{"pageNumber":"229","pageRowStart":"5700","pageSize":"25","recordCount":184717,"records":[{"id":70250986,"text":"70250986 - 2023 - Marginal value analysis reveals shifting importance of migration habitat for waterfowl under a changing climate","interactions":[],"lastModifiedDate":"2024-01-18T11:47:53.770787","indexId":"70250986","displayToPublicDate":"2023-11-09T05:46:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Marginal value analysis reveals shifting importance of migration habitat for waterfowl under a changing climate","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Migratory waterfowl are an important resource for consumptive and non-consumptive users alike and provide tremendous economic value in North America. These birds rely on a complex matrix of public and private land for forage and roosting during migration and wintering periods, and substantial conservation effort focuses on increasing the amount and quality of target habitat. Yet, the value of habitat is a function not only of a site's resources but also of its geographic position and weather. To quantify this value, we used a continental-scale energetics-based model of daily dabbling duck movement to assess the marginal value of lands across the contiguous United States during the non-breeding period (September to May). We examined effects of eliminating each habitat node (32 × 32 km) in both a particularly cold and a particularly warm winter, asking which nodes had the largest effect on survival. The marginal value of habitat nodes for migrating dabbling ducks was a function of forage and roosting habitat but, more importantly, of geography (especially latitude and region). Irrespective of weather, nodes in the Southeast, central East Coast, and California made the largest positive contributions to survival. Conversely, nodes in the Midwest, Northeast, Florida, and the Pacific Northwest had consistent negative effects. Effects (positive and negative) of more northerly nodes occurred in late fall or early spring when climate was often severe and was most variable. Importance and effects of many nodes varied considerably between a cold and a warm winter. Much of the Midwest and central Great Plains benefited duck survival in a warm winter, and projected future warming may improve the value of lands in these regions, including many National Wildlife Refuges, for migrating dabbling ducks. Our results highlight the geographic variability in habitat value, as well as shifts that may occur in these values due to climate change.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10632","usgsCitation":"Burner, R.C., Golas, B.D., Aagaard, K.J., Lonsdorf, E.V., and Thogmartin, W.E., 2023, Marginal value analysis reveals shifting importance of migration habitat for waterfowl under a changing climate: Ecology and Evolution, v. 13, no. 11, e10632, 25 p., https://doi.org/10.1002/ece3.10632.","productDescription":"e10632, 25 p.","ipdsId":"IP-145212","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":441655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10632","text":"Publisher Index Page"},{"id":424552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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0000-0002-7314-9506","orcid":"https://orcid.org/0000-0002-7314-9506","contributorId":304152,"corporation":false,"usgs":true,"family":"Burner","given":"Ryan","email":"","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":892664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golas, Benjamin Donald 0000-0003-0568-6702","orcid":"https://orcid.org/0000-0003-0568-6702","contributorId":333396,"corporation":false,"usgs":true,"family":"Golas","given":"Benjamin","email":"","middleInitial":"Donald","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":892665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aagaard, Kevin J.","contributorId":302397,"corporation":false,"usgs":false,"family":"Aagaard","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":892666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lonsdorf, Eric V.","contributorId":149495,"corporation":false,"usgs":false,"family":"Lonsdorf","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":892667,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":892668,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70249963,"text":"tm5D5 - 2023 - Creating oriented and precisely sectioned mineral mounts for in situ chemical analyses—An example using olivine for diffusion chronometry studies","interactions":[],"lastModifiedDate":"2024-01-12T18:31:49.724753","indexId":"tm5D5","displayToPublicDate":"2023-11-08T12:29:39","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"5-D5","displayTitle":"Creating Oriented and Precisely Sectioned Mineral Mounts for In Situ Chemical Analyses—An Example Using Olivine for Diffusion Chronometry Studies","title":"Creating oriented and precisely sectioned mineral mounts for in situ chemical analyses—An example using olivine for diffusion chronometry studies","docAbstract":"<p>Diffusion chronometry is now a widely applied methodology for determining the rates and timescales of geologic processes from the chemical zoning observed in minerals. Despite the popularity of the method, several challenges still remain during its application, including: (1) the random sectioning of minerals either in thin sections or grain mounts in which both off-center and oblique sections contribute substantial uncertainty to modeled timescales and (2) diffusion anisotropy needs to be accounted for in models, which generally requires determining the principal crystallographic axes of the mineral using electron backscatter diffraction, a technique that is both challenging and limiting because few scanning electron microscopes have an electron backscatter detector. This guide developed by the U.S. Geological Survey focuses on a step-by-step methodology for mounting individually oriented minerals that are sectioned through their cores prior to polishing for analytical work. Using this technique, one can significantly reduce the uncertainties associated with off-center sections and minimize or completely remove the need for determining crystallographic orientation via electron backscatter diffraction analyses. This report is presented as a guide for using the technique on olivine crystals but can be applied to any minerals that can be extracted for analysis. Two variations of the methodology are included here: (1) The individual crystal method that entails mounting individually sectioned single crystals and crystal groups and (2) the whole mount method in which multiple single crystals or crystal clusters are mounted and sectioned at the same time.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm5D5","programNote":"Volcano Hazards Program","usgsCitation":"Lynn, K.J., and DeSmither, L.G., 2023, Creating oriented and precisely sectioned mineral mounts for in situ chemical analyses—An example using olivine for diffusion chronometry studies: U.S. Geological Survey Techniques and Methods, book 5, chap. D5, 36 p., https://doi.org/10.3133/tm5D5.","productDescription":"ix, 36 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-142373","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":422457,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/05/d5/covrthb.jpg"},{"id":422458,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/05/d5/tm5d5.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":422459,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/05/d5/tm5d5.xml"},{"id":422460,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/05/d5/images"},{"id":422461,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm5D5/full"}],"contact":"<p><a data-mce-href=\"https://www.usgs.gov/centers/volcano-science-center/connect\" href=\"https://www.usgs.gov/centers/volcano-science-center/connect\" target=\"_blank\" rel=\"noopener\">Director</a>,&nbsp;<br><a href=\"https://www.usgs.gov/centers/volcano-science-center\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/volcano-science-center\"></a><a href=\"https://www.usgs.gov/centers/volcano-science-center\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/volcano-science-center\">Volcano Science Center</a><br><a data-mce-href=\"https://www.usgs.gov/\" href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>1300 SE Cardinal Court<br>Vancouver, WA 38683</p>","tableOfContents":"<ul><li>Preface</li><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Sample Preparation and Picking</li><li>Orienting, Sectioning, and Mounting Individual Single Crystals or Crystal Groups (Individual Crystal Method)</li><li>Orienting, Mounting, and Sectioning Multiple Single Crystals or Crystal Clusters (Whole Mount Method)</li><li>Proof of Concept</li><li>Method Summary</li><li>References Cited</li><li>Appendix 1. Electron Microprobe Analyses of Standard San Carlos Olivine Reported as Weight Percent Oxides</li><li>Appendix 2. Electron Microprobe Profiles of Olivine Samples</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-11-08","noUsgsAuthors":false,"publicationDate":"2023-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":887825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Desmither, Liliana G. 0000-0002-2422-3490","orcid":"https://orcid.org/0000-0002-2422-3490","contributorId":215610,"corporation":false,"usgs":true,"family":"Desmither","given":"Liliana","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":887826,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70256441,"text":"70256441 - 2023 - Effects of landcover on mesocarnivore density and detection rate along an urban to rural gradient","interactions":[],"lastModifiedDate":"2024-08-02T15:31:51.494526","indexId":"70256441","displayToPublicDate":"2023-11-08T10:28:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Effects of landcover on mesocarnivore density and detection rate along an urban to rural gradient","docAbstract":"<p><span>Human development has major implications for wildlife populations. Urban-exploiter species can benefit from human subsidized resources, whereas urban-avoider species can vanish from wildlife communities in highly developed areas. Therefore, understanding how the density of different species varies in response to landcover changes associated with human development can provide important insight into how wildlife communities are likely to change and provide a starting point for predicting the consequences of those changes. Here, we estimated the population density of five common mesocarnivore species (coyote (</span><span><i>Canis latrans</i></span><span>), bobcat (</span><i>Lynx rufus</i><span>),&nbsp;red fox&nbsp;(</span><i>Vulpes vulpes</i><span>), raccoon (</span><span><i>Procyon lotor</i></span><span>), and Virginia opossum (</span><i>Didelphis virginiana)</i><span>) at 12 study sites along an urban to rural gradient in the greater Fayetteville Area, Northwest Arkansas, USA between November 2021, and March 2022. At each study site, we applied the Random Encounter Model (REM) to data from&nbsp;camera traps&nbsp;to calculate the density of five focal species. Coyote density ranged from 0.5 to 0.93 individuals/km</span><sup>2</sup><span>. Raccoon density ranged from 0.19 to 20.25 individuals/km</span><sup>2</sup><span>. Bobcat density ranged from 0 to 1.06 individuals/km</span><sup>2</sup><span>. Opossum density ranged from 0 to 3.43 individuals/km</span><sup>2</sup><span>. Red fox density ranged from 0 to 0.10 individuals/km</span><sup>2</sup><span>. Coyote and raccoon density showed a positive relationship with anthropogenic noise. Opossum density increased with HUD. Red Fox and bobcat density showed a negative relationship with forest area and a positive relationship with distance to water respectively, however confidence intervals for both species overlapped zero. The density estimates we report based on camera trap data of unmarked animals were consistent with reports from the literature for these same species derived from traditional methods, providing additional support to the REM as a viable, non-invasive method to calculate density of unmarked species. Our second analysis consisted of taking camera level density estimates and treating them as detection rates corrected for camera viewshed and animal movement. Coyote and raccoon detection rate showed a positive relationship with anthropogenic noise. Red Fox detection rate was positively related to developed&nbsp;open space, and negatively related to distance to water. Similarly to red fox, opossums detection rate was higher in areas with more developed open space. We found no evidence that bobcat density or detection rate varied with any of the landcover or anthropogenic variables we measured.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2023.e02716","usgsCitation":"McTigue, L., and DeGregorio, B.A., 2023, Effects of landcover on mesocarnivore density and detection rate along an urban to rural gradient: Global Ecology and Conservation, v. 48, e02716, 14 p., https://doi.org/10.1016/j.gecco.2023.e02716.","productDescription":"e02716, 14 p.","ipdsId":"IP-149643","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441657,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2023.e02716","text":"Publisher Index Page"},{"id":432148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","city":"Fayetteville","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -94.703264661285,\n              36.581012567484365\n            ],\n            [\n              -94.703264661285,\n              35.69179592709919\n            ],\n            [\n              -93.38479477781208,\n              35.69179592709919\n            ],\n            [\n              -93.38479477781208,\n              36.581012567484365\n            ],\n            [\n              -94.703264661285,\n              36.581012567484365\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McTigue, Leah","contributorId":310420,"corporation":false,"usgs":false,"family":"McTigue","given":"Leah","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907389,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70250113,"text":"70250113 - 2023 - Shifted sediment-transport regimes by climate change and amplified hydrological variability in cryosphere-fed rivers","interactions":[],"lastModifiedDate":"2023-11-20T15:15:03.789762","indexId":"70250113","displayToPublicDate":"2023-11-08T09:10:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Shifted sediment-transport regimes by climate change and amplified hydrological variability in cryosphere-fed rivers","docAbstract":"<p><span>Climate change affects cryosphere-fed rivers and alters seasonal sediment dynamics, affecting cyclical fluvial material supply and year-round water-food-energy provisions to downstream communities. Here, we demonstrate seasonal sediment-transport regime shifts from the 1960s to 2000s in four cryosphere-fed rivers characterized by glacial, nival, pluvial, and mixed regimes, respectively. Spring sees a shift toward pluvial-dominated sediment transport due to less snowmelt and more erosive rainfall. Summer is characterized by intensified glacier meltwater pulses and pluvial events that exceptionally increase sediment fluxes. Our study highlights that the increases in hydroclimatic extremes and cryosphere degradation lead to amplified variability in fluvial fluxes and higher summer sediment peaks, which can threaten downstream river infrastructure safety and ecosystems and worsen glacial/pluvial floods. We further offer a monthly-scale sediment-availability-transport model that can reproduce such regime shifts and thus help facilitate sustainable reservoir operation and river management in wider cryospheric regions under future climate and hydrological change.</span></p>","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.adi5019","usgsCitation":"Zhang, T., Li, D., East, A.E., Kettner, A.J., Best, J., Ni, J., and Lu, X., 2023, Shifted sediment-transport regimes by climate change and amplified hydrological variability in cryosphere-fed rivers: Science Advances, v. 9, no. 45, eadi5019, 12 p., https://doi.org/10.1126/sciadv.adi5019.","productDescription":"eadi5019, 12 p.","ipdsId":"IP-147639","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":441660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adi5019","text":"Publisher Index Page"},{"id":422725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"45","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Tinghu","contributorId":210005,"corporation":false,"usgs":false,"family":"Zhang","given":"Tinghu","email":"","affiliations":[],"preferred":false,"id":888409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Dongfeng","contributorId":297068,"corporation":false,"usgs":false,"family":"Li","given":"Dongfeng","email":"","affiliations":[{"id":64287,"text":"National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":888410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":888411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kettner, Albert J.","contributorId":331669,"corporation":false,"usgs":false,"family":"Kettner","given":"Albert","email":"","middleInitial":"J.","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":888412,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Best, James L.","contributorId":331670,"corporation":false,"usgs":false,"family":"Best","given":"James L.","affiliations":[{"id":35161,"text":"University of Illinois, Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":888413,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ni, Jinren","contributorId":331671,"corporation":false,"usgs":false,"family":"Ni","given":"Jinren","email":"","affiliations":[{"id":79261,"text":"Peking University, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":888414,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lu, Xixi","contributorId":298889,"corporation":false,"usgs":false,"family":"Lu","given":"Xixi","email":"","affiliations":[{"id":64287,"text":"National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":888415,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70250105,"text":"70250105 - 2023 - Alternative lifestyles: A plague persistence hypothesis","interactions":[],"lastModifiedDate":"2023-11-20T14:52:30.594993","indexId":"70250105","displayToPublicDate":"2023-11-08T08:49:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Alternative lifestyles: A plague persistence hypothesis","docAbstract":"<p><span>Several explanations have been posited for how the plague bacterium (</span><i>Yersinia pestis</i><span>) reemerges during sylvatic cycles within the same foci over many years, and often without direct evidence of host die-offs. One prevalent view is that transmission-optimized&nbsp;</span><i>Y. pestis</i><span>&nbsp;bacteria, exhibiting epizootic/enzootic behavior, almost continually replicate and survive through repeated, linked, host-centered propagation events. These bacteria, we will refer to as “</span><i>r-pestis</i><span>” type ecotype(s), represent a limited number of phenotypic lineages exhibiting optimal transmissibility and high rates of reproduction. These attributes, it is thought, assure their durability through time. For continuous&nbsp;</span><i>r-pestis</i><span>&nbsp;type expansions to be successful, adequate numbers of fleas and hosts must become infected to produce massive numbers of bacteria. In the process, host and flea numbers decline as they succumb to plague. Here we hypothesize that&nbsp;</span><i>r-pestis</i><span>&nbsp;population expansions seed the environment and confront a unique, highly competitive local milieu, where natural selection favors new ecotypes that incorporate a range of emergent adaptive survival strategies. These newly adapted survivors we recognize as a range of “</span><i>K</i><span>-</span><i>pestis</i><span>” ecotypes with greater durability and lower reproduction rates. These emergent&nbsp;</span><i>K</i><span>-</span><i>pestis</i><span>&nbsp;forms may arise in succession or coexist for varying periods of time with&nbsp;</span><i>r-pestis</i><span>&nbsp;ecotypes, and with other&nbsp;</span><i>K</i><span>-</span><i>pestis</i><span>&nbsp;ecotypes. Among&nbsp;</span><i>K-pestis</i><span>&nbsp;ecotypes, we hypothesize that through adaptive radiations, some persist within flea life stages, soil, organic waste, amoebae, plants, carcasses, hosts, or within niches yet to be characterized. In some settings, after a long quiet period, when favorable,&nbsp;</span><i>K-pestis</i><span>&nbsp;bacteria may trigger a singular event where an&nbsp;</span><i>r-pestis</i><span>&nbsp;transmission stream emerges precipitating another enzootic/epizootic progression. If this hypothesis withstands rigorous testing, then&nbsp;</span><i>Y. pestis</i><span>&nbsp;might represent an even more formidable, enduring, and adaptable foe, where unforeseen local events could trigger new epidemic and epizootic/enzootic events threatening humans and populations of other mammals, including those of conservation concern.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4673","usgsCitation":"Wimsatt, J., Eads, D.A., Matchett, M.R., and Biggins, D.E., 2023, Alternative lifestyles: A plague persistence hypothesis: Ecosphere, v. 14, e4673, 20 p., https://doi.org/10.1002/ecs2.4673.","productDescription":"e4673, 20 p.","ipdsId":"IP-135732","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":441662,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4673","text":"Publisher Index Page"},{"id":422722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2023-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Wimsatt, Jeffrey","contributorId":173421,"corporation":false,"usgs":false,"family":"Wimsatt","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":888368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":888369,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matchett, Marc R.","contributorId":193409,"corporation":false,"usgs":false,"family":"Matchett","given":"Marc","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":888370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":888371,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70250689,"text":"70250689 - 2023 - Response of lake metabolism to catchment inputs inferred using high-frequency lake and stream data from across the northern hemisphere","interactions":[],"lastModifiedDate":"2023-12-27T12:49:16.223157","indexId":"70250689","displayToPublicDate":"2023-11-08T06:46:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7120,"text":"Limnology & Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Response of lake metabolism to catchment inputs inferred using high-frequency lake and stream data from across the northern hemisphere","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>In lakes, the rates of gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) are often controlled by resource availability. Herein, we explore how catchment vs. within lake predictors of metabolism compare using data from 16 lakes spanning 39°N to 64°N, a range of inflowing streams, and trophic status. For each lake, we combined stream loads of dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP) with lake DOC, TN, and TP concentrations and high frequency<span>&nbsp;</span><i>in situ</i><span>&nbsp;</span>monitoring of dissolved oxygen. We found that stream load stoichiometry indicated lake stoichiometry for C : N and C : P (<i>r</i><sup>2</sup> = 0.74 and<span>&nbsp;</span><i>r</i><sup>2</sup> = 0.84, respectively), but not for N : P (<i>r</i><sup>2</sup> = 0.04). As we found a strong positive correlation between TN and TP, we only used TP in our statistical models. For the catchment model, GPP and R were best predicted by DOC load, TP load, and load N : P (<i>R</i><sup>2</sup> = 0.85 and<span>&nbsp;</span><i>R</i><sup>2</sup> = 0.82, respectively). For the lake model, GPP and R were best predicted by TP concentrations (<i>R</i><sup>2</sup> = 0.86 and<span>&nbsp;</span><i>R</i><sup>2</sup> = 0.67, respectively). The inclusion of N : P in the catchment model, but not the lake model, suggests that both N and P regulate metabolism and that organisms may be responding more strongly to catchment inputs than lake resources. Our models predicted NEP poorly, though it is unclear why. Overall, our work stresses the importance of characterizing lake catchment loads to predict metabolic rates, a result that may be particularly important in catchments experiencing changing hydrologic regimes related to global environmental change.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/lno.12449","usgsCitation":"Corman, J.R., Zwart, J.A., Klug, J., Bruesewitz, D.A., de Eyto, E., Klaus, M., Knoll, L.B., Rusak, J.A., Vanni, M.J., Alfonso, M.B., Fernandez, R.L., Yao, H., Austnes, K., Couture, R., de Wit, H.A., Karlsson, J., and Laas, A., 2023, Response of lake metabolism to catchment inputs inferred using high-frequency lake and stream data from across the northern hemisphere: Limnology & Oceanography, v. 68, no. 12, p. 2617-2631, https://doi.org/10.1002/lno.12449.","productDescription":"15 p.","startPage":"2617","endPage":"2631","ipdsId":"IP-148966","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":441665,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.12449","text":"Publisher Index Page"},{"id":423902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"68","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Corman, Jessica R.","contributorId":316647,"corporation":false,"usgs":false,"family":"Corman","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":68662,"text":"University of Nebraska-Lincoln, School of Natural Resources, Lincoln, NE 68583","active":true,"usgs":false}],"preferred":false,"id":890980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":890981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klug, Jennifer","contributorId":194475,"corporation":false,"usgs":false,"family":"Klug","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":890982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bruesewitz, Denise A 0000-0001-6108-5181","orcid":"https://orcid.org/0000-0001-6108-5181","contributorId":332790,"corporation":false,"usgs":false,"family":"Bruesewitz","given":"Denise","email":"","middleInitial":"A","affiliations":[{"id":51887,"text":"Colby College","active":true,"usgs":false}],"preferred":false,"id":890983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Eyto, Elvira","contributorId":150319,"corporation":false,"usgs":false,"family":"de Eyto","given":"Elvira","affiliations":[{"id":17992,"text":"Marine Institute","active":true,"usgs":false}],"preferred":false,"id":890984,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klaus, Marcus 0000-0003-0747-3524","orcid":"https://orcid.org/0000-0003-0747-3524","contributorId":332791,"corporation":false,"usgs":false,"family":"Klaus","given":"Marcus","email":"","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":890985,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Knoll, Lesley B. 0000-0003-0347-5979","orcid":"https://orcid.org/0000-0003-0347-5979","contributorId":194463,"corporation":false,"usgs":false,"family":"Knoll","given":"Lesley","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":890986,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rusak, James A. 0000-0002-4939-6478","orcid":"https://orcid.org/0000-0002-4939-6478","contributorId":150301,"corporation":false,"usgs":false,"family":"Rusak","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":17970,"text":"Dorset Environmental Science Centre, Ontario Ministry of the Environment and Climate Change, Dorset, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":890987,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vanni, Michael J.","contributorId":204106,"corporation":false,"usgs":false,"family":"Vanni","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":36846,"text":"Department of Zoology, Miami University (Ohio)","active":true,"usgs":false}],"preferred":false,"id":890988,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Alfonso, Maria Belen 0000-0003-0543-8098","orcid":"https://orcid.org/0000-0003-0543-8098","contributorId":332794,"corporation":false,"usgs":false,"family":"Alfonso","given":"Maria","email":"","middleInitial":"Belen","affiliations":[{"id":41525,"text":"Kyushu University","active":true,"usgs":false}],"preferred":false,"id":890989,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fernandez, Rocio Luz 0000-0001-9996-8975","orcid":"https://orcid.org/0000-0001-9996-8975","contributorId":332797,"corporation":false,"usgs":false,"family":"Fernandez","given":"Rocio","email":"","middleInitial":"Luz","affiliations":[{"id":62895,"text":"National Scientific and Technical Research Council","active":true,"usgs":false}],"preferred":false,"id":890990,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Yao, Huaxia 0000-0001-5875-7215","orcid":"https://orcid.org/0000-0001-5875-7215","contributorId":261759,"corporation":false,"usgs":false,"family":"Yao","given":"Huaxia","email":"","affiliations":[{"id":52996,"text":"Dorset Environmental Science Centre","active":true,"usgs":false}],"preferred":false,"id":890991,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Austnes, Kari 0000-0003-2618-0698","orcid":"https://orcid.org/0000-0003-2618-0698","contributorId":332798,"corporation":false,"usgs":false,"family":"Austnes","given":"Kari","email":"","affiliations":[{"id":13695,"text":"Norwegian Institute for Water Research","active":true,"usgs":false}],"preferred":false,"id":890992,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Couture, Raoul-Marie","contributorId":297272,"corporation":false,"usgs":false,"family":"Couture","given":"Raoul-Marie","email":"","affiliations":[{"id":64337,"text":"Université Laval, Department of chemistry, Quebec, Canada","active":true,"usgs":false}],"preferred":false,"id":890993,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"de Wit, Heleen A. 0000-0001-5646-5390","orcid":"https://orcid.org/0000-0001-5646-5390","contributorId":332803,"corporation":false,"usgs":false,"family":"de Wit","given":"Heleen","email":"","middleInitial":"A.","affiliations":[{"id":13695,"text":"Norwegian Institute for Water Research","active":true,"usgs":false}],"preferred":false,"id":890994,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Karlsson, Jan","contributorId":139660,"corporation":false,"usgs":false,"family":"Karlsson","given":"Jan","email":"","affiliations":[{"id":12869,"text":"Dept. of Ecology and Environmental Science, Umeå University, Umeå, Sweden.","active":true,"usgs":false}],"preferred":false,"id":890995,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Laas, Alo 0000-0002-4801-0377","orcid":"https://orcid.org/0000-0002-4801-0377","contributorId":261753,"corporation":false,"usgs":false,"family":"Laas","given":"Alo","email":"","affiliations":[{"id":18000,"text":"Estonian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":890996,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70250501,"text":"70250501 - 2023 - Horizon scanning for potentially invasive non-native marine species to inform trans-boundary conservation management – Example of the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2023-12-14T12:52:20.253868","indexId":"70250501","displayToPublicDate":"2023-11-08T06:44:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Horizon scanning for potentially invasive non-native marine species to inform trans-boundary conservation management – Example of the northern Gulf of Mexico","docAbstract":"<div class=\"P-Article-Preview-Block\"><div class=\"P-Article-Preview-Block-Content\"><p data-obkms-id=\"C537FD2C-3231-4050-AE3F-B2A123FCB77F\">Prevention of non-native species introductions and establishment is essential to avoid adverse impacts of invasive species in marine environments. To identify potential new invasive species and inform non-native species management options for the northern Gulf of Mexico (Alabama, Mississippi, Louisiana, Texas), 138 marine species were risk screened for current and future climate conditions using the Aquatic Species Invasiveness Screening Kit. Species were risk-ranked as low, medium, high, and very high risk based on separate (calibrated) thresholds for fishes, tunicates, and invertebrates. In the basic screening, 15 fishes, two tunicates, and 26 invertebrates were classified as high or very high risk under current climate conditions. Whereas, under future climate conditions, 16 fishes, three tunicates, and 33 invertebrates were classified as high or very high risk. Very high risk species included: California scorpionfish<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"D8B2425E-36DC-42A1-9D96-6FE3B31CFFE8\" data-taxon-parsed-name=\"Scorpaena guttata\"><span class=\"genus\">Scorpaena</span>&nbsp;<span class=\"species\">guttata</span></span></span></i>, red scorpionfish<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"3981FA6B-FDB5-4198-AE5A-15917B30F073\" data-taxon-parsed-name=\"Scorpaena scrofa\"><span class=\"genus\">Scorpaena</span>&nbsp;<span class=\"species\">scrofa</span></span></span></i>, purple whelk<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"5F88CB09-65DA-420F-B3DF-C7F01E19EC12\" data-taxon-parsed-name=\"Rapana venosa\"><span class=\"genus\">Rapana</span>&nbsp;<span class=\"species\">venosa</span></span></span></i>, and Santo Domingo false mussel<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"96E17F1E-D5C3-4016-9482-B277263D0095\" data-taxon-parsed-name=\"Mytilopsis sallei\"><span class=\"genus\">Mytilopsis</span>&nbsp;<span class=\"species\">sallei</span></span></span></i><span>&nbsp;</span>under both current and future climates, with weedy scorpionfish<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"D7F0EFBE-721A-4D41-8AD9-1D457AD1F80E\" data-taxon-parsed-name=\"Rhinopias frondosa\"><span class=\"genus\">Rhinopias</span>&nbsp;<span class=\"species\">frondosa</span></span></span></i>, Papuan scorpionfish<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"1C8E6A14-9513-43A6-BE59-E2EB41189B86\" data-taxon-parsed-name=\"Scorpaenopsis papuensis\"><span class=\"genus\">Scorpaenopsis</span>&nbsp;<span class=\"species\">papuensis</span></span></span></i>, daggertooth pike conger<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"5BD4D093-5FEA-4299-B626-D903CAC2BB9B\" data-taxon-parsed-name=\"Muraenesox cinereus\"><span class=\"genus\">Muraenesox</span>&nbsp;<span class=\"species\">cinereus</span></span></span></i>, yellowfin scorpionfish<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"383C0496-25B7-40DA-A6C9-AFD2B46561F6\" data-taxon-parsed-name=\"Scorpaenopsis neglecta\"><span class=\"genus\">Scorpaenopsis</span>&nbsp;<span class=\"species\">neglecta</span></span></span></i>, tassled scorpionfish<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"A2A27373-9E1C-4E19-B198-9E12F7860C18\" data-taxon-parsed-name=\"Scorpaenopsis oxycephalus\"><span class=\"genus\">Scorpaenopsis</span>&nbsp;<span class=\"species\">oxycephalus</span></span></span></i>, brush-clawed shore crab<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"FB5867B4-CA0B-4A1A-80BF-85465698EEC3\" data-taxon-parsed-name=\"Hemigrapsus takanoi\"><span class=\"genus\">Hemigrapsus</span>&nbsp;<span class=\"species\">takanoi</span></span></span></i>, honeycomb oyster<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"50594E36-6B58-45AC-A4F7-9E8D0442EBAF\" data-taxon-parsed-name=\"Hyotissa hyotis\"><span class=\"genus\">Hyotissa</span>&nbsp;<span class=\"species\">hyotis</span></span></span></i>, carinate rock shell<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"A672A7AE-C6FB-47FD-A4C0-EAA98D35A77F\" data-taxon-parsed-name=\"Indothais lacera\"><span class=\"genus\">Indothais</span>&nbsp;<span class=\"species\">lacera</span></span></span></i>, and Asian green mussel<span>&nbsp;</span><i><span><span class=\"tn\" data-obkms-id=\"67311C47-F294-45FF-B04C-CCA0696050BA\" data-taxon-parsed-name=\"Perna viridis\"><span class=\"genus\">Perna</span>&nbsp;<span class=\"species\">viridis</span></span></span></i><span>&nbsp;</span>under climate change conditions only. This study provides evidence to inform trans-boundary management plans across the five Gulf of Mexico states to prevent, detect, and respond rapidly to new species arrivals.</p></div></div>","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/ai.2023.18.4.114182","usgsCitation":"O’Shaughnessy, K.A., Vilizzi, L., Daniel, W., McGarrity, M.E., Bauer, H., Hartman, L., Geiger, S., Sammarco, P., Kolian, S., Porter, S., Dutton, J., McClure, M.R., Norberg, M., Fogg, A., Lyons, T., Procopio, J., Bantista, L., Bennett, W., Wicksten, M., Reeves, D.B., Lively, J., Robinson, E.M., Brenner, J., Goy, J., Morgan-Olvera, A., Yunnie, A.L., and Copp, G.H., 2023, Horizon scanning for potentially invasive non-native marine species to inform trans-boundary conservation management – Example of the northern Gulf of Mexico: Aquatic Invasions, v. 18, no. 4, p. 415-453, https://doi.org/10.3391/ai.2023.18.4.114182.","productDescription":"39 p.","startPage":"415","endPage":"453","ipdsId":"IP-154555","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":441667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2023.18.4.114182","text":"Publisher Index Page"},{"id":423573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Louisiana, Mississippi, Texas","otherGeospatial":"Northern Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -87.44754208385507,\n              30.500778551705963\n            ],\n            [\n              -88.45828427135463,\n              30.95408530133362\n            ],\n            [\n              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A.","contributorId":332438,"corporation":false,"usgs":false,"family":"O’Shaughnessy","given":"Kathryn","email":"","middleInitial":"A.","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":890174,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vilizzi, Lorenzo","contributorId":332439,"corporation":false,"usgs":false,"family":"Vilizzi","given":"Lorenzo","email":"","affiliations":[{"id":79459,"text":"University of Lodz, Poland","active":true,"usgs":false}],"preferred":false,"id":890175,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daniel, Wesley M. 0000-0002-7656-8474","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":219320,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":890176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGarrity, Monica E.","contributorId":332440,"corporation":false,"usgs":false,"family":"McGarrity","given":"Monica","email":"","middleInitial":"E.","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":890177,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bauer, Hanna","contributorId":332441,"corporation":false,"usgs":false,"family":"Bauer","given":"Hanna","email":"","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":890178,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hartman, Leslie","contributorId":332442,"corporation":false,"usgs":false,"family":"Hartman","given":"Leslie","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":890179,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Geiger, Stephen","contributorId":332444,"corporation":false,"usgs":false,"family":"Geiger","given":"Stephen","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":890180,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sammarco, Paul","contributorId":332445,"corporation":false,"usgs":false,"family":"Sammarco","given":"Paul","email":"","affiliations":[{"id":12699,"text":"Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":890181,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kolian, Steve","contributorId":332446,"corporation":false,"usgs":false,"family":"Kolian","given":"Steve","email":"","affiliations":[{"id":79461,"text":"EcoRigs Non-Profit Organization","active":true,"usgs":false}],"preferred":false,"id":890182,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Porter, Scott","contributorId":332447,"corporation":false,"usgs":false,"family":"Porter","given":"Scott","email":"","affiliations":[{"id":79461,"text":"EcoRigs Non-Profit Organization","active":true,"usgs":false}],"preferred":false,"id":890183,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dutton, Jessica","contributorId":332448,"corporation":false,"usgs":false,"family":"Dutton","given":"Jessica","email":"","affiliations":[{"id":79462,"text":"Texas State University, Aquatic Station","active":true,"usgs":false}],"preferred":false,"id":890184,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McClure, Matthew R.","contributorId":332449,"corporation":false,"usgs":false,"family":"McClure","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":79463,"text":"Lamar State College Orange","active":true,"usgs":false}],"preferred":false,"id":890185,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Norberg, Michael","contributorId":332450,"corporation":false,"usgs":false,"family":"Norberg","given":"Michael","email":"","affiliations":[{"id":79464,"text":"Okaloosa County Board of County Commissioners, Florida","active":true,"usgs":false}],"preferred":false,"id":890186,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Fogg, Alex","contributorId":332451,"corporation":false,"usgs":false,"family":"Fogg","given":"Alex","email":"","affiliations":[{"id":79464,"text":"Okaloosa County Board of County Commissioners, Florida","active":true,"usgs":false}],"preferred":false,"id":890187,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Lyons, Timothy J.","contributorId":332452,"corporation":false,"usgs":false,"family":"Lyons","given":"Timothy J.","affiliations":[{"id":79465,"text":"University of Florida/IFAS and New Mexico Biopark Society","active":true,"usgs":false}],"preferred":false,"id":890188,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Procopio, Justin","contributorId":214946,"corporation":false,"usgs":false,"family":"Procopio","given":"Justin","email":"","affiliations":[{"id":25340,"text":"Cherokee Nation Technologies","active":true,"usgs":false}],"preferred":false,"id":890189,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Bantista, Lauren","contributorId":332453,"corporation":false,"usgs":false,"family":"Bantista","given":"Lauren","email":"","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":890190,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Bennett, Wayne A","contributorId":248816,"corporation":false,"usgs":false,"family":"Bennett","given":"Wayne A","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":890191,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Wicksten, Mary","contributorId":332454,"corporation":false,"usgs":false,"family":"Wicksten","given":"Mary","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":890192,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Reeves, David B.","contributorId":181809,"corporation":false,"usgs":false,"family":"Reeves","given":"David","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":890193,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Lively, Julie","contributorId":332455,"corporation":false,"usgs":false,"family":"Lively","given":"Julie","email":"","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":890194,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Robinson, Elizabeth M.","contributorId":257731,"corporation":false,"usgs":false,"family":"Robinson","given":"Elizabeth","email":"","middleInitial":"M.","affiliations":[{"id":40763,"text":"Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":890195,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Brenner, Jorge","contributorId":205829,"corporation":false,"usgs":false,"family":"Brenner","given":"Jorge","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":890196,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Goy, Joseph","contributorId":332456,"corporation":false,"usgs":false,"family":"Goy","given":"Joseph","email":"","affiliations":[{"id":79466,"text":"Harding University","active":true,"usgs":false}],"preferred":false,"id":890197,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Morgan-Olvera, Ashley","contributorId":332458,"corporation":false,"usgs":false,"family":"Morgan-Olvera","given":"Ashley","email":"","affiliations":[{"id":37056,"text":"Sam Houston State University","active":true,"usgs":false}],"preferred":false,"id":890198,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Yunnie, Anna L.E.","contributorId":332459,"corporation":false,"usgs":false,"family":"Yunnie","given":"Anna","email":"","middleInitial":"L.E.","affiliations":[{"id":79468,"text":"PML Applications Ltd, UK","active":true,"usgs":false}],"preferred":false,"id":890199,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Copp, Gordon H.","contributorId":332460,"corporation":false,"usgs":false,"family":"Copp","given":"Gordon","email":"","middleInitial":"H.","affiliations":[{"id":79469,"text":"Centre for Environment, Fisheries and Aquaculture Science and Bournemouth University, UK","active":true,"usgs":false}],"preferred":false,"id":890200,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}}
,{"id":70249965,"text":"70249965 - 2023 - Georectified polygon database of ground-mounted large-scale solar photovoltaic sites in the United States","interactions":[],"lastModifiedDate":"2023-11-09T12:40:22.673273","indexId":"70249965","displayToPublicDate":"2023-11-08T06:37:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Georectified polygon database of ground-mounted large-scale solar photovoltaic sites in the United States","docAbstract":"<p>Over 4,400 large-scale solar photovoltaic (LSPV) facilities operate in the United States as of December 2021, representing more than 60 gigawatts of electric energy capacity. Of these, over 3,900 are ground-mounted LSPV facilities with capacities of 1 MWdc or more. Ground mounted LSPV installations continue increasing, with more than 400 projects appearing online in 2021 alone; however, a comprehensive, publicly available georectified dataset including spatial footprints of these facilities is lacking. Analysts from U.S.</p><div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Over 4,400 large-scale solar photovoltaic (LSPV) facilities operate in the United States as of December 2021, representing more than 60 gigawatts of electric energy capacity. Of these, over 3,900 are ground-mounted LSPV facilities with capacities of 1 megawatt direct current (MW<sub>dc</sub>) or more. Ground-mounted LSPV installations continue increasing, with more than 400 projects appearing online in 2021 alone; however, a comprehensive, publicly available georectified dataset including spatial footprints of these facilities is lacking. The United States Large-Scale Solar Photovoltaic Database (USPVDB) was developed to fill this gap. Using US Energy Information Administration (EIA) data, locations of 3,699 LSPV facilities were verified using high-resolution aerial imagery, polygons were digitized around panel arrays, and attributes were appended. Quality assurance and control were achieved via team peer review and comparison to other US PV datasets. Data are publicly available via an interactive web application and multiple downloadable formats, including: comma-separated value (CSV), application programming interface (API), and GIS shapefile and GeoJSON.</p></div></div><p>Survey and Lawrence Berkeley National Laboratory collaborated to develop the United States Large-Scale Solar Photovoltaic Database (USPVDB). Using Energy Information Administration (EIA) data, locations of LSPV facilities were verified using high-resolution aerial imagery, polygons were digitized around panel arrays, and attributes were appended. Quality assurance and control were achieved via team peer review and comparison to other US PV datasets. Data are publicly available in an interactive web application, and a number of downloadable formats, including: comma-separated value spreadsheet (CSV), application programming interface (API), and GIS shapefile.</p>","language":"English","publisher":"Nature","doi":"10.1038/s41597-023-02644-8","usgsCitation":"Fujita, K.S., Ancona, Z.H., Kramer, L., Straka, M., Gautreau, T.E., Robson, D., Garrity, C.P., Hoen, B., and Diffendorfer, J., 2023, Georectified polygon database of ground-mounted large-scale solar photovoltaic sites in the United States: Scientific Data, v. 10, 760, 14 p., https://doi.org/10.1038/s41597-023-02644-8.","productDescription":"760, 14 p.","ipdsId":"IP-152694","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441671,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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 \"}}]}","volume":"10","noUsgsAuthors":false,"publicationDate":"2023-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Fujita, K. Sydny","contributorId":331485,"corporation":false,"usgs":false,"family":"Fujita","given":"K.","middleInitial":"Sydny","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":887829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ancona, Zachary H. 0000-0001-5430-0218 zancona@usgs.gov","orcid":"https://orcid.org/0000-0001-5430-0218","contributorId":5578,"corporation":false,"usgs":true,"family":"Ancona","given":"Zachary","email":"zancona@usgs.gov","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":887830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kramer, Louisa 0000-0002-6776-9768","orcid":"https://orcid.org/0000-0002-6776-9768","contributorId":204878,"corporation":false,"usgs":true,"family":"Kramer","given":"Louisa","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":887831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Straka, Mary","contributorId":331486,"corporation":false,"usgs":false,"family":"Straka","given":"Mary","email":"","affiliations":[{"id":27102,"text":"USGS student contractor","active":true,"usgs":false}],"preferred":false,"id":887832,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gautreau, Tandie E.","contributorId":331487,"corporation":false,"usgs":false,"family":"Gautreau","given":"Tandie","email":"","middleInitial":"E.","affiliations":[{"id":27102,"text":"USGS student contractor","active":true,"usgs":false}],"preferred":false,"id":887833,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robson, Dana","contributorId":331488,"corporation":false,"usgs":false,"family":"Robson","given":"Dana","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":887834,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garrity, Christopher P. 0000-0002-5565-1818 cgarrity@usgs.gov","orcid":"https://orcid.org/0000-0002-5565-1818","contributorId":644,"corporation":false,"usgs":true,"family":"Garrity","given":"Christopher","email":"cgarrity@usgs.gov","middleInitial":"P.","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":887835,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hoen, Ben 0000-0002-9512-5572","orcid":"https://orcid.org/0000-0002-9512-5572","contributorId":204879,"corporation":false,"usgs":false,"family":"Hoen","given":"Ben","email":"","affiliations":[{"id":37001,"text":"DOE Lawrence Berkeley National Labs","active":true,"usgs":false}],"preferred":false,"id":887836,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":887837,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70249658,"text":"ofr20231055 - 2023 - Monitoring Avian Productivity and Survivorship (MAPS) 6-year summary, Naval Outlying Landing Field, Imperial Beach, southwestern San Diego County, California, 2014–20","interactions":[],"lastModifiedDate":"2024-01-12T18:28:24.030626","indexId":"ofr20231055","displayToPublicDate":"2023-11-07T14:26:21","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1055","displayTitle":"Monitoring Avian Productivity and Survivorship (MAPS) 6-Year Summary, Naval Outlying Landing Field, Imperial Beach, Southwestern San Diego County, California, 2014–20","title":"Monitoring Avian Productivity and Survivorship (MAPS) 6-year summary, Naval Outlying Landing Field, Imperial Beach, southwestern San Diego County, California, 2014–20","docAbstract":"<h1>Executive Summary</h1><p>From 2014 to 2020, a Monitoring Avian Productivity and Survivorship (MAPS) banding station (station) was operated at the Naval Outlying Landing Field (NOLF), Imperial Beach, in southwestern San Diego County, California. The station was established as part of a long-term monitoring program of Neotropical migratory bird populations on NOLF and helps Naval Base Coronado (NOLF is a component) meet the goals and objectives of the Department of Defense Partners in Flight program and the Birds and Migratory Birds Management Strategies of the Naval Base Coronado Integrated Natural Resources Management Plan. The station was established in 2009 and has been in operation during the spring and summer since 2009 except for 2016 when it was not funded. The station was operated by AMEC Earth and Environmental, Inc., from 2009 to 2011, by the U.S. Geological Survey from 2012 to 2015, the San Diego Natural History Museum in 2017, and the U.S. Geological Survey again from 2018 to 2023. This report synthesizes results from 2014 to 2020. A prior report presents summaries and analyses from 2009 to 2013.</p><p>The banding station at NOLF was operated according to the standard MAPS protocol with some exceptions. Ten mist nets used to capture birds were erected in fixed locations that remained consistent between and within years, with few minor relocations. Nets were open for 6 hours per day, once every 10 days (a netting period) for 13 netting periods starting April 1 each year. Occasionally, poor weather conditions (for example, rain, wind, or excessive heat) prevented net operation or forced nets to be closed early (or, rarely, late). Nets were checked periodically throughout the day and birds were removed, processed (leg bands affixed, measurements recorded), and released.</p><p>From 2014 to 2020, we had 3,543 captures (including initial captures and recaptures) of a maximum of 3,264 year-unique captures (543±143 year-unique captures [the total number of individual birds captured for the first time each year]). The count of year-unique captures included 2,702 newly banded birds, 258 individuals that were recaptured from previous years, and 304 birds that were released unbanded (218 hummingbirds and 86 other birds that were intentionally released unbanded [game birds, and so forth] or escaped before banding). Individuals of 68 species were captured, 39 of which breed at or in the immediate vicinity of the MAPS banding station. Bird capture rate averaged 43±30 captures per day (corrected to account for variation in effort) for all years (range 7–163 effort-corrected captures per day) and species richness per year averaged 43±4. Bushtit (<i>Psaltriparus minimus</i>) was the most abundant species captured, followed by Orange-crowned Warbler (<i>Leiothlypis celata</i>), Wilson’s Warbler (<i>Cardellina pusilla</i>), House Finch (<i>Haemorhous mexicanus</i>), Song Sparrow (<i>Melospiza melodia</i>), and Common Yellowthroat (<i>Geothlypis trichas</i>). The mean adult sex ratio of all species combined across all years was 54:46 male:female. Adults averaged 73±12 percent of known age captures per year (range 59–94 percent), and juveniles averaged 27±12 percent (range 6–41 percent).</p><p>Nineteen sensitive species were detected at NOLF (12 captured and 7 observed only). During 2014–20, we captured one State and federally endangered species, Least Bell’s Vireo (<i>Vireo bellii pusillus</i>); one federally threatened species, California Gnatcatcher (<i>Polioptila californica</i>); one State endangered species, Willow Flycatcher (<i>Empidonax traillii</i>); and two State species of concern, Yellow-breasted Chat (<i>Icteria virens</i>) and Yellow Warbler (<i>Setophaga petechia</i>). One additional State species of concern, Northern Harrier (<i>Circus hudsonius</i>), was observed at the MAPS banding station but not captured. Peregrine Falcon (<i>Falco peregrinus</i>) and White-tailed Kite (<i>Elanus leucurus</i>), California State fully protected species, also were observed at the MAPS banding station. Seven federal bird species of conservation concern—Calliope Hummingbird (<i>Selasphorus calliope</i>), Rufous Hummingbird (<i>Selasphorus rufus</i>), Allen’s Hummingbird (<i>Selasphorus sasin</i>), Nuttall’s Woodpecker (<i>Dryobates nuttallii</i>), Wrentit (<i>Chamaea fasciata</i>), California Thrasher (<i>Toxostoma redivivum</i>), and Lawrence’s Goldfinch (<i>Spinus lawrencei</i>)—also were captured, and four additional federal bird species of conservation concern—Willet (<i>Tringa semipalmata</i>), Western Gull (<i>Larus occidentalis</i>), California Gull (<i>Larus californicus</i>), and Bullock’s Oriole (<i>Icterus bullockii</i>)—were observed but not captured.</p><p>Local population trends varied among species and years. From 2012 to 2019, year-round residents Bushtit, Song Sparrow, and Common Yellowthroat significantly decreased, whereas the migrant Least Bell’s Vireo increased. The total number of captures for all species except Least Bell’s Vireo was lowest in 2017, corresponding to the habitat damage caused by Kuroshio shot hole borer beetle (<i>Euwallacea kuroshio</i>) in the Tijuana River Valley.</p><p>Annual productivity and annual adult survival were calculated for seven breeding species based on criteria used by the Institute for Bird Populations (Least Bell’s Vireo, Bushtit, Wrentit, House Wren [<i>Troglodytes aedon</i>], Song Sparrow, Orange-crowned Warbler, and Common Yellowthroat). Productivity was highest for most species in 2010 and 2019, years with high precipitation, and lowest in 2014 and 2018, years with low precipitation. Song Sparrow demonstrated the highest productivity among species and Least Bell’s Vireo had the lowest productivity. Annual adult survival was generally high from 2011 to 2012 and from 2018 to 2019. Bushtit had higher annual survival with lower late winter precipitation. Either temperature or precipitation was associated with productivity for all species except Wrentit, and with survival for all species except Least Bell’s Vireo and Common Yellowthroat. For most species, productivity was positively associated with precipitation, and both productivity and survival were negatively associated with temperature. Other studies have found that higher temperatures led to increased predation by snakes and birds and also increased vector-borne disease transmission, such as West Nile virus. Predicted regional increases in temperature over the next 30 years will likely affect the demographics of these species.</p><p>The Song Sparrow population increased with higher breeding productivity during the previous year, and the Bushtit population increased with higher annual survival and higher productivity during the previous year. Aside from a possible positive association between survivorship and Common Yellowthroat population growth, productivity and survival rates did not appear to influence population change for other focal species.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231055","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Lynn, S., Mendia, S., and Kus, B.E., 2023, Monitoring Avian Productivity and Survivorship (MAPS) 6-year summary, Naval Outlying Landing Field, Imperial Beach, southwestern San Diego County, California, 2014–20: U.S. Geological Survey Open-File Report 2023–1055, 68 p., https://doi.org/10.3133/ofr20231055.","productDescription":"viii, 68 p.","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-150872","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":422046,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1055/images"},{"id":422047,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231055/full"},{"id":422044,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1055/ofr20231055.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":422043,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1055/covrthb.jpg"},{"id":422045,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1055/ofr20231055.xml"}],"country":"United States","state":"California","county":"San Diego County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.13399491171916,\n              32.5777941285686\n            ],\n            [\n              -117.13399491171916,\n              32.54958248003706\n            ],\n            [\n              -117.08507141928763,\n              32.54958248003706\n            ],\n            [\n              -117.08507141928763,\n              32.5777941285686\n            ],\n            [\n              -117.13399491171916,\n              32.5777941285686\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>References Cited</li><li>Appendix 1</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2023-11-07","noUsgsAuthors":false,"publicationDate":"2023-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynn, Suellen 0000-0003-1543-0209 suellen_lynn@usgs.gov","orcid":"https://orcid.org/0000-0003-1543-0209","contributorId":3843,"corporation":false,"usgs":true,"family":"Lynn","given":"Suellen","email":"suellen_lynn@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":886623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mendia, Shannon M. 0000-0003-4520-7024 smendia@usgs.gov","orcid":"https://orcid.org/0000-0003-4520-7024","contributorId":223097,"corporation":false,"usgs":true,"family":"Mendia","given":"Shannon","email":"smendia@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":886624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":886625,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70249940,"text":"ofr20221070 - 2023 - Development and application of a risk assessment tool for aquatic invasive species in the international Rainy-Lake of the Woods Basin, United States and Canada","interactions":[],"lastModifiedDate":"2026-02-10T20:50:17.948983","indexId":"ofr20221070","displayToPublicDate":"2023-11-07T12:03:21","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1070","displayTitle":"Development and Application of a Risk Assessment Tool for Aquatic Invasive Species in the International Rainy-Lake of the Woods Basin, United States and Canada","title":"Development and application of a risk assessment tool for aquatic invasive species in the international Rainy-Lake of the Woods Basin, United States and Canada","docAbstract":"<p>The Rainy-Lake of the Woods Basin covers 70,000 square kilometers in mid-central North America and is contained within the Provinces of Ontario and Manitoba in Canada and the State of Minnesota in the United States. This basin contains natural wilderness areas, national parks, and thousands of lakes that bring outdoor enthusiasts from around the world for hunting, fishing, backpacking, boating, and other forms of recreation. However, trade, commerce, visitors, and wildlife can inadvertently transport hitchhiking exotic invasive species that affect the functioning of natural systems by displacing native organisms, introducing diseases, and modifying predator/prey relations. In cooperation with the International Joint Commission, the U.S. Geological Survey evaluated the aquatic invasive species that pose a possible threat to North America. The outcome of this project is a set of lists of invasive species that have traits amenable or proximity to the Rainy-Lake of the Woods Basin. These lists can be referenced to further evaluate known and potential nonindigenous invasive species. The lists were derived by evaluating more than 1,500 species from several online sources including Non-Indigenous Aquatic Species, Great Lakes Aquatic Nonindigenous Species Information System, Biodiversity Information Serving Our Nation, and other State, Provincial, and Federal lists in the United States and Canada. The purpose of these lists is to be a coarse filter to determine which species pose the greatest risk to the Rainy-Lake of the Woods Basin. Using this filter, seven categories of risk assessment priorities were developed: Very High-Approaching, Very High-Present, High-Approaching, High-Present, Moderate, Low, and Native. These categories can be used by the International Rainy-Lake of the Woods Multi-Agency Arrangement Aquatic Invasive Species Subcommittee to prioritize which species will be evaluated further focusing on five risk factors: arrival risk, vulnerability assessment, ecological impact, socioeconomic impact, and beneficial impact. Based on proximity, ease of transport or introduction, and known impact to Rainy-Lake of the Woods or other impacted ecosystems, this project identified the following 10 species that could be prioritized first for risk evaluations: <i>Bythotrephes longimanus</i> (spiny waterflea), <i>Faxonius rusticus</i> (rusty crayfish), <i>Neogobius melanostomus</i> (round goby), <i>Dreissena polymorpha</i> (zebra mussel), <i>Bithynia tentaculata</i> (mud Bithynia or faucet snail), <i>Potamopyrgus antipodarum</i> (New Zealand mud snail), <i>Butomus umbellatus</i> (flowering rush), <i>Nitellopsis obtusa</i> (starry stonewort), <i>Myriophyllum spicatum</i> (Eurasian watermilfoil), and <i>Phragmites australis australis</i> (common reed).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221070","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Bell, A.H., Katona, L.R., and Vellequette, N.M., 2023, Development and application of a risk assessment tool for aquatic invasive species in the international Rainy-Lake of the Woods Basin, United States and Canada: U.S. Geological Survey Open-File Report 2022–1070, 26 p., https://doi.org/10.3133/ofr20221070.","productDescription":"Report: vi, 26 p.; 3 Datasets","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127028","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499719,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115587.htm","linkFileType":{"id":5,"text":"html"}},{"id":422425,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221070/full"},{"id":422424,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://bison.usgs.gov/","text":"USGS database","linkHelpText":"—Biodiversity Information Serving Our Nation (BISON)"},{"id":422421,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1070/images/"},{"id":422418,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1070/coverthb.jpg"},{"id":422420,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1070/ofr20221070.XML"},{"id":422419,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1070/ofr20221070.pdf","text":"Report","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1070"},{"id":422422,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://www.glerl.noaa.gov/glansis/riskAssessment.html","text":"NOAA database","linkHelpText":"—Great Lake Aquatic Nonindigenous Species Information System (GLANSIS) Risk Assessment Clearinghouse"},{"id":422423,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://nas.er.usgs.gov/","text":"USGS database","linkHelpText":"—NAS—Nonindigenous Aquatic Species"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -95.7568318410593,\n              50.39164460188181\n            ],\n            [\n              -95.7568318410593,\n              47.02962883799128\n            ],\n            [\n              -90.08788652855912,\n              47.02962883799128\n            ],\n            [\n              -90.08788652855912,\n              50.39164460188181\n            ],\n            [\n              -95.7568318410593,\n              50.39164460188181\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/umid-water\" data-mce-href=\"https://www.usgs.gov/centers/umid-water\">Upper Midwest Water Science Center</a><br>U.S. Geological Survey<br>1 Gifford Pinchot Drive<br>Madison, WI 53726</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Development of Lists and Ranking of Species</li><li>Final Priority for Risk Evaluation Lists and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-11-07","noUsgsAuthors":false,"publicationDate":"2023-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katona, Leon R. 0000-0001-5323-1871","orcid":"https://orcid.org/0000-0001-5323-1871","contributorId":331458,"corporation":false,"usgs":true,"family":"Katona","given":"Leon","email":"","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vellequette, Nicole M.","contributorId":331457,"corporation":false,"usgs":true,"family":"Vellequette","given":"Nicole","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887760,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250002,"text":"70250002 - 2023 - Extinction risk modeling predicts range-wide differences of climate change impact on Karner blue butterfly (Lycaeides melissa samuelis)","interactions":[],"lastModifiedDate":"2023-11-12T13:23:11.157831","indexId":"70250002","displayToPublicDate":"2023-11-07T07:16:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Extinction risk modeling predicts range-wide differences of climate change impact on Karner blue butterfly (Lycaeides melissa samuelis)","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p>The Karner blue butterfly (<i>Lycaeides melissa samuelis</i>, or Kbb), a federally endangered species under the U.S. Endangered Species Act in decline due to habitat loss, can be further threatened by climate change. Evaluating how climate shapes the population trend of the Kbb can help in the development of adaptive management plans. Current demographic models for the Kbb incorporate in either a density-dependent or density-independent manner. We instead created mixed density-dependent and -independent (hereafter “endo-exogenous”) models for Kbbs based on long-term count data of five isolated populations in the upper Midwest, United States during two flight periods (May to June and July to August) to understand how the growth rates were related to previous population densities and abiotic environmental conditions, including various macro- and micro-climatic variables. Our endo-exogenous extinction risk models showed that both density-dependent and -independent components were vital drivers of the historical population trends. However, climate change impacts were not always detrimental to Kbbs. Despite the decrease of population growth rate with higher overwinter temperatures and spring precipitations in the first generation, the growth rate increased with higher summer temperatures and precipitations in the second generation. We concluded that finer spatiotemporally scaled models could be more rewarding in guiding the decision-making process of Kbb restoration under climate change.</p></div></div>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0262382","usgsCitation":"Li, Y., Wilson, D., Grundel, R., Campbell, S., Knight, J., Perry, J., and Hellmann, J., 2023, Extinction risk modeling predicts range-wide differences of climate change impact on Karner blue butterfly (Lycaeides melissa samuelis): PLoS ONE, v. 18, no. 11, e0262382, 17 p., https://doi.org/10.1371/journal.pone.0262382.","productDescription":"e0262382, 17 p.","ipdsId":"IP-133245","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":441675,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1371/journal.pone.0262382","text":"Publisher Index Page"},{"id":422516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"11","noUsgsAuthors":false,"publicationDate":"2023-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Yudi","contributorId":331504,"corporation":false,"usgs":false,"family":"Li","given":"Yudi","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":887933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, David","contributorId":331505,"corporation":false,"usgs":false,"family":"Wilson","given":"David","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":887934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grundel, Ralph 0000-0002-2949-7087 rgrundel@usgs.gov","orcid":"https://orcid.org/0000-0002-2949-7087","contributorId":2444,"corporation":false,"usgs":true,"family":"Grundel","given":"Ralph","email":"rgrundel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":887935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell, Steven","contributorId":331506,"corporation":false,"usgs":false,"family":"Campbell","given":"Steven","affiliations":[{"id":79223,"text":"Albany Pine Bush Commission","active":true,"usgs":false}],"preferred":false,"id":887936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knight, Joe","contributorId":331507,"corporation":false,"usgs":false,"family":"Knight","given":"Joe","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":887937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perry, Jim","contributorId":331508,"corporation":false,"usgs":false,"family":"Perry","given":"Jim","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":887938,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hellmann, Jessica J.","contributorId":331509,"corporation":false,"usgs":false,"family":"Hellmann","given":"Jessica J.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":887939,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70250055,"text":"70250055 - 2023 - Empirical estimation of habitat suitability for rare plant restoration in an era of ongoing climatic shifts","interactions":[],"lastModifiedDate":"2023-11-15T12:57:38.715568","indexId":"70250055","displayToPublicDate":"2023-11-07T06:55:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Empirical estimation of habitat suitability for rare plant restoration in an era of ongoing climatic shifts","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Accurate estimates of current and future habitat suitability are needed for species that may require assistance in tracking a shifting climate. Standard species distribution models (SDMs) based on occurrence data are the most common approach for evaluating climatic suitability, but these may suffer from inaccuracies stemming from disequilibrium dynamics and/or an inability to identify suitable climate regions that have no analogues within the current range. An alternative approach is to test performance with experimental introductions, and model suitability from the empirical results. We used this method with the Haleakalā silversword (<i>Argyroxiphium sandwicense</i><span>&nbsp;</span>subsp.<span>&nbsp;</span><i>macrocephalum</i>), using a network of out-plant plots across the top of Haleakalā volcano, Hawaiʻi. Over a ~ 5-year period, survival varied strongly across this network and was effectively explained by a simple model including mean rainfall and air temperature. We then applied this model to estimate current climatic suitability for restoration or translocation activities, to define trends in suitability over the past three decades, and to project future suitability through 2051. This empirical approach indicated that much of the current range has low suitability for long-term successful restoration, but also identified areas of high climatic suitability in a region where plants do not currently occur. These patterns contrast strongly with projections obtained with a standard SDM, which predicted continued suitability throughout the current range. Under continued climatic shifts, these results caution against the common SDM presumption of equilibrium between species’ distributions and their environment, even for long-established native species.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-46793-7","usgsCitation":"Krushelnycky, P., Fortini, L., Mallinson, J., and Felts, J., 2023, Empirical estimation of habitat suitability for rare plant restoration in an era of ongoing climatic shifts: Scientific Reports, v. 13, 19257, 13 p., https://doi.org/10.1038/s41598-023-46793-7.","productDescription":"19257, 13 p.","ipdsId":"IP-151354","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":441677,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-46793-7","text":"Publisher Index Page"},{"id":422616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -156.33374758383275,\n              20.80695004021031\n            ],\n            [\n              -156.33374758383275,\n              20.64768384880557\n            ],\n            [\n              -156.0645825447702,\n              20.64768384880557\n            ],\n            [\n              -156.0645825447702,\n              20.80695004021031\n            ],\n            [\n              -156.33374758383275,\n              20.80695004021031\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2023-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Krushelnycky, Paul","contributorId":265727,"corporation":false,"usgs":false,"family":"Krushelnycky","given":"Paul","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":888153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":888154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mallinson, Jeffrey","contributorId":331594,"corporation":false,"usgs":false,"family":"Mallinson","given":"Jeffrey","email":"","affiliations":[{"id":79247,"text":"Haleakalā National Park","active":true,"usgs":false}],"preferred":false,"id":888155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Felts, Jesse","contributorId":331595,"corporation":false,"usgs":false,"family":"Felts","given":"Jesse","email":"","affiliations":[{"id":79247,"text":"Haleakalā National Park","active":true,"usgs":false}],"preferred":false,"id":888156,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70253151,"text":"70253151 - 2023 - Movement dynamics influence population monitoring and adaptive harvest management strategies in migratory birds","interactions":[],"lastModifiedDate":"2024-04-23T11:38:02.939504","indexId":"70253151","displayToPublicDate":"2023-11-07T06:35:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Movement dynamics influence population monitoring and adaptive harvest management strategies in migratory birds","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif text-s\"><div id=\"ab0010\" class=\"abstract author\"><div id=\"abs0010\"><p id=\"sp0030\"><span>Informed population monitoring efforts are essential for sound management of harvested species, and adaptive strategies that provide detailed information to monitoring efforts often require data inputs from complimentary sources. Movement ecology information is seldom directly incorporated into population monitoring or adaptive harvest management strategies, yet can provide valuable information on species distributions, emigration and immigration rates, and aid in determining optimal population monitoring timing. The Rocky Mountain Population (RMP) of&nbsp;Sandhill Cranes&nbsp;is a harvested population subject to a stringent adaptive harvest management framework and an annual&nbsp;aerial survey&nbsp;to estimate population abundance, but movements of Sandhill Cranes during survey windows, and subsequent changes to harvest quotas based on their movement and distribution have not been investigated. We used seven years of&nbsp;GPS&nbsp;tracking data to estimate state-specific emigration and immigration rates, using a Bayesian multi-state capture-recapture model, among states within the RMP distribution to understand how seasonal crane movements may influence optimal aerial survey timing. We then leveraged these&nbsp;transition probabilities&nbsp;in conjunction with aerial survey count data to model how changes in aerial survey timing and movement-informed crane distribution would influence the current RMP Sandhill Crane adaptive harvest management model resulting in estimated changes to harvest allocation among states based on Sandhill Crane movement. We found that Sandhill Crane emigration from northern states began to increase the week of the aerial survey in late September, and continued to increase as autumn migration progressed into October. As expected, immigration to southern states began as emigration from northern states increased. Importantly, little movement among states occurred prior to the current aerial survey design timing. Overall, we found that current survey timing and shortly thereafter (∼1 week) did not greatly influence estimates of Sandhill Crane distribution, and did not greatly influence the harvest reallocation to each state until mid to late October (range of −42–+52 tag allocation change), much later than the current survey design would allow. Using&nbsp;GPS&nbsp;locations, we found that optimal population monitoring efforts could be improved to account for both detection and seasonal movements, while minimally influencing current adaptive harvest management strategies to stakeholders. Linking movement ecology with population monitoring efforts and subsequently adaptive harvest management strategies yields insightful information that can be beneficial for&nbsp;</span>conservation planning, decision-making, and optimal species management of a migratory bird.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2023.e02715","usgsCitation":"VonBank, J.A., Collins, D.P., Ellis, K.S., Donnelly, J.P., and Knetter, J.M., 2023, Movement dynamics influence population monitoring and adaptive harvest management strategies in migratory birds: Global Ecology and Conservation, v. 48, e02715, 14 p., https://doi.org/10.1016/j.gecco.2023.e02715.","productDescription":"e02715, 14 p.","ipdsId":"IP-156596","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":441681,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2023.e02715","text":"Publisher Index Page"},{"id":428045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Idaho, Montaha, Utah, Wyoming","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.053249,41.001406],[-102.051718,41.002377],[-102.051569,39.849805],[-102.041574,37.680436],[-102.04224,36.993083],[-102.698142,36.995149],[-102.814616,37.000783],[-104.338833,36.993535],[-105.447255,36.996017],[-106.869796,36.992426],[-106.877292,37.000139],[-110.47019,36.997997],[-110.50069,37.00426],[-111.278286,37.000465],[-114.0506,37.000396],[-114.052962,37.592783],[-114.048473,37.809861],[-114.050485,38.499955],[-114.040231,41.49169],[-114.041723,41.99372],[-114.598267,41.994511],[-114.831077,42.002207],[-115.031783,41.996008],[-116.368478,41.996281],[-117.026222,42.000252],[-117.026871,43.832479],[-117.01077,43.862269],[-116.98294,43.86771],[-116.976024,43.895548],[-116.977332,43.905812],[-116.963666,43.921363],[-116.96247,43.928336],[-116.963666,43.952644],[-116.971835,43.962806],[-116.942944,43.987512],[-116.934485,44.021249],[-116.943361,44.035645],[-116.972504,44.048771],[-116.977351,44.085364],[-116.967203,44.090936],[-116.943132,44.09406],[-116.933704,44.100039],[-116.894309,44.158114],[-116.895757,44.171267],[-116.900103,44.176851],[-116.925392,44.191544],[-116.971675,44.197256],[-116.971958,44.235677],[-116.975905,44.242844],[-117.031862,44.248635],[-117.042283,44.242775],[-117.047062,44.229742],[-117.05303,44.229076],[-117.067284,44.24401],[-117.089503,44.258234],[-117.098531,44.275533],[-117.107673,44.280763],[-117.121037,44.277585],[-117.143394,44.258262],[-117.170342,44.25889],[-117.198147,44.273828],[-117.216974,44.288357],[-117.222647,44.297578],[-117.217843,44.30718],[-117.203323,44.313024],[-117.189842,44.335007],[-117.196149,44.346362],[-117.235117,44.373853],[-117.242675,44.396548],[-117.22698,44.405583],[-117.215072,44.427162],[-117.215573,44.453746],[-117.225076,44.482346],[-117.200237,44.492027],[-117.181583,44.52296],[-117.161033,44.525166],[-117.149242,44.536151],[-117.14293,44.557236],[-117.147934,44.562143],[-117.146032,44.568603],[-117.124754,44.583834],[-117.120522,44.614658],[-117.098221,44.640689],[-117.095868,44.664737],[-117.080772,44.684161],[-117.07912,44.692175],[-117.061799,44.706654],[-117.062273,44.727143],[-117.03827,44.748179],[-117.013802,44.756841],[-116.998903,44.756382],[-116.972902,44.772581],[-116.9368,44.782881],[-116.9307,44.789881],[-116.933799,44.796781],[-116.931099,44.804781],[-116.896249,44.84833],[-116.865338,44.870599],[-116.852427,44.887577],[-116.838467,44.923601],[-116.832176,44.931373],[-116.850737,44.958113],[-116.858313,44.978761],[-116.846103,44.999878],[-116.844796,45.015312],[-116.848037,45.021728],[-116.841314,45.030907],[-116.825133,45.03784],[-116.797329,45.060267],[-116.78371,45.076972],[-116.783537,45.093605],[-116.774847,45.105536],[-116.754643,45.113972],[-116.729607,45.142091],[-116.724205,45.171501],[-116.709536,45.203015],[-116.70975,45.217243],[-116.703607,45.239757],[-116.691388,45.263739],[-116.675587,45.274867],[-116.672733,45.283183],[-116.673793,45.321511],[-116.619057,45.39821],[-116.597447,45.41277],[-116.588195,45.44292],[-116.554829,45.46293],[-116.558803,45.480076],[-116.548676,45.510385],[-116.535482,45.525079],[-116.523638,45.54661],[-116.502756,45.566608],[-116.48297,45.577008],[-116.463635,45.602785],[-116.463504,45.615785],[-116.487894,45.649769],[-116.523961,45.677639],[-116.535396,45.691734],[-116.538014,45.714929],[-116.535698,45.734231],[-116.546643,45.750972],[-116.559444,45.755189],[-116.593004,45.778541],[-116.632032,45.784979],[-116.646342,45.779815],[-116.665344,45.781998],[-116.680139,45.79359],[-116.697192,45.820135],[-116.711822,45.826267],[-116.736268,45.826179],[-116.759787,45.816167],[-116.782676,45.825376],[-116.788329,45.831928],[-116.787792,45.844267],[-116.796051,45.858473],[-116.814142,45.877551],[-116.84355,45.892273],[-116.859795,45.907264],[-116.869655,45.923799],[-116.875706,45.945008],[-116.886843,45.958617],[-116.892935,45.974396],[-116.911409,45.988912],[-116.91868,45.999875],[-116.923005,46.018293],[-116.942656,46.061],[-116.957372,46.075449],[-116.978938,46.080007],[-116.981962,46.084915],[-116.978823,46.095731],[-116.955263,46.102237],[-116.950276,46.123464],[-116.922648,46.160744],[-116.92187,46.167808],[-116.965841,46.203417],[-116.955264,46.23088],[-116.966742,46.256923],[-116.991134,46.276342],[-116.98491,46.289738],[-116.986688,46.296662],[-117.020663,46.314793],[-117.023149,46.334759],[-117.027744,46.338751],[-117.051735,46.343833],[-117.06263,46.352522],[-117.062785,46.365287],[-117.046915,46.379577],[-117.034696,46.418318],[-117.039813,46.425425],[-117.042657,47.760857],[-117.041107,48.124904],[-117.035178,48.370878],[-117.032351,48.999188],[-114.375977,49.00139],[-113.692982,48.997632],[-111.500812,48.996963],[-109.454023,49.001132],[-104.048736,48.999877],[-104.048054,48.500025],[-104.041662,47.862282],[-104.046822,46.000199],[-104.039977,45.124988],[-104.040128,44.999987],[-104.057698,44.997431],[-104.052583,42.650062],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 \"}}]}","volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"VonBank, Jay Alan 0000-0002-4319-4998","orcid":"https://orcid.org/0000-0002-4319-4998","contributorId":305827,"corporation":false,"usgs":true,"family":"VonBank","given":"Jay","email":"","middleInitial":"Alan","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":899313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collins, Daniel P.","contributorId":198065,"corporation":false,"usgs":false,"family":"Collins","given":"Daniel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":899314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Kristen S. 0000-0003-2759-3670","orcid":"https://orcid.org/0000-0003-2759-3670","contributorId":251877,"corporation":false,"usgs":true,"family":"Ellis","given":"Kristen","email":"","middleInitial":"S.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":899315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donnelly, J. Patrick","contributorId":266037,"corporation":false,"usgs":false,"family":"Donnelly","given":"J.","email":"","middleInitial":"Patrick","affiliations":[{"id":54869,"text":"Intermountain West Joint Venture – U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":899316,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knetter, Jeffrey M.","contributorId":198067,"corporation":false,"usgs":false,"family":"Knetter","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":899317,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70274329,"text":"70274329 - 2023 - Magnetotelluric insights into the formation and reactivation of trans-crustal shear zones in Precambrian basement of the eastern U.S. Midcontinent","interactions":[],"lastModifiedDate":"2026-03-26T17:08:24.080638","indexId":"70274329","displayToPublicDate":"2023-11-07T00:00:00","publicationYear":"2023","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":"Magnetotelluric insights into the formation and reactivation of trans-crustal shear zones in Precambrian basement of the eastern U.S. Midcontinent","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Three-dimensional inversion of regional long-period magnetotelluric (MT) data reveals the presence of two distinct sets of high-conductivity belts in the Precambrian basement of the eastern U.S. Midcontinent. One set, beneath Missouri, Illinois, Indiana, and western Ohio, is defined by northwest–southeast-oriented conductivity structures; the other set, beneath Kentucky, West Virginia, western Virginia, and eastern Ohio, includes structures that are generally oriented northeast–southwest. The northwest-trending belts occur mainly in Paleoproterozoic crust, and we suggest that their high conductivity values are due to graphite precipitated within trans-crustal shear zones from intrusion-related CO</span><sub>2</sub><span>-rich fluids. Our MT inversion results indicate that some of these structures dip steeply through the crust and intersect the Moho, which supports an interpretation that the shear zones originated as “leaky” transcurrent faults or transforms during the late Paleoproterozoic or the early Mesoproterozoic. The northeast-trending belts are associated with Grenvillian orogenesis and also potentially with Iapetan rifting, although further work is needed to verify the latter possibility. We interpret the different geographic positions of these two sets of conductivity belts as reflecting differences in origin and/or crustal rheology, with the northwest-trending belts largely confined to older, stable, pre-Grenville cratonic Laurentia, and the northeast-trending belts largely having formed in younger, weaker marginal crust. Notably, these high-conductivity zones spatially correlate with Midcontinent fault-and-fold zones that affect Phanerozoic strata. Stratigraphic evidence indicates that Midcontinent fault-and-fold zones were particularly active during Phanerozoic orogenic events, and some remain seismically active today, so the associated high-conductivity belts likely represent long-lived weaknesses that transect the crust.</span></span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B37099.1","usgsCitation":"Murphy, B.S., DeLucia, M.S., Marshak, S., Ravat, D., and Bedrosian, P.A., 2023, Magnetotelluric insights into the formation and reactivation of trans-crustal shear zones in Precambrian basement of the eastern U.S. Midcontinent: Geological Society of America Bulletin, v. 136, no. 7-8, p. 2661-2675, https://doi.org/10.1130/B37099.1.","productDescription":"15 p.","startPage":"2661","endPage":"2675","ipdsId":"IP-156454","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / 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To this end, the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the North Carolina Department of Transportation (NCDOT), developed a decision-support software tool based on a statewide version of the Stochastic Empirical Loading and Dilution Model (SELDM). This decision-support tool is designed to identify potential adverse effects of highway runoff by using a criterion based on a measurable change in water quality from a surrogate pollutant. The NCDOT worked with the North Carolina Department of Environmental Quality to select a 25-percent change in suspended sediment concentration as the decision-rule criterion for identifying measurable downstream water-quality change; this selection was based on available data and widely accepted stormwater monitoring uncertainties. Development of the statewide tool and its application to the Piedmont ecoregion are described in this report. Because SELDM can be applied to build a similar decision-support tool in any State, this report describes practice-ready methods that other State departments of transportation and municipal permittees can use to streamline environmental permitting and project delivery while protecting the environment.</p><p>Hydraulic design engineers can use this decision-support tool to establish stormwater-treatment goals for highway construction or improvement projects without having to learn SELDM or interpret its statistical output. The tool is a spreadsheet that determines if a selected highway segment can directly discharge highway runoff, if the highway segment can discharge runoff following treatment using a basic vegetated conveyance best management practice (BMP), or if treatment using an advanced BMP is needed to minimize effects of discharges on downstream water quality. To use the tool, hydraulic design engineers obtain upstream-basin characteristics from the U.S. Geological Survey StreamStats application and highway-site characteristics from preliminary design plans. They then enter these characteristics in the decision-support tool, which identifies the necessary stormwater-treatment goal.</p><p>The Piedmont ecoregion was used as a case study to demonstrate the type of information the decision-support tool can provide. In this ecoregion, 100 percent of direct discharges meet the water-quality criterion when the drainage-area ratio is less than about 0.007 acres of highway per square mile of upstream basin. Advanced BMPs are needed in 100 percent of basins with drainage-area ratios greater than about 50 acres per square mile. 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Carolina\",\"nation\":\"USA  \"}}]}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water-science-center\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Development of Operational Definitions</li><li>Development of the North Carolina Decision-Support System</li><li>Application of the North Carolina Decision-Support System</li><li>Example of Regional Results of Analyses</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-11-06","noUsgsAuthors":false,"publicationDate":"2023-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":203250,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stillwell, Charles C. 0000-0002-4571-4897","orcid":"https://orcid.org/0000-0002-4571-4897","contributorId":270394,"corporation":false,"usgs":true,"family":"Stillwell","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weaver, J. Curtis 0000-0001-7068-5445 jcweaver@usgs.gov","orcid":"https://orcid.org/0000-0001-7068-5445","contributorId":2229,"corporation":false,"usgs":true,"family":"Weaver","given":"J.","email":"jcweaver@usgs.gov","middleInitial":"Curtis","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":887507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDaniel, Andrew H. 0000-0002-7223-9307","orcid":"https://orcid.org/0000-0002-7223-9307","contributorId":331352,"corporation":false,"usgs":false,"family":"McDaniel","given":"Andrew","email":"","middleInitial":"H.","affiliations":[{"id":79187,"text":"North Carolina Department of Transportation","active":true,"usgs":false}],"preferred":false,"id":887508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lipscomb, Brian S. 0000-0001-5514-1511","orcid":"https://orcid.org/0000-0001-5514-1511","contributorId":331353,"corporation":false,"usgs":false,"family":"Lipscomb","given":"Brian","email":"","middleInitial":"S.","affiliations":[{"id":79187,"text":"North Carolina Department of Transportation","active":true,"usgs":false}],"preferred":false,"id":887509,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Susan C. 0000-0002-5891-5209","orcid":"https://orcid.org/0000-0002-5891-5209","contributorId":64716,"corporation":false,"usgs":false,"family":"Jones","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":34302,"text":"Federal Highway Administration (United States)","active":true,"usgs":false}],"preferred":false,"id":887510,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mullins, Ryan M. 0000-0001-5619-1035","orcid":"https://orcid.org/0000-0001-5619-1035","contributorId":331354,"corporation":false,"usgs":false,"family":"Mullins","given":"Ryan","email":"","middleInitial":"M.","affiliations":[{"id":79187,"text":"North Carolina Department of Transportation","active":true,"usgs":false}],"preferred":false,"id":887511,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70254893,"text":"70254893 - 2023 - Sea ice concentration decline in an important Adélie penguin molt area","interactions":[],"lastModifiedDate":"2024-06-10T14:33:15.0121","indexId":"70254893","displayToPublicDate":"2023-11-06T09:17:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Sea ice concentration decline in an important Adélie penguin molt area","docAbstract":"Unlike in many polar regions, the spatial extent and duration of the sea ice season have increased in the Ross Sea sector of the Southern Ocean during the satellite era. Simultaneously, populations of Adélie penguins, a sea ice obligate, have been stable or increasing in the region.  Relationships between Adélie penguin population growth and sea ice concentration are complex, with sea ice driving different, sometimes contrasting, demographic patterns. Adélie penguins undergo a complete molt annually, replacing all their feathers while fasting shortly after the breeding season. Unlike most penguin species, a majority of Adélies are thought to molt on sea ice, away from the breeding colonies, which makes this period particularly difficult to study. Here, we evaluate the hypothesis that persistent areas of high sea ice concentration provide important molting habitat for Adélie penguins. We analyzed data from geolocating dive recorders deployed year-round on 195 adult penguins at two colonies in the Ross Sea from 2017-2019. We identified molt by detecting extended gaps in post-breeding diving activity and used associated locations to define two key molting areas. Remotely sensed data indicated that sea ice concentration during molt was anomalously low during the study and has declined in the primary molt area since 1980. Further, annual return rates of penguins to breeding colonies were positively correlated with sea ice concentration in the molt areas over 20 years. Together these results suggest that sea ice conditions during Adélie penguin molt may represent a previously underappreciated annual bottleneck for adult survival.","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2306840120","usgsCitation":"Schmidt, A.E., Lescroël, A., Lisovski, S., Elrod, M., Jongsomjit, D., Dugger, K., and Ballard, G., 2023, Sea ice concentration decline in an important Adélie penguin molt area: PNAS, v. 120, 2306840120, 9 p., https://doi.org/10.1073/pnas.2306840120.","productDescription":"2306840120, 9 p.","ipdsId":"IP-154191","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":441683,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10655226","text":"Publisher Index Page"},{"id":429749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Ross Sea, Southern Ocean","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              165.56396484375,\n              -77.91566898632583\n            ],\n            [\n              170.00244140625,\n              -77.91566898632583\n            ],\n            [\n              170.00244140625,\n              -77.05911588252368\n            ],\n            [\n              165.56396484375,\n              -77.05911588252368\n            ],\n            [\n              165.56396484375,\n              -77.91566898632583\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"120","noUsgsAuthors":false,"publicationDate":"2023-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, Annie E.","contributorId":337934,"corporation":false,"usgs":false,"family":"Schmidt","given":"Annie","email":"","middleInitial":"E.","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":902793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lescroël, Amélie","contributorId":337935,"corporation":false,"usgs":false,"family":"Lescroël","given":"Amélie","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":902794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lisovski, Simeon","contributorId":337936,"corporation":false,"usgs":false,"family":"Lisovski","given":"Simeon","affiliations":[{"id":62783,"text":"Alfred Wegener Institute","active":true,"usgs":false}],"preferred":false,"id":902795,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elrod, Megan","contributorId":337937,"corporation":false,"usgs":false,"family":"Elrod","given":"Megan","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":902796,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jongsomjit, Dennis","contributorId":337938,"corporation":false,"usgs":false,"family":"Jongsomjit","given":"Dennis","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":902797,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902798,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ballard, Grant","contributorId":337939,"corporation":false,"usgs":false,"family":"Ballard","given":"Grant","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":902799,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70249831,"text":"fs20233038 - 2023 - Geologic carbon management options for the North Atlantic-Appalachian Region","interactions":[],"lastModifiedDate":"2023-12-14T20:56:39.351729","indexId":"fs20233038","displayToPublicDate":"2023-11-06T08:20:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3038","displayTitle":"Geologic Carbon Management Options for the North Atlantic-Appalachian Region","title":"Geologic carbon management options for the North Atlantic-Appalachian Region","docAbstract":"<h1>Introduction</h1><p>The U.S. Geological Survey (USGS) North Atlantic-Appalachian Region is developing the regionwide capacity to provide timely science support for decision-makers attempting to enhance carbon removal, sequestration, and emissions mitigation to meet national atmospheric carbon reduction goals. The U.S. Environmental Protection Agency (EPA) reported that in 2021, the fourteen States and the District of Columbia in the northeastern region account about for approximately 18 percent of the total national greenhouse gas (GHG) emissions. This Fact Sheet provides a summary of USGS science information and ongoing and new investigations or data-collection programs that may help the northeastern region decrease the release of carbon-containing GHG to the atmosphere.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233038","usgsCitation":"Warwick, P.D., Blondes, M.S., Brennan, S.T., Cahan, S.M., Karacan, C.Ö., Kroeger, K.D., and Merrill, M.D., 2023, Geologic carbon management options for the North Atlantic-Appalachian Region: U.S. Geological Survey Fact Sheet 2023–3038, 6 p., https://doi.org/10.3133/fs20233038.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-149218","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":422295,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3038/fs20233038.XML"},{"id":422291,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3038/coverthb.jpg"},{"id":422294,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3038/images/"},{"id":422293,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233038/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3038"},{"id":422292,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3038/fs20233038.pdf","text":"Report","size":"4.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3038"}],"country":"United States","state":"Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -77.26577580636953,\n              36.4871201165721\n            ],\n            [\n              -75.46948418608685,\n              38.28668271756587\n            ],\n            [\n              -73.51070016109207,\n              41.05603971547217\n            ],\n            [\n              -71.95706878291493,\n              41.50333448444454\n            ],\n            [\n              -71.00596870454174,\n              42.379951218421894\n            ],\n            [\n              -70.18176569603114,\n              43.65118954946408\n            ],\n            [\n              -67.0599117586491,\n              44.903001098203504\n            ],\n            [\n              -68.03473227073835,\n              47.25857286501821\n            ],\n            [\n              -69.06116066206772,\n              47.51130156334898\n            ],\n            [\n              -71.18990395428646,\n              45.21595765124482\n            ],\n            [\n              -74.64906462208842,\n              44.958321658703426\n            ],\n            [\n              -77.16670105999457,\n              41.68183359906362\n            ],\n            [\n              -82.15942155266379,\n              36.60328960559353\n            ],\n            [\n              -77.26577580636953,\n              36.4871201165721\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Center Director, <a href=\"https://www.usgs.gov/centers/geology-energy-and-minerals-science-center/connect\" data-mce-href=\"https://www.usgs.gov/centers/geology-energy-and-minerals-science-center/connect\">Geology, Energy &amp; Minerals Science Center</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"https://pubs.er.usgs.gov/contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Geologic Carbon Storage</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-11-06","noUsgsAuthors":false,"publicationDate":"2023-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Warwick, Peter D. 0000-0002-3152-7783","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":207248,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":887247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":887248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brennan, Sean T. 0000-0002-7102-9359","orcid":"https://orcid.org/0000-0002-7102-9359","contributorId":204982,"corporation":false,"usgs":true,"family":"Brennan","given":"Sean T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":887249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cahan, Steven M. 0000-0002-4776-3668","orcid":"https://orcid.org/0000-0002-4776-3668","contributorId":205929,"corporation":false,"usgs":true,"family":"Cahan","given":"Steven M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":887250,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":887251,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":887252,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Merrill, Matthew D. 0000-0003-3766-847X","orcid":"https://orcid.org/0000-0003-3766-847X","contributorId":205698,"corporation":false,"usgs":true,"family":"Merrill","given":"Matthew D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":887253,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70249944,"text":"70249944 - 2023 - Thirty years of regional groundwater-quality trend studies in the United States: Major findings and lessons learned","interactions":[],"lastModifiedDate":"2023-11-20T17:45:12.269668","indexId":"70249944","displayToPublicDate":"2023-11-04T06:53:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Thirty years of regional groundwater-quality trend studies in the United States: Major findings and lessons learned","docAbstract":"<div id=\"ab015\" class=\"abstract author\"><div id=\"as015\"><p id=\"sp0015\">Changes in groundwater quality have been evaluated for more than 2,200 wells in 25 Principal Aquifers in the United States based on repeated decadal sampling (once every 10 years) from 1988 to 2021. The purpose of this study is to identify contaminants with changing concentrations, the locations and magnitude of those changes, the factors driving those changes, the obstacles to interpreting the changes, and approaches to ameliorate those obstacles. Sampling was conducted in 89 networks of 20–30 wells each that represent various geographic regions, aquifer types and land use types. Each network, and the wells that comprise them, are sampled on a rotating basis once every 10 years. Of the 28 constituents evaluated for trends, concentrations of Na, Cl, dissolved solids, SO<sub>4</sub>, and NO<sub>3</sub><span>&nbsp;</span>exhibited statistically significant increases at the network level more frequently than other constituents. Factors affecting trends in Cl and NO<sub>3</sub><span>&nbsp;</span>are emphasized in this study. Regional patterns show large increases of Cl in urban areas in the Northeast and Midcontinent, where road-deicing salt application rates are 10 to 100 times greater than in other regions of the country, and in semiarid and arid regions of the western United States, where evaporation concentrates solutes in recharge. The largest increases in NO<sub>3</sub><span>&nbsp;</span>were in agricultural areas of the semiarid west, arid west and Pacific regions which are characterized by oxic groundwater, long-term increases in nitrogen fertilizer usage, and high rates of irrigation. However, finding a direct relation between increasing contaminant sources and corresponding groundwater quality response, particularly when sampling once every 10 years, can be complicated by factors such as uncertainty in the timing, mass, and location of contaminant sources, groundwater residence time (recharge date), geochemical conditions in the aquifer that affect contaminant transport, and variability in water quality due to climatic factors such as seasonality and hydrologic conditions. Understanding groundwater residence time allows the changes in groundwater quality to be evaluated in the context of recharge date rather than the sample date. Likewise, information on geochemical characteristics of the aquifer can be helpful for understanding relations between contaminant source inputs and groundwater concentrations. For example, oxic geochemical conditions in the aquifer may allow for conservative transport and accumulation of NO<sub>3</sub><span>&nbsp;</span>in groundwater, whereas reducing environments could favor NO<sub>3</sub><span>&nbsp;</span>degradation. Differences in hydrologic conditions (wetter or drier than average) on the date of sampling could impact the statistical results of sampling at decadal intervals and obscure long-term patterns. Samples collected under substantially different hydrologic conditions can be identified, and high-frequency sampling can improve interpretation of measured results in these cases. Although decadal sampling and associated water-quality interpretations have limitations, repeated, scheduled sampling of thousands of wells over multiple decades has great value for identifying and understanding long-term, regional groundwater-quality trends. Despite these limitations, the concepts presented herein provide options that could be used to interpret trends or changes when sampling over longer timespans, which is less common than trend networks with higher frequency sampling intervals.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.130427","usgsCitation":"Lindsey, B.D., Fleming, B.J., Goodling, P.J., and May, A.N., 2023, Thirty years of regional groundwater-quality trend studies in the United States: Major findings and lessons learned: Journal of Hydrology, v. 627, no. 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,{"id":70249916,"text":"70249916 - 2023 - Two centuries of southwest Iceland annually-resolved marine temperature reconstructed from Arctica islandica shells","interactions":[],"lastModifiedDate":"2023-11-07T12:37:58.835524","indexId":"70249916","displayToPublicDate":"2023-11-04T06:37:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Two centuries of southwest Iceland annually-resolved marine temperature reconstructed from Arctica islandica shells","docAbstract":"<div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Iceland's exposure to major ocean current pathways of the central North Atlantic makes it a useful location for developing long-term proxy records of past marine climate. Such records provide more detailed understanding of the full range of past variability which is necessary to improve predictions of future changes. We constructed a 225-year (1791–2015 CE) master shell growth chronology from 29 shells of<span>&nbsp;</span><i>Arctica islandica</i><span>&nbsp;</span>collected at 100&nbsp;m water depth in southwest Iceland (Faxaflói). The growth chronology provides a robust age model for shell oxygen isotope (δ<sup>18</sup>O<sub>shell</sub>) data produced at annual resolution for 251 years (1765–2015 CE). The temperature reconstruction derived from δ<sup>18</sup>O<sub>shell</sub><span>&nbsp;</span>shows coherence with May–October local surface temperature records and sea surface temperatures in the North Atlantic region, suggesting it is a useful proxy indicator of water temperature variability at 100&nbsp;m depth within Faxaflói. Field correlations between the shell-based records and gridded sea surface temperature data reveal strong positive correlations between the 1-year lagged shell growth and temperatures within the subpolar gyre post-1972, suggesting a delayed influence of subpolar gyre dynamics on ecological indicators in southwest Iceland in recent decades. However, the shell growth chronology and δ<sup>18</sup>O<sub>shell</sub><span>&nbsp;</span>record generally show relatively weak and insignificant correlations with larger region climate indices including the Atlantic Multidecadal Variability, North Atlantic Oscillation, and East Atlantic pattern. Therefore the interannual variations in the newly produced shell-based records appear to reflect more local to regional dynamics around southwest Iceland than large-scale modes of climate variability.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2023.108525","usgsCitation":"Mette, M.J., Andersson, C., Schöne, B., Bonitz, F., Melvik, V., Trofimova, T., and Miles, M., 2023, Two centuries of southwest Iceland annually-resolved marine temperature reconstructed from Arctica islandica shells: Estuarine, Coastal and Shelf Science, v. 294, 108525, 11 p., https://doi.org/10.1016/j.ecss.2023.108525.","productDescription":"108525, 11 p.","ipdsId":"IP-148228","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":441688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2023.108525","text":"Publisher Index Page"},{"id":422414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iceland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-14.5087,66.45589],[-14.73964,65.80875],[-13.60973,65.12667],[-14.90983,64.36408],[-17.79444,63.67875],[-18.65625,63.49638],[-19.97275,63.64363],[-22.76297,63.96018],[-21.77848,64.40212],[-23.95504,64.89113],[-22.1844,65.08497],[-22.22742,65.37859],[-24.32618,65.61119],[-23.65051,66.26252],[-22.13492,66.41047],[-20.57628,65.73211],[-19.05684,66.2766],[-17.79862,65.99385],[-16.16782,66.52679],[-14.5087,66.45589]]]},\"properties\":{\"name\":\"Iceland\"}}]}","volume":"294","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mette, Madelyn Jean 0000-0002-4504-8847","orcid":"https://orcid.org/0000-0002-4504-8847","contributorId":279717,"corporation":false,"usgs":true,"family":"Mette","given":"Madelyn","email":"","middleInitial":"Jean","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":887694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersson, Carin","contributorId":300778,"corporation":false,"usgs":false,"family":"Andersson","given":"Carin","affiliations":[{"id":65258,"text":"NORCE Norwegian Research Centre and Bjerknes Centre for Climate Research, Norway","active":true,"usgs":false}],"preferred":false,"id":887695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schöne, Bernd","contributorId":331433,"corporation":false,"usgs":false,"family":"Schöne","given":"Bernd","affiliations":[{"id":79208,"text":"Institute of Geosciences, University of Mainz, Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":887696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonitz, Fabian","contributorId":331434,"corporation":false,"usgs":false,"family":"Bonitz","given":"Fabian","email":"","affiliations":[{"id":79209,"text":"NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research","active":true,"usgs":false}],"preferred":false,"id":887697,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Melvik, Vilde","contributorId":331435,"corporation":false,"usgs":false,"family":"Melvik","given":"Vilde","email":"","affiliations":[{"id":79209,"text":"NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research","active":true,"usgs":false}],"preferred":false,"id":887698,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Trofimova, Tamara","contributorId":331436,"corporation":false,"usgs":false,"family":"Trofimova","given":"Tamara","email":"","affiliations":[{"id":79209,"text":"NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research","active":true,"usgs":false}],"preferred":false,"id":887699,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miles, Martin","contributorId":331437,"corporation":false,"usgs":false,"family":"Miles","given":"Martin","email":"","affiliations":[{"id":79209,"text":"NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research","active":true,"usgs":false}],"preferred":false,"id":887700,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70249297,"text":"fs20233036 - 2023 - The 3D Elevation Program—Supporting Maine’s economy","interactions":[],"lastModifiedDate":"2024-01-25T17:25:43.988085","indexId":"fs20233036","displayToPublicDate":"2023-11-03T13:05:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3036","displayTitle":"The 3D Elevation Program—Supporting Maine’s Economy","title":"The 3D Elevation Program—Supporting Maine’s economy","docAbstract":"<h1>Introduction</h1><p>Inland flooding, sea-level rise, and pollution pose challenges for Maine’s infrastructure and natural resources. A highly detailed, three-dimensional (3D) model of the Earth’s surface is allowing the State of Maine to address these challenges in an increasingly comprehensive and timely manner. In addition, highly accurate elevation data facilitate land development, forest management, agricultural practices, and wildlife conservation, all of which are key pillars of Maine’s economy. 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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/programs/national-geospatial-program\" data-mce-href=\"https://www.usgs.gov/programs/national-geospatial-program\">National Geospatial Program</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive, Mail Stop 511<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:3DEP@usgs.gov\" data-mce-href=\"mailto:3DEP@usgs.gov\">3DEP@usgs.gov</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Flood Risk Management</li><li>Natural Resources Conservation</li><li>Coastal Zone Management</li><li>Forest Resources Management</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-11-03","noUsgsAuthors":false,"publicationDate":"2023-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Walters, Dan","contributorId":291381,"corporation":false,"usgs":true,"family":"Walters","given":"Dan","email":"","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":885344,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70255246,"text":"70255246 - 2023 - Reach-scale associations between introduced Brook Trout and juvenile and stream-resident Bull Trout in Idaho","interactions":[],"lastModifiedDate":"2024-06-14T15:39:29.933098","indexId":"70255246","displayToPublicDate":"2023-11-03T10:33:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13429,"text":"Transactions of American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Reach-scale associations between introduced Brook Trout and juvenile and stream-resident Bull Trout in Idaho","docAbstract":"<h3 id=\"tafs10443-sec-2001-title\" class=\"article-section__sub-title section1\">Objective</h3><p>Native Bull Trout<span>&nbsp;</span><i>Salvelinus confluentus</i><span>&nbsp;</span>populations can be influenced by a variety of stressors operating at multiple spatial scales, making the relative importance of biotic versus abiotic controls difficult to discern at small scales where monitoring and management typically occur. Nonnative Brook Trout<span>&nbsp;</span><i>S. fontinalis</i><span>&nbsp;</span>were widely introduced throughout western North America and negatively affect Bull Trout occurrence. Here, we examine reach-scale associations between nonnative Brook Trout and juvenile and stream-resident Bull Trout (i.e., &lt;250 mm) abundances through the lens of a constraining threshold, where nonnative fish&nbsp;exceeding a certain fish density may constrain native fish abundance.</p><h3 id=\"tafs10443-sec-2002-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We used a large spatial data set to define the abiotic conditions in which stream-dwelling Brook Trout and Bull Trout smaller than 250 mm typically co-occur in Idaho. Next, we queried multipass electrofishing survey data collected in reaches with abiotic conditions suitable for both species within localized areas where their distributions overlap. We then used two-dimensional Kolmogorov–Smirnov tests to identify threshold Brook Trout densities beyond which Bull Trout less than 250 mm were consistently rare or absent.</p><h3 id=\"tafs10443-sec-2003-title\" class=\"article-section__sub-title section1\">Result</h3><p>Bull Trout smaller than 250 mm were rare or absent where Brook Trout density exceeded 0.54 fish/100 m<sup>2</sup><span>&nbsp;</span>across the full range of abiotic conditions over which both species overlapped. However, Brook Trout rarely occurred in habitats associated with high Bull Trout density (e.g., where mean August water temperatures were 8.2°C).</p><h3 id=\"tafs10443-sec-2004-title\" class=\"article-section__sub-title section1\">Conclusion</h3><p>Our results support existing hypotheses that the long-term co-occurrence of Bull Trout and Brook Trout in stream reaches suitable for both species may be unstable. Because low densities of Brook Trout appear to threaten Bull Trout, additional research is needed to better understand factors driving ongoing range shifts and invasion dynamics in Bull Trout habitat. We provide a simple tool to inform where Brook Trout represent a primary threat to Bull Trout, with potential applications for future monitoring, threat assessments, and conservation efforts.</p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10443","usgsCitation":"Voss, N.S., Bowersox, B.J., and Quist, M.C., 2023, Reach-scale associations between introduced Brook Trout and juvenile and stream-resident Bull Trout in Idaho: Transactions of American Fisheries Society, v. 152, no. 6, p. 835-848, https://doi.org/10.1002/tafs.10443.","productDescription":"14 p.","startPage":"835","endPage":"848","ipdsId":"IP-151044","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":498854,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10443","text":"Publisher Index Page"},{"id":430209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.03090213547928,\n              43.207652040414814\n            ],\n            [\n              -111.03202746708995,\n              43.2200826637544\n            ],\n            [\n              -111.0540054745273,\n              44.480723993881384\n            ],\n            [\n              -111.38063590540663,\n              44.7211838491711\n            ],\n            [\n              -112.32600707694,\n              44.55386220030201\n            ],\n            [\n              -112.43093922496412,\n              44.442261666637535\n            ],\n            [\n              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0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903855,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70253016,"text":"70253016 - 2023 - Multi-year tracing of spatial and temporal dynamics of post-fire aeolian sediment transport using rare earth elements provide insights into grassland management","interactions":[],"lastModifiedDate":"2024-04-16T15:28:42.457575","indexId":"70253016","displayToPublicDate":"2023-11-03T10:21:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7357,"text":"JGR Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Multi-year tracing of spatial and temporal dynamics of post-fire aeolian sediment transport using rare earth elements provide insights into grassland management","docAbstract":"<p><span>Aeolian sediment transport occurs as a function of, and with feedback to ecosystem changes and disturbances. Many desert grasslands are undergoing rapid changes in vegetation, including the encroachment of woody plants, which alters fire regimes and in turn can change the spatial and temporal patterns of aeolian sediment transport. We investigated aeolian sediment transport and spatial distribution of sediment in the surface soil for 7&nbsp;years following a prescribed fire using a multiple rare earth element (REE) tracer-based approach in a shrub-encroached desert grassland in the northern Chihuahuan desert. Results indicate that even though the aeolian horizontal sediment mass flux increased approximately three-fold in the first windy season in the burned areas compared to control areas, there were no significant differences after three windy seasons. The soil surface of bare microsites was the major contributor of aeolian sediments in unburned areas (87%), while the shrub microsites contributed the least (&lt;2%) during the observation period. However, after the prescribed fire, the contribution of aeolian sediments from shrub microsites increased considerably (∼40%), indicating post-fire microsite-scale sediment redistribution. The findings of this study, which is the first to use multiple REE tracers for multi-year analysis of the spatial and temporal dynamics of aeolian sediment transport, illustrate how disturbance by prescribed fire can influence aeolian processes and alters dryland soil geomorphology in which distinct soils develop over time at very fine spatial scales of individual plants.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JF007274","usgsCitation":"Burger, W., Van Pelt, R., Grandstaff, D.E., Wang, G., Sankey, T.T., Li, J., Sankey, J., and Ravi, S., 2023, Multi-year tracing of spatial and temporal dynamics of post-fire aeolian sediment transport using rare earth elements provide insights into grassland management: JGR Earth Surface, v. 128, no. 11, e2023JF007274, 14 p., https://doi.org/10.1029/2023JF007274.","productDescription":"e2023JF007274, 14 p.","ipdsId":"IP-152706","costCenters":[{"id":568,"text":"Southwest Biological Science 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Pelt","given":"Robert","email":"","affiliations":[{"id":80456,"text":"Wind Erosion and Water Conservation Research, USDA-ARS, Big Spring, TX, USA","active":true,"usgs":false}],"preferred":false,"id":898935,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grandstaff, David E.","contributorId":202739,"corporation":false,"usgs":false,"family":"Grandstaff","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":36520,"text":"Department of Earth and Environmental Science, Temple University","active":true,"usgs":false}],"preferred":false,"id":898936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Guan","contributorId":202741,"corporation":false,"usgs":false,"family":"Wang","given":"Guan","email":"","affiliations":[{"id":36521,"text":"Department of Geosciences, University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":898937,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":898938,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Junran","contributorId":202740,"corporation":false,"usgs":false,"family":"Li","given":"Junran","email":"","affiliations":[{"id":36521,"text":"Department of Geosciences, University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":898939,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898940,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ravi, 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,{"id":70249893,"text":"70249893 - 2023 - Probabilistic source classification of large tephra producing eruptions using supervised machine learning: An example from the Alaska-Aleutian arc","interactions":[],"lastModifiedDate":"2023-11-04T13:41:33.169601","indexId":"70249893","displayToPublicDate":"2023-11-03T08:38:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic source classification of large tephra producing eruptions using supervised machine learning: An example from the Alaska-Aleutian arc","docAbstract":"<div class=\"article-section__content en main\"><p>Alaska contains over 130 volcanoes and volcanic fields that have been active within the last 2 million years. Of these, roughly 90 have erupted during the Holocene, with many characterized by at least one large explosive eruption. These large tephra-producing eruptions (LTPEs) generate orders of magnitude more erupted material than a “typical” arc explosive eruption and distribute ash thousands of kilometers from their source. Because LTPEs occur infrequently, and the proximal explosive deposit record in Alaska is generally limited to the Holocene, we require a method that links distal deposits to a source volcano where the correlative proximal deposits from that eruption are no longer preserved. We present a model that accurately and confidently identifies LTPE volcanic sources in the Alaska-Aleutian arc using only in situ geochemistry. The model is a voting ensemble classifier comprised of six conceptually different machine learning algorithms trained on proximal tephra deposits that have had their source positively identified. We show that incompatible trace element ratios (e.g., Nb/U, Th/La, Rb/Sm) help produce a feature space that contains significantly more variance than one produced by major element concentrations, ultimately creating a model that can achieve high accuracy, precision, and recall on predicted volcanic sources, regardless of the perceived 2D data distribution (i.e., bimodal, uniform, normal) or composition (i.e., andesite, trachyte, rhyolite) of that source. Finally, we apply our model to unidentified distal marine tephra deposits in the region to better understand explosive volcanism in the Alaska-Aleutian arc, specifically its pre-Holocene spatiotemporal distribution.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GC011037","usgsCitation":"Lubbers, J.E., Loewen, M.W., Wallace, K.L., Coombs, M.L., and Addison, J.A., 2023, Probabilistic source classification of large tephra producing eruptions using supervised machine learning: An example from the Alaska-Aleutian arc: Geochemistry, Geophysics, Geosystems, v. 24, no. 11, e2023GC011037, 32 p., https://doi.org/10.1029/2023GC011037.","productDescription":"e2023GC011037, 32 p.","ipdsId":"IP-153612","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":441693,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gc011037","text":"Publisher Index Page"},{"id":422393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -133.08003662231607,\n              57.22654031267055\n            ],\n            [\n              -136.06831787231613,\n              59.75177682633975\n            ],\n            [\n              -139.75972412231607,\n              61.223543890524866\n            ],\n            [\n              -145.03316162231616,\n              63.07071371777923\n            ],\n            [\n              -153.2069897473162,\n              62.26365593788125\n            ],\n            [\n              -156.89839599731616,\n              59.30608826772951\n            ],\n            [\n              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Matthew W. 0000-0002-5621-285X","orcid":"https://orcid.org/0000-0002-5621-285X","contributorId":213321,"corporation":false,"usgs":true,"family":"Loewen","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":887575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":887576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 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,{"id":70249908,"text":"70249908 - 2023 - CreelCat, a Catalog of United States Inland Creel and Angler Survey Data","interactions":[],"lastModifiedDate":"2023-11-04T13:13:47.039354","indexId":"70249908","displayToPublicDate":"2023-11-03T08:10:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"CreelCat, a Catalog of United States Inland Creel and Angler Survey Data","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>The United States Inland Creel and Angler Survey Catalog (CreelCat) contains a national compilation of angler and creel survey data collected by natural resource management agencies across the United States (including Washington, D.C. and Puerto Rico). These surveys are used to help inform the management of recreational fisheries, by collecting information about anglers including what they are catching and harvesting, the amount of effort they expend, their angling preferences, and demographic information. As of May 1, 2023, CreelCat houses over 14,729 surveys from 33 states, Puerto Rico, and Washington, D.C., comprising 235 data fields across 8 tables. These tables contain 235,015 records of fish catch and harvest metrics, 27,250 angler preference metrics, 14,729 records of survey characteristics, 13,576 records of effort metrics, and 409 records of angler demographics. Though individual creel surveys are often deployed to meet local science and management objectives, creel data aggregated across jurisdictions has the potential to address larger scale research and management needs.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41597-023-02523-2","usgsCitation":"Sievert, N.A., Lynch, A., Embke, H.S., Robertson, A., Lang, M., Kaz, A., Robertson, M., Midway, S.R., Wszola, L.S., and Paukert, C.P., 2023, CreelCat, a Catalog of United States Inland Creel and Angler Survey Data: Scientific Data, v. 10, 762, 9 p., https://doi.org/10.1038/s41597-023-02523-2.","productDescription":"762, 9 p.","ipdsId":"IP-152029","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":441696,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-023-02523-2","text":"Publisher Index 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,{"id":70250089,"text":"70250089 - 2023 - Growth of coal mining operations in the Elk River Valley (Canada) linked to increasing solute transport of Se, NO3-, and SO42- into the transboundary Koocanusa Reservoir (USA-Canada)","interactions":[],"lastModifiedDate":"2023-11-17T12:48:03.643931","indexId":"70250089","displayToPublicDate":"2023-11-03T06:43:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Growth of coal mining operations in the Elk River Valley (Canada) linked to increasing solute transport of Se, NO3-, and SO42- into the transboundary Koocanusa Reservoir (USA-Canada)","docAbstract":"<div id=\"abstractBox\" class=\"article_abstract-content hlFld-Abstract\"><p class=\"articleBody_abstractText\">Koocanusa Reservoir (KOC) is a waterbody that spans the United States (U.S.) and Canadian border. Increasing concentrations of total selenium (Se), nitrate + nitrite (NO<sub>3</sub><sup>–</sup>, nitrite is insignificant or not present), and sulfate (SO<sub>4</sub><sup>2–</sup>) in KOC and downstream in the Kootenai River (Kootenay River in Canada) are tied to expanding coal mining operations in the Elk River Watershed, Canada. Using a paired watershed approach, trends in flow-normalized concentrations and loads were evaluated for Se, NO<sub>3</sub><sup>–</sup>, and SO<sub>4</sub><sup>2–</sup><span>&nbsp;</span>for the two largest tributaries, the Kootenay and Elk Rivers, Canada. Increases in concentration (SO<sub>4</sub><sup>2–</sup><span>&nbsp;</span>120%, Se 581%, NO<sub>3</sub><sup>–</sup><span>&nbsp;</span>784%) and load (SO<sub>4</sub><sup>2–</sup><span>&nbsp;</span>129%, Se 443%, NO<sub>3</sub><sup>–</sup><span>&nbsp;</span>697%) in the Elk River (1979–2022 for NO<sub>3</sub><sup>–</sup>, 1984–2022 for Se and SO<sub>4</sub><sup>2–</sup>) are among the largest documented increases in the primary literature, while only a small magnitude increase in SO<sub>4</sub><sup>2–</sup><span>&nbsp;</span>(7.7% concentration) and decreases in Se (−10%) and NO<sub>3</sub><sup>–</sup><span>&nbsp;</span>(−8.5%) were observed in the Kootenay River. Between 2009 and 2019, the Elk River contributed, on average, 29% of the combined flow, 95% of the Se, 76% of the NO<sub>3</sub><sup>–</sup>, and 38% of the SO<sub>4</sub><sup>2–</sup><span>&nbsp;</span>entering the reservoir from these two major tributaries. The largest increase in solute concentrations occurred during baseflows, indicating a change in solute transport and delivery dynamics in the Elk River Watershed, which may be attributable to altered landscapes from coal mining operations including altered groundwater flow paths and increased chemical weathering in waste rock dumps. More recently there is evidence of surface water treatment operations providing some reduction in concentrations during low flow times of year; however, these appear to have a limited effect on annual loads entering KOC. These findings imply that current mine water treatment, which is focused on surface waters, may not sufficiently reduce the influence of mine-waste-derived solutes in the Elk River to allow constituent concentrations in KOC to meet U.S. water-quality standards.</p></div>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.3c05090","usgsCitation":"Storb, M.B., Bussell, A.M., Caldwell Eldridge, S.L., Hirsch, R.M., and Schmidt, T., 2023, Growth of coal mining operations in the Elk River Valley (Canada) linked to increasing solute transport of Se, NO3-, and SO42- into the transboundary Koocanusa Reservoir (USA-Canada): Environmental Science and Technology, v. 57, no. 45, p. 17465-17480, https://doi.org/10.1021/acs.est.3c05090.","productDescription":"16 p.","startPage":"17465","endPage":"17480","ipdsId":"IP-147512","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":441698,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.3c05090","text":"Publisher Index Page"},{"id":422674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.04695939656004,\n              52.642544219500934\n            ],\n            [\n              -118.04695939656004,\n              48.428632763883456\n            ],\n            [\n              -112.86141252155994,\n              48.428632763883456\n            ],\n            [\n              -112.86141252155994,\n              52.642544219500934\n            ],\n            [\n              -118.04695939656004,\n              52.642544219500934\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"57","issue":"45","noUsgsAuthors":false,"publicationDate":"2023-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Storb, Meryl Biesiot 0000-0002-4346-5022","orcid":"https://orcid.org/0000-0002-4346-5022","contributorId":305621,"corporation":false,"usgs":true,"family":"Storb","given":"Meryl","email":"","middleInitial":"Biesiot","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bussell, Ashley Morgan 0000-0003-4586-7305","orcid":"https://orcid.org/0000-0003-4586-7305","contributorId":303898,"corporation":false,"usgs":true,"family":"Bussell","given":"Ashley","email":"","middleInitial":"Morgan","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":888281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell Eldridge, Sara L. 0000-0001-8838-8940 seldridge@usgs.gov","orcid":"https://orcid.org/0000-0001-8838-8940","contributorId":4981,"corporation":false,"usgs":true,"family":"Caldwell Eldridge","given":"Sara","email":"seldridge@usgs.gov","middleInitial":"L.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":888282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":888283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":888284,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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