Coordinated wildlife disease surveillance (WDS) can help professionals across disciplines effectively safeguard human, animal, and environmental health. The aims of this study were to understand how WDS in Thailand is utilized, valued, and can be improved within a One Health framework. An online questionnaire was distributed to 183 professionals (55.7% response rate) across Thailand working in wildlife, marine animal, livestock, domestic animal, zoo animal, environmental, and public health sectors. Twelve semi-structured interviews with key professionals were then performed. Three-quarters of survey respondents reported using WDS data and information. Sectors agreed upon ranking disease control (76.5% of respondents) as the most beneficial outcome of WDS, while fostering new ideas through collaboration was valued by few participants (2.0%). Accessing data collected by ones own sector was identified as the most challenging (50%) yet least difficult to improve (88.3%). Having legal authority to conduct WDS was the second most frequently identified challenge. Interviewees explained that legal documentation required for crossinstitutional collaborations posed a barrier to efficient communication and use of human resources. Survey respondents identified allocation of human resources (75.5%), adequate budget (71.6%), and having a clear communication system between sectors (71.6%) as highest priority areas for improvement to WDS in Thailand. Authorization from administrative officials and support from local community members were identified as challenges during in-person interviews. Future outreach should be directed towards these groups. As 42.9% of marine health professionals had difficulty knowing whom to contact in other sectors and 28.4% of survey respondents indicated that communication with marine health professionals was not applicable to their work, connecting the marine sector with other sectors may be prioritized. This study identifies priorities for addressing current challenges in the establishment of a general WDS system and information management system in Thailand while presenting a model for such evaluation in other regions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.onehlt.2023.100600","usgsCitation":"George, S.E., Smink, M., Sangkachai, N., Wiratsudakul, A., Sakcamduang, W., Suwanpakdee, S., and Sleeman, J.M., 2023, Stakeholder attitudes and perspectives on wildlife disease surveillance as a component of a One Health approach in Thailand: One Health Newsletter, v. 17, 100600, 10 p., https://doi.org/10.1016/j.onehlt.2023.100600.","productDescription":"100600, 10 p.","ipdsId":"IP-154964","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":442811,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.onehlt.2023.100600","text":"Publisher Index 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Serena Elise","contributorId":317781,"corporation":false,"usgs":false,"family":"George","given":"Serena","email":"","middleInitial":"Elise","affiliations":[{"id":69152,"text":"University of Wisconsin-Madison, School of Veterinary Medicine","active":true,"usgs":false}],"preferred":false,"id":879297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smink, Moniek","contributorId":317782,"corporation":false,"usgs":false,"family":"Smink","given":"Moniek","email":"","affiliations":[{"id":69153,"text":"University of Wisconsin-Madison, Department of Computer Sciences,","active":true,"usgs":false}],"preferred":false,"id":879298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sangkachai, Nareerat","contributorId":317783,"corporation":false,"usgs":false,"family":"Sangkachai","given":"Nareerat","email":"","affiliations":[{"id":69154,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science & The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals","active":true,"usgs":false}],"preferred":false,"id":879299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiratsudakul, Anuwat","contributorId":317784,"corporation":false,"usgs":false,"family":"Wiratsudakul","given":"Anuwat","email":"","affiliations":[{"id":69155,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science, The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals & Department of Clinical Sciences and Public Health, Faculty of Veterinary Science","active":true,"usgs":false}],"preferred":false,"id":879300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sakcamduang, Walasinee","contributorId":317785,"corporation":false,"usgs":false,"family":"Sakcamduang","given":"Walasinee","email":"","affiliations":[{"id":69156,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science & Department of Clinical Sciences and Public Health, Faculty of Veterinary Science","active":true,"usgs":false}],"preferred":false,"id":879301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Suwanpakdee, Sarin","contributorId":317786,"corporation":false,"usgs":false,"family":"Suwanpakdee","given":"Sarin","email":"","affiliations":[{"id":69155,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science, The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals & Department of Clinical Sciences and Public Health, Faculty of Veterinary Science","active":true,"usgs":false}],"preferred":false,"id":879302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":879303,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70246562,"text":"70246562 - 2023 - Dissolved organic carbon dynamics and fluxes in Mississippi-Atchafalaya deltaic system impacted by an extreme flood event and hurricanes: A multi-satellite approach using Sentinel-2/3 and Landsat-8/9 data","interactions":[],"lastModifiedDate":"2023-07-10T15:42:41.208404","indexId":"70246562","displayToPublicDate":"2023-07-10T10:15:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Dissolved organic carbon dynamics and fluxes in Mississippi-Atchafalaya deltaic system impacted by an extreme flood event and hurricanes: A multi-satellite approach using Sentinel-2/3 and Landsat-8/9 data","docAbstract":"Transport of riverine and wetland-derived dissolved organic carbon (DOC) spanning tidal wetlands, estuaries, and continental shelf waters functionally connects terrestrial and aquatic carbon reservoirs, yet the magnitude and ecological significance of this variable and its spatiotemporal linkage remains uncertain for coastal deltaic regions, such as Mississippi River Delta Plain, which includes Mississippi (MR) and Atchafalaya (AR) rivers and estuaries with vast expanses of wetlands and coastal forests. We examined DOC dynamics and fluxes in this large river-dominated wetland-estuarine system for the period between 2019 and 2021 that included an extreme river flood event in 2019, two major hurricanes (Barry in 2019 and Ida in 2021), and cold front passage using an improved adaptive quasi-analytical algorithm (QAA-AD) applied to multi-satellite sensors (Sentinel 3A/B OLCI, Landsat-8/OLI and Sentinel-2A/B MSI) with varying spectral and spatial (10/30/300 m) resolutions. The DOC estimates from multi-satellite sensors in combination with water fluxes were used to assess DOC fluxes from two large rivers (MR and AR) and small channels across the delta plain. Overall, this system delivered a total of 6.7 Tg C yr-1 (1 Tg = 1012g) into the estuarine zone and the northern Gulf of Mexico (nGoM) during 2019. High DOC fluxes from the AR (1.3 Tg C yr-1) and MR (4.5 Tg C yr-1) were associated with the extreme flood event in 2019. Hurricanes that occurred in the study period also contributed to the wetland and estuarine DOC fluxes into continental shelf waters; for example, the passage of Hurricane Barry in July 2019, delivered over a 3-day period ~1.33 ×109 g DOC from Barataria Basin into the nGoM. Sentinel 2-MSI land and water classification revealed that Hurricane Ida eroded a total of 1.34×108 m2 of marshes in middle Barataria Basin, converting those habitats into open water with 3.0 m inundation depth and high DOC concentrations (16.4 mg L-1), a potentially large DOC source to the coastal waters. Overall, storms and flood events are major sources of DOC flux that facilitate transport of upstream carbon as well as transformation of carbon in the wetlands, through the conversion of vegetated wetland to open water.
","language":"English","publisher":"Frontiers Media S.A.","doi":"10.3389/fmars.2023.1159367","usgsCitation":"Liu, B., D’Sa, E.J., Messina, F., Baustian, M.M., Maiti, K., Rivera-Monroy, V.H., Huang, W., and Georgiou, I.Y., 2023, Dissolved organic carbon dynamics and fluxes in Mississippi-Atchafalaya deltaic system impacted by an extreme flood event and hurricanes: A multi-satellite approach using Sentinel-2/3 and Landsat-8/9 data: Frontiers in Marine Science, v. 10, 1159367, 24 p., https://doi.org/10.3389/fmars.2023.1159367.","productDescription":"1159367, 24 p.","ipdsId":"IP-148973","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2023.1159367","text":"Publisher Index Page"},{"id":418810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Atchafalaya River, Mississippi River, Mississippi River Delta Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.31893133610087,\n 30.458926156651998\n ],\n [\n -92.31893133610087,\n 27.86368380104267\n ],\n [\n -89.10966256396617,\n 27.86368380104267\n ],\n [\n -89.10966256396617,\n 30.458926156651998\n ],\n [\n -92.31893133610087,\n 30.458926156651998\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2023-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Bingqing","contributorId":304014,"corporation":false,"usgs":false,"family":"Liu","given":"Bingqing","email":"","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":877207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Sa, Eurico J.","contributorId":316255,"corporation":false,"usgs":false,"family":"D’Sa","given":"Eurico","email":"","middleInitial":"J.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":877208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Messina, Francesca","contributorId":316256,"corporation":false,"usgs":false,"family":"Messina","given":"Francesca","email":"","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":877209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baustian, Melissa Millman 0000-0003-2467-2533","orcid":"https://orcid.org/0000-0003-2467-2533","contributorId":304015,"corporation":false,"usgs":true,"family":"Baustian","given":"Melissa","email":"","middleInitial":"Millman","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":877210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maiti, Kanchan","contributorId":316257,"corporation":false,"usgs":false,"family":"Maiti","given":"Kanchan","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":877211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":877212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huang, Wei","contributorId":316258,"corporation":false,"usgs":false,"family":"Huang","given":"Wei","email":"","affiliations":[{"id":40642,"text":"Oak Ridge National Lab","active":true,"usgs":false}],"preferred":false,"id":877213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Georgiou, Ioannis Y.","contributorId":205361,"corporation":false,"usgs":false,"family":"Georgiou","given":"Ioannis","email":"","middleInitial":"Y.","affiliations":[{"id":37089,"text":"Pontchartrain Institute for Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":877214,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70246625,"text":"70246625 - 2023 - BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species","interactions":[],"lastModifiedDate":"2023-07-12T12:15:02.02119","indexId":"70246625","displayToPublicDate":"2023-07-10T07:10:53","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":"BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species","docAbstract":"Aquatic invasive species (AIS) present major ecological and economic challenges globally, endangering ecosystems and human livelihoods. Managers and policy makers thus need tools to predict invasion risk and prioritize species and areas of concern, and they often use native range climate matching to determine whether a species could persist in a new location. However, climate matching for AIS often relies on air temperature rather than water temperature due to a lack of global water temperature data layers, and predictive power of models is seldom evaluated. We developed 12 global lake (water) temperature-derived “BioLake” bioclimatic layers for distribution modeling of aquatic species and compared “climatch” climate matching predictions (from climatchR package) from BioLake with those based on BioClim temperature layers and with a null model. We did this for 73 established AIS in the United States, training the models on their ranges outside of the United States and Canada. Models using either set of climate layers outperformed the null expectation by a similar (but modest) amount on average, but some species were occasionally found in locations with low climatch scores. Mean US climatch scores were higher for most species when using air temperature. Including additional climate layers in models reduced mean climatch scores, indicating that commonly used climatch score thresholds are not absolute but can be context specific and may require calibration based upon climate data used. Although finer resolution global lake temperature data would likely improve predictions, our BioLake layers provide a starting point for aquatic species distribution modeling. Climate matching was most effective for some species that originated at low latitudes or had small ranges. Climatch scores remain useful but limited for predicting AIS risk, perhaps because current ranges seldom fully reflect climatic tolerances (fundamental niches). Managers could consider climate matching as one of a suite of tools that can be used in AIS prioritization.
The Ibex Hollow Tuff, 12.08 ± 0.03 Ma (40Ar/39Ar), is a widespread tephra layer erupted from the Bruneau-Jarbidge volcanic field of southern Idaho. Tephra from this eruption was deposited across much of western and central North America and adjacent ocean areas. We identified the Ibex Hollow Tuff at Trapper Creek, Idaho, near its eruption site, and at 15 distal sites, from the Pacific Ocean to the Gulf of Mexico, by the chemical composition of its glass shards, using electron-microprobe analysis, instrumental neutron activation analysis, and laser-ablation–inductively coupled plasma–mass spectrometry. By these methods, we distinguished the Ibex Hollow Tuff from overlying and underlying tephra layers near its source and at distal sites. Fluvially reworked Ibex Hollow Tuff ash was transported by the ancestral Mississippi River drainage from the interior of the North American continent to the Gulf of Mexico, where it is present within an ~50-m-thick deposit in marine sediments in the subsurface. The minimum fallout area covered by the ash is ~2.7 million km2, with a minimum volume of ~800 km3, and potential dispersal farther to the north and northeast. The areal distribution for the Ibex Hollow Tuff is similar to that of the Lava Creek B (0.63 Ma) supereruption. The Ibex Hollow Tuff represents a unique chronostratigraphic marker allowing a synoptic view of paleoenvironments at a virtual moment in time across a large terrestrial and marine region. The Ibex Hollow Tuff is also an important marker bed for North American Land Mammal Ages, and it coincides with climatic cooling in the middle to late Miocene documented in marine cores.
The duration of inundation or saturation (i.e., hydroperiod) controls many wetland functions. In particular, it is a key determinant of whether a wetland will provide suitable breeding habitat for amphibians and other taxa that often have specific hydrologic requirements. Yet, scientists and land managers often are challenged by a lack of sufficient monitoring data to enable the understanding of the wetting and drying dynamics of small depressional wetlands. In this study, we present and evaluate an approach to predict daily inundation dynamics using a large wetland water-level dataset and a random forest algorithm. We relied on predictor variables that described characteristics of basin morphology of each wetland and atmospheric water budget estimates over various antecedent periods. These predictor variables were derived from datasets available over the conterminous United States making this approach potentially extendable to other locations. Model performance was evaluated using two metrics, median hydroperiod and the proportion of correctly classified days. We found that models performed well overall with a median balanced accuracy of 83% on validation data. Median hydroperiod was predicted most accurately for wetlands that were infrequently inundated and least accurate for permanent wetlands. The proportion of inundated days was predicted most accurately in permanent wetlands (99%) followed by frequently inundated wetlands (98%) and infrequently inundated wetlands (93%). This modeling approach provided accurate estimates of inundation and could be useful in other depressional wetlands where the primary water flux occurs with the atmosphere and basin morphology is a critical control on wetland inundation and hydroperiods.
Welcome to the resurrected series of U.S. Geological Survey (USGS) reports on stratigraphy entitled “Stratigraphic Notes.” For several decades, until the mid-1990s, the USGS published volumes of short papers that highlighted stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. The purpose was to encourage formal documentation on these topics.
Today (2023) the need for such documentation has become especially important because of the increasing number of informal reports that use new or updated stratigraphic nomenclature. Because the North American Stratigraphic Code does not recognize informal reports as proper publications to formalize stratigraphic studies, a report series such as “Stratigraphic Notes” is needed to bridge this gap.
“Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated into Geolex, https://ngmdb.usgs.gov/Geolex/). The papers in “Stratigraphic Notes” are meant to be an outlet to communicate changes in stratigraphic nomenclature, to support geologic map publications, and to facilitate compilation of new geologic maps and their databases.
The goal is to publish a new volume each year, each of which will contain papers that present results of stratigraphic studies drawn from scientific interpretations of stratigraphic and biostratigraphic changes related to changes in environments of deposition and facies, as well as interpretations of igneous and metamorphic units.
We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee (gnc@usgs.gov). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted here at https://doi.org/10.3133/pp1879.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1879","usgsCitation":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2023, Stratigraphic notes: U.S. Geological Survey Professional Paper 1879, https://doi.org/10.3133/pp1879.","productDescription":"Multiple volumes","onlineOnly":"Y","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":64806,"text":"National Cooperative Geologic Mapping","active":true,"usgs":true}],"links":[{"id":418718,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1879/covrthb_main.jpg"},{"id":480772,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1879V2","text":"Professional Paper 1879-2","description":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2025, Stratigraphic notes—Volume 2, 2025: U.S. Geological Survey Professional Paper 1879–2, 28 p., https://doi.org/10.3133/pp1879v2.","linkHelpText":"- Stratigraphic Notes—Volume 2, 2025 - Edited by: Randall C. Orndorff, Nancy R. Stamm, and David R. Soller"},{"id":419310,"rank":2,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1879v1","text":"Professional Paper 1879-1","description":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2023, Stratigraphic notes—Volume 1, 2022: U.S. Geological Survey Professional Paper 1879–1, 38 p., https://doi.org/10.3133/pp1879V1.","linkHelpText":"- Stratigraphic Notes - Volume 1, 2022 - Edited by: Randall C. Orndorff, Nancy R. Stamm, and David R. Soller"}],"contact":"National Cooperative Geologic Mapping Program
U.S. Geological Survey
12201 Sunrise Valley Drive Mail Stop 908
Reston, VA 20192
This is the first volume in the U.S. Geological Survey (USGS) series of reports on stratigraphy entitled “Stratigraphic Notes,” which consists of short papers that highlight stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. “Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated by National Geologic Map Database personnel into Geolex, https://ngmdb.usgs.gov/Geolex/).
We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee (gnc@usgs.gov). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted at https://doi.org/10.3133/pp1879.
This first volume (\"Stratigraphic notes—Volume 1, 2022\") includes articles that provide guidance for those who wish to submit papers to “Stratigraphic Notes,” as well as information on how to make your manuscripts compliant for geologic names reviews and how to organize your paper’s content to facilitate inclusion of new or revised names in Geolex. This volume also includes some specific guidance on conducting geologic names reviews of geologic and hydrogeologic reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1879V1","usgsCitation":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2023, Stratigraphic notes—Volume 1, 2022: U.S. Geological Survey Professional Paper 1879–1, 38 p., https://doi.org/10.3133/pp1879V1.","productDescription":"v, 38 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-127066","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":64806,"text":"National Cooperative Geologic Mapping","active":true,"usgs":true}],"links":[{"id":418722,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1.pdf","text":"Stratigraphic Notes—Volume 1, 2022","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- All Chapters"},{"id":418723,"rank":3,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1a.pdf","text":"Chapter A. \"Stratigraphic Notes”—An Outlet for Stratigraphic Studies","size":"150 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":418721,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1879/v1/covrthb.jpg"},{"id":418725,"rank":5,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1c.pdf","text":"Chapter C. Divisions of Geologic Time—Major Chronostratigraphic and Geochronologic Units","size":"250 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":480770,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1879V2","text":"Professional Paper 1879-2","description":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2025, Stratigraphic notes—Volume 2, 2025: U.S. Geological Survey Professional Paper 1879–2, 28 p., https://doi.org/10.3133/pp1879v2.","linkHelpText":"- Stratigraphic Notes—Volume 2, 2025"},{"id":480769,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1879","text":"Professional Paper 1879","description":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2023, Stratigraphic notes: U.S. Geological Survey Professional Paper 1879, https://doi.org/10.3133/pp1879.","linkHelpText":"- This publication is Volume 1 in Stratigraphic Notes"},{"id":418727,"rank":7,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1e.pdf","text":"Chapter E. Guidelines for Conducting Reviews of Geologic Names and Aquifer Names in U.S. Geological Survey Hydrogeologic Maps and Reports","size":"200 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":500194,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118314.htm","linkFileType":{"id":5,"text":"html"}},{"id":418724,"rank":4,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1b.pdf","text":"Chapter B. Suggestions for Proposing Changes in Nomenclature in Papers Submitted to “Stratigraphic Notes”","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":418726,"rank":6,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1d.pdf","text":"Chapter D. Guidance on Geologic Names Usage for Authors and Peer Reviewers of Geologic Maps and Reports—A Primer on Stratigraphic Nomenclature","size":"600 KB","linkFileType":{"id":1,"text":"pdf"}}],"volume":"1","contact":"National Cooperative Geologic Mapping Program
U.S. Geological Survey
12201 Sunrise Valley Drive Mail Stop 908
Reston, VA 20192
The steep, tectonically active terrain along the Central California (USA) coast is well known to produce deadly and destructive debris flows. However, the extent to which fire affects debris-flow susceptibility in this region is an open question. We documented the occurrence of postfire debris floods and flows following the landfall of a storm that delivered intense rainfall across multiple burn areas. We used this inventory to evaluate the predictive performance of the US Geological Survey M1 likelihood model, a tool that presently underlies the emergency assessment of postfire debris-flow hazards in the western USA. To test model performance, we used the threat score skill statistic and found that the rainfall thresholds estimated by the M1 model for the Central California coast performed similarly to training (Southern California) and testing (Intermountain West) data associated with the original model calibration. Model performance decreased when differentiating between “minor” and “major” postfire hydrologic response types, which weigh effects on human life and infrastructure. Our results underscore that the problem of false positives is a major challenge for developing accurate rainfall thresholds for the occurrence of postfire debris flows. As wildfire activity increases throughout the western USA, so too will the demand for the assessment of postfire debris-flow hazards. We conclude that additional collection of field-verified inventories of postfire hydrologic response will be critical to prioritize which model variables may be suitable candidates for regional calibration or replacement.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-023-02106-7","usgsCitation":"Thomas, M.A., Kean, J.W., McCoy, S., Lindsay, D.N., Kostelnik, J., Cavagnaro, D.B., Rengers, F.K., East, A.E., Schwartz, J., Smith, D.P., and Collins, B.D., 2023, Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards: Landslides, v. 20, p. 2421-2436, https://doi.org/10.1007/s10346-023-02106-7.","productDescription":"16 p.","startPage":"2421","endPage":"2436","ipdsId":"IP-139528","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442830,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10346-023-02106-7","text":"Publisher Index Page"},{"id":435262,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91O03Y7","text":"USGS data release","linkHelpText":"Field-verified inventory of postfire hydrologic response for the 2020 CZU Lightning Complex, River, Camel, and Dolan Fires following a 26-29 January 2021 atmospheric river storm sequence"},{"id":418804,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.47368381570269,\n 35.81897449008355\n ],\n [\n -120.78708136085193,\n 36.2836437903476\n ],\n [\n -121.84398626326276,\n 37.24464732874951\n ],\n [\n -122.37243871446816,\n 36.97394608796073\n ],\n [\n -121.47368381570269,\n 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Center","active":true,"usgs":true}],"preferred":true,"id":877144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Scott W.","contributorId":267182,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":877145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsay, Donald N.","contributorId":216337,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","email":"","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":877146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards 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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":877150,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schwartz, Jonathan","contributorId":312505,"corporation":false,"usgs":false,"family":"Schwartz","given":"Jonathan","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":877151,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Douglas P.","contributorId":201716,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","email":"","middleInitial":"P.","affiliations":[{"id":35924,"text":"California State University, Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":877152,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":877153,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70246596,"text":"70246596 - 2023 - Translating stakeholder narratives for participatory modeling in landscape ecology","interactions":[],"lastModifiedDate":"2023-09-06T16:23:41.955537","indexId":"70246596","displayToPublicDate":"2023-07-07T06:57:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Translating stakeholder narratives for participatory modeling in landscape ecology","docAbstract":"Engaging stakeholders in research is needed for many of the sustainability challenges that landscape ecologists address. Involving stakeholders’ perspectives through narratives in participatory modeling fosters better understanding of the problem and evaluation of the acceptability of tradeoffs and creates buy-in for management actions. However, stakeholder-driven inputs often take the form of complex qualitative descriptions, rather than model-ready numerical or categorical inputs.
Translating narratives into models, model parameters, or scenarios is essential for leveraging stakeholder knowledge and engagement. Drawing from varied experiences to identify lessons learned and pitfalls, we address the practice of translating narratives into models and using those narratives to interpret and communicate results.
We drew from seven participatory landscape ecology projects across North America to synthesize lessons for the inclusion of stakeholder narratives in modeling studies.
We offer 8 lessons as practical guidance for other landscape ecologists to move the science beyond a unilateral focus on ecological systems and to maximize the benefits of landscape sustainability science.
These lessons are starting points, as real projects are complex, nuanced, and sometimes contradictory. Translating narratives into models is important for addressing complex sustainability challenges; we hope that these starting points are helpful to those foraying into this type of research.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-023-01724-9","usgsCitation":"Vukomanovic, J., Smart, L., Koch, J., Dale, V., Plassin, S., Byrd, K.B., Beier, C., and Doyon, F., 2023, Translating stakeholder narratives for participatory modeling in landscape ecology: Landscape Ecology, v. 38, p. 2453-2474, https://doi.org/10.1007/s10980-023-01724-9.","productDescription":"22 p.","startPage":"2453","endPage":"2474","ipdsId":"IP-136700","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":502612,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.wur.nl/en/publications/translating-stakeholder-narratives-for-participatory-modeling-in-","text":"External Repository"},{"id":418854,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2023-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Vukomanovic, Jelena","contributorId":316275,"corporation":false,"usgs":false,"family":"Vukomanovic","given":"Jelena","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":877297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smart, Lindsey","contributorId":316276,"corporation":false,"usgs":false,"family":"Smart","given":"Lindsey","affiliations":[{"id":68543,"text":"North Carolina State University, The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":877298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Jennifer","contributorId":316277,"corporation":false,"usgs":false,"family":"Koch","given":"Jennifer","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":877299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dale, Virginia","contributorId":316278,"corporation":false,"usgs":false,"family":"Dale","given":"Virginia","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":877300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plassin, Sophie","contributorId":316279,"corporation":false,"usgs":false,"family":"Plassin","given":"Sophie","email":"","affiliations":[{"id":34610,"text":"Universite de Toulouse","active":true,"usgs":false}],"preferred":false,"id":877301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":877302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beier, Colin","contributorId":316280,"corporation":false,"usgs":false,"family":"Beier","given":"Colin","affiliations":[{"id":37519,"text":"SUNY College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":877303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Doyon, Frederik","contributorId":316282,"corporation":false,"usgs":false,"family":"Doyon","given":"Frederik","email":"","affiliations":[{"id":68544,"text":"Institut des sciences de la foret temperee, Universite du Quebec","active":true,"usgs":false}],"preferred":false,"id":877304,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70249249,"text":"70249249 - 2023 - Introduction to the special section on seismoacoustics and seismoacoustic data fusion","interactions":[],"lastModifiedDate":"2023-10-03T11:59:00.224775","indexId":"70249249","displayToPublicDate":"2023-07-07T06:56:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Introduction to the special section on seismoacoustics and seismoacoustic data fusion","docAbstract":"A variety of geophysical hazards (e.g., volcanic activity, earthquakes, mass movements, marine storms, bolides) and anthropogenic sources (e.g., chemical and nuclear explosions, mining blasts, rocket launches) can release energy as mechanical waves in the ground, ocean, and atmosphere (Arrowsmith et al., 2010; Campus and Christie, 2009). Due to the mechanical coupling between a planetary body, its ocean, and its atmosphere, waves can propagate across these interfaces (Ben-Menahem and Singh, 1981) and carry information about the source and the media they propagated through. The field of seismoacoustics, driven by geophysical observations of both seismic and low-frequency acoustic (infrasound) waves, has several interdisciplinary applications. Observations of both seismic and infrasonic waves can be used to discriminate between atmospheric and subsurface events, such as sonic booms and earthquakes. Moreover, seismoacoustic analyses can provide useful information for the source characterization of shallow anthropogenic events, such as underground or surface explosions, volcanic, and tectonic events (e.g., Arrowsmith et al., 2020; Assink et al., 2016; de Groot-Hedlin and Hedlin, 2019; Matoza et al., 2009). Similarly, remote observations (e.g., on regional seismic and infrasonic arrays) can help monitor natural events such as volcanic eruptions and provide additional details about eruption dynamics. Recent works additionally suggest that infrasound can be used to discriminate between different volcanic processes (Watson et al., 2022). Finally, looking outwards, the study of seismo-acoustics has been a particularly valuable tool for planetary science (e.g., Krishnamoorthy et al., 2018; Martire et al., 2018; Krishnamoorthy et al., 2019; Martire et al., 2020; Garcia et al., 2020; Brissaud et al., 2021).","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230049","usgsCitation":"Dannemann Dugick, F.K., Bishop, J.W., Martire, L., Iezzi, A.M., Assink, J.D., Brissaud, Q., and Arrowsmith, S., 2023, Introduction to the special section on seismoacoustics and seismoacoustic data fusion: Bulletin of the Seismological Society of America, v. 113, no. 4, p. 1383-1389, https://doi.org/10.1785/0120230049.","productDescription":"7 p.","startPage":"1383","endPage":"1389","ipdsId":"IP-149117","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442836,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1992277","text":"External Repository"},{"id":421528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Dannemann Dugick, Fransiska K.","contributorId":330421,"corporation":false,"usgs":false,"family":"Dannemann Dugick","given":"Fransiska","email":"","middleInitial":"K.","affiliations":[{"id":78886,"text":"Sandia National Laboratories, Albuquerque, NM 87110","active":true,"usgs":false}],"preferred":false,"id":884899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bishop, Jordan W.","contributorId":330422,"corporation":false,"usgs":false,"family":"Bishop","given":"Jordan","email":"","middleInitial":"W.","affiliations":[{"id":78887,"text":"Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA","active":true,"usgs":false}],"preferred":false,"id":884900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martire, Leo 0000-0002-9402-6150","orcid":"https://orcid.org/0000-0002-9402-6150","contributorId":296471,"corporation":false,"usgs":false,"family":"Martire","given":"Leo","email":"","affiliations":[{"id":64057,"text":"NASA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, Pasadena, CA 91109","active":true,"usgs":false}],"preferred":false,"id":884901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":304206,"corporation":false,"usgs":true,"family":"Iezzi","given":"Alexandra","email":"","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":884902,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Assink, Jelle D.","contributorId":236650,"corporation":false,"usgs":false,"family":"Assink","given":"Jelle","email":"","middleInitial":"D.","affiliations":[{"id":47493,"text":"R and D Seismology and Acoustics, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA De Bilt, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":884903,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brissaud, Quentin 0000-0001-8189-4699","orcid":"https://orcid.org/0000-0001-8189-4699","contributorId":296470,"corporation":false,"usgs":false,"family":"Brissaud","given":"Quentin","email":"","affiliations":[{"id":64063,"text":"NORSAR, Kjeller, Norway","active":true,"usgs":false}],"preferred":false,"id":884904,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arrowsmith, Stephen 0000-0002-9150-0363","orcid":"https://orcid.org/0000-0002-9150-0363","contributorId":296478,"corporation":false,"usgs":false,"family":"Arrowsmith","given":"Stephen","email":"","affiliations":[{"id":64065,"text":"Roy M. Huffington Department of Earth Sciences, Southern Methodist University, Dallas, Texas, U.S.A","active":true,"usgs":false}],"preferred":false,"id":884905,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70246564,"text":"70246564 - 2023 - Wildfire immediately reduces nest and adult survival of greater sage-grouse","interactions":[],"lastModifiedDate":"2023-07-10T15:06:50.842357","indexId":"70246564","displayToPublicDate":"2023-07-06T10:02:40","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":"Wildfire immediately reduces nest and adult survival of greater sage-grouse","docAbstract":"Wildfire events are becoming more frequent and severe on a global scale. Rising temperatures, prolonged drought, and the presence of pyrophytic invasive grasses are contributing to the degradation of native vegetation communities. Within the Great Basin region of the western U.S., increasing wildfire frequency is transforming the ecosystem toward a higher degree of homogeneity, one dominated by invasive annual grasses and declining landscape productivity. Greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) are a species of conservation concern that rely on large tracts of structurally and functionally diverse sagebrush (Artemisia spp.) communities. Using a 12-year (2008–2019) telemetry dataset, we documented immediate impacts of wildfire on demographic rates of a population of sage-grouse that were exposed to two large wildfire events (Virginia Mountains Fire Complex—2016; Long Valley Fire—2017) near the border of California and Nevada. Spatiotemporal heterogeneity in demographic rates were accounted for using a Before-After Control-Impact Paired Series (BACIPS) study design. Results revealed a 40% reduction in adult survival and a 79% reduction in nest survival within areas impacted by wildfires. Our results indicate that wildfire has strong and immediate impacts to two key life stages of a sagebrush indicator species and underscores the importance of fire suppression and immediate restoration following wildfire events.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-32937-2","usgsCitation":"Tyrrell, E.A., Coates, P.S., Prochazka, B.G., Brussee, B.E., Espinosa, S.P., and Hull, J.M., 2023, Wildfire immediately reduces nest and adult survival of greater sage-grouse: Scientific Reports, v. 13, 10970, 12 p., https://doi.org/10.1038/s41598-023-32937-2.","productDescription":"10970, 12 p.","ipdsId":"IP-146503","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442838,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-32937-2","text":"Publisher Index Page"},{"id":435263,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WA2M2Y","text":"USGS data release","linkHelpText":"Greater Sage-Grouse Adult and Nest Observations Before and After Wildfire in Northwest Nevada (2008-2019)"},{"id":418807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.05463957331938,\n 40.372305246838636\n ],\n [\n -120.02911844443898,\n 40.02532619716558\n ],\n [\n -119.87905420662038,\n 39.93067219828927\n ],\n [\n -119.64119728545204,\n 39.97214835081692\n ],\n [\n -119.66671841433293,\n 40.07455694499603\n ],\n [\n -119.77696969109726,\n 40.26645064715103\n ],\n [\n -119.96072181903847,\n 40.3777491537939\n ],\n [\n -120.05463957331938,\n 40.372305246838636\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2023-07-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Tyrrell, Emily A 0000-0002-9937-9713","orcid":"https://orcid.org/0000-0002-9937-9713","contributorId":306167,"corporation":false,"usgs":false,"family":"Tyrrell","given":"Emily","email":"","middleInitial":"A","affiliations":[{"id":66381,"text":"previously Western Ecological Research Center","active":true,"usgs":false}],"preferred":false,"id":877215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":877216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":877217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":877218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Espinosa, Shawn P.","contributorId":195583,"corporation":false,"usgs":false,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":877219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hull, Joshua M.","contributorId":127686,"corporation":false,"usgs":false,"family":"Hull","given":"Joshua","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":877220,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256513,"text":"70256513 - 2023 - Refining capture-recapture recruitment estimation methods for Atlantic sturgeon","interactions":[],"lastModifiedDate":"2026-02-10T18:11:12.038485","indexId":"70256513","displayToPublicDate":"2023-07-06T05:58:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Refining capture-recapture recruitment estimation methods for Atlantic sturgeon","docAbstract":"The Atlantic sturgeon Acipenser oxyrinchus oxyrinchus was once of great commercial importance in many coastal rivers of the eastern USA. Over the 19th and 20th centuries, most historical stocks of Atlantic sturgeon were depleted by human activities. Estimating recruitment for the remaining populations is challenging due to sampling constraints, limited age data, and natural variability. However, recruitment estimates could inform recovery efforts. The objectives of this study were to compare 2 modeling approaches to estimate recruitment of age-1 Atlantic sturgeon and provide an updated index of abundance across more than a decade of sampling in the Altamaha River, Georgia. First, we constructed capture histories of river-resident juveniles, using capture-mark-recapture data collected from 2008 to 2020, and assigned ages based on length-frequency analysis. Second, we compared more traditional Huggins closed population models and a recent nonlinear extension of Huggins models—vector generalized additive models (VGAMs)—to estimate abundance of age-1 fish. Both model types indicated similar yearly age-1 abundance estimates (Huggins: 163 in 2017 to 3839 in 2010; VGAM: 312 in 2020 to 4448 in 2010), but the VGAMs provided more direct interpretation for factors that might affect capture probability (e.g. sampling effort, temperature, fish length). This study indicates that the age-1 Altamaha River Atlantic sturgeon population has remained relatively stable over the past decade and provides a long-term baseline which will better enable managers to assess the effects of either future restoration actions or environmental disturbances on the population.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01250","usgsCitation":"Baker, M., Ingram, E., Higginbotham, D., Irwin, B., and Fox, A., 2023, Refining capture-recapture recruitment estimation methods for Atlantic sturgeon: Endangered Species Research, v. 51, p. 203-214, https://doi.org/10.3354/esr01250.","productDescription":"12 p.","startPage":"203","endPage":"214","ipdsId":"IP-143737","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432972,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":442856,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01250","text":"Publisher Index Page"}],"country":"United States","state":"Georgia","otherGeospatial":"Altamaha River estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.48760060177855,\n 31.490539509150565\n ],\n [\n -81.48760060177855,\n 31.14793158914553\n ],\n [\n -81.23488559221977,\n 31.14793158914553\n ],\n [\n -81.23488559221977,\n 31.490539509150565\n ],\n [\n -81.48760060177855,\n 31.490539509150565\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baker, M.A.","contributorId":340977,"corporation":false,"usgs":false,"family":"Baker","given":"M.A.","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":907756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ingram, E.C.","contributorId":340978,"corporation":false,"usgs":false,"family":"Ingram","given":"E.C.","email":"","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":907757,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higginbotham, D.L.","contributorId":340979,"corporation":false,"usgs":false,"family":"Higginbotham","given":"D.L.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":907758,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irwin, Brian J. 0000-0002-0666-2641","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":280043,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907759,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fox, A.G.","contributorId":340980,"corporation":false,"usgs":false,"family":"Fox","given":"A.G.","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":907760,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250980,"text":"70250980 - 2023 - Identifying invertebrate indicators for streamflow duration assessments in forested headwater streams","interactions":[],"lastModifiedDate":"2024-01-17T12:49:54.187192","indexId":"70250980","displayToPublicDate":"2023-07-05T06:46:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Identifying invertebrate indicators for streamflow duration assessments in forested headwater streams","docAbstract":"Streamflow-duration assessment methods (SDAMs) are rapid, indicator-based tools for classifying streamflow duration (e.g., intermittent vs perennial flow) at the reach scale. Indicators are easily assessed stream properties used as surrogates of flow duration, which is too resource intensive to measure directly for many reaches. Invertebrates are commonly used as SDAM indicators because many are not highly mobile, and different species have life stages that require flow for different durations and times of the year. The objectives of this study were to 1) identify invertebrate taxa that can be used as SDAM indicators to distinguish between stream reaches having intermittent and perennial flow, 2) to compare indicator strength across different taxonomic and numeric resolutions, and 3) to assess the relative importance of season and habitat type on the ability of invertebrates to predict streamflow-duration class. We used 2 methods, random forest models and indicator species analysis, to analyze aquatic and terrestrial invertebrate data (presence/absence, density, and biomass) at the family and genus levels from 370 samples collected from both erosional and depositional habitats during both wet and dry seasons. In total, 36 intermittent and 53 perennial reaches were sampled along 31 forested headwater streams in 4 level II ecoregions across the United States. Random forest models for family- and genus-level datasets had stream classification accuracy ranging from 88.9 to 93.2%, with slightly higher accuracy for density than for presence/absence and biomass datasets. Season (wet/dry) tended to be a stronger predictor of streamflow-duration class than habitat (erosional/depositional). Many taxa at the family (58.8%) and genus level (61.6%) were collected from both intermittent and perennial reaches, and most taxa that were exclusive to 1 streamflow-duration class were rarely collected. However, 23 family-level or higher taxa (20 aquatic and 3 terrestrial) and 44 aquatic genera were identified as potential indicators of streamflow-duration class for forested headwater streams. The utility of the potential indicators varied across level II ecoregions in part because of representation of intermittent and perennial reaches in the dataset but also because of variable ecological responses to drying among species. Aquatic invertebrates have been an important field indicator of perennial reaches in existing SDAMs, but our findings highlight how including aquatic and terrestrial invertebrates as indicators of intermittent reaches can further maximize the data collected for streamflow-duration classifications.
Plastic pollution is distributed patchily around the world’s oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and non-breeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging species.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-023-38900-z","usgsCitation":"Clark, B.L., Carneiro, A.P., Pearmin, E.J., Rouyer, M., Clay, T.A., Cowger, W., Phillips, R.A., Manica, A., Hazin, C., Eriksen, M., Gonzalez-Solis, J., Adams, J., Albores-Barajas, Y.V., Alfaro-Shigueto, J., Alho, M.S., Araujo, D.T., Arcos, J.M., Arnould, J., Barbosa, N.J., Barbraud, C., Beard, A.M., Beck, J., Bell, E., Bennet, D.G., Berlincourt, M., Biscoito, M., Bjornstad, O.K., Bolton, M., Booth Jones, K.A., Borg, J.J., Bourgeois, K., Bretagnolle, V., Bried, J., Briskie, J.V., de L. Brooke, M., Brownlie, K.C., Bugoni, L., Calabrese, L., Campioni, L., Carey, M.J., Carle, R., Carlile, N., Carreiro, A.R., Catry, P., Catry, T., Cecere, J.G., Ceia, F.R., Cherel, Y., Choi, C., Cianchetti-Benedetti, M., Clarke, R.H., Cleeland, J., Colodro, V., Congdon, B.C., Danielsen, J., De Pascalis, F., Deakin, Z., Dehnhard, N., Dell’Omo, G., Delord, K., Descamps, S., Dilley, B.J., Dinis, H.A., Dubos, J., Dunphy, B.J., Emmerson, L.M., Fagundes, A.I., Fayet, A.L., Felis, J.J., Fischer, J.H., Freeman, A., Fromant, A., Gaibani, G., Garcia, D., Gjerdrum, C., Gomes, I.S., Forero, M.G., Granadeiro, J.P., Grecian, W.J., Gremillet, D., Guilford, T., Hallgrimsson, G.T., Halpin, L.R., Hansen, E.S., Hedd, A., Helberg, M., Helgason, H.H., Henry, L.M., Hereward, H.F., Hernandez-Montero, M., Hindell, M.A., Hodum, P., Imperio, S., Jaeger, A., Jessopp, M., Jodice, P.G., Jones, C.G., Jones, C.W., Jonsson, J.E., Kane, A., Kapelj, S., Kim, Y., Kirk, H., Kolbeinsson, Y., Kraemer, P.L., Kruger, L., Lago, P., Landers, T., Lavers, J.L., Le Corre, M., Leal, A., Louzao, M., Madeiros, J., Magalhaes, M., Mallory, M.L., Masello, J., Massa, B., Matsumoto, S., McDuie, F., McFarlane Tranquilla, L., Medrano, F., Metzger, B.J., Militao, T., Montevecchi, W.A., Montone, R.C., Navarro-Herrero, L., Neves, V.C., Nicholls, D.G., Nicoll, M.A., Norris, K., Oppel, S., Oro, D., Owen, E., Padget, O., Paiva, V.H., Pala, D., Pereira, J.M., Peron, C., Petry, M.V., de Pina, A., Moreira Pina, A.T., Pinet, P., Pistorius, P.A., Pollet, I.L., Porter, B.J., Poupart, T.A., Powell, C.D., Proano, C.B., Pujol-Casado, J., Quillfeldt, P., Quinn, J.L., Raine, A.F., Raine, H., Ramírez, I., Ramos, J.A., Ramos, R., Ravache, A., Rayner, M.J., Reid, T.A., Robertson, G.J., Rocamora, G.J., Rollinson, D.P., Ronconi, R.A., Rotger, A., Rubolini, D., Ruhomaun, K., Ruiz, A., Russell, J.C., Ryan, P.G., Saldanha, S., Sanz-Aguilar, A., Sarda-Serra, M., Satge, Y.G., Sato, K., Schafer, W.C., Schoombie, S., Shaffer, S.A., Shah, N.J., Shoji, A., Shutler, D., Sigurdsson, I.A., Silva, M.C., Small, A.E., Soldatini, C., Strom, H., Surman, C.A., Takahashi, A., Tatayah, V.R., Taylor, G.A., Thomas, R.J., Thompson, D.R., Thompson, P.M., Thorarinsson, T.L., Vicente-Sastre, D., Vidal, E., Wakefield, E.D., Waugh, S.M., Weimerskirch, H., Wittmer, H.U., Yamamoto, T., Yoda, K., Zavalaga, C.B., Zino, F.J., and Dias, M.P., 2023, Global assessment of marine plastic exposure for oceanic birds: Nature Communications, v. 14, 3665, 14 p., https://doi.org/10.1038/s41467-023-38900-z.","productDescription":"3665, 14 p.","ipdsId":"IP-132806","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442871,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-023-38900-z","text":"Publisher Index Page"},{"id":419253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2023-07-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Clark, Bethany L. 0000-0001-5803-7744","orcid":"https://orcid.org/0000-0001-5803-7744","contributorId":317087,"corporation":false,"usgs":false,"family":"Clark","given":"Bethany","email":"","middleInitial":"L.","affiliations":[{"id":37309,"text":"BirdLife International","active":true,"usgs":false}],"preferred":false,"id":878596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carneiro, Ana P. 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A core assumption of many applications of oxygen isotope values (δ18O) of pedogenic carbonate is that they reflect the δ18O value of precipitation (rain/snow). This assumption is violated if soil carbonates form in evaporated soil waters. In this work, we develop a means to identify evaporation in ancient soils using the triple oxygen isotope composition (16O-17O-18O) of pedogenic carbonates. Both theoretical predictions of isotope kinetics during evaporation and studies of triple oxygen isotopes in other geological materials show that the deviation in the relationship between δ17O and δ18O from a reference line, evaluated using the parameter Δ'17O, is sensitive to evaporation. As a first step in developing the use of Δ'17O in ancient pedogenic carbonates, we report Δ'17O values from 47 near-modern pedogenic carbonate samples from globally distributed environments that vary in aridity (hyper-arid to humid). The Δ'17O values of pedogenic carbonate range from -154 to -60 per meg (as CaCO3, measured via O2, VSMOW-SLAP), corresponding to calculated soil water values of -66 to +27 per meg (VSMOW-SLAP) (using a carbonate-water triple oxygen isotope fractionation exponent of 0.5250 and clumped isotope-derived carbonate growth temperatures). The Δ'17O values indicate that evaporative modification of soil water from which pedogenic carbonate forms is common, especially in arid environments. Arid environments host pedogenic carbonates formed from soil waters ranging from highly to minimally evaporated, while humid environments host pedogenic carbonates formed from waters that are only minimally evaporated. The variability in Δ'17O within environments classified by the same aridity may relate to the fact that pedogenic carbonates record soil conditions only during times of carbonate mineralization, which may deviate from annual conditions. Thus, Δ'17O may be useful in understanding the specific circumstances of pedogenic carbonate formation but may not provide incontrovertible evidence of the magnitude of environmental aridity. Evaporative modification of δ18O values of pedogenic carbonates can be detected with Δ'17O, thereby improving estimates of δ18O of unevaporated waters. Our data show that evaporation must be (re)considered for all paleoclimate inferences based on the δ18O of pedogenic carbonate. The addition of Δ'17O will re-energize paleoclimate studies that use (or have avoided using) δ18O of pedogenic carbonate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2023.06.034","usgsCitation":"Kelson, J., Huth, T., Passey, B.H., Levin, N.E., Petersen, S.V., Ballato, P., Beverly, E.J., Breecker, D.O., Hoke, G.D., Hudson, A.M., Haoyuan, J., Licht, A., and Quade, J., 2023, Triple oxygen isotope compositions of globally distributed soil carbonates record widespread evaporation of soil waters: Geochimica et Cosmochimica Acta, v. 355, p. 138-160, https://doi.org/10.1016/j.gca.2023.06.034.","productDescription":"23 p.","startPage":"138","endPage":"160","ipdsId":"IP-148273","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":442883,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hal.science/hal-04160695","text":"Publisher Index 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H.","contributorId":315600,"corporation":false,"usgs":false,"family":"Passey","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":68361,"text":"Department of Earth & Environmental Sciences, University of Michigan","active":true,"usgs":false}],"preferred":false,"id":876924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Levin, Naomi E.","contributorId":315601,"corporation":false,"usgs":false,"family":"Levin","given":"Naomi","email":"","middleInitial":"E.","affiliations":[{"id":68361,"text":"Department of Earth & Environmental Sciences, University of Michigan","active":true,"usgs":false}],"preferred":false,"id":876925,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petersen, Sierra V.","contributorId":201014,"corporation":false,"usgs":false,"family":"Petersen","given":"Sierra","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":876926,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ballato, Paolo","contributorId":315602,"corporation":false,"usgs":false,"family":"Ballato","given":"Paolo","email":"","affiliations":[{"id":68362,"text":"Department of Science, Geological Sciences Section, University of Roma Tre","active":true,"usgs":false}],"preferred":false,"id":876927,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beverly, Emily J.","contributorId":315603,"corporation":false,"usgs":false,"family":"Beverly","given":"Emily","email":"","middleInitial":"J.","affiliations":[{"id":68365,"text":"Department of Earth and Atmospheric Sciences, University of Houston","active":true,"usgs":false}],"preferred":false,"id":876928,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Breecker, Daniel O.","contributorId":215845,"corporation":false,"usgs":false,"family":"Breecker","given":"Daniel","email":"","middleInitial":"O.","affiliations":[{"id":39318,"text":"University of Texas-Austin","active":true,"usgs":false}],"preferred":false,"id":876929,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hoke, Gregory D.","contributorId":315604,"corporation":false,"usgs":false,"family":"Hoke","given":"Gregory","email":"","middleInitial":"D.","affiliations":[{"id":68366,"text":"Department of Earth and Environmental Sciences, Syracuse University,","active":true,"usgs":false}],"preferred":false,"id":876930,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":876931,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Haoyuan, Ji","contributorId":315605,"corporation":false,"usgs":false,"family":"Haoyuan","given":"Ji","email":"","affiliations":[{"id":68367,"text":"Google LLC, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":876932,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Licht, Alexis","contributorId":315606,"corporation":false,"usgs":false,"family":"Licht","given":"Alexis","email":"","affiliations":[{"id":68368,"text":"Aix-Marseille Université","active":true,"usgs":false}],"preferred":false,"id":876933,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Quade, Jay","contributorId":22108,"corporation":false,"usgs":false,"family":"Quade","given":"Jay","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":876934,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70250589,"text":"70250589 - 2023 - Earthquake scenarios for Quito, Ecuador; Cali, Colombia; and Santiago De Los Caballeros, Dominican Republic","interactions":[],"lastModifiedDate":"2023-12-16T12:48:43.189443","indexId":"70250589","displayToPublicDate":"2023-07-03T06:41:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake scenarios for Quito, Ecuador; Cali, Colombia; and Santiago De Los Caballeros, Dominican Republic","docAbstract":"Earthquake risk associated with Quito, Ecuador; Cali, Colombia; and Santiago de los Caballeros, Dominican Republic is examined by generating a set of hypothetical earthquake scenarios considering seismic sources, recent seismicity, and major historical earthquakes recorded in the vicinity. In this study, particular focus is given to the development of earthquake scenarios for use in emergency planning in each city as well as stimulating discussion with respect to addressing the gaps in current understanding of built stock inventory and their vulnerability when subjected to strong shaking. Exposure and vulnerability models from the Global Earthquake Model foundation, hazard and local site information available for the cities, and the U.S. Geological Survey near‐real‐time products are utilized to estimate potential consequences for postearthquake response planning. Results showed that the historic city centers remain the most susceptible to experiencing severe damage resulting in widespread casualties. Similarly, the scenarios highlight areas susceptible to shaking induced ground failure hazards, which may pose additional challenges when responding to such earthquakes. Moderate earthquakes originating from nearby seismic sources, for example, Quito fault system for Quito or the Septentrional fault zone in the case of Santiago de Los Caballeros, could potentially be of greater consequence in terms of direct economic impact and disruption to the city when compared to very large distant subduction interface earthquakes.
Submerged aquatic vegetation (SAV) provides critical structural habitat for valuable nekton and wildlife species across coastal ecosystems and can buffer the negative effects of land loss. Landscape change and restoration efforts across coastal Louisiana can impact the occurrence, coverage, and species assemblages of SAV, and changes to these foundational species can have cascading impacts across food webs. To support the 2023 Coastal Master Plan efforts, a unique SAV model was developed to assess coverage and occurrence of SAV across aquatic waterbodies in response to environmental variables evaluated.
This effort created a spatial model describing the probability of presence of SAV across the study area in response to changing conditions over the modeled time period. To develop the initial coverage data layer, we used remotely sensed Normalized Difference Vegetation Index (NDVI) and modified Normalized Difference Water Index (mNDWI) data from 2015-2018 to identify areas containing variable vegetation and water spectral reflectance. Key environmental variables evaluated included total suspended sediments (TSS), salinity, and physical exposure. Seasonal estimates for TSS and salinity were used, as research indicates that seasonal environmental variability is a significant driver for SAV establishment. Seasonal salinity was derived from Coast-wide Reference Monitoring Station (CRMS) data, and seasonal TSS was estimated from hyperspectral imagery. Estimates of physical exposure have previously been provided by calculating fetch (the distance across water over which waves can propagate), but this proved to be too computationally intensive to be feasible, and we found distance to land to be a reasonable proxy for exposure. To represent geographic conditions and historical factors influences on SAV establishment and occurrence (e.g., variables too numerous and complex to model) we developed a basin variable that served as a proxy for complex historical, or prior, conditions, determined by the forested, fresh, intermediate, brackish, or saline (FFIBS) score. The final model included spring TSS, spring salinity, distance to land, and the basin prior.
The model performed well for the area evaluated, correctly classifying SAV (as present or absent) 89% of the time (Kappa = 580). SAV probability of presence responded as expected to change in these environmental variables, with likelihood of occurrence decreasing in response to increasing spring TSS, spring salinity, and distance to land. However, the model was more accurate at predicting absence (true negative = 0.940) than predicting presence (true positive = 0.626), suggesting that the scale of the model may limit the ability to predict presence. Moreover, the simplicity of the model limited the accuracy in highly dynamic environments, for example near the outflow of diversions or areas of significant changes in salinity or TSS. Through incorporating underwater communities like SAV, this master plan provides a holistic view of coastal change and restoration. To create healthy ecological structure and function in wetland habitats, the submergent communities must be considered alongside the emergent habitats. As the benefits of SAV are increasingly recognized, both here in Louisiana and beyond, SAV restoration and the use of SAV communities in assessing and improving ecological condition are becoming more common.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2023 Louisiana’s comprehensive master plan for a sustainable coast","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Louisiana Coastal Protection and Restoration Authority","usgsCitation":"DeMarco, K., Schoolmaster, D., and Couvillion, B., 2023, 2023 Coastal master plan: ICM-wetlands – Submerged aquatic vegetation (SAV) updates (Version 2), 58 p.","productDescription":"58 p.","ipdsId":"IP-151482","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":419827,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419802,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://coastal.la.gov/our-plan/2023-coastal-master-plan/2023-plan-appendices/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.79077632406495,\n 30.706267411766817\n ],\n [\n -93.79077632406495,\n 28.854615329475607\n ],\n [\n -88.34722956694776,\n 28.27842992330551\n ],\n [\n -89.00478141362511,\n 30.706267411766817\n ],\n [\n -93.79077632406495,\n 30.706267411766817\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeMarco, Kristin","contributorId":200003,"corporation":false,"usgs":false,"family":"DeMarco","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":880146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoolmaster, Donald 0000-0003-0910-4458","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":202356,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Couvillion, Brady 0000-0001-5323-1687","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":222810,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880148,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70247717,"text":"70247717 - 2023 - 2023 Coastal master plan: Landscape input data","interactions":[],"lastModifiedDate":"2023-08-15T15:32:51.936815","indexId":"70247717","displayToPublicDate":"2023-07-01T10:19:53","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"chapter":"Attachment B1","title":"2023 Coastal master plan: Landscape input data","docAbstract":"Coastal Louisiana is a complex landscape. The composition of the landscape, as well as the processes which influence said landscape, vary in both space and time. The models used in the 2023 Coastal Master Plan must attempt to reflect that spatial and temporal variability. It is therefore of the utmost importance that the spatial data sets upon which the models are initialized are of the highest quality.
This task focused on the compilation and creation of spatial data sets pertaining to parameters necessary to initialize models, calibrate their operations, and/or validate their results. Spatial data sets compiled and/or created as part of this effort include 1) an initial Landscape Composition and Configuration spatial data set, 2) an Integrated Topo/Bathymetric Digital Elevation Model 3) a Wetland Vegetation Community Type data set, and 4) Historical Marsh Edge Erosion Rates.
Each of these data sets constitutes a fundamental descriptor of the coastal landscape, upon which the models depend. This document describes the data sets compiled and the methodologies used to create the best-available spatial data describing the landscape in coastal Louisiana. While data collection dates vary, the data sets created for this effort are intended to represent 2018. The data described herein form initialization data sets upon which most, if not all, models of the 2023 Coastal Master Plan depend in one way or another.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2023 Louisiana’s comprehensive master plan for a sustainable coast","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Louisiana Coastal Protection and Restoration Authority","usgsCitation":"Couvillion, B., 2023, 2023 Coastal master plan: Landscape input data (Version 5), 43 p.","productDescription":"43 p.","ipdsId":"IP-151483","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":419826,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419803,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://coastal.la.gov/our-plan/2023-coastal-master-plan/2023-plan-appendices/"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.79077632406495,\n 30.706267411766817\n ],\n [\n -93.79077632406495,\n 28.854615329475607\n ],\n [\n -88.34722956694776,\n 28.27842992330551\n ],\n [\n -89.00478141362511,\n 30.706267411766817\n ],\n [\n -93.79077632406495,\n 30.706267411766817\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Couvillion, Brady 0000-0001-5323-1687","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":216668,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880149,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239906,"text":"70239906 - 2023 - Automated georeferencing and feature extraction of geologic maps and mineral sites","interactions":[],"lastModifiedDate":"2023-08-24T14:12:20.426596","indexId":"70239906","displayToPublicDate":"2023-07-01T08:51:21","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Automated georeferencing and feature extraction of geologic maps and mineral sites","docAbstract":"The predictive power of mineral prospectivity analysis depends on high quality, spatially accurate, analysis-ready datasets. Of paramount importance are geologic maps and mineral site data, but the state of readiness for utilizing these datasets remains sub-optimal for advanced computational techniques. As the U.S. Geological Survey (USGS) fulfils its mission to map the distribution of critical mineral commodities, non-georeferenced maps held within historical collections represent rich sources of input data. Through a series of machine learning challenges organized by the Defense Advanced Research Projects Agency (DARPA) in collaboration with the USGS, significant progress has been made in accelerating data ingestion, processing, and preparation tasks that enable mineral prospectivity mapping and mineral resource assessment workflows. Specifically, two tasks that previously required time-intensive human effort, 1) georeferencing map images, and 2) legend-based feature extraction from map images, are discussed.","largerWorkTitle":"Abstract proceedings: MinProXT 2022","conferenceTitle":"Mineral Prospectivity and Exploration Targeting (MinProXT 2022)","conferenceDate":"November 1-3, 2022","conferenceLocation":"Freiberg, Germany","language":"English","publisher":"Geological Survey of Finland","usgsCitation":"Lederer, G.W., Rosera, J.M., Goldman, M.A., Graham, G.E., Mishra, A., Towler, A., Wilson, B., Graf, D., Milano, M., Roberts, E., Hedrick, G., Oertel, C., Dardas, A., and McEntee, T., 2023, Automated georeferencing and feature extraction of geologic maps and mineral sites, in Abstract proceedings: MinProXT 2022, Freiberg, Germany, November 1-3, 2022, p. 8-10.","productDescription":"3 p.","startPage":"8","endPage":"10","ipdsId":"IP-145356","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":420118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lederer, Graham W. 0000-0002-9505-9923","orcid":"https://orcid.org/0000-0002-9505-9923","contributorId":202407,"corporation":false,"usgs":true,"family":"Lederer","given":"Graham","email":"","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":862322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosera, Joshua Mark 0000-0003-3807-5000","orcid":"https://orcid.org/0000-0003-3807-5000","contributorId":270284,"corporation":false,"usgs":true,"family":"Rosera","given":"Joshua","email":"","middleInitial":"Mark","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":862323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldman, Margaret A. 0000-0003-2232-6362 mgoldman@usgs.gov","orcid":"https://orcid.org/0000-0003-2232-6362","contributorId":176468,"corporation":false,"usgs":true,"family":"Goldman","given":"Margaret","email":"mgoldman@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":862324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":862325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mishra, Asitang","contributorId":301178,"corporation":false,"usgs":false,"family":"Mishra","given":"Asitang","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":862326,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Towler, Amanda","contributorId":301179,"corporation":false,"usgs":false,"family":"Towler","given":"Amanda","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":862327,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, Brian","contributorId":301180,"corporation":false,"usgs":false,"family":"Wilson","given":"Brian","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":862328,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Graf, Dustin","contributorId":301181,"corporation":false,"usgs":false,"family":"Graf","given":"Dustin","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":862329,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Milano, Michael","contributorId":301182,"corporation":false,"usgs":false,"family":"Milano","given":"Michael","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":862330,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Roberts, Elizabeth","contributorId":301183,"corporation":false,"usgs":false,"family":"Roberts","given":"Elizabeth","affiliations":[{"id":65325,"text":"MITRE","active":true,"usgs":false}],"preferred":false,"id":862331,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hedrick, Gabrielle 0000-0002-4941-3565","orcid":"https://orcid.org/0000-0002-4941-3565","contributorId":301184,"corporation":false,"usgs":false,"family":"Hedrick","given":"Gabrielle","email":"","affiliations":[{"id":65325,"text":"MITRE","active":true,"usgs":false}],"preferred":false,"id":862332,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Oertel, Carsten","contributorId":301185,"corporation":false,"usgs":false,"family":"Oertel","given":"Carsten","email":"","affiliations":[{"id":65325,"text":"MITRE","active":true,"usgs":false}],"preferred":false,"id":862333,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dardas, Anastassios 0000-0003-0518-4788","orcid":"https://orcid.org/0000-0003-0518-4788","contributorId":301186,"corporation":false,"usgs":false,"family":"Dardas","given":"Anastassios","email":"","affiliations":[{"id":65325,"text":"MITRE","active":true,"usgs":false}],"preferred":false,"id":862334,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McEntee, Thomas","contributorId":301187,"corporation":false,"usgs":false,"family":"McEntee","given":"Thomas","email":"","affiliations":[{"id":65325,"text":"MITRE","active":true,"usgs":false}],"preferred":false,"id":862335,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70254723,"text":"70254723 - 2023 - Winners and losers over a ½ century of change in crayfish assemblages of Wyoming, USA","interactions":[],"lastModifiedDate":"2024-06-10T23:58:26.927419","indexId":"70254723","displayToPublicDate":"2023-06-30T10:14:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Winners and losers over a ½ century of change in crayfish assemblages of Wyoming, USA","docAbstract":"Crayfish have experienced extensive assemblage reorganization as a result of global change, with some species becoming globally invasive and others becoming rare or extinct. We combined historical and contemporary sampling data to determine temporal trends of crayfish assemblages of Wyoming, USA, identifying winners and losers over a ½ century of change (1969–2020). We first documented range expansions of several species, including the Virile Crayfish Faxonius virilis (Hagen, 1870), Ringed Crayfish Faxonius neglectus (Faxon, 1885), and Rusty Crayfish Faxonius rusticus (Girard, 1852) as well as range contractions of the Calico Crayfish Faxonius immunis (Hagen, 1870) and Pilose Crayfish Pacifastacus gambelii (Girard, 1852). We then used multispecies occupancy models to investigate potential mechanisms behind the replacement of F. immunis by F. virilis as the most commonly detected crayfish species in Wyoming over time. We hypothesized that F. virilis is more likely to competitively displace F. immunis from more permanent waterbodies, whereas F. immunis is more likely to persist in more ephemeral habitats because of its superior burrowing ability and tolerance of low dissolved oxygen concentrations. Our occupancy models supported this prediction, with F. immunis occupancy declining at more permanent sites in the presence of F. virilis, but F. immunis occupancy was unaffected by F. virilis in less permanent sites. We also found positive associations of F. virilis occupancy and detection probability with water temperature, suggesting that warmer streams may be more vulnerable to new invasions or spread by this species in nonnative regions of western North America. Our results highlight the value of regular, statewide crayfish surveys through documenting substantial changes in Wyoming’s crayfish assemblage structure that may be driven by habitat-mediated competitive interactions.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/725318","usgsCitation":"Newkirk, B., Larson, E.R., Walker, A.D., and Walters, A.W., 2023, Winners and losers over a ½ century of change in crayfish assemblages of Wyoming, USA: Freshwater Science, v. 42, no. 2, p. 146-160, https://doi.org/10.1086/725318.","productDescription":"15 p.","startPage":"146","endPage":"160","ipdsId":"IP-139290","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":429757,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"42","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Newkirk, Braxton","contributorId":302721,"corporation":false,"usgs":false,"family":"Newkirk","given":"Braxton","email":"","affiliations":[{"id":65540,"text":"Nebraska Cooperative Research Unit","active":true,"usgs":false}],"preferred":false,"id":902883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Eric R.","contributorId":175281,"corporation":false,"usgs":false,"family":"Larson","given":"Eric","email":"","middleInitial":"R.","affiliations":[{"id":16989,"text":"University of Tennessee, Knoxville, TN","active":true,"usgs":false}],"preferred":false,"id":902884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walker, Andrew D.","contributorId":337329,"corporation":false,"usgs":false,"family":"Walker","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":902355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902356,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248105,"text":"70248105 - 2023 - Modeling habitat suitability across different levels of invasive plant abundance","interactions":[],"lastModifiedDate":"2023-10-11T15:53:15.201181","indexId":"70248105","displayToPublicDate":"2023-06-30T09:55:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Modeling habitat suitability across different levels of invasive plant abundance","docAbstract":"Predicting where invasive plants are likely to spread and become abundant is critical for informing invasive plant management. Species distribution models are a key tool for informing the geography of invasion risk, but most distribution models are limited by their use of presence data, including no information on invader population abundance. In this study, we ask how habitat suitability varies for different levels of abundance for three invasive plants: stiltgrass (Microstegium vimineum), sericea lespedeza (Lespedeza cuneata), and privet (Ligustrum sinense). For each species, we used an ensemble distribution modeling approach to compare suitability for invasion estimated from subsets of point location data: all presences vs. locations with percent cover ≥ 1%, ≥ 5%, ≥ 10%, ≥ 25%, and ≥ 50%. For all species, the total area predicted as suitable for abundant populations was 32%–68% less than the area predicted as suitable for presence. For stiltgrass and sericea lespedeza, the area suitable for invasion decreased when predicted from higher levels of abundance, whereas for privet, suitable area was similar across abundance levels. Stiltgrass and sericea lespedeza are therefore likely to become highly abundant in a smaller portion of their ranges, while privet could become highly abundant anywhere it can establish at low abundance. Different environmental predictors explained suitability for presence versus abundance, suggesting the environmental niche associated with presence differs from that associated with high population abundance. Analyses of more species and growth forms are still needed, but our results combined with previous studies consistently show that fitting distribution models to point locations with ≥ 5–10% cover refines range maps and can produce a more targeted assessment of invasion risk.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-023-03118-z","usgsCitation":"Beaury, E.M., Jarnevich, C.S., Pearse, I., Evans, A.E., Teich, N., Engelstad, P., LaRoe, J., and Bradley, B., 2023, Modeling habitat suitability across different levels of invasive plant abundance: Biological Invasions, v. 25, p. 3471-3483, https://doi.org/10.1007/s10530-023-03118-z.","productDescription":"13 p.","startPage":"3471","endPage":"3483","ipdsId":"IP-137901","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":435269,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P939IXCP","text":"USGS data release","linkHelpText":"Thresholded abundance models for three invasive plant species in the United States"},{"id":420481,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","noUsgsAuthors":false,"publicationDate":"2023-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Beaury, Evelyn M.","contributorId":236820,"corporation":false,"usgs":false,"family":"Beaury","given":"Evelyn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":881874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881876,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, Annette E. 0000-0001-6439-4908","orcid":"https://orcid.org/0000-0001-6439-4908","contributorId":328976,"corporation":false,"usgs":false,"family":"Evans","given":"Annette","email":"","middleInitial":"E.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":881877,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teich, Nathan","contributorId":328972,"corporation":false,"usgs":false,"family":"Teich","given":"Nathan","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":881878,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Engelstad, Peder","contributorId":238758,"corporation":false,"usgs":false,"family":"Engelstad","given":"Peder","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":881879,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LaRoe, Jillian 0000-0002-1429-9811","orcid":"https://orcid.org/0000-0002-1429-9811","contributorId":299950,"corporation":false,"usgs":false,"family":"LaRoe","given":"Jillian","affiliations":[{"id":64987,"text":"Student contractor to USGS Fort Collins Science Center","active":true,"usgs":false}],"preferred":false,"id":881880,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Bethany A. 0000-0003-4912-4971","orcid":"https://orcid.org/0000-0003-4912-4971","contributorId":299998,"corporation":false,"usgs":true,"family":"Bradley","given":"Bethany A.","affiliations":[{"id":64995,"text":"University of Massachusetts, Northeast Climate Adaptation Science Center","active":true,"usgs":false}],"preferred":false,"id":881881,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70245765,"text":"ofr20231040 - 2023 - Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey Flood Risk Management Project Area in San Diego County, California—Breeding activities and habitat use—2022 annual report","interactions":[],"lastModifiedDate":"2023-06-30T10:52:30.004365","indexId":"ofr20231040","displayToPublicDate":"2023-06-29T09:10:19","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":"2023-1040","displayTitle":"Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey Flood Risk Management Project Area in San Diego County, California: Breeding Activities and Habitat Use—2022 Annual Report","title":"Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey Flood Risk Management Project Area in San Diego County, California—Breeding activities and habitat use—2022 annual report","docAbstract":"We completed four protocol surveys for Least Bell’s Vireos (Vireo bellii pusillus; vireo) during the breeding season, supplemented by weekly territory monitoring visits. We identified a total of 133 territorial male vireos; 114 were confirmed as paired, and 3 were confirmed as single males. For the remaining 16 territories, we were unable to confirm breeding status. Two transient vireos were detected in 2022. The vireo population in the Project Area increased by 9 percent from 2021 to 2022. The vireo population at Marine Corps Base Camp Pendleton also increased (4 percent), whereas the population at Marine Corps Air Station remained relatively stable (decreased from 10 pairs to 9) and the Otay River population decreased by 10 percent (2 territories).
We used an index of treatment (Treatment Index) to evaluate the effect of on-going vegetation clearing on the Project Area vireo population. The Treatment Index measures the cumulative effect of vegetation treatment within a territory (since 2005) by using the percentage area treated weighted by the number of years since treatment. We determined that the Treatment Index for unoccupied habitat was more than four times that of occupied habitat, indicating that vireos selected habitat that was less treated in which to settle.
We monitored vireo nests at three general site types: (1) within the flood channel where exotic and native vegetation removal has occurred regularly (Channel), (2) three sites near the flood channel where limited exotic and native vegetation removal has occurred (Off-channel), and (3) three sites that have been actively restored by planting native vegetation (Restoration). Nesting activity was monitored in 80 territories, 3 of which were occupied by single males and 1 by a male whose breeding status could not be confirmed. Overall, 38 percent of completed nests were successful and nest success did not differ among the three sites. In 2022, there were no differences with regard to clutch size, hatching, or fledging success among Channel, Off-channel and Restoration sites. Overall breeding success and productivity were slightly higher in 2022 than in 2021, with 72 percent of pairs fledgling at least one young and pairs fledging an average of 2.2±1.7 young.
To investigate if the cumulative years of treatment had an effect on vireo reproductive effort, we looked at the effects of the Treatment Index on reproductive parameters. Results from generalized linear models indicated that treatment did not have an effect on vireo nesting effort or the number of vireo fledglings per pair produced in 2022. Similarly, we did not detect an effect of Treatment Index on daily survival rate (DSR) of nests.
Analysis of vegetation data collected at vireo nests from 2006 to 2022 did not reveal an effect of vegetation cover at the nest on DSR. We did find, however, that Channel nests were placed higher in the host plant than Off-channel nests. In the Channel and Off-channel sites, successful nests were placed closer to the edge of the host plants than unsuccessful nests. Additionally, successful Off-channel nests were placed lower in the vegetation, in shorter host plants, and closer to the edge of the vegetation clump than unsuccessful nests.
Red/arroyo willow (Salix laevigata or Salix lasiolepis) were the species most commonly selected for nesting by vireos in all three site types. Black willow (Salix gooddingii) and mule fat (Baccharis salicifolia) also were commonly used. Vireos used a wider variety of species for nesting in Channel and Off-channel sites (eight and six species, respectively) compared to Restoration sites (two species), although there was limited nesting in Restoration sites in 2022.
There were 43 vireos banded before the 2022 breeding season that were resighted and identified at the Project Area in 2022, all of which were originally banded in the Project Area. Adult birds of known age ranged from 1 to 7 years old. A total of 146 vireos were newly banded in 2022. There were 8 adult vireos banded with a unique color combination, and 138 nestlings were banded with a single dark blue numbered federal band on the left leg. Between 2006 and 2022, survivorship of males (66±11 percent) was consistently higher than that of females (59±12 percent). First-year birds from 2006 to 2022 had an average annual survivorship of 15±6 percent.
First-year dispersal in 2022 averaged 6.7±7.4 kilometers (km), with the longest dispersal (15.3 km) by a male that was recaptured at Fallbrook Creek, Fallbrook Naval Weapons Station (FNWS). From 2007 to 2011, most returning first-year vireos returned to the Project Area, whereas from 2014 to 2016, the majority of returning birds dispersed to areas outside of the Project Area. From 2018 to 2021, the trend shifted, and more first-year vireos returned to the Project area. In 2022, only one first-year vireo returned to the project area and two dispersed to sites outside the Project Area (upstream to the middle San Luis Rey River and to Fallbrook Creek, FNWS). However, the total number of identified first-year vireos was low and the trend in 2022 will likely shift as additional returning first-year vireos are identified in subsequent years.
Most of the returning adult male vireos showed strong between-year site fidelity to their previous territories. Seventy-three percent of males (27/37) occupied a territory in 2022 that they had defended in 2021 (within 100 meters [m]). There were no females (0/4) detected in 2022 that returned to a territory they occupied in 2021; however, 50 percent of females (2/4) detected in 2022 returned to areas adjacent to their previous territories (within 300 m). The average between-year movement for returning adult vireos was 0.3±0.7 km. The amount of treatment at adults’ 2021 territories did not affect the distance adults moved to their 2022 territories.
We completed four protocol surveys for the endangered Southwestern Willow Flycatcher (Empidonax traillii extimus; flycatcher) at the Project Area between May 16 and July 25, 2022. Four transient Willow Flycatchers were detected in the Project Area in 2022. Two transients were detected in Reach 1, one in Reach 3a, and one in Pilgrim Pond. There were not any resident flycatchers documented in the Project Area in 2022.
A total of 46 vegetation transects (528 points) were sampled at the Project Area in 2022. Seventy-one percent (378/528) of points were located in the Channel, and 22 percent (115/528) were in Upper Pond. The remaining 7 percent (35/528) of points were at the Whelan Restoration site. Foliage cover below 2 m was higher at the Channel points compared to Upper Pond and Whelan Restoration, which can be attributed to the dense herbaceous vegetation that grows after mowing. Above 2 m, foliage cover was similar at the Channel and Whelan Restoration sites and was higher than at Upper Pond. Average canopy height was higher in the Channel (5.6±3.4 m) compared to Upper Pond (4.7±2.9 m) and Whelan Restoration (4.6±1.9 m). From 2006 to 2022, total foliage cover declined above 2 m in the Channel, in contrast to Upper Pond and Whelan Restoration, where little directional change in vegetation cover has occurred and where vegetation cover has largely recovered to 2006 levels. Within the Channel, the steepest declines occurred between 2009 and 2013 and between 2014 and 2016. Since 2016, we observed an increase in foliage cover, largely herbaceous, between 0 and 2 m within the Channel. The percent cover remained below levels detected before 2009 for other height classes.
We sampled vegetation at 44 vireo nests and 44 random plots (“territory” plots) within territories in the Channel and Upper Pond after the 2022 breeding season. Vireos in the Channel established territories in areas with significantly more cover from 3 to 6 m but less cover below 2 m relative to the available habitat. Within territories, Channel vireos selected nest sites with significantly more foliage cover from 2 to 3 m. Vireos at Upper Pond established territories in areas with significantly more foliage cover from 5 to 6 m and below 1 m relative to available habitat. However, within territories, Upper Pond vireos selected nest sites with significantly less foliage cover from 5 to 6 m and below 1 m.
Data either are not available or have limited availability owing to restrictions of the funding entity (U.S. Army Corps of Engineers). Please contact Christopher Chabot, Planning Division, Los Angeles District, U.S. Army Corps of Engineers, for more information.
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Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Mobile radio tracking is an important tool in fisheries research and management. Yet, the accuracy of location estimates can be highly variable across studies and within a given dataset. While some methods are available to deal with error, they generally assume a static value for error across all detections. We provide a novel method for making detection-specific error estimates using detections of recovered transmitters (i.e., mortalities or tag expulsion). These data are used to establish the relationship between received signal strength (RSS) and positional error, which can then be used to predict positional error of detections for fish at large. We then show how detection-specific estimates can be integrated into a Monte Carlo framework to analyze movement in ways robust to spatial uncertainty.
In a telemetry study in a large river (~ 90 m), we recovered 22 transmitters to estimate and model positional error. Error averaged 94 m (range = 1–727 m) for transmitters tracked by researchers on foot using a Yagi antenna, and 200 m (range = 1–1141 m) for transmitters tracked from vehicles using an omnidirectional whip antenna. Transmitters located near roads were tracked more accurately with both methods. Received signal strength was a strong predictor of positional error (r2 = 0.86, ground tracking; 0.65, tracking from truck) and was thus used to make detection-specific estimates of error for detections of fish at large. Monte Carlo analysis for a binary movement classification revealed that only 18% of location estimates could be confidently assigned to movement (p < 0.05); the remainder were associated with stasis or movement that was within the range of positional error. Ignoring positional error led to positive bias of up to 1300% in individual movement estimates and varied seasonally—it was highest when fish were inactive and lowest when fish were most active.
Using recovered transmitters and RSS models to estimate telemetry error is a viable alternative to staged ‘dummy transmitter’ trials and assuming error is a constant. Our proposed approaches to incorporate detection-specific error estimates into analysis are broadly applicable and can ‘make the most’ out of highly accurate detections while also cautiously extracting spatial information from less-accurate detections.
Wildfire alters the hydrologic cycle, with important implications for water supply and hazards including flooding and debris flows. In this study we use a combination of electrical resistivity and stable water isotope analyses to investigate the hydrologic response during storms in three catchments: one unburned and two burned during the 2020 Bobcat Fire in the San Gabriel Mountains, California, USA. Electrical resistivity imaging shows that in the burned catchments, rainfall infiltrated into the weathered bedrock and persisted. Stormflow isotope data indicate that the amount of mixing of surface and subsurface water during storms was similar in all catchments, despite higher streamflow post-fire. Therefore, both surface runoff and infiltration likely increased in tandem. These results suggest that the hydrologic response to storms in post-fire environments is dynamic and involves more surface-subsurface exchange than previously conceptualized, which has important implications for vegetation regrowth and post-fire landslide hazards for years following wildfire.