Lithology and geologic structure are important controls on landslide susceptibility and are incorporated into many regional landslide hazard models. Typically, metrics for mapped geologic units are used as model input variables and a single set of values for material strength are assumed, regardless of spatial heterogeneities that may exist within a map unit. Here we describe how differences in bedding thickness, grain size, inferred uniaxial compressive strength, and bedding dip control the inherent susceptibility of slopes to deep-seated failure within a single mapped geologic unit - the Tyee Formation of Oregon, USA. The Tyee, which covers over 15,000 km2 and underlies much of the Oregon Coast Range, comprises gently folded alternating beds of sandstone and siltstone deposited as turbidites, forming a 2-km thick Eocene submarine fan which has been uplifted and exhumed through the Cenozoic. Deep-seated landslides are widespread in the Tyee, but form a complex spatial pattern such that landslide density ranges from 0 to 24% of the total landscape area. These slides are often extensive and sufficiently deep to reduce local hillslope gradients, resulting in a strong negative correlation between landslide density and mean local slope. Mean annual precipitation and predicted strong ground motions from Cascadia earthquake scenarios also fail to explain the spatial distribution of deep-seated landslides. Consequently, landslide stability models, which are strongly influenced by landscape slope, pore-water pressure, and seismic acceleration, yield landslide susceptibility maps which are broadly anti-correlated with mapped deep-seated landslide density. Through a multivariable linear regression model, we show that much of the variance in deep-seated landslide density can be explained by variability of intra-unit stratigraphic and structural characteristics, which we measure at 128 sites across two study areas totaling ∼3000 km2. Our results suggest bedding dip is only weakly correlated to landslide density, but strongly influences landslide failure style. Subtle increases in bedding dip, even in the gently folded Tyee Formation, result in a substantially higher likelihood of a landslide being cataclinal, or parallel to bedding. Overall, we find a slight majority of landslides fail within these cataclinal slopes, and that these landslides tend to be larger than non-cataclinal landslides. We also show that the lithological and structural properties that influence landslide susceptibility are distinct for these two populations of landslides. Our results demonstrate how localized, intra-unit, geologic variability can exert strong control on landslide susceptibility and failure style. This suggests that in some locations, landslide hazard models could be significantly improved by incorporating detailed, spatially variable, geologic properties rather than relying solely on generalized geologic map units.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.enggeo.2023.107387","usgsCitation":"LaHusen, S.R., and Grant, A.R., 2024, Complex landslide patterns explained by local intra-unit variability of stratigraphy and structure: Case study in the Tyee Formation, Oregon, USA: Engineering Geology, v. 329, 107387, 14 p., https://doi.org/10.1016/j.enggeo.2023.107387.","productDescription":"107387, 14 p.","ipdsId":"IP-146959","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":440788,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.enggeo.2023.107387","text":"Publisher Index Page"},{"id":426489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Tyee Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.10474453625554,\n 42.47204971687748\n ],\n [\n -121.72095547375605,\n 42.47204971687748\n ],\n [\n -121.72095547375605,\n 45.35210028381104\n ],\n [\n -125.10474453625554,\n 45.35210028381104\n ],\n [\n -125.10474453625554,\n 42.47204971687748\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"329","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"LaHusen, Sean Richard 0000-0003-4246-4439","orcid":"https://orcid.org/0000-0003-4246-4439","contributorId":294677,"corporation":false,"usgs":true,"family":"LaHusen","given":"Sean","email":"","middleInitial":"Richard","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":896262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":896263,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70274033,"text":"70274033 - 2024 - Integrating the human dimensions into fish and wildlife management depends on increasing managers’ social science fluency","interactions":[],"lastModifiedDate":"2026-02-23T17:50:15.823548","indexId":"70274033","displayToPublicDate":"2024-01-06T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1909,"text":"Human Dimensions of Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"Integrating the human dimensions into fish and wildlife management depends on increasing managers’ social science fluency","docAbstract":"It is a common experience in human dimensions to hear people say, “wildlife management is people management.” Good people management requires the full integration of the human dimensions into natural resources work. This means going beyond conducting human dimensions research to understanding and applying lessons learned from social science. A key step here is building managers’ fluency in social science concepts so they can more easily relate existing literature to their own practical questions. I use three example issues from human-wildlife conflict – calibrating trust, managing anger, and fostering autonomy – to illustrate how increased fluency in psychology could inform conflict management in the context of larger sociopolitical discourses. I conclude with ideas for how organizations and scientists could help managers build this integrative capacity in order to better achieve a shared objective of a wildlife management profession that works well with people for the good of humans and wildlife.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10871209.2024.2301965","usgsCitation":"Jones, M.S., 2024, Integrating the human dimensions into fish and wildlife management depends on increasing managers’ social science fluency: Human Dimensions of Wildlife, v. 30, no. 4, p. 442-449, https://doi.org/10.1080/10871209.2024.2301965.","productDescription":"8 p.","startPage":"442","endPage":"449","ipdsId":"IP-149593","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500595,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/10871209.2024.2301965","text":"Publisher Index Page"},{"id":500435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Megan Siobhan 0000-0002-4284-3650","orcid":"https://orcid.org/0000-0002-4284-3650","contributorId":294651,"corporation":false,"usgs":true,"family":"Jones","given":"Megan","email":"","middleInitial":"Siobhan","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956227,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70250949,"text":"70250949 - 2024 - Environmental and geographical factors influence the occurrence and abundance of the southern house mosquito, Culex quinquefasciatus, in Hawai‘i","interactions":[],"lastModifiedDate":"2024-01-13T15:15:09.210779","indexId":"70250949","displayToPublicDate":"2024-01-05T09:11:23","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":"Environmental and geographical factors influence the occurrence and abundance of the southern house mosquito, Culex quinquefasciatus, in Hawai‘i","docAbstract":"Hawaiian honeycreepers, a group of endemic Hawaiian forest birds, are being threatened by avian malaria, a non-native disease that is driving honeycreepers populations to extinction. Avian malaria is caused by the parasite Plasmodium relictum, which is transmitted by the invasive mosquito Culex quinquefasciatus. Environmental and geographical factors play an important role in shaping mosquito-borne disease transmission dynamics through their influence on the distribution and abundance of mosquitoes. We assessed the effects of environmental (temperature, precipitation), geographic (site, elevation, distance to anthropogenic features), and trap type (CDC light trap, CDC gravid trap) factors on mosquito occurrence and abundance. Occurrence was analyzed using classification and regression tree models (CART) and generalized linear models (GLM); abundance (count data) was analyzed using generalized linear mixed models (GLMMs). Models predicted highest mosquito occurrence at mid-elevation sites and between July and November. Occurrence increased with temperature and precipitation up to 580 mm. For abundance, the best model was a zero-inflated negative-binomial model that indicated higher abundance of mosquitoes at mid-elevation sites and peak abundance between August and October. Estimation of occurrence and abundance as well as understanding the factors that influence them are key for mosquito control, which may reduce the risk of forest bird extinction.
Bird populations are declining globally. Wind and solar energy can reduce emissions of fossil fuels that drive anthropogenic climate change, yet renewable-energy production represents a potential threat to bird species. Surveys to assess potential effects at renewable-energy facilities are exclusively local, and the geographic extent encompassed by birds killed at these facilities is largely unknown, which creates challenges for minimizing and mitigating the population-level and cumulative effects of these fatalities. We performed geospatial analyses of stable hydrogen isotope data obtained from feathers of 871 individuals of 24 bird species found dead at solar- and wind-energy facilities in California (USA). Most species had individuals with a mix of origins, ranging from 23% to 98% nonlocal. Mean minimum distances to areas of likely origin for nonlocal individuals were as close as 97 to >1250 km, and these minimum distances were larger for species found at solar-energy facilities in deserts than at wind-energy facilities in grasslands (Cohen's d = 6.5). Fatalities were drawn from an estimated 30–100% of species’ desingated ranges, and this percentage was significantly smaller for species with large ranges found at wind facilities (Pearson's r = −0.67). Temporal patterns in the geographic origin of fatalities suggested that migratory movements and nonmigratory movements, such as dispersal and nomadism, influence exposure to fatality risk for these birds. Our results illustrate the power of using stable isotope data to assess the geographic extent of renewable-energy fatalities on birds. As the buildout of renewable-energy facilities continues, accurate assessment of the geographic footprint of wildlife fatalities can be used to inform compensatory mitigation for their population-level and cumulative effects.
In October 2020, a new population of invasive brown treesnakes (Boiga irregularis) was discovered on the 33-ha Cocos Island, 2.5 km off the south coast of Guam. Cocos Island is a unique conservation resource, providing refuge for many lizards and birds, including endangered species, which were extirpated from mainland Guam by invasive predators including brown treesnakes. We sought to evaluate the usefulness of toxic baiting with acetaminophen-treated carrion baits and cage trapping, common tools for the control of brown treesnakes on mainland Guam, as potential eradication tools on Cocos Island. We evaluated multiple bait types and bait presentations: on the ground, suspended in the canopy emulating aerial bait applications and in four plastic-tube bait station configurations intended to exclude non-target species. We monitored all baits with time-lapse cameras. Despite improved exclusion of non-targets by bait station design, most baits were quickly removed by non-target species, particularly coconut crabs (Birgus latro) and Mariana monitors (Varanus tsukamotoi). Monitoring of 1,250 baits available for 2,427 bait nights resulted in no observations of brown treesnakes taking any bait. Subsequently, we tested two trap types commonly used on Guam and compared trapping success with live versus dead mouse lures. In 10,553 trap nights using live and dead mouse lures, we only captured one brown treesnake, in a trap with a live mouse lure. These baiting and trapping rates are so low as to be ineffectual for all practical purposes. Concurrent visual searching and hand capture of brown treesnakes during initial rapid response efforts demonstrates that these low baiting and trapping success rates are not a result of low snake density. We make a case for our assumption that the ineffectiveness of these tools on Cocos Island is due to the context of extremely high abundance of preferred live prey, primarily large geckos and birds. Our results have profound conservation ramifications, because any future island invasions by brown treesnakes are likely to occur within similarly prey-rich environments where these baiting and trapping methods might be similarly ineffective.
","language":"English","publisher":"Pensoft","doi":"10.3897/neobiota.90.103041","usgsCitation":"Siers, S.R., Nafus, M., Calaor, J.E., Volsteadt, R.M., Grassi, M.S., Volsteadt, M., Collins, A.F., Barnhart, P., Huse, L.T., Yackel Adams, A.A., and Vice, D.L., 2024, Limitations of invasive snake control tools in the context of a new invasion on an island with abundant prey: NeoBiota, v. 90, p. 1-33, https://doi.org/10.3897/neobiota.90.103041.","productDescription":"33 p.","startPage":"1","endPage":"33","ipdsId":"IP-143261","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":440793,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.90.103041","text":"Publisher Index Page"},{"id":435065,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MT1JNO","text":"USGS data release","linkHelpText":"Cocos Island, Guam Brown Treesnake Rapid Response Visual Survey and Capture Data, 10/2020 - 05/2023"},{"id":426051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Cocos Island, Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.65710932315943,\n 13.243675349902261\n ],\n [\n 144.64497735020223,\n 13.236713036998665\n ],\n [\n 144.64352875641617,\n 13.232747079534391\n ],\n [\n 144.66100241895901,\n 13.23988576858983\n ],\n [\n 144.65710932315943,\n 13.243675349902261\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"90","noUsgsAuthors":false,"publicationDate":"2024-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Siers, Shane R.","contributorId":152305,"corporation":false,"usgs":false,"family":"Siers","given":"Shane","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":895542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nafus, Melia Gail 0000-0002-7325-3055","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":245717,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia Gail","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":895543,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calaor, Jaried E.","contributorId":334395,"corporation":false,"usgs":false,"family":"Calaor","given":"Jaried","email":"","middleInitial":"E.","affiliations":[{"id":54632,"text":"Research Corporation of the University of Guam","active":true,"usgs":false}],"preferred":false,"id":895544,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Volsteadt, Rachel M.","contributorId":257490,"corporation":false,"usgs":false,"family":"Volsteadt","given":"Rachel","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":895545,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grassi, Matthew S.","contributorId":334396,"corporation":false,"usgs":false,"family":"Grassi","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":54632,"text":"Research Corporation of the University of Guam","active":true,"usgs":false}],"preferred":false,"id":895546,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Volsteadt, Megan","contributorId":334397,"corporation":false,"usgs":false,"family":"Volsteadt","given":"Megan","email":"","affiliations":[{"id":80127,"text":"Guam Department of Agriculture, Division of Aquatic and Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":895547,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Collins, Aaron F.","contributorId":334398,"corporation":false,"usgs":false,"family":"Collins","given":"Aaron","email":"","middleInitial":"F.","affiliations":[{"id":65960,"text":"USDA Wildlife Services","active":true,"usgs":false}],"preferred":false,"id":895548,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barnhart, Patrick D","contributorId":334399,"corporation":false,"usgs":false,"family":"Barnhart","given":"Patrick D","affiliations":[{"id":65960,"text":"USDA Wildlife Services","active":true,"usgs":false}],"preferred":false,"id":895549,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huse, Logan Tanner 0000-0002-8237-1248","orcid":"https://orcid.org/0000-0002-8237-1248","contributorId":334400,"corporation":false,"usgs":true,"family":"Huse","given":"Logan","email":"","middleInitial":"Tanner","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":895550,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":895551,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Vice, Diane L.","contributorId":334401,"corporation":false,"usgs":false,"family":"Vice","given":"Diane","email":"","middleInitial":"L.","affiliations":[{"id":80127,"text":"Guam Department of Agriculture, Division of Aquatic and Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":895552,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70251132,"text":"70251132 - 2024 - Heterogeneous multi-stage accretionary orogenesis — Evidence from the Gunnison block in the Yavapai Province, southwest USA","interactions":[],"lastModifiedDate":"2024-01-24T13:12:49.893969","indexId":"70251132","displayToPublicDate":"2024-01-05T07:09:56","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"Heterogeneous multi-stage accretionary orogenesis — Evidence from the Gunnison block in the Yavapai Province, southwest USA","docAbstract":"Proterozoic rocks exposed in the southwestern U.S.A. represent one of the best examples of crustal growth by arc-related magmatism and accretionary orogenesis. Within the Southwest the 1.8–1.7 Ga Yavapai Province is widely regarded as a classic example of juvenile arc crust, however 1.8–2.5 Ga inherited zircon and Nd and Hf model ages have been recognized near Gunnison in central Colorado. These data have led to questions regarding the extent and nature of pre-1.8 Ga crustal material and the genesis of the Yavapai Province. We present evidence for a geochemically distinct, spatially restricted crustal block underlain by pre-1.8 Ga crust material (referred to here as the Gunnison block) in central to western Colorado within the Yavapai Province. The Gunnison block is characterized by 1.8–1.9 and 2.4–2.6 Ga inherited zircon, Pb isotopic systematics (μ = 9.8 ± 0.1, κ = 3.7 ± 0.1) elevated relative to 1.8 Ga depleted mantle values, 1.8–2.5 Ga Nd and Hf model ages, and a distinct pressure-temperature-time history. The geochemical data are consistent with mixing between juvenile 1.8 Ga and pre-1.8 Ga sources. The older crustal component is most similar to the isotopically enriched Mojave Province of eastern California and western Arizona, suggesting greater similarities between these provinces than previously recognized. Monazite and xenotime petrochronology indicate ca. 1.75–1.74, 1.72–1.69, 1.67, and 1.47–1.38 Ga tectono-metamorphic events. These data suggest that the Gunnison block accreted to other components of the Yavapai Province outboard of Laurentia at 1.75–1.74 Ga. The composite Yavapai Province was accreted to the margin of Laurentia during the 1.72–1.69 Ga Yavapai orogeny. Later overprinting is associated with the ∼1.68–1.60 Ga Mazatzal and ∼1.47–1.37 Ga Picuris orogenies. Identification of distinct crustal terranes within the Yavapai Province supports models involving multiple arcs and back-arcs that were progressively assembled prior to their accretion to Laurentia, perhaps akin to the present-day Banda Sea in Indonesia.
Accurate estimation and monitoring of wildlife population trends is foundational to evidence-based conservation. Here, we use hierarchical modelling to estimate population trends for six species of management interest (coyotes; red foxes, white-tailed deer, gray foxes; eastern wild turkey, and bobcats) while accounting for observation error from a long-term camera trap survey conducted across the State of New York. We were able to detect population level trends in occurrence and abundance and produce spatially explicit predictions for all six species using a combination of single-species occupancy models and Royle-Nichols models. Coyote (mean λ = 1.22, 95 % CI = 0.85–1.82) and red fox (mean λ = 1.17, 95 % CI = 0.95–1.46) populations were widely distributed with stable populations across the sampling period from 2014 to 2021. White-tailed deer populations were highly abundant and displayed an increasing population trend (mean λ = 1.85, 95 % CI = 1.54–2.10). Eastern wild turkey occupancy remained low across the state despite displaying a slight increase in occupancy over the sampling period (mean ψ = 0.16, 95 % CI = 0.07–0.25). Gray fox occupancy was also low (mean ψ = 0.22, 95 % CI = 0.12–0.29), consistent with growing concerns over the species across North America. Despite recent recoveries elsewhere, bobcat populations in New York State displayed very low occupancy (mean ψ = 0.07, 95 % CI = 0.02–0.12), highlighting the necessity of monitoring to inform conservation action. We provide empirically supported management implications for each species and demonstrate the efficacy of long-term camera trapping to provide robust evidence on population trends while accounting for imperfect detections, over scales meaningful to species management and conservation.
In June 2017, we documented the first observed spawning event by a reintroduced population of Lake Sturgeon (Acipenser fulvescens) in Fall Creek, a tributary to Cayuga Lake, New York, USA. This is the first observed spawning encounter of adult Lake Sturgeon since the beginning of the multi-agency Lake Sturgeon restoration effort in Cayuga Lake initiated in 1995 by the New York State Department of Environmental Conservation. Lake Sturgeon egg deposition was found specifically on substrate mainly composed of gravel sized rocks with depths and flows that made up a unique microhabitat combination within the creek which is not typical of habitat identified in other Lake Sturgeon spawning habitat studies across the Great Lakes. An estimated 810,052 ± 24,386 eggs were deposited in the sampled area of Fall Creek. The identified, potentially productive spawning microhabitat type in Fall Creek is likely to be widespread in similar tributaries around Cayuga Lake as well as small tributaries to other Finger Lakes and Lake Ontario. Ongoing research is focused on the evaluation of the extent of Finger Lakes habitat similar to that identified in Fall Creek. This microhabitat evaluation of sturgeon spawning and the broad scale landscape knowledge of tributary habitats, should support subsequent management to restore Lake Sturgeon.
Paciorek and Wehner raise important questions around our use of the Mann-Kendall nonparametric trend test on smoothed data for analyzing long-term hydrometeorological trends in Zhang et al. (2021, https://doi.org/10.1029/2020gl092293). We thank them for initiating this important conversation and their gracious cooperation in exploring the issues addressed in their comment. In this reply we confirm the inflation of significant p-values by our choice to smooth, illustrate the relatively minor impacts on the main conclusions of our paper, and add our voices to those of Paciorek and Wehner in highlighting the lack of methodology for hypothesis testing across multiple stations that have spatial structure (i.e., testing for regionally consistent trends).
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School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona 85721","active":true,"usgs":false}],"preferred":false,"id":908529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dannenberg, Matthew P.","contributorId":239668,"corporation":false,"usgs":false,"family":"Dannenberg","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":47960,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ; Geographical and Sustainability Services, University of Iowa, Iowa City, IA","active":true,"usgs":false}],"preferred":false,"id":908530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yan, Dong","contributorId":207300,"corporation":false,"usgs":false,"family":"Yan","given":"Dong","email":"","affiliations":[{"id":37515,"text":"University of Arizona School of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":908531,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":908532,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, William K. 0000-0002-5785-6489","orcid":"https://orcid.org/0000-0002-5785-6489","contributorId":239667,"corporation":false,"usgs":false,"family":"Smith","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":47959,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":908533,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70251052,"text":"70251052 - 2024 - Using local monitoring results to inform the Chesapeake Bay Program’s Watershed Model","interactions":[],"lastModifiedDate":"2024-01-19T15:15:53.833192","indexId":"70251052","displayToPublicDate":"2024-01-04T09:15:25","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":17129,"text":"STAC Workshop Report","active":true,"publicationSubtype":{"id":3}},"seriesNumber":"24-002","title":"Using local monitoring results to inform the Chesapeake Bay Program’s Watershed Model","docAbstract":"The Chesapeake Bay Program’s Watershed Model (CBWM) has been used as an accounting tool for the Chesapeake Bay Total Maximum Daily Load (TMDL). However, some of the fundamental parameters that underpin the watershed model may not represent local watershed characteristics at all scales. Significant investments have been made by state and local governments, and other local stakeholders, who are interested in validating loads and progress in implementing measures to achieve the pollutant reductions called for in the TMDL through local monitoring data. For the purposes of this STAC workshop, local monitoring is considered any relevant data collected by a local, regional, state, or federal organization that has not been used previously in the development, calibration, or validation of the CBWM. Some of these local monitoring efforts have been collecting data over the past 5-10 years, with some datasets extending back over more than two decades. However, the data and the CBWM are often not directly comparable due to differences in temporal and spatial scales or because the water quality parameters being monitored are not those estimated by the model. Therefore, a Scientific and Technical Advisory Committee (STAC) workshop was convened to bring together Chesapeake Bay Program (CBP) modelers, local and state government stakeholders, and scientists who are monitoring and analyzing local water quality data to recommend ways in which local monitoring data can be used to inform the CBWM, identify gaps between modeled and monitored data, and validate model predictions at the local scale.\n\nThe workshop, “Using Local Monitoring Results to Inform the Chesapeake Bay Program’s Watershed Model”, was held in March 2023 to provide insight on the scope of local water quality monitoring efforts within and outside of the Bay watershed that could be used to inform the CBWM. Scientists and managers developed recommendations that could be used by modelers for either calibration or knowledge generation to inform the Phase 7 version of the CBWM currently under development for a 2027 decision by the CBP, recommendations for how local monitoring efforts could be designed or altered to better inform the CBWM, and recommendations for how monitored trends could be used in management. The preliminary presentations for the workshop provided essential background information on the CBWM and data used to parameterize it. This information was the foundation for discussions on existing data gaps, the importance of current local monitoring networks, and best practices for developing future monitoring networks. More information on this STAC-funded effort including workshop presentation slides and recordings can be accessed on the workshop webpage. \n\nConfidence in the loading estimates of the CBWM is critical because of its role as the accounting mechanism for measuring progress toward the Bay TMDL’s nutrient and sediment reduction goals. Those who are being asked or required to pay for these reductions, from state and local government managers to farmers, property owners and developers, must have confidence in the scientific validity of the CBWM’s loading estimates or trust in the restoration effort will dissipate. Toward that end, several local entities have invested in extensive urban, suburban, and agricultural monitoring programs to characterize nutrient and sediment loading (among other water quality parameters) at a relatively fine scale (from a few acres to 5 square miles). Monitoring networks outside of the Bay watershed were also included as their relevance and similarities to Bay watershed landscapes, hydrology, and climate conditions can help build the body of knowledge necessary for better parameterization of the CBWM.\nLocal monitoring results could be analyzed for loads and trends for calibration of Phase 7, comparison against trends, informing the structure and parameterization of the model, and potentially in policy evaluation. The effectiveness of management practices at the small watershed scale is a primary question of watershed managers that could be addressed by local monitoring, but to do so study design and statistical techniques may need to be altered if these datasets are intended to inform parameterization of the Bay modeling tools. The partnership would benefit from the redesign of some existing monitoring programs so that they are hypothesis-driven, with fully described inputs, outputs, and practices. New statistical tools could be applied to evaluate the relative importance of various drivers affecting water quality and influenced by hydrogeologic setting and watershed condition.","language":"English","publisher":"Chesapeake Bay Program STAC (Scientific and Technical Advisory Committee)","usgsCitation":"Berger, K., Filippino, K.C., Shenk, G.W., Goulet, N., Lookenbill, M., Moyer, D.L., Noe, G.E., Porter, A.J., Shallenberger, J., Thomas, B., and Yactayo, G., 2024, Using local monitoring results to inform the Chesapeake Bay Program’s Watershed Model: STAC Workshop Report 24-002, 35 p.","productDescription":"35 p.","ipdsId":"IP-160274","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":424622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":424607,"rank":1,"type":{"id":15,"text":"Index 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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":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":892898,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Porter, Aaron J. 0000-0002-0781-3309","orcid":"https://orcid.org/0000-0002-0781-3309","contributorId":239980,"corporation":false,"usgs":true,"family":"Porter","given":"Aaron","email":"","middleInitial":"J.","affiliations":[{"id":37759,"text":"VA/WV Water Science 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Environment","active":true,"usgs":false}],"preferred":false,"id":892902,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70255769,"text":"70255769 - 2024 - Contrasting demographic responses under future climate for two populations of a montane amphibian","interactions":[],"lastModifiedDate":"2024-07-03T12:04:54.242749","indexId":"70255769","displayToPublicDate":"2024-01-04T07:03:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12584,"text":"Climate Change Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Contrasting demographic responses under future climate for two populations of a montane amphibian","docAbstract":"For species with complex life histories, climate change can have contrasting effects for different life stages within locally adapted populations and may result in responses counter to general climate change predictions. Using data from two, 14-year demographic studies for a North American montane amphibian, Cascades frog (Rana cascadae), we quantified how aspects of current climate influenced annual survival of larvae and adult stages and modeled the stochastic population growth rate (λs) of each population for current (1980–2006) and future periods (2080s). Climate drivers of survival for the populations were similar for larvae (i.e., decreases in precipitation lead to pond drying and mortality), but diverged for terrestrial stages where decreases in winter length and summer precipitation had opposite effects. By the 2080s, we predict one population will be in sharp decline (λs = 0.90), while the other population will remain nearly stable (λs = 0.99) in the absence of other stressors, such as mortality due to disease. Our case study demonstrates a result counter to many climate envelope predictions in that stage-specific responses to local climate and hydrology result in a higher extinction risk for the more northern population.
The failure of a 144-m-high lava-dam waterfall on the Río Coca, Ecuador, in February 2020 initiated a catastrophic watershed reset—regressive erosion upstream and a massive sediment pulse downstream—as the river evolves towards a new equilibrium grade. The evolution of this river corridor after a sudden base-level fall embodies the “complex response” concepts long understood through laboratory experiments, numerical modelling and smaller-scale field studies, but that have not been observed in the field before on this scale. This paper presents geomorphic and geotechnical data to characterize the evolution of the Río Coca since 2020. In the three years after the lava-dam failure, the erosion front migrated almost 13 km upstream along the mainstem river and triggered secondary headcuts that began migrating up tributaries. Erosion of the mainstem and tributary valleys generated a sediment pulse estimated to be 277 million m3 and ~500 million tonnes (Mt) over three years, depositing sediment tens of meters thick over tens of kilometres downstream from the former waterfall. This sediment pulse is one of the largest in modern times, comparable to the annual sediment load of a major continent-draining river but with orders-of-magnitude greater sediment yield. Geomorphic adjustment of the Río Coca represents a highly unusual natural disaster threatening life, property, water quality, the regional economy, major infrastructure and energy security. However, this event also provides a rare opportunity to learn how a large autogenic watershed disturbance and recovery evolve, with important lessons for interpreting the sedimentary record of volcanic landscapes.
National parks and other protected areas are important for preserving landscapes and biodiversity worldwide. An essential component of the mission of the United States (U.S.) National Park Service (NPS) requires understanding and maintaining accurate inventories of species on protected lands. We describe a new, national-scale synthesis of amphibian species occurrence in the NPS system. Many park units have a list of amphibian species observed within their borders compiled from various sources and available publicly through the NPSpecies platform. However, many of the observations in NPSpecies remain unverified and the lists are often outdated. We updated the amphibian dataset for each park unit by collating old and new park-level records and had them verified by regional experts. The new dataset contains occurrence records for 292 of the 424 NPS units and includes updated taxonomy, international and state conservation rankings, hyperlinks to a supporting reference for each record, specific notes, and related fields which can be used to better understand and manage amphibian biodiversity within a single park or group of parks.
The eastern migratory population of monarch butterflies (Danaus plexippus) started declining as early as the mid-1970s and seemed to stop declining by the early 2000s; the population now (about 2022) persists at a much-reduced abundance. Stochastic variation in abundance, at levels typical of monarch butterflies and other insects, was assessed to determine whether this population is at heightened risk of quasi-extinction, a level of abundance below which recovery of the migratory behavior is uncertain. Using previously published Bayesian state-space modeling methods it was determined roughly equivalent risk of quasi-extinction as was reported in 2016 for the species (28.7 percent [1.9–81.0 credible interval] and 52.0 percent [3.2–97.7 credible interval] at the 10- and 20-year marks, respectively). Though highly uncertain, the risk is non-negligibly positive. Warning signal analysis indicates the current dynamic is dominated by stochastic variation, which seems to be heightening risk with the passage of time. Increasing breeding opportunities through restoration of milkweed in its northern breeding locations seems to be the most promising means of mitigating extinction risk for this species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231097","usgsCitation":"Thogmartin, W.E., 2024, Non-negligible near-term risk of extinction to the eastern migratory population of monarch butterflies—An updated assessment (2006–22): U.S. Geological Survey Open-File Report 2023–1097, 10 p., https://doi.org/10.3133/ofr20231097.","productDescription":"Report: iii, 10 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-152775","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":423797,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WRARO7","text":"USGS data release","linkHelpText":"Eastern migratory monarch butterfly population estimates and associated early warning signals (2006–22)"},{"id":423796,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1097/images/"},{"id":423798,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231097/full"},{"id":423795,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1097/ofr20231097.XML"},{"id":423794,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1097/ofr20231097.pdf","text":"Report","size":"949 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1097"},{"id":423793,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1097/coverthb.jpg"}],"contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
Slope units are terrain partitions bounded by drainage and divide lines. In landslide modeling, including susceptibility modeling and event-specific modeling of landslide occurrence, slope units provide several advantages over gridded units, such as better capturing terrain geometry, improved incorporation of geospatial landslide-occurrence data in different formats (e.g., point and polygon), and better accommodating the varying data accuracy and precision in landslide inventories. However, the use of slope units in regional (> 100 km2) landslide studies remains limited due, in part, to the large computational costs and/or poor reproducibility with current delineation methods. We introduce a computationally efficient algorithm for the parameter-free delineation of slope units that leverages tools from within TauDEM and GRASS, using an R interface. The algorithm uses geomorphic laws to define the appropriate scaling of the slope units representative of hillslope processes, avoiding the often ambiguous determination of slope unit size. We then demonstrate how slope units enable more robust regional-scale landslide susceptibility and event-specific landslide occurrence maps.
Mangrove is one of the most productive and sensitive ecosystems in the world. Due to the complexity and specificity of mangrove habitat, the development of mangrove is regulated by several factors. Species distribution models (SDMs) are effective tools to identify the potential habitats for establishing and regenerating the ecosystem. Such models usually include exclusively environmental factors. Nevertheless, recent studies have challenged this notion and highlight the importance of including biotic interactions. Both factors are necessary for a mechanistic understanding of the mangrove distribution in order to promote the protection and restoration of mangroves. Thus, we present a novel approach of combining environmental factors and interactions with salt marsh for projecting mangrove distributions at the global level and within latitudinal zones. To test the salt marsh interaction, we fit the MaxEnt model with two predicting sets: (1) environments only and (2) environments + salt marsh interaction index (SII). We found that both sets of models had good predictive ability, although the SII improved model performance slightly. Potential distribution areas of mangrove decrease with latitudes, and are controlled by biotic and abiotic factors. Temperature, precipitation and wind speed are generally critical at both global scale and ecotones along latitudes. SII is important on global scale, with a contribution of 5.9%, ranking 6th, and is particularly critical in the 10–30°S and 20–30°N zone. Interactions with salt marsh, including facilitation and competition, are shown to affect the distribution of mangroves at the zone of coastal ecotone, especially in the latitudinal range from 10° - 30°. The contribution of SII to mangrove distribution increases with latitudes due to the difference in the adaptive capacity of salt marsh plants and mangroves to environments. Totally, this study identified and quantified the effects of salt marsh on mangrove distribution by establishing the SII. The results not only facilitate to establish a more accurate mangrove distribution map, but also improve the efficiency of mangrove restoration by considering the salt marsh interaction in the mangrove management projects. In addition, the method of incorporating biotic interaction into SDMs through establish the biotic interaction index has contributed to the development of SDMs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2023.119892","usgsCitation":"Cui, L., DeAngelis, D., Berger, U., Cao, M., Zhang, Y., Zhang, X., and Jiang, J., 2024, Global potential distribution of mangroves: Taking into account salt marsh interactions along latitudinal gradients: Journal of Environmental Management, v. 351, 119892, 13 p., https://doi.org/10.1016/j.jenvman.2023.119892.","productDescription":"119892, 13 p.","ipdsId":"IP-142484","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":424944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"351","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cui, Lina","contributorId":333612,"corporation":false,"usgs":false,"family":"Cui","given":"Lina","email":"","affiliations":[{"id":79946,"text":"Nanjing Forestry University","active":true,"usgs":false}],"preferred":false,"id":893338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Don 0000-0002-1570-4057","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":221357,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Don","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":893339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berger, Uta","contributorId":224016,"corporation":false,"usgs":false,"family":"Berger","given":"Uta","affiliations":[{"id":40811,"text":"TU Dresden, Institute of Forest Growth and Computer Science, Germany","active":true,"usgs":false}],"preferred":false,"id":893340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cao, Minmin","contributorId":333613,"corporation":false,"usgs":false,"family":"Cao","given":"Minmin","email":"","affiliations":[{"id":79946,"text":"Nanjing Forestry University","active":true,"usgs":false}],"preferred":false,"id":893341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Yaqi","contributorId":333614,"corporation":false,"usgs":false,"family":"Zhang","given":"Yaqi","email":"","affiliations":[{"id":79946,"text":"Nanjing Forestry University","active":true,"usgs":false}],"preferred":false,"id":893342,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhang, Xiaomin","contributorId":333615,"corporation":false,"usgs":false,"family":"Zhang","given":"Xiaomin","email":"","affiliations":[{"id":79948,"text":"Zhejiang Academy of Forestry","active":true,"usgs":false}],"preferred":false,"id":893343,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jiang, Jiang","contributorId":191968,"corporation":false,"usgs":false,"family":"Jiang","given":"Jiang","email":"","affiliations":[],"preferred":false,"id":893344,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70250880,"text":"70250880 - 2024 - Estimating lithium concentrations in groundwater used as drinking water for the conterminous United States","interactions":[],"lastModifiedDate":"2024-01-25T14:57:06.787905","indexId":"70250880","displayToPublicDate":"2024-01-02T10:47:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating lithium concentrations in groundwater used as drinking water for the conterminous United States","docAbstract":"Lithium (Li) concentrations in drinking-water supplies are not regulated in the United States; however, Li is included in the 2022 U.S. Environmental Protection Agency list of unregulated contaminants for monitoring by public water systems. Li is used pharmaceutically to treat bipolar disorder, and studies have linked its occurrence in drinking water to human-health outcomes. An extreme gradient boosting model was developed to estimate geogenic Li in drinking-water supply wells throughout the conterminous United States. The model was trained using Li measurements from ∼13,500 wells and predictor variables related to its natural occurrence in groundwater. The model predicts the probability of Li in four concentration classifications, ≤4 μg/L, >4 to ≤10 μg/L, >10 to ≤30 μg/L, and >30 μg/L. Model predictions were evaluated using wells held out from model training and with new data and have an accuracy of 47–65%. Important predictor variables include average annual precipitation, well depth, and soil geochemistry. Model predictions were mapped at a spatial resolution of 1 km2 and represent well depths associated with public- and private-supply wells. This model was developed by hydrologists and public-health researchers to estimate Li exposure from drinking water and compare to national-scale human-health data for a better understanding of dose–response to low (<30 μg/L) concentrations of Li.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.3c03315","usgsCitation":"Lombard, M.A., Brown, E.E., Saftner, D., Arienzo, M.M., Fuller-Thomson, E., Brown, C., and Ayotte, J.D., 2024, Estimating lithium concentrations in groundwater used as drinking water for the conterminous United States: Environmental Science and Technology, v. 58, no. 2, p. 1255-1264, https://doi.org/10.1021/acs.est.3c03315.","productDescription":"10 p.","startPage":"1255","endPage":"1264","ipdsId":"IP-152446","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":440811,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.3c03315","text":"Publisher Index Page"},{"id":435066,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90DZA9M","text":"USGS data release","linkHelpText":"Data and model archive used to model and map lithium concentrations 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0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Eric E.","contributorId":333096,"corporation":false,"usgs":false,"family":"Brown","given":"Eric","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":891897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saftner, Daniel","contributorId":333090,"corporation":false,"usgs":false,"family":"Saftner","given":"Daniel","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":891898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arienzo, Monica M.","contributorId":333091,"corporation":false,"usgs":false,"family":"Arienzo","given":"Monica","email":"","middleInitial":"M.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":891899,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller-Thomson, Esme","contributorId":333092,"corporation":false,"usgs":false,"family":"Fuller-Thomson","given":"Esme","email":"","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":891900,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Craig J. 0000-0002-3858-3964","orcid":"https://orcid.org/0000-0002-3858-3964","contributorId":210450,"corporation":false,"usgs":true,"family":"Brown","given":"Craig J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891901,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891902,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256598,"text":"70256598 - 2024 - Rapid estimation of single-station earthquake magnitudes with machine learning on a global scale","interactions":[],"lastModifiedDate":"2024-08-01T14:48:54.943118","indexId":"70256598","displayToPublicDate":"2024-01-02T09:45:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Rapid estimation of single-station earthquake magnitudes with machine learning on a global scale","docAbstract":"The foundation of earthquake monitoring is the ability to rapidly detect, locate, and estimate the size of seismic sources. Earthquake magnitudes are particularly difficult to rapidly characterize because magnitude types are only applicable to specific magnitude ranges, and location errors propagate to substantial magnitude errors. We developed a method for rapid estimation of single‐station earthquake magnitudes using raw three‐component P waveforms observed at local to teleseismic distances, independent of prior size or location information. We used the MagNet regression model architecture (Mousavi and Beroza, 2020b), which combines convolutional and recurrent neural networks. We trained our model using ∼2.4 million P‐phase arrivals labeled by the authoritative magnitude assigned by the U.S. Geological Survey. We tested input data parameters (e.g., window length) that could affect the performance of our model in near‐real‐time monitoring applications. At the longest waveform window length of 114 s, our model (Artificial Intelligence Magnitude [AIMag]) is accurate (median estimated magnitude within ±0.5 magnitude units from catalog magnitude) between M 2.3 and 7.6. However, magnitudes above M ∼7 are more underestimated as true magnitude increases. As the windows are shortened down to 1 s, the point at which higher magnitudes begin to be underestimated moves toward lower magnitudes, and the degree of underestimation increases. The over and underestimation of magnitudes for the smallest and largest earthquakes, respectively, are potentially related to the limited number of events in these ranges within the training data, as well as magnitude saturation effects related to not capturing the full source time function of large earthquakes. Importantly, AIMag can determine earthquake magnitudes with individual stations’ waveforms without instrument response correction or knowledge of an earthquake’s source‐station distance. This work may enable monitoring agencies to more rapidly recognize large, potentially tsunamigenic global earthquakes from few stations, allowing for faster event processing and reporting. This is critical for timely warnings for seismic‐related hazards.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230171","usgsCitation":"Dybing, S., Yeck, W.L., Cole, H.M., and Melgar, D., 2024, Rapid estimation of single-station earthquake magnitudes with machine learning on a global scale: Bulletin of the Seismological Society of America, v. 114, no. 3, p. 1523-1538, https://doi.org/10.1785/0120230171.","productDescription":"16 p.","startPage":"1523","endPage":"1538","ipdsId":"IP-158857","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":432030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"114","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Dybing, Sydney","contributorId":341314,"corporation":false,"usgs":false,"family":"Dybing","given":"Sydney","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":908222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":908223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cole, Hank M. 0000-0003-1684-9116","orcid":"https://orcid.org/0000-0003-1684-9116","contributorId":335228,"corporation":false,"usgs":true,"family":"Cole","given":"Hank","email":"","middleInitial":"M.","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":908224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Melgar, Diego","contributorId":341315,"corporation":false,"usgs":false,"family":"Melgar","given":"Diego","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":908225,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250758,"text":"70250758 - 2024 - Note to All Banders - January 2024","interactions":[],"lastModifiedDate":"2024-02-16T15:11:52.550919","indexId":"70250758","displayToPublicDate":"2024-01-02T09:05:09","publicationYear":"2024","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"title":"Note to All Banders - January 2024","docAbstract":"Note to All Banders was a special extra communication with more urgent information relevant to banders. . This note includes holiday greetings and a review of the 2023 successes at the Bird Banding Laboratory. Throughout 2022, the BBL increased communication, engagement, and collaboration, within the Eastern Ecological Science Center, U.S. Geological Survey, and with organization partners and local communities. This Note to All Banders highlights these efforts in more detail.","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Celis-Murillo, A., 2024, Note to All Banders - January 2024, 5 p.","productDescription":"5 p.","ipdsId":"IP-160851","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":425726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":424056,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/media/files/note-banders-january-2024","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Celis-Murillo, Antonio 0000-0002-3371-6529","orcid":"https://orcid.org/0000-0002-3371-6529","contributorId":237851,"corporation":false,"usgs":true,"family":"Celis-Murillo","given":"Antonio","email":"","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":891288,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70256115,"text":"70256115 - 2024 - Mass-balance-consistent geological stock accounting: A new approach toward sustainable management of mineral resources","interactions":[],"lastModifiedDate":"2024-07-23T13:40:07.15414","indexId":"70256115","displayToPublicDate":"2024-01-02T08:33:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Mass-balance-consistent geological stock accounting: A new approach toward sustainable management of mineral resources","docAbstract":"Global resource extraction raises concerns about environmental pressures and the security of mineral supply. Strategies to address these concerns depend on robust information on natural resource endowments, and on suitable methods to monitor and model their changes over time. However, current mineral resources and reserves reporting and accounting workflows are poorly suited for addressing mineral depletion or answering questions about the long-term sustainable supply. Our integrative review finds that the lack of a robust theoretical concept and framework for mass-balance (MB)-consistent geological stock accounting hinders systematic industry-government data integration, resource governance, and strategy development. We evaluate the existing literature on geological stock accounting, identify shortcomings of current monitoring of mine production, and outline a conceptual framework for MB-consistent system integration based on material flow analysis (MFA). Our synthesis shows that recent developments in Earth observation, geoinformation management, and sustainability reporting act as catalysts that make MB-consistent geological stock accounting increasingly feasible. We propose first steps for its implementation and anticipate that our perspective as “resource realists” will facilitate the integration of geological and anthropogenic material systems, help secure future mineral supply, and support the global sustainability transition.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.3c03088","usgsCitation":"Simoni, M.U., Drielsma, J.A., Ericsson, M., Gunn, A.G., Heiberg, S., Heldal, T.A., Nassar, N.T., Petavratz, E., and Muller, D.B., 2024, Mass-balance-consistent geological stock accounting: A new approach toward sustainable management of mineral resources: Environmental Science and Technology, v. 58, p. 971-990, https://doi.org/10.1021/acs.est.3c03088.","productDescription":"20 p.","startPage":"971","endPage":"990","ipdsId":"IP-145992","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":440814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.3c03088","text":"Publisher Index Page"},{"id":431350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","noUsgsAuthors":false,"publicationDate":"2024-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Simoni, Mark U.","contributorId":340251,"corporation":false,"usgs":false,"family":"Simoni","given":"Mark","email":"","middleInitial":"U.","affiliations":[{"id":81520,"text":"Norwegian University of Science and Technology, Norway","active":true,"usgs":false}],"preferred":false,"id":906749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drielsma, Johannes A.","contributorId":340252,"corporation":false,"usgs":false,"family":"Drielsma","given":"Johannes","email":"","middleInitial":"A.","affiliations":[{"id":81521,"text":"Drielsma Resources Europe, Germany","active":true,"usgs":false}],"preferred":false,"id":906750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ericsson, Magnus","contributorId":340253,"corporation":false,"usgs":false,"family":"Ericsson","given":"Magnus","email":"","affiliations":[{"id":81522,"text":"Luleå University of Technology, Sweden","active":true,"usgs":false}],"preferred":false,"id":906751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunn, Andrew G.","contributorId":340254,"corporation":false,"usgs":false,"family":"Gunn","given":"Andrew","email":"","middleInitial":"G.","affiliations":[{"id":25567,"text":"British Geological Survey","active":true,"usgs":false}],"preferred":false,"id":906752,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heiberg, Sigurd","contributorId":340255,"corporation":false,"usgs":false,"family":"Heiberg","given":"Sigurd","email":"","affiliations":[{"id":81523,"text":"Petronavit AS, Norway","active":true,"usgs":false}],"preferred":false,"id":906753,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Heldal, Tom A.","contributorId":340256,"corporation":false,"usgs":false,"family":"Heldal","given":"Tom","email":"","middleInitial":"A.","affiliations":[{"id":35509,"text":"Geological Survey of Norway","active":true,"usgs":false}],"preferred":false,"id":906754,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":906755,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Petavratz, Evi","contributorId":340257,"corporation":false,"usgs":false,"family":"Petavratz","given":"Evi","email":"","affiliations":[{"id":25567,"text":"British Geological Survey","active":true,"usgs":false}],"preferred":false,"id":906756,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Muller, Daniel B.","contributorId":340258,"corporation":false,"usgs":false,"family":"Muller","given":"Daniel","email":"","middleInitial":"B.","affiliations":[{"id":39348,"text":"Norwegian University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":906757,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70251342,"text":"70251342 - 2024 - Identifying conditions where reed canarygrass (Phalaris arundinacea) functions as a driver of forest loss in the Upper Mississippi River floodplain under different hydrological scenarios","interactions":[],"lastModifiedDate":"2024-02-06T13:19:35.568516","indexId":"70251342","displayToPublicDate":"2024-01-02T07:15:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Identifying conditions where reed canarygrass (Phalaris arundinacea) functions as a driver of forest loss in the Upper Mississippi River floodplain under different hydrological scenarios","docAbstract":"Most of the world’s river-floodplain ecosystems are simultaneously undergoing modifications to their hydrological regimes and experiencing species invasions, making it unclear whether invasive species are the main drivers of ecosystem change or simply responding to changes in the hydrological regime.
We simulated patterns of forest recruitment and succession in a 2500-ha portion of the Upper Mississippi River floodplain with and without removal of invasive Phalaris arundinacea and under two different future 100-year hydrological scenarios: a future maintaining the average flooding conditions of the past 40 years (random) and a future that projects an observed upward 40-year trend in flooding conditions forward (trending). By comparing scenarios that included Phalaris removal and ones that did not, we were able to identify the conditions where Phalaris was the main driver of forest loss vs. the conditions where hydrology was the main driver of forest loss. Areas where Phalaris was the main driver of forest loss had mean annual flood inundation durations that were similar to areas that did not lose forest cover (60–90 growing season days), while areas where flooding was the main driver of forest loss had longer mean inundation durations (102–124 growing season days). In comparison to the random hydrology scenario, the trending scenario produced a decrease in the area over which Phalaris was identified as the main driver of forest loss and an increase in the area over which flood inundation was identified as the main driver of forest loss. Thus, if the observed trends in flooding continue, our model projects an increase in the area over which eradicating Phalaris is unlikely to result in the maintenance of forest cover. We used the Resist-Accept-Direct (RAD) framework to discuss potential management options to resist changes and maintain forest cover where Phalaris is likely to be the main driver of forest loss and to accept or direct changes in areas where forest loss is likely driven by hydrological change.
Coastal communities are vulnerable to multihazards, which are exacerbated by land subsidence. On the US east coast, the high density of population and assets amplifies the region's exposure to coastal hazards. We utilized measurements of vertical land motion rates obtained from analysis of radar datasets to evaluate the subsidence-hazard exposure to population, assets, and infrastructure systems/facilities along the US east coast. Here, we show that 2,000 to 74,000 km2 land area, 1.2 to 14 million people, 476,000 to 6.3 million properties, and >50% of infrastructures in major cities such as New York, Baltimore, and Norfolk are exposed to subsidence rates between 1 and 2 mm per year. Additionally, our analysis indicates a notable trend: as subsidence rates increase, the extent of area exposed to these hazards correspondingly decreases. Our analysis has far-reaching implications for community and infrastructure resilience planning, emphasizing the need for a targeted approach in transitioning from reactive to proactive hazard mitigation strategies in the era of climate change.
","language":"English","publisher":"Proceedings of the National Academy of Sciences","doi":"10.1093/pnasnexus/pgad426","usgsCitation":"Ohenhen, L.O., Shirzaei, M., and Barnard, P.L., 2024, Slowly but surely: Exposure of communities and infrastructure to subsidence on the US east coast: PNAS Nexus, v. 3, no. 1, pgad426, 14 p., https://doi.org/10.1093/pnasnexus/pgad426.","productDescription":"pgad426, 14 p.","ipdsId":"IP-144579","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":440818,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/pnasnexus/pgad426","text":"Publisher Index Page"},{"id":424065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.68468831217973,\n 40.41367726741822\n ],\n [\n -69.60900471842967,\n 40.41367726741822\n ],\n [\n -69.60900471842967,\n 42.22869359582157\n ],\n [\n -74.68468831217973,\n 42.22869359582157\n ],\n [\n -74.68468831217973,\n 40.41367726741822\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Ohenhen, Leonard O.","contributorId":290168,"corporation":false,"usgs":false,"family":"Ohenhen","given":"Leonard","email":"","middleInitial":"O.","affiliations":[{"id":62367,"text":"Department of Earth Sciences, University of Delaware, Newark, DE, USA","active":true,"usgs":false}],"preferred":false,"id":891289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shirzaei, Manoochehr 0000-0003-0086-3722","orcid":"https://orcid.org/0000-0003-0086-3722","contributorId":245637,"corporation":false,"usgs":false,"family":"Shirzaei","given":"Manoochehr","email":"","affiliations":[{"id":49242,"text":"Dept. of Geosciences, Virginia Tech Univ.","active":true,"usgs":false}],"preferred":false,"id":891290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":891291,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263337,"text":"70263337 - 2024 - K-12 trade books’ representation of earthquake safety and protective actions: A content analysis","interactions":[],"lastModifiedDate":"2025-02-06T15:37:21.697759","indexId":"70263337","displayToPublicDate":"2024-01-02T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2324,"text":"Journal of Geoscience Education","active":true,"publicationSubtype":{"id":10}},"title":"K-12 trade books’ representation of earthquake safety and protective actions: A content analysis","docAbstract":"Meaningful learning resources for earthquake safety and survival have become an increasingly important topic among geoscientists, especially educators and researchers. Various members of the public, especially K-12 (ages 5–18) learners, continue to depend on scientific trade books available at their local public and school libraries for information about earthquake concepts. To our knowledge, no research has empirically examined how trade books represent earthquake safety and survival actions. In this research, we combine an iterative qualitative inductive and deductive analysis to explore the representation of earthquake safety and protective actions in 50 trade books. We categorize these actions into time-based practices related to preparedness before an earthquake, protective actions during an earthquake, and recovery after an earthquake. These trade books emphasize preparedness by means of building earthquake-resistant structures and urban planning, and efforts toward community resilience and keeping home supplies. The recommended personal protective action during an earthquake in the United States (“Drop, Cover, and Hold On”) is emphasized in the majority of the trade books, as well as other protective actions related to emotional actions and current technological automated actions such as earthquake early warning systems. Finally, the books highlight actions such as damage evaluation and support as ways to recover after an earthquake. Our findings highlight the issues between accepted earthquake safety and survival actions and the limited and/or inaccurate knowledge represented in some trade books. We provide interpretations of how presentation of limited or inaccurate information may increase confusion about appropriate protective actions. The inclusion of accepted and recommended protective actions in future trade books and the use of earthquake drills in public libraries as a supplement for trade book users may improve understanding and implementation of appropriate actions. We further demonstrate the potential of trade book contents in fostering earthquake education through library-community partnerships.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10899995.2023.2294672","usgsCitation":"Nyarko, S., Sumy, D.F., and McBride, S., 2024, K-12 trade books’ representation of earthquake safety and protective actions: A content analysis: Journal of Geoscience Education, v. 73, no. 1, p. 28-45, https://doi.org/10.1080/10899995.2023.2294672.","productDescription":"18 p.","startPage":"28","endPage":"45","ipdsId":"IP-150274","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":490089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/10899995.2023.2294672","text":"Publisher Index Page"},{"id":481743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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States\"}}]}","volume":"73","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Nyarko, Samuel","contributorId":350630,"corporation":false,"usgs":false,"family":"Nyarko","given":"Samuel","affiliations":[{"id":32889,"text":"Indiana University-Purdue University Indianapolis","active":true,"usgs":false}],"preferred":false,"id":926503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sumy, Danielle F.","contributorId":197628,"corporation":false,"usgs":false,"family":"Sumy","given":"Danielle","middleInitial":"F.","affiliations":[],"preferred":false,"id":926504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":926505,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249904,"text":"70249904 - 2024 - Drought prediction and water availability: A report on the 2022 USGS-NIDIS National Listening Session Series","interactions":[],"lastModifiedDate":"2024-04-01T17:30:03.617149","indexId":"70249904","displayToPublicDate":"2024-01-01T12:27:08","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Drought prediction and water availability: A report on the 2022 USGS-NIDIS National Listening Session Series","docAbstract":"The U.S. Geological Survey (USGS) and NOAA’s National Integrated Drought Information System (NIDIS) conducted a series of four Listening Sessions in 2022 – each with a different application or topical focus – to seek input on priorities and needs related to predicting water availability changes under drought conditions at national and regional scales. This input was gathered to help inform the USGS Drought Program, regional and national drought efforts at NIDIS, and other national drought efforts. The series started with a February 2022 kick-off that introduced the series of Listening Sessions being held from March through September 2022. This kickoff also provided an overview of the USGS Drought Program’s work to characterize hydrological (e.g., streamflow and groundwater) drought, drought variability, drivers, and trends over the past century. Participants in these Listening Sessions included diverse stakeholder representation and perspectives.\n\nThe first of the four Listening Sessions focused on streamflow (March 3, 2022), and included a short introduction to the USGS national streamflow drought research, the properties of a national drought prediction system, as well as presentations by other agencies on different drought prediction and forecasting efforts. The second session focused on groundwater (May 5, 2022), and included presentations on groundwater drought, sustainable groundwater management, and improving our understanding of soil moisture, groundwater, and surface water drought. The third session focused on water use (July 14, 2022), and included a discussion of the different drought types, as well as an introduction to several key projects, including the USGS Upper Colorado River Basin Study, the Ogallala Data Directory project, and a multi-agency drought prediction partnership in Oklahoma. The fourth and final Listening Session focused on water availability prediction for ecosystems (September 8, 2022), and included presentations on the development of a national capacity for eco-hydrological and drought science, building climate resilience, and actionable ecodrought resources.","language":"English","publisher":"National Integrated Drought Information System","usgsCitation":"Skumanich, M., Smith, E., Lisonbee, J., and Hammond, J., 2024, Drought prediction and water availability: A report on the 2022 USGS-NIDIS National Listening Session Series, 24 p.","productDescription":"24 p.","ipdsId":"IP-153596","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":427276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":422385,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.drought.gov/documents/drought-prediction-and-water-availability-report-2022-usgs-nidis-national-listening","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Skumanich, Marina","contributorId":260137,"corporation":false,"usgs":false,"family":"Skumanich","given":"Marina","email":"","affiliations":[{"id":52519,"text":"NOAA National Integrated Drought Information System","active":true,"usgs":false}],"preferred":false,"id":897766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Erik 0000-0001-8434-0798","orcid":"https://orcid.org/0000-0001-8434-0798","contributorId":221804,"corporation":false,"usgs":true,"family":"Smith","given":"Erik","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lisonbee, Joel","contributorId":298624,"corporation":false,"usgs":false,"family":"Lisonbee","given":"Joel","email":"","affiliations":[{"id":64629,"text":"NOAA-NIDIS","active":true,"usgs":false}],"preferred":false,"id":897768,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887629,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}