Imperfect detection and misclassification errors are often ignored in the context of invasive species management. Here we present an approach that combines spatially explicit models and an optimization technique to design optimal search and destroy strategies based on noisy monitoring observations. We focus on two invasive plants, melaleuca (Melaleuca quinquenervia) and Old World climbing fern (Lygodium microphyllum), which continue to cause important damages to the Everglades ecosystem. We present a methodological framework that combines Hidden Markov Random Field (HMRF, initially developed for image analysis) and linear programming to optimally search for invasive species. A benefit of this approach is that it accounts for the spatial structure of the system by using a spatially explicit modeling approach (i.e. HMRF), and does not require repeated visits to model the probability of occurrence of species. We found on simulated cases that our approach can lead to substantial improvements in control efficiency when compared to state of the art model-free approaches. For example, in the case of the old world fern, simulations showed that the optimal strategy would allow managers to control up to 34% more sites than with model-free approaches that ignored misclassification and imperfect detection. For melaleuca it was possible to control up to 20% more sites. The vast increase in imagery data obtained from different sources (e.g. unmanned aerial systems, and satellite) provides great opportunities to improve management of natural resources by applying modern computational methods such as the one we present. Our approach can substantially increases the efficiency of invasive species control by accounting for imperfect detection, misclassification error and the spatial structure of the system. Our approach is applicable to other systems and problems, for example it could be applied to the control of plant pathogens, or optimal extraction of resources (e.g. minerals or biological resources).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.11.012","usgsCitation":"Bonneau, M., Martin, J., Peyrard, N., Rodgers, L., Romagosa, C.M., and Johnson, F., 2019, Optimal spatial allocation of control effort to manage invasives in the face of imperfect detection and misclassification: Ecological Modelling, v. 392, p. 108-116, https://doi.org/10.1016/j.ecolmodel.2018.11.012.","productDescription":"9 p.","startPage":"108","endPage":"116","ipdsId":"IP-089846","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2018.11.012","text":"Publisher Index Page"},{"id":366875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"392","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bonneau, Mathieu","contributorId":150041,"corporation":false,"usgs":false,"family":"Bonneau","given":"Mathieu","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":769177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":214502,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peyrard, Nathalie","contributorId":218403,"corporation":false,"usgs":false,"family":"Peyrard","given":"Nathalie","email":"","affiliations":[],"preferred":false,"id":769179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodgers, LeRoy","contributorId":217557,"corporation":false,"usgs":false,"family":"Rodgers","given":"LeRoy","email":"","affiliations":[{"id":7036,"text":"South Florida Water Management District","active":true,"usgs":false}],"preferred":false,"id":769180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romagosa, Christina M.","contributorId":200925,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":769181,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Fred A. 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":213877,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769182,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70207458,"text":"70207458 - 2019 - C–O stable isotope geochemistry and 40Ar/39Ar geochronology of the Bear Lodge carbonatite stockwork, Wyoming, USA","interactions":[],"lastModifiedDate":"2019-12-19T15:41:54","indexId":"70207458","displayToPublicDate":"2018-11-28T15:29:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2588,"text":"LITHOS","active":true,"publicationSubtype":{"id":10}},"displayTitle":"C–O stable isotope geochemistry and 40Ar/39Ar geochronology of the Bear Lodge carbonatite stockwork, Wyoming, USA","title":"C–O stable isotope geochemistry and 40Ar/39Ar geochronology of the Bear Lodge carbonatite stockwork, Wyoming, USA","docAbstract":"The carbonatite dike swarm and vein stockwork at the center of the Paleogene Bear Lodge alkaline complex (BLAC), Wyoming, USA, is host to diverse REE mineral assemblages that are largely a result of subsolidus modification and REE redistribution. Pseudomorphic replacement of primary burbankite by an assemblage of ancylite, strontianite, and barite is the result of interaction with late-stage hydrothermal fluids that added Sr, Ba, S, F, and REE, analogous to the replacement processes described for some carbonatite complexes of Russia's Kola Peninsula. Carbon and oxygen stable isotope ratios indicate that the primary carbonatite mineralogy experienced degassing/pneumatolysis and alteration by fluids of variable temperature, CO2/H2O ratios, and/or meteoric water content. Isotopic differences of matrix calcite between Group 1 carbonatites (avg. δ13C = −7.3‰; δ18O = 9.1‰) and Group 2 carbonatites (avg. δ13C = −9.9‰; δ18O = 10.2‰) are consistent with loss of CO2 during degassing. The open-system alteration of burbankite caused a pronounced positive δ18O-shift in bulk ancylite pseudomorphs (δ18O: 14.3–25.7‰) relative to matrix calcite (δ18O: 8.7–11.2‰). Oxygen isotope compositions of biotite (δ18O: 4.5–5.9‰) and K-feldspar (δ18O: 7.3–7.9‰) in unoxidized carbonatite are typical of primary magmatic silicates and suggest that fluids responsible for the burbankite-to-ancylite conversion remained predominantly magmatic (carbohydrothermal). Concomitant increases toward the surface in 13C and 18O, oxidation, matrix carbonate dissolution, and the replacement of REE carbonates (ancylite, carbocernaite, and burbankite) by Ca-REE fluorocarbonates (bastnäsite, parisite, synchysite) suggest interaction with late-stage, low temperature (<250 °C) fluids characterized by lower CO2/H2O ratios, and an increasing meteoric water component. The first 40Ar/39Ar ages from carbonatite-hosted biotite and K-feldspar at the BLAC are between 51.45 ± 0.08 and 51.89 ± 0.14 Ma. Although carbonatite is commonly observed as the final intrusive phase in alkaline igneous complexes, relative-age relationships and previously published geochronology for Bear Lodge rocks indicate that alkaline silicate magmatism both preceded and followed carbonatite emplacement.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.lithos.2018.11.030","usgsCitation":"Andersen, A.K., Larson, P.B., and Cosca, M.A., 2019, C–O stable isotope geochemistry and 40Ar/39Ar geochronology of the Bear Lodge carbonatite stockwork, Wyoming, USA: LITHOS, v. 324-324, p. 640-660, https://doi.org/10.1016/j.lithos.2018.11.030.","productDescription":"21 p.","startPage":"640","endPage":"660","ipdsId":"IP-097912 ","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":370516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bear Lodge alkaline complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.79721069335938,\n 44.40827836571936\n ],\n [\n -104.3975830078125,\n 44.40827836571936\n ],\n [\n -104.3975830078125,\n 44.71063416158254\n ],\n [\n -104.79721069335938,\n 44.71063416158254\n ],\n [\n -104.79721069335938,\n 44.40827836571936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"324-324","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Andersen, Allen K. 0000-0002-6865-2561","orcid":"https://orcid.org/0000-0002-6865-2561","contributorId":217476,"corporation":false,"usgs":true,"family":"Andersen","given":"Allen","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":778124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Peter B.","contributorId":22645,"corporation":false,"usgs":true,"family":"Larson","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":778125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":778126,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204970,"text":"70204970 - 2019 - Overview of spirit microscopic imager results","interactions":[],"lastModifiedDate":"2019-08-28T10:57:49","indexId":"70204970","displayToPublicDate":"2018-11-28T14:22:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Overview of spirit microscopic imager results","docAbstract":"This paper provides an overview of Mars Exploration Rover Spirit Microscopic Imager (MI) operations and the calibration, processing, and analysis of MI data. The focus of this overview is on the last five Earth years (2005–2010) of Spirit's mission in Gusev crater, supplementing the previous overview of the first 450 sols of the Spirit MI investigation. Updates to radiometric calibration using in‐flight data and improvements in high‐level processing are summarized. Released data products are described, and a table of MI observations, including target/feature names and associated data sets, is appended. The MI observed natural and disturbed exposures of rocks and soils as well as magnets and other rover hardware. These hand‐lens‐scale observations have provided key constraints on interpretations of the formation and geologic history of features, rocks, and soils examined by Spirit. MI images complement observations by other Spirit instruments, and together show that impact and volcanic processes have dominated the origin and evolution of the rocks in Gusev crater, with aqueous activity indicated by the presence of silica‐rich rocks and sulfate‐rich soils. The textures of some of the silica‐rich rocks are similar to terrestrial hot spring deposits, and observations of subsurface cemented layers indicate recent aqueous mobilization of sulfates in places. Wind action has recently modified soils and abraded many of the rocks imaged by the MI, as observed at other Mars landing sites.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JE005774","usgsCitation":"Herkenhoff, K., Squyres, S., Arvidson, R.E., Cole, S.B., Sullivan, R., Yingst, A., Cabrol, N., Lee, E., Richie, J., Sucharski, R.M., Calef, F.J., Bell, J., Chapman, M., Geissler, P., Edgar, L.A., Franklin, B., Hurowitz, J.A., Jensen, E., Johnson, J.R., Kirk, R.L., Lanagan, P., Mullins, K., Leff, C., Maki, J., Redding, B.L., Rice, M., Sims, M.H., Spanovich, N., Soderblom, L.A., Sunda, A., Springer, R., and Vaughan, A., 2019, Overview of spirit microscopic imager results: Journal of Geophysical Research E: Planets, v. 124, no. 2, p. 528-584, https://doi.org/10.1029/2018JE005774.","productDescription":"57 p.","startPage":"528","endPage":"584","ipdsId":"IP-087430","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468048,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/633773","text":"External Repository"},{"id":367004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gusev Crater, Mars","volume":"124","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":206170,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Squyres, Steve W","contributorId":218471,"corporation":false,"usgs":false,"family":"Squyres","given":"Steve W","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":769328,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arvidson, Raymond E.","contributorId":106626,"corporation":false,"usgs":false,"family":"Arvidson","given":"Raymond","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":769334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cole, Shoshanna B","contributorId":218473,"corporation":false,"usgs":false,"family":"Cole","given":"Shoshanna","email":"","middleInitial":"B","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":769335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Rob","contributorId":218474,"corporation":false,"usgs":false,"family":"Sullivan","given":"Rob","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":769336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yingst, Aileen","contributorId":172313,"corporation":false,"usgs":false,"family":"Yingst","given":"Aileen","email":"","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":769337,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cabrol, Nathalie","contributorId":218475,"corporation":false,"usgs":false,"family":"Cabrol","given":"Nathalie","affiliations":[{"id":39853,"text":"NASA Ames Research Center/SETI Institute","active":true,"usgs":false}],"preferred":false,"id":769338,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lee, Ella 0000-0001-6144-7197 elee@usgs.gov","orcid":"https://orcid.org/0000-0001-6144-7197","contributorId":218476,"corporation":false,"usgs":true,"family":"Lee","given":"Ella","email":"elee@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769339,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Richie, Janet 0000-0003-4151-1010","orcid":"https://orcid.org/0000-0003-4151-1010","contributorId":206347,"corporation":false,"usgs":true,"family":"Richie","given":"Janet","email":"","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769329,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sucharski, Robert M. bsucharski@usgs.gov","contributorId":5051,"corporation":false,"usgs":true,"family":"Sucharski","given":"Robert","email":"bsucharski@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":769601,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Calef, Fred J.","contributorId":146331,"corporation":false,"usgs":false,"family":"Calef","given":"Fred","email":"","middleInitial":"J.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":769341,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bell, James F. 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","suffix":"III","affiliations":[{"id":34032,"text":"School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287","active":true,"usgs":false}],"preferred":false,"id":769340,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Chapman, Mary","contributorId":218574,"corporation":false,"usgs":false,"family":"Chapman","given":"Mary","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":false,"id":769602,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Geissler, Paul","contributorId":206262,"corporation":false,"usgs":true,"family":"Geissler","given":"Paul","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769603,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Edgar, Lauren A. 0000-0001-7512-7813 ledgar@usgs.gov","orcid":"https://orcid.org/0000-0001-7512-7813","contributorId":167501,"corporation":false,"usgs":true,"family":"Edgar","given":"Lauren","email":"ledgar@usgs.gov","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769330,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Franklin, Brenda","contributorId":210516,"corporation":false,"usgs":false,"family":"Franklin","given":"Brenda","email":"","affiliations":[{"id":18954,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":769342,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Hurowitz, Joel A.","contributorId":200390,"corporation":false,"usgs":false,"family":"Hurowitz","given":"Joel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":769343,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Jensen, Elsa","contributorId":218477,"corporation":false,"usgs":false,"family":"Jensen","given":"Elsa","affiliations":[{"id":36716,"text":"Malin Space Science Systems","active":true,"usgs":false}],"preferred":false,"id":769344,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Johnson, Jeffrey R.","contributorId":200393,"corporation":false,"usgs":false,"family":"Johnson","given":"Jeffrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":769345,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769353,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Lanagan, Peter","contributorId":210517,"corporation":false,"usgs":false,"family":"Lanagan","given":"Peter","email":"","affiliations":[{"id":25655,"text":"Lunar and Planetary Laboratory, 1629 E. University Blvd., The University of Arizona, Tucson, AZ 85721, United States","active":true,"usgs":false}],"preferred":false,"id":769346,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Mullins, Kevin","contributorId":218575,"corporation":false,"usgs":false,"family":"Mullins","given":"Kevin","affiliations":[],"preferred":false,"id":769604,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Leff, Craig","contributorId":210518,"corporation":false,"usgs":false,"family":"Leff","given":"Craig","email":"","affiliations":[],"preferred":false,"id":769347,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Maki, Justin","contributorId":218478,"corporation":false,"usgs":false,"family":"Maki","given":"Justin","affiliations":[{"id":18876,"text":"California Institute of Technology, Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":769348,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Redding, Bonnie L. 0000-0001-8178-1467 bredding@usgs.gov","orcid":"https://orcid.org/0000-0001-8178-1467","contributorId":4798,"corporation":false,"usgs":true,"family":"Redding","given":"Bonnie","email":"bredding@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769332,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Rice, Melissa","contributorId":172306,"corporation":false,"usgs":false,"family":"Rice","given":"Melissa","affiliations":[{"id":12723,"text":"Western Washington University","active":true,"usgs":false}],"preferred":false,"id":769349,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Sims, Michael H.","contributorId":210519,"corporation":false,"usgs":false,"family":"Sims","given":"Michael","email":"","middleInitial":"H.","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":769350,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Sunda, Annette 0000-0002-3485-6398","orcid":"https://orcid.org/0000-0002-3485-6398","contributorId":218472,"corporation":false,"usgs":true,"family":"Sunda","given":"Annette","email":"","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769333,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Spanovich, Nicole","contributorId":210520,"corporation":false,"usgs":false,"family":"Spanovich","given":"Nicole","email":"","affiliations":[{"id":18954,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":769351,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Springer, Richard","contributorId":210521,"corporation":false,"usgs":false,"family":"Springer","given":"Richard","email":"","affiliations":[{"id":18954,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":769352,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Soderblom, Laurence A. 0000-0002-0917-853X lsoderblom@usgs.gov","orcid":"https://orcid.org/0000-0002-0917-853X","contributorId":2721,"corporation":false,"usgs":true,"family":"Soderblom","given":"Laurence","email":"lsoderblom@usgs.gov","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769354,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Vaughan, Alicia","contributorId":218576,"corporation":false,"usgs":false,"family":"Vaughan","given":"Alicia","affiliations":[],"preferred":false,"id":769605,"contributorType":{"id":1,"text":"Authors"},"rank":32}]}} ,{"id":70204461,"text":"70204461 - 2019 - Modeling White Sucker (Catostomus commersonii) populations to assess commercial harvest influence on age structure","interactions":[],"lastModifiedDate":"2019-07-26T10:22:58","indexId":"70204461","displayToPublicDate":"2018-11-28T11:29:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2299,"text":"Journal of Freshwater Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modeling White Sucker (Catostomus commersonii) populations to assess commercial harvest influence on age structure","title":"Modeling White Sucker (Catostomus commersonii) populations to assess commercial harvest influence on age structure","docAbstract":"Commercial harvest of White Suckers Catostomus commersonii for bait in the American Lobster Homarus americanus industry is minimally regulated in Maine and there are concerns as to the influence of increasing harvest. We built a population model using parameters (i.e. age-specific mortality, age at maturity, and size-specific fecundity) from literature and field studies to investigate the theoretical effects of harvest mortality on age structure. Because stock-recruitment relations are poorly characterized for this species, we explored the influence of both Beverton-Holt and Ricker recruitment processes. Our base model closely resembled the empirical age structures reported from three unfished lakes in Maine, with four percent of fish in the modeled spawning run being age-10 or older. We assessed the additive effects of harvest mortality on age structure using the full range of possible mortalities. As expected, increased harvest mortality in the model resulted in a decline and disappearance of older age-classes such that few fish greater than age-10 remained in the population under a realistic harvest mortality scenario. This age-truncation was qualitatively comparable to data from aggregate age distributions reported from three commercially harvested lakes in Maine. Because the loss of older fish may compromise population viability, this model is a valuable guidance tool for managers to craft regulation of this growing fishery.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02705060.2018.1496951","usgsCitation":"Zydlewski, J.D., Begley, M., and Coghlan, S., 2019, Modeling White Sucker (Catostomus commersonii) populations to assess commercial harvest influence on age structure: Journal of Freshwater Ecology, v. 33, no. 1, p. 413-428, https://doi.org/10.1080/02705060.2018.1496951.","productDescription":"16 p.","startPage":"413","endPage":"428","ipdsId":"IP-084184","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2018.1496951","text":"Publisher Index Page"},{"id":365939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"33","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":767018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Begley, Meg","contributorId":217535,"corporation":false,"usgs":false,"family":"Begley","given":"Meg","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":767191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coghlan, Stephen","contributorId":199623,"corporation":false,"usgs":false,"family":"Coghlan","given":"Stephen","email":"","affiliations":[],"preferred":false,"id":767020,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227741,"text":"70227741 - 2019 - Modelling effects of invasive species and drought on crayfish extinction risk and population dynamics","interactions":[],"lastModifiedDate":"2022-01-28T16:15:17.750707","indexId":"70227741","displayToPublicDate":"2018-11-28T10:07:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Modelling effects of invasive species and drought on crayfish extinction risk and population dynamics","docAbstract":"The occurrence of plant species across the globe is largely constrained by climate. Ecologists use plant-climate relationships such as bioclimatic envelopes and related niche models to determine potential environmental conditions promoting probable species occurrence. Traditionally bioclimatic envelopes either exclude disturbance explicitly, or only include disturbance as infrequent and smaller scale processes, assuming that the net effect of climate parameters on key demographic processes predict longer-term equilibrial responses of biota. Due to increasing frequency and extent of extreme events associated with climate change, ecologists may need to increase focus on individual demographic events driven by environmental extremes such as widespread coral bleaching or large-scale tree die-off. An expanded focus on how extreme events catalyze individual demographic events would complement existing tools that predict long-term equilibrial biogeographic responses associated with long-term trends in climate. In many cases, extreme conditions (e.g. drought) are a necessary precursor for an abrupt demographic event (e.g. large-scale tree die-off) and the effects of extremes can be exacerbated by climatic trends (e.g. higher temperatures in combination with drought). Here, we highlight application of bioclimatic models for predicting individual demographic events. Defining the environmental conditions that precipitate demographic events such as widespread tree mortality is a necessary precursor for applying predictions to geographic space, and may require challenging biota with experiments that impose a combination of ecologically extreme conditions in one parameter and a shifting distribution in another (e.g. drought under higher temperatures). Currently data on conditions that drive individual demographic events associated with extremes are usually rare, aggregated across time, and/or correlative. We highlight this approach with a case study of drought-induced mortality in adult Pinus edulis trees that predicts a more than five-fold increase in frequency of die-off events under a global change scenario of high emissions. This general approach complements both traditional bioclimatic envelopes and more detailed physiological approaches currently being refined to address climate change challenges. Notably, this proposed approach could be developed for any climate condition or plant life stage, offering promise for improving predictions of individual demographic events that are rapidly altering ecosystems globally.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/700702","usgsCitation":"Law, D.J., Adams, H.D., Breshears, D.D., Cobb, N.S., Bradford, J.B., Zou, C.B., Field, J.P., Gardea, A.A., Williams, A.P., and Huxman, T.E., 2019, Bioclimatic envelopes for individual demographic events driven by extremes: Plant mortality from drought and warming: International Journal of Plant Sciences, v. 80, no. 1, p. 53-62, https://doi.org/10.1086/700702.","productDescription":"10 p.","startPage":"53","endPage":"62","ipdsId":"IP-066810","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":367246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Law, Darin J.","contributorId":216390,"corporation":false,"usgs":false,"family":"Law","given":"Darin","email":"","middleInitial":"J.","affiliations":[{"id":39400,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":770258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Henry D.","contributorId":218785,"corporation":false,"usgs":false,"family":"Adams","given":"Henry","email":"","middleInitial":"D.","affiliations":[{"id":39910,"text":"Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544, USA","active":true,"usgs":false}],"preferred":false,"id":770261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breshears, David D.","contributorId":51620,"corporation":false,"usgs":false,"family":"Breshears","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":770260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cobb, Neil S.","contributorId":200776,"corporation":false,"usgs":false,"family":"Cobb","given":"Neil","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":770262,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":770257,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zou, Chris B.","contributorId":218786,"corporation":false,"usgs":false,"family":"Zou","given":"Chris","email":"","middleInitial":"B.","affiliations":[{"id":39911,"text":"Oklahoma State University, Stillwater, OK 74074, USA","active":true,"usgs":false}],"preferred":false,"id":770263,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Field, Jason P.","contributorId":216389,"corporation":false,"usgs":false,"family":"Field","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":39400,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":770259,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gardea, Alfonso A.","contributorId":218787,"corporation":false,"usgs":false,"family":"Gardea","given":"Alfonso","email":"","middleInitial":"A.","affiliations":[{"id":39912,"text":"Centro de Investigación en Alimentación y Desarrollo, A.C., Guaymas, Sonora, Mexico","active":true,"usgs":false}],"preferred":false,"id":770264,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Williams, A. Park","contributorId":200207,"corporation":false,"usgs":false,"family":"Williams","given":"A.","email":"","middleInitial":"Park","affiliations":[{"id":27369,"text":"Lamont-Doherty Earth Observatory at Columbia University","active":true,"usgs":false}],"preferred":false,"id":770265,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Huxman, Travis E.","contributorId":53898,"corporation":false,"usgs":false,"family":"Huxman","given":"Travis","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":770266,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70201074,"text":"70201074 - 2019 - Extreme value-based methods for modeling elk yearly movements","interactions":[],"lastModifiedDate":"2019-02-11T15:03:17","indexId":"70201074","displayToPublicDate":"2018-11-27T10:08:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2151,"text":"Journal of Agricultural, Biological, and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Extreme value-based methods for modeling elk yearly movements","docAbstract":"Species range shifts and the spread of diseases are both likely to be driven by extreme movements, but are difficult to statistically model due to their rarity. We propose a statistical approach for characterizing movement kernels that incorporate landscape covariates as well as the potential for heavy-tailed distributions. We used a spliced distribution for distance travelled paired with a resource selection function to model movements biased toward preferred habitats. As an example, we used data from 704 annual elk movements around the Greater Yellowstone Ecosystem from 2001 to 2015. Yearly elk movements were both heavy-tailed and biased away from high elevations during the winter months. We then used a simulation to illustrate how these habitat effects may alter the rate of disease spread using our estimated movement kernel relative to a more traditional approach that does not include landscape covariates. Supplementary materials accompanying this paper appear online.
","language":"English","publisher":"Springer","doi":"10.1007/s13253-018-00342-2","usgsCitation":"Wijeyakulasuriya, D.A., Hanks, E.M., Shaby, B.A., and Cross, P.C., 2019, Extreme value-based methods for modeling elk yearly movements: Journal of Agricultural, Biological, and Environmental Statistics, v. 24, no. 1, p. 73-91, https://doi.org/10.1007/s13253-018-00342-2.","productDescription":"19 p.","startPage":"73","endPage":"91","ipdsId":"IP-094523","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":359698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-12","publicationStatus":"PW","scienceBaseUri":"5bfe65e0e4b0815414ca60f2","contributors":{"authors":[{"text":"Wijeyakulasuriya, Dhanushi A. 0000-0001-6244-6575","orcid":"https://orcid.org/0000-0001-6244-6575","contributorId":210839,"corporation":false,"usgs":false,"family":"Wijeyakulasuriya","given":"Dhanushi","email":"","middleInitial":"A.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":752266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, Ephraim M. 0000-0003-0345-7164","orcid":"https://orcid.org/0000-0003-0345-7164","contributorId":210840,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim","email":"","middleInitial":"M.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":752267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaby, Benjamin A.","contributorId":210841,"corporation":false,"usgs":false,"family":"Shaby","given":"Benjamin","email":"","middleInitial":"A.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":752268,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":752265,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215506,"text":"70215506 - 2019 - Early arc development recorded in Permian–Triassic plutons of the northern Mojave Desert region, California, USA","interactions":[],"lastModifiedDate":"2020-10-21T14:12:28.072247","indexId":"70215506","displayToPublicDate":"2018-11-27T09:09:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Early arc development recorded in Permian–Triassic plutons of the northern Mojave Desert region, California, USA","docAbstract":"Permian–Middle Triassic plutons in the northern Mojave Desert, USA, are emplaced into the cryptic El Paso terrane, which is characterized by a northwest-striking belt of deep marine eugeoclinal strata juxtaposed against Proterozoic basement and its miogeoclinal cover. Fourteen new zircon U-Pb ages from the El Paso Mountains and Lane Mountain region of the Mojave Desert record nearly continuous magmatism occurring between ca. 275 and 240 Ma. These ages, which are taken to record the onset of subduction-related magmatism along the southwestern Laurentian margin, are older than the earliest arc plutons documented in the southern Sierra Nevada region to the north and in the Transverse Ranges to the south. They overlap, however, with Permian arc plutons documented in Sonora, Mexico. Dated plutons are compositionally variable, but can be characterized as intermediate to felsic, calcic to calc-alkalic, and having chemistries consistent with generation in an arc setting. Whole rock Sr-Nd isotopic compositions vary widely from relatively primitive (Sri = 0.7035, initial εNd = +3, initial εHf in zircon = +13) to moderately evolved (Sri = 0.708, initial εNd = –5, initial εHf in zircon = –3). Isotopic signatures differ considerably from partially coeval Triassic suites of the Transverse Ranges and central Mojave, which are more evolved and consistent with emplacement in Proterozoic continental crust of the Mojave province. They also differ considerably from those typical of intermediate plutons generated in intra-oceanic arcs, which are overall much more mantle-like. This suggests that the underpinnings of the El Paso terrane may be at least partly composed of continental crust and that magmas emplaced into the terrane may have been variably contaminated by crustal components. This is supported by the presence of Precambrian and early Paleozoic zircon inheritance recorded in some plutons. In all isotopic systems, values are the most evolved in the oldest plutons (ca. 275–270 Ma), becoming more juvenile in the Middle Triassic. These temporal trends, together with pluton fabrics and new estimates of Permian plate vectors, are interpreted to reflect generation of the earliest arc in a contractional setting that may have driven crustal thickening and a greater involvement of crustal materials in Permian magmas. This result supports a model of forced subduction initiation, which is favored by a change in plate motions along a previously weak margin, and predicts an initial compressive state in the upper plate. The uniformly primitive signatures of Triassic melts are taken to indicate a change to a transtensional upper-plate stress regime that promoted the development of more voluminous, primarily mantle-derived melts. Regional pluton age patterns suggest that arc magmatism initiated in restricted areas of the southwestern Laurentian margin (northern Mojave, Sonora) and then migrated north and south ultimately becoming a continuous arc by Jurassic time.
Aims
Understanding the conditions associated with dryland vegetation recovery after restoration treatments is challenging due to a lack of monitoring data and high environmental variability over time and space. Tracking recovery trajectories with satellite‐based vegetation indices can strengthen predictions of restoration outcomes across broad areas with varying environmental conditions.
Location
Southwestern United States.
Methods
We quantified the recovery trajectories of spring and summer soil‐adjusted total vegetation index (SATVI) for 5 to 10 year periods following post‐wildfire seeding or prescribed burns for 241 treatment sites, and related SATVI to ground‐based vegetation cover. We modeled SATVI based on time since treatment, yearly temperature and precipitation, weather extremes following treatment, soil available water capacity, invasive species presence, and treatment type. We also tested for the effects of environmental variables on trajectories, by examining interactions with years post‐treatment.
Results
Ground‐based vegetation cover and SATVI were highly correlated. Most treatment sites had positive recovery rates for spring (82%) and summer (85%) SATVI. Several environmental variables affected vegetation recovery trajectories as indicated by interactions with time since treatment. Yearly warm season precipitation had a positive effect on SATVI recovery that increased over time, whereas the positive effect of extreme high warm season precipitation following treatment decreased over time for both seasons of vegetation measurements. For spring SATVI, the positive effect of cool season yearly precipitation increased over time while the negative effect of extreme high temperatures following treatment became more negative over time. Invasive species presence led to higher spring, but not summer, SATVI.
Conclusions
Satellite‐based remote sensing is a promising tool to assess vegetation recovery following restoration treatments, particularly when it is combined with ground‐based monitoring. Our results suggest that weather extremes following restoration treatments can affect vegetation recovery trajectories and should be considered in decisions such as the timing of restoration treatments.
Early ocean survival of Chinook salmon, Oncorhynchus tshawytscha, varies greatly inter-annually and may be the period during which later spawning abundance and fishery recruitment are set. Therefore, identifying environmental drivers related to early survival may inform better models for management and sustainability of salmon in a variable environment. With this in mind, our main objectives were to (a) identify regions of high temporal variability in growth potential over a 23-year time series, (b) determine whether the spatial distribution of growth potential was correlated with observed oceanographic conditions, and (c) determine whether these spatial patterns in growth potential could be used to estimate juvenile salmon survival. We applied this method to the fall run of the Central Valley Chinook salmon population, focusing on the spring and summer period after emigration into central California coastal waters. For the period from 1988 to 2010, juvenile salmon growth potential on the central California continental shelf was described by three spatial patterns. These three patterns were most correlated with upwelling, detrended sea level anomalies, and the strength of onshore/offshore currents, respectively. Using the annual strength of these three patterns, as well as the overall growth potential throughout central California coastal waters, in a generalized linear model we explained 82% of the variation in juvenile salmon survival estimates. We attributed the relationship between growth potential and survival to variability in environmental conditions experienced by juvenile salmon during their first year at sea, as well as potential shifts in predation pressure following out-migration into coastal waters.
Topographic surveys inevitably contain error, introducing uncertainty into estimates of volumetric or mean change based on the differencing of repeated surveys. In the geomorphic community, uncertainty has often been framed as a problem of separating out real change from apparent change due purely to error, and addressed by removing measured change considered indistinguishable from random noise from analyses (thresholding). Thresholding is important when quantifying gross changes (i.e. total erosion or total deposition), which are systematically biased by random errors in stable parts of a landscape. However, net change estimates are not substantially influenced by those same random errors, and the use of thresholds results in inherently biased, and potentially misleading, estimates of net change and uncertainty. More generally, thresholding is unrelated to the important process of propagating uncertainty in order to place uncertainty bounds around final estimates. Error propagation methods for uncorrelated, correlated, and systematic errors are presented. Those equations demonstrate that uncertainties in modern net change analyses, as well as in gross change analyses using reasonable thresholds, are likely to be dominated by low‐magnitude but highly correlated or systematic errors, even after careful attempts to reduce those errors. In contrast, random errors with little to no correlation largely cancel to negligible levels when averaged or summed. Propagated uncertainty is then typically insensitive to the precision of individual measurements, and is instead defined by the relative mean error (accuracy) over the area of interest. Given that real‐world mean elevation changes in many landscape settings are often similar in magnitude to potential mean errors in repeat topographic analyses, reducing highly correlated or systematic errors will be central to obtaining accurate change estimates, while placing uncertainty bounds around those results provides essential context for their interpretation.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4551","usgsCitation":"Anderson, S.W., 2019, Uncertainty in quantitative analyses of topographic change: Error propagation and the role of thresholding: Earth Surface Processes and Landforms, v. 44, no. 5, p. 1015-1033, https://doi.org/10.1002/esp.4551.","productDescription":"19 p.","startPage":"1015","endPage":"1033","ipdsId":"IP-097288","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":361175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757062,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70200978,"text":"70200978 - 2019 - Distance models as a tool for modelling detection probability and density of native bumblebees","interactions":[],"lastModifiedDate":"2019-03-15T12:42:58","indexId":"70200978","displayToPublicDate":"2018-11-20T10:58:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5782,"text":"Journal of Applied Entomology","active":true,"publicationSubtype":{"id":10}},"title":"Distance models as a tool for modelling detection probability and density of native bumblebees","docAbstract":"Effective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed‐area net surveys (“net counts”) and fixed‐width transect counts (“transect counts”) at 47 early‐successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey‐ and site‐covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombusspp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/non‐detection data collected via point‐counts, line‐transects and distance sampling for Bombus spp. are unlikely to yield species‐specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp.and other pollinators.
","language":"English","publisher":"Wiley","doi":"10.1111/jen.12583","usgsCitation":"McNeil, D.J., Otto, C., Moser, E.L., Urban-Mead, K.R., King, D.E., Rodewald, A.D., and Larkin, J.L., 2019, Distance models as a tool for modelling detection probability and density of native bumblebees: Journal of Applied Entomology, v. 143, no. 3, p. 225-235, https://doi.org/10.1111/jen.12583.","productDescription":"11 p.","startPage":"225","endPage":"235","ipdsId":"IP-096861","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":359602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Centre County, Clinton County","otherGeospatial":"Pennsylvania 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Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":751542,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216090,"text":"70216090 - 2019 - New approach to assessing age uncertainties – The 2300-year varve chronology from Eklutna Lake, Alaska (USA)","interactions":[],"lastModifiedDate":"2023-11-08T14:28:34.652988","indexId":"70216090","displayToPublicDate":"2018-11-19T10:49:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"New approach to assessing age uncertainties – The 2300-year varve chronology from Eklutna Lake, Alaska (USA)","docAbstract":"Developing robust chronological frameworks of lacustrine sediment is central to reconstructing past environmental changes. We present varve chronologies from five sites extending back 2300 years from Eklutna Lake, in the Chugach Mountains of south-central Alaska. The chronologies are built from image analysis of high-resolution photographs and CT scans of sediment cores. The age uncertainty of each record is tested by three methods. We first present varve chronologies from individual sites and reconcile the difference in varve delimitation from two observers. The varve chronologies from each site are then compared to each other using a series of marker beds that can be traced across the lake basin. Finally, using a new Bayesian probabilistic model, we develop age models that incorporate information regarding age uncertainty from the multiple-observer method and the age distribution of marker layers from multiple cores. To evaluate the accuracy of the Bayesian model output, we used seven radiocarbon ages from terrestrial macrofossils and four tephra layers traceable across the core sites. The major-element geochemistry of the tephra layers and their ages are presented here for the first time. The Bayesian age model offers a new approach to quantifying age uncertainty in inter-correlated cores of varved sediment.
Low survival rates of Chinook salmon (Oncorhynchus tshawytscha) smolts in California’s Central Valley have been attributed to multiple biological and physical factors, but it is not clear which factors have the largest impact. We used 5 years of acoustic telemetry data for 1709 late-fall Chinook salmon smolts to evaluate the effect of habitat- and predation-related covariates on outmigration survival through the Sacramento River. Using a Cormack–Jolly–Seber mark–recapture model, we estimated survival rates both as a function of covariates (covariate model) and as a function of river location and release year (spatial–temporal model). Our covariate model was overwhelmingly supported as the preferred model based on model selection criteria, suggesting the covariates adequately replicated spatial and temporal patterns in smolt survival. The covariates in the selected model included individual fish covariates, habitat-specific covariates, and temporally variable physical conditions. The most important covariate affecting salmon survival was flow. We describe the importance of these parameters in the context of juvenile salmon predation risk and suggest that additional research on predator distribution and density could improve model estimates.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0212","usgsCitation":"Henderson, M., Iglesias, I.S., Michel, C.J., Ammann, A.J., and Huff, D.D., 2019, Estimating spatial–temporal differences in Chinook salmon outmigration survival with habitat- and predation-related covariates: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 9, p. 1549-1561, https://doi.org/10.1139/cjfas-2018-0212.","productDescription":"13 p.","startPage":"1549","endPage":"1561","ipdsId":"IP-097049","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":501022,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/94927","text":"External Repository"},{"id":395356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.3,\n 38.70265930723801\n ],\n [\n -120.9375,\n 38.70265930723801\n ],\n [\n -120.9375,\n 40.44694705960048\n ],\n [\n -122.3,\n 40.44694705960048\n ],\n [\n -122.3,\n 38.70265930723801\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":832954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iglesias, Ilysa S.","contributorId":274387,"corporation":false,"usgs":false,"family":"Iglesias","given":"Ilysa","email":"","middleInitial":"S.","affiliations":[{"id":56613,"text":"uc sc","active":true,"usgs":false}],"preferred":false,"id":832955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michel, Cyril J.","contributorId":207096,"corporation":false,"usgs":false,"family":"Michel","given":"Cyril","email":"","middleInitial":"J.","affiliations":[{"id":37452,"text":"National Marine Fisheries Service, Southwest Fisheries Science Center, 110 Shaffer Rd., Santa Cruz, CA 95060","active":true,"usgs":false}],"preferred":false,"id":832956,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ammann, Arnold J.","contributorId":207095,"corporation":false,"usgs":false,"family":"Ammann","given":"Arnold","email":"","middleInitial":"J.","affiliations":[{"id":37452,"text":"National Marine Fisheries Service, Southwest Fisheries Science Center, 110 Shaffer Rd., Santa Cruz, CA 95060","active":true,"usgs":false}],"preferred":false,"id":832957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huff, David D.","contributorId":171694,"corporation":false,"usgs":false,"family":"Huff","given":"David","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":832958,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215783,"text":"70215783 - 2019 - A reinterpretation of “Homing pigeons’ flight over and under low stratus” based on atmospheric propagation modeling of infrasonic navigational cues","interactions":[],"lastModifiedDate":"2020-10-29T14:05:55.372525","indexId":"70215783","displayToPublicDate":"2018-11-14T09:03:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2225,"text":"Journal of Comparative Physiology A","active":true,"publicationSubtype":{"id":10}},"title":"A reinterpretation of “Homing pigeons’ flight over and under low stratus” based on atmospheric propagation modeling of infrasonic navigational cues","docAbstract":"Pigeons flying above temperature inversion and related low-stratus layers appear to lack important navigational cues, and a reinterpretation of Wagner’s 1978 study suggests that these cues are low-frequency acoustic signals (infrasound). Wagner released homing pigeons above opaque stratus over the Swiss Plateau to determine whether they could locate their loft beneath it. Birds above the clouds appeared lost, while those that descended beneath them returned home directly. Atmospheric propagation modeling of infrasonic waves virtually transmitted from the loft area shows that these signals would have been ducted beneath the inversion layer, and would not have reached the release sites above it. The absence of homeward infrasonic cues above temperature inversions could explain the disorientation of Wagner’s birds, especially if such signals are the predominant cues used by pigeons to home. The possible generation of infrasonic navigational signals in the loft area and recent queries concerning the infrasound navigational “map” hypothesis are also discussed.
In managing invasive species, land managers and policy makers need information to help allocate scarce resources as efficiently and effectively as possible. Decisions regarding treatment methods, locations, effort, and timing can be informed by the integration of landscape simulation models with economic tools. State and transition simulation models align with conceptual models of ecosystem change often used by practitioners and have been used to characterize the potential consequences of invasions. Outputs of these simulations are typically summarized to describe landscape changes (e.g., infested area), which may provide sufficient information for mangers to make informed decisions. However, it is sometimes helpful or necessary to go a step further to consider the social and economic values associated with treating (or not treating) invasions. Here, we describe when and how to integrate state and transition simulation models with economic and decision tools to aid in the control of emerging and established populations of invasive species. The paper provides an overview of three types of questions that can be addressed: 1) how big is the problem? 2) which management strategy is most appropriate? and 3) what are key sources of uncertainty? For each question, we describe aspects that can be addressed by landscape simulation models alone, and outstanding questions that can be evaluated by integrating economic and decision tools. Through a series of example applications from the literature, we reinforce how the integration of these tools, and the interdisciplinary perspective such an integration requires, can increase relevance and utility of modeling efforts for resource managers and decision makers.
","language":"English","publisher":"InvasivesNet","doi":"10.3391/mbi.2019.10.1.02","usgsCitation":"Cullinane Thomas, C., Sofaer, H., Cline, S.A., and Jarnevich, C.S., 2019, Integrating landscape simulation models with economic and decision tools for invasive species control : Management of Biological Invasions, v. 10, no. 1, p. 6-22, https://doi.org/10.3391/mbi.2019.10.1.02.","productDescription":"17 p.","startPage":"6","endPage":"22","ipdsId":"IP-094494","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468058,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2019.10.1.02","text":"Publisher Index Page"},{"id":363413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cullinane Thomas, Catherine 0000-0001-8168-1271 ccullinanethomas@usgs.gov","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":215221,"corporation":false,"usgs":true,"family":"Cullinane Thomas","given":"Catherine","email":"ccullinanethomas@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen 0000-0002-9450-5223 hsofaer@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":169118,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"hsofaer@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":761850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cline, Sarah A.","contributorId":203552,"corporation":false,"usgs":false,"family":"Cline","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":36651,"text":"Department of the Interior Office of Policy Analysis","active":true,"usgs":false}],"preferred":false,"id":761851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761852,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200789,"text":"70200789 - 2019 - Effects of prescribed fire on San Francisco gartersnake survival and movement","interactions":[],"lastModifiedDate":"2019-01-28T08:52:55","indexId":"70200789","displayToPublicDate":"2018-11-01T17:06:22","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":"Effects of prescribed fire on San Francisco gartersnake survival and movement","docAbstract":"The application of fire is prescribed for management of habitats for many plant and animal communities, but its effects on herpetofauna are diverse and remain poorly understood. To date no studies have examined the effects of prescribed fire on endangered San Francisco gartersnake (Thamnophis sirtalis tetrataenia) populations, despite a call for prescribed fire in the recovery plan for the species. We used multi‐state capture‐mark‐recapture models to assess whether effects of prescribed fire were ephemeral, occurring only during the year of the fire, or persisted for 3 years following the fire, and to estimate the effects of prescribed fire on demographic parameters of San Francisco gartersnakes inhabiting California coastal prairie. Ephemeral fire effects were better supported for transitions (movement) between burned and unburned areas, but persistent fire effects were better supported for apparent survival and recapture probabilities. Movement between burned and unburned areas decreased during the year of the fire, but transition rates from burned to unburned areas decreased less than transition rates from unburned to burned areas in the year of the fire. Apparent survival probabilities increased in the unburned areas following the fire but were largely unchanged, though more uncertain, in burned areas following the fire. Recapture probabilities decreased site‐wide following the fire, though the decrease was greater in burned areas than in unburned areas. Although imprecise, our estimates of the effects of prescribed fire suggest that under the conditions of this fire (low‐intensity fall burn applied to a small area within a robust population and followed by wet weather), prescribed fire is a viable management tool for maintaining open habitats where San Francisco gartersnakes occur.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21585","usgsCitation":"Halstead, B., Thompson, M.E., Amarello, M., Smith, J.J., Wylie, G.D., Routman, E.J., and Casazza, M.L., 2019, Effects of prescribed fire on San Francisco gartersnake survival and movement: Journal of Wildlife Management, v. 83, no. 1, p. 231-240, https://doi.org/10.1002/jwmg.21585.","productDescription":"10 p.","startPage":"231","endPage":"240","ipdsId":"IP-060673","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468060,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21585","text":"Publisher Index Page"},{"id":437618,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73F4NJK","text":"USGS data release","linkHelpText":"Coastal California San Francisco Gartersnake Capture-Mark-Recapture Data (2008-2013)"},{"id":359092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"83","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-23","publicationStatus":"PW","scienceBaseUri":"5c10a8fde4b034bf6a7e4ece","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":750515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Michelle E.","contributorId":210341,"corporation":false,"usgs":false,"family":"Thompson","given":"Michelle","email":"","middleInitial":"E.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":750518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amarello, Melissa","contributorId":210342,"corporation":false,"usgs":false,"family":"Amarello","given":"Melissa","email":"","affiliations":[{"id":38103,"text":"USGS Western Ecological Research Center","active":true,"usgs":false}],"preferred":false,"id":750519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Jeffrey J.","contributorId":210344,"corporation":false,"usgs":false,"family":"Smith","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[{"id":38103,"text":"USGS Western Ecological Research Center","active":true,"usgs":false}],"preferred":false,"id":750521,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wylie, Glenn D. 0000-0002-7061-6658 glenn_wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-6658","contributorId":3052,"corporation":false,"usgs":true,"family":"Wylie","given":"Glenn","email":"glenn_wylie@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":750516,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Routman, Eric J.","contributorId":210343,"corporation":false,"usgs":false,"family":"Routman","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":750520,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":750517,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204464,"text":"70204464 - 2019 - Climate change implications for irrigation and groundwater in the Republican River Basin, U.S.A.","interactions":[],"lastModifiedDate":"2019-07-25T11:27:01","indexId":"70204464","displayToPublicDate":"2018-11-01T11:25:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1246,"text":"Climate Change","onlineIssn":"1573-1480","printIssn":"0165-0009","active":true,"publicationSubtype":{"id":10}},"title":"Climate change implications for irrigation and groundwater in the Republican River Basin, U.S.A.","docAbstract":"This study investigates the influence of climate change on groundwater availability, and thereby, irrigation across political boundaries within the United States’ High Plains aquifer. A regression model is developed to predict changes in irrigation according to predicted changes in precipitation and temperature from a downscaled dataset of 32 general circulation models (GCMs). Precipitation recharge changes are calculated with precipitation-recharge curves developed for prognostic representations of precipitation across the Nebraska-Colorado-Kansas area and within the Republican River Basin focal landscape. Irrigation-recharge changes are scaled with changes in irrigation. The groundwater responses to climate forcings are then simulated under new pumping and recharge rates using a MODFLOW groundwater flow model. Results show that groundwater pumping and recharge both will increase and that the effects of groundwater pumping will overshadow those from natural fluctuations. Groundwater levels will decline more in areas with irrigation-driven decreasing trends in the baseline. The methodologies and predictions of this study can inform long-term water planning and the design of management strategies that help avoid and resolve water-related conflicts, enabling irrigation sustainability.","language":"English","publisher":"Springer","doi":"10.1007/s10584-018-2278-z","usgsCitation":"Ou, G., Munoz-Arriola, F., Uden, D., Martin, D.R., Allen, C.R., and Shank, N., 2019, Climate change implications for irrigation and groundwater in the Republican River Basin, U.S.A.: Climate Change, v. 151, no. 2, p. 303-316, https://doi.org/10.1007/s10584-018-2278-z.","productDescription":"14 p.","startPage":"303","endPage":"316","ipdsId":"IP-100829","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10584-018-2278-z","text":"Publisher Index Page"},{"id":365937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, Nebraska","otherGeospatial":"Republican River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.9873046875,\n 40.04443758460856\n ],\n [\n -100.37109375,\n 41.29431726315258\n ],\n [\n -102.216796875,\n 41.02964338716638\n ],\n [\n -103.4033203125,\n 40.245991504199026\n ],\n [\n -103.84277343749999,\n 39.30029918615029\n ],\n [\n -102.63427734374999,\n 38.61687046392973\n ],\n [\n -100.04150390625,\n 39.317300373271024\n ],\n [\n -98.7890625,\n 39.7240885773337\n ],\n [\n -96.9873046875,\n 40.04443758460856\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"151","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Ou, Gengxin","contributorId":217537,"corporation":false,"usgs":false,"family":"Ou","given":"Gengxin","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":767024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munoz-Arriola, F.","contributorId":217538,"corporation":false,"usgs":false,"family":"Munoz-Arriola","given":"F.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":767025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Uden, D. R.","contributorId":217539,"corporation":false,"usgs":false,"family":"Uden","given":"D. R.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":767026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, D. R.","contributorId":171766,"corporation":false,"usgs":false,"family":"Martin","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":767027,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":767023,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shank, N.","contributorId":217540,"corporation":false,"usgs":false,"family":"Shank","given":"N.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":767028,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70204140,"text":"70204140 - 2019 - Effectiveness of shallow water habitat remediation for improving fish habitat in a large temperate river","interactions":[],"lastModifiedDate":"2019-07-10T09:23:40","indexId":"70204140","displayToPublicDate":"2018-11-01T09:46:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Effectiveness of shallow water habitat remediation for improving fish habitat in a large temperate river","docAbstract":"Loss of shallow water riparian zones in the St. Clair River has reduced availability of nursery areas and refuge for fishes. To remediate habitat losses and provide fish nursery areas, five remediation projects were carried out along the river’s United States bank from 2012 to 2014, replacing seawalls with sloping banks and adding in-stream structure (e.g., root wads and boulders). Project evaluation is necessary to determine success, however there is no standard sampling protocol for shallow habitat in large rivers, especially when both adults and juvenile fishes should be targeted. Therefore, to assess remediation effectiveness and suggest appropriate sampling techniques for large river shorelines, we employed a multi-gear sampling strategy targeting multiple fish species and life history stages at five shoreline remediation and four control sites. We collected juvenile fishes with minnow traps and backpack electrofishing and adult fishes with gillnets. Poisson models were used to evaluate catch per unit effort (CPUE) differences between remediation and control sites for species of management priority (e.g., game fishes and rare species) and taxonomic groups. Model estimates were then used to calculate proportional abundances and compare species composition between site types. Results indicated that electrofishing CPUEs of Darters, mottled sculpin Cottus bairdi, rare threatened and endangered species, and juvenile and adult Centrarchidae were higher at remediation sites than at control sites. Additionally, juvenile Centrarchidae and mottled sculpin had a higher proportional abundance in electrofishing collections at remediation sites than at control sites. In contrast, CPUEs and proportional abundances were similar for all taxonomic and management priority groups of fish collected in minnow traps and gillnets. Electrofishing captured more species and more individuals and is therefore a valuable sampling technique for large river shorelines. Nevertheless, addition of minnow traps and gillnets allowed for a more comprehensive assessment of fish assemblages. Overall, this multi-faceted survey approach demonstrates that shoreline remediation projects were beneficial to recreational and ecologically important species in the St. Clair River.