Two Monitoring Avian Productivity and Survivorship (MAPS) stations were operated at Marine Corps Base Camp Pendleton (MCBCP), California, in 2021: one at De Luz Creek and one at the Santa Margarita River. The stations were established to provide data on Neotropical migratory birds at MCBCP to support the dual missions of environmental stewardship and military readiness.
A total of 1,227 individual birds were captured in 2021 between the two stations: 395 at De Luz and 832 at Santa Margarita (both 15 banding days). Of these 1,227 individuals captured, 955 were newly banded (273 at De Luz and 682 at Santa Margarita), 150 were recaptures banded before 2021 (28 at De Luz and 122 at Santa Margarita, excluding recaptures released before reading band number [1 at De Luz and 3 at Santa Margarita]), and 118 were unbanded (93 at De Luz and 25 at Santa Margarita). Return rate in 2021 was much lower than the annual mean at De Luz (1995–2019) and similar to the annual mean at the Santa Margarita station (1998–2020). The sex ratio of known-sex adult birds was skewed toward males at both stations in 2021.
Species richness was similar at De Luz from 2019 to 2021, increased at Santa Margarita from 2020 to 2021 and was above annual means at both sites (1995–2019 and 1998–2020, respectively). The most abundant species at De Luz were Wrentit (Chamaea fasciata) and Allen’s Hummingbird (Selasphorus sasin). Song Sparrow (Melospiza melodia) and Common Yellowthroat (Geothlypis trichas) were most abundant at Santa Margarita.
Since 2002, we have examined the population trends of 12 species at De Luz and 13 species at Santa Margarita for which numbers of known-age individuals were adequate for statistical analysis. We estimated population size and calculated indices of productivity and survival for a subset of these species with sufficient captures and recaptures for valid parameter estimation—four at De Luz and six at Santa Margarita. We determined that in 2021, abundance of 42 percent (5 of 12) of focal species at De Luz and 38 percent (5 of 13) of focal species at Santa Margarita was below the annual mean abundance. Of the focal species below mean abundance, 40 percent (2 of 5) at De Luz and 60 percent (3 of 5) at Santa Margarita were migrant populations. Of the focal species, 25 (3 of 12) percent at De Luz and 31 percent (4 of 13) at Santa Margarita had declining population trends during the span of station operation. With few exceptions, these declines appeared to be associated with conditions on the breeding grounds.
Annual productivity (calculated as the ratio of juveniles to adults among individual captures) was zero for all focal species at De Luz in 2021. At Santa Margarita, productivity increased from year 2020 to 2021 for Common Yellowthroat, Song Sparrow, and Yellow Warbler (Setophaga petechia) and declined from year 2020 to 2021 for Least Bell’s Vireo (Vireo bellii pusillus), but productivity was above the 1998–2020 mean for all four species, whereas productivity was maintained for Orange-crowned Warbler (Leiothlypis celata) and Yellow-breasted Chat (Icteria virens). Winter precipitation affected productivity of Black-headed Grosbeak (Pheucticus melanocephalus), Common Yellowthroat, and Song Sparrow at De Luz and affected productivity of Common Yellowthroat, Orange-crowned Warbler, Song Sparrow, Yellow-breasted Chat, and Yellow Warbler at Santa Margarita.
We calculated the mean annual adult survival for 1998–2020 at Santa Margarita, excluding years when the station was not operated. Survival could not be calculated for De Luz in 2021 because the station was not operated in 2020. Model-averaged annual adult survival ranged from 42 to 66 percent for residents and from 30 to 66 percent for migrants at Santa Margarita. Survival of Common Yellowthroat, Song Sparrow, and possibly Yellow Warbler was found to be affected by winter precipitation. Sex was a significant predictor of survival for Common Yellowthroat, Least Bell’s Vireo, Orange-crowned Warbler, and Yellow-breasted Chat at Santa Margarita, where females were found to have lower survival than males.
At Santa Margarita, multiple regression analyses examining adult survival and productivity as predictors of future population size indicated that resident Song Sparrow and migrant Yellow Warbler populations were affected by population size from the previous year, migrant Yellow-breasted Chat populations were affected by productivity from the previous year, and migrant Orange-Crowned Warbler populations were affected by survival from the previous year. Updated previous-year population size predictions could not be calculated for De Luz because the station was not operated in 2020.
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Drought is one of the key drivers of food insecurity in Afghanistan, which is among the most food insecure countries in the world. In this study, we build on previous research and seek to answer the central question: “What is the influence of El Niño-Southern Oscillation (ENSO) on drought outlooks and agricultural yield outcome in Afghanistan, and how do these influences vary spatially?” We do so by utilizing multiple indicators of droughts and available wheat yield reports. We find a clear distinction in the probability of drought (defined as being in the lower tercile) in Afghanistan during La Niña compared to El Niño events since 1981. The probability of drought in Afghanistan increased during La Niña, particularly in the North, Northeast, and West regions. La Niña events are related to an increase in the probability of snow drought, particularly in parts of the Amu Darya basin. It is found that relative to El Niño events, snow water equivalent [total runoff] during La Niña events January–March (March–July total runoff) decreases between 9% and 30% (28%–42%) for the five major basins in the country. The probability of agricultural drought during La Niña events is found to be higher than 70% in the rainfed and irrigated areas of the Northeast, North, and West regions. This result is at least partly supported by reported wheat yield composites related to La Niña events that tend to be lower than for El Niño events across all regions in the case of rainfed wheat (statistically significant in Northeast, West, and South regions) and in some cases for irrigated wheat. The results of this study have direct implications for improving early warning of worsening food insecurity in Afghanistan during La Niña events, given that we now have long-lead and skillful forecasts of ENSO up to 18–24 months in advance, which could potentially be used to provide earlier warning of worsening food insecurity in Afghanistan
","language":"English","publisher":"Elsevier","doi":"10.1016/j.wace.2024.100697","usgsCitation":"Shukla, S., Zaheer, F., Hoell, A., Anderson, W., Jayanthi, H., Husak, G., Lee, D., Barker, B., Pervez, S., Slinski, K., Justice, C., Rowland, J., McNally, A., Budde, M., and Verdin, J., 2024, ENSO-based outlook of droughts and agricultural outcomes in Afghanistan: Weather and Climate Extremes, v. 45, 100697, 16 p., https://doi.org/10.1016/j.wace.2024.100697.","productDescription":"100697, 16 p.","ipdsId":"IP-155371","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":493783,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.wace.2024.100697","text":"Publisher Index 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Whereas event-based forecasting approaches have been successful, some eruptions remain unanticipated, resulting in casualties and damage. Our study leverages the recent advancements in ambient field seismology. We explore features extracted from continuous ambient fields using traditional methods, for example, peak ground velocity, peak ground acceleration, root mean square, root median square, real-time seismic amplitude measurement, and novel methods (displacement seismic amplitude ratio and spectral width). In addition, we explore unsupervised learning of higher order wavelet features using scattering networks. We find that combining all the methods was necessary to disentangle the effects of seismic sources from structural changes at Mount St. Helens. Although the ambient wavefield-based approach does not yield additional or more significant precursory signals than event-based methods at Mount St. Helens, our study demonstrates that the ambient wavefield provides supplementary information, mainly about structural changes and complements traditional methods. The ambient seismic wavefield offers additional insights into long-lasting processes. We find enhanced wave attenuation correlating with geochemical measurements. We interpret this as ongoing structural changes, such as dome growth or the evolution of the volcanic conduit system. On annual and decadal timescales, we interpret seasonal seismic attenuation in the shallow subsurface as groundwater fluctuations, corroborated by observations at the nearby Spirit Lake level. This multimethod approach at Mount St. Helens sheds light on a volcanic system’s underlying dynamics and structure.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240079","usgsCitation":"Kopfli, M., Denolle, M.A., Thelen, W., Makus, P., and Malone, S.D., 2024, Examining 22 years of ambient seismic wavefield at Mount St. Helens: Seismological Research Letters, v. 95, no. 5, p. 2622-2636, https://doi.org/10.1785/0220240079.","productDescription":"15 p.","startPage":"2622","endPage":"2636","ipdsId":"IP-165361","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":502426,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://gfzpublic.gfz-potsdam.de/pubman/item/item_5028930","text":"External Repository"},{"id":463321,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.31756649267834,\n 46.312979175785955\n ],\n [\n -122.31756649267834,\n 46.11452113542518\n ],\n [\n -122.04090627523671,\n 46.11452113542518\n ],\n [\n -122.04090627523671,\n 46.312979175785955\n ],\n [\n -122.31756649267834,\n 46.312979175785955\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"95","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Kopfli, Manuela","contributorId":345688,"corporation":false,"usgs":false,"family":"Kopfli","given":"Manuela","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":917258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Denolle, Marine A.","contributorId":345689,"corporation":false,"usgs":false,"family":"Denolle","given":"Marine","email":"","middleInitial":"A.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":917259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thelen, Weston 0000-0003-2534-5577","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":215530,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Makus, Peter","contributorId":345690,"corporation":false,"usgs":false,"family":"Makus","given":"Peter","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":917261,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Malone, Stephen D.","contributorId":202015,"corporation":false,"usgs":false,"family":"Malone","given":"Stephen","email":"","middleInitial":"D.","affiliations":[{"id":34100,"text":"Earth and Space Sciences, University of Washington, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":917262,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256219,"text":"70256219 - 2024 - An ensemble mean method for remote sensing of actual evapotranspiration to estimate water budget response across a restoration landscape","interactions":[],"lastModifiedDate":"2024-07-29T13:58:25.97437","indexId":"70256219","displayToPublicDate":"2024-06-12T08:41:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"An ensemble mean method for remote sensing of actual evapotranspiration to estimate water budget response across a restoration landscape","docAbstract":"Estimates of actual evapotranspiration (ETa) are valuable for effective monitoring and management of water resources. In areas that lack ground-based monitoring networks, remote sensing allows for accurate and consistent estimates of ETa across a broad scale—though each algorithm has limitations (i.e., ground-based validation, temporal consistency, spatial resolution). We developed an ensemble mean ETa (EMET) product to incorporate advancements and reduce uncertainty among algorithms (e.g., energy-balance, optical-only), which we use to estimate vegetative water use in response to restoration practices being implemented on the ground using management interventions (i.e., fencing pastures, erosion control structures) on a private ranch in Baja California Sur, Mexico. This paper describes the development of a monthly EMET product, the assessment of changes using EMET over time and across multiple land use/land cover types, and the evaluation of differences in vegetation and water distribution between watersheds treated by restoration and their controls. We found that in the absence of a ground-based monitoring network, the EMET product is more robust than using a single ETa data product and can augment the efficacy of ETa-based studies. We then found increased ETa within the restored watershed when compared to the control sites, which we attribute to increased plant water availability.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16122122","usgsCitation":"Petrakis, R., Norman, L., Villarreal, M.L., Senay, G.B., Friedrichs, M., Cassassuce, F., Gomis, F., and Nagler, P.L., 2024, An ensemble mean method for remote sensing of actual evapotranspiration to estimate water budget response across a restoration landscape: Remote Sensing, v. 16, no. 12, 2122, 35 p.; Data Release, https://doi.org/10.3390/rs16122122.","productDescription":"2122, 35 p.; Data Release","ipdsId":"IP-160120","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":439410,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16122122","text":"Publisher Index Page"},{"id":434943,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZBXG2R","text":"USGS data release","linkHelpText":"Monthly Ensemble Mean Evapotranspiration (EMET) Product for the Los Planes basin in Baja California Sur, Mexico from January 2006 through December 2021: U.S. Geological Survey Data Release"},{"id":431560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Baja California Sur","otherGeospatial":"Los Planes Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.15,\n 24.185882621902465\n ],\n [\n -110.15,\n 23.666\n ],\n [\n -109.796162654228,\n 23.666\n ],\n [\n -109.796162654228,\n 24.185882621902465\n ],\n [\n -110.15,\n 24.185882621902465\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Petrakis, Roy E. 0000-0001-8932-077X 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mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":907136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":907137,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Friedrichs, MacKenzie 0000-0002-9602-321X 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Ancon","active":true,"usgs":false}],"preferred":false,"id":907140,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":907141,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70255312,"text":"70255312 - 2024 - Source, migration pathways, and atmospheric release of geologic methane associated with the complex permafrost regimes of the outer Mackenzie River Delta, Arctic, Canada","interactions":[],"lastModifiedDate":"2024-06-17T12:07:59.713806","indexId":"70255312","displayToPublicDate":"2024-06-12T07:06:05","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Source, migration pathways, and atmospheric release of geologic methane associated with the complex permafrost regimes of the outer Mackenzie River Delta, Arctic, Canada","docAbstract":"Sources and fluxes of methane to the atmosphere from permafrost are significant but poorly constrained in global climate models. We present data collected from the variable permafrost setting of the outer Mackenzie River Delta, including observations of aquatic methane seepage, core determinations of in situ methane occurrence and seep gas isotope geochemistry. The sources and locations of in situ geologic methane occurrence and aquatic and atmospheric gas release appear to be controlled by the regional geology and permafrost conditions. Where permafrost is >250 m thick, thermogenic gas deposits at depth are isolated by laterally continuous, low permeability ice-bearing sediments with few through-going thawed taliks. Thus, the observed in situ methane and aquatic gas seepage appears to be dominated by microbial methane. In contrast, where permafrost is <80 m thick, taliks are more likely to be through-going, providing permeable conduits from depth and migration pathways for both thermogenic and biogenic gas. Continuous annual fluid sampling of two lakes and a river channel documents aquatic methane flux from microbial sources, more deeply buried thermogenic sources, and mixtures of both. Using estimates of in situ methane concentration from deep core samples and observations of in situ free gas occurrences, we conclude that the reservoir of in situ geologic methane within ice bonded permafrost is substantial and that this methane is presently migrating with ongoing atmospheric release. It is our assessment that the permafrost setting, and processes described are sensitive to future climate change as the permafrost warms.
The concentration of chlorophyll a in phytoplankton and periphyton represents the amount of algal biomass. We compiled an 18-year record (2005–2022) of pigment data from water bodies across the United States (US) to support efforts to develop process-based, machine learning, and remote sensing models for prediction of harmful algal blooms (HABs). To our knowledge, this dataset of nearly 84,000 sites and over 1,374,000 pigment measurements is the largest compilation of harmonized discrete, laboratory-extracted chlorophyll data for the US. These data were compiled from the Water Quality Portal (WQP) and previously unpublished U.S. Geological Survey’s National Water Quality Laboratory (NWQL) data. Data were harmonized for reporting units, pigment type, duplicate values, collection depth, site name, negative values, and some extreme values. Across the country, data show great variation by state in sampling frequency, distribution, and methods. Uses for such data include the calibration of models, calibration of field sensors, examination of relationship to nutrients and other drivers, evaluation of temporal trends, and other applications addressing local to national scale concerns.
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road
Mail Stop 977
Menlo Park, CA 94025
Offshore of the Pacific Northwest of the United States is the Cascadia Subduction Zone, a 1,000-kilometer-long tectonic boundary defined by a large fault, called a megathrust, that extends from the Mendocino Junction off northern California to the Nootka Fracture Zone off Vancouver Island, Canada (U.S. Geological Survey, 2023). The Juan de Fuca and Gorda oceanic plates to the west of this boundary subduct under the North America continental plate to the east. Several other smaller faults that cut through the North America plate crust also affect the region. Although their effects upon Ozette Lake are uncertain, geological evidence for past earthquakes, such as underwater landslides, may be found in Pacific Northwest lakes.
Underwater landslides caused by past earthquakes should be well preserved in these relatively undisturbed lake environments. The floor of Ozette Lake, Washington, located along the Pacific coast of the United States, west of the Puget Sound region and about 140 kilometers east of the megathrust was mapped by the U.S. Geological Survey in July of 2019 to search for evidence of past earthquakes. Mapping was completed using a SWATHplus-M 234-kHz interferometric side scan sonar system pole-mounted on the U.S. Geological Survey research vessel San Lorenzo. The system collected full-coverage bathymetric and acoustic backscatter data that were processed to 2-meter spatial resolution (Dartnell and others, 2024). This two-map series displays the results of this mapping. A colored shaded relief bathymetry map (sheet 1) and an acoustic backscatter map (sheet 2) show the lake floor morphology and backscatter intensities, respectively, that can be analyzed for evidence of past earthquakes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3517","usgsCitation":"Dartnell, P., Brothers, D., Ritchie, A.C., Sherrod, B., Currie, J.E., Dal Ferro, P., and Powers, D.C., 2024, Colored shaded relief bathymetry and acoustic backscatter of Ozette Lake, Washington: U.S. Geological Survey Scientific Investigations Map 3517, 2 sheets, scale 1:18,000, https://doi.org/10.3133/sim3517.","productDescription":"2 Sheets: 27.81 × 37.40 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-155366","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":429905,"rank":1,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3517/sim3517_sheet1.pdf","text":"Sheet 1","size":"45 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Colored shaded relief bathymetry map"},{"id":429906,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3517/sim3517_sheet2.pdf","text":"Sheet 2","size":"50 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Acoustic backscatter map"},{"id":429912,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3517/covrthb.jpg"},{"id":499286,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117068.htm","linkFileType":{"id":5,"text":"html"}},{"id":429913,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U91FSB","text":"USGS Data Release","description":"Dartnell, P., Brothers, D.S., Ritchie, A.C.,Sherrod, B., Currie, J.E., Dal Ferro, P., Powers, D.C., 2024, Bathymetry and acoustic-backscatter data for Ozette Lake, Washington collected during USGS field activity 2019-622-FA: U.S. Geological Survey data release, https://doi.org/10.5066/P9U91FSB.","linkHelpText":"Bathymetry and acoustic-backscatter data for Ozette Lake, Washington collected during USGS field activity 2019-622-FA"}],"country":"United States","state":"Washington","otherGeospatial":"Ozette Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.7303438621736,\n 48.18265809125998\n ],\n [\n -124.7303438621736,\n 48.025264988649184\n ],\n [\n -124.54883551443689,\n 48.025264988649184\n ],\n [\n -124.54883551443689,\n 48.18265809125998\n ],\n [\n -124.7303438621736,\n 48.18265809125998\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Letterkenny Army Depot in Chambersburg, Pennsylvania, built an Ammonium Perchlorate Rocket Motor Destruction (ARMD) Facility in 2016 to centralize rocket motor destruction and contain all waste during the destruction process. The U.S. Geological Survey has collected environmental samples from groundwater, surface water, and soils at ARMD since 2016.
During 2021, samples were collected from four groundwater wells in September, one surface-water site in October, and five soil sites in November near the facility. Samples were analyzed for nutrients, trace metals, major ions, total volatile organic compounds, and perchlorate. Perchlorate was not detected in any 2021 samples.
Groundwater results showed no constituents exceeded any U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL). Dissolved arsenic (As) was detected in one well above the reporting detection level (RDL) of 3 micrograms per liter (μg/L) at 5.4 μg/L but below its MCL of 10 μg/L. Dissolved iron (Fe) was the only inorganic constituent measured above an EPA secondary maximum contaminant level (SMCL). All groundwater samples collected in 2021 exceeded the Fe SMCL of 300 μg/L, with concentrations ranging from 390 μg/L to 3,500 μg/L.
Surface-water data collected during 2021 showed no measured constituents in the surface-water sample that exceeded any EPA MCL or SMCL.
Soil samples collected from 2016 through 2021 showed all concentrations of As exceeded the EPA soil screening levels of 3 milligrams per kilogram (mg/kg) but did not exceed the Pennsylvania medium-specific concentrations for As of 61 mg/kg. Arsenic concentrations in 2021 ranged from 9.1 mg/kg to 12.9 mg/kg.
The 2021 results for the ARMD Facility indicate no increases in concentrations of reported compounds compared to data from 2016 to 2020. The contained burn treatment facility for demilitarization of rocket motors during 2021 appears to have operated without elevating concentrations of target compounds compared to previous years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241031","collaboration":"Prepared in Cooperation with the Letterkenny Army Depot","usgsCitation":"Galeone, D.G., and Donmoyer, S.J., 2024, Environmental monitoring of groundwater, surface water, and soil at the Ammonium Perchlorate Rocket Motor Destruction Facility at the Letterkenny Army Depot, Chambersburg, Pennsylvania, 2021: U.S. Geological Survey Open-File Report 2024–1031, 31 p., https://doi.org/10.3133/ofr20241031","productDescription":"Report: vii, 31 p.; Data Release","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-148346","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":499252,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117074.htm","linkFileType":{"id":5,"text":"html"}},{"id":429681,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1031/ofr20241031.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1031 XML"},{"id":429679,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92YIATZ","text":"USGS data release","linkHelpText":"Groundwater, surface water, and soil data collected near and at the Ammonium Perchlorate Rocket Motor Destruction (ARMD) facility at the Letterkenny Army Depot, Chambersburg, Pennsylvania"},{"id":429680,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1031/images/"},{"id":429677,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1031/ofr20241031.pdf","text":"Report","size":"2.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1031 PDF"},{"id":429678,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241031/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1031 HTML"},{"id":429676,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1031/coverthb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Letterkenny Army Depot","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.7937803364734,\n 40.07953712912567\n ],\n [\n -77.7937803364734,\n 39.95565132046923\n ],\n [\n -77.61334530644311,\n 39.95565132046923\n ],\n [\n -77.61334530644311,\n 40.07953712912567\n ],\n [\n -77.7937803364734,\n 40.07953712912567\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
This study was completed to provide timely scientific information regarding greater sage-grouse population trends, habitat selection, and the efficacy of previous conservation actions implemented to benefit the Bi-State Distinct Population Segment (DPS). Specifically, we provide these analyses to inform the current (2024) status review and pending listing decision for the DPS being undertaken by the U.S. Fish and Wildlife Service. These findings provide updated, detailed, and comprehensive information regarding the status of a geographically isolated and genetically distinct population of a species of high conservation concern and their habitat. Importantly, this report also provides information on the efficacy of previously implemented conservation actions targeting the Bi-State DPS in a framework that is transferable throughout the species’ range.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241030","collaboration":"Prepared in cooperation with the Nevada Department of Wildlife, California Department of Fish and Wildlife, U.S. Fish and Wildlife Service, Bureau of Land Management, Great Basin Bird Observatory, and U.S. Forest Service","programNote":"Ecosystems Mission Areas—Species Management Research Program","usgsCitation":"Coates, P.S., Milligan, M.C., Prochazka, B.G., Brussee, B.E., O’Neil, S.T., Lundblad, C.G., Webster, S.C., Weise, C.L., Mathews, S.R., Chenaille, M.P., Aldridge, C.L., O’Donnell, M.S., Espinosa, S.P., Sturgill, A.C., Doherty, K.E., Tull, J.C., Miller, K., Wiechman, L.A., Abele, S., Boone, J., Stone, H., and Casazza, M.L., 2024, Status of greater sage-grouse in the Bi-State Distinct Population Segment—An evaluation of population trends, habitat selection, and efficacy of conservation actions: U.S. Geological Survey Open-File Report 2024–1030, 74 p., https://doi.org/10.3133/ofr20241030.","productDescription":"Report: x, 74 p.; 2 Data Releases","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-159648","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":429902,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1AATW9D","text":"USGS Data Release","description":"Coates, P.S., Milligan, M.C., Brussee, B.E., O’Neil, S.T., and Chenaille, M.P., 2024, Greater sage-grouse habitat selection, survival, abundance, and space-use in the Bi-State Distinct Population Segment of California and Nevada: U.S. Geological Survey data release, https://doi.org/10.5066/P1AATW9D","linkHelpText":"Greater sage-grouse habitat selection, survival, abundance, and space-use in the Bi-State Distinct Population Segment of California and Nevada"},{"id":429901,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95HTJG8","text":"USGS Data Release","description":"Coates, P.S., Milligan, M.C., Brussee, B.E., O’Neil, S.T., and Chenaille, M.P., 2024, Rasters and tables for selection and survival of greater sage-grouse nests and broods in the Bi-State Distinct Population Segment of California and Nevada: U.S. Geological Survey data release, https://doi.org/10.5066/P95HTJG8.","linkHelpText":"Rasters and tables for selection and survival of greater sage-grouse nests and broods in the Bi-State Distinct Population Segment of California and Nevada"},{"id":429897,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1030/ofr20241030.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":429896,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1030/covrthb.jpg"},{"id":429898,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1030/ofr20241030.xml"},{"id":429899,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1030/images"},{"id":429900,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241030/full"}],"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 -120.20887464654662,\n 39.28064195888885\n ],\n [\n -120.20887464654662,\n 36.4538803548043\n ],\n [\n -116.49549574029646,\n 36.4538803548043\n ],\n [\n -116.49549574029646,\n 39.28064195888885\n ],\n [\n -120.20887464654662,\n 39.28064195888885\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
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":70255067,"text":"70255067 - 2024 - Potential hazards of polycyclic aromatic hydrocarbons in Great Lakes tributaries using water column and porewater passive samplers and sediment wquilibrium partitioning","interactions":[],"lastModifiedDate":"2024-07-01T14:50:05.168294","indexId":"70255067","displayToPublicDate":"2024-06-11T10:03:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Potential hazards of polycyclic aromatic hydrocarbons in Great Lakes tributaries using water column and porewater passive samplers and sediment wquilibrium partitioning","docAbstract":"The potential for polycyclic aromatic hydrocarbon (PAH)-related effects in benthic organisms is commonly estimated from organic carbon-normalized sediment concentrations based on equilibrium partitioning (EqP). Although this approach is useful for screening purposes, it may overestimate PAH bioavailability by orders of magnitude in some sediments, leading to inflated exposure estimates and potentially unnecessary remediation costs. Recently, passive samplers have been shown to provide an accurate assessment of the freely dissolved concentrations of PAHs, and thus their bioavailability and possible biological effects, in sediment porewater and overlying surface water. We used polyethylene passive sampling devices (PEDs) to measure freely dissolved porewater and water column PAH concentrations at 55 Great Lakes (USA/Canada) tributary locations. The potential for PAH-related biological effects using PED concentrations were estimated with multiple approaches by applying EqP, water quality guidelines, and pathway-based biological activity based on in vitro bioassay results from ToxCast. Results based on the PED-based exposure estimates were compared with EqP-derived exposure estimates for concurrently collected sediment samples. The results indicate a potential overestimation of bioavailable PAH concentrations by up to 960-fold using the EqP-based method compared with measurements using PEDs. Even so, PED-based exposure estimates indicate a high potential for PAH-related biological effects at 14 locations. Our findings provide an updated, weight-of-evidence–based site prioritization to help guide possible future monitoring and mitigation efforts.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.5896","usgsCitation":"Baldwin, A.K., Corsi, S., Alvarez, D.A., Villeneuve, D.L., Ankley, G., Blackwell, B., Mills, M.A., Lenaker, P.L., and Nott, M.A., 2024, Potential hazards of polycyclic aromatic hydrocarbons in Great Lakes tributaries using water column and porewater passive samplers and sediment wquilibrium partitioning: Environmental Toxicology and Chemistry, v. 43, no. 7, p. 1509-1523, https://doi.org/10.1002/etc.5896.","productDescription":"15 p.","startPage":"1509","endPage":"1523","ipdsId":"IP-150118","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":439414,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5896","text":"Publisher Index Page"},{"id":430014,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Pennsylvania, Wisconsin","otherGeospatial":"Great lakes tributaries","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.50038664600407,\n 47.734293732737\n ],\n [\n -93.32668214062738,\n 47.781822909562834\n ],\n [\n -93.66522319683997,\n 46.6205914248724\n ],\n [\n -90.10144072177354,\n 45.72245658797377\n ],\n [\n -89.24336353619054,\n 43.31706446043586\n ],\n [\n -87.74990312848416,\n 41.14799638657436\n ],\n [\n -84.68233074166602,\n 40.27325147141107\n ],\n [\n -80.98474656912649,\n 40.9132970607065\n ],\n [\n -75.35756182467634,\n 42.91509952407404\n ],\n [\n -75.72359765908611,\n 44.31876428021542\n ],\n [\n -76.89109191305005,\n 43.68270068891388\n ],\n [\n -79.27814795358721,\n 43.46605571456897\n ],\n [\n -78.96930286423293,\n 42.9910648317088\n ],\n [\n -82.81924582493077,\n 41.844014344440694\n ],\n [\n -83.20482143032358,\n 42.31054790382913\n ],\n [\n -82.31114877039539,\n 42.8842174758241\n ],\n [\n -81.9076889466279,\n 44.500553732181515\n ],\n [\n -84.24318006713943,\n 46.72260994496574\n ],\n [\n -87.10560312557051,\n 47.83801940362676\n ],\n [\n -90.50038664600407,\n 47.734293732737\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"43","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":903310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":903311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alvarez, David A. 0000-0002-6918-2709","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":220763,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":903312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villeneuve, David L.","contributorId":338508,"corporation":false,"usgs":false,"family":"Villeneuve","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":903313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ankley, Gerald T.","contributorId":332307,"corporation":false,"usgs":false,"family":"Ankley","given":"Gerald T.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":903314,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blackwell, Brett R.","contributorId":173601,"corporation":false,"usgs":false,"family":"Blackwell","given":"Brett R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":903315,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mills, Marc A.","contributorId":141085,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":903316,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lenaker, Peter L. 0000-0002-9469-6285 plenaker@usgs.gov","orcid":"https://orcid.org/0000-0002-9469-6285","contributorId":5572,"corporation":false,"usgs":true,"family":"Lenaker","given":"Peter","email":"plenaker@usgs.gov","middleInitial":"L.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":903317,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nott, Michelle A. 0000-0003-3968-7586","orcid":"https://orcid.org/0000-0003-3968-7586","contributorId":221766,"corporation":false,"usgs":true,"family":"Nott","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":903318,"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
While previous resource conflicts have often been linked to fuel minerals such as oil, future resource conflict may revolve around nonfuel minerals that enable strategic emerging technologies. During a 2010 diplomatic dispute, China reportedly blocked exports of rare earth elements to Japan, thereby leveraging China’s near-monopoly to threaten Japanese manufacturers of advanced technologies including batteries and permanent magnets. Although this caused significant concern for manufacturers outside China, China’s control over other critical minerals has yet to be studied comprehensively. Besides rare earth elements, perhaps no mineral has received more attention for its supply risks than cobalt. Here Chinese control is estimated for each cobalt material at each stage of the cobalt supply chain from 2000 through 2022. The results show that from mining, to refining, consumption, recycling, stocks, and trade, China dominates the cobalt materials that feed lithium-ion battery cathode production. Specifically, the results show that in 2022 Chinese firms had control over 62% of cobalt mine materials primarily used for cobalt chemical refining, 95% control of refined commercial-grade cobalt chemicals, 92% control of battery-grade tricobalt tetroxide, 85% control of battery-grade cobalt sulfate, and 91% control of nickel–cobalt-manganese cathode precursor materials. China’s monopoly over cobalt battery materials may imply a serious supply risk to non-Chinese battery producing and consuming industries—especially given rising geopolitical tensions and the reemergence of critical mineral export restrictions including gallium for semiconductors, germanium for solar panels, graphite for lithium-ion batteries, and (again) rare earth elements.
","language":"English","publisher":"Springer Link","doi":"10.1007/s13563-024-00447-w","usgsCitation":"Gulley, A.L., 2024, The development of China’s monopoly over cobalt battery materials: Mineral Economics, v. 37, p. 619-631, https://doi.org/10.1007/s13563-024-00447-w.","productDescription":"13 p.","startPage":"619","endPage":"631","ipdsId":"IP-130175","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":439419,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13563-024-00447-w","text":"Publisher Index 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Andrew L. 0000-0003-4717-2080","orcid":"https://orcid.org/0000-0003-4717-2080","contributorId":203953,"corporation":false,"usgs":true,"family":"Gulley","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":906092,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70261481,"text":"70261481 - 2024 - Middle-late Holocene paleolimnological changes in central Lake Tanganyika: Integrated evidence from the Kavala Island Ridge (Tanzania)","interactions":[],"lastModifiedDate":"2024-12-11T16:12:29.148441","indexId":"70261481","displayToPublicDate":"2024-06-10T09:00:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3562,"text":"The Holocene","active":true,"publicationSubtype":{"id":10}},"title":"Middle-late Holocene paleolimnological changes in central Lake Tanganyika: Integrated evidence from the Kavala Island Ridge (Tanzania)","docAbstract":"Middle and Late Holocene sediments have not been extensively sampled in Lake Tanganyika, and much remains unknown about the response of the Rift Valley’s largest lake to major environmental shifts during the Holocene, including the termination of the African Humid Period (AHP). Here, we present an integrated study (sedimentology, mineralogy, and geochemistry) of a radiocarbon-dated sediment core from the Kavala Island Ridge (KIR) that reveals paleoenvironmental variability in Lake Tanganyika since the Middle Holocene with decadal to centennial resolution. Massive blue-gray sandy silts represent sediments deposited during the terminal AHP (~5880–4640 cal yr BP), with detrital particle size, carbon concentrations, light stable isotopes, and mineralogy suggesting an influx of river-borne soil organic matter and weathered clay minerals to the lake at that time. Enhanced by the AHP’s warm and wet conditions, chemical weathering and erosion of Lake Tanganyika’s watershed appears to have promoted considerable nutrient recharge to the lake system. Following a relatively gradual termination of the AHP over the period from ~4640 cal yr BP to ~3680 cal yr BP, laminated and organic carbon-rich sediments began accumulating on the KIR. δ15Nbulk, C/N, and hydrogen index data suggest high relative primary production from a mix of algae and cyanobacteria, most likely in response to nutrient availability in the water column under a cooler and seasonally dry climate from ~3680 to 1100 cal yr BP. Sediments deposited during the Common Era show considerable variability in magnetic susceptibility, total organic carbon content, carbon isotopes, and C/N, consistent with dynamic hydroclimate conditions that affected the depositional patterns, including substantial changes around the Medieval Climate Anomaly and Little Ice Age. Data from this study highlight the importance of sedimentary records to constrain boundary conditions in hydroclimate and nutrient flux that can inform long-term ecosystem response in Lake Tanganyika.
","language":"English","publisher":"Sage","doi":"10.1177/09596836241254475","usgsCitation":"Domingos-Luz, L., Soreghan, M.J., Rasbold, G., Ellis, G.S., Birdwell, J.E., Kimirei, I.A., Scholz, C., and McGlue, M., 2024, Middle-late Holocene paleolimnological changes in central Lake Tanganyika: Integrated evidence from the Kavala Island Ridge (Tanzania): The Holocene, v. 34, no. 9, p. 1167-1180, https://doi.org/10.1177/09596836241254475.","productDescription":"14 p.","startPage":"1167","endPage":"1180","ipdsId":"IP-158298","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":465011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Tanzania","otherGeospatial":"Kavala Island Ridge, Lake Tanganyika","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 29.043817847394536,\n -5.6155120583288465\n ],\n [\n 29.043817847394536,\n -6.203461467324189\n ],\n [\n 30.023780732233263,\n -6.203461467324189\n ],\n [\n 30.023780732233263,\n -5.6155120583288465\n ],\n [\n 29.043817847394536,\n -5.6155120583288465\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"34","issue":"9","noUsgsAuthors":false,"publicationDate":"2024-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Domingos-Luz, Leandro","contributorId":347061,"corporation":false,"usgs":false,"family":"Domingos-Luz","given":"Leandro","email":"","affiliations":[{"id":83051,"text":"Department of Earth and Environmental Sciences, University of Kentucky, Lexington KY, 40506, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":920731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soreghan, Michael J.","contributorId":347062,"corporation":false,"usgs":false,"family":"Soreghan","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":83052,"text":"School of Geosciences, University of Oklahoma, Norman, OK, 73019, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":920732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rasbold, Giliane G.","contributorId":347063,"corporation":false,"usgs":false,"family":"Rasbold","given":"Giliane G.","affiliations":[{"id":83051,"text":"Department of Earth and Environmental Sciences, University of Kentucky, Lexington KY, 40506, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":920733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellis, Geoffrey S. 0000-0003-4519-3320 gsellis@usgs.gov","orcid":"https://orcid.org/0000-0003-4519-3320","contributorId":1058,"corporation":false,"usgs":true,"family":"Ellis","given":"Geoffrey","email":"gsellis@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":920734,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":920735,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kimirei, Ishmael A.","contributorId":347064,"corporation":false,"usgs":false,"family":"Kimirei","given":"Ishmael","email":"","middleInitial":"A.","affiliations":[{"id":83053,"text":"Tanzania Fisheries Research Institute, Dar-es-Salaam, Tanzania","active":true,"usgs":false}],"preferred":false,"id":920736,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Scholz, Christopher A.","contributorId":149267,"corporation":false,"usgs":false,"family":"Scholz","given":"Christopher A.","affiliations":[{"id":17692,"text":"Syracuse University, Syracuse NY","active":true,"usgs":false}],"preferred":false,"id":920737,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McGlue, Michael M.","contributorId":225229,"corporation":false,"usgs":false,"family":"McGlue","given":"Michael M.","affiliations":[{"id":41081,"text":"Department of Geosciences, The University of Arizona, Tucson AZ","active":true,"usgs":false}],"preferred":false,"id":920738,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70257513,"text":"70257513 - 2024 - Human activity drives establishment, but not invasion, of non-native plants on islands","interactions":[],"lastModifiedDate":"2024-09-06T14:50:40.411326","indexId":"70257513","displayToPublicDate":"2024-06-10T07:40:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Human activity drives establishment, but not invasion, of non-native plants on islands","docAbstract":"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":70257875,"text":"70257875 - 2024 - Evolutionary ecology of masting: Mechanisms, models, and climate change","interactions":[],"lastModifiedDate":"2024-09-11T16:27:42.339891","indexId":"70257875","displayToPublicDate":"2024-06-10T07:10:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Evolutionary ecology of masting: Mechanisms, models, and climate change","docAbstract":"In birds, mercury embryotoxicity can occur through the transfer of mercury from the female to her eggs. Maternal transfer of mercury can vary by egg position in the laying sequence, with first-laid eggs often exhibiting greater mercury concentrations than subsequently laid eggs. We studied egg mercury concentration, mercury burden (total amount of mercury in the egg), and egg morphometrics by egg position in the laying sequence for two songbirds: tree swallows (Tachycineta bicolor) and house wrens (Troglodytes aedon). Egg mercury concentration in the second egg laid was 14% lower for tree swallows and 6% lower for house wrens in comparison with the first egg laid. These results indicate that in both species, after an initial relatively high transfer of mercury into the first egg laid, a smaller amount of mercury was transferred to the second egg laid. This lower mercury concentration persisted among all subsequently laid eggs (eggs three to eight) in tree swallows (all were 14%–16% lower than egg 1), but mercury concentrations in subsequently laid house wren eggs (eggs three to seven) returned to levels observed in the first egg laid (all were 1% lower to 3% greater than egg 1). Egg size increased with position in the laying sequence in both species; the predicted volume of egg 7 was 5% and 6% greater than that of egg 1 in tree swallows and house wrens, respectively. This change was caused by a significant increase in egg width, but not egg length, with position in the laying sequence. The percentage of decline in mercury concentration with position in the laying sequence was considerably lower in tree swallows and house wrens compared with other bird taxonomic groups, suggesting that there are key differences in the maternal transfer of mercury into songbird eggs compared with other birds. Finally, we performed simulations to evaluate how within-clutch variation in egg mercury concentrations affected estimates of mean mercury concentrations in each clutch and the overall sampled population, which has direct implications for sampling designs. Environ Toxicol Chem 2024;00:1–11. Published 2024. This article is a U.S. Government work and is in the public domain in the USA.
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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