gentle and open terrain, and greater distances from roads and developed areas.
The risk map revealed areas with relatively high potential for cattle depredations that can inform future expansion of Mexican wolf distribution (e.g., by avoiding hotspots) and prioritize areas for depredation risk mitigation including the implementation of active non-lethal methods in depredation hotspots. We suggest that livestock be better protected in or moved from potential hotspots, especially during periods when they are vulnerable to depredation (e.g. calving season). Our approach to create natural prey and livestock abundance variables can facilitate the process of spatial risk modeling when limitations in availability of abundance data are a challenge, especially in large-scale studies.
The USGS California Water Science Center is heavily involved in the measurement of flow and water quality parameters in the San Francisco Estuary, with support from many partner agencies. The California Department of Water Resources (DWR), through the Interagency Ecological Program (IEP) is one of those agencies. This article describes the resulting efforts and methodologies and provides examples of some of the uses of the data sets for science and management interests.
The DWR/IEP-funded flow and water quality network provides high resolution data in both space and time, over a large portion of the San Francisco Estuary. This measurement network has evolved over the preceding decades, and proven invaluable for both management and science interests, with particular relevance to water supply and endangered species issues. Presented below are a summary of the measurement network, some of the methods being utilized, and some interesting conditions that became evident during the recent drought that spanned Water Years (WY) 2013-2016, and the wet WY2017 (water year spans Oct 1-Sept 30).
","language":"English","publisher":"California Department of Water Resources","usgsCitation":"Work, P.A., and Downing-Kunz, M.A., 2018, State of the network: Long-term, high-frequency flow and water quality data in the San Francisco Estuary, California: Interagency Ecological Program (IEP) Newsletter, v. 32, no. 1, p. 59-64.","productDescription":"6 p.","startPage":"59","endPage":"64","ipdsId":"IP-098804","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":375085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":375084,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://www.usgs.gov/center-news/usgs-science-work-san-francisco-bay-estuary"},{"id":375083,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://water.ca.gov/Programs/Environmental-Services/Interagency-Ecological-Program"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.1622314453125,\n 36.756490329505176\n ],\n [\n -120.86608886718749,\n 36.756490329505176\n ],\n [\n -120.86608886718749,\n 38.45789034424927\n ],\n [\n -123.1622314453125,\n 38.45789034424927\n ],\n [\n -123.1622314453125,\n 36.756490329505176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Work, Paul A. 0000-0002-2815-8040 pwork@usgs.gov","orcid":"https://orcid.org/0000-0002-2815-8040","contributorId":168561,"corporation":false,"usgs":true,"family":"Work","given":"Paul","email":"pwork@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Downing-Kunz, Maureen A. 0000-0002-4879-0318 mdowning-kunz@usgs.gov","orcid":"https://orcid.org/0000-0002-4879-0318","contributorId":3690,"corporation":false,"usgs":true,"family":"Downing-Kunz","given":"Maureen","email":"mdowning-kunz@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744157,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202690,"text":"70202690 - 2018 - Improving ecological restoration to curb biotic invasion - A practical guide","interactions":[],"lastModifiedDate":"2019-03-18T16:19:44","indexId":"70202690","displayToPublicDate":"2019-01-04T16:19:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2100,"text":"Invasive Plant Science and Management","active":true,"publicationSubtype":{"id":10}},"title":"Improving ecological restoration to curb biotic invasion - A practical guide","docAbstract":"Common practices for invasive species control and management include physical, chemical, and biological approaches. The first two approaches have clear limitations and may lead to unintended (negative) consequences, unless carefully planned and implemented. For example, physical removal rarely completely eradicates the targeted invasive species and can cause disturbances that facilitate new invasions by nonnative species from nearby habitats. Chemical treatments can harm native, and especially rare, species through unanticipated side effects. Biological methods may be classified as biocontrol and the ecological approach. Similar to physical and chemical methods, biocontrol also has limitations and sometimes leads to unintended consequences. Therefore, a relatively safer and more practical choice may be the ecological approach, which has two major components: (1) restoration of native species and (2) biomass manipulation of the restored community, such as selective grazing or prescribed burning (to achieve and maintain viable population sizes). Restoration requires well-planned and implemented planting designs that consider alpha-, beta-, and gamma-diversity and the abundance of native and invasive component species at local, landscape, and regional levels. Given the extensive destruction or degradation of natural habitats around the world, restoration could be most effective for enhancing ecosystem resilience and resistance to biotic invasions. At the same time, ecosystems in human-dominated landscapes, especially those newly restored, require close monitoring and careful intervention (e.g., through biomass manipulation), especially when successional trajectories are not moving as intended. Biomass management frequently uses prescribed burning, grazing, harvesting, and thinning to maintain overall ecosystem health and sustainability. Thus, the resulting optimal, balanced, and relatively stable ecological conditions could more effectively limit the spread and establishment of invasive species. Here we review the literature (especially within the last decade) on ecological approaches that involve biodiversity, biomass, and productivity, three key community/ecosystem variables that reciprocally influence one another. We focus on the common and most feasible ecological practices that can aid in resisting new invasions and/or suppressing the dominance of existing invasive species. We contend that, because of the strong influences from neighboring areas (i.e., as exotic species pools), local restoration and management efforts in the future need to consider the regional context and projected climate changes.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/inp.2018.29","usgsCitation":"Guo, Q., Brockway, D.G., Larson, D.L., Wang, D., and Ren, H., 2018, Improving ecological restoration to curb biotic invasion - A practical guide: Invasive Plant Science and Management, v. 11, no. 4, p. 163-174, https://doi.org/10.1017/inp.2018.29.","productDescription":"12 p.","startPage":"163","endPage":"174","ipdsId":"IP-097426","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468155,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/inp.2018.29","text":"Publisher Index Page"},{"id":362157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Guo, Qinfeng","contributorId":214263,"corporation":false,"usgs":false,"family":"Guo","given":"Qinfeng","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":759492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brockway, Dale G.","contributorId":214264,"corporation":false,"usgs":false,"family":"Brockway","given":"Dale","email":"","middleInitial":"G.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":759493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":759491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Deli","contributorId":214265,"corporation":false,"usgs":false,"family":"Wang","given":"Deli","email":"","affiliations":[{"id":39004,"text":"Northeast Normal University","active":true,"usgs":false}],"preferred":false,"id":759494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ren, Hai","contributorId":214266,"corporation":false,"usgs":false,"family":"Ren","given":"Hai","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":759495,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202177,"text":"70202177 - 2018 - Preliminary assessment of stable nitrogen and oxygen isotopic composition of USGS51 and USGS52 nitrous oxide reference gases and perspectives on calibration needs","interactions":[],"lastModifiedDate":"2019-02-12T16:46:35","indexId":"70202177","displayToPublicDate":"2019-01-01T16:46:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3233,"text":"Rapid Communications in Mass Spectrometry","active":true,"publicationSubtype":{"id":10}},"title":"Preliminary assessment of stable nitrogen and oxygen isotopic composition of USGS51 and USGS52 nitrous oxide reference gases and perspectives on calibration needs","docAbstract":"Rationale
Despite a long history and growing interest in isotopic analyses of N2O, there is a lack of isotopically characterized N2O isotopic reference materials (standards) to enable normalization and reporting of isotope‐delta values. Here we report the isotopic characterization of two pure N2O gas reference materials, USGS51 and USGS52, which are now available for laboratory calibration (https://isotopes.usgs.gov/lab/referencematerials.html).
Methods
A total of 400 sealed borosilicate glass tubes of each N2O reference gas were prepared from a single gas filling of a high vacuum line. We demonstrated isotopic homogeneity via dual‐inlet isotope‐ratio mass spectrometry. Isotopic analyses of these reference materials were obtained from eight laboratories to evaluate interlaboratory variation and provide preliminary isotopic characterization of their δ15N, δ18O, δ15Nα, δ15Nβ and site preference (SP) values.
Results
The isotopic homogeneity of both USGS51 and USGS52 was demonstrated by one‐sigma standard deviations associated with the determinations of their δ15N, δ18O, δ15Nα, δ15Nβand SP values of 0.12 mUr or better. The one‐sigma standard deviations of SPmeasurements of USGS51 and USGS52 reported by eight laboratories participating in the interlaboratory comparison were 1.27 and 1.78 mUr, respectively.
Conclusions
The agreement of isotope‐delta values obtained in the interlaboratory comparison was not sufficient to provide reliable accurate isotope measurement values for USGS51 and USGS52. We propose that provisional values for the isotopic composition of USGS51 and USGS52 determined at the Tokyo Institute of Technology can be adopted for normalizing and reporting sample data until further refinements are achieved through additional calibration efforts.
Marine terraces are common on the Pacific Coast of North America and record interglacial high-sea stands superimposed on either stable or tectonically rising crustal blocks. Despite many years of study of these landforms in southern California, little work on terraces has been conducted on the two smallest of the California Channel Islands, Santa Barbara Island (SBI) and Anacapa Island (ANA). Presented here are new field and laboratory data on the ages, paleontology, and sea level history of marine terraces of these two islands. On both islands, the lowest marine terraces have shoreline angle elevations of ∼11 m above sea level. Amino acid geochronology shows that terrace deposits on both islands host fossils of two ages, one group dating to the ∼120-ka high-sea stand and the other group likely dating to the ∼100-ka high-sea stand. A mix of fossil ages is consistent with the paleontology as well, with SBI in particular showing a faunal assemblage that includes both extralimital southern and southward-ranging species (inferred to be from the ∼120-ka high-sea stand) and extralimital northern and northward-ranging species (inferred to be from the ∼100-ka high-sea stand). Fossil mixing from these two high-sea stands supports the hypothesis that glacial isostatic adjustment (GIA) processes have left a strong imprint on the geologic record of sea level history in southern California. Nevertheless, the elevations of these terraces and that of a low terrace on Santa Cruz Island indicate that modeled GIA estimates of paleo-sea level for the peak of the last interglacial period at ∼120 ka could be too high. Future development of models of GIA effects on the Pacific Coast of North America will need to consider geologic records, such as those from SBI and ANA, in refining reconstructions of sea level history.
","language":"English","publisher":"Brigham Young University","doi":"10.3398/064.078.0403","usgsCitation":"Muhs, D., and Groves, L.T., 2018, Little islands recording global events: Late Quaternary sea level history and paleozoogeography of Santa Barbara and Anacapa Islands, Channel Islands National Park, California: Western North American Naturalist, v. 78, no. 4, p. 540-589, https://doi.org/10.3398/064.078.0403.","productDescription":"50 p.","startPage":"540","endPage":"589","ipdsId":"IP-084957","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":361393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Anacapa Island, Channel Islands National Park, Santa Barbara Island, Santa Cruz Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.95834350585936,\n 33.44633901936737\n ],\n [\n -119.00939941406249,\n 33.44633901936737\n ],\n [\n -119.00939941406249,\n 34.110667538758996\n ],\n [\n -119.95834350585936,\n 34.110667538758996\n ],\n [\n -119.95834350585936,\n 33.44633901936737\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":168575,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel R.","email":"dmuhs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":757693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Groves, Lindsey T.","contributorId":213427,"corporation":false,"usgs":false,"family":"Groves","given":"Lindsey","email":"","middleInitial":"T.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":757694,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203296,"text":"70203296 - 2018 - Extreme‐value geoelectric amplitude and polarization across the northeast United States","interactions":[],"lastModifiedDate":"2019-05-02T09:06:48","indexId":"70203296","displayToPublicDate":"2018-12-26T06:55:46","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Extreme‐value geoelectric amplitude and polarization across the northeast United States","docAbstract":"Maps are presented of extreme‐value geoelectric field amplitude and horizontal polarization for the Northeast United States. These maps are derived from geoelectric time series calculated for sites across the Northeast by frequency‐domain multiplication (time‐domain convolution) of 172 magnetotelluric impedance tensors, acquired during a survey, with decades‐long, 1‐min resolution time series of geomagnetic variation, acquired at three magnetic observatories. The maps show that, during intense magnetic storms, high geoelectric amplitude hazards are realized across electrically resistive, igneous and metamorphic rock of the Appalachian Mountains and the New England Highlands, while low geoelectric hazards are realized across electrically conductive, sedimentary rock of the Appalachian Plateau and the Mid‐Atlantic Coastal Plain. From statistical extrapolation, once‐per‐century (100‐year) geoelectric amplitudes are highest at a site in Virginia at 25.44 V/km (followed by a site in Maine at 21.75 V/km and a site in Connecticut at 19.39 V/km); 100‐year geoelectric amplitude exceeds 10 V/km at 12 sites across the northeast; geoelectric amplitude is lowest at a site in Virginia at 0.05 V/km. Average errors for these values are estimated to be about 38%, or much less than the more than 2 orders of magnitude range seen in geoelectric amplitudes from one survey site to another across the northeast. It is noteworthy that geoelectric fields tend to be most (least) polarized at locations with high (low) geoelectric hazard. Furthermore, geoelectric fields over the Appalachians tend to be polarized southeast‐to‐northwest, or generally in a direction orthogonal to the southwest‐to‐northeast geological strike. Results reported here inform utility companies in projects for evaluating and managing the response of power grid systems to the deleterious effects of geomagnetic disturbance.