Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Hawaiian, Mariana, and American Samoan Islands as a result of climate change and sea-level rise. We followed a hybrid (dynamical and statistical) downscaling approach to map flooding due to waves and storm surge at 10-square meter resolution along all 1,870 kilometers of these islands’ coastlines for annual (1-year), 20-year, and 100-year return-interval storm events and +0.00 meter (m), +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios. We quantified the coastal flood depths and extents using the latest climate forcing from Intergovernmental Panel for Climate Change’s Sixth Assessment Report Coupled Model Intercomparison Project. The data generated using these methods provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when climate change and sea-level rise increase coastal storm-induced flooding to help identify areas where management and (or) restoration could potentially help reduce the risk to, and increase the resiliency of, the coastal communities in the populated Hawaiian, Mariana, and American Samoan Islands.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1184","usgsCitation":"Storlazzi, C.D., Reguero, B.G., Gaido L., C., Alkins, K.C., Lowrie, C., Nederhoff, K.M., Erikson, L.H., O’Neill, A.C., and Beck, M.W., 2024, Forecasting storm-induced coastal flooding for 21st century sea-level rise scenarios in the Hawaiian, Mariana, and American Samoan Islands: U.S. Geological Survey Data Report 1184, 21 p., https://doi.org/10.3133/dr1184.","productDescription":"Report: iv, 21 p.; Data Release","numberOfPages":"21","onlineOnly":"Y","ipdsId":"IP-151075","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499103,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116008.htm","text":"Guam"},{"id":499102,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116007.htm","text":"Maui, Hawaii"},{"id":425198,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1184/dr1184.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":425197,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1184/covrthb.jpg"},{"id":425199,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1184/dr1184.xml"},{"id":425200,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1184/images"},{"id":425201,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1184/full"},{"id":425196,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RIQ7S7","text":"USGS Data Release","description":"Alkins, K.C., Gaido L., C., Reguero, B.G, and Storlazzi, C.D., 2024, Projected coastal flooding extents and depths for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Hawaiian, Mariana, and American Samoan Islands: U.S. Geological Survey data release, https://doi.org/10.5066/P9RIQ7S7.","linkHelpText":"Projected coastal flooding extents and depths for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Hawaiian, Mariana, and American Samoan Islands"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -160.95732441583095,\n 22.88608719647806\n ],\n [\n -160.95732441583095,\n 18.613495973781937\n ],\n [\n -153.97001972833093,\n 18.613495973781937\n ],\n [\n -153.97001972833093,\n 22.88608719647806\n ],\n [\n -160.95732441583095,\n 22.88608719647806\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
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Prioritizing restoration opportunities effectively across entire riverscape networks (i.e., riverine landscape including floodplain and stream channel networks) can be difficult when relying on in-channel, reach-scale monitoring data, or watershed-level summaries that fail to capture riverscape heterogeneity and the information necessary to implement restoration actions. Leveraging remote sensing and geospatial tools to develop spatially continuous information across nested hierarchical scales may support increased understanding of local riverscape reaches in their broader network context. Using riparian (vegetation) and geomorphic (elevation) indicators to assess status of riverscape health, along with a measure of restoration capacity (valley bottom area), could be adapted to fit specific management goals related to riverscape restoration. Frameworks using remotely sensed vegetation and elevation data to prioritize restoration continuously across riverscapes at restoration-relevant, reach-scales may uphold the ecosystem services provided by riverscapes. By incorporating local knowledge and identifying caveats for using these datasets, continuous inferences can be applied at network scales (watershed to regional extent and reach-scale resolution) to prioritize restoration over a wide variety of ecoregions.
","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1716","usgsCitation":"Glassic, H.C., McGwire, K.C., Macfarlane, W., Rasmussen, C., Bouwes, N., Wheaton, J.M., and Al-Chokhachy, R., 2024, From pixels to riverscapes: How remote sensing and geospatial tools can prioritize riverscape restoration at multiple scales: WIREs Water, v. 11, no. 3, e1716, 22 p., https://doi.org/10.1002/wat2.1716.","productDescription":"e1716, 22 p.","ipdsId":"IP-154971","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":440545,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wat2.1716","text":"Publisher Index Page"},{"id":433404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Reese River, Upper Humboldt River, West Walker River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.28783058394662,\n 38.09843600904033\n ],\n [\n -114.17949392211462,\n 40.01850103667016\n ],\n [\n -114.21927949998788,\n 41.75225521374173\n ],\n [\n -117.26200493565987,\n 41.87323893635414\n ],\n [\n -120.03969790583245,\n 38.533308782806046\n ],\n [\n -119.28783058394662,\n 38.09843600904033\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glassic, Hayley Corrine 0000-0001-6839-1026","orcid":"https://orcid.org/0000-0001-6839-1026","contributorId":305858,"corporation":false,"usgs":true,"family":"Glassic","given":"Hayley","email":"","middleInitial":"Corrine","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":911984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGwire, Kenneth C.","contributorId":140699,"corporation":false,"usgs":false,"family":"McGwire","given":"Kenneth","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":911985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macfarlane, William W.","contributorId":337429,"corporation":false,"usgs":false,"family":"Macfarlane","given":"William W.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":911986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rasmussen, Cashe","contributorId":305859,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Cashe","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":911987,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bouwes, Nicolaas","contributorId":305860,"corporation":false,"usgs":false,"family":"Bouwes","given":"Nicolaas","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":911988,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wheaton, Joseph M.","contributorId":343789,"corporation":false,"usgs":false,"family":"Wheaton","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":911989,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":222450,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":911990,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70251277,"text":"70251277 - 2024 - Twenty years of explosive-effusive activity at El Reventador volcano (Ecuador) recorded in its geomorphology","interactions":[],"lastModifiedDate":"2024-02-08T18:56:27.243981","indexId":"70251277","displayToPublicDate":"2024-02-01T07:04:59","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Twenty years of explosive-effusive activity at El Reventador volcano (Ecuador) recorded in its geomorphology","docAbstract":"Shifts in activity at long-active, open-vent volcanoes are difficult to forecast because precursory signals are enigmatic and can be lost in and amongst daily activity. Here, we propose that crater and vent morphologies, along with summit height, can help us bring some insights into future activity at one of Ecuador’s most active volcanoes El Reventador. On 3 November 2002, El Reventador volcano experienced the largest eruption in Ecuador in the last 140 years and has been continuously active ever since with transitions between and coexistence of explosive and effusive activity, characterized by Strombolian and Vulcanian behavior. Based on the analysis of a large dataset of thermal and visual images, we determined that in the last 20 years of activity, the volcano faced three destructive events: A. Destruction of the upper part of the summit leaving a north-south breached crater (3 November 2002), B. NE border crater collapse (2017), and C. NW flank collapse (2018), with two periods of reconstruction of the edifice: Period 1. Refill of the crater (2002-early 2018) and Period 2. Refill of the 2018 scar (April 2018–December 2022). Through photogrammetric analysis of visual and thermal images acquired in 11 overflights of the volcano, we created a time-series of digital elevation models (DEMs) to determine the maximum height of the volcano at each date, quantify the volume changes between successive dates, and characterize the morphological changes in the summit region. We estimate that approximately 34.1x106 m3 of volcanic material was removed from the volcano due to destructive events, whereas 64.1x106 m3 was added by constructive processes. The pre-2002 summit height was 3,560 m and due to the 2002 eruption it decreased to 3,527 m; it regained its previous height between 2014 and 2015 and the summit crater was completely filled by early April 2018. Event A resulted from an intrusion of magma that erupted violently; we proposed that Events B and C could be a result of an intrusion as well but may also be due to a lack of stability of the volcano summit which occurs when it reaches its maximum height of approximately 3,590 and 3,600 m.
Agriculture consumes the largest share of freshwater globally; therefore, distinguishing between rainfed and irrigated croplands is essential for agricultural water management and food security. In this study, a framework incorporating the Budyko model was used to differentiate between rainfed and irrigated cropland areas in Africa for eight remote sensing landcover products and a high-confidence cropland map (HCCM). The HCCM was generated for calibration and validation of the crop partitioning framework as an alternative to individual cropland masks which exhibit high disagreement. The accuracy of the framework in partitioning the HCCM was evaluated using an independent validation dataset, yielding an overall accuracy rate of 73 %. The findings of this study indicate that out of the total area covered by the HCCM (2.36 million km2), about 461,000 km2 (19 %) is irrigated cropland. The partitioning framework was applied on eight landcover products, and the extent of irrigated areas varied between 19 % and 30 % of the total cropland area. The framework demonstrated high precision and specificity scores, indicating its effectiveness in correctly identifying irrigated areas while minimizing the misclassification of rainfed areas as irrigated. This study provides an enhanced understanding of rainfed and irrigation patterns across Africa, supporting efforts towards achieving sustainable and resilient agricultural systems. Consequently, the approach outlined expands on the suite of remote sensing landcover products that can be used for agricultural water studies in Africa by enabling the extraction of irrigated and rainfed cropland data from landcover products that do not have disaggregated cropland classes.
The Mississippi Alluvial Plain (MAP) in the United States (US).
Understanding local-scale groundwater use, a critical component of the water budget, is necessary for implementing sustainable water management practices. The MAP is one of the most productive agricultural regions in the US and extracts more than 11 km3/year for irrigation activities. Consequently, groundwater-level declines in the MAP region pose a substantial challenge to water sustainability, and hence, we need reliable groundwater pumping monitoring solutions to manage this resource appropriately.
We incorporate remote sensing datasets and machine learning to improve an existing lookup table-based model of groundwater use previously developed by the U.S. Geological Survey (USGS). Here, we employ Distributed Random Forests, an ensemble machine learning algorithm to predict annual and monthly groundwater use (2014–2020) throughout this region at 1-km resolution, using pumping data from existing flowmeters in the Mississippi Delta. Our model compares favorably with the existing USGS model, with higher R2 (0.51 compared to 0.42 in the previous model), and lower root mean square error (RMSE) and mean absolute error (MAE)— 0.14 m and 0.09 m, respectively in our model, compared to 0.15 m and 0.1 m in the previous model. Therefore, this work advances our ability to predict groundwater use in regions with scarce or limited in-situ groundwater withdrawal data availability.
Light detection and ranging (lidar) has emerged as a valuable tool for examining the fine-scale characteristics of vegetation. However, lidar is rarely used to examine coastal wetland vegetation or the habitat selection of small mammals. Extensive anthropogenic modification has threatened the endemic species in the estuarine wetlands of the California coast, such as the endangered salt marsh harvest mouse (Reithrodontomys raviventris; SMHM). A better understanding of SMHM habitat selection could help managers better protect this species. We assessed the ability of airborne topographic lidar imagery in measuring the vegetation structure of SMHM habitats in a coastal wetland with a narrow range of vegetation heights. We also aimed to better understand the role of vegetation structure in habitat selection at different spatial scales. Habitat selection was modeled from data compiled from 15 small mammal trapping grids collected in the highly urbanized San Francisco Estuary in California, USA. Analyses were conducted at three spatial scales: microhabitat (25 m2), mesohabitat (2025 m2), and macrohabitat (~10,000 m2). A suite of structural covariates was derived from raw lidar data to examine vegetation complexity. We found that adding structural covariates to conventional habitat selection variables significantly improved our models. At the microhabitat scale in managed wetlands, SMHM preferred areas with denser and shorter vegetation and selected for proximity to levees and taller vegetation in tidal wetlands. At the mesohabitat scale, SMHM were associated with a lower percentage of bare ground and with pickleweed (Salicornia pacifica) presence. All covariates were insignificant at the macrohabitat scale. Our results suggest that SMHM preferentially selected microhabitats with access to tidal refugia and mesohabitats with consistent food sources. Our findings showed that lidar can contribute to improving our understanding of habitat selection of wildlife in coastal wetlands and help to guide future conservation of an endangered species.
Landsat orthorectified products use Ground Control Points (GCPs) and Digital Elevation Models (DEM) to improve the geolocation accuracy and temporal consistency, and to account for the relief displacements due to the sensor-target geometry. In Collection-2, to improve the geometric harmonization between Landsat and Sentinel-2 (S2) orthorectified products, the Landsat GCP's absolute and relative accuracies were improved using the S2 Global Reference Image (GRI) dataset through a continent-level bundle adjustment method. The GRI is a highly accurate global image dataset that was developed by the European Space Agency (ESA) to improve the S2 multi-temporal geolocation accuracy. Since late August 2021, ESA has been using the GRI dataset in the geometric refinement process to generate S2 terrain-corrected (L1C) products. This paper presents the co-registration accuracy between the Landsat-8 (L8) Collection-2 terrain-corrected products and the S2 L1C products that were processed with and without the use of the GRI dataset. The image-to-image registration (I2I) analysis performed between the L8 and S2 data products over a set of globally distributed tiles shows a significant improvement in their co-registration accuracy when GRI is used in the S2 L1C product generation. The co-registration error is estimated to be <6 m circular error at 90% probability (CE90) when GRI is used, and >12 m CE90 when GRI is not used in the S2 product generation process. A similar I2I analysis was conducted between S2 L1C products, L8 L1TP products, and L8 and Landsat 9 (L9) L1TP products. The analysis shows that the S2 L1C products are co-registered with each other temporally to better than 5.1 m CE90 when GRI is used. The L8 L1TP products and L8 versus L9 L1TP products are both co-registered temporally to better than 3 m CE90.
Geographical distributions of waterfowl exhibit annual variation in response to spatiotemporal variation in weather conditions, habitat availability, and other factors. Continuing changes in climate and land use could lead to persistent shifts of waterfowl distributions, potentially causing a mismatch with habitat conservation planning, wetland restoration efforts, and harvest management decisions informed by historical distributions. We used band recoveries and harvest records (i.e., hunter-harvested wings) from the United States Fish and Wildlife Service Waterfowl Parts Collection Survey as indices of duck distribution in autumn and winter, and quantified intra-annual, interannual, and interspecific variation in their geographic distributions across 6 decades (1960–2019) for 15 duck species in the Central and Mississippi flyways in North America. Specifically, we tested for annual and decadal shifts in mean latitude and longitude of recoveries for each month (Oct–Jan) by species and taxonomic guild (i.e., dabbling, diving ducks). Overall, species varied in the extent, timing, and sometimes direction, of distributional change in recoveries. From 1960–2019, mean recovery locations for dabbling ducks shifted south 105–296 km in October and 27 km in November (wings only), whereas mean latitudes shifted north 144–234 km in December and 186–301 km in January. Mean recovery locations for diving ducks shifted north 162 km in October (wings only), 84–173 km in December, and 66–120 km in January, but shifted 99–512 km south in November. Shifts in longitude were less consistent between guilds and data types. Finally, distributional change rarely accelerated during recent decades, except for southward shifts of band recoveries of diving ducks in November and northward shifts of band and wing recoveries of dabbling ducks in January. Although anecdotal accounts of large-scale northward shifts in duck distributions are prolific in the land management and hunting communities, our data demonstrate more subtle shifts that vary considerably by species and month. Observed changes in recovery distributions could necessitate changes in timing of habitat management practices throughout the Central and Mississippi flyways and may result in fewer hunting and recreational opportunities for some species in southern states. Quantifying patterns of historical change is a necessary first step to understanding temporal and interspecific variation in waterfowl distributions, which will help with landscape-scale conservation and management efforts in the future and enable effective communication to core constituencies regarding ongoing changes and their implications for recreational engagement.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.22521","usgsCitation":"Verheijen, B., Webb, E.B., Brasher, M., and Hagy, H.M., 2024, Spatiotemporal dynamics of duck harvest distributions in the Central and Mississippi flyways, 1960–2019: The Journal of Wildlife Management, v. 88, no. 2, e22521, 18 p., https://doi.org/10.1002/jwmg.22521.","productDescription":"e22521, 18 p.","ipdsId":"IP-151486","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432886,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.31640625,\n 28.92163128242129\n ],\n [\n -85.4296875,\n 28.92163128242129\n ],\n [\n -85.4296875,\n 51.069016659603896\n ],\n [\n -99.31640625,\n 51.069016659603896\n ],\n [\n -99.31640625,\n 28.92163128242129\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Verheijen, Bram H. F.","contributorId":274514,"corporation":false,"usgs":false,"family":"Verheijen","given":"Bram H. F.","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":907872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907873,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brasher, Michael G.","contributorId":338627,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael G.","affiliations":[{"id":81180,"text":"Ducks Unlimited, Inc","active":true,"usgs":false}],"preferred":false,"id":907874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hagy, Heath M.","contributorId":172326,"corporation":false,"usgs":false,"family":"Hagy","given":"Heath","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":907875,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70256492,"text":"70256492 - 2024 - Both Landsat- and LiDAR-derived measures predict forest bee response to large-scale wildfire","interactions":[],"lastModifiedDate":"2024-08-19T17:28:46.841111","indexId":"70256492","displayToPublicDate":"2024-02-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Both Landsat- and LiDAR-derived measures predict forest bee response to large-scale wildfire","docAbstract":"Large-scale disturbances such as wildfire can have profound impacts on the composition, structure, and functioning of ecosystems. Bees are critical pollinators in natural settings and often respond positively to wildfires, particularly in forests where wildfire leads to more open conditions and increased floral resources. The use of Light Detection and Ranging (LiDAR) provides opportunities for quantifying habitat features across large spatial scales and is increasingly available to scientists and land managers for post-fire habitat assessment. We evaluated the extent to which LiDAR-derived forest structure measurements can predict forest bee communities after a large, mixed-severity fire. We hypothesized that LiDAR measurements linked to post-fire forest structure would improve our ability to predict bee abundance and species richness when compared to satellite-based maps of burn severity. To test this hypothesis, we sampled wild bee communities within the Douglas Fire Complex in southwestern Oregon, USA. We then used LiDAR and Landsat data to quantify forest structure and burn severity, respectively, across bee sampling locations. We found that the LiDAR forest structure model was the best predictor of abundance, whereas the Landsat burn severity model had better predictive ability for species richness. Furthermore, the Landsat burn severity model was better at predicting the presence and species richness of bumble bees (Bombus spp.), an ecologically distinct and economically important group within the Pacific Northwest. We posit that the divergent responses of the two modeling approaches are due to distinct responses by bee taxa to variation in forest structure as mediated by wildfire, with bumble bees in particular depending on closed-canopy forest for some portions of their life cycle. Our study demonstrates that LiDAR data can provide information regarding the drivers of bee abundance in post-wildfire conifer forest, and that both remote sensing approaches are useful for predicting components of wild bee diversity after large-scale wildfire.
","language":"English","doi":"10.1002/rse2.354","usgsCitation":"Galbraith, S.M., Valente, J., Dunn, C.J., and Rivers, J.W., 2024, Both Landsat- and LiDAR-derived measures predict forest bee response to large-scale wildfire: Remote Sensing in Ecology and Conservation, v. 10, no. 1, p. 24-38, https://doi.org/10.1002/rse2.354.","productDescription":"15 p.","startPage":"24","endPage":"38","ipdsId":"IP-144537","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":440572,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.354","text":"Publisher Index Page"},{"id":432888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Douglas Fire Complex, southwestern Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.576158064366,\n 43.53770092737449\n ],\n [\n -123.576158064366,\n 42.89081714418663\n ],\n [\n -123.04040779515724,\n 42.89081714418663\n ],\n [\n -123.04040779515724,\n 43.53770092737449\n ],\n [\n -123.576158064366,\n 43.53770092737449\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Galbraith, Sara M.","contributorId":340887,"corporation":false,"usgs":false,"family":"Galbraith","given":"Sara","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":907638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Valente, Jonathon Joseph 0000-0002-6519-3523","orcid":"https://orcid.org/0000-0002-6519-3523","contributorId":340615,"corporation":false,"usgs":true,"family":"Valente","given":"Jonathon Joseph","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":910913,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Christopher J.","contributorId":340888,"corporation":false,"usgs":false,"family":"Dunn","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":907640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rivers, James W.","contributorId":23072,"corporation":false,"usgs":false,"family":"Rivers","given":"James","email":"","middleInitial":"W.","affiliations":[{"id":7005,"text":"Department of Forest Ecosystems and Society, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":907641,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70251343,"text":"70251343 - 2024 - Top-predator recovery abates geomorphic decline of a coastal ecosystem","interactions":[],"lastModifiedDate":"2024-02-07T01:15:12.912408","indexId":"70251343","displayToPublicDate":"2024-01-31T19:12:53","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Top-predator recovery abates geomorphic decline of a coastal ecosystem","docAbstract":"The recovery of top predators is thought to have cascading effects on vegetated ecosystems and their geomorphology1,2, but the evidence for this remains correlational and intensely debated3,4. Here we combine observational and experimental data to reveal that recolonization of sea otters in a US estuary generates a trophic cascade that facilitates coastal wetland plant biomass and suppresses the erosion of marsh edges—a process that otherwise leads to the severe loss of habitats and ecosystem services5,6. Monitoring of the Elkhorn Slough estuary over several decades suggested top-down control in the system, because the erosion of salt marsh edges has generally slowed with increasing sea otter abundance, despite the consistently increasing physical stress in the system (that is, nutrient loading, sea-level rise and tidal scour7,8,9). Predator-exclusion experiments in five marsh creeks revealed that sea otters suppress the abundance of burrowing crabs, a top-down effect that cascades to both increase marsh edge strength and reduce marsh erosion. Multi-creek surveys comparing marsh creeks pre- and post-sea otter colonization confirmed the presence of an interaction between the keystone sea otter, burrowing crabs and marsh creeks, demonstrating the spatial generality of predator control of ecosystem edge processes: densities of burrowing crabs and edge erosion have declined markedly in creeks that have high levels of sea otter recolonization. These results show that trophic downgrading could be a strong but underappreciated contributor to the loss of coastal wetlands, and suggest that restoring top predators can help to re-establish geomorphic stability.
Forest thinning on public lands in the Pacific Northwest USA is an important tool for restoring diversity in forest stands with a legacy of simplified structure from decades of intensive management for timber production. A primary application of thinning in young (< 50-year-old) stands is to accelerate forest development to mitigate loss of late-seral habitat to decades of logging. However, thinning may have short-term negative effects for some species associated with mature forest that are expected to benefit from the practice over the long term. An increased risk of nest predation is a primary concern to managers charged with stewardship of habitat for the federally threatened Marbled Murrelet (Brachyramphus marmoratus), a species that nests in older forests. Predation by corvids is the greatest cause of nest failure for the Marbled Murrelet, and corvids are known to respond positively to forest disturbance, but quantitative information is lacking on the potential impacts of thinning on risk of nest predation. We investigated the response of two common corvid nest predators, Steller’s Jay (Cyanocitta stelleri) and Canada Jay (Perisoreus canadensis), to variation in thinning intensity in young forest (< 50 years old) using data from a long-term silviculture experiment. We used a Before-After-Control-Impact (BACI) design, linear mixed modeling, and occupancy modeling to quantify differences in corvid observation rates among varying levels of thinning intensity, and to assess changes in jay response over more than a decade following thinning. We found an increase in observation rates of both species in the heavily thinned treatment during the first 5 to 7 years following thinning, and some evidence of a short-term increase in Steller’s Jay activity in the thinning-with-gaps treatment. Neither jay species responded to the least intensive thinning treatment, which reduced average canopy cover by < 30%. By approximately a decade after thinning, observation rates of jays did not differ between unthinned controls and any of the thinning treatments. Incorporating our quantitative information into landscape-level planning can help managers balance short- and long-term conservation goals.
","language":"English","publisher":"Avian Conservation and Ecology","doi":"10.5751/ACE-02578-190103","usgsCitation":"Hagar, J., Owen, T.K., Stevens, T.K., and Waianuhea, L.K., 2024, Response of corvid nest predators to thinning: implications for balancing short- and long-term goals for restoration of forest habitat: Avian Conservation and Ecology, v. 19, no. 1, 3, 11 p., https://doi.org/10.5751/ACE-02578-190103.","productDescription":"3, 11 p.","ipdsId":"IP-110816","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":440576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02578-190103","text":"Publisher Index Page"},{"id":425446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.31669804329832,\n 43.72071322185553\n ],\n [\n -122.22828499277165,\n 43.72071322185553\n ],\n [\n -122.22828499277165,\n 46.34467865412955\n ],\n [\n -124.31669804329832,\n 46.34467865412955\n ],\n [\n -124.31669804329832,\n 43.72071322185553\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hagar, Joan 0000-0002-3044-6607 joan_hagar@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-6607","contributorId":3369,"corporation":false,"usgs":true,"family":"Hagar","given":"Joan","email":"joan_hagar@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":894180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Owen, Theodore K","contributorId":333872,"corporation":false,"usgs":false,"family":"Owen","given":"Theodore","email":"","middleInitial":"K","affiliations":[{"id":38051,"text":"Western EcoSystems Technology, Inc.","active":true,"usgs":false}],"preferred":false,"id":894181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stevens, Thomas K.","contributorId":333873,"corporation":false,"usgs":false,"family":"Stevens","given":"Thomas","email":"","middleInitial":"K.","affiliations":[{"id":38051,"text":"Western EcoSystems Technology, Inc.","active":true,"usgs":false}],"preferred":false,"id":894182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waianuhea, Lorraine K 0000-0001-9697-6857","orcid":"https://orcid.org/0000-0001-9697-6857","contributorId":333874,"corporation":false,"usgs":false,"family":"Waianuhea","given":"Lorraine","email":"","middleInitial":"K","affiliations":[{"id":79996,"text":"Pacific Biosciences Research Center, University of Hawai’i at Mānoa","active":true,"usgs":false}],"preferred":false,"id":894183,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70251262,"text":"70251262 - 2024 - The impact of future changes in climate on breeding waterfowl pairs in the US Prairie Pothole Region","interactions":[],"lastModifiedDate":"2026-03-23T16:01:03.814623","indexId":"70251262","displayToPublicDate":"2024-01-31T10:51:02","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"title":"The impact of future changes in climate on breeding waterfowl pairs in the US Prairie Pothole Region","docAbstract":"Millions of small (< 10 ha) waterbodies embedded in grassland and agroecosystems in midcontinental North America provide breeding habitat to an estimated 50–80% of North America’s migratory ducks. Tens of millions of dollars are invested annually to conserve and enhance upland and wetland habitats for breeding ducks by prioritizing locations predicted to have high densities of breeding pairs under average precipitation conditions. An implicit assumption of this approach is that the distribution of breeding habitat remains relatively static. Climate change is an identified risk to this strategy. To assess this assumption and plan for potential forthcoming conditions, we estimated changes in potential breeding duck pairs under different climate scenarios by combining results of 1) a mechanistic hydrology model that simulates ecosystem processes for a subset of wetlands distributed across the U.S. Prairie Pothole Region (USPPR); 2) four downscaled climate model projections at mid- and late-century time horizons; and 3) U.S. Fish and Wildlife Service multi-decadal datasets and predictive breeding waterfowl pair statistical models. We conducted virtual and in-person informational sessions with partners to inform them on the best practices of using downscaled global circulation models and approaches for climate scenario planning. This close coordination led to a joint presentation at a monthly North Central Climate Adaptation Science Center seminar. We are also co-developing simulated wetland- waterfowl responses under different climate futures for wetlands. Information from these robust predictions of waterfowl habitat and settling patterns in this region provides land-management agencies insights in prioritizing current conservation actions given uncertainty. In addition, understanding how many breeding pairs the USPPR might support in coming decades will likely influence overall breeding population sizes and sustainable harvest objectives across North America.
","language":"English","publisher":"North Central Climate Adaptation Science Center","usgsCitation":"McKenna, O.P., and Rangwala, I., 2024, The impact of future changes in climate on breeding waterfowl pairs in the US Prairie Pothole Region: Final Report, 12 p.","productDescription":"12 p.","ipdsId":"IP-160169","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":501397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501396,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f83509de4b0e84f60868124/65c3d314d34ef4b119cae715"}],"country":"United States","state":"Iowa, Minnesota, Nebraska, North Dakota, South Dakota","otherGeospatial":"Prairie Pothole region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.05393441199925,\n 48.93957527305318\n ],\n [\n -108.27686560641123,\n 49.13252538326782\n ],\n [\n -108.40976144212098,\n 47.91192273687099\n ],\n [\n -106.07828064784712,\n 47.88578029277039\n ],\n [\n -101.59819304168207,\n 47.10144151067459\n ],\n [\n -100.41457783182686,\n 42.307798494527646\n ],\n [\n -96.89275640038099,\n 41.01374950027804\n ],\n [\n -96.60513562002711,\n 43.75532782507912\n ],\n [\n -94.98321580753591,\n 41.5817220442664\n ],\n [\n -94.20767561860225,\n 41.328376780271384\n ],\n [\n -93.63954575827131,\n 42.51490897209834\n ],\n [\n -93.78977025276507,\n 43.36437770770755\n ],\n [\n -94.24637551611141,\n 47.33263848178828\n ],\n [\n -95.05393441199925,\n 48.93957527305318\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, Owen P. 0000-0002-5937-9436 omckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-9436","contributorId":198598,"corporation":false,"usgs":true,"family":"McKenna","given":"Owen","email":"omckenna@usgs.gov","middleInitial":"P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":893736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rangwala, Imtiaz 0000-0002-4313-9374","orcid":"https://orcid.org/0000-0002-4313-9374","contributorId":148973,"corporation":false,"usgs":false,"family":"Rangwala","given":"Imtiaz","email":"","affiliations":[{"id":34534,"text":"Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado","active":true,"usgs":false}],"preferred":true,"id":957215,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70251310,"text":"70251310 - 2024 - Predicting the spatial distribution of wintering golden eagles to inform full annual cycle conservation in western North America","interactions":[],"lastModifiedDate":"2024-02-03T15:25:37.454332","indexId":"70251310","displayToPublicDate":"2024-01-31T09:21:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the spatial distribution of wintering golden eagles to inform full annual cycle conservation in western North America","docAbstract":"Wildlife conservation strategies focused on one season or population segment may fail to adequately protect populations, especially when a species’ habitat preferences vary among seasons, age-classes, geographic regions, or other factors. Conservation of golden eagles (Aquila chrysaetos) is an example of such a complex scenario, in which the distribution, habitat use, and migratory strategies of this species of conservation concern vary by age-class, reproductive status, region, and season. Nonetheless, research aimed at mapping priority use areas to inform management of golden eagles in western North America has typically focused on territory-holding adults during the breeding period, largely to the exclusion of other seasons and life-history groups. To support population-wide conservation planning across the full annual cycle for golden eagles, we developed a distribution model for individuals in a season not typically evaluated–winter–and in an area of the interior western U.S. that is a high priority for conservation of the species. We used a large GPS-telemetry dataset and library of environmental variables to develop a machine-learning model to predict spatial variation in the relative intensity of use by golden eagles during winter in Wyoming, USA, and surrounding ecoregions. Based on a rigorous series of evaluations including cross-validation, withheld and independent data, our winter-season model accurately predicted spatial variation in intensity of use by multiple age- and life-history groups of eagles not associated with nesting territories (i.e., all age classes of long-distance migrants, and resident non-adults and adult “floaters”, and movements of adult territory holders and their offspring outside their breeding territories). Important predictors in the model were wind and uplift (40.2% contribution), vegetation and landcover (27.9%), topography (14%), climate and weather (9.4%), and ecoregion (8.7%). Predicted areas of high-use winter habitat had relatively low spatial overlap with nesting habitat, suggesting a conservation strategy targeting high-use areas for one season would capture as much as half and as little as one quarter of high-use areas for the other season. The majority of predicted high-use habitat (top 10% quantile) occurred on private lands (55%); lands managed by states and the Bureau of Land Management (BLM) had a lower amount (33%), but higher concentration of high-use habitat than expected for their area (1.5–1.6x). These results will enable those involved in conservation and management of golden eagles in our study region to incorporate spatial prioritization of wintering habitat into their existing regulatory processes, land-use planning tasks, and conservation actions.
Each mineral commodity chapter of the 2024 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production, reserves, and resources. The MCS is the earliest comprehensive source of 2023 mineral production data for the world. More than 90 individual minerals and materials are covered by 2-page synopses.
Abbreviations and units of measure and definitions of selected terms used in the report are in Appendix A and Appendix B, respectively. Reserves and resources information is in Appendix C, which includes “Part A—Resource and Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is in Appendix D.
The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2024 are welcomed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/mcs2024","isbn":"978-1-4113-4544-7","usgsCitation":"U.S. Geological Survey, 2024, Mineral commodity summaries 2024: U.S. Geological Survey, 212 p., https://doi.org/10.3133/mcs2024.","productDescription":"Report: 212 p.; Data Release","numberOfPages":"212","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-160630","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":425029,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://tableau.usgs.gov/views/MCSDashboardWorkbook_2024-01-30/MCSDashboard?%3Aembed=y&%3AisGuestRedirectFromVizportal=y#7","text":"Data visualization"},{"id":424958,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/centers/national-minerals-information-center/commodity-statistics-and-information","text":"Commodity Statistics and Information"},{"id":424956,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/periodicals/mcs2024/mcs2024.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"MCS 2024"},{"id":424955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/periodicals/mcs2024/coverthb.jpg"},{"id":424959,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P144BA54","text":"USGS data release","linkHelpText":"U.S. Geological Survey Mineral Commodity Summaries 2024 Data Release"},{"id":424957,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/centers/national-minerals-information-center/mineral-commodity-summaries","text":"Mineral Commodity Summaries Prior to 2024"},{"id":499130,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115979.htm","linkFileType":{"id":5,"text":"html"}}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Species with extensive geographical ranges pose special challenges to assessing drivers of wildlife disease, necessitating collaborative and large-scale analyses. The imperilled foothill yellow-legged frog (Rana boylii) inhabits a wide geographical range and variable conditions in rivers of California and Oregon (USA), and is considered threatened by the pathogen Batrachochytrium dendrobatidis (Bd). To assess drivers of Bd infections over time and space, we compiled over 2000 datapoints from R. boylii museum specimens (collected 1897–2005) and field samples (2005–2021) spanning 9° of latitude. We observed a south-to-north spread of Bd detections beginning in the 1940s and increase in prevalence from the 1940s to 1970s, coinciding with extirpation from southern latitudes. We detected eight high-prevalence geographical clusters through time that span the species' geographical range. Field-sampled male R. boylii exhibited the highest prevalence, and juveniles sampled in autumn exhibited the highest loads. Bd infection risk was highest in lower elevation rain-dominated watersheds, and with cool temperatures and low stream-flow conditions at the end of the dry season. Through a holistic assessment of relationships between infection risk, geographical context and time, we identify the locations and time periods where Bd mitigation and monitoring will be critical for conservation of this imperilled species.
Avian eggshell thickness is an important life history metric in birds and has broad applications across disciplines ranging from animal behavior to toxicology. Empirical eggshell thickness values for songbirds (Order Passeriformes) are under-represented in the literature due to the difficulty of measuring smaller eggs using traditional methods. We used a Hall-effect thickness gauge to measure eggs of five focal songbird species from California’s Central Valley: House Wren (Troglodytes aedon; n = 567), Tree Swallow (Tachycineta bicolor; n = 297), Ash-throated Flycatcher (Myiarchus cinerascens; n = 21), Western Bluebird (Sialia mexicana; n = 13), and Bewick’s Wren (Thryomanes bewickii; n = 5). We compared minimum eggshell thickness measurements at the equator and sharp pole, and we related eggshell thickness to other egg morphometrics and adult body mass. Eggshell thickness at the equator was 5.6% thicker in Ash-throated Flycatchers and 3.5% thinner in Tree Swallows compared with eggshell thickness at the sharp pole. Among species, eggshell thickness at the sharp pole was greater in species with larger eggs, whereas, within species, larger eggs were thinner at the sharp pole. Eggshells were 8% and 11% thinner in late incubation eggs (≥75% of total incubation duration) than early incubation (≤10% of total incubation duration) for House Wren and Tree Swallow eggs, respectively. Whenever possible, it is preferable to use empirical eggshell thickness data that are specific to the species and geographic region being studied, and a relatively new method used in this study allows accurate measurement of small eggs without having to compromise the integrity of preserved eggshell specimens.
","language":"English","publisher":"Journal of Field Ornithology","doi":"10.5751/JFO-00410-950103","usgsCitation":"Schacter, C., Peterson, S.H., Hartman, C.A., Herzog, M.P., and Ackerman, J.T., 2024, Eggshell thickness and egg morphometrics in five songbird species from the Central Valley, California: Journal of Field Ornithology, v. 95, no. 1, 3, 10 p., https://doi.org/10.5751/JFO-00410-950103.","productDescription":"3, 10 p.","ipdsId":"IP-154263","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":440588,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.5751/jfo-00410-950103","text":"Publisher Index Page"},{"id":435054,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GL21VQ","text":"USGS data release","linkHelpText":"Eggshell Thickness in 5 Songbird Species"},{"id":425282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schacter, Carley R. 0000-0001-5493-2768","orcid":"https://orcid.org/0000-0001-5493-2768","contributorId":333758,"corporation":false,"usgs":false,"family":"Schacter","given":"Carley R.","affiliations":[{"id":79969,"text":"USFWS; Former USGS employee","active":true,"usgs":false}],"preferred":false,"id":893844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893848,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254428,"text":"70254428 - 2024 - Earthquake rupture forecast model construction for the 2023 U.S. 50‐State National Seismic Hazard Model Update: Central and eastern U.S. fault‐based source model","interactions":[],"lastModifiedDate":"2024-05-24T11:59:35.15136","indexId":"70254428","displayToPublicDate":"2024-01-31T06:56:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake rupture forecast model construction for the 2023 U.S. 50‐State National Seismic Hazard Model Update: Central and eastern U.S. fault‐based source model","docAbstract":"As part of the U.S. Geological Survey’s 2023 50‐State National Seismic Hazard Model (NSHM), we make modest revisions and additions to the central and eastern U.S. (CEUS) fault‐based seismic source model that result in locally substantial hazard changes. The CEUS fault‐based source model was last updated as part of the 2014 NSHM and considered new information from the Seismic Source Characterization for Nuclear Facilities (CEUS‐SSCn) Project. Since then, new geologic investigations have led to revised fault and fault‐zone inputs, and the release of databases of fault‐based sources in the CEUS. We have reviewed these databases and made minor revisions to six of the current fault‐based sources in the NSHM, as well as added five new fault‐based sources. Implementation of these sources follows the current NSHM methodology for CEUS fault‐based sources, as well as the incorporation of a new magnitude–area relationship and updated maximum magnitude and recurrence rate estimates following the methods used by the CEUS‐SSCn Project. Seismic hazard sensitivity calculations show some substantial local changes in hazard (−0.4g to 1.1g) due to some of these revisions and additions, especially from the addition of the central Virginia, Joiner ridge, and Saline River sources and revisions made to the Meers and New Madrid sources.
Many studies use landscape form to determine spatial patterns of tectonic deformation, and these are particularly effective when paired with independent measures of rock uplift and erosion. Here, we use morphometric analyses and 10Be catchment-averaged erosion rates, together with reverse slip rates from the Sierra Madre−Cucamonga fault zone, to reveal patterns in uplift, erosion, and fault activity in the range front of the San Gabriel Mountains in southern California, USA. Our analysis tests two prevailing hypotheses: (1) the range front of the San Gabriel Mountains is at steady state, in which rock uplift balances erosion and topographic elevations are stable throughout time, and (2) that west-to-east increases in elevation, relief, erosion rate, and stream-channel steepness across the interior of the massif reflect a parallel reverse-slip rate gradient on the range-bounding Sierra Madre−Cucamonga fault zone. We show that although deviations from steady state occur, the range-front hillslopes and stream channels are typically both well-connected and adjusted to patterns in Quaternary uplift driven by motion on the range-front fault network. Accordingly, landscape morphometrics, 10Be erosion rates, and model erosion rates effectively image spatial and temporal patterns in uplift. Interpreted jointly, these data reveal comparable peak slip rates on the Sierra Madre−Cucamonga fault zone and show that they do not monotonically increase from west to east. Thus, the eastward-increasing gradients developed within the interior of the massif are not solely related to reverse slip on the range-front faults. Evaluated on shorter length scales (<10 km), morphometric data corroborate earlier descriptions of the Sierra Madre−Cucamonga fault zone as multiple individual faults or fault sections, with slip rates tapering toward fault tips. We infer that these patterns imply the predominance of independent fault or fault section ruptures throughout the Quaternary, though data cannot rule out the possibility of large, connected Sierra Madre−Cucamonga fault zone ruptures. Deeper in the hanging wall of the Sierra Madre−Cucamonga fault zone, secondary faults accommodate range-front uplift. Motion on these faults may contribute to active uplift of the highest topography within the massif, in addition to partly reconciling differences between geologic and geodetic Sierra Madre−Cucamonga fault zone reverse-slip rates. This study provides a new, unified perspective on tectonics and landscape evolution in the San Gabriel Mountains.
Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. This work is part of that reexamination.
The stationarity assumption is a concern because flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done to assess potential nonstationarity in peak flows in the north-central United States.
This report summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235064","collaboration":"Prepared in cooperation with Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation","usgsCitation":"Ryberg, K.R., comp., 2024, Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin: U.S. Geological Survey Scientific Investigations Report 2023–5064, [variously paged], https://doi.org/10.3133/sir20235064.","productDescription":"1 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":424953,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5064/sir20235064.pdf","text":"Abstract","size":"522 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5064"},{"id":424911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5064/coverthb.jpg"}],"contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. Flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done by the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, to assess potential nonstationarity in peak flows in the north-central United States.
This chapter summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flow. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The climate data consist of monthly time series estimates of temperature, precipitation, potential evapotranspiration, actual evapotranspiration, snowfall, soil moisture storage, snow water equivalent, and runoff on a 3.1-mile by 3.1-mile grid for the conterminous United States.
Statistical and graphical analyses were used to investigate potential changes in hydrology and climate. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. To examine potential causal drivers of changes, the climate data were analyzed graphically and statistically. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Peak Streamflow Trends and Their Relation to Changes in Climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235064A","collaboration":"Prepared in cooperation with Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation","usgsCitation":"Ryberg, K.R., Over, T.M., Levin, S.B., Heimann, D.C., Barth, N.A., Marti, M.K., O’Shea, P.S., Sanocki, C.A., Williams-Sether, T.J., Wavra, H.N., Sando, T.R., Sando, S.K., and Liu, M.S., 2024, Introduction and methods of analysis for peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin, chap. A of Ryberg, K.R., comp., Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin: U.S. Geological Survey Scientific Investigations Report 2023–5064, 27 p., https://doi.org/10.3133/sir20235064A.","productDescription":"Report: vi, 27 p.; Data Release; Dataset","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-145865","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science 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\"}}]}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Lead isotope values for volcanogenic massive sulfide (VMS) deposits provide important insights into metal sources and the nature of pre-accretionary tectonostratigraphic terranes and underlying basements. Deposits of this type in New England formed in diverse tectonic settings including volcanic arcs and backarcs, a supra–subduction zone arc, a rifted forearc foreland basin, and a rifted continental margin. Following VMS mineralization on or near the seafloor, components of the tectonostratigraphic assemblages—volcanic ± sedimentary rocks, coeval intrusions, sulfide deposits, and underlying basements—were diachronously accreted to the Laurentian margin during the Paleozoic. Lead isotope data for galena show relatively large ranges for 206Pb/204Pb, 207Pb/204Pb, and 208Pb/204Pb. Evaluation of potential lead sources, using for comparison Pb-isotope data from modern and ancient settings, suggests that principal sources include the mantle, volcanic ± sedimentary rocks, and deeper basement rocks. Integration of the Pb-isotope values with published data such as Nd isotopes for the volcanic rocks and from deep seismic reflection profiles points to the involvement of several basements, including those of Grenvillian, Ganderian, Avalonian, and West African (and (or) Amazonian) affinity. Clustering of Pb-isotope data for VMS deposits within individual Cambrian and Ordovician volcanic and volcanosedimentary settings, delineated by differences in 206Pb/204Pb and µ (238U/204Pb) values, are consistent with lead derivation from at least four and possibly five different tectonostratigraphic assemblages with isotopically distinct basements. Collectively, our Pb-isotope data for New England VMS deposits provide a novel window into the nature of subarc basement rocks during pre-accretionary sulfide mineralization outboard of Laurentia during early Paleozoic time.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjes-2023-0058","usgsCitation":"Slack, J.F., Swinden, S., Piercey, S., Ayuso, R.A., Van Staal, C., and LeHuray, A., 2024, Lead isotopes in New England (USA) volcanogenic massive sulphide deposits: Implications for metal sources and pre-accretionary tectonostratigraphic terranes: Canadian Journal of Earth Sciences, v. 61, no. 3, p. 329-354, https://doi.org/10.1139/cjes-2023-0058.","productDescription":"26 p.","startPage":"329","endPage":"354","ipdsId":"IP-150600","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":488061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjes-2023-0058","text":"Publisher Index Page"},{"id":481924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -51.10577731806529,\n 46.61275186321612\n ],\n [\n -55.35082263691291,\n 54.182554388508834\n ],\n [\n -61.35588171642382,\n 57.46002851922097\n ],\n [\n -73.28079877295971,\n 45.00743093796049\n ],\n [\n -73.47490888047565,\n 41.05036540728776\n ],\n [\n -70.9730034551954,\n 41.1363051887171\n ],\n [\n -69.42632131232216,\n 40.955457251309355\n ],\n [\n -70.14968181955982,\n 42.77227106840391\n ],\n [\n -67.14459409952332,\n 44.41871947402353\n ],\n [\n -65.06951975286547,\n 43.051439551694585\n ],\n [\n -59.341656766565194,\n 45.94306586960545\n ],\n [\n -58.30143626152355,\n 47.009132973035605\n ],\n [\n -54.6406975038181,\n 46.28851454484371\n ],\n [\n -51.10577731806529,\n 46.61275186321612\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"61","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":926991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swinden, Scott","contributorId":350789,"corporation":false,"usgs":false,"family":"Swinden","given":"Scott","affiliations":[],"preferred":false,"id":926992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piercey, Stephen","contributorId":221364,"corporation":false,"usgs":false,"family":"Piercey","given":"Stephen","email":"","affiliations":[],"preferred":false,"id":926993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":926994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Staal, Cees","contributorId":350790,"corporation":false,"usgs":false,"family":"Van Staal","given":"Cees","affiliations":[],"preferred":false,"id":926995,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LeHuray, Anne P. 0000-0003-3988-6673","orcid":"https://orcid.org/0000-0003-3988-6673","contributorId":334884,"corporation":false,"usgs":false,"family":"LeHuray","given":"Anne P.","affiliations":[{"id":80277,"text":"Chemical Management Associates LLC","active":true,"usgs":false}],"preferred":false,"id":926996,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70251275,"text":"70251275 - 2024 - The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters","interactions":[],"lastModifiedDate":"2024-02-05T15:24:29.754603","indexId":"70251275","displayToPublicDate":"2024-01-25T06:55:25","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters","docAbstract":"Rare earth elements (REEs) are a class of critical minerals, all of which can have supply chain vulnerability that impacts economic security. These elements are widely measured in environmental matrices via inductively coupled plasma mass spectrometry (ICP-MS); however, successful quantification can require time-consuming, sample-specific optimization. While a sample-by-sample approach is appropriate for targeted quantification studies, this approach is not suitable for mineral exploration efforts where rapidly screening thousands of samples for the presence of REEs is desired. Here, we demonstrated the use of a Quick Screening Tool for Approximating REEs (Q-STAR) to detect REEs in surface water and groundwater matrices, collected as part of existing environmental studies. A mass-to-charge ratio of 144 (m/z = 144) was added to an ICP-MS method to screen for REEs in filtered water samples submitted for metals analyses to the U.S. Geological Survey (USGS) National Water Quality Laboratory. We detected the presence of REEs above a reference threshold of 1200 counts per second in 18 % of pre-selected 6626 samples. Using this screened dataset, we mapped estimated dissolved REE concentrations across the United States in relation to ecoregions and underlying geology. Data are constrained to where sample collection took place but nevertheless show estimated aqueous dissolved REE concentrations on a geographic scale that has not yet been studied. To validate Q-STAR, REEs were measured in a USGS standard reference sample, a subset of 88 archived filtered water samples, and in fresh filtered surface water samples. Our targeted analyses demonstrated a strong linear relationship between Q-STAR predicted and measured values in all archived samples for Nd (r2 = 0.94), and light REEs (LREEs) such as lanthanum (La) (r2 = 0.93), praseodymium (Pr) (r2 = 0.94) and samarium (Sm) (r2 = 0.94). Using Q-STAR screen values, nine field sites were identified and surface water samples recollected to confirm the continued presence of Nd and LREEs. Q-STAR can be used to screen an unlimited number of water samples for the presence of REEs prior to time-intensive and costly quantitative analyses and to generate large REE datasets for further investigation.
The evolutionary origins of sexual preferences for chemical signals remain poorly understood, due, in part, to scant information on the molecules involved. In the current study, we identified a male pheromone in lake char (Salvelinus namaycush) to evaluate the hypothesis that it exploits a non-sexual preference for juvenile odour. In anadromous char species, the odour of stream-resident juveniles guides migratory adults into spawning streams. Lake char are also attracted to juvenile odour but have lost the anadromous phenotype and spawn on nearshore reefs, where juvenile odour does not persist long enough to act as a cue for spawning site selection by adults. Previous behavioural data raised the possibility that males release a pheromone that includes components of juvenile odour. Using metabolomics, we found that the most abundant molecule released by males was also released by juveniles but not females. Tandem mass spectrometry and nuclear magnetic resonance were used to identify the molecule as taurocholic acid (TCA), which was previously implicated as a component of juvenile odour. Additional chemical analyses revealed that males release TCA at high rates via their urine during the spawning season. Finally, picomolar concentrations of TCA attracted pre-spawning and spawning females but not males. Taken together, our results indicate that male lake char release TCA as a mating pheromone and support the hypothesis that the pheromone is a partial match of juvenile odour.
Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
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