The groundwater below the Red Hill Bulk Fuel Storage Facility (the facility) in Oʻahu, Hawaiʻi, contains fuel compounds from past spills. This study used carbon-14 analyses to distinguish fuel-derived carbon from background carbon, along with other biodegradation indicators, to address two goals: (1) determine the extent and migration direction of groundwater affected by residual fuel below the facility and (2) determine if residual fuel locations in the subsurface could be identified by analyzing soil gas at the surface above the facility.
Groundwater from 19 wells was sampled between September 2022 and April 2023. Nonvolatile dissolved organic carbon (NVDOC) from a well presumed to be unaffected by past spills contained 38 percent ancient carbon indicating a natural source of ancient carbon in the subsurface. The NVDOC concentrations and ancient carbon percentages indicate fuel biodegradation products are likely present on the north and south of Red Hill with the greatest effects at well RHMW02 near the 2014 spill site. The NVDOC concentrations are almost three times higher than diesel range organic (DRO) concentrations in groundwater from the same sites. Major ion data indicate that iron reduction is an important biodegradation process.
Soil probe samples and soil carbon traps were used to determine the carbon-14 content of soil carbon dioxide. Ancient carbon from fuel biodegradation was not detected at any soil probe or carbon trap site in contrast to a 2017 study which reported ancient carbon detections. A reanalysis of the 2017 results using a range of local values for background carbon-14 indicates that ancient carbon from fuel biodegradation was probably only detected in lower tunnel exhaust system samples and not in any soil carbon trap samples. Measurements of carbon dioxide efflux with a dynamic closed chamber were highly variable. The soil gas results indicate that soil gas measurements at land surface were not useful for detecting residual fuel at the facility.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245034","collaboration":"Prepared in cooperation with the U.S. Navy and the Defense Logistics Agency","programNote":"Environmental Health Program","usgsCitation":"Trost, J.J., Bekins, B.A., Jaeschke, J.B., Delin, G.N., Sinclair, D.A., Stack, J.K., Nakama, R.K., Miyajima, U.M., Pagaduan, L.D., and Cozzarelli, I.M., 2024, Distribution of ancient carbon in groundwater and soil gas from degradation of petroleum near the Red Hill Bulk Fuel Storage Facility, Oʻahu, Hawaiʻi: U.S. Geological Survey Scientific Investigations Report 2024–5034, 54 p., https://doi.org/10.3133/sir20245034.","productDescription":"Report: xi, 54 p.; Data Release; Dataset","numberOfPages":"70","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-155367","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":429760,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5034/sir20245034.pdf","text":"Report","size":"42.6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":429761,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5034/sir20245034.XML"},{"id":429767,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245034/full"},{"id":429766,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":429762,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5034/images/"},{"id":429759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5034/coverthb.jpg"},{"id":429765,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TIDAA4","text":"USGS data release","linkHelpText":"Groundwater and soil gas data, methods, and quality assurance information for samples collected to determine ancient carbon distributions at Red Hill Bulk Fuel Storage Facility, Oʻahu, Hawaiʻi, 2022–2023"},{"id":497942,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117072.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Hawaii","otherGeospatial":"Red Hill Bulk Fuel Storage Facility","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.91707912662315,\n 21.38710545210772\n ],\n [\n -157.91707912662315,\n 21.358702773157617\n ],\n [\n -157.87618345098332,\n 21.358702773157617\n ],\n [\n -157.87618345098332,\n 21.38710545210772\n ],\n [\n -157.91707912662315,\n 21.38710545210772\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
or
Director, Pacific Islands Water Science Center
U.S. Geological Survey
1845 Wasp Blvd., B176
Honolulu, HI 96818
Large wood (LW) plays important geomorphic and ecological roles in rivers and is widely used as a restoration tool. Changes to floodplain land use and historical removal have altered wood dynamics in fluvial systems globally. We know little about the distribution and dynamics of LW in great rivers (approximately >105 km2) like the Upper Mississippi and Illinois Rivers despite its ecosystem importance and use in restoration projects. We assessed LW occurrence data collected by the fisheries component of the Upper Mississippi River Restoration Program's Long Term Resource Monitoring element. We analysed 25 years of data collected across six reaches of the Upper Mississippi and Illinois Rivers that represented contrasting physiographic settings, and across four aquatic area types comprising gradients of hydrology, connectivity and geomorphology. We tested hypotheses on drivers of LW occurrence using generalised linear mixed effects models, where occurrence was predicted by reach- and local-scale environmental variables. Occurrence varied significantly across reaches and aquatic area types. In general, wood occurred more frequently upriver and in side channels compared to other aquatic areas. Large wood was most strongly predicted systemically by reach identity but not local-scale variables, underscoring the importance of broad-scale physiographic gradients in defining hydrogeomorphic processes. Floodplain forests and shoreline revetment were consistently important predictors across reaches. Our findings show that the spatial variability of LW occurrence reflects the physical variability of the Upper Mississippi and Illinois Rivers. They also reveal the value in using geomorphic classifications as frameworks for understanding physical processes like LW dynamics because of their ability to contextualise site-scale conditions. The baseline understanding of LW abundance across different hydrogeomorphic gradients and scales presented here can give insight into how to more effectively target restoration efforts in great rivers and contribute to a broader understanding of LW dynamics where such studies have been lacking.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.5911","usgsCitation":"Van Appledorn, M., Jankowski, K.J., Gahm, K., Budd, S., Baumann, D., Bennie, B., Erickson, R.A., Haro, R.J., and Rohweder, J.J., 2024, The where and why of large wood occurrence in the Upper Mississippi and Illinois Rivers: Earth Surface Processes and Landforms, v. 49, no. 11, p. 3383-3398, https://doi.org/10.1002/esp.5911.","productDescription":"16 p.","startPage":"3383","endPage":"3398","ipdsId":"IP-156995","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":430017,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Illinois River, Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.73578092131349,\n 45.12080357067936\n ],\n [\n -91.01148319916909,\n 42.06683000374717\n ],\n [\n -92.03223565670272,\n 40.356697147602766\n ],\n [\n -91.38931153946832,\n 38.69309735425202\n ],\n [\n -89.14510076231794,\n 36.650083721260515\n ],\n [\n -88.69332581972627,\n 40.70515855929407\n ],\n [\n -89.58402008394364,\n 41.68908264434286\n ],\n [\n -90.9223085282444,\n 44.553043048533425\n ],\n [\n -93.73578092131349,\n 45.12080357067936\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":903500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":903501,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gahm, Kaija","contributorId":338731,"corporation":false,"usgs":false,"family":"Gahm","given":"Kaija","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":903502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Budd, Serenity","contributorId":338732,"corporation":false,"usgs":false,"family":"Budd","given":"Serenity","email":"","affiliations":[{"id":38728,"text":"Virginia Commonwealth University","active":true,"usgs":false}],"preferred":false,"id":903503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baumann, Douglas","contributorId":328549,"corporation":false,"usgs":false,"family":"Baumann","given":"Douglas","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":903504,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bennie, Barbara","contributorId":328550,"corporation":false,"usgs":false,"family":"Bennie","given":"Barbara","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":903505,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":903506,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haro, Roger J.","contributorId":139538,"corporation":false,"usgs":false,"family":"Haro","given":"Roger","email":"","middleInitial":"J.","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":903507,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rohweder, Jason J. 0000-0001-5131-9773 jrohweder@usgs.gov","orcid":"https://orcid.org/0000-0001-5131-9773","contributorId":150539,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":903508,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70255313,"text":"70255313 - 2024 - Temporal habitat use of mule deer in the Pueblo of Santa Ana, New Mexico","interactions":[],"lastModifiedDate":"2024-07-15T15:38:36.010069","indexId":"70255313","displayToPublicDate":"2024-06-11T06:39:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Temporal habitat use of mule deer in the Pueblo of Santa Ana, New Mexico","docAbstract":"Mule deer (Odocoileus hemionus) are important economically, culturally, and recreationally to the Pueblo of Santa Ana in central New Mexico, USA. Studies of habitat selection improve our understanding of mule deer ecology in central New Mexico and provide the Tribe with valuable information for management of mule deer. We used global positioning system telemetry-collar data collected on mule deer around the Pueblo of Santa Ana to create resource selection functions from proximity-based habitat predictors using a generalized linear mixed model. We created separate resource selection functions for females and males during summer and winter at different times of the day. Season generally had a greater effect on mule deer habitat use than the time of day. Female and male mule deer selected for similar habitats but were sexually segregated in their summer distributions. These findings are consistent with results from other locations where mule deer partitioned habitat similarly between seasons and sexes. Supported models reaffirm accepted patterns of habitat selection for mule deer to the Pueblo of Santa Ana where local results were lacking. Our results can help managers identify locations in and around the Pueblo of Santa Ana where future development such as highway expansion are likely to conflict with mule deer activity and locations where habitat enhancement projects such as adding water sources can have the greatest effect for the deer population.
Female and male cooperative breeders can use different strategies to maximize reproduction and fitness over their lifetimes. Answering questions about fitness in cooperative breeders requires long-term studies as well as complete data on group composition and size which can be exceedingly difficult to obtain. Using a long-term genetic data set of complete group pedigrees, I asked how lifetime reproductive characteristics of female and male gray wolves (Canis lupus) differed. I predicted that genetic relatedness to helpers would be higher for females than males due to philopatric behavior of female wolves, group size would be similar between the sexes, females would inherit breeding positions from within groups more often than males due to differences in dispersal strategies between the sexes, males would have more lifetime mates and produce more young than females because of polygamy, and females would breed for more years than males due to the likelihood that females would still breed (with a new partner) after a mate died or was expelled from the group. I documented complete lifetime breeding histories for 11 male and 18 female wolves in Idaho, United States, 2008 to 2018. Genetic relatedness to helpers, group size, number of mates, pups, and years breeding did not differ between the sexes. Females, however, inherited breeding positions within groups far more often than males. Individuals who secured breeding positions generally reproduced for 2 seasons and commonly had more than 1 partner during their lifetimes if they were able to maintain their breeding position longer. Direct fitness varied greatly within female and male breeding wolves.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyae042","usgsCitation":"Ausband, D.E., 2024, Lifetime reproductive characteristics of gray wolves: Journal of Mammalogy, gyae042, 6 p., https://doi.org/10.1093/jmammal/gyae042.","productDescription":"gyae042, 6 p.","ipdsId":"IP-138491","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":439417,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyae042","text":"Publisher Index Page"},{"id":429805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902718,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70253190,"text":"dr1192 - 2024 - Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2020","interactions":[],"lastModifiedDate":"2026-01-27T17:27:32.350825","indexId":"dr1192","displayToPublicDate":"2024-06-10T11:30:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1192","displayTitle":"Streamflow, Water Quality, and Constituent Loads and Yields, Scituate Reservoir Drainage Area, Rhode Island, Water Year 2020","title":"Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2020","docAbstract":"As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey in cooperation with Providence Water (sometimes known as Providence Water Supply Board) collected streamflow and water-quality data in tributaries to the Scituate Reservoir, Rhode Island. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance for 14 tributaries were used to calculate loads of chloride and sodium during water year 2020 (October 1, 2019, through September 30, 2020). Water-quality samples were collected by Providence Water at 37 sampling stations on tributaries to the Scituate Reservoir during water year 2020. These water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields of selected water-quality constituents for water year 2020 in this report.
Annual mean streamflows for monitoring stations in this study ranged from about 0.32 to 26.7 cubic feet per second during water year 2020. At the 14 continuous-record streamgages, tributaries transported about 2,200 metric tons of chloride and 1,400 metric tons of sodium to the Scituate Reservoir; annual chloride yields for the tributaries ranged from 13 to 110 metric tons per square mile, and annual sodium yields ranged from 8.8 to 6 metric tons per square mile. At the stations where water-quality samples were collected by Providence Water, the medians of the median daily loads were 220 kilograms chloride per day, 10 grams nitrite as nitrogen per day, 500 grams nitrate as nitrogen per day, 290 grams orthophosphate as phosphate per day, 55,000 million colony forming units of coliform bacteria per day, and less than 900 million colony forming units of Escherichia coli per day. The medians of the median yields were 76 kilograms chloride per day per square mile, 4.1 grams nitrite as nitrogen per day per square mile, 240 grams nitrate as nitrogen per day per square mile, 100 grams orthophosphate as phosphate per day per square mile, 31,000 million colony forming units of coliform bacteria per day per square mile, and less than 260 million colony forming units of Escherichia coli per day per square mile.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1192","collaboration":"Prepared in cooperation with Providence Water","usgsCitation":"Smith, K.P., 2024, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2020: U.S. Geological Survey Data Report 1192, 31 p., https://doi.org/10.3133/dr1192.","productDescription":"Report: v, 31 p.; Data Release","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-139757","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":499106,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117055.htm","linkFileType":{"id":5,"text":"html"}},{"id":428114,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1192/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1192"},{"id":428113,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1192/dr1192.pdf","text":"Report","size":"5.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1192"},{"id":428112,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1192/coverthb2.jpg"},{"id":428116,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1192/dr1192.XML","linkFileType":{"id":8,"text":"xml"}},{"id":428115,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1192/images/"},{"id":428117,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WK8N0F","text":"USGS data release","linkHelpText":"Water-quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir (ver. 2.0, July 2022)"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.77640344375646,\n 41.94712091202689\n ],\n [\n -71.77640344375646,\n 41.72813307145168\n ],\n [\n -71.53464552766611,\n 41.72813307145168\n ],\n [\n -71.53464552766611,\n 41.94712091202689\n ],\n [\n -71.77640344375646,\n 41.94712091202689\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Island ecosystems are particularly susceptible to the impacts of invasive species. Many rare and endangered species that are endemic to islands are negatively affected by invasions. Past studies have shown that the establishment of non-native species on islands is related to native plant richness, habitat heterogeneity, island age, human activity, and climate. However, it is unclear whether the factors promoting establishment (i.e. the formation of self-sustaining populations) also promote subsequent invasion (i.e. spread and negative impacts). Using data from 4308 non-native plant species across 46 islands and archipelagos globally, we examined which biogeographic characteristics influence established and invasive plant richness using generalized linear models nested within piecewise structural equation models. Our results indicate that anthropogenic land use (i.e. human modification) is strongly associated with establishment but not invasion, that climate (maximum monthly temperature) is strongly associated with invasion but not establishment, and that habitat heterogeneity (represented by maximum elevation and island area) is strongly associated with both establishment and invasion. Island isolation explains native plant richness well, but is not associated with established and invasive plant richness, likely due to anthropogenic introductions. We conclude that anthropogenic land use on islands is likely to be a proxy for the number of introductions (i.e. propagule pressure), which is more important for establishment than invasion. Conversely, islands with more diverse habitats and favorable (warm) climate conditions are likely to contain more available niche space (i.e. ‘vacant niches’) which create opportunities for both establishment and invasion. By evaluating multiple stages of the invasion process, we differentiate between the biogeographic characteristics that influence plant establishment (which does not necessarily lead to ecological impacts) versus those that influence subsequent plant invasion (which does lead to negative impacts).
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.07379","usgsCitation":"Pfadenhauer, W.G., DiRenzo, G.V., and Bradley, B.A., 2024, Human activity drives establishment, but not invasion, of non-native plants on islands: Ecography, e07379, 14 p., https://doi.org/10.1111/ecog.07379.","productDescription":"e07379, 14 p.","ipdsId":"IP-159338","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439421,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.07379","text":"Publisher Index Page"},{"id":434944,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XES5OI","text":"USGS data release","linkHelpText":"Code for Human activity drives establishment, but not invasion, of non-native plants on islands"},{"id":433550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pfadenhauer, William G.","contributorId":343029,"corporation":false,"usgs":false,"family":"Pfadenhauer","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":910581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":910582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradley, Bethany A.","contributorId":343032,"corporation":false,"usgs":false,"family":"Bradley","given":"Bethany","email":"","middleInitial":"A.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":910583,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70255314,"text":"70255314 - 2024 - Climate change scenarios for air and water temperatures in the upper San Francisco Estuary: Implications for thermal regimes and Delta Smelt","interactions":[],"lastModifiedDate":"2024-06-17T11:31:00.075621","indexId":"70255314","displayToPublicDate":"2024-06-10T06:28:14","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Climate change scenarios for air and water temperatures in the upper San Francisco Estuary: Implications for thermal regimes and Delta Smelt","docAbstract":"Seasonally abundant arthropods are a crucial food source for many migratory birds that breed in the Arctic. In cold environments, the growth and emergence of arthropods are particularly tied to temperature. Thus, the phenology of arthropods is anticipated to undergo a rapid change in response to a warming climate, potentially leading to a trophic mismatch between migratory insectivorous birds and their prey. Using data from 19 sites spanning a wide temperature gradient from the Subarctic to the High Arctic, we investigated the effects of temperature on the phenology and biomass of arthropods available to shorebirds during their short breeding season at high latitudes. We hypothesized that prolonged exposure to warmer summer temperatures would generate earlier peaks in arthropod biomass, as well as higher peak and seasonal biomass. Across the temperature gradient encompassed by our study sites (>10°C in average summer temperatures), we found a 3-day shift in average peak date for every increment of 80 cumulative thawing degree-days. Interestingly, we found a linear relationship between temperature and arthropod biomass only below temperature thresholds. Higher temperatures were associated with higher peak and seasonal biomass below 106 and 177 cumulative thawing degree-days, respectively, between June 5 and July 15. Beyond these thresholds, no relationship was observed between temperature and arthropod biomass. Our results suggest that prolonged exposure to elevated temperatures can positively influence prey availability for some arctic birds. This positive effect could, in part, stem from changes in arthropod assemblages and may reduce the risk of trophic mismatch.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.17356","usgsCitation":"Chagnon-Lafortune, A., Duchesne, E., Legagneux, P., McKinnon, L., Reneerkens, J., Casajus, N., Abraham, K.F., Bolduc, E., Brown, G.S., Brown, S.C., Gates, H.R., Gilg, O., Giroux, M., Gurney, K., Kendall, S., Kwon, E., Lanctot, R., Lank, D.B., Lecomte, N., Leung, M., Liebezeit, J., Morrison, R., Nol, E., Payer, D.C., Reid, D., Ruthrauff, D.R., Saalfeld, S.T., Sandercock, B., Smith, P., Schmidt, N.M., Tulp, I., Ward, D.H., Hoye, T.T., Berteaux, D., and Bety, J., 2024, A circumpolar study unveils a positive non-linear effect of temperature on arctic arthropod availability that may reduce the risk of warming-induced trophic mismatch for breeding shorebirds: Global Change Biology, v. 30, no. 6, e17356, 17 p., https://doi.org/10.1111/gcb.17356.","productDescription":"e17356, 17 p.","ipdsId":"IP-148021","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":439431,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.17356","text":"External Repository"},{"id":432444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"circumpolar Arctic region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -179.9,\n 85\n ],\n [\n -179.9,\n 58\n ],\n [\n 179.9,\n 58\n ],\n [\n 179.9,\n 85\n ],\n [\n -179.9,\n 85\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"30","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Chagnon-Lafortune, Aurelie","contributorId":341999,"corporation":false,"usgs":false,"family":"Chagnon-Lafortune","given":"Aurelie","email":"","affiliations":[{"id":36676,"text":"Université du Québec à Rimouski","active":true,"usgs":false}],"preferred":false,"id":909423,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duchesne, Eliane","contributorId":342000,"corporation":false,"usgs":false,"family":"Duchesne","given":"Eliane","email":"","affiliations":[{"id":36676,"text":"Université du Québec à Rimouski","active":true,"usgs":false}],"preferred":false,"id":909424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Legagneux, Pierre","contributorId":337103,"corporation":false,"usgs":false,"family":"Legagneux","given":"Pierre","email":"","affiliations":[],"preferred":false,"id":909425,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKinnon, Laura","contributorId":169353,"corporation":false,"usgs":false,"family":"McKinnon","given":"Laura","email":"","affiliations":[],"preferred":false,"id":909426,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reneerkens, Jeroen","contributorId":169357,"corporation":false,"usgs":false,"family":"Reneerkens","given":"Jeroen","email":"","affiliations":[],"preferred":false,"id":909427,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casajus, Nicolas","contributorId":342001,"corporation":false,"usgs":false,"family":"Casajus","given":"Nicolas","email":"","affiliations":[{"id":36676,"text":"Université du Québec à Rimouski","active":true,"usgs":false}],"preferred":false,"id":909428,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Abraham, Kenneth F.","contributorId":139810,"corporation":false,"usgs":false,"family":"Abraham","given":"Kenneth","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":909429,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bolduc, Elise","contributorId":342002,"corporation":false,"usgs":false,"family":"Bolduc","given":"Elise","email":"","affiliations":[{"id":81819,"text":"Universite du Quebec a Rimouski","active":true,"usgs":false}],"preferred":false,"id":909430,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Brown, Glen S.","contributorId":216260,"corporation":false,"usgs":false,"family":"Brown","given":"Glen","email":"","middleInitial":"S.","affiliations":[{"id":39382,"text":"Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":909431,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Brown, Stephen C.","contributorId":38457,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":909475,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gates, H. 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Here, patterns of variation within and among samples of the mouthbrooding gafftopsail catfish (Bagre marinus, Family Ariidae) captured in the U.S. Atlantic and throughout the Gulf of Mexico were analyzed using genomics to generate neutral and non-neutral SNP data sets. Because genomic resources are lacking for ariids, linkage disequilibrium network analysis was used to examine patterns of putatively adaptive variation. Finally, historical demographic parameters were estimated from site frequency spectra. The results show four differentiated groups, corresponding to the (1) U.S. Atlantic, and the (2) northeastern, (3) northwestern, and (4) southern Gulf of Mexico. The non-neutral data presented two contrasting signals of structure, one due to increases in diversity moving west to east and north to south, and another to increased heterozygosity in the Atlantic. Demographic analysis suggested that recently reduced long-term effective population size in the Atlantic is likely an important driver of patterns of genetic variation and is consistent with a known reduction in population size potentially due to an epizootic. Overall, patterns of genetic variation resemble that of other fishes that use the same estuarine habitats as nurseries, regardless of the presence/absence of a larval phase, supporting the idea that adult/juvenile behavior and habitat are important predictors of contemporary patterns of genetic structure.
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Mail Stop 511
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High-quality elevation data are proving to be a resource of great economic value in dealing with many important issues in Ohio. Current and accurate high-resolution elevation data support flood risk management, water quantity and quality assessment, precision farming, conservation planning, impervious-surface modeling, forest and other natural resources management, abandoned mine and geologic hazard assessment, karst mapping, and siting of wellhead pads for horizontal drilling. These data also support coastal zone management, traffic safety and preliminary engineering site-selection studies for transportation infrastructure, solar potential and other renewable energy planning, aviation safety, and identification of features of interest or concern such as archaeological sites and orphan oil and gas wells. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
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\"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, Mail Stop 511
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Significant marine heatwaves (MHWs) developed along the Western Australian coast in 1999 and 2011. Despite ecosystem losses and the southwards occurrence of many tropical fish species during and after the extreme MHW in 2011, there have been few studies on the effects of this MHW on seabirds, and no biological impacts related to the 1999 MHW have been reported. Using data from 1986-2019, we investigated the impacts of these events on breeding outcomes, body condition, diet composition, population size and mortality of little penguins on Penguin Island, in the temperate waters off Western Australia. Breeding outcomes were negatively impacted by the MHWs but body condition was not. Diet composition changed after the MHW, with sandy sprat Hyperlophus vittatus, the penguins’ typical major prey component, replaced by scaly mackerel Sardinella lemuru, a tropical fish species. Using an open robust design analysis that accounts for imperfect capture probabilities and staggered annual arrival and departure dates, we found that the population decreased by 80% following the 2011 MHW. Finally, more penguins died from starvation or from novel protozoal parasitic infections in 2011 and 2012 that were potentially introduced with the changed diet. This research highlights that the temporal and spatial influence of MHWs on seabirds depends on several factors. Furthermore, the magnitude and direction of a prey species’ response can be very localised and have significant impacts on avian predators. There are no obvious ways to mediate climate effects, but perhaps measures taken to reduce any synergistic impacts on prey abundance, particularly during MHW events, could be effective.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps14425","usgsCitation":"Cannell, B., Kendall, W.L., Tyne, J., Bunce, M., Hetzel, Y., Murray, D., and Radford, B., 2024, Marine heatwaves affect breeding, diet and population size but not body condition of a range-edge little penguin colony: Marine Ecology Progress Series, v. 737, p. 193-213, https://doi.org/10.3354/meps14425.","productDescription":"21 p.","startPage":"193","endPage":"213","ipdsId":"IP-148271","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":429888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","otherGeospatial":"Penguin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 115.68697660871345,\n -32.30069384374752\n ],\n [\n 115.68697660871345,\n -32.31026862299318\n ],\n [\n 115.69405059696402,\n -32.31026862299318\n ],\n [\n 115.69405059696402,\n -32.30069384374752\n ],\n [\n 115.68697660871345,\n -32.30069384374752\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"737","noUsgsAuthors":false,"publicationDate":"2024-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Cannell, B.L.","contributorId":337918,"corporation":false,"usgs":false,"family":"Cannell","given":"B.L.","email":"","affiliations":[{"id":16662,"text":"University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":902780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tyne, J.A.","contributorId":337919,"corporation":false,"usgs":false,"family":"Tyne","given":"J.A.","email":"","affiliations":[{"id":6757,"text":"Murdoch University","active":true,"usgs":false}],"preferred":false,"id":902782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bunce, M.","contributorId":337920,"corporation":false,"usgs":false,"family":"Bunce","given":"M.","email":"","affiliations":[{"id":81056,"text":"Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":902783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hetzel, Y.","contributorId":337921,"corporation":false,"usgs":false,"family":"Hetzel","given":"Y.","email":"","affiliations":[{"id":16662,"text":"University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":902784,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murray, D.","contributorId":337924,"corporation":false,"usgs":false,"family":"Murray","given":"D.","email":"","affiliations":[{"id":13639,"text":"Curtin University","active":true,"usgs":false}],"preferred":false,"id":902785,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Radford, B.","contributorId":337926,"corporation":false,"usgs":false,"family":"Radford","given":"B.","email":"","affiliations":[{"id":16662,"text":"University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":902786,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70255969,"text":"70255969 - 2024 - Change in growth and prey utilization for a native salmonid following invasion by an omnivorous minnow in an oligotrophic reservoir","interactions":[],"lastModifiedDate":"2024-07-11T14:30:42.569141","indexId":"70255969","displayToPublicDate":"2024-06-04T09:26:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Change in growth and prey utilization for a native salmonid following invasion by an omnivorous minnow in an oligotrophic reservoir","docAbstract":"Aquatic invasive species can affect food web structure, native fish growth, and production, depending on the traits of the invasive species and the pre-invasion conditions of the ecosystem. Thermal tolerances and behavioral traits can further influence differential exploitation of resources shared between native and invasive species. An unauthorized introduction of redside shiner (Richardsonius balteatus) into reservoirs in the Upper Skagit River, Washington, USA caused concern of potential competition, decreased production, and recruitment of rainbow trout (Oncorhynchus mykiss). We combined bioenergetics modeling and stable isotope analysis with field data to quantify consumption demand of native and invasive fishes and related consumption to the availability of key zooplankton prey. Per capita consumption on Daphnia by redside shiner was low; however, their high abundance imposed considerable demand on prey resources in Ross Lake. Although monthly consumption demand by the fish community was less than 50% of the monthly production and biomass of Daphnia in Ross Lake, the current Daphnia densities and growth of rainbow trout were considerably lower than before the invasion. These reductions correspond to lower annual consumption of Daphnia. Our study provides insight on mechanisms that influence food web impacts of an invasive omnivore in cold-water reservoirs.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-024-05540-3","usgsCitation":"Johnson, R.C., Code, T.J., Stenberg, K.D., Mclean, J.H., Jensen, B.L., Hoy, M.S., and Beauchamp, D., 2024, Change in growth and prey utilization for a native salmonid following invasion by an omnivorous minnow in an oligotrophic reservoir: Hydrobiologia, v. 851, p. 3767-3785, https://doi.org/10.1007/s10750-024-05540-3.","productDescription":"19 p.","startPage":"3767","endPage":"3785","ipdsId":"IP-156682","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":430962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Ross Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.23800601163671,\n 48.99950480041659\n ],\n [\n -121.23800601163671,\n 48.70447051967537\n ],\n [\n -120.91401693322638,\n 48.70447051967537\n ],\n [\n -120.91401693322638,\n 48.99950480041659\n ],\n [\n -121.23800601163671,\n 48.99950480041659\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"851","noUsgsAuthors":false,"publicationDate":"2024-06-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Rachelle Carina 0000-0003-1480-4088","orcid":"https://orcid.org/0000-0003-1480-4088","contributorId":241962,"corporation":false,"usgs":true,"family":"Johnson","given":"Rachelle","email":"","middleInitial":"Carina","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906171,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Code, Tessa Julianne 0000-0003-1481-020X","orcid":"https://orcid.org/0000-0003-1481-020X","contributorId":331687,"corporation":false,"usgs":true,"family":"Code","given":"Tessa","email":"","middleInitial":"Julianne","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stenberg, Karl D. 0000-0001-9802-2707 kstenberg@usgs.gov","orcid":"https://orcid.org/0000-0001-9802-2707","contributorId":3747,"corporation":false,"usgs":true,"family":"Stenberg","given":"Karl","email":"kstenberg@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906173,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mclean, Jonathan H 0000-0001-5940-3689","orcid":"https://orcid.org/0000-0001-5940-3689","contributorId":331688,"corporation":false,"usgs":true,"family":"Mclean","given":"Jonathan","email":"","middleInitial":"H","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906174,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jensen, Benjamin Lorenz 0000-0003-1199-973X","orcid":"https://orcid.org/0000-0003-1199-973X","contributorId":306036,"corporation":false,"usgs":true,"family":"Jensen","given":"Benjamin","email":"","middleInitial":"Lorenz","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906175,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hoy, Marshal S. 0000-0003-2828-9697","orcid":"https://orcid.org/0000-0003-2828-9697","contributorId":220730,"corporation":false,"usgs":true,"family":"Hoy","given":"Marshal","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906176,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906177,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70259261,"text":"70259261 - 2024 - The utility of TerraSAR-X, TanDEM-X, and PAZ for studying global volcanic activity: Successes, challenges, and future prospects","interactions":[],"lastModifiedDate":"2024-10-02T13:56:03.177492","indexId":"70259261","displayToPublicDate":"2024-06-04T08:52:37","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7593,"text":"Volcanica","active":true,"publicationSubtype":{"id":10}},"title":"The utility of TerraSAR-X, TanDEM-X, and PAZ for studying global volcanic activity: Successes, challenges, and future prospects","docAbstract":"TerraSAR-X (TSX), TanDEM-X (TDX), and PAZ Synthetic Aperture Radar data have been used at over 120 volcanoes to assess surface characteristics and change over time. We examine previous work, adding additional examples to understand where and when these data are most useful for volcanology. We focus on volcanoes as part of the Committee on Earth Observation Satellites (CEOS) Volcano Demonstrator Project. TSX/TDX/PAZ data provide a valuable means of detecting small surface changes from amplitude images and topographic changes from bistatic TSX/TDX data. For short temporal and perpendicular baselines, TDX/TSX/PAZ can also provide useful deformation data, even in presence of vegetation. No global background mission currently acquires TSX/TDX/PAZ data at volcanoes: 70 % high spatial resolution data, limiting their suitability for studying pre-eruptive unrest. Coordinated targeting by SAR constellations of priority volcanoes would provide data and insights valuable for forecasting eruptions and associated hazards.
","language":"English","publisher":"Presses universitaires de Strasbourg","doi":"10.30909/vol.07.01.273301","usgsCitation":"Galetto, F., Dualeh, E., Delgado, F., Pritchard, M., Poland, M.P., Ebmeier, S., Shreve, T., Biggs, J., Hamling, I., Wauthier, C., Gonzalez Santana, J., Froger, J., and Bemelmans, M., 2024, The utility of TerraSAR-X, TanDEM-X, and PAZ for studying global volcanic activity: Successes, challenges, and future prospects: Volcanica, v. 7, no. 1, p. 273-301, https://doi.org/10.30909/vol.07.01.273301.","productDescription":"29 p.","startPage":"273","endPage":"301","ipdsId":"IP-157718","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol.07.01.273301","text":"Publisher Index 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Francisco","contributorId":174989,"corporation":false,"usgs":false,"family":"Delgado","given":"Francisco","affiliations":[],"preferred":false,"id":914595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pritchard, Matthew","contributorId":206388,"corporation":false,"usgs":false,"family":"Pritchard","given":"Matthew","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":914596,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914597,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ebmeier, Susanna","contributorId":174225,"corporation":false,"usgs":false,"family":"Ebmeier","given":"Susanna","affiliations":[{"id":7172,"text":"University of Bristol, U.K. and University of Oregon, Eugene","active":true,"usgs":false}],"preferred":false,"id":914598,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shreve, Tara","contributorId":331794,"corporation":false,"usgs":false,"family":"Shreve","given":"Tara","email":"","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":914599,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Biggs, Juliet","contributorId":206389,"corporation":false,"usgs":false,"family":"Biggs","given":"Juliet","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":914600,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hamling, Ian","contributorId":344731,"corporation":false,"usgs":false,"family":"Hamling","given":"Ian","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":914601,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wauthier, Christelle","contributorId":176224,"corporation":false,"usgs":false,"family":"Wauthier","given":"Christelle","email":"","affiliations":[],"preferred":false,"id":914602,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gonzalez Santana, Judit","contributorId":344732,"corporation":false,"usgs":false,"family":"Gonzalez Santana","given":"Judit","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":914603,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Froger, 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Article"},"seriesTitle":{"id":2516,"text":"Journal of the Acoustical Society of America","active":true,"publicationSubtype":{"id":10}},"title":"Feature-based maximum entropy for geophysical properties of the seabed","docAbstract":"The coherent recombination of a direct and seabed reflected path is sensitive to the geophysical properties of the seabed. The concept of feature-based inversion is used in the analysis of acoustic data collected on a vertical line array (VLA) on the New England continental shelf break in about 200 m of water. The analysis approach for the measurements is based on a ray approach in which a direct and bottom reflected path is recombined, resulting in constructive and destructive interference of the acoustic amplitudes with frequency. The acoustic features have the form of prominent nulls of the measured received levels as a function of frequency as a broadband (500–4500 Hz) source passes the closest point of approach to the VLA. The viscous grain shearing (VGS) model is employed to parameterize a two-layer seabed model. The most likely seabed is a sand sediment with a porosity of about 0.42. There is a possibility of a thin (less than 0.5 m) surface layer having a slightly higher porosity between 0.45 and 0.50. Using the estimates for the VGS parameters inferred from the short-range frequency features, a normal mode model is used to predict the received acoustic levels over larger range scales.
","language":"English","publisher":"Acoustical Society of America","doi":"10.1121/10.0026202","usgsCitation":"Knobles, D., Hodgkiss, W.S., Chaytor, J., Neilsen, T., and Lin, Y., 2024, Feature-based maximum entropy for geophysical properties of the seabed: Journal of the Acoustical Society of America, v. 155, https://doi.org/10.1121/10.0026202.","productDescription":"9 p.","startPage":"3567","ipdsId":"IP-161138","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1121/10.0026202","text":"Publisher Index Page"},{"id":465279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"New England shelf break","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.233333,\n 40.1\n ],\n [\n -71.233333,\n 39.6833\n ],\n [\n -70.4333,\n 39.6833\n ],\n [\n -70.4333,\n 40.1\n ],\n [\n -71.233333,\n 40.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"155","edition":"3559","noUsgsAuthors":false,"publicationDate":"2024-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Knobles, D.P.","contributorId":347335,"corporation":false,"usgs":false,"family":"Knobles","given":"D.P.","affiliations":[{"id":83140,"text":"KSA, LLC","active":true,"usgs":false}],"preferred":false,"id":921396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodgkiss, William S..","contributorId":317854,"corporation":false,"usgs":false,"family":"Hodgkiss","given":"William","email":"","middleInitial":"S..","affiliations":[{"id":34004,"text":"Scripps Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":921397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":921398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neilsen, Tracianne","contributorId":347336,"corporation":false,"usgs":false,"family":"Neilsen","given":"Tracianne","email":"","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":921399,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lin, Ying-Tsong","contributorId":302804,"corporation":false,"usgs":false,"family":"Lin","given":"Ying-Tsong","email":"","affiliations":[],"preferred":false,"id":921400,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261472,"text":"70261472 - 2024 - A seismic nodal deployment to understand magmatic structure in the vicinity of the Pahala earthquake swarm","interactions":[],"lastModifiedDate":"2024-12-11T16:56:59.978079","indexId":"70261472","displayToPublicDate":"2024-06-03T09:46:07","publicationYear":"2024","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":"A seismic nodal deployment to understand magmatic structure in the vicinity of the Pahala earthquake swarm","docAbstract":"In summer-fall 2022, 80 three-component SmartSolo IGU-BD3C-5 nodal seismometers were deployed surrounding the Pāhala seismic swarm on the Island of Hawaiʻi, with the goal of improving seismicity catalogs, and seismic velocity images of the crust and upper mantle in this region. The Pāhala swarm, located south of Mauna Loa and Kīlauea, has been the site of a multiyear sustained swarm of seismicity at depths of ~ 25 – 40 km, with order of magnitude increases in rate in 2015, and then again in 2019. This seismicity is possibly related to the input of magma from the mantle plume below, which may then be subsequently transported to volcanic edifices. However, these processes remain enigmatic, in part due to a lack of precise earthquake locations and seismic velocity models in this region. Here we provide an overview of the deployment, an assessment of the quality of the collected data, and discuss the viability of the dataset for local earthquake relocation, tomography, and teleseismic receiver functions. Through comparisons with proximal permanent broadband and short period instruments, we find that the nodes produce high quality data, particularly at periods shorter than 5 s, although we find, document, and correct discrepancies with the gain and polarities of the instruments. We successfully record signals from teleseismic earthquakes, even at periods longer than 5 s (the corner of the flat response of the nodes). We also record local earthquakes, including details related to source characteristics. This indicates that the data is likely to prove useful for investigations using both local and teleseismic earthquake signals to better understand the connections between the deep and shallow magmatic systems of Hawaiʻi. While this deployment provides a snapshot in time, its success may provide a useful benchmark for future studies as the volcanic systems of Hawaiʻi continue to evolve in the future.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240060","usgsCitation":"Janiszewski, H., Bennington, N.L., and Wight, J., 2024, A seismic nodal deployment to understand magmatic structure in the vicinity of the Pahala earthquake swarm: Seismological Research Letters, v. 95, no. 5, p. 3082-3092, https://doi.org/10.1785/0220240060.","productDescription":"11 p.","startPage":"3082","endPage":"3092","ipdsId":"IP-164906","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":465020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.51281317815642,\n 19.2248706279249\n ],\n [\n -155.51281317815642,\n 19.184914533216954\n ],\n [\n -155.44541433375278,\n 19.184914533216954\n ],\n [\n -155.44541433375278,\n 19.2248706279249\n ],\n [\n -155.51281317815642,\n 19.2248706279249\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"95","issue":"5","edition":"2024","noUsgsAuthors":false,"publicationDate":"2024-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Janiszewski, Helen","contributorId":347043,"corporation":false,"usgs":false,"family":"Janiszewski","given":"Helen","affiliations":[{"id":82286,"text":"University of Hawai'i at Mānoa","active":true,"usgs":false}],"preferred":false,"id":920672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennington, Ninfa Lucia 0000-0003-3230-6744","orcid":"https://orcid.org/0000-0003-3230-6744","contributorId":346226,"corporation":false,"usgs":true,"family":"Bennington","given":"Ninfa","email":"","middleInitial":"Lucia","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":920673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wight, Jade","contributorId":347044,"corporation":false,"usgs":false,"family":"Wight","given":"Jade","email":"","affiliations":[{"id":82286,"text":"University of Hawai'i at Mānoa","active":true,"usgs":false}],"preferred":false,"id":920674,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70257451,"text":"70257451 - 2024 - Predicting the odds of chronic wasting disease with Habitat Risk software","interactions":[],"lastModifiedDate":"2024-09-09T16:06:16.803506","indexId":"70257451","displayToPublicDate":"2024-06-03T08:55:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6475,"text":"Spatial and Spatio-temporal Epidemiology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the odds of chronic wasting disease with Habitat Risk software","docAbstract":"Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy that was first detected in captive cervids in Colorado, United States (US) in 1967, but has since spread into free-ranging white-tailed deer (Odocoileus virginianus) across the US and Canada as well as to Scandinavia and South Korea. In some areas, the disease is considered endemic in wild deer populations, and governmental wildlife agencies have employed epidemiological models to understand long-term environmental risk. However, continued rapid spread of CWD into new regions of the continent has underscored the need for extension of these models into broader tools applicable for wide use by wildlife agencies. Additionally, efforts to semi-automate models will facilitate access of technical scientific methods to broader users. We introduce software (Habitat Risk) designed to link a previously published epidemiological model with spatially referenced environmental and disease testing data to enable agency personnel to make up-to-date, localized, data-driven predictions regarding the odds of CWD detection in surrounding areas after an outbreak is discovered. Habitat Risk requires pre-processing publicly available environmental datasets and standardization of disease testing (surveillance) data, after which an autonomous computational workflow terminates in a user interface that displays an interactive map of disease risk. We demonstrated the use of the Habitat Risk software with surveillance data of white-tailed deer from Tennessee, USA.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.sste.2024.100650","usgsCitation":"Walter, W., Hanley, B.J., Them, C.E., Mitchell, C.I., Kelly, J., Grove, D., Hollingshead, N., Abbott, R.C., and Schuler, K., 2024, Predicting the odds of chronic wasting disease with Habitat Risk software: Spatial and Spatio-temporal Epidemiology, v. 49, 100650, 9 p., https://doi.org/10.1016/j.sste.2024.100650.","productDescription":"100650, 9 p.","ipdsId":"IP-135533","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439453,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.sste.2024.100650","text":"Publisher Index Page"},{"id":433630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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At the landscape scale, disturbances and stressors can increase spatial variability and heterogeneity — indicators that can serve as potential early warnings of declining ecosystem resilience. Increased spatial variability in salt marshes at the landscape scale has been used to quantify the propagation of ponding in salt marsh interiors, but ponding at the landscape scale follows a state change rather than predicts it. Here, we suggest a novel application of commonly collected surface elevation table (SET) data and explore millimeter-scale marsh surface microtopography as a potential early indicator of ecosystem transition. We find an increase in spatial variability using multiple metrics of microtopographic heterogeneity in vulnerable salt marsh communities across the North American Atlantic seaboard. Increasing microtopographic heterogeneity in vulnerable salt marshes mirrored increasing trends in variance when a tipping point is approached in other alternative stable state systems — indicating that early warning signals of marsh drowning and ecosystem transition are observable at small-spatial scales prior to runaway ecosystem degradation. Congruence between traditional and novel metrics of marsh vulnerability suggests that microtopographic metrics can be used to identify hidden vulnerability before widespread marsh degradation. This novel analysis can be easily applied to existing SET records expanding the traditional focus on vertical change to additionally encapsulate lateral processes.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-024-01368-1","usgsCitation":"Smith, A., Guntenspergen, G.R., Carr, J., Walters, D., and Kirwan, M.L., 2024, Microtopographic variation as a potential early indicator of ecosystem state change and vulnerability in salt marshes: Estuaries and Coasts, v. 47, p. 2120-2134, https://doi.org/10.1007/s12237-024-01368-1.","productDescription":"15 p.","startPage":"2120","endPage":"2134","ipdsId":"IP-152225","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":439454,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-024-01368-1","text":"Publisher Index Page"},{"id":429630,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Atlantic Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.39758178435103,\n 45.14475385540766\n ],\n [\n -70.3084213352815,\n 44.02821671855119\n ],\n [\n -71.19813131307133,\n 42.49696112101563\n ],\n [\n -71.57437875840237,\n 41.77400052856967\n ],\n [\n -74.40185334833625,\n 40.717694399570604\n ],\n [\n -75.82782658631511,\n 39.87862316287672\n ],\n [\n -76.95565253223305,\n 39.00647866570182\n ],\n [\n -77.26038548427893,\n 38.094322653850526\n ],\n [\n -76.28092406797784,\n 36.66944073621046\n ],\n [\n -75.72598894650827,\n 36.54233944412836\n ],\n [\n -74.75705330756968,\n 38.64678711786095\n ],\n [\n -73.69818233519185,\n 40.18344404740452\n ],\n [\n -71.96808333306974,\n 40.73212702940066\n ],\n [\n -69.6902480827983,\n 41.09470832081422\n ],\n [\n -69.72249581894347,\n 42.0772922743393\n ],\n [\n -70.83603122003584,\n 42.39345455358591\n ],\n [\n -70.33580285947554,\n 42.8225641153189\n ],\n [\n -69.75405469649851,\n 43.62569649795407\n ],\n [\n -66.82164389282606,\n 44.61783474223677\n ],\n [\n -67.39758178435103,\n 45.14475385540766\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","noUsgsAuthors":false,"publicationDate":"2024-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Alexander J.","contributorId":140345,"corporation":false,"usgs":false,"family":"Smith","given":"Alexander J.","affiliations":[{"id":13464,"text":"Environmental Analyst, NY State Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":902307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":902308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":902309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, David 0000-0002-5836-681X waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-5836-681X","contributorId":270366,"corporation":false,"usgs":true,"family":"Walters","given":"David","email":"waltersd@usgs.gov","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":902310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirwan, Matt L.","contributorId":189205,"corporation":false,"usgs":false,"family":"Kirwan","given":"Matt","middleInitial":"L.","affiliations":[],"preferred":false,"id":902311,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257449,"text":"70257449 - 2024 - Integrating presence-only and detection/non-detection data to estimate distributions and expected abundance of difficult-to-monitor species on a landscape-scale","interactions":[],"lastModifiedDate":"2024-09-06T16:55:15.495908","indexId":"70257449","displayToPublicDate":"2024-06-03T07:55:10","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating presence-only and detection/non-detection data to estimate distributions and expected abundance of difficult-to-monitor species on a landscape-scale","docAbstract":"Sea-level rise rates are predicted to surpass rates of wetland vertical adjustment in the coming decades in many areas, increasing the potential for wetland submergence. Information on where wetland migration is possible can help natural resource managers for planning land acquisition or enhancing habitat connectivity to bolster adaptation of coastal wetlands to rising seas. Elevation-based models of wetland migration are often hampered with uncertainty associated with ground surface elevation, current water levels (i.e., tides and extreme water levels), and future water levels from sea-level rise. Here, we developed an approach that involved digital elevation model error reduction and the use of Monte Carlo simulations that utilize uncertainty assumptions regarding elevation error, contemporary water levels, and future sea levels to identify potential wetland migration areas. Our analyses were developed for Duvall and Nassau Counties in northeastern Florida (USA). We focus on the migration of regularly oceanic-flooded wetlands (i.e., flooded by oceanic water daily) and irregularly oceanic-flooded wetlands (i.e., flooded by oceanic water less frequently than daily). For two relative sea-level rise scenarios based on the 0.5 m and the 1.5 m global mean sea-level rise scenarios, we quantified migration by wetland flooding frequency class and identified land cover and land use types that are vulnerable to future exposure to oceanic waters. The variability in total coverage and relative coverage of wetland migration from our results highlights how topography and accelerated sea-level rise interact. Our wetland migration results communicate uncertainty by showing flooding frequency class as probabilistic outputs.
Wildlife telemetry data may be used to answer a diverse range of questions relevant to wildlife ecology and management. One challenge to modeling telemetry data is that animal movement often varies greatly in pattern over time, and current continuous-time modeling approaches to handle such nonstationarity require bespoke and often complex models that may pose barriers to practitioner implementation. We demonstrate a novel application of treed Gaussian process (TGP) modeling, a Bayesian machine learning approach that automatically captures the nonstationarity and abrupt transitions present in animal movement. The machine learning formulation of TGPs enables modeling to be nearly automated, while their Bayesian formulation allows for the derivation of movement descriptors with associated uncertainty measures. We demonstrate the use of an existing R package to implement TGPs using the familiar Markov chain Monte Carlo algorithm. We then use estimated movement trajectories to derive movement descriptors that can be compared across individuals and populations. We applied the TGP model to a case study of lesser prairie-chickens (Tympanuchus pallidicinctus) to demonstrate the benefits of TGP modeling and compared distance traveled and residence times across lesser prairie-chicken individuals and populations. For broad usability, we outline all steps necessary for practitioners to specify relevant movement descriptors (e.g., turn angles, speed, contact points) and apply TGP modeling and trajectory comparison to their own telemetry datasets. Combining the predictive power of machine learning and the statistical inference of Bayesian methods to model movement trajectories allows for the estimation of statistically comparable movement descriptors from telemetry studies. Our use of an accessible R package allows practitioners to model trajectories and estimate movement descriptors, facilitating the use of telemetry data to answer applied management questions.
Invasive carp tracking, monitoring, and contracted removal will continue throughout the Upper IWW system as part of an adaptive management effort to mitigate, control, and contain invasive carp. To help facilitate these actions, there is a need to compile and analyze data from the multitude of partner agencies that are collecting invasive carp-related data throughout the Illinois River system. These data are often in disparate formats, and integrating these data into a common format allows both researchers and managers to assess invasive carp monitoring, control, and removal efforts at several scales is necessary. Ensuring the interoperability of these data sets allows for their use in various analyses and modeling efforts. Implementing an interoperable data management framework also provides mechanisms for end users to find and use existing data. Integrating data for use in modeling and analysis furthers the MRWG partnership’s collective understanding of invasive carp life history, distribution, and movement and can be used to facilitate adaptive management actions (e.g., directing monitoring, sampling, and removal efforts; assessing invasive carp abundance to support modeling efforts; informing deployment of control actions). An effective data management strategy will streamline the database update process, providing partners with timely, well-organized, uniformly formatted data and analyses in support of informed decision-making processes.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2023 Monitoring and response plan","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Invasive Carp Regional Coordinating Committee","usgsCitation":"Brey, M.K., and Fritts, A.K., 2024, USGS invasive carp database management & integration support, 4 p.","productDescription":"4 p.","startPage":"90","endPage":"93","ipdsId":"IP-151293","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":432420,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://invasivecarp.us/PlansReports.html","linkFileType":{"id":5,"text":"html"}},{"id":432447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.48380903104598,\n 41.68958409016773\n ],\n [\n -87.64143789713586,\n 41.8332919304695\n ],\n [\n -89.48044133484973,\n 41.38806459671454\n ],\n [\n -90.75022942279477,\n 39.83926695317629\n ],\n [\n -90.66265783052245,\n 39.082040884611246\n ],\n [\n -90.47000032752403,\n 38.809609526616384\n ],\n [\n -90.39118589447908,\n 38.89826454066113\n ],\n [\n -90.39118589447908,\n 39.86615823720618\n ],\n [\n -89.32281246875988,\n 40.847090394251495\n ],\n [\n -89.200212239579,\n 41.184074184856854\n ],\n [\n -88.24568188381326,\n 41.32233092104789\n ],\n [\n -87.80782392245264,\n 41.46029495699605\n ],\n [\n -87.48380903104598,\n 41.68958409016773\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":909371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fritts, Andrea K. 0000-0003-2142-3339","orcid":"https://orcid.org/0000-0003-2142-3339","contributorId":204594,"corporation":false,"usgs":true,"family":"Fritts","given":"Andrea","email":"","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":909372,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70259356,"text":"70259356 - 2024 - North American bird banding program longevity records","interactions":[],"lastModifiedDate":"2024-10-04T14:35:43.621082","indexId":"70259356","displayToPublicDate":"2024-06-01T09:31:19","publicationYear":"2024","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":18732,"text":"North American Bird Bander","active":true,"publicationSubtype":{"id":30}},"title":"North American bird banding program longevity records","docAbstract":"Longevity in wild birds refers to the longest-lived individual of any particular species. This measure of age can reflect important life history traits and identifying differences in longevity patterns between species can reveal unique threats or conservation needs. Because it requires the identification of individual birds, longevity can usually only be measured through banding or marking of individuals. A bird’s age can generally be determined at the time of banding and then recalculated whenever the bird is subsequently recovered, recaptured, or resighted. The North American Bird Banding Program (NABBP), comprised of the U.S. Geological Survey Eastern Ecological Science Center Bird Banding Laboratory (BBL) and Canada’s Bird Banding Office (BBO), curates a vast dataset of all North American bird banding records, as well as subsequent encounters of banded birds reported by banders and members of the public. Although not all bird populations are banded equally and band encounters are only reported voluntarily, the NABBP is thus uniquely situated to catalogue and report longevity records for bird species under our purview.","language":"English","publisher":"Eastern Bird Banding Association","usgsCitation":"Walker, L.E., Rogosky, M., and Harvey, K., 2024, North American bird banding program longevity records: North American Bird Bander, v. 49, no. 2, p. 58-60.","productDescription":"3 p.","startPage":"58","endPage":"60","ipdsId":"IP-165183","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":462571,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://easternbirdbanding.org/volume-49-number-2-apr-jun-2024/","linkFileType":{"id":5,"text":"html"}},{"id":462599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walker, Lauren Emily 0000-0002-4316-3577","orcid":"https://orcid.org/0000-0002-4316-3577","contributorId":344936,"corporation":false,"usgs":true,"family":"Walker","given":"Lauren","email":"","middleInitial":"Emily","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":915025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogosky, Matthew 0000-0001-6053-5742","orcid":"https://orcid.org/0000-0001-6053-5742","contributorId":344937,"corporation":false,"usgs":true,"family":"Rogosky","given":"Matthew","email":"","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":915026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harvey, Kyra 0000-0003-4781-1874","orcid":"https://orcid.org/0000-0003-4781-1874","contributorId":296250,"corporation":false,"usgs":true,"family":"Harvey","given":"Kyra","email":"","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":915027,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}