We created a 270-m coupled model of land-use and groundwater conditions, LUCAS-W[ater], for California’s Central Coast. This groundwater-dependent region is undergoing a dramatic reorganization of groundwater management under California’s 2014 Sustainable Groundwater Management Act (SGMA).
Understanding land-use and land-cover change supports long-term sustainable water management. Anthropogenic water demand has depleted groundwater aquifers worldwide, while future water shortages will likely affect land-use change, creating system feedbacks. Our novel participatory approach fused changes in land-use and associated water use from county-scale data to local water agencies’ estimates of total sustainable supply, scaling up local hydro-geologic knowledge from heterogeneous aquifers and diverse management approaches to a regional level. We assessed five stakeholder-driven scenarios with the same historic rates of urban and agricultural land-use change, but different water and land-use management, analyzing how management strategies altered both the spatial pattern of development and subsequent water sustainability from 2001 to 2061.
Transformative strategies using demand-side interventions that coupled water availability to land-use more effectively achieved long-term sustainability than adaptive strategies using supply-side interventions to increase water supplies. Limiting water withdrawals within SGMA regulated basins resulted in leakage of development into unregulated basins, increasing groundwater pumping there. Protecting ecosystems, farmlands, and recharge areas from development reduced leakage into undeveloped basins without negatively affecting water sustainability.
Gas hydrates are found in significant quantities on the North Slope of Alaska in subpermafrost sand units and intermixed in lower portions of permafrost within the hydrate stability window. While conventional surface seismic data and established imaging methods can indicate the presence of gas hydrate reservoirs, producing high-resolution images of (seismically) thin layers remains challenging due to the preferential attenuation of the higher-frequency data components. An alternative strategy is to use distributed acoustic sensing (DAS) involving cementing optical fibers into boreholes to measure seismic wavefield energy closer to the strata of interest using vertical seismic profiling (VSP). DAS VSP imaging takes advantage of the shorter travel paths and reduced attenuation to generate higher-resolution near-well images. We illustrate these benefits on a DAS VSP data set acquired at the Hydrate-01 stratigraphic test well located in the Prudhoe Bay Unit of Alaska where significant gas hydrate deposits have been detected in two subpermafrost sand layers that are intended for long-duration production testing. Our DAS data preprocessing workflow effectively isolates the upgoing compressional-wave (P-wave) reflections required for subsurface acoustic imaging. After applying three-dimensional (3-D) tomography to improve the quality of the 3-D migration velocity model, we use 3-D reverse-time migration (RTM) to develop high-quality images of the two target sands and minor near-well faulting. We validate our RTM images through highly accurate well-ties with previously acquired petrophysical log data. This study demonstrates that combining 3-D RTM imaging with DAS VSP data provides significant value to gas hydrate and similar projects, and it suggests that more advanced inversion approaches such as (elastic) least-squares RTM could recover higher-resolution and more quantitative estimates of subsurface reflectivity, which would be valuable for refining the understanding of gas hydrate systems.
Releases of water from Flaming Gorge Dam together with climate-related variations in runoff determine the streamflow regime of the Green River, which affects the physical characteristics of the channel and riparian ecosystem of the Green River corridor in Canyonlands National Park. The dam has decreased peak streamflows and raised base streamflows, resulting in vegetation encroachment and channel narrowing and simplification, which could be detrimental to endangered fish habitats over time. Operations of Flaming Gorge Dam are in part determined by flow recommendations provided by the Upper Colorado River Basin Endangered Fish Recovery Program that are designed to benefit native fish and disadvantage nonnative fish. These recommendations alone may not be sufficient to prevent channel narrowing and simplification. Increases in base flows may contribute to channel narrowing and simplification by increasing the water available to riparian vegetation and reducing the water volume available for increasing peak-flow magnitude or duration This report describes how proposed revisions to these flow recommendations would affect the physical characteristics of the Green River corridor in Canyonlands National Park, with a focus on riparian vegetation and channel width.
Hydrologic conditions for the Green River downstream from Flaming Gorge Dam are classified by the U.S. Department of the Interior Bureau of Reclamation as dry, moderately dry, average, moderately wet, or wet. The flow recommendations for peak-flow magnitude and duration in wet years are consistent with geomorphic objectives and historical post-dam flows. In moderately wet years, although the recommended peaks may be sufficient to prevent narrowing over the short term, these peaks are lower than historical post-dam peak flows for moderately wet years and could therefore allow reduction in the occasional large peaks necessary to maintain sediment mobility and channel complexity. For average and drier years, the recommendations allow, but do not require, peak-flow magnitude and durations that are likely to achieve geomorphic objectives.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221019","collaboration":"Prepared in cooperation with Canyonlands National Park","usgsCitation":"Grams, P.E., Friedman, J.M., Dean, D.J., and Topping, D.J., 2022, The effects of requested flows for native fish on sediment dynamics, geomorphology, and riparian vegetation for the Green River in Canyonlands National Park, Utah: U.S. Geological Survey Open-File Report 2022–1019, 20 p., https://doi.org/10.3133/ofr20221019.","productDescription":"vi, 20 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-126163","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":501764,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112531.htm","linkFileType":{"id":5,"text":"html"}},{"id":396864,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1019/ofr20221019.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":396863,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1019/covrthb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Green River, Canyonlands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.4730224609375,\n 38.19502155795575\n ],\n [\n -109.64630126953125,\n 38.19502155795575\n ],\n [\n -109.64630126953125,\n 39.1833042481843\n ],\n [\n -110.4730224609375,\n 39.1833042481843\n ],\n [\n -110.4730224609375,\n 38.19502155795575\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"The U.S. Geological Survey (USGS) created a virtual training series for the Afghanistan Ministry of Energy and Water (MEW), now known as the National Water Affairs Regulation Authority (NWARA), to provide critical hydrological training as an alternative to an in-person training. The USGS was scheduled to provide in-person surface-water training for NWARA during 2020; however, travel was halted because of the Coronavirus disease 2019 (COVID–19) pandemic. The virtual training consisted of prerecorded and live presentations that were scheduled during 4 weeks in August 2021. However, the training was halted after the second week due to the collapse of the Afghan Government. Fortunately, the prerecorded presentations and training materials were delivered before the trainings were halted, so they can be viewed or shared by the participants in the future. A benefit to having produced prerecorded trainings is that USGS can leverage or adapt the trainings for nongovernmental organizations (NGOs) involved in humanitarian water relief efforts in Afghanistan or can be used for other international training efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223014","collaboration":"Prepared in cooperation with U.S. Agency for International Development","usgsCitation":"Groten, J.T., Valder, J.F., Densmore, B.K., Neal, L.W., Krahulik, J., and Mack, T.J., 2022, Virtual training prepared for the former Afghanistan Ministry of Energy and Water—Streamgaging, fluvial sediment sampling, bathymetry, and streamflow and sediment modeling: U.S. Geological Survey Fact Sheet 2022–3014, 2 p., https://doi.org/10.3133/fs20223014.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-137256","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":396849,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3014/coverthb.jpg"},{"id":396850,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3014/fs20223014.pdf","text":"Report","size":"545 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3014"},{"id":396851,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3014/fs20223014.XML"},{"id":396854,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3014/images"}],"contact":"Director, Office of International Programs
U.S. Geological Survey
411 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Many grass-dominated ecosystems in dryland regions have experienced increasing woody plant density and abundance during the past century. In many cases, this process has led to land degradation and declines in ecosystem functions. An example is the Chihuahuan Desert in the southwestern United States, which experienced different stages of shrub encroachment in the past 150 years. Among a wide variety of mechanisms to explain the grass–shrub transitions in this dryland system, soil erosion (both wind and water) and fire are particularly well studied. Here, we synthesize recent developments on the drivers and feedback in the process of shrub encroachment in the Chihuahuan Desert through the intercomparison of two Long Term Ecological Research (LTER) sites, namely Jornada and Sevilleta. Experimental and modeling studies support a conceptual framework, which underscores the important roles of erosion and fire in woody plant encroachment. Collectively, research at the Jornada LTER provided complementary, quantitative support to the well-known fertile-islands framework. Studies at the Sevilleta LTER expanded the framework, adding fire as a major disturbance to woody plants. Conceptual models derived from the synthesis represent the general understanding of shrub encroachment that emerged from research at these two sites, and can guide management interventions aimed at reducing or mitigating undesirable ecosystem state change in many other drylands worldwide.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.3949","usgsCitation":"Li, J., Ravi, S., Wang, G., Van Pelt, R.S., Gill, T.E., and Sankey, J., 2022, Woody plant encroachment of grassland and the reversibility of shrub dominance: Erosion, fire, and feedback processes: Ecosphere, v. 13, no. 3, e3949, 13 p., https://doi.org/10.1002/ecs2.3949.","productDescription":"e3949, 13 p.","ipdsId":"IP-124265","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":448558,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecs2.3949","text":"External Repository"},{"id":402103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":844606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Pelt, R. Scott","contributorId":195937,"corporation":false,"usgs":false,"family":"Van Pelt","given":"R.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":844607,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gill, Thomas E.","contributorId":255127,"corporation":false,"usgs":false,"family":"Gill","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":844608,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844609,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262412,"text":"70262412 - 2022 - The cost of avoiding predators: A bioenergetic analysis of diel vertical migration by the opossum shrimp Mysis diluviana","interactions":[],"lastModifiedDate":"2025-01-22T23:07:25.031633","indexId":"70262412","displayToPublicDate":"2022-03-08T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"The cost of avoiding predators: A bioenergetic analysis of diel vertical migration by the opossum shrimp Mysis diluviana","docAbstract":"The freshwater opossum shrimp Mysis diluviana can undergo extensive diel vertical migration (DVM) to feed in shallow, prey rich strata at night. Bright moonlight limits their night-time migration presumably due to predator avoidance. Using a linked, foraging-bioenergetics model, we evaluated the cost of avoiding predators by simulating the effects of prey density, water temperature, and light intensity on daily feeding and growth of M. diluviana in Lake Pend Oreille, Idaho, USA. We found that when mysid distribution was not limited by moonlight intensity, simulated food consumption (10.3 J day−1) increased 1.6-fold compared to estimated consumption (6.1 J day−1) based on their observed, vertical distribution. Moreover, simulated growth of mysids (0.61 mg day−1) increased 74% compared to that estimated from observed distribution patterns (0.35 mg day−1), when they were located in deeper, darker strata. Given recent insights into partial DVM by M. diluviana, we note that proximate factors associated with predator avoidance in pelagic (light availability) and benthic (hunger level, body size and reproductive status) habitats may convey complimentary benefits to M. diluviana fitness by reducing predation mortality and increasing metabolic efficiency.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10750-022-04832-w","usgsCitation":"Chipps, S.R., Bennett, D., Deslauriers, D., and Rudstam, L., 2022, The cost of avoiding predators: A bioenergetic analysis of diel vertical migration by the opossum shrimp Mysis diluviana: Hydrobiologia, v. 849, p. 1871-1884, https://doi.org/10.1007/s10750-022-04832-w.","productDescription":"14 p.","startPage":"1871","endPage":"1884","ipdsId":"IP-127536","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Lake Pend Oreille","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.67324526551994,\n 48.40859279963456\n ],\n [\n -116.67324526551994,\n 47.92834413614517\n ],\n [\n -116.14169467852497,\n 47.92834413614517\n ],\n [\n -116.14169467852497,\n 48.40859279963456\n ],\n [\n -116.67324526551994,\n 48.40859279963456\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"849","noUsgsAuthors":false,"publicationDate":"2022-03-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennett, David H.","contributorId":349207,"corporation":false,"usgs":false,"family":"Bennett","given":"David H.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":924142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deslauriers, David","contributorId":349208,"corporation":false,"usgs":false,"family":"Deslauriers","given":"David","affiliations":[{"id":36676,"text":"Université du Québec à Rimouski","active":true,"usgs":false}],"preferred":false,"id":924143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rudstam, Lars G.","contributorId":349209,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":924144,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230135,"text":"70230135 - 2022 - Multi-scale patterns in occurrence of an ephemeral pool-breeding amphibian","interactions":[],"lastModifiedDate":"2022-03-30T14:15:19.966579","indexId":"70230135","displayToPublicDate":"2022-03-07T08:48:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale patterns in occurrence of an ephemeral pool-breeding amphibian","docAbstract":"Species distributions are governed by processes occurring at multiple spatial scales. For species with complex life cycles, the needs of all life stages must be met within the dispersal limitations of the species. Multi-scale processes can be particularly important for these species, where small-scale patterns in specific habitat components can affect the distribution of one life stage, whereas large-scale patterns in land cover might better explain the distribution of other life stages. Using a conditional multi-scale model, we evaluated which aspects of the landscape and local environment are most strongly related to occupancy patterns of western spadefoots (Spea hammondii). In northern and central California, the proportion of grassland land cover within 2 km of a site was positively related to the occurrence of the northern clade of the western spadefoot. At the pond scale, we found that western spadefoots were more likely to breed in pools with lower pH. Our results indicate that protecting remaining grasslands for adult spadefoots and ensuring multiple pools with diverse characteristics and hydroperiods so at least some pools result in successful breeding will likely be necessary to conserve western spadefoots, especially with a changing climate. Considering the processes that affect species distributions at multiple life stages and spatial scales is an essential component of effective conservation.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3960","usgsCitation":"Halstead, B., Rose, J.P., Clark, D., Kleeman, P.M., and Fisher, R., 2022, Multi-scale patterns in occurrence of an ephemeral pool-breeding amphibian: Ecosphere, v. 13, no. 3, e3960, 14 p., https://doi.org/10.1002/ecs2.3960.","productDescription":"e3960, 14 p.","ipdsId":"IP-127818","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":489146,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3960","text":"Publisher Index Page"},{"id":435933,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E1SP64","text":"USGS data release","linkHelpText":"Western Spadefoot Survey Data in Northern and Central California (2019)"},{"id":397856,"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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.0244140625,\n 33.46810795527896\n ],\n [\n -119.091796875,\n 33.46810795527896\n ],\n [\n -119.091796875,\n 40.48038142908172\n ],\n [\n -125.0244140625,\n 40.48038142908172\n ],\n [\n -125.0244140625,\n 33.46810795527896\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Denise 0000-0002-9688-2946 drclark@usgs.gov","orcid":"https://orcid.org/0000-0002-9688-2946","contributorId":213957,"corporation":false,"usgs":true,"family":"Clark","given":"Denise","email":"drclark@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839226,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229393,"text":"70229393 - 2022 - Deep learning detection and recognition of spot elevations on historic topographic maps","interactions":[],"lastModifiedDate":"2022-03-07T14:39:01.222238","indexId":"70229393","displayToPublicDate":"2022-03-07T08:33:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Deep learning detection and recognition of spot elevations on historic topographic maps","docAbstract":"Some information contained in historical topographic maps has yet to be captured digitally, which limits the ability to automatically query such data. For example, U.S. Geological Survey’s historical topographic map collection (HTMC) displays millions of spot elevations at locations that were carefully chosen to best represent the terrain at the time. Although research has attempted to reproduce these data points, it has proven inadequate to automatically detect and recognize spot elevations in the HTMC. We propose a deep learning workflow pretrained using large benchmark text datasets. To these datasets we add manually crafted training image/label pairs, and test how many are required to improve prediction accuracy. We find that the initial model, pretrained solely with benchmark data, fails to predict any HTMC spot elevations correctly, whereas the addition of just 50 custom image/label pairs increases the predictive ability by ~50%, and the inclusion of 350 data pairs increased performance by ~80%. Data augmentation in the form of rotation, scaling and translation (offset) expanded the size and diversity of the training dataset and vastly improved recognition accuracy up to ~95%. Visualization methods, such as heat map generation and salient feature detection are recommended to better understand why some predictions fail.","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2022.804155","usgsCitation":"Arundel, S., Morgan, T.P., and Thiem, P.T., 2022, Deep learning detection and recognition of spot elevations on historic topographic maps: Frontiers in Environmental Science, v. 10, p. 1-10, https://doi.org/10.3389/fenvs.2022.804155.","productDescription":"804155, 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-129409","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":448574,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2022.804155","text":"Publisher Index Page"},{"id":396784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-02-18","publicationStatus":"PW","contributors":{"editors":[{"text":"Chiang, Yao-Yi","contributorId":288084,"corporation":false,"usgs":false,"family":"Chiang","given":"Yao-Yi","email":"","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":837350,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":837265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan, Trenton P.","contributorId":287989,"corporation":false,"usgs":false,"family":"Morgan","given":"Trenton","email":"","middleInitial":"P.","affiliations":[{"id":61682,"text":"Rolla, MO","active":true,"usgs":false}],"preferred":false,"id":837341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thiem, Philip T. 0000-0002-3324-2589","orcid":"https://orcid.org/0000-0002-3324-2589","contributorId":287990,"corporation":false,"usgs":true,"family":"Thiem","given":"Philip","email":"","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":837342,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230446,"text":"70230446 - 2022 - Warming in the upper San Francisco Estuary: Patterns of water temperature change from five decades of data","interactions":[],"lastModifiedDate":"2022-06-01T15:16:59.494274","indexId":"70230446","displayToPublicDate":"2022-03-07T06:34:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Warming in the upper San Francisco Estuary: Patterns of water temperature change from five decades of data","docAbstract":"Temperature is a key controlling variable from subcellular to ecosystem scales. Thus, climatic warming is expected to have broad impacts, especially in economically and ecologically valuable systems such as estuaries. The heavily managed upper San Francisco Estuary supplies water to millions of people and is home to fish species of high conservation, commercial, and recreational interest. Despite a long monitoring record (> 50 yr), we do not yet know how water temperatures have already changed or how trends vary spatially or seasonally. We fit generalized additive models on an integrated database of discrete water temperature observations to estimate long-term trends with spatio-seasonal variability. We found that water temperatures have increased 0.017°C yr−1 on average over the past 50 yr. Rates of temperature change have varied over time, but warming was predominant. Temperature increases were most widespread in the late-fall to winter (November to February) and mid-spring (April to June), coinciding with the winter development of juvenile Chinook salmon and spring spawning window of the endangered delta smelt. Warming was fastest in the northern regions, a key fish migration corridor with important tidal wetland habitat. However, no long-term temperature trends were detected in October and were only observed in some regions in May, July, and August. These results can help identify optimal areas for restoration or refugia to buffer the effects of a warming climate, and the methods can be leveraged to understand the spatiotemporal variability in climate warming patterns in other aquatic systems.
The moment magnitude (
Annual bank erosion was measured at multiple cross sections along the free-flowing meandering Powder River in the western United States from 1979 through 2019. Bank erosion was separated into two components—above water and underwater erosion. Above water erosion was measured as the annual bank retreat rate (0–15.4 m y−1). Underwater erosion rate (0–47 m3 m−1 y−1) was calculated as the volume eroded below the water level corresponding to the dominant annual peak discharge, Qp. This paper focuses primarily on the underwater erosion. A total of 491 annual erosion rates were calculated for 23 bank sites along a 90-km study reach in southeastern Montana. Sites were not just hotspots for bank erosion but represent the spectra of variables such as the radius of curvature divided by channel width, R/w (2–86), the peak discharge, Qp (22.7–314 m3 s−1), and the bank orientation (0–360°).
Local annual bank erosion was extremely variable in time and space. It was episodic and unsynchronized along the study reach with the maximum annual bank erosion occurring in different years at different bank sites. The composite probability distribution of all 491 annual bank erosion rates was best modeled by a zero-adjusted Weibull distribution. Individual probability distributions for each of the 23 sites were all different from each other and from the composite distribution highlighting the extreme variability. The correlation of the annual underwater erosion with channel geometry and bank variables was low (R2 < 0.31) but the correlation was higher for peak discharge with 25% of the sites having R2 > 0.50.
Time-averaging reduced the variability at each site and when grouped into five peak-discharge classes each class was correlated with R/w as a power law with an exponent of about −1. Reach-averaging also reduced the variability for each year, and when grouped by bank orientation (north-, east-, south-, and west-facing), bank erosion was linearly related to Qp with south- and west-facing orientations having about twice as much erosion per unit discharge (0.030 m3 m−1 y−1/m3 s−1) than north- and east-facing orientations.
Bank erosion was found to be not just a multi-variate complex process with little correlation and high variability that suggests randomness, but also a process that was a function of a different combinations of variables at different sites at the same time. However, this high variability was reduced by time- and reach-averaging, which produced predictable results analogous to the central limit theorem.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2022.108134","usgsCitation":"Moody, J.A., 2022, The effects of discharge and bank orientation on the annual riverbank erosion along Powder River in Montana, USA: Geomorphology, v. 403, 108134, 17 p., https://doi.org/10.1016/j.geomorph.2022.108134.","productDescription":"108134, 17 p.","ipdsId":"IP-128404","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":409321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Powder River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.1060780230682,\n 44.99730993309305\n ],\n [\n -105.34780716843096,\n 44.99730993309305\n ],\n [\n -105.34780716843096,\n 45.476708847648894\n ],\n [\n -106.1060780230682,\n 45.476708847648894\n ],\n [\n -106.1060780230682,\n 44.99730993309305\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"403","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":856974,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70247365,"text":"70247365 - 2022 - Electrical properties and anisotropy of schists and fault rocks from New Zealand’s Southern Alps under confining pressure","interactions":[],"lastModifiedDate":"2023-07-31T11:09:59.450954","indexId":"70247365","displayToPublicDate":"2022-03-04T14:47:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1816,"text":"Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Electrical properties and anisotropy of schists and fault rocks from New Zealand’s Southern Alps under confining pressure","docAbstract":"Magnetotelluric models spanning the Pacific–Australian Plate boundary in New Zealand’s South Island indicate a localized zone of low electrical resistivity that is spatially coincident with theductile mid-crustal part of the Alpine Fault Zone (AFZ). We explored the source of this anomaly bymeasuring the electrical properties of samples collected from surface outcrops approaching the AFZthat have accommodated a gradient of systematic strain and deformation conditions. We investigatedthe effects of tectonite fabric, fluid saturated pore/fracture networks and surface conductivity on the bulk electrical response and the anisotropy of resistivity measured under increasing confining pressures up to 200 MPa. We find that porosity and resistivity increase while porosity and the change in anisotropy of resistivity with confining pressure (δ (ρk/ρ⊥)/δ (peff)) decreases approaching theAFZ, indicating the electrical response is controlled by pore fluid conductivity and modified during progressive metamorphism. Conversely, Alpine mylonites exhibit relatively low resistivities at low porosities, and lower δ (ρk/ρ⊥)/δ (peff) than the schists. These findings indicate a transition in both the porosity distribution and electrical charge transport processes in rocks that have experienced progressive grain size reduction and mixing of phases during development of mylonitic fabrics due to creep shear strain within the AFZ.
","language":"English","publisher":"MDPI","doi":"10.3390/geosciences12030121","usgsCitation":"Kluge, K.E., Toy, V.G., and Lockner, D., 2022, Electrical properties and anisotropy of schists and fault rocks from New Zealand’s Southern Alps under confining pressure: Geosciences, v. 12, 121, 19 p., https://doi.org/10.3390/geosciences12030121.","productDescription":"121, 19 p.","ipdsId":"IP-132712","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":448588,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences12030121","text":"Publisher Index Page"},{"id":435938,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91A6OMH","text":"USGS data release","linkHelpText":"Data from the manuscript: Electrical properties and anisotropy of schists and fault rocks from New Zealand’s Southern Alps under confining pressure"},{"id":419434,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Southern Alps","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[173.02037,-40.91905],[173.24723,-41.332],[173.95841,-40.9267],[174.24759,-41.34916],[174.24852,-41.77001],[173.87645,-42.23318],[173.22274,-42.97004],[172.71125,-43.37229],[173.08011,-43.85334],[172.30858,-43.86569],[171.45293,-44.24252],[171.18514,-44.8971],[170.6167,-45.90893],[169.83142,-46.35577],[169.33233,-46.64124],[168.41135,-46.61994],[167.76374,-46.2902],[166.67689,-46.21992],[166.50914,-45.8527],[167.04642,-45.11094],[168.30376,-44.12397],[168.94941,-43.93582],[169.66781,-43.55533],[170.52492,-43.03169],[171.12509,-42.51275],[171.56971,-41.76742],[171.94871,-41.51442],[172.09723,-40.9561],[172.79858,-40.49396],[173.02037,-40.91905]]],[[[174.61201,-36.1564],[175.33662,-37.2091],[175.3576,-36.52619],[175.80889,-36.79894],[175.95849,-37.55538],[176.7632,-37.88125],[177.43881,-37.96125],[178.01035,-37.57982],[178.51709,-37.69537],[178.27473,-38.58281],[177.97046,-39.16634],[177.20699,-39.14578],[176.93998,-39.44974],[177.03295,-39.87994],[176.88582,-40.06598],[176.50802,-40.60481],[176.01244,-41.28962],[175.23957,-41.68831],[175.0679,-41.42589],[174.65097,-41.28182],[175.22763,-40.45924],[174.90016,-39.90893],[173.82405,-39.50885],[173.85226,-39.1466],[174.5748,-38.79768],[174.74347,-38.02781],[174.69702,-37.38113],[174.29203,-36.71109],[174.319,-36.53482],[173.841,-36.12198],[173.05417,-35.23713],[172.63601,-34.52911],[173.00704,-34.45066],[173.5513,-35.00618],[174.32939,-35.2655],[174.61201,-36.1564]]]]},\"properties\":{\"name\":\"New Zealand\"}}]}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Kluge, Katherine E","contributorId":317793,"corporation":false,"usgs":false,"family":"Kluge","given":"Katherine","email":"","middleInitial":"E","affiliations":[{"id":69160,"text":"Univ. of Otago, New Zealand","active":true,"usgs":false}],"preferred":false,"id":879333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toy, Virginia G.","contributorId":195078,"corporation":false,"usgs":false,"family":"Toy","given":"Virginia","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":879334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lockner, David A. 0000-0001-8630-6833","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":261920,"corporation":false,"usgs":true,"family":"Lockner","given":"David A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879332,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229369,"text":"70229369 - 2022 - Leveraging rangeland monitoring data for wildlife: From concept to practice","interactions":[],"lastModifiedDate":"2022-03-04T15:45:24.688257","indexId":"70229369","displayToPublicDate":"2022-03-04T09:31:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3230,"text":"Rangelands","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging rangeland monitoring data for wildlife: From concept to practice","docAbstract":"Available rangeland data, from field-measured plots to remotely sensed landscapes, provide much needed information for mapping and modeling wildlife habitats.
Better integration of wildlife habitat characteristics into rangeland monitoring schemes is needed for most rangeland wildlife species at varying spatial and temporal scales.
Here, we aim to stimulate use of and inspire ideas about rangeland monitoring data in the context of wildlife habitat modeling and species conservation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rala.2021.09.005","usgsCitation":"Pilliod, D., Beck, J.L., Duchardt, C.J., Rachlow, J.L., and Veblen, K.E., 2022, Leveraging rangeland monitoring data for wildlife: From concept to practice: Rangelands, v. 44, no. 1, p. 87-98, https://doi.org/10.1016/j.rala.2021.09.005.","productDescription":"12 p.","startPage":"87","endPage":"98","ipdsId":"IP-125490","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448591,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rala.2021.09.005","text":"Publisher Index Page"},{"id":396752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, Montana, Nebraska, New Mexico, North Dakota, Oklahoma, South Dakota, Texas, Utah, Wyoming","otherGeospatial":"Great 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USA","interactions":[],"lastModifiedDate":"2022-03-04T15:17:53.244939","indexId":"70229387","displayToPublicDate":"2022-03-04T09:06:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Power analysis for detecting the effects of best management practices on reducing nitrogen and phosphorus fluxes to the Chesapeake Bay watershed, USA","docAbstract":"In 2010 the U.S. Environmental Protection Agency established the Total Maximum Daily Load (TMDL) which is a “pollution diet” that aims to reduce the amount of nitrogen and phosphorus entering the Chesapeake Bay, the largest estuary in the United States, by 25 and 24% percent, respectively. To achieve this goal the TMDL requires the implementation of Best Management Practices (BMPs), which are accepted land management practices for reducing pollutant runoff to nearby bodies of water. While the TMDL requires that the necessary management actions be in place by 2025 to eventually reach targeted nutrient loads, the ability to detect an effect of BMPs while assuming that one has occurred (i.e. statistical power) is still not well understood. The goal of this study was to investigate the power and required timelines to detect nutrient reductions in streams and rivers as the result of BMP implementation at the Chesapeake Watershed scale. Power estimates were produced using SPAtially Referenced Regression On Watershed attributes (SPARROW) models, which offer a flexible statistical framework and were recently extended to allow for modeling multiple time steps. Nitrogen and phosphorus focused models were calibrated to estimate the power to detect reductions in flux from numerous constituent sources. To confidently detect a decrease in constituent flux reaching the Chesapeake Bay’s tidal waters from a specific constituent source, reductions ranging from 30–60% were required for the nitrogen model. In contrast, reductions of up to 80% were not detectable under the phosphorus model. The timelines necessary to detect reductions in nitrogen flux ranged from 11 to several hundred years under different rates-of-change and management scenarios. The approach proposed here can help better understand the ability to detect the effects of BMPs on a regional scale and help guide future management actions and monitoring programs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.108713","usgsCitation":"McLaughlin, P., Alexander, R., Blomquist, J.D., Devereux, O.H., Noe, G.E., Wagner, T., and Smalling, K., 2022, Power analysis for detecting the effects of best management practices on reducing nitrogen and phosphorus fluxes to the Chesapeake Bay watershed, USA: Ecological Indicators, v. 136, p. 1-12, https://doi.org/10.1016/j.ecolind.2022.108713.","productDescription":"108713, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-136202","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":448593,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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University","active":true,"usgs":false}],"preferred":false,"id":837243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, Richard","contributorId":219089,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":837262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blomquist, Joel D. 0000-0002-0140-6534","orcid":"https://orcid.org/0000-0002-0140-6534","contributorId":215461,"corporation":false,"usgs":true,"family":"Blomquist","given":"Joel","middleInitial":"D.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Devereux, Olivia H.","contributorId":97238,"corporation":false,"usgs":true,"family":"Devereux","given":"Olivia","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":837245,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":837246,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":837248,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837247,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229392,"text":"70229392 - 2022 - Early Neoproterozoic gold deposits of the Alto Guaporé province, southwestern Amazon craton, western Brazil","interactions":[],"lastModifiedDate":"2022-03-04T15:06:26.624931","indexId":"70229392","displayToPublicDate":"2022-03-04T08:56:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Early Neoproterozoic gold deposits of the Alto Guaporé province, southwestern Amazon craton, western Brazil","docAbstract":"The Alto Guaporé gold province, southwestern Amazon craton, contains gold deposits that have been mined since the beginning of the 18th century and these deposits, together, have modern-day, pre-mining gold resources of at least 1.8 Moz. The ore is associated with quartz vein systems along the southeastern part of the Aguapei belt, a ~35-km-wide and ~500-km-long, NNW-trending shear zone formed due to reactivation of a terrane-bounding suture. The Aguapei belt evolved by ca. 1150 to 1100 Ma rifting and deposition of siliciclastic sediments in an aulacogen basin, followed by deformation and low-grade metamorphism of the sedimentary sequences during 1100 to 900 Ma terrane collision along the craton margin. The deformation was characterized by a compressional regime until ca. 950 Ma and transition to a transpressional setting during the final 50 m.y.
The gold deposits are hosted in a variety of structures that are second-order to the main Aguapei shear zone. The Ernesto and Pau-a-Pique deposits are located ~40 km apart and at jogs along the Aguapei belt. They are marginal to pre-ore igneous rocks, with Ernesto hosted in the basal part of the metasedimentary Fortuna Formation that overlies tonalite and Pau-a-Pique at the contact between metasedimentary rocks and diorite. Three deformational phases comprise the compressional (D1 to D2) to transpressional (D3) tectonic events. In the Pau-a-Pique deposit and the deeper level of the Ernesto deposit, the ore-bearing veins are bedding parallel and follow D2 strike-slip and reverse fault zones, respectively. However, the veins formed during D3 reactivation of the older structures by an array of oblique accommodation faults. In contrast, ores at shallower levels of Ernesto, both in discordant and bedding-parallel veins, are hosted within a ~20-m-thick rigid metaconglomerate with associated dilation due to the structural complexity as sedimentary rocks of the Aguapei Group were folded around the dome-shaped roof of the pre-ore tonalite. The ores in both deposits, as well as in many other deposits of the province, are characterized by disseminated and vein-hosted pyrite. Gold occurs mainly as inclusions in the pyrite, with other hydrothermal phases comprising muscovite, Fe-Ti oxides, and minor apatite, chalcopyrite, and galena.
Fluid inclusion data, coupled with stable isotope geochemistry and geothermometry, indicate that gold precipitated from a low-salinity, CO2-rich fluid at ~300°C and ~2.5 kbar. The source for the fluid and gold was the interbedded pelites during devolatilization of the Aguapei Group sequence. The aqueous-carbonic fluid inclusions and the narrow range of δ18O values of quartz (12 ± 1‰) from many auriferous veins from the central part of the province represent a regional ore-forming fluid. The broad range of δD for hydrous minerals (–116 to –55‰) reflects influx of small amounts of meteoric water into the steeply dipping shear zones during postgold exhumation. The 40Ar/39Ar geochronology from hydrothermal muscovite indicates a widespread hydrothermal event along the belt between 928 and 920 Ma. Collectively, the geological, geochronological, and geochemical data suggest that metamorphic fluids migrated laterally into and then upward along the Aguapei belt and deposited gold in lower-order structures where strain gradients existed between lithounits. The province has many characteristics of large orogenic gold provinces worldwide and represents a highly prospective and underexplored target region for early Neoproterozoic gold, a time period that generally is not well endowed in gold ores.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4852","usgsCitation":"de Melo, R.P., de Oliveira, M.A., Goldfarb, R.J., Johnson, C.A., Marsh, E.E., Xavier, R.P., de Oliveira, L.R., and Morgan, L.E., 2022, Early Neoproterozoic gold deposits of the Alto Guaporé province, southwestern Amazon craton, western Brazil: Economic Geology, v. 117, no. 1, p. 127-163, https://doi.org/10.5382/econgeo.4852.","productDescription":"37 p.","startPage":"127","endPage":"163","ipdsId":"IP-121052","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488405,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11449/222995","text":"External Repository"},{"id":396749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Alto Guaporé gold province, Amazon craton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.7314453125,\n -20.756113874762068\n ],\n [\n -45.966796875,\n -20.756113874762068\n ],\n [\n -45.966796875,\n -8.146242825034385\n ],\n [\n -64.7314453125,\n -8.146242825034385\n ],\n [\n -64.7314453125,\n -20.756113874762068\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"117","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"de Melo, Rodrigo Prudente","contributorId":287985,"corporation":false,"usgs":false,"family":"de Melo","given":"Rodrigo","email":"","middleInitial":"Prudente","affiliations":[{"id":61677,"text":"Faculdade de Ciência e Tecnologia, Univ. Federal de Goiás, R. Mucuri S/N, Aparecida de Goiânia, GO, CEP 74968-755, Brazil.","active":true,"usgs":false}],"preferred":false,"id":837254,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Oliveira, Marcos Aurelio Farias","contributorId":287986,"corporation":false,"usgs":false,"family":"de Oliveira","given":"Marcos","email":"","middleInitial":"Aurelio Farias","affiliations":[{"id":61678,"text":"Instituto de Geociências e Ciências Exatas, Univ. Estadual Paulista, R. 24A 1515, Rio Claro, SP, CEP 13506-900, Brazil.","active":true,"usgs":false}],"preferred":false,"id":837255,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldfarb, Richard J. goldfarb@usgs.gov","contributorId":210729,"corporation":false,"usgs":false,"family":"Goldfarb","given":"Richard","email":"goldfarb@usgs.gov","middleInitial":"J.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":837256,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":837257,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marsh, Erin E. 0000-0001-5245-9532 emarsh@usgs.gov","orcid":"https://orcid.org/0000-0001-5245-9532","contributorId":1250,"corporation":false,"usgs":true,"family":"Marsh","given":"Erin","email":"emarsh@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":837258,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xavier, Roberto Perez","contributorId":287987,"corporation":false,"usgs":false,"family":"Xavier","given":"Roberto","email":"","middleInitial":"Perez","affiliations":[{"id":61679,"text":"Departamento de Geologia e Recursos Naturais, Instituto de Geociências, Universidade de Campinas, Campinas, SP, CEP 13083-970, Brazil","active":true,"usgs":false}],"preferred":false,"id":837259,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"de Oliveira, Leandro Rocha","contributorId":287988,"corporation":false,"usgs":false,"family":"de Oliveira","given":"Leandro","email":"","middleInitial":"Rocha","affiliations":[{"id":61680,"text":"Yamana Desenvolvimento Mineral, R. Ministro Orozimbo Nonato 272/19º andar, Belo Horizonte, MG, CEP 34006-053, Brazil","active":true,"usgs":false}],"preferred":false,"id":837260,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":837261,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70229391,"text":"70229391 - 2022 - Adaptive monitoring in support of adaptive management in rangelands","interactions":[],"lastModifiedDate":"2022-03-04T15:51:02.822444","indexId":"70229391","displayToPublicDate":"2022-03-04T08:56:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3230,"text":"Rangelands","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive monitoring in support of adaptive management in rangelands","docAbstract":"Monitoring supports iterative learning about the effectiveness of management actions, information that can help managers plan future actions, facilitate decision-making, and improve outcomes.
Adaptive monitoring is the evolution of a monitoring program in response to new management questions; new or changing environmental or socioeconomic conditions, improved monitoring methods, models, and tools; and experience implementing the monitoring program.
Adaptive monitoring is connected to research and management through the exchange of data; analytical, methodological, and technological developments; information; and understanding.
We review recent advances in adaptive monitoring and discuss new opportunities for both the research and management communities to improve monitoring in the years ahead.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rala.2021.07.003","usgsCitation":"McCord, S.E., and Pilliod, D., 2022, Adaptive monitoring in support of adaptive management in rangelands: Rangelands, v. 44, no. 1, p. 1-7, https://doi.org/10.1016/j.rala.2021.07.003.","productDescription":"7 p.","startPage":"1","endPage":"7","ipdsId":"IP-127736","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rala.2021.07.003","text":"Publisher Index Page"},{"id":396753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McCord, Sarah E.","contributorId":195931,"corporation":false,"usgs":false,"family":"McCord","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":837252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":837253,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255537,"text":"70255537 - 2022 - Stage-specific environmental correlates of reproductive success in Boreal Toads (Anaxyrus boreas boreas)","interactions":[],"lastModifiedDate":"2024-06-21T11:53:57.84801","indexId":"70255537","displayToPublicDate":"2022-03-04T06:51:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Stage-specific environmental correlates of reproductive success in Boreal Toads (Anaxyrus boreas boreas)","docAbstract":"Compensatory recruitment can facilitate the persistence of populations experiencing high adult mortality. Because early life-stages of many taxa, including amphibians, are difficult to mark and recapture, sources of variation in survival at these stages often are unknown, which creates barriers to improving in situ recruitment rates. We leveraged count data and open N-mixture models to examine the environmental factors associated with the hatching of egg clutches, tadpole survival, and probability of metamorphosis in Boreal Toads (Anaxyrus boreas boreas) that inhabit pastures leased for cattle grazing in western Wyoming, USA. We conducted weekly surveys and measured a suite of environmental variables at 20 breeding ponds during May–September 2018. The hatching of egg clutches was most strongly related to pond surface area, as clutches often desiccated at smaller ponds. Weekly tadpole survival was lowest in ponds with high abundance of aquatic predators. Predation did not preclude metamorphosis, which was more strongly associated with higher dissolved oxygen and vegetation cover. Cattle grazing reduced vegetation cover in and around breeding ponds, which resulted in lower levels of dissolved oxygen. Grazing-induced habitat changes are therefore likely to negatively influence tadpole metamorphosis both via indirect effects on dissolved oxygen, and direct effects on vegetation cover, which also serves as feeding sites and escape cover from predators. We demonstrate the success of three critical phases in early life-stage development (egg hatching, tadpole survival, metamorphosis) was associated with different environmental factors. The inclusion of stage-specific responses in demographic analyses is therefore critical for a thorough understanding of what limits populations.
The goal of the Louisiana Barrier Island Comprehensive Monitoring (BICM) program is to provide long-term data on coastal Louisiana for monitoring change and assisting in coastal management. This study (carried out under Coastal Protection and Restoration Authority contract number 2000339324, BICM2—Chenier TopoBathy DEM) builds upon the previous BICM physical assessment of the Chenier Plain region using bathymetric data from three periods (1930, 2007, and 2017) to develop digital elevation models for historical and current periods. In addition to bathymetric datasets, the study includes light detection and ranging elevation measurements along the coastline to produce elevation datasets for the 2007 and 2017 periods. This report describes the methods used to acquire, process, and produce these products.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221014","collaboration":"Prepared in cooperation with Coastal Protection and Restoration Authority of Louisiana","programNote":"Louisiana Barrier Island Comprehensive Monitoring Program 2015–2020","usgsCitation":"Flocks, J.G., Forde, A.S., and Bernier, J.C., 2022, Chenier Plain region bathymetric and topographic datasets: Methodology report: U.S. Geological Survey Open-File Report 2022–1014, 21 p., https://doi.org/10.3133/ofr20221014.","productDescription":"vii, 21 p.","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122902","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501759,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112530.htm","linkFileType":{"id":5,"text":"html"}},{"id":396683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1014/ofr20221014.pdf","text":"Report","size":"6.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1014"},{"id":396682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1014/coverthb.jpg"},{"id":396685,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1014/images/"},{"id":396684,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1014/ofr20221014.XML"},{"id":396704,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221014/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Chenier Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.85620117187499,\n 29.439597566602902\n ],\n [\n -92.1258544921875,\n 29.439597566602902\n ],\n [\n -92.1258544921875,\n 29.8\n ],\n [\n -93.85620117187499,\n 29.8\n ],\n [\n -93.85620117187499,\n 29.439597566602902\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
We use a suite of historical earthquakes to quantitatively determine earthquake early warning (EEW) alert threshold strategies for a range of shaking intensity targets for EEW in the U.S. West Coast. The current method for calculating alert regions for the ShakeAlert EEW System does not take into account variabilities and uncertainties in shaking distribution. As a result, if the modified Mercalli intensity (MMI) level used to determine the extent of the alert region (the alert threshold) is the same as the target intensity threshold, the alert region will be too small to include all locations that require alerts even if earthquake source parameters are estimated accurately. Missed alerts can be reduced by using a lower alert threshold than the target threshold. This expands the alert region, increasing the number of precautionary alerts issued to people who experience shaking below the target level. We determine alert thresholds that optimize this tradeoff between missed and precautionary alerts for target thresholds of MMI 4.0-6.0 using a ShakeMap catalog of 143 M5.0-7.3 earthquakes as ground truth. We examine the quality of each alerting strategy relative to the target MMI, where we define alert quality metrics in terms of both the area and population alerted. Optimal alert thresholds maximize correct alerts while limiting most precautionary alerts to regions that are likely to still feel some shaking. We find these optimal alert thresholds also maximize warning times. This analysis presents a quantitative framework ShakeAlert can use to communicate alerting strategies and performance expectations to ShakeAlert users.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EF002515","usgsCitation":"Saunders, J.K., Minson, S.E., and Baltay Sundstrom, A.S., 2022, How low should we alert? Quantifying intensity threshold alerting strategies for earthquake early warning in the United States: Earth's Future, v. 10, no. 3, e2021EF002515, 20 p., https://doi.org/10.1029/2021EF002515.","productDescription":"e2021EF002515, 20 p.","ipdsId":"IP-130454","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489935,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ef002515","text":"Publisher Index Page"},{"id":482033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"10","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Saunders, Jessie Kate 0000-0001-5340-6715","orcid":"https://orcid.org/0000-0001-5340-6715","contributorId":290634,"corporation":false,"usgs":true,"family":"Saunders","given":"Jessie","email":"","middleInitial":"Kate","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927334,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229816,"text":"70229816 - 2022 - Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations","interactions":[],"lastModifiedDate":"2022-03-18T14:39:48.68884","indexId":"70229816","displayToPublicDate":"2022-03-03T09:34:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations","docAbstract":"Conservation translocations are increasingly used to help recover imperiled species. However, success of establishing populations remains low, especially for amphibians. Identifying factors associated with translocation success can help increase efficiency and efficacy of recovery efforts. Since the 1990s, several captive and semi-captive facilities have produced Chiricahua Leopard Frogs (Rana chiricahuensis) to establish or augment wild populations in Arizona and New Mexico, USA. During this same time, personnel associated with several programs surveyed translocation and non-translocation sites for presence of amphibians. We used 25 years (1995–2019) of survey and translocation data for the federally threatened Chiricahua Leopard Frog to identify factors linked with population persistence. Our dataset included approximately 40,642 egg masses or animals translocated in 314 events to 115 distinct sites and > 5800 visual encounter surveys from 641 sites; 120 of these sites were also surveyed with environmental DNA methods in 2018. We used a hierarchical dynamic occupancy model that accounted for imperfect detection to identify patch- and landscape-level attributes associated with site occupancy, and then used predictions from that model to evaluate factors associated with population persistence at translocation sites. Across all sites, extinction probability for Chiricahua Leopard Frogs was higher in lotic (stream) than lentic (pond) habitats and when Western Tiger Salamanders (Ambystoma mavortium) were present. Restoration of sites specifically for frog conservation reduced extinction probability. Colonization of unoccupied sites increased moderately with increasing numbers of translocation sites within 2 km, indicating a benefit of translocation efforts beyond sites where frogs were stocked. At translocation sites, persistence was greater in lentic than lotic habitats and was negatively correlated with the proportion of years tiger salamanders were present. Increasing numbers of translocation events, especially of late-stage larvae, increased persistence. There was little difference in population persistence based on whether stock was from captive, semi-captive, or wild sources, but translocations during the dry season (January—July) succeeded more than those after the typical arrival of summer rains (August—December). Based on the number of years translocation sites were predicted to be occupied, 2 or more translocations produced, on average, a > 4-yr increase in predicted occupancy compared to sites without translocations. While translocations have increased the number of populations across the landscape, continued management of water availability and threats such as invasive predators and disease remain critical to recovery of the Chiricahua Leopard Frog.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02078","usgsCitation":"Hossack, B., Howell, P., Owens, A., Cobos, C., Goldberg, C.S., Hall, D.L., Hedwall, S., MacVean, S., McCaffery, M., McCall, A.H., Mosley, C., Oja, E.B., Rorabaugh, J.C., Sigafus, B., and Sredl, M.J., 2022, Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations: Global Ecology and Conservation, v. 35, e02078, 22 p., https://doi.org/10.1016/j.gecco.2022.e02078.","productDescription":"e02078, 22 p.","ipdsId":"IP-135486","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":448603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02078","text":"Publisher Index Page"},{"id":397306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.35717773437499,\n 31.325486676506983\n ],\n [\n -106.0400390625,\n 31.325486676506983\n ],\n [\n -106.0400390625,\n 35.10193405724606\n ],\n [\n -112.35717773437499,\n 35.10193405724606\n ],\n [\n -112.35717773437499,\n 31.325486676506983\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":838451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":838452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Owens, Audrey K","contributorId":288932,"corporation":false,"usgs":false,"family":"Owens","given":"Audrey K","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cobos, C","contributorId":288933,"corporation":false,"usgs":false,"family":"Cobos","given":"C","email":"","affiliations":[{"id":38107,"text":"Turner Endangered Species Fund","active":true,"usgs":false}],"preferred":false,"id":838454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldberg, Caren S.","contributorId":76879,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","email":"","middleInitial":"S.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":838455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, David L.","contributorId":222395,"corporation":false,"usgs":false,"family":"Hall","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":838456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hedwall, Shaula","contributorId":288934,"corporation":false,"usgs":false,"family":"Hedwall","given":"Shaula","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":838457,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"MacVean, Susi","contributorId":288935,"corporation":false,"usgs":false,"family":"MacVean","given":"Susi","email":"","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838458,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McCaffery, Magnus","contributorId":288936,"corporation":false,"usgs":false,"family":"McCaffery","given":"Magnus","email":"","affiliations":[{"id":38107,"text":"Turner Endangered Species Fund","active":true,"usgs":false}],"preferred":false,"id":838459,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCall, A. Hunter","contributorId":288937,"corporation":false,"usgs":false,"family":"McCall","given":"A.","email":"","middleInitial":"Hunter","affiliations":[{"id":48661,"text":"Private","active":true,"usgs":false}],"preferred":false,"id":838460,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mosley, C","contributorId":288938,"corporation":false,"usgs":false,"family":"Mosley","given":"C","email":"","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838461,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Oja, Emily Bea 0000-0002-8621-9665","orcid":"https://orcid.org/0000-0002-8621-9665","contributorId":261164,"corporation":false,"usgs":true,"family":"Oja","given":"Emily","email":"","middleInitial":"Bea","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":838462,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rorabaugh, James C.","contributorId":191978,"corporation":false,"usgs":false,"family":"Rorabaugh","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":838463,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sigafus, Brent H. 0000-0002-7422-8927","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":264740,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":838464,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sredl, Michael J","contributorId":288939,"corporation":false,"usgs":false,"family":"Sredl","given":"Michael","email":"","middleInitial":"J","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":838465,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70229202,"text":"tm6A62 - 2022 - Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","interactions":[],"lastModifiedDate":"2022-03-03T17:29:27.921518","indexId":"tm6A62","displayToPublicDate":"2022-03-03T09:21:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A62","displayTitle":"Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","title":"Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","docAbstract":"This report describes the skeletal storage, compaction and subsidence (CSUB) package of MODFLOW 6. The CSUB package simulates the vertical compaction of compressible sediments and land subsidence. The package simulates groundwater storage changes and elastic compaction in coarse-grained aquifer sediments. The CSUB package also simulates groundwater storage changes and elastic and inelastic compaction in fne-grained, compressible interbeds, or in extensive confning units. The package can account for effective stress-dependent changes in storage properties. The CSUB package can also explicitly account for the contribution of water compressibility to groundwater storage changes.
Compaction of compressible sediments is formulated using Terzaghi’s elastoplastic model and assumes the total compaction is a small fraction of the total initial thickness of compressible sediments. Compaction is controlled by head or pore-pressure changes and overburden stress changes associated with water-table changes, and thus by effective stress changes within coarse-and fne-grained compressible sediments. If the stress in a compressible unit is less than the preconsolidation stress, compaction is elastic (recoverable). If the stress in a compressible sediment is greater than the preconsolidation stress, compaction is inelastic (irrecoverable) and permanent land subsidence occurs.
The propagation of head changes within fne-grained, compressible interbeds is represented numerically using a transient, one-dimensional (vertical) groundwater fow equation. This equation accounts for delayed release of water from storage or uptake of water into storage in the interbeds. Vertical hydraulic conductivity, elastic and inelastic skeletal specifc storage, and interbed thickness control the timing of interbed storage changes. Interbeds that are thin, have a relatively large vertical hydraulic conductivity, or relatively small specifc-storage values equilibrate quickly with heads/pore pressures in surrounding coarse-grained sediments and can be represented as no-delay interbeds that use the simulated groundwater head in a cell to calculate interbed compaction and do not need to be solved numerically using a vertically discretized interbed and the vertical groundwater fow equation.
In addition to the applicability to confned groundwater fow systems, several features of the CSUB package make it applicable to shallow, unconfned groundwater fow systems. Geostatic stress can be treated as a function of water-table elevation, and compaction is a function of computed changes in effective stress. The porosity, void ratio, and thickness of shallow and deep coarse-grained aquifer sediments, fne-grained interbeds, and extensive confning units can vary in time based on calculated strain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A62","usgsCitation":"Hughes, J.D., Leake, S.A., Galloway, D.L., and White, J.T., 2022, Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6: U.S. Geological Survey Techniques and Methods, book 6, chap. A62, 57 p., https://doi.org/10.3133/tm6A62.","productDescription":"Report: vi, 57 p.; Software Release","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114536","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":396667,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A55","text":"Techniques and Methods 6-A55","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Flow Model"},{"id":396668,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A56","text":"Techniques and Methods 6-A56","linkHelpText":"- Documentation for the “XT3D” option in the Node Property Flow (NPF) Package of MODFLOW 6"},{"id":396669,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A57","text":"Techniques and Methods 6-A57","linkHelpText":"- Documentation for the MODFLOW 6 framework"},{"id":396639,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a62/coverthb.jpg"},{"id":396642,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/F76Q1VQV","text":"USGS software release","linkHelpText":"- MODFLOW 6: USGS Modular Hydrologic Model"},{"id":396640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a62/tm6a62.pdf","text":"Report","size":"5.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-A62"},{"id":396641,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A61","text":"Techniques and Methods 6-A61","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Transport Model"}],"contact":"Director, Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 411
Reston, VA 20192-0002
This report documents a new Groundwater Transport (GWT) Model for MODFLOW 6. The GWT Model simulates three-dimensional transport of a single chemical species in fowing groundwater based on a generalized control-volume fnite-difference approach. Although each GWT Model is only able to represent a single chemical species, multiple GWT Models may be invoked within a single MODFLOW 6 simulation to represent solute transport of multiple non-interacting chemical species. The GWT Model is designed to work with the Groundwater Flow (GWF) Model for MODFLOW 6, which simulates transient, three-dimensional groundwater fow. The version of the GWT model documented here must use the same spatial discretization used by the GWF Model; however, that spatial discretization can be represented by regular MODFLOW grids consisting of layers, rows, and columns, or by more general unstructured grids. The GWT Model simulates (1) advective transport, (2) the combined hydrodynamic dispersion processes of velocity-dependent mechanical dispersion and molecular diffusion, (3) adsorption and absorption (collectively referred to as sorption) of solutes by the aquifer matrix, (4) transfer between the mobile domain and one or more immobile domains, (5) frst-or zero-order solute decay or production, (6) mixing from groundwater sources and sinks, and (7) direct addition of solute mass. The GWT Model can also represent advective solute transport through advanced package features, such as streams, lakes, multi-aquifer wells, and the unsaturated zone. If the GWF Model application uses the Water Mover (MVR) Package to connect fow packages, then solute transport between these packages can also be represented. The transport processes described in this report have been implemented in a fully implicit manner and are solved in a system of equations using iterative numerical methods. The present version of the GWT Model for MODFLOW 6 does not have an option to calculate steady-state transport solutions; if a steady-state solution is required, then transient evolution of the solute must be represented using multiple time steps until no further changes in solute concentrations are detected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A61","usgsCitation":"Langevin, C.D., Provost, A.M., Panday, Sorab, and Hughes, J.D., 2022, Documentation for the MODFLOW 6 Groundwater Transport Model: U.S. Geological Survey Techniques and Methods, book 6, chap. A61, 56 p., https://doi.org/10.3133/tm6A61.","productDescription":"Report: vi, 56 p.; Software Release","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120850","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":396637,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A62","text":"Techniques and Methods 6-A62","linkHelpText":"- Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6"},{"id":396666,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A57","text":"Techniques and Methods 6-A57","linkHelpText":"- Documentation for the MODFLOW 6 framework"},{"id":396665,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A56","text":"Techniques and Methods 6-A56","linkHelpText":"- Documentation for the “XT3D” option in the Node Property Flow (NPF) Package of MODFLOW 6"},{"id":396664,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A55","text":"Techniques and Methods 6-A55","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Flow Model"},{"id":396635,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a61/coverthb2.jpg"},{"id":396636,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a61/tm6a61.pdf","text":"Report","size":"3.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-A61"},{"id":396638,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/F76Q1VQV","text":"USGS software release","linkHelpText":"- MODFLOW 6: USGS Modular Hydrologic Model"}],"contact":"Director, Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 411
Reston, VA 20192-0002
Coastal marshes are globally important, carbon dense ecosystems simultaneously maintained and threatened by sea-level rise. Warming temperatures may increase wetland plant productivity and organic matter accumulation, but temperature-modulated feedbacks between productivity and decomposition make it difficult to assess how wetlands and their thick, organic rich soils will respond to climate warming. Here, we actively increased aboveground plant-surface and below-ground soil temperatures in two marsh plant communities, and found that a moderate amount of warming (1.7°C above ambient temperatures) consistently maximized root growth, marsh elevation gain, and below-ground carbon accumulation. Marsh elevation loss observed at higher temperatures was associated with increased carbon mineralization and increased microtopographic heterogeneity, a potential early warning signal of marsh drowning. Maximized elevation and below-ground carbon accumulation for moderate warming scenarios uniquely suggest linkages between metabolic theory of individuals and landscape-scale ecosystem resilience and function, but our work indicates nonpermanent benefits as global temperatures continue to rise.
Deep learning (DL) models can accurately predict many hydrologic variables including streamflow and water temperature; however, these models have typically predicted hydrologic variables independently. This study explored the benefits of modeling two interdependent variables, daily average streamflow and daily average stream water temperature, together using multi-task DL. A multi-task scaling factor controlled the relative contribution of the auxiliary variable's error to the overall loss during training. Our experiments examined the improvement in prediction accuracy of the multi-task approach using paired streamflow and water temperature data from sites across the conterminous United States. Our results showed that for 56 out of 101 sites, the best performing multi-task models performed better overall than the single-task models in terms of Nash-Sutcliffe efficiency for predicting streamflow with single-site models. For 43 sites, the best multi-task, single-site models made no significant difference in predicting streamflow. The multi-task approach had a smaller effect when applied to a model trained with data from 101 sites together, significantly improving performance for only 17 sites. The multi-task scaling factor was consequential in determining to what extent the multi-task approach was beneficial. A naïve selection of this factor led to significantly worse-performing models for 3 of 101 sites when predicting streamflow as the primary variable, and 47 of 53 sites when predicting stream temperature as the primary variable. We conclude that a multi-task approach can make more accurate predictions by leveraging information from interdependent hydrologic variables, but only for some sites, variables, and model configurations.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021WR030138","usgsCitation":"Sadler, J.M., Appling, A.P., Read, J., Oliver, S.K., Jia, X., Zwart, J.A., and Kumar, V., 2022, Multi-task deep learning of daily streamflow and water temperature: Water Resources Research, v. 58, no. 4, e2021WR030138, 18 p., https://doi.org/10.1029/2021WR030138.","productDescription":"e2021WR030138, 18 p.","ipdsId":"IP-129032","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":448611,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr030138","text":"Publisher Index Page"},{"id":386338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":817232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":817235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":817237,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}