The U.S. Geological Survey, in cooperation with the National Marine Sanctuary Program of the National Oceanic and Atmospheric Administration, has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The area being mapped using geophysical and geological data includes the SBNMS and the surrounding region, which totals approximately 3,700 square kilometers (km2) and is subdivided into 18 quadrangles. The seabed is a glaciated terrain that is topographically and texturally diverse. Quadrangle 5, the subject of this scientific investigations map, has an area of 211 km2 and has water depths that range from 23 meters (m) on the Stellwagen Bank crest to 105 m in the Stellwagen Basin. Seven map types, each at a scale of 1:25,000, depict seabed topography, ruggedness, backscatter intensity, distribution of geologic substrates, sediment mobility, distribution of fine- and coarse-grained sand, and substrate mud content. These maps show the distribution of geologic substrates on the crest and western flank of the south-central part of Stellwagen Bank and in Stellwagen Basin to the west. Interpretations of multibeam sonar bathymetric and seabed backscatter imagery, photographs, video imagery, and grain-size analyses were used to create the geology-based maps. Data from 729 stations were analyzed, including 620 sediment samples. The geologic substrate maps of quadrangle 5 show the distribution of 20 substrates that represent a wide range of textures, such as mobile and rippled sand, immobile sand, sand that partially veneers gravel, boulder ridges, and mud. Mapped substrates are characterized by sediment grain-size composition, surface morphology, substrate layering, the mobility or immobility of substrate surfaces, and water depth range. This scientific investigations map portrays the major geological elements (substrates, topographic features, and processes) of environments in quadrangle 5. It is intended to provide a foundation for research into present and past sediment transport processes in a complex terrain, provide insights into the ecological requirements of invertebrate and vertebrate species that utilize the various substrates, and to support seabed management in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3515","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","programNote":"Coastal/Marine Hazards and Resources Program","usgsCitation":"Valentine, P.C., and Cross, V.A., 2024, Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 5 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts: U.S. Geological Survey Scientific Investigations Map 3515, 8 sheets, scale 1:25,000, 27-p. pamphlet, https://doi.org/10.3133/sim3515.","productDescription":"Pamphlet: v, 27 p.; 8 Sheets: 26.96 × 32.43 inches or smaller; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082905","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":502035,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sim3544","text":"Scientific Investigations Map 3544","linkHelpText":"- Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 3 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts"},{"id":465153,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sim3530","text":"Scientific Investigations Map 3530","linkHelpText":"- Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 2 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts"},{"id":426776,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sim3341","text":"Scientific Investigations Map 3341","linkHelpText":"- Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in Quadrangle 6 of the Stellwagen Bank National Marine Sanctuary Region offshore of Boston, Massachusetts"},{"id":426652,"rank":14,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W9BN3S","text":"USGS data release","linkHelpText":"Geospatial datasets of seabed topography, sediment mobility, and the distribution of geologic substrates in quadrangle 5 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts"},{"id":426650,"rank":13,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3515/sim3515_mapG.pdf","text":"Map G","size":"1.53 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Distribution of Substrate Mud Content and Boulder Ridges"},{"id":426644,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3515/sim3515_mapA.pdf","text":"Map A","size":"11.4 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Sun-Illuminated Topography and Boulder Ridges"},{"id":426651,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3515/full","text":"Pamphlet","linkFileType":{"id":5,"text":"html"},"description":"SIM 3515 HTML"},{"id":426643,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3515/sim3515_pamphlet.pdf","text":"Pamphlet","size":"2.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3515 Pamphlet"},{"id":426645,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3515/sim3515_mapB.pdf","text":"Map B","size":"1.72 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Seabed Ruggedness"},{"id":426642,"rank":5,"type":{"id":34,"text":"Image 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U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
Nonnative species may display unique life history traits when established in habitats with distinctive environmental and biotic contexts compared with their native ecosystems. Gulf killifish (Fundulus grandis), native to coastal habitats of the Gulf of Mexico, are established in several inland river systems where they pose a potential threat to native fishes. In the Pecos River, Texas, nonnative Gulf killifish have shown a high rate of piscivory compared with native coastal populations; otherwise, little is known about the ecology of the species in inland systems. We examined reproductive characteristics, size, and age of Gulf killifish in the Pecos River. We found that reproduction takes place approximately between late March and September, with the gonadosomatic index of females showing a large and extended peak in spring and a second minor peak in late August–September. Our age estimations indicate that this population consists mostly of fish <2 years old, similarly to that reported for coastal populations. Total length ranged 11.9–143.4 mm for males and 32.3–162.5 mm for females, indicating a sexually dimorphic size structure with Pecos River individuals reaching larger sizes compared with coastal populations. The relatively large size and piscivorous nature of Gulf killifish, along with tolerance for a wide range of environmental conditions, are attributes in nonnative species hypothesized to promote invasion success and replacement of native species.
","language":"English","publisher":"Southwestern Association of Naturalists","doi":"10.1894/0038-4909-68.1.1","usgsCitation":"Delaune, K., Pease, A., Patino, R., Brown, C.L., and Barnes, M., 2024, Gulf killifish (Fundulus grandis) in the Pecos River: Unique life history traits in a nonnative, island population: Southwestern Naturalist, v. 68, no. 1, p. 1-12, https://doi.org/10.1894/0038-4909-68.1.1.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-132094","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.15125403534212,\n 33.460380957090834\n ],\n [\n -103.65531606145227,\n 31.30384163898544\n ],\n [\n -101.34407369303406,\n 29.483966031206847\n ],\n [\n -100.89623060006912,\n 29.591781476453974\n ],\n [\n -102.11190768833953,\n 31.27083588828689\n ],\n [\n -103.39674006007425,\n 31.828767129152226\n ],\n [\n -104.10922146734698,\n 32.919266235303375\n ],\n [\n -104.12287053645167,\n 34.47343853197968\n ],\n [\n -104.89267803396459,\n 35.913954955016834\n ],\n [\n -105.75078791826955,\n 35.58270848916575\n ],\n [\n -104.62887284443381,\n 33.66932615920572\n ],\n [\n -105.15125403534212,\n 33.460380957090834\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"68","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Delaune, K.D.","contributorId":340643,"corporation":false,"usgs":false,"family":"Delaune","given":"K.D.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":907421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pease, A.A.","contributorId":340644,"corporation":false,"usgs":false,"family":"Pease","given":"A.A.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":907422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patino, Reynaldo 0000-0002-4831-8400 r.patino@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-8400","contributorId":2311,"corporation":false,"usgs":true,"family":"Patino","given":"Reynaldo","email":"r.patino@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Connor L.","contributorId":341842,"corporation":false,"usgs":false,"family":"Brown","given":"Connor","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":908997,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnes, M.A.","contributorId":340646,"corporation":false,"usgs":false,"family":"Barnes","given":"M.A.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":907424,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70252548,"text":"70252548 - 2024 - Assessing giant sequoia mortality and regeneration following high-severity wildfire","interactions":[],"lastModifiedDate":"2024-03-28T12:01:19.78198","indexId":"70252548","displayToPublicDate":"2024-03-21T07:00:21","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Assessing giant sequoia mortality and regeneration following high-severity wildfire","docAbstract":"Fire is a critical driver of giant sequoia (Sequoiadendron giganteum [Lindl.] Buchholz) regeneration. However, fire suppression combined with the effects of increased temperature and severe drought has resulted in fires of an intensity and size outside of the historical norm. As a result, recent mega-fires have killed a significant portion of the world's sequoia population (13%–19%), and uncertainty surrounds whether severely affected groves will be able to recover naturally, potentially leading to a loss of grove area. To assess the likelihood of natural recovery, we collected spatially explicit data assessing mortality, crown condition, and regeneration within four giant sequoia groves that were severely impacted by the SQF- (2020) and KNP-Complex (2021) wildfires within Sequoia and Kings Canyon National Parks. In total, we surveyed 5.9 ha for seedlings and assessed the crown condition of 1104 giant sequoias. To inform management, we used a statistical methodology that robustly quantifies the uncertainty in inherently “noisy” seedling data and takes advantage of readily available remote sensing metrics that would make our findings applicable to other recently burned groves. A loss of giant sequoia grove area would be a consequence of giant sequoia tree mortality followed by a failure of natural regeneration. We found that areas that experienced very high-severity fire (above ~800 RdNBR) are at substantial risk for the loss of grove area, with tree mortality rapidly increasing and giant sequoia seedling density simultaneously decreasing with fire severity. Such high-severity areas comprised 17.8, 142.0, 14.6, 1.6 ha and ~90%, ~14%, ~53%, and ~27% of Board Camp, Redwood Mountain, Suwanee, and New Oriole Lake groves, respectively. In all sampling areas, we found that seedling densities fell far below the average density measured after prescribed fires, where seedling numbers were almost certainly adequate to maintain giant sequoia populations and postfire conditions were more in keeping with historical norms. Importantly, spatial pattern is also important in assessing the risk of grove loss, and in two groves, Suwanee and New Oriole Lake, the high-severity patches were not always contiguous, potentially making some areas more resilient to regeneration failure due to the proximity of surviving trees.
The use of nature-based solutions (NBS) for coastal climate adaptation has broad and growing interest, but NBS are rarely assessed with the same rigor as traditional engineering solutions or with respect to future climate change scenarios. These gaps pose challenges for the use of NBS for climate adaptation. Here, we value the flood protection benefits of stakeholder-identified marsh restoration under current and future climate change within San Francisco Bay, a densely urbanized estuary, and specifically on the shores of San Mateo County, the county most vulnerable to future flooding in California. Marsh restoration provides a present value of 21 million dollars which increases to over 100 million dollars with 0.5 m of sea level rise (SLR), and to about 500 million dollars with 1 m of SLR. There are hotspots within the county where marsh restoration delivers very high benefits for adaptation, which reach 9 million dollars/hectare with likely future sea level and storm conditions. Today’s investments in nature and community resilience can result in increasing payoffs as climate change progresses and risk increases.
Restoring biological crust (biocrust) in disturbed drylands is challenging due to the difficult environmental conditions, such as limited soil moisture, low soil nutrients, and extreme temperatures, that impede growth. Understanding how the key components of biocrust—mosses, lichens, and cyanobacteria—react to different environmental factors informs the optimal timing, locations, and species composition for biocrust reintroduction, thereby increasing the likelihood of establishment. Here, we inoculated soils with a diverse range of biocrust organisms, analogous to seeding an area with diverse vascular plant seeds, and varied environmental conditions to observe how these changes influenced the development and functions of reintroduced biocrust. We found that by manipulating soil texture and time spent wet, we can change the proportional cover of biocrust within a restoration-like setting. Specifically, we found that 4 months after inoculation, finer textured soils that received more water become dominated by moss cover, while coarser textured soils with less water remained dominated by cyanobacteria cover, and the interactions between texture and time spent wet strongly influenced cover. We found biocrust morphological group cover had a small, but detectable, effect on ecosystem functions (soil stability and nitrogenase activity, a proxy for nitrogen fixation), but that environmental conditions had a stronger impact on the functions we measured. Manipulative experiments in controlled environments, like this one, can help elucidate the mechanisms underlying the establishment rate and patterns of biocrusts post-inoculation, and inform implementation of inoculations in the field.
Observed links between parasites, such as ticks, and climate change have aroused concern for human health, wildlife population dynamics, and broader ecosystem effects. The one-host life history of the winter tick (Dermacentor albipictus) links each annual cohort to environmental conditions during three specific time periods when they are predictably vulnerable: spring detachment from hosts, summer larval stage, and fall questing for hosts. We used mixed-effects generalized linear models to investigate the drivers of tick loads carried by moose (Alces alces) relative to these time periods and across 750 moose, 10 years, and 16 study areas in the western United States. We tested for the effects of biotic factors (moose density, shared winter range, vegetation, migratory behavior) and weather conditions (temperature, snow, humidity) during each seasonal period when ticks are vulnerable and off-host. We found that warm climatic regions, warm seasonal periods across multiple partitions of the annual tick life cycle, and warm years relative to long-term averages each contributed to increased tick loads. We also found important effects of snow and other biotic factors such as host density and vegetation. Tick loads in the western United States were, on average, lower than those where tick-related die-offs in moose populations have occurred recently, but loads carried by some individuals may be sufficient to cause mortality. Lastly, we found interannual variation in tick loads to be most correlated with spring snowpack, suggesting this environmental component may have the highest potential to induce change in tick load dynamics in the immediate future of this region.
The Babouri-Figuil Basin (BFB) is a frontier basin for petroleum in Cameroon. It belongs to the series of Cretaceous rift basins of the West and Central Rift System (WCARS), the origin of which is related to the opening of the South Atlantic. Within the same rift system, commercial hydrocarbon accumulations have been discovered in Chad, Sudan, Niger and, more recently, in Nigeria (Gongola Basin). The study of the geology of the BFB just recently received considerable attention, mainly because of its presumed hydrocarbon potential. In the pursuit of researching possible petroleum systems in the BFB, the current study provides a first look into the characterization of source and reservoir rock and its integration into a 2D lithostratigraphic model. The study was solely based on outcrop samples. Black shale and massive claystone are good to excellent hydrocarbon source rocks [e.g., up to 38 wt% total organic carbon (TOC), up to 943 mg/g hydrogen index, up to 85 m thickness, up to 20–30 km lateral extension], with moderate to high values of extractable organic matter (e.g., >10,000 ppm). Calcareous claystone, on the other hand, are poor source rocks [e.g., <0.20 wt% TOC]. The samples are thermally immature, except for those located close to volcanic intrusion at Golombe that have reached the threshold for oil generation (Tmax >435 °C, production index >0.1). The petrographic analysis of sandstone revealed that they are fine-grained to coarse-grained, poorly to moderately sorted, texturally and compositionally immature to submature, subarkosic to arkosic arenites. The main diagenetic processes that affected sandstones are as follows: moderate to intense compaction characterized by the development of long, concavo-convex, and sutured contacts between grains; cementation through calcite, iron oxide, and quartz cements; alteration of mica and feldspar grains; partial to complete dissolution of feldspar, mica, amphibole grains, and calcite cement; and the replacement of feldspar and mica grains by clay minerals. Alteration and dissolution increase the porosity of sandstone through the creation of secondary pores. However, mechanical compaction through the development of a pseudomatrix and cementation as pore-filling materials have significantly reduced the quality of sandstone beds as conventional petroleum reservoirs. Hence, the best reservoir-quality sandstones in the basin are generally located in the upper portion of the basin in terms of its lithostratigraphic model. They are the cleanest sandstones with the smallest amount of cement and the lowest ductile grain content (pseudomatrix), with a thickness that varies from 3 m to 120 m and a lateral extension of 20 km. The lithostratigraphic model of the basin is characterized by an extensive lacustrine environment that provided a thick sequence of organic-rich formations; sand deposited as extensive reservoirs sandwiched between shale/claystone beds; the development of stratigraphic traps through lateral facies change; and the widespread deposition of lacustrine and floodplain claystone that provide regional seals. The similarities between the Babouri-Figuil Basin and proven petroleum systems in other WCARS rift basins suggest that the basin may host at least one petroleum system where actively generating source rocks are present.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2024.104491","usgsCitation":"Gaspard, M., Hatcherian, J.J., Hackley, P.C., Bessong, M., Bapowa, C., Pougue, H., and Meying, A., 2024, Novel insights about petroleum systems from source and reservoir rock characterization, Cretaceous Deposits, Babouri-Figuil Basin, Northern Cameroon: International Journal of Coal Geology, v. 285, 104491, 21 p., https://doi.org/10.1016/j.coal.2024.104491.","productDescription":"104491, 21 p.","ipdsId":"IP-158392","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":427402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Cameroon","otherGeospatial":"Babouri-Figuil Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 13.666,\n 9.85\n ],\n [\n 13.666,\n 9.633\n ],\n [\n 14.033,\n 9.633\n ],\n [\n 14.033,\n 9.85\n ],\n [\n 13.666,\n 9.85\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"285","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gaspard, Manga","contributorId":335306,"corporation":false,"usgs":false,"family":"Gaspard","given":"Manga","email":"","affiliations":[],"preferred":false,"id":898040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":898041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":898039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bessong, Moise","contributorId":335307,"corporation":false,"usgs":false,"family":"Bessong","given":"Moise","email":"","affiliations":[],"preferred":false,"id":898042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bapowa, Carole","contributorId":335308,"corporation":false,"usgs":false,"family":"Bapowa","given":"Carole","email":"","affiliations":[],"preferred":false,"id":898043,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pougue, Henry","contributorId":335309,"corporation":false,"usgs":false,"family":"Pougue","given":"Henry","email":"","affiliations":[],"preferred":false,"id":898044,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meying, Arsene","contributorId":335311,"corporation":false,"usgs":false,"family":"Meying","given":"Arsene","email":"","affiliations":[],"preferred":false,"id":898045,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261502,"text":"70261502 - 2024 - Changes in landscape and climate in Mexico and Texas reveal small effects on migratory habitat of monarch butterflies (Danaus plexippus)","interactions":[],"lastModifiedDate":"2024-12-13T14:14:04.429932","indexId":"70261502","displayToPublicDate":"2024-03-20T08:19:36","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Changes in landscape and climate in Mexico and Texas reveal small effects on migratory habitat of monarch butterflies (Danaus plexippus)","docAbstract":"The decline of the iconic monarch butterfly (Danaus plexippus) in North America has motivated research on the impacts of land use and land cover (LULC) change and climate variability on monarch habitat and population dynamics. We investigated spring and fall trends in LULC, milkweed and nectar resources over a 20-year period, and ~ 30 years of climate variables in Mexico and Texas, U.S. This region supports spring breeding, and spring and fall migration during the annual life cycle of the monarch. We estimated a − 2.9% decline in milkweed in Texas, but little to no change in Mexico. Fall and spring nectar resources declined < 1% in both study extents. Vegetation greenness increased in the fall and spring in Mexico while the other climate variables did not change in both Mexico and Texas. Monarch habitat in Mexico and Texas appears relatively more intact than in the midwestern, agricultural landscapes of the U.S. Given the relatively modest observed changes in nectar and milkweed, the relatively stable climate conditions, and increased vegetation greenness in Mexico, it seems unlikely that habitat loss (quantity or quality) in Mexico and Texas has caused large declines in population size or survival during migration.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-024-56693-z","usgsCitation":"Diffendorfer, J., Botello, F., Drummond, M.A., Ancona, Z.H., Corro, L.M., Thogmartin, W.E., Ibsen, P.C., Moreno-Sanchez, R., Lukens, L., and Sanchez-Cordero, V., 2024, Changes in landscape and climate in Mexico and Texas reveal small effects on migratory habitat of monarch butterflies (Danaus plexippus): Scientific Reports, v. 14, 6703, 13 p., https://doi.org/10.1038/s41598-024-56693-z.","productDescription":"6703, 13 p.","ipdsId":"IP-158913","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467022,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-56693-z","text":"Publisher Index Page"},{"id":465063,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United 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Understanding the effects of climate change on hydrology is important to State and community officials to evaluate the potential effects on infrastructure and water systems. To better understand the effects of climate change on hydrology, the U.S. Geological Survey, in partnership with Cornell University and Tufts University, conducted a study in cooperation with the Massachusetts Executive Office of Energy and Environmental Affairs to develop tools for projecting 21st-century climate and hydrologic characteristics in Massachusetts.
A stochastic weather generator was developed to project future climatic characteristics for Massachusetts. The stochastic weather generator estimates daily precipitation, minimum temperature, and maximum temperature for 17 warming scenarios (from 0 to 8 degrees Celsius, in 0.5-degree increments). To project future hydrologic characteristics, the stochastic weather generator output data were input to the Precipitation-Watershed Modeling System deterministic watershed model for the Squannacook River watershed, which is the watershed selected as the pilot study location for investigating future hydrologic characteristics. Hydrologic data output from the deterministic watershed model were then input to a stochastic watershed model developed for this study to correct model errors (model errors are often observed in the output from deterministic models at the high- and low-flow extremes). The output from the stochastic watershed model was then used to characterize hydrology for the 17 warming scenarios. For the Squannacook River watershed, the results project more extreme flood and low streamflows under the warming scenarios.
Output from the tools allows the characterization of future streamflows for the years 2030, 2050, 2070, and 2090, which expands our understanding of 21st-century climatic and hydrologic risk in Massachusetts. These tools could improve Federal, State, and community officials’ ability to mitigate the effects of climate change over the next several decades.
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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 7, 8, and 9 for quarter 3 (July–September) of 2023. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
This is the first quarterly report to include analysis results for Landsat 9, which was launched in September 2021. The inclusion of Landsat 9 analysis results was dependent on two factors: a complete reprocessing of the Landsat 9 data archive and enough time elapsing to begin formulating lifetime trends. In April 2023, all Landsat 9 image data acquired since the satellite’s launch were reprocessed to take advantage of calibration updates identified by the ECCOE Landsat Cal/Val Team. Additional information about the Landsat 9 reprocessing effort is available at https://www.usgs.gov/landsat-missions/news/upcoming-reprocessing-all-landsat-9-data.
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U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Human populations have utilized heavy metals and persistent organic pollutants for their physiochemical properties in industrial, agricultural, and consumer goods for decades. Limited knowledge on their persistence and toxicological effects has resulted in organisms being exposed to some of the most problematic compounds ever generated by humans. Although overlap in exposure paradigms exists for historical and emerging contaminants, the different physiochemical properties, sources into the environment, and bioactivity of contaminants of emerging concern (CECs) have highlighted the importance of characterizing their risk to aquatic wildlife under chronic low-dose exposure scenarios. This chapter defines the fundamental terminology associated with characterizing the exposure paradigm in ecological risk assessment. The different sources and fate, routes of exposure, and biotransformation of common contaminants are covered using model chemicals to emphasize important factors that affect their partitioning among different environmental matrices. Finally, this chapter concludes with a discussion about bioaccumulation models and an example of how two similar CECs demonstrate different clearance rates and bioaccumulation potentials in fish.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Aquatic ecotoxicology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-031-53130-9_8","usgsCitation":"Saari, G.N., Siddiqui, S., and Brander, S.M., 2024, Partitioning of chemicals in aquatic organisms, chap. of Aquatic ecotoxicology, p. 115-130, https://doi.org/10.1007/978-3-031-53130-9_8.","productDescription":"16 p.","startPage":"115","endPage":"130","ipdsId":"IP-146203","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":433696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-03-19","publicationStatus":"PW","contributors":{"editors":[{"text":"Siddiqui, Samreen","contributorId":298402,"corporation":false,"usgs":false,"family":"Siddiqui","given":"Samreen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":912940,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Brander, Susanne M.","contributorId":187546,"corporation":false,"usgs":false,"family":"Brander","given":"Susanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":912941,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Saari, Gavin N. 0000-0002-3593-5127 gsaari@usgs.gov","orcid":"https://orcid.org/0000-0002-3593-5127","contributorId":289203,"corporation":false,"usgs":true,"family":"Saari","given":"Gavin","email":"gsaari@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":912888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siddiqui, Samreen","contributorId":298402,"corporation":false,"usgs":false,"family":"Siddiqui","given":"Samreen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":912889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brander, Susanne M.","contributorId":187546,"corporation":false,"usgs":false,"family":"Brander","given":"Susanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":912890,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70253020,"text":"70253020 - 2024 - Invasive-dominated grasslands in Hawaiʻi are resilient to disturbance","interactions":[],"lastModifiedDate":"2024-04-17T12:12:10.505348","indexId":"70253020","displayToPublicDate":"2024-03-19T07:10:38","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Invasive-dominated grasslands in Hawaiʻi are resilient to disturbance","docAbstract":"Non-native-dominated landscapes may arise from invasion by competitive plant species, disturbance and invasion of early-colonizing species, or some combination of these. Without knowing site history, however, it is difficult to predict how native or non-native communities will reassemble after disturbance events. Given increasing disturbance levels across anthropogenically impacted landscapes, predictive understanding of these patterns is important. We asked how disturbance affected community assembly in six invaded habitat types common in dryland, grazed landscapes on Island of Hawai‘i. We mechanically disturbed 100 m2 plots in six vegetation types dominated by one of four invasive perennial grasses (Cenchrus ciliaris, Cenchrus clandestinus, Cenchrus setaceus, or Melinis repens), a native shrub (Dodonaea viscosa), or a native perennial bunchgrass (Eragrostis atropioides). We censused vegetation before disturbance and monitored woody plant colonization and herbaceous cover for 21 months following the disturbance, categorizing species as competitors, colonizers, or a combination, based on recovery patterns. In addition, we planted individuals of the native shrub and bunchgrass and monitored survival to overcome dispersal limitation of native species when exploring these patterns. We found that the dominant vegetation types showed variation in post-disturbance syndrome, and that the variation in colonizer versus competitor syndrome occurred both between species, but also within species among different vegetation types. Although there were flushes of native shrub seedlings, these did not survive to 21 months within invaded habitats, probably due to regrowth by competitive invasive grasses. Similarly, survival of planted native individuals was related to the rate of regrowth by dominant species. Regardless of colonization/competitor syndrome, however, all dominant vegetation types were relatively resilient to change. Our results highlight that the altered post-agricultural, invaded grassland landscapes in Hawaiʻi are stable states. More generally, they point to the importance of resident communities and their effects on species interactions and seed availability in shaping plant community response to disturbance.
Watershed nutrient management often focuses on actions that reduce the movement of nitrogen (N) and phosphorus (P) from agricultural lands into streams. One area of management focus is the buffer of land adjacent to streams. Wetlands and forests in this buffer can intercept and retain N and P from the landscape. In addition to directly intercepting agricultural nutrients, natural habitats in the buffer can alter stream geomorphology and influence the in-stream processing and transformation of N and P to less labile and mobile forms. Here, we assess the influence of buffer land cover on in-stream processing of N and P. We measured nutrient dynamics in the water column and sediments of agricultural streams in the Fox River and Duck Creek watersheds (WI, USA) during the growing season. In these streams, water column processing was low, possibly due to a lack of primary producers in the water column. Water column P processing was weakly associated with wetland land cover in the buffer, but buffer land cover had no clear effect on inorganic N processing. On the other hand, sediments were almost always a source of inorganic P and a sink for inorganic N. Sediment P release was higher in streams with more agricultural land cover in the buffer. Sediments in streams with agricultural land cover in the buffer also removed more nitrate, even after accounting for the greater availability of nitrate in those streams. The buffer land cover conditions we quantified occupy a very small portion of the overall watershed (100 m wide, for 1 km upstream of the study site) but nevertheless appear to influence in-stream cycling of N and P. For P management, reducing agricultural land cover in buffers is already a priority due to the ability of wetlands and forests to intercept nutrients, but this study suggests there may be some additional benefit due to changes in in-stream P processing.
The U.S. Geological Survey (USGS) collected data on the vertical distribution of hydraulic head, specific capacity, and water quality using aquifer-interval-isolation tests and other vertical profiling methods in 15 boreholes completed in fractured sedimentary bedrock in Northampton, Warminster, and Warwick Townships, Bucks County, Pennsylvania during 2018–19. This work was done, in cooperation with the U.S. Navy, to support detailed investigations at and near the former Naval Air Warfare Center (NAWC) Warminster, where groundwater contamination with per- and polyfluoroalkyl substances (PFAS) had become a concern since 2014. Two PFAS compounds, perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), have been measured in groundwater samples from supply and monitoring wells at or near NAWC Warminster in concentrations above U.S. Environmental Protection Agency health advisory levels for drinking water. The area is underlain by the Triassic Stockton Formation, which predominantly consists of sandstone interbedded with shale and siltstone beds and forms a layered fractured-rock aquifer used for private, industrial, and public drinking water supply.
The vertical distribution of aquifer properties and water quality was assessed through hydraulic tests and sampling of aquifer intervals using a straddle-packer system (13 boreholes) or depth-discrete point sampling under known borehole-flow conditions (2 boreholes). Geophysical and video logs collected by USGS during 2017–19 were used to identify potential water-bearing fractures in 15 boreholes, which ranged in depth from 210 to 604 feet (ft) and included 6 boreholes drilled in 2018 and 9 existing wells on or near the former NAWC Warminster. Measured borehole flow was predominantly downward in most of the deepest boreholes (greater than 400 ft), which were commonly located at the highest land-surface elevations, with inflow from fractures at relatively shallow depths and outflow through fractures near or below depths of 500 ft below land surface. Hydraulic head differences measured during packer tests were up to about 60 ft between shallow and deep intervals. Borehole flow was predominantly upward in most boreholes less than 400 ft in depth and farther from, and at lower land-surface elevations than, the former NAWC Warminster. Total borehole specific capacity ranged from about 0.07 to 41 gallons per minute per foot [(gal/min)/ft]. Specific-capacity values for individual intervals ranged from 0.02 to 40.0 (gal/min)/ft, with a median of 1.14 (gal/min)/ft and a large range in values at most depths.
Differences in water quality of samples as indicated by field properties (pH, dissolved oxygen, and specific conductance) and concentrations of dissolved major ions, PFOA, and PFOS were apparent among isolated intervals in the boreholes. Summed concentrations of PFOA and PFOS ranged from about 11 to 10,780 nanograms per liter (ng/L) and were greater than the 2016 U.S. Environmental Protection Agency health advisory of 70 ng/L for summed PFOA and PFOS concentrations in 62 of 104 intervals and discrete depths tested. The mass ratio of PFOS to PFOA was generally higher than 1.0 in samples with summed PFOA and PFOS concentrations greater than 70 ng/L, with ratio values as high as 8.7. In many boreholes, summed concentrations of PFOA and PFOS were positively related to chloride concentrations, which were elevated above natural-background values [less than 10 milligrams per liter] in most samples and as high as 717 milligrams per liter. Sources of the elevated chloride other than, or in addition to, common rock salt (sodium chloride) were indicated by chloride to sodium molar ratios greater than 1.0. Water-quality data indicated that sampled water from some intervals with lower hydraulic heads may be affected by water from intervals with higher hydraulic heads because of vertical flow in open boreholes; samples from these intervals with lower hydraulic heads may not be fully representative due to some component of cross contamination and should be interpreted with caution.
Through a preliminary correlation of natural gamma and resistivity logs of boreholes drilled at and near the former NAWC Warminster, 11 lithologic units were identified and interpreted to strike northeast and dip to the northwest. Hydraulic heads were generally highest in isolated intervals that intercepted beds which, when projected up dip, crop out at the highest land-surface elevation on the former NAWC Warminster, indicating that the dipping-bed structure and topography are factors affecting the distribution of hydraulic head in the aquifer. The hydrogeologic framework in conjunction with the vertical distribution of hydraulic heads and water quality may assist in evaluating the locations of various PFAS sources and potential migration pathways of PFAS in groundwater at and near NAWC Warminster.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241007","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Senior, L.A., and Fiore, A.R., 2024, Results of 2018–19 water-quality and hydraulic characterization of aquifer intervals using packer tests and preliminary geophysical-log correlations for selected boreholes at and near the former Naval Air Warfare Center Warminster, Bucks County, Pennsylvania (ver. 1.1, January 2025): U.S. Geological Survey Open-File Report 2024–1007, 136 p., https://doi.org/10.3133/ofr20241007.","productDescription":"Report: xv, 136 p.; 5 Plates; Data Release","numberOfPages":"136","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-138405","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":426405,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241007/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1007 HTML"},{"id":426406,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007.XML","description":"OFR 2024-1007 XML"},{"id":426407,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1007/images/"},{"id":426403,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1007/coverthb2.jpg"},{"id":426404,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007.pdf","text":"Report","size":"9.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1007 PDF"},{"id":426408,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TC92B5","text":"USGS data release","linkHelpText":"Water-level data and selected field notes for aquifer-interval-isolation tests at and near the former Naval Air Warfare Center Warminster, Bucks County, Pennsylvania, 2018–19 (ver. 2.0, January 2024)"},{"id":426409,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007_plates.pdf","text":"Plates 1–5","size":"921 KB"},{"id":481558,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007_versionHist.txt","size":"949 B","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Naval Air Warfare Center Warminster","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.21874919403015,\n 40.292862181975266\n ],\n [\n -75.21874919403015,\n 40.12697956762551\n ],\n [\n -74.97075997042653,\n 40.12697956762551\n ],\n [\n -74.97075997042653,\n 40.292862181975266\n ],\n [\n -75.21874919403015,\n 40.292862181975266\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: March 2024; Version 1.1 January 2025","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
This report is an update to the presentation by Schulz (1989) introducing potential users to the creepmeter data collected between the publication of Schulz’s report and mid-2020. The creepmeter network monitors aseismic, surface slip at various locations on the Hayward, Calaveras, and San Andreas Faults in northern and central California. There are different designs of creepmeters and these are briefly described. For a majority of the creepmeters, these data are automatically sent to the U.S. Geological Survey (USGS) offices where they are stored and processed. In addition, for most of the creepmeters, occasional manual measurements are made and these are compared with digitally recorded data. For some sites, the comparisons indicated degradation of the electronic sensor and consequently corrections are made to the digital data. The largest transient deformation is that which followed the 2004, M6, Parkfield earthquake. Various functions found in the literature that have been used to model postseismic slip were tested with the observed postseismic behavior seen on the creepmeters in the vicinity of Parkfield, California. No single function adequately fit all the data from these Parkfield instruments. This report is a discussion and analysis of data from creepmeters deployed by the USGS. The discussion primarily focuses on instruments that are currently operating in 2020 or have operated quite recently but are no longer in service.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241011","usgsCitation":"Langbein, J., Bilham, R.G., Snyder, H.A., and Ericksen, T., 2024, Summary of Creepmeter Data from 1980 to 2020—Measurements Spanning the Hayward, Calaveras, and San Andreas Faults in Northern and Central California: U.S. Geological Survey Report 2024–1011, 110 p., https://doi.org/10.3133/ofr20241011.","productDescription":"vi, 110 p.","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-143918","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499206,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116172.htm","linkFileType":{"id":5,"text":"html"}},{"id":426750,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1011/ofr20241011.pdf","text":"Report","size":"60 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":426749,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1011/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.83784784258054,\n 37.99394764431494\n ],\n [\n -122.83784784258054,\n 34.52234572819374\n ],\n [\n -119.36616815508066,\n 34.52234572819374\n ],\n [\n -119.36616815508066,\n 37.99394764431494\n ],\n [\n -122.83784784258054,\n 37.99394764431494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Rd.
Moffett Field, CA 94035
A massive bloom of the raphidophyte Heterosigma akashiwo occurred in summer 2022 in San Francisco Bay, causing widespread ecological impacts including events of low dissolved oxygen and mass fish kills. The rapidly evolving bloom required equally rapid management response, leading to the use of near-real-time image analysis of chlorophyll from the Ocean and Land Colour Instrument (OLCI) aboard Sentinel-3. Standard algorithms failed to adequately capture the bloom, signifying a need to refine a two-band algorithm developed for coastal and inland waters that relates the red-edge part of the remote sensing reflectance spectrum to chlorophyll. While the bloom was the initial motivation for optimizing this algorithm, an extensive dataset of in-water validation measurements from both bloom and non-bloom periods was used to evaluate performance over a range of concentrations and community composition. The modified red-edge algorithm with a simplified atmospheric correction scheme outperformed existing standard products across diverse conditions, and given the modest computational requirements, was found suitable for operational use and near-real-time product generation. The final version of the algorithm successfully minimizes error for non-bloom periods when chlorophyll a is typically <30 mg m−3, while also capturing bloom periods of >100 mg m−3 chlorophyll a.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16061103","usgsCitation":"Kudela, R.M., Senn, D.B., Richardson, E.T., Bouma-Gregson, K., Bergamaschi, B.A., and Sim, L., 2024, Evaluation and refinement of chlorophyll-a algorithms for high-biomass blooms in San Francisco Bay (USA): Remote Sensing, v. 16, no. 6, 1103, 15 p., https://doi.org/10.3390/rs16061103.","productDescription":"1103, 15 p.","ipdsId":"IP-160723","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":440089,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16061103","text":"Publisher Index Page"},{"id":435018,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GXJHZ3","text":"USGS data release","linkHelpText":"Assessing spatial variability of nutrients, phytoplankton, and related water-quality constituents in the San Francisco Bay, California: 2021-2022 High-resolution mapping surveys"},{"id":427314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.07594813067364,\n 37.409521554962424\n ],\n [\n -122.01459141030173,\n 37.543473010939294\n ],\n [\n -122.3138751078345,\n 37.9439399615851\n ],\n [\n -122.2371288097209,\n 38.076947981745235\n ],\n [\n -122.4289707157553,\n 38.1493978144897\n ],\n [\n -122.49802549540809,\n 38.08298835733879\n ],\n [\n -122.5286656402067,\n 37.93788689033987\n ],\n [\n -122.4673236665621,\n 37.792501512759955\n ],\n [\n -122.35216906140471,\n 37.610380642182776\n ],\n [\n -122.07594813067364,\n 37.409521554962424\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Kudela, Raphael M.","contributorId":205181,"corporation":false,"usgs":false,"family":"Kudela","given":"Raphael","email":"","middleInitial":"M.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":897798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senn, David B.","contributorId":205182,"corporation":false,"usgs":false,"family":"Senn","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":897799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Emily T. 0000-0003-2696-8266","orcid":"https://orcid.org/0000-0003-2696-8266","contributorId":304430,"corporation":false,"usgs":true,"family":"Richardson","given":"Emily","email":"","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bouma-Gregson, Keith 0000-0002-0304-6034","orcid":"https://orcid.org/0000-0002-0304-6034","contributorId":311235,"corporation":false,"usgs":true,"family":"Bouma-Gregson","given":"Keith","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897802,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sim, Lawrence","contributorId":168731,"corporation":false,"usgs":false,"family":"Sim","given":"Lawrence","email":"","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":897803,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70252559,"text":"70252559 - 2024 - All tidal wetlands are blue carbon ecosystems","interactions":[],"lastModifiedDate":"2024-03-28T11:57:06.250175","indexId":"70252559","displayToPublicDate":"2024-03-18T06:55:55","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"All tidal wetlands are blue carbon ecosystems","docAbstract":"Managing coastal wetlands is one of the most promising activities to reduce atmospheric greenhouse gases, and it also contributes to meeting the United Nations Sustainable Development Goals. One of the options is through blue carbon projects, in which mangroves, saltmarshes, and seagrass are managed to increase carbon sequestration and reduce greenhouse gas emissions. However, other tidal wetlands align with the characteristics of blue carbon. These wetlands are called tidal freshwater wetlands in the United States, supratidal wetlands in Australia, transitional forests in Southeast Asia, and estuarine forests in South Africa. They have similar or larger potential for atmospheric carbon sequestration and emission reductions than the currently considered blue carbon ecosystems and have been highly exploited. In the present article, we suggest that all wetlands directly or indirectly influenced by tides should be considered blue carbon. Their protection and restoration through carbon offsets could reduce emissions while providing multiple cobenefits, including biodiversity.
","language":"English","publisher":"American Institute of Biological Sciences","doi":"10.1093/biosci/biae007","usgsCitation":"Adame, M.F., Kelleway, J., Krauss, K., Lovelock, C.E., Adams, J.B., Trevathan-Tackett, S.M., Noe, G.E., Jeffrey, L., Ronan, M., Zann, M., Carnell, P.E., Iram, N., Maher, D.T., Murdiyarso, D., Sasmito, S.D., Tran, D.B., Dargusch, P., Kauffman, J.B., and Brophy, L.S., 2024, All tidal wetlands are blue carbon ecosystems: BioScience, biae007, 16 p., https://doi.org/10.1093/biosci/biae007.","productDescription":"biae007, 16 p.","ipdsId":"IP-152962","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":440093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biae007","text":"Publisher Index Page"},{"id":427204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Adame, Maria Fernanda","contributorId":242984,"corporation":false,"usgs":false,"family":"Adame","given":"Maria","email":"","middleInitial":"Fernanda","affiliations":[{"id":48596,"text":"Australian Rivers Institute, Griffith University","active":true,"usgs":false}],"preferred":false,"id":897548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelleway, Jeffrey","contributorId":149007,"corporation":false,"usgs":false,"family":"Kelleway","given":"Jeffrey","email":"","affiliations":[{"id":17618,"text":"Plant Functional Biology and Climate Change Cluster, University of Technology, Sydney, Broadway, NSW, Australia","active":true,"usgs":false}],"preferred":false,"id":897549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":222384,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":897550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovelock, Catherine E.","contributorId":215562,"corporation":false,"usgs":false,"family":"Lovelock","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":39280,"text":"School of Biological Sciences, The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":897551,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Janine B.","contributorId":303863,"corporation":false,"usgs":false,"family":"Adams","given":"Janine","email":"","middleInitial":"B.","affiliations":[{"id":65919,"text":"Nelson Mandela University (South Africa)","active":true,"usgs":false}],"preferred":false,"id":897552,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Trevathan-Tackett, Stacey M.","contributorId":335151,"corporation":false,"usgs":false,"family":"Trevathan-Tackett","given":"Stacey","email":"","middleInitial":"M.","affiliations":[{"id":68587,"text":"Deakin University, Australia","active":true,"usgs":false}],"preferred":false,"id":897553,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - 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Boone","contributorId":243963,"corporation":false,"usgs":false,"family":"Kauffman","given":"J.","email":"","middleInitial":"Boone","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":897565,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Brophy, Laura S.","contributorId":47266,"corporation":false,"usgs":false,"family":"Brophy","given":"Laura","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":897566,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70252241,"text":"70252241 - 2024 - Multiple stressors mediate the effects of warming on leaf decomposition in a large regulated river","interactions":[],"lastModifiedDate":"2024-03-21T11:57:22.485186","indexId":"70252241","displayToPublicDate":"2024-03-18T06:53:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Multiple stressors mediate the effects of warming on leaf decomposition in a large regulated river","docAbstract":"Predicting how increasing temperatures interact with other global change drivers to influence the structure and dynamics of Earth's ecosystems is a primary challenge in ecology. Our study made use of multiple simultaneous “natural experiments” to examine how rapid warming, declining nutrients, invasive consumers, and riparian invasive species management interact to influence leaf decomposition in a large and regulated river. Specifically, we compared the breakdown of cottonwood (Populus fremontii), willow (Salix exigua), and saltcedar (Tamarix sp.) leaf litter in 2022 to a previous experiment from 1998 that occurred under much cooler water temperatures, and had higher water phosphorus concentrations, low numbers of invasive New Zealand mudsnails (Potamopyrgus antipodarum), and unaltered litter chemistry from the herbivory of saltcedar leaf beetles (Diorhabda carinulata). We found that the effects of up to 10°C warmer temperatures on leaf decomposition were mediated by the establishment and management of invasive species and declining water nutrient concentrations arising from upstream reservoir lowering. Such interactions led to accelerated breakdown of saltcedar, but relatively minor effects of warming on the rate of cottonwood and willow decomposition. Additionally, our results demonstrate the potential for favorable invasive species management outcomes in the terrestrial environment to produce unintended responses in adjacent freshwater ecosystems. As temperatures continue to rise, it is critical that future studies consider how warming interacts with multiple stressors and environmental factors to influence processes such as decomposition in freshwater ecosystems.
Two earthquake sequences occurred a year apart at the Mendocino Triple Junction in northern California: first the 20 December 2021 �w 6.1 and 6.0 Petrolia sequence, then the 20 December 2022 �w 6.4 Ferndale sequence. To delineate active faults and understand the relationship between these sequences, we applied an automated deep‐learning workflow to create enhanced and relocated earthquake catalogs for both the sequences. The enhanced catalog newly identified more than 14,000 M 0–2 earthquakes and also found 852 of 860 already cataloged events. We found that deep‐learning and template‐matching approaches complement each other to improve catalog completeness because deep learning finds more M 0–2 background seismicity, whereas template‐matching finds the smallest M < 0 events near already known events. The enhanced catalog revealed that the 2021 Petrolia and 2022 Ferndale sequences were distinct in space and time, but adjacent in space. Though both the sequences happened in the downgoing Gorda slab, the shallower Ferndale sequence ruptured within the uppermost slab near the subduction interface, while the onshore Petrolia sequence occurred deeper in the mantle. Deep‐learning‐enhanced earthquake catalogs could help monitor evolving earthquake sequences, identify detailed seismogenic fault structures, and understand space–time variations in earthquake rupture and sequence behavior in a complex tectonic setting.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320230053","usgsCitation":"Yoon, C., and Shelly, D.R., 2024, Distinct yet adjacent earthquake sequences near the Mendocino Triple Junction: 20 December 2021 Mw 6.1 and 6.0 Petrolia, and 20 December 2022 Mw 6.4 Ferndale: The Seismic Record, v. 4, no. 1, p. 81-92, https://doi.org/10.1785/0320230053.","productDescription":"12 p.","startPage":"81","endPage":"92","ipdsId":"IP-160618","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":440099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320230053","text":"Publisher Index Page"},{"id":426825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.13993753734817,\n 41.452141149959374\n ],\n [\n -125.13993753734817,\n 39.78442225223091\n ],\n [\n -123.11845316234829,\n 39.78442225223091\n ],\n [\n -123.11845316234829,\n 41.452141149959374\n ],\n [\n -125.13993753734817,\n 41.452141149959374\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Yoon, Clara 0000-0003-4521-3889","orcid":"https://orcid.org/0000-0003-4521-3889","contributorId":222019,"corporation":false,"usgs":true,"family":"Yoon","given":"Clara","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":896979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":896980,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70252931,"text":"70252931 - 2024 - Analysis of mitochondrial DNA sequence data demonstrates that monophyly of myotis occultus is complicated by greater sampling of myotis lucifugus","interactions":[],"lastModifiedDate":"2024-04-11T11:48:04.087404","indexId":"70252931","displayToPublicDate":"2024-03-18T06:45:03","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3451,"text":"Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of mitochondrial DNA sequence data demonstrates that monophyly of myotis occultus is complicated by greater sampling of myotis lucifugus","docAbstract":"The validity of Myotis occultus as a species unique from Myotis lucifugus has been a source of debate. Most recently, many authorities treat M. occultus as a distinct species, at least in part because a previous study showed that M. occultus and M. l. carissima (the subspecies that occurs in closest geographic proximity to M. occultus) form separate monophyletic clades based on sequences of two mitochondrial genes (cytochrome-b [cytb] and cytochrome oxidase subunit II [COII]). We re-evaluated the phylogenetic relationship between M. occultus and M. lucifugus based on mitochondrial sequences using an expanded dataset of cytb and COII sequences that originated from more genetically diverse specimens of M. lucifugus collected across a broader geographic area. Based on a phylogenetic analysis, we found that M. occultus sublineages embedded within a well-supported clade that included some specimens of M. lucifugus. These results indicate that the previous genetic analysis demonstrating that M. occultus and M. lucifugus form distinct monophyletic groups is unsupported by our larger dataset. Future research will likely need to focus on genetic work involving whole-genome sequencing of nuclear DNA to better resolve the true taxonomic relationship between M. occultus and M. lucifugus.
La valides de Myotis occultus como una especie distinta a Myotis lucifugus ha sido fuente de debate. Recientemente, muchas autoridades han considerado M. occultus como una especie diferente, en parte porque un estudio anterior mostró que M. occultus y M. l. carissima (la subespecie con la mayor proximidad geográfica a M. occultus) forman clados monofiléticos separados basados en secuencias de dos genes mitocondriales (el citocromo-b [cytb] y la subunidad II de citocromo oxidasa [COII]). Nosotros hemos reevaluado la relación filogenética entre M. occultus y M. lucifugus usando una ampliada colección de datos que contiene secuencias de los genes mitocondriales cytb y COII de especímenes de M. lucifugus genéticamente más diversos que fueron muestreados en un área geográfica más extensa. Nuestro análisis filogenético muestra que los sublinajes de M. occultus están incrustados dentro de un clado bien respaldado que incluye algunos especímenes de M. lucifugus. Estos resultados indican que el análisis genético anterior que demostró que M. occultus y M. lucifugus forman grupos monofiléticos distintos no está respaldado por nuestra más amplia colección de datos. Es probable que para resolver mejor la verdadera relación taxonómica entre M. occultus y M. lucifugus sea necesario el uso de secuenciación del genoma completo del ADN nuclear.
Predator species can indirectly affect prey species through the cost of anti-predator behavior responses, which may involve shifts in occupancy, space use, or movement. Quantifying the various strategies implemented by prey species to avoid adverse interactions with predators can lead to a better understanding of potential population-level repercussions. Therefore, the purpose of this study was to examine predator–prey interactions by quantifying the effect of predator species presence on detection rates of prey species, using coyotes (Canis latrans) and white-tailed deer (Odocoileus virginianus) in Central Appalachian forests of the eastern United States as a model predator–prey system. To test two competing hypotheses related to interspecific interactions, we modeled species detections from 319 camera traps with a two-species occupancy model that incorporated a continuous-time detection process. We found that white-tailed deer occupancy was independent of coyote occupancy, but white-tailed deer were more frequently detectable and had greater detection intensity at sites where coyotes were present, regardless of vegetation-related covariates. In addition, white-tailed deer detection rates at sites with coyotes were highest when presumed forage availability was relatively low. These findings suggest that white-tailed deer may be exhibiting an active avoidance behavioral response to predators by increasing movement rates when coyotes are present in an area, perhaps due to reactive evasive maneuvers and/or proactive attempts to reduce adverse encounters with them. Concurrently, coyotes could be occupying sites with higher white-tailed deer densities. Because white-tailed deer did not exhibit significant shifts in daily activity patterns based on coyote occupancy, we further suggest that white-tailed deer in our study system generally do not use temporal partitioning as their primary strategy for avoiding encounters with coyotes. Overall, our study implements a recently developed analytical approach for modeling multi-species occupancy from camera traps and provides novel ecological insight into the complex relationships between predator and prey species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.11149","usgsCitation":"Clipp, H.L., Pesi, S.M., Miller, M.L., Gigliotti, L., Skelly, B.P., and Rota, C., 2024, White-tailed deer detection rates increase when coyotes are present: Ecology and Evolution, v. 14, no. 3, e11149, 13 pp., https://doi.org/10.1002/ece3.11149.","productDescription":"e11149, 13 pp.","ipdsId":"IP-157302","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":440105,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.11149","text":"Publisher Index Page"},{"id":433571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.4877790212181,\n 39.94978819373756\n ],\n [\n -82.01878727948417,\n 39.01317775882444\n ],\n [\n -82.58830516880357,\n 38.2047845680037\n ],\n [\n -79.5468825034643,\n 37.66652638635898\n ],\n [\n -77.96682473836029,\n 39.5141262945331\n ],\n [\n -76.37907636338417,\n 40.11338027059526\n ],\n [\n -77.28462588707731,\n 41.09189702989761\n ],\n [\n -80.4877790212181,\n 39.94978819373756\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Clipp, Hannah L.","contributorId":342785,"corporation":false,"usgs":false,"family":"Clipp","given":"Hannah","email":"","middleInitial":"L.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pesi, Sarah M.","contributorId":342786,"corporation":false,"usgs":false,"family":"Pesi","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Madison L.","contributorId":342787,"corporation":false,"usgs":false,"family":"Miller","given":"Madison","email":"","middleInitial":"L.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gigliotti, Laura C. 0000-0002-6390-4133","orcid":"https://orcid.org/0000-0002-6390-4133","contributorId":200327,"corporation":false,"usgs":false,"family":"Gigliotti","given":"Laura C.","affiliations":[],"preferred":false,"id":910395,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skelly, Brett P.","contributorId":342789,"corporation":false,"usgs":false,"family":"Skelly","given":"Brett","email":"","middleInitial":"P.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910396,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rota, Christopher T.","contributorId":342791,"corporation":false,"usgs":false,"family":"Rota","given":"Christopher T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910397,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70252441,"text":"70252441 - 2024 - Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models","interactions":[],"lastModifiedDate":"2024-05-07T14:35:47.184916","indexId":"70252441","displayToPublicDate":"2024-03-17T08:31:39","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models","docAbstract":"Model development in the Next Generation Attenuation-East (NGA-East) project included two components developed concurrently and independently: (1) earthquake ground-motion models (GMMs) that predict the median and aleatory variability of various intensity measures conditioned on magnitude and distance, derived for a reference hard-rock site condition with an average shear-wave velocity in the upper 30 m (VS30) = 3000 m/s; and (2) a site amplification model that modifies intensity measures for softer site conditions. We investigate whether these models, when used in tandem, are compatible with ground-motion recordings in central and eastern North America (CENA) using an expanded version of the NGA-East database that includes new events from November 2011 (end date of NGA-East data curation) to April 2022. Following this expansion, the data set has 187 events, 2096 sites, and 16,272 three-component recordings, although the magnitude range remains limited (∼4 to 5.8). We compute residuals using 17 NGA-East GMMs and three data selection criteria that reflect within-CENA regional variations in ground-motion attributes. Mixed-effects regression of the residuals reveals a persistent pattern in which ground motions are overpredicted at short periods (0.01–0.6 s, including peak ground acceleration (PGA)) and underpredicted at longer periods. These misfits are regionally variable, with the Texas–Oklahoma–Kansas region having larger absolute misfits than other parts of CENA. Two factors potentially influencing these misfits are (1) differences in the site amplification models used to adjust the data to the reference condition during NGA-East GMM development relative to CENA amplification models applied since the 2018 National Seismic Hazard Model (NSHM), and (2) potential bias in simulation-based factors used to adjust ground motions from the hard-rock reference condition to a VS30 = 760 m/s condition. We provide adjustment factors and their epistemic uncertainties and discuss implications for applications.
","language":"English","publisher":"Sage Journals","doi":"10.1177/87552930241231825","usgsCitation":"Ramos-Sepulveda, M.E., Stewart, J.P., Parker, G.A., Moschetti, M.P., Thompson, E.M., Brandenberg, S.J., Hashash, Y.M., and Rathje, E., 2024, Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models: Earthquake Spectra, v. 40, no. 2, p. 1132-1157, https://doi.org/10.1177/87552930241231825.","productDescription":"26 p.","startPage":"1132","endPage":"1157","ipdsId":"IP-153071","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":440108,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/87552930241231825","text":"Publisher Index 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0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":897172,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897174,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandenberg, Scott J.","contributorId":303895,"corporation":false,"usgs":false,"family":"Brandenberg","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":897175,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hashash, Youssef M A","contributorId":146595,"corporation":false,"usgs":false,"family":"Hashash","given":"Youssef","email":"","middleInitial":"M A","affiliations":[{"id":15289,"text":"University of Illinois, Ven Te Chow Hydrosystems Laboratory","active":true,"usgs":false}],"preferred":false,"id":897176,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rathje, Ellen 0000-0002-4169-7153","orcid":"https://orcid.org/0000-0002-4169-7153","contributorId":197024,"corporation":false,"usgs":false,"family":"Rathje","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":897177,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70252201,"text":"70252201 - 2024 - Vulnerability to sea-level rise varies among estuaries and habitat types: Lessons learned from a network of surface elevation tables in Puget Sound","interactions":[],"lastModifiedDate":"2024-08-26T14:32:10.591453","indexId":"70252201","displayToPublicDate":"2024-03-17T06:41:27","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability to sea-level rise varies among estuaries and habitat types: Lessons learned from a network of surface elevation tables in Puget Sound","docAbstract":"Estuarine systems that provide valuable ecosystem services to society and important foraging and rearing habitat for fish and wildlife species continue to undergo degradation. In Puget Sound, WA, as much as 70–80% of historic estuarine habitat has been lost to anthropogenic development, and continued losses are expected through the end of the twenty-first century due to rising sea levels. To evaluate whether Puget Sound’s estuarine habitats will keep pace with current and projected sea-level rise (SLR), we assessed vertical rates of elevation change from a regional network of surface elevation tables and marker horizons (SET-MH). Over the past two decades, SET-MH equipment has been installed throughout a variety of habitats in five Puget Sound estuaries: the Nisqually, Snohomish, Stillaguamish, and Skagit River estuaries, and Padilla Bay. These data provide a unique opportunity to assess elevation change and habitat resilience across a spatiotemporal and environmental gradient. We observed different rates of surface elevation change among estuaries and habitats (Nisqually = 4.64 ± 2.81 mm/year, Snohomish = 5.71 ± 5.83 mm/year, Stillaguamish = 12.82 ± 10.29 mm/year, Skagit = 16.13 ± 7.57 mm/year, Padilla = − 1.25 ± 1.58 mm/year). The highest rates were found at restoring sites with regular sediment input in the Stillaguamish and Skagit estuaries, whereas rates were consistently negative at low elevation sites in sediment starved Padilla Bay. Many sites in Puget Sound appear to be keeping pace with current rates of relative SLR, and some areas are on track to exceed projected rates through the end of the century. These findings indicate that Puget Sound’s estuarine habitats can be resilient to rising tidal levels—as long as sediment delivery is maintained.