{"pageNumber":"109","pageRowStart":"2700","pageSize":"25","recordCount":41032,"records":[{"id":70243946,"text":"sir20235051 - 2023 - Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region","interactions":[],"lastModifiedDate":"2023-12-23T14:28:31.061588","indexId":"sir20235051","displayToPublicDate":"2023-12-22T15:44:25","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5051","displayTitle":"Automated Construction of Streamflow-Routing Networks for MODFLOW—Application in the Mississippi Embayment Region","title":"Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region","docAbstract":"<p>In humid regions with dense stream networks, surface water exerts a fundamental control on the water levels and flow directions of shallow groundwater. Understanding interactions between groundwater and surface water is critical for managing groundwater resources and groundwater-dependent ecosystems. Representing streams in groundwater models has historically been arduous and error prone. In recent years, however, all the information needed to numerically describe stream boundary conditions for a model area has become readily available online, as have robust open-source software tools for translating that information to a model grid. The SFRmaker Python package leverages geospatial capabilities in the scientific Python ecosystem to robustly automate the production of input to the Streamflow-Routing (SFR) Package of MODFLOW from the National Hydrography Dataset Plus or other hydrography data. This report documents an application of SFRmaker to automate production of SFR Package input for groundwater models within the Mississippi Embayment Regional Aquifer Study area. SFR Package input was developed in three steps: (1) preprocessing to develop a single set of grid-independent flowlines from National Hydrography Dataset Plus version 2 data; (2) setting up the SFR package from the preprocessed flowlines, and (3) correcting streambed top elevations after an initial model run. Separating the hydrography preprocessing from the construction of SFR Package input was advantageous in that it minimized the need to repeat computationally expensive geoprocessing (thereby speeding model construction) and also allowed for the curation of a single set of grid-independent SFR input data that can be used for any MODFLOW model within the study area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235051","usgsCitation":"Leaf, A.T., 2023, Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region: U.S. Geological Survey Scientific Investigations Report 2023–5051, 28 p., https://doi.org/10.3133/sir20235051.","productDescription":"Report: vii, 28 p.; 4 Data Releases; Dataset","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-105069","costCenters":[{"id":37947,"text":"Upper Midwest Water Science 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Area</li><li>Methods</li><li>Results and Discussion</li><li>Limitations</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-22","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":873850,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250336,"text":"sir20235100 - 2023 - Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta","interactions":[],"lastModifiedDate":"2026-03-13T15:20:23.277736","indexId":"sir20235100","displayToPublicDate":"2023-12-22T15:26:20","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5100","displayTitle":"Simulating Groundwater Flow in the Mississippi Alluvial Plain with a Focus on the Mississippi Delta","title":"Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta","docAbstract":"<p>The Mississippi Alluvial Plain has become one of the most important agricultural regions in the United States but relies heavily on groundwater for irrigation. On average, more than 12 billion gallons are withdrawn daily from the Mississippi River Valley alluvial aquifer. Declining groundwater levels, especially in the Delta region of northwest Mississippi and the Cache and Grand Prairie regions of eastern Arkansas, have led to concerns about future sustainability. The U.S. Geological Survey Mississippi Alluvial Plain Project is focused on quantifying the groundwater system in the alluvial plain and the response of groundwater resources to future development. A key objective of the project is to provide updated groundwater flow models supported by extensive data collection and analyses. MODFLOW 6, PEST++, and several open-source python packages were used to develop a simplified, faster running version of the Mississippi Embayment Regional Aquifer Study model that can provide boundary conditions for local inset models, including the Mississippi Delta model described in this report. An automated workflow was used for model construction, history matching, and development of baseline future climate scenarios. The models incorporate information from a Soil-Water-Balance code simulation of the terrestrial water balance, metering-based estimates of water use from thousands of wells, measured and estimated streamflow and stages, and the largest airborne electromagnetic survey flown to date in the United States. Baseline scenarios for the Mississippi Delta under potential future climates were constructed using recharge, surface runoff and irrigation pumping forcings from a future version of the Soil-Water-Balance model, driven by downscaled temperature and precipitation output from 10 general circulation model simulations, including high and moderate carbon emissions pathways.</p><p>Results indicate a complex water balance that varies in time and space in terms of the terrestrial recharge, stream leakage, and regional groundwater flow components, which are affected by seasonal forcings, human activity, and alluvial geomorphology. The general circulation model outputs indicate a continued rise in average temperatures but no clear precipitation trend. Increased crop water demand is anticipated from the higher temperatures, resulting in increased irrigation withdrawals to sustain current levels of irrigated agriculture. Simulated drawdowns in groundwater levels at the mid-21st century vary greatly. Under moderate or wet climate scenarios, and in parts of the aquifer that are well connected to surface water, little to no additional drawdown is anticipated. Under dry or warm scenarios, drawdowns of as much as 10 meters or more are possible in parts of the aquifer that are relatively disconnected from surface water. Under dry or warm scenarios, the portion of the Delta with greater than 60 feet of saturated thickness could be reduced from near 100 percent currently (2018) to 80–90 percent by mid-century. Future simulations with the model could include alternative management scenarios to identify options for improving groundwater sustainability. The automated model construction workflows are designed to facilitate regular updating, making this a “living” framework that the Mississippi Department of Environmental Quality and other stakeholders can use for adaptive management going forward.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235100","programNote":"Water Use and Availability Science Program","usgsCitation":"Leaf, A.T., Duncan, L.L., Haugh, C.J., Hunt, R.J., and Rigby, J.R., 2023, Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta: U.S. Geological Survey Scientific Investigations Report 2023–5100, 143 p., https://doi.org/10.3133/sir20235100.","productDescription":"Report: viii, 143 p.; 4 Data Releases","numberOfPages":"156","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135342","costCenters":[{"id":37947,"text":"Upper Midwest Water Science 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to 2020, simulated with the Soil-Water-Balance model"},{"id":423186,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BC6UB8","text":"USGS data release","linkHelpText":"Soil-Water-Balance forecasted climate model output for simulations of water budget components in the Mississippi Embayment Regional Aquifer System, 2020 to 2055"},{"id":423185,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TSDEAC","text":"USGS data release","linkHelpText":"Digital surfaces and site data of well-screen top and bottom altitudes defining the irrigation production zone of the Mississippi River Valley alluvial aquifer within the Mississippi Alluvial Plain project region"},{"id":423182,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5100/sir20235100.XML"},{"id":423181,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5100/sir20235100.pdf","text":"Report","size":"59.9 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Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Area Description and Hydrogeologic Setting</li><li>Conceptual Model</li><li>Modeling Approach</li><li>Results and Discussion</li><li>Assumptions, Limitations, and Suggestions for Future Work</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. Groundwater Flow Model Constructions</li><li>Appendix 2. Parameter Estimation and Uncertainty Analysis</li><li>Appendix 3. Additional Model Results</li><li>Appendix 4. General Circulation Models Used in the Future Climate Scenarios</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-22","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duncan, Leslie L. 0000-0002-5938-5721","orcid":"https://orcid.org/0000-0002-5938-5721","contributorId":204004,"corporation":false,"usgs":true,"family":"Duncan","given":"Leslie","email":"","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haugh, Connor J. 0000-0002-5204-8271","orcid":"https://orcid.org/0000-0002-5204-8271","contributorId":219945,"corporation":false,"usgs":true,"family":"Haugh","given":"Connor J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889497,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rigby, James R. 0000-0002-5611-6307","orcid":"https://orcid.org/0000-0002-5611-6307","contributorId":260894,"corporation":false,"usgs":true,"family":"Rigby","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889498,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70250314,"text":"sir20235080 - 2023 - Updated estimates of water budget components for the Mississippi Embayment Region using a soil-water-balance model, 2000–2020","interactions":[],"lastModifiedDate":"2026-03-12T20:54:31.140336","indexId":"sir20235080","displayToPublicDate":"2023-12-22T15:17:09","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5080","displayTitle":"Updated Estimates of Water Budget Components for the Mississippi Embayment Region Using a Soil-Water-Balance Model, 2000–2020","title":"Updated estimates of water budget components for the Mississippi Embayment Region using a soil-water-balance model, 2000–2020","docAbstract":"<p>A Soil-Water-Balance (SWB) model for the Mississippi embayment region in Arkansas, Tennessee, Mississippi, and Louisiana was constructed and calibrated to gain insight into potential recharge patterns for the Mississippi River Valley alluvial aquifer, which has had substantial drawdown under intense pumping stress over the last several decades. An analysis of the net infiltration term from the SWB model combined with newly gathered airborne electromagnetic geophysical data on the surficial sediments in a calibrated modular three-dimensional finite-difference (MODFLOW 6) groundwater flow model of one area in the alluvial plain found that the distribution of net infiltration was significantly different from the recharge that gets to the water table through the complicated silt and clay stratigraphy of the unsaturated zone. The net infiltration of water through the rooting zone as simulated by SWB ranges from 5.7 to 12.3 inches per year in the alluvial plain part of the model domain, and is fairly evenly distributed within local areas. Recharge to the underlying aquifer is less and is much more focused in particular zones where the connectivity through the upper layers of the unsaturated zone above the water table is greater, indicating possible horizontal flow and perched water table conditions in the unsaturated zone. Runoff and net infiltration together account for 32 percent of the incoming precipitation overall and somewhat higher percentages in the alluvial plain area on an annual basis. These terms are much higher in the fall and winter than in the summer. Actual evapotranspiration accounts for between 62 and 72 percent on average of the annual precipitation but dominates all other terms in the summer months. Without irrigation, summertime net infiltration and runoff would be near zero in the crop-dominated alluvial plain area. The SWB model reproduced reported irrigation rates for corn, soybeans, rice, and cotton on an annual basis fairly well. The SWB model for the Mississippi embayment region was calibrated using more than 15,000 observations representing four parts of the calculated water budget: actual evapotranspiration, surface runoff, net infiltration, and irrigation. Using a Monte Carlo approach to determine the uncertainty in the model results stemming from the uncertainty in the model parameters used in the calibration, the uncertainty in the annual actual evapotranspiration values was around 5 percent, whereas the uncertainty in the irrigation, net infiltration, and runoff was around 20 percent.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235080","programNote":"Water Availability and Use Science Program","usgsCitation":"Nielsen, M.G., and Westenbroek, S.M., 2023, Updated estimates of water budget components for the Mississippi embayment region using a Soil-Water-Balance model, 2000–2020: U.S. Geological Survey Scientific Investigations Report 2023–5080, 58 p., https://doi.org/10.3133/sir20235080","productDescription":"Report: vii, 58 p.; Data Release; 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archive and output files for net infiltration, runoff, and irrigation water use for the Mississippi Embayment Regional Aquifer System, 2000 to 2020, simulated with the Soil-Water-Balance model"}],"country":"United States","otherGeospatial":"Mississippi Embayment Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -94.12089542031869,\n              28.886284478842654\n            ],\n            [\n              -86.65019229531852,\n              28.886284478842654\n            ],\n            [\n              -86.65019229531852,\n              37.89501192204163\n            ],\n            [\n              -94.12089542031869,\n              37.89501192204163\n            ],\n            [\n              -94.12089542031869,\n              28.886284478842654\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/upper-midwest-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/upper-midwest-water-science-center\">Upper Midwest Water Science Center</a><br>U.S. Geological Survey<br>1 Gifford Pinchot Drive<br>Madison, WI 53726</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods—Soil-Water-Balance Model Construction and Calibration</li><li>Results and Discussion</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-22","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Nielsen, Martha G. 0000-0003-3038-9400 mnielsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3038-9400","contributorId":4169,"corporation":false,"usgs":true,"family":"Nielsen","given":"Martha","email":"mnielsen@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westenbroek, Stephen, M. 0000-0002-6284-8643","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":206429,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen, M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889420,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70250566,"text":"cir1516 - 2023 - Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States","interactions":[],"lastModifiedDate":"2025-08-07T21:10:28.947951","indexId":"cir1516","displayToPublicDate":"2023-12-22T07:00:34","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1516","displayTitle":"Integrated Science Strategy for Assessing and Monitoring Water Availability and Migratory Birds for Terminal Lakes Across the Great Basin, United States","title":"Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States","docAbstract":"<h1>Executive Summary</h1><p>In 2022, the U.S. Geological Survey (USGS) established the Saline Lake Ecosystems Integrated Water Availability Assessment (IWAAs) to monitor and assess the hydrology of terminal lakes in the Great Basin and the migratory birds and other wildlife dependent on those habitats. Scientists from across the USGS (with specialties in water quantity, water quality, limnology, avian biology, data science, landscape ecology, and science communication) formed the Saline Lake Ecosystems IWAAs Team. The team has developed this regional strategic science plan to guide data collection and assessment activities at terminal lakes in the Great Basin.</p><p>The U.S. Congress requested the USGS to establish the Saline Lake Ecosystems IWAAs in response to historically low water levels at terminal lakes and associated wetlands across the Great Basin. Not all Great Basin terminal lakes have high salinity; however, all terminal lakes occur in endorheic, closed, basins with no surface-water outflow. Low lake levels across the Great Basin are the result of increased water use for agriculture and municipalities, drought conditions, and a warming climate. Great Basin terminal lake water extents have decreased by as much as 90 percent over the last 150 years, and terminal lake wetlands have decreased in area by as much as 47 percent since 1984. Lake elevations and wetland areas are primarily supported by freshwater inputs from snowmelt feeding upgradient rivers, streams, and springs. These freshwater inputs have been severely reduced because of continued and increased surface-water diversions and surface-water capture through groundwater pumping for agriculture, mining, and public supply as well as unprecedented drought conditions and warming temperatures related to climate change.</p><p>Water quality, specifically salinity, is highly variable for terminal lakes of the Great Basin, and this variability is a result of the balance between freshwater inflow and evaporation. Variability of salinity at each of the terminal lakes can be affected by lake morphology, hydrogeologic features of the basin, annual variability in weather patterns, and changes in upgradient water use. Hypersaline terminal lakes provide abundant food resources such as brine shrimp and brine flies that support nesting and migrating birds. The density and composition of invertebrates are closely tied to lake salinity. Increased salinity can exceed the tolerance of invertebrates, severely limiting their biomass. In contrast, decreased salinity can lead to altered invertebrate community composition, reducing the abundance of optimal avian prey resources.</p><p>Great Basin terminal lake ecosystems, including open-water and adjacent aquatic and terrestrial environments, provide resources necessary to sustain many animal populations throughout the year. Although a variety of taxa use terminal lakes, these ecosystems are of acute importance for the millions of migratory waterbirds (for example, shorebirds, wading birds, and waterfowl) dependent on the network of terminal lakes and their associated wetlands. Migratory birds transiting the Pacific and Central Flyways use Great Basin terminal lake ecosystems throughout the year to feed, nest, and transit between wintering and breeding ranges. As such, successful conservation of birds and their habitats requires coordinated management of water and habitats across the Great Basin network of terminal lakes and wetlands.</p><p>The linkages between water availability and ecosystem vulnerability of terminal lakes in the Great Basin are not well understood. The vulnerability of terminal lakes is related to the factors driving change and adaptive capacity of the lake ecosystem. Saline lake ecosystems are vulnerable when changes in water quantity affect ecosystem function. Water quantity affects salinity, which affects food webs and habitat; these linkages can be investigated with water-quality and food web monitoring. Water quantity also affects inundated habitat, which can be quantified through remote sensing. It is necessary to quantify hydroclimatic and water use controls on water availability to terminal lakes to assess the response of the ecosystems. Remotely sensed data can provide a broad-scale and long-term synoptic view of terminal lake hydrologic characteristics, but ground observations are required to interpret changes in water quality and ecological functions. Some terminal lake basins have ongoing monitoring and modeling efforts within the Great Basin (for example, Great Salt Lake, Carson River Basin), yet most monitoring locations are hydrologically upgradient and too far away from lake inflows to provide an accurate assessment of hydrological trends for the lake ecosystems. Other terminal lakes have no long-term hydrological monitoring in their respective watersheds (for example, Lake Abert).</p><p>Ecological data collection in the Great Basin is also insufficient to understand how many birds exist on the landscape, how birds use the mosaic of terminal-lake habitats as an interconnected system, and how Great Basin terminal lakes are linked to the larger continental system of the Pacific and Central Flyways. Across agencies and organizations, tracking bird movement, abundance, and diversity is inconsistent, with some lakes having once- or twice-a-year bird survey efforts and a few locations having more intensive ecological data-gathering efforts (for example, Great Salt Lake, Lake Abert). Bridging hydrological and ecological information gaps will improve understanding of the trends in water supply and water quality, habitat availability and usage, and impacts on vulnerable waterbird species, all of which would be used by managers in coordinated conservation of this unique network of terminal-lake habitats.</p><p>The terminal lakes of the Great Basin are part of the Basin and Range physiographic province that extends from the Colorado Plateau on the east to the Sierra Nevada on the west, and from the Snake River Plain on the north to the Garlock fault and the Mojave block on the south. The Great Basin is larger than 650,000 square kilometers and encompasses most of the State of Nevada but also extends to western Utah, eastern California, southeastern Idaho, southwestern Wyoming, and southeastern Oregon. The climate is arid to semiarid with a hydrologic regime that is snowmelt dominated, providing as much as 75 percent of total annual runoff for the region. Terminal lakes of the Great Basin occupy the lowest areas of closed (endorheic) drainage basins, such that lake levels and water quality respond rapidly to surface-water inflow. Terminal lakes provide local and regional economic value to the States in the Great Basin, including mineral extraction, aquaculture, public works, and recreational uses. As an example, assessments of Great Salt Lake’s ecological health and economic impact find hemispheric importance for the former and regional importance for the latter. Great Salt Lake creates about 7,000 jobs and $2 billion of economic output per year, most of which would be lost with further declines in lake level.</p><p>The objectives of this Science Strategy are threefold: (1) to identify how changing water availability affects the quality, diversity, and abundance of habitats supporting continental waterbird populations; (2) to highlight the scientific monitoring and assessment needs of Great Basin terminal lakes; and (3) to support coordinated management and conservation actions to benefit those ecosystems, migratory birds, and other wildlife. There are long-term hydrological, ecological, and societal challenges associated with terminal lakes ecosystems in the Great Basin. This Science Strategy benefits partners by providing a conceptual model, nested at different spatial extents, that identifies key scientific information needs to inform coordinated implementation of management and conservation plans within and among hydrologic basins to address these complex challenges.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1516","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Frus, R.J., Aldridge, C.L., Casazza, M.L., Eagles-Smith, C.A., Herring, G., Hynek, S.A., Jones, D.K., Kemp, S.K., Marston, T.M., Morris, C.M., Naranjo, R.C., Nell, C.S., O’Leary, D.R., Overton, C.T., Pulver, B.A., Reichert, B.E., Rumsey, C.A., Schuster, R., and Smith, C.D., 2023, Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States (ver. 1.1, May 2025): U.S. Geological 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Geological Survey<br>2329 West Orton Circle<br>Salt Lake City, Utah 84119-2047</p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Science Strategy for Terminal Lakes of the Great Basin</li><li>Adaptive Implementation Framework</li><li>Summary</li><li>References Cited</li><li>Appendixes 1– 3</li></ul>","publishedDate":"2023-12-22","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Frus, Rebecca J. 0000-0002-2435-7202","orcid":"https://orcid.org/0000-0002-2435-7202","contributorId":206261,"corporation":false,"usgs":true,"family":"Frus","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 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ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":215925,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":890391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herring, Garth 0000-0003-1106-4731 gherring@usgs.gov","orcid":"https://orcid.org/0000-0003-1106-4731","contributorId":4403,"corporation":false,"usgs":true,"family":"Herring","given":"Garth","email":"gherring@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":890392,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hynek, Scott A. 0000-0002-6885-0445","orcid":"https://orcid.org/0000-0002-6885-0445","contributorId":52091,"corporation":false,"usgs":true,"family":"Hynek","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":false,"id":890393,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":332532,"corporation":false,"usgs":false,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":false,"id":890394,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kemp, Susan K 0000-0002-8183-5741 skemp@usgs.gov","orcid":"https://orcid.org/0000-0002-8183-5741","contributorId":5889,"corporation":false,"usgs":true,"family":"Kemp","given":"Susan","email":"skemp@usgs.gov","middleInitial":"K","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":890395,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Marston, Thomas M. 0000-0003-1053-4172 tmarston@usgs.gov","orcid":"https://orcid.org/0000-0003-1053-4172","contributorId":3272,"corporation":false,"usgs":true,"family":"Marston","given":"Thomas","email":"tmarston@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890396,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Morris, Christopher M. 0000-0002-0477-7605 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,{"id":70250772,"text":"70250772 - 2023 - Train, inform, borrow, or combine? Approaches to process-guided deep learning for groundwater-influenced stream temperature prediction","interactions":[],"lastModifiedDate":"2024-01-04T12:51:48.498521","indexId":"70250772","displayToPublicDate":"2023-12-22T06:44:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Train, inform, borrow, or combine? Approaches to process-guided deep learning for groundwater-influenced stream temperature prediction","docAbstract":"<div class=\"article-section__content en main\"><p>Although groundwater discharge is a critical stream temperature control process, it is not explicitly represented in many stream temperature models, an omission that may reduce predictive accuracy, hinder management of aquatic habitat, and decrease user confidence. We assessed the performance of a previously-described process-guided deep learning model of stream temperature in the Delaware River Basin (USA). We found lower accuracy (root mean square error [RMSE] of 1.71 versus 1.35°C) and stronger seasonal bias (absolute mean monthly bias of 1.06 vs. 0.68°C) for reaches primarily influenced by deep groundwater as compared to atmospheric conditions. We then tested four approaches for improving groundwater process representation: (a) a custom loss function leveraging the unique patterns of air and water temperature coupling characteristic of different temperature drivers, (b) inclusion of additional groundwater-relevant catchment attributes, (c) incorporation of additional process model outputs, and (d) a composite model. The custom loss function and the additional attributes significantly improved the predictive accuracy in groundwater-dominated reaches (RMSE of 1.37 and 1.26°C) and reduced the seasonal bias (absolute mean monthly bias of 0.44 and 0.48°C), but neither approach could identify holdout groundwater reaches. Variable importance analysis indicates the custom loss function nudges the model to use the existing inputs more efficiently, whereas with the added features the model relies on a broader suite of inputs. This analysis is a substantial step toward more accurately representing groundwater discharge processes in stream temperature models and will improve predictive accuracy and inform habitat management.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR035327","usgsCitation":"Barclay, J.R., Topp, S.N., Koenig, L.E., Sleckman, M.J., and Appling, A.P., 2023, Train, inform, borrow, or combine? Approaches to process-guided deep learning for groundwater-influenced stream temperature prediction: Water Resources Research, v. 59, no. 12, e2023WR035327, 19 p., https://doi.org/10.1029/2023WR035327.","productDescription":"e2023WR035327, 19 p.","ipdsId":"IP-150248","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":441375,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr035327","text":"Publisher Index Page"},{"id":435108,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KO49OT","text":"USGS data release","linkHelpText":"Model Code, Outputs, and Supporting Data for Approaches to Process-Guided Deep Learning for Groundwater-Influenced Stream Temperature Predictions"},{"id":424108,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -76.0,\n              38.46095870619746\n            ],\n            [\n              -74.27398526052804,\n              38.46095870619746\n            ],\n            [\n              -74.27398526052804,\n              42.406071951802744\n            ],\n            [\n              -76,\n              42.406071951802744\n            ],\n            [\n              -76,\n              38.46095870619746\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"59","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topp, Simon Nemer 0000-0001-7741-5982","orcid":"https://orcid.org/0000-0001-7741-5982","contributorId":268229,"corporation":false,"usgs":true,"family":"Topp","given":"Simon","email":"","middleInitial":"Nemer","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":891361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koenig, Lauren Elizabeth 0000-0002-7790-330X","orcid":"https://orcid.org/0000-0002-7790-330X","contributorId":295259,"corporation":false,"usgs":true,"family":"Koenig","given":"Lauren","email":"","middleInitial":"Elizabeth","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":891362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sleckman, Margaux Jeanne 0000-0002-1843-6932","orcid":"https://orcid.org/0000-0002-1843-6932","contributorId":295257,"corporation":false,"usgs":true,"family":"Sleckman","given":"Margaux","email":"","middleInitial":"Jeanne","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":891363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":891364,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70252083,"text":"70252083 - 2023 - A decade of death and other dynamics: Deepening perspectives on the diversity and distribution of sea stars and wasting","interactions":[],"lastModifiedDate":"2024-03-13T11:42:12.578809","indexId":"70252083","displayToPublicDate":"2023-12-22T06:41:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1014,"text":"Biological Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"A decade of death and other dynamics: Deepening perspectives on the diversity and distribution of sea stars and wasting","docAbstract":"<div class=\"col-lg-9 article__content\"><div class=\"article__body show-references \"><div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Mass mortality events provide valuable insight into biological extremes and also ecological interactions more generally. The sea star wasting epidemic that began in 2013 catalyzed study of the microbiome, genetics, population dynamics, and community ecology of several high-profile species inhabiting the northeastern Pacific but exposed a dearth of information on the diversity, distributions, and impacts of sea star wasting for many lesser-known sea stars and a need for integration across scales. Here, we combine datasets from single-site to coast-wide studies, across time lines from weeks to decades, for 65 species. We evaluated the impacts of abiotic characteristics hypothetically associated with sea star wasting (sea surface temperature, pelagic primary productivity, upwelling wind forcing, wave exposure, freshwater runoff) and species characteristics (depth distribution, developmental mode, diet, habitat, reproductive period). We find that the 2010s sea star wasting outbreak clearly affected a little over a dozen species, primarily intertidal and shallow subtidal taxa, causing instantaneous wasting prevalence rates of 5%–80%. Despite the collapse of some populations within weeks, environmental and species variation protracted the outbreak, which lasted 2–3 years from onset until declining to chronic background rates of ∼2% sea star wasting prevalence. Recruitment began immediately in many species, and in general, sea star assemblages trended toward recovery; however, recovery was heterogeneous, and a marine heatwave in 2019 raised concerns of a second decline. The abiotic stressors most associated with the 2010s sea star wasting outbreak were elevated sea surface temperature and low wave exposure, as well as freshwater discharge in the north. However, detailed data speaking directly to the biological, ecological, and environmental cause(s) and consequences of the sea star wasting outbreak remain limited in scope, unavoidably retrospective, and perhaps always indeterminate. Redressing this shortfall for the future will require a broad spectrum of monitoring studies not less than the taxonomically broad cross-scale framework we have modeled in this synthesis.</p></div></div></div></div>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/727969","usgsCitation":"Dawson, M., Duffin, P., Giakoumis, M., Schiebelhut, L.M., Beas-Luna, R., Bosley, K., Castilho, R., Ewers-Saucedo, C., Gavenus, K., Keller, A., Konar, B., Largier, J.L., Lorda, J., Miner, M., Moritsch, M., Navarette, S., Raimondi, P.T., Traiger, S.B., Turner, M., and Wares, J., 2023, A decade of death and other dynamics: Deepening perspectives on the diversity and distribution of sea stars and wasting: Biological Bulletin, v. 244, no. 3, https://doi.org/10.1086/727969.","ipdsId":"IP-131426","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":441377,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/56754","text":"External Repository"},{"id":426574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"244","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dawson, Michael","contributorId":334800,"corporation":false,"usgs":false,"family":"Dawson","given":"Michael","affiliations":[{"id":16805,"text":"University of California, Merced","active":true,"usgs":false}],"preferred":false,"id":896550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duffin, Paige","contributorId":295356,"corporation":false,"usgs":false,"family":"Duffin","given":"Paige","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":896551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giakoumis, Melina","contributorId":334801,"corporation":false,"usgs":false,"family":"Giakoumis","given":"Melina","email":"","affiliations":[{"id":39562,"text":"City University of New York","active":true,"usgs":false}],"preferred":false,"id":896552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schiebelhut, Lauren M","contributorId":295369,"corporation":false,"usgs":false,"family":"Schiebelhut","given":"Lauren","email":"","middleInitial":"M","affiliations":[{"id":54780,"text":"UC Merced","active":true,"usgs":false}],"preferred":false,"id":896553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beas-Luna, Rodrigo","contributorId":127447,"corporation":false,"usgs":false,"family":"Beas-Luna","given":"Rodrigo","email":"","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":896554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bosley, Keith","contributorId":334802,"corporation":false,"usgs":false,"family":"Bosley","given":"Keith","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":896555,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Castilho, Rita","contributorId":334803,"corporation":false,"usgs":false,"family":"Castilho","given":"Rita","email":"","affiliations":[{"id":80253,"text":"University of Algarve","active":true,"usgs":false}],"preferred":false,"id":896556,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ewers-Saucedo, Christine","contributorId":334804,"corporation":false,"usgs":false,"family":"Ewers-Saucedo","given":"Christine","email":"","affiliations":[{"id":80254,"text":"Zoological Museum Christian-Albrechts University","active":true,"usgs":false}],"preferred":false,"id":896557,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gavenus, Katie","contributorId":334805,"corporation":false,"usgs":false,"family":"Gavenus","given":"Katie","email":"","affiliations":[{"id":80255,"text":"Center for Alaskan Coastal Studies","active":true,"usgs":false}],"preferred":false,"id":896558,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Keller, Aimee","contributorId":334806,"corporation":false,"usgs":false,"family":"Keller","given":"Aimee","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":896559,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Konar, Brenda","contributorId":131034,"corporation":false,"usgs":false,"family":"Konar","given":"Brenda","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":896560,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Largier, John L.","contributorId":175121,"corporation":false,"usgs":false,"family":"Largier","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":896561,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lorda, Julio","contributorId":334807,"corporation":false,"usgs":false,"family":"Lorda","given":"Julio","affiliations":[{"id":34468,"text":"Universidad Autonoma de Baja California","active":true,"usgs":false}],"preferred":false,"id":896562,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Miner, Melissa","contributorId":334808,"corporation":false,"usgs":false,"family":"Miner","given":"Melissa","email":"","affiliations":[{"id":80256,"text":"University of Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":896563,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Moritsch, Monica","contributorId":304091,"corporation":false,"usgs":false,"family":"Moritsch","given":"Monica","affiliations":[{"id":65966,"text":"EDF","active":true,"usgs":false}],"preferred":false,"id":896564,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Navarette, Sergio","contributorId":334809,"corporation":false,"usgs":false,"family":"Navarette","given":"Sergio","email":"","affiliations":[{"id":66274,"text":"Pontifica Universidad Catolica de Chile","active":true,"usgs":false}],"preferred":false,"id":896565,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Raimondi, Peter T.","contributorId":139302,"corporation":false,"usgs":false,"family":"Raimondi","given":"Peter","email":"","middleInitial":"T.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":896566,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Traiger, Sarah Beth 0000-0002-6222-1445","orcid":"https://orcid.org/0000-0002-6222-1445","contributorId":293218,"corporation":false,"usgs":true,"family":"Traiger","given":"Sarah","email":"","middleInitial":"Beth","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":896567,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Turner, Monica","contributorId":193037,"corporation":false,"usgs":false,"family":"Turner","given":"Monica","affiliations":[],"preferred":false,"id":896568,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wares, John","contributorId":177199,"corporation":false,"usgs":false,"family":"Wares","given":"John","affiliations":[],"preferred":false,"id":896569,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}}
,{"id":70251923,"text":"70251923 - 2023 - Identifying structural priors in a hybrid differentiable model for stream water temperature modeling","interactions":[],"lastModifiedDate":"2024-03-07T13:01:44.619138","indexId":"70251923","displayToPublicDate":"2023-12-21T06:59:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Identifying structural priors in a hybrid differentiable model for stream water temperature modeling","docAbstract":"<div class=\"article-section__content en main\"><div class=\"article-section__content en main\"><p>Although deep learning models for stream temperature (<i>T</i><sub>s</sub>) have recently shown exceptional accuracy, they have limited interpretability and cannot output untrained variables. With hybrid differentiable models, neural networks (NNs) can be connected to physically based equations (called structural priors) to output intermediate variables such as water source fractions (specifying what portion of water is groundwater, subsurface, and surface flow). However, it is unclear if such outputs are physically meaningful when only limited physics is imposed, and if structural priors have enough impacts to be identifiable from data. Here, we tested four alternative structural priors describing basin-scale water temperature memory and instream heat processes in a differentiable stream temperature model where NNs freely estimate the water source fractions. We evaluated models’ abilities to predict<span>&nbsp;</span><i>T</i><sub>s</sub><span>&nbsp;</span>and baseflow ratio. The four priors exhibited noticeably different behaviors in these two metrics and their tradeoffs, with some dominating others. Therefore, the better structural priors can be identified. Moreover, testing different priors yielded valuable insights: having a separate shallow subsurface flow component better matches observations, and a recency-weighted averaging of past air temperature for calculating source water temperature resulted in better<span>&nbsp;</span><i>T</i><sub>s</sub><span>&nbsp;</span>and baseflow prediction than traditionally employed simple averaging. However, we also highlight the limitations when insufficient physical constraints are implemented: the internal variables (water source fractions) may not be adequately constrained by a single target variable (stream temperature) alone. To ensure the physical significance of the internal fluxes, one can either employ multivariate data for model selection, or include more physical processes in the priors.</p></div></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR034420","usgsCitation":"Rahmani, F., Appling, A.P., Feng, D., Lawson, K., and Shen, C., 2023, Identifying structural priors in a hybrid differentiable model for stream water temperature modeling: Water Resources Research, v. 59, no. 12, e2023WR034420, 21 p., https://doi.org/10.1029/2023WR034420.","productDescription":"e2023WR034420, 21 p.","ipdsId":"IP-148327","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":441379,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr034420","text":"Publisher Index Page"},{"id":426426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Rahmani, Farshid","contributorId":265775,"corporation":false,"usgs":false,"family":"Rahmani","given":"Farshid","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":896103,"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":896104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feng, Dapeng 0000-0002-5653-6504","orcid":"https://orcid.org/0000-0002-5653-6504","contributorId":317078,"corporation":false,"usgs":false,"family":"Feng","given":"Dapeng","email":"","affiliations":[{"id":68932,"text":"Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA, USA","active":true,"usgs":false}],"preferred":false,"id":896105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawson, Kathryn","contributorId":265776,"corporation":false,"usgs":false,"family":"Lawson","given":"Kathryn","affiliations":[{"id":54792,"text":"Civil and Environmental Engineering, Pennsylvania State University, University Park, PA","active":true,"usgs":false}],"preferred":false,"id":896106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shen, Chaopeng","contributorId":152465,"corporation":false,"usgs":false,"family":"Shen","given":"Chaopeng","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":896107,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70251950,"text":"70251950 - 2023 - Satellite-derived prefire vegetation predicts variation in field-based invasive annual grass cover after fire","interactions":[],"lastModifiedDate":"2024-03-07T12:47:38.158193","indexId":"70251950","displayToPublicDate":"2023-12-21T06:44:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Satellite-derived prefire vegetation predicts variation in field-based invasive annual grass cover after fire","docAbstract":"<h3 id=\"avsc12759-sec-0001-title\" class=\"article-section__sub-title section1\">Aims</h3><p>Invasion by annual grasses (IAGs) and concomitant increases in wildfire are impacting many drylands globally, and an understanding of factors that contribute to or detract from community resistance to IAGs is needed to inform postfire restoration interventions. Prefire vegetation condition is often unknown in rangelands but it likely affects variation in postfire invasion resistance across large burned scars. Whether satellite-derived products like the Rangeland Analysis Platform (RAP) can fulfill prefire information needs and be used to parametrize models of fire recovery to inform postfire management of IAGs is a key question.</p><h3 id=\"avsc12759-sec-0002-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We used random forests to ask how IAG abundances in 669 field plots measured in the 2-3 years following megafires in sagebrush steppe rangelands of western USA responded to RAP estimates of annual:perennial prefire vegetation cover, the effects of elevation, heat load, postfire treatments, soil moisture–temperature regimes, and land-agency ratings of ecosystem resistance to invasion and resilience to disturbance.</p><h3 id=\"avsc12759-sec-0003-title\" class=\"article-section__sub-title section1\">Results</h3><p>Postfire IAG cover measured in the field was<span>&nbsp;</span>22¯% and RAP-estimated prefire annual herbaceous cover was<span>&nbsp;</span>15.7¯%. The random forest model had an<span>&nbsp;</span><i>R</i><sup>2</sup><span>&nbsp;</span>of 0.36 and a root-mean-squared error (RMSE) of 4.41. Elevation, postfire herbicide treatment, and prefire estimates from RAP for the ratio of annual:perennial and shrub cover were the most important predictors of postfire IAG cover. Threshold-like relationships between postfire IAG cover and the predictors indicate that maintaining annual:perennial cover below 0.4 and shrub cover below &lt;10% prior to wildfire would decrease invasion, at low elevations below 1400 m above sea level.</p><h3 id=\"avsc12759-sec-0004-title\" class=\"article-section__sub-title section1\">Conclusion</h3><p>Despite known differences between RAP and field-based estimates of vegetation cover, RAP was still a useful predictor of variation in IAG abundances after fire. IAG management is oftentimes reactive, but our findings indicate impactful roles for more inclusively addressing the exotic annual community, and focusing on prefire maintenance of annual:perennial herbaceous and shrub cover at low elevations.</p>","language":"English","publisher":"Wiley","doi":"10.1111/avsc.12759","usgsCitation":"Anthony, C.A., Applestein, C., and Germino, M., 2023, Satellite-derived prefire vegetation predicts variation in field-based invasive annual grass cover after fire: Applied Vegetation Science, v. 26, no. 4, e12759, 11 p., https://doi.org/10.1111/avsc.12759.","productDescription":"e12759, 11 p.","ipdsId":"IP-153942","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":426424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Anthony, Christopher A 0000-0003-0968-224X","orcid":"https://orcid.org/0000-0003-0968-224X","contributorId":334644,"corporation":false,"usgs":false,"family":"Anthony","given":"Christopher","email":"","middleInitial":"A","affiliations":[{"id":80198,"text":"USFWS (current)","active":true,"usgs":false}],"preferred":false,"id":896157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":205748,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":896158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":896159,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70256474,"text":"70256474 - 2023 - Achieving success with RISE: A widely implementable, iterative, structured process for mastering interdisciplinary team science collaborations","interactions":[],"lastModifiedDate":"2024-08-08T10:55:46.557875","indexId":"70256474","displayToPublicDate":"2023-12-20T10:49:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Achieving success with RISE: A widely implementable, iterative, structured process for mastering interdisciplinary team science collaborations","docAbstract":"<p><span>Scientific experts from different disciplines often struggle to mesh their specialized perspectives into the shared mindset that is needed to address difficult and persistent environmental, ecological, and societal problems. Many traditional graduate programs provide excellent research and technical skill training. However, these programs often do not teach a systematic way to learn team skills, nor do they offer a protocol for identifying and tackling increasingly integrated interdisciplinary (among disciplines) and transdisciplinary (among researchers and stakeholders) questions. As a result, professionals trained in traditional graduate programs (e.g., current graduate students and employed practitioners) may not have all of the collaborative skills needed to advance solutions to difficult scientific problems. In the present article, we illustrate a tractable, widely implementable structured process called RISE that accelerates the development of these missing skills. The RISE process (Route to Identifying, learning, and practicing interdisciplinary and transdisciplinary team Skills to address difficult Environmental problems) can be used by diverse teams as a tool for research, professional interactions, or training. RISE helps professionals with different expertise learn from each other by repeatedly asking team-developed questions that are tested using an interactive quantitative tool (e.g., agent-based models, machine learning, case studies) applied to a shared problem framework and data set. Outputs from the quantitative tool are then discussed and interpreted as a team, considering all team members’ perspectives, disciplines, and expertise. After this synthesis, RISE is repeated with new questions that the team jointly identified in earlier data interpretation discussions. As a result, individual perspectives, originally informed by disciplinary training, are complemented by a shared understanding of team function and elevated interdisciplinary knowledge.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biad097","usgsCitation":"Mather, M.E., Granco, G., Bergtold, J., Caldas, M., Heier Stamm, J., Sheshukov, A., Sanderson, M., and Daniels, M., 2023, Achieving success with RISE: A widely implementable, iterative, structured process for mastering interdisciplinary team science collaborations: BioScience, v. 73, no. 12, p. 891-905, https://doi.org/10.1093/biosci/biad097.","productDescription":"15 p.","startPage":"891","endPage":"905","ipdsId":"IP-148659","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441388,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biad097","text":"Publisher Index Page"},{"id":432344,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mather, Martha E. 0000-0003-0827-3006 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-0827-3006","contributorId":340771,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granco, Gabriel","contributorId":340772,"corporation":false,"usgs":false,"family":"Granco","given":"Gabriel","email":"","affiliations":[{"id":66019,"text":"Cal Poly Pomona","active":true,"usgs":false}],"preferred":false,"id":907538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergtold, Jason","contributorId":340773,"corporation":false,"usgs":false,"family":"Bergtold","given":"Jason","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldas, Marcellus","contributorId":340774,"corporation":false,"usgs":false,"family":"Caldas","given":"Marcellus","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heier Stamm, Jessica","contributorId":340775,"corporation":false,"usgs":false,"family":"Heier Stamm","given":"Jessica","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sheshukov, Aleksey","contributorId":340776,"corporation":false,"usgs":false,"family":"Sheshukov","given":"Aleksey","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sanderson, Matthew","contributorId":340777,"corporation":false,"usgs":false,"family":"Sanderson","given":"Matthew","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907543,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Daniels, Melinda","contributorId":340778,"corporation":false,"usgs":false,"family":"Daniels","given":"Melinda","affiliations":[{"id":37456,"text":"Stroud Water Research Center","active":true,"usgs":false}],"preferred":false,"id":907544,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70250593,"text":"pp1842LL - 2023 - The effects of management practices on grassland birds—Bobolink (<em>Dolichonyx oryzivorus</em>)","interactions":[{"subject":{"id":70250593,"text":"pp1842LL - 2023 - The effects of management practices on grassland birds—Bobolink (<em>Dolichonyx oryzivorus</em>)","indexId":"pp1842LL","publicationYear":"2023","noYear":false,"chapter":"LL","displayTitle":"The Effects of Management Practices on Grassland Birds—Bobolink (<em>Dolichonyx oryzivorus</em>)","title":"The effects of management practices on grassland birds—Bobolink (<em>Dolichonyx oryzivorus</em>)"},"predicate":"IS_PART_OF","object":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"id":1}],"isPartOf":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"lastModifiedDate":"2024-06-26T14:36:14.181107","indexId":"pp1842LL","displayToPublicDate":"2023-12-19T13:44:15","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1842","chapter":"LL","displayTitle":"The Effects of Management Practices on Grassland Birds—Bobolink (<em>Dolichonyx oryzivorus</em>)","title":"The effects of management practices on grassland birds—Bobolink (<em>Dolichonyx oryzivorus</em>)","docAbstract":"<p>Keys to Bobolink (<i>Dolichonyx oryzivorus</i>) management are providing large areas of suitable habitat (for example, native or tame grasslands of moderate vegetative height and density, low shrub density, and moderate litter and forb cover), and protecting nesting habitat from disturbance during the breeding season. Bobolinks have been reported to use habitats with 10–166 centimeters (cm) average vegetation height, 6–75 cm visual obstruction reading, 17–65 percent grass cover, 3–50 percent forb cover, less than or equal to (≤) 22 percent shrub cover, ≤38 percent bare ground, 5–39 percent litter cover, and ≤9 cm litter depth.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842LL","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Zimmerman, A.L., Wooten, T.L., and Euliss, B.R., 2023, The effects of management practices on grassland birds—Bobolink (<i>Dolichonyx oryzivorus</i>), chap. LL <i>of</i> Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 44 p., https://doi.org/10.3133/pp1842LL.","productDescription":"v, 44 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-097127","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":423745,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/ll/coverthb.jpg"},{"id":423746,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/ll/pp1842ll.pdf","text":"Report","size":"2.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–LL"}],"contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/northern-prairie-wildlife-research-center\" href=\"https://www.usgs.gov/centers/northern-prairie-wildlife-research-center\">Northern Prairie Wildlife Research Center</a><br>U.S. Geological Survey<br>8711 37th Street Southeast<br>Jamestown, North Dakota 58401</p><p><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Capsule Statement</li><li>Breeding Range</li><li>Suitable Habitat</li><li>Area Requirements and Landscape Associations</li><li>Brood Parasitism by Cowbirds and Other Species</li><li>Breeding-Season Phenology and Site Fidelity</li><li>Species’ Response to Management</li><li>Management Recommendations from the Literature</li><li>References</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-19","noUsgsAuthors":false,"publicationDate":"2023-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Jill A. 0000-0003-3172-0708","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":214803,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":890488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Igl, Lawrence D. 0000-0003-0530-7266","orcid":"https://orcid.org/0000-0003-0530-7266","contributorId":220514,"corporation":false,"usgs":true,"family":"Igl","given":"Lawrence D.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":890489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Douglas H. 0000-0002-7778-6641","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":221269,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":890490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sondreal, Marriah L.","contributorId":215631,"corporation":false,"usgs":false,"family":"Sondreal","given":"Marriah","email":"","middleInitial":"L.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":890491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldade, Christopher M.","contributorId":215632,"corporation":false,"usgs":false,"family":"Goldade","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":890492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimmerman, Amy L.","contributorId":217210,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Amy","email":"","middleInitial":"L.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":890493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wooten, Travis L.","contributorId":215633,"corporation":false,"usgs":false,"family":"Wooten","given":"Travis","email":"","middleInitial":"L.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":890494,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Euliss, Betty R.","contributorId":191881,"corporation":false,"usgs":false,"family":"Euliss","given":"Betty","email":"","middleInitial":"R.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":890495,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70250603,"text":"70250603 - 2023 - Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum)","interactions":[],"lastModifiedDate":"2023-12-19T12:50:26.049418","indexId":"70250603","displayToPublicDate":"2023-12-19T06:32:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3824,"text":"Letters in Biomathematics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (<i>Hypophthalmichthys molitrix</i>) and gizzard shad (<i>Dorosoma cepedianum</i>)","title":"Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum)","docAbstract":"<p><span>As a generalization of stage-based matrix models, integral projection models&nbsp;(IPMs) have been used to describe the size-based dynamics of wildlife and fisheries populations. Although some matrix models have explicitly included species interactions, few IPMs have expanded beyond single species, which limits their ability to describe the competitive dynamics of co-occuring taxa. We present a coupled system of IPMs where intra- and inter-specific competition may reciprocally affect the life-histories of two species. We investigated the potential role that competition has on two overlapping fish species in the upper Mississippi River system: the native gizzard shad (</span><i>Dorosoma cepedianum</i><span>) and the invasive silver carp (</span><i>Hypophthalmichthys molitrix</i><span>). Numerical simulations of this system indicated that the coupled IPMs could exhibit asymptotic behaviors similar to traditional, non-linear competition models. Specifically, by altering the competition coefficients, we demonstrate this model's ability to detect competitive exclusion, species coexistence, and dual extinction outcomes.</span></p>","language":"English","publisher":"Intercollegiate Biomathematics Alliance","usgsCitation":"Peirce, J.P., Sandland, G., Schumann, D., Thompson, H.M., and Erickson, R.A., 2023, Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum): Letters in Biomathematics, v. 10, no. 1, p. 175-184.","productDescription":"10 p.","startPage":"175","endPage":"184","ipdsId":"IP-156781","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":423743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423740,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://lettersinbiomath.journals.publicknowledgeproject.org/index.php/lib/article/view/645"}],"volume":"10","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peirce, James P 0000-0002-7147-3695","orcid":"https://orcid.org/0000-0002-7147-3695","contributorId":316559,"corporation":false,"usgs":false,"family":"Peirce","given":"James","email":"","middleInitial":"P","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":890531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandland, Gregory","contributorId":332579,"corporation":false,"usgs":false,"family":"Sandland","given":"Gregory","email":"","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":890532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schumann, David","contributorId":199504,"corporation":false,"usgs":false,"family":"Schumann","given":"David","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":890533,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Hannah Mann 0000-0001-8316-3232","orcid":"https://orcid.org/0000-0001-8316-3232","contributorId":316560,"corporation":false,"usgs":true,"family":"Thompson","given":"Hannah","email":"","middleInitial":"Mann","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890534,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890535,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70259695,"text":"70259695 - 2023 - Two-dimensional inverse energy cascade in a laboratory surf zone for varying wave directional spread","interactions":[],"lastModifiedDate":"2024-10-21T11:29:40.817354","indexId":"70259695","displayToPublicDate":"2023-12-19T06:26:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3070,"text":"Physics of Fluids","active":true,"publicationSubtype":{"id":10}},"title":"Two-dimensional inverse energy cascade in a laboratory surf zone for varying wave directional spread","docAbstract":"<p><span>Surfzone eddies enhance the dispersion and transport of contaminants, bacteria, and larvae across the nearshore, altering coastal water quality and ecosystem health. During directionally spread wave conditions, vertical vortices (horizontal eddies) are injected near the ends of breaking crests. Energy associated with these eddies may be transferred to larger-scale, low-frequency rotational motions through an inverse energy cascade, consistent with two-dimensional turbulence. However, our understanding of the relationships between the wave conditions and the dynamics and energetics of low-frequency surfzone eddies are largely based on numerical modeling. Here, we test these relationships with remotely sensed and&nbsp;</span><i>in situ</i><span>&nbsp;observations from large-scale directional wave basin experiments with varying wave conditions over alongshore-uniform barred bathymetry. Surface velocities derived with particle image velocimetry were employed to assess the spatial scales of low-frequency surfzone eddies and compute structure functions with alongshore velocities. Second-order structure functions for directionally spread waves (</span><span class=\"inline-formula no-formula-id\">⁠<span>&nbsp;</span></span></p>","language":"English","publisher":"AIP Publishing","doi":"10.1063/5.0169895","usgsCitation":"Baker, C., Moulton, M., Chickadel, C.C., Nuss, E., Palmsten, M.L., and Brodie, K.L., 2023, Two-dimensional inverse energy cascade in a laboratory surf zone for varying wave directional spread: Physics of Fluids, v. 35, 125140, 18 p., https://doi.org/10.1063/5.0169895.","productDescription":"125140, 18 p.","ipdsId":"IP-156274","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467067,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1063/5.0169895","text":"Publisher Index Page"},{"id":463055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationDate":"2023-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Baker, Christine","contributorId":305678,"corporation":false,"usgs":false,"family":"Baker","given":"Christine","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":916354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moulton, Melissa","contributorId":194341,"corporation":false,"usgs":false,"family":"Moulton","given":"Melissa","email":"","affiliations":[],"preferred":false,"id":916355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chickadel, C Chris 0000-0002-0770-7725","orcid":"https://orcid.org/0000-0002-0770-7725","contributorId":221998,"corporation":false,"usgs":false,"family":"Chickadel","given":"C","email":"","middleInitial":"Chris","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":916356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nuss, Emma","contributorId":305681,"corporation":false,"usgs":false,"family":"Nuss","given":"Emma","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":916357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Palmsten, Margaret L. 0000-0002-6424-2338","orcid":"https://orcid.org/0000-0002-6424-2338","contributorId":239955,"corporation":false,"usgs":true,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":916358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brodie, Katherine L.","contributorId":345330,"corporation":false,"usgs":false,"family":"Brodie","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":916359,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250567,"text":"ofr20231077 - 2023 - Applying intrinsic potential models to evaluate salmon (Oncorhynchus spp.) introduction into main-stem and tributary habitats upstream from the Skagit River Hydroelectric Project, northern Washington","interactions":[],"lastModifiedDate":"2024-12-03T19:37:33.744214","indexId":"ofr20231077","displayToPublicDate":"2023-12-18T14:53:20","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1077","displayTitle":"Applying Intrinsic Potential Models to Evaluate Salmon (<em>Oncorhynchus spp.</em>) Introduction into Main-Stem and Tributary Habitats Upstream from the Skagit River Hydroelectric Project, Northern Washington","title":"Applying intrinsic potential models to evaluate salmon (Oncorhynchus spp.) introduction into main-stem and tributary habitats upstream from the Skagit River Hydroelectric Project, northern Washington","docAbstract":"<p>We assessed habitat suitability for salmonids across selected tributaries upstream from three hydroelectric dams on the upper Skagit River in Whatcom County, northern Washington. We used NetMap, a commercial toolset within the ArcMap geographic information system (GIS), to analyze stream attributes based upon a synthetic stream channel network derived from digital elevation models. The GIS-derived stream attributes—including gradient, bankfull width, valley width index, elevation, and stream flow—allowed us to examine the spatial distribution and relative quality of spawning and rearing habitat for salmonids based on existing intrinsic potential (IP) models. As a first step, we created maps of potential anadromous fish distribution by identifying potential migration barriers within the synthetic stream network. Next, we applied a suite of existing IP models for steelhead, coho, and Chinook salmon (<i>Oncorhynchus mykiss</i>, <i>O. kisutch</i>, and <i>O. tshawytscha</i>, respectively) to estimate low, medium, and high IP habitat for each species. Three different IP models were used for each species, based on species preference curves from populations from coastal Oregon, northern California, Alaska, and western Washington. We found that at least 25 tributaries that were greater than third order and contained habitat with the potential for anadromous fish, totaling about 470 river kilometers in 4,453 synthetic stream reaches averaging about 100 meters (m) in length. The IP of each of these reaches was calculated and placed into low, medium, and high IP categories. For Chinook salmon, the only stream with significantly (in other words, greater than 1 kilometer [km]) high IP reaches was the upper Skagit River upstream from Ross Lake reservoir in Canada, upstream from the third dam in the hydroelectric system. There were differences among the three models evaluated, with the model derived for the lower Skagit River showing more high and medium IP habitat than the other two models that were designed for the Columbia River Basin. For coho salmon, all three models showed similar results favoring medium IP over low and high IP habitat. Of the 3 species examined with existing IP models, steelhead had the most habitat rated as high IP with 19 targeted tributaries showing greater than 1 km of high intrinsic potential habitat.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231077","collaboration":"Prepared in cooperation with Seattle City Light","usgsCitation":"Duda, J.J., and Hardiman, J.M., 2023, Applying intrinsic potential models to evaluate salmon (Oncorhynchus spp.) introduction into main-stem and tributary habitats upstream from the Skagit River Hydroelectric Project, northern Washington: U.S. Geological Survey Open-File Report 2023-1077, 44 p. https://doi.org/10.3133/ofr20231077.","productDescription":"Report: viii, 44 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-147497","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":423653,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.XML"},{"id":423733,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MKQ2UK","text":"USGS data release","description":"USGS data release","linkHelpText":"Upper Skagit River intrinsic potential results"},{"id":423650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.pdf"},{"id":423649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.jpg"},{"id":423652,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1077/Images"},{"id":423651,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231077/full"}],"country":"Canada, United States","state":"Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.3,\n              49.3\n            ],\n            [\n              -121.3,\n              48.3\n            ],\n            [\n              -120.3,\n              48.3\n            ],\n            [\n               -120.3,\n              49.3\n            ],\n            [\n              -121.3,\n              49.3\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/wfrc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/wfrc\">Western Fisheries Research Center</a><br>U.S. Geological Survey<br>6505 NE 65th Street<br>Seattle, Washington 98115-5016</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Methodology</li><li>Results and Interpretations</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2023-12-18","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":890407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hardiman, Jill M. 0000-0002-3661-9695 jhardiman@usgs.gov","orcid":"https://orcid.org/0000-0002-3661-9695","contributorId":2672,"corporation":false,"usgs":true,"family":"Hardiman","given":"Jill","email":"jhardiman@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":890408,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70256475,"text":"70256475 - 2023 - The context dependency of fish-habitat associations in separated karst ecoregions","interactions":[],"lastModifiedDate":"2024-08-07T16:04:22.691671","indexId":"70256475","displayToPublicDate":"2023-12-18T10:54:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"The context dependency of fish-habitat associations in separated karst ecoregions","docAbstract":"<p><span>Fish populations may be isolated via natural conditions in geographically separated ecoregions. Although reconnecting these populations is not a management goal, we need to understand how these populations persist across landscapes to develop meaningful conservation actions, particularly for species occupying sensitive karst ecosystems. Our study objective was to determine the physicochemical factors related to the occurrence of four spring-associated fishes. Arbuckle Uplift and Ozark Highlands ecoregions, USA. We used a hierarchical approach to identify habitat relationships at multiple spatial scales. We collected detection data using snorkeling and seining. We examined the physicochemical relationships related to the detection and occurrence of four spring-associated fishes using occupancy modeling in a Bayesian framework. We found physicochemical relationships that differed and were similar between ecoregions for several fishes. For three species, we found different water temperature relationships between ecoregions. Smallmouth bass were ubiquitous in their use of drainage areas in the Ozark Highlands but only associated with the lower network of the Arbuckle Uplift. There were several mirrored relationships between ecoregions, including an interaction between residual pool depth and water temperature, where sites with deeper pools were more likely to be occupied during warmer water temperatures. There were single-species occurrence relationships with percent vegetation and percent agriculture. Lastly, snorkeling was a more efficient sampling method compared to seining for all fishes. Our results indicate stream temperature mitigation may be possible via the maintenance of key channel morphologies, and we identify shared stressors between ecoregions. Channel mitigation to maintain reaches with deeper pools may be an important strategy for maintaining thermal refugia, particularly when considering climate change. Identifying the mechanistic underpinning of other multiscale ecological relationships would be helpful to discern if some of the different ecoregion relationships represent warning signals or interactions with unmeasured biotic or abiotic factors.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10701","usgsCitation":"Swedberg, D.A., Mollenhauer, R.M., and Brewer, S.K., 2023, The context dependency of fish-habitat associations in separated karst ecoregions: Ecology and Evolution, v. 13, no. 12, e10701, 18 p., https://doi.org/10.1002/ece3.10701.","productDescription":"e10701, 18 p.","ipdsId":"IP-146272","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441399,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10701","text":"Publisher Index Page"},{"id":432361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -94.6056935051375,\n              36.99095780343694\n            ],\n            [\n              -95.25818479665297,\n              36.77262795781087\n            ],\n            [\n              -95.51281809235115,\n              35.597221761955254\n            ],\n            [\n              -94.4536118118592,\n              35.530687987028585\n            ],\n            [\n              -94.6056935051375,\n              36.99095780343694\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -97.16528274367352,\n              34.594939532905144\n            ],\n            [\n              -97.44206576958777,\n              33.94434112413069\n            ],\n            [\n              -96.10069816898147,\n              33.94433280692786\n            ],\n            [\n              -96.13328126204877,\n              34.75563707296074\n            ],\n            [\n              -97.16528274367352,\n              34.594939532905144\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Swedberg, Dusty A.","contributorId":340779,"corporation":false,"usgs":false,"family":"Swedberg","given":"Dusty","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mollenhauer, Robert M.","contributorId":340780,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907547,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70254772,"text":"70254772 - 2023 - Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2024-06-07T15:57:01.046173","indexId":"70254772","displayToPublicDate":"2023-12-18T10:45:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem","docAbstract":"<p><span>For various temperate ungulate species, recent research has highlighted the potential for spring vegetation phenology (“green-up”) to influence individual condition, with purported benefits to population productivity. However, few studies have been able to measure the benefit on vital rates directly, and fewer still have investigated the comparative influence of other phenological periods on ungulate vital rates. In this study, we tracked phenological changes throughout the duration of the growing season and examined how their timing affected the probability of pregnancy in an ungulate population. We did this for elk (</span><i>Cervus canadensis</i><span>) across the Greater Yellowstone Ecosystem (GYE) by sampling 1106 adult females in winter at 25 sites over a 13-year period and assessing sources of variation in pregnancy using a Bayesian hierarchical model. Pregnancy rates were generally high across the GYE (82.4%), and the primary influences on probability of pregnancy were the timing of vegetation senescence (“brown-down”) in autumn and exposure to the reproductive disease brucellosis. Earlier forage brown-down in fall negatively influenced the probability of pregnancy of elk aged 6–9 years by an estimated 17.2% within the range (ca. 32 days) of observed brown-down end dates. While summer habitat quality has been inferred to influence elk pregnancy previously, our findings specify the key influence of foraging conditions later in the seasonal cycle, immediately before the breeding season. The reproductive disease brucellosis was also an important factor, reducing the probability of pregnancy by 12.4% in elk in the 6- to 9-year age class. Because pregnancy was tested before most disease-induced abortions occur, the apparent mechanism for this effect is a prolonged reduction in fertility beyond the period of initial exposure in which fetal mortality is typically expected. Our results prompt greater scrutiny of the combined effects of late-season phenology and disease on reproductive rates and population productivity in temperate ungulates.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4694","usgsCitation":"Bidder, O.R., Connor, T., Morales, J.M., Rickbeil, G.J., Merkle, J., Fuda, R.K., Rogerson, J., Scurlock, B.M., Edwards, W.H., Cole, E., McWhirter, D.E., Courtemanch, A.B., Dewey, S., Kauffman, M., MacNulty, D.R., du Toit, J., Stahler, D., and Middleton, A.D., 2023, Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem: Ecosphere, v. 14, e4694, 14 p., https://doi.org/10.1002/ecs2.4694.","productDescription":"e4694, 14 p.","ipdsId":"IP-157765","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":441401,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4694","text":"Publisher Index Page"},{"id":429652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.01112913216181,\n              46.437409339504086\n            ],\n            [\n              -114.01112913216181,\n              42.020821465341925\n            ],\n            [\n              -105.94049421049453,\n              42.020821465341925\n            ],\n            [\n              -105.94049421049453,\n              46.437409339504086\n            ],\n            [\n              -114.01112913216181,\n              46.437409339504086\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bidder, Owen R.","contributorId":337529,"corporation":false,"usgs":false,"family":"Bidder","given":"Owen","email":"","middleInitial":"R.","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":902480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connor, Thomas","contributorId":337530,"corporation":false,"usgs":false,"family":"Connor","given":"Thomas","email":"","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":902481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morales, Juan M.","contributorId":171521,"corporation":false,"usgs":false,"family":"Morales","given":"Juan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":902482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rickbeil, Gregory J.M.","contributorId":270401,"corporation":false,"usgs":false,"family":"Rickbeil","given":"Gregory","email":"","middleInitial":"J.M.","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":false,"id":902483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Merkle, Jerod A.","contributorId":264421,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":902484,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fuda, Rebecca K.","contributorId":203303,"corporation":false,"usgs":false,"family":"Fuda","given":"Rebecca","email":"","middleInitial":"K.","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":902485,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rogerson, Jared D.","contributorId":106401,"corporation":false,"usgs":true,"family":"Rogerson","given":"Jared D.","affiliations":[],"preferred":false,"id":902486,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Scurlock, Brandon M.","contributorId":93788,"corporation":false,"usgs":false,"family":"Scurlock","given":"Brandon","email":"","middleInitial":"M.","affiliations":[{"id":6917,"text":"Wyoming Game and Fish Department, Laramie, USA","active":true,"usgs":false}],"preferred":false,"id":902487,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Edwards, William H","contributorId":189799,"corporation":false,"usgs":false,"family":"Edwards","given":"William","email":"","middleInitial":"H","affiliations":[],"preferred":false,"id":902488,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cole, Eric K.","contributorId":337540,"corporation":false,"usgs":false,"family":"Cole","given":"Eric K.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902489,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McWhirter, Douglas E.","contributorId":264424,"corporation":false,"usgs":false,"family":"McWhirter","given":"Douglas","email":"","middleInitial":"E.","affiliations":[{"id":54471,"text":"wyfg","active":true,"usgs":false}],"preferred":false,"id":902490,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Courtemanch, Alyson B.","contributorId":198651,"corporation":false,"usgs":false,"family":"Courtemanch","given":"Alyson","email":"","middleInitial":"B.","affiliations":[{"id":35682,"text":"Wyoming Game and Fish Department, Jackson, WY","active":true,"usgs":false}],"preferred":false,"id":902491,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dewey, Sarah","contributorId":337547,"corporation":false,"usgs":false,"family":"Dewey","given":"Sarah","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":902492,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902493,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"MacNulty, Daniel R.","contributorId":210842,"corporation":false,"usgs":false,"family":"MacNulty","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":902494,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"du Toit, Johan T.","contributorId":86583,"corporation":false,"usgs":true,"family":"du Toit","given":"Johan T.","affiliations":[],"preferred":false,"id":902495,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stahler, Daniel R.","contributorId":337554,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":902496,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Middleton, Arthur D.","contributorId":210264,"corporation":false,"usgs":false,"family":"Middleton","given":"Arthur","email":"","middleInitial":"D.","affiliations":[{"id":33770,"text":"University of California at Berkeley","active":true,"usgs":false}],"preferred":false,"id":902497,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70250712,"text":"70250712 - 2023 - Bayesian hierarchical modeling for probabilistic estimation of tsunami amplitude from far-field earthquake sources","interactions":[],"lastModifiedDate":"2023-12-28T12:44:48.760618","indexId":"70250712","displayToPublicDate":"2023-12-18T06:36:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian hierarchical modeling for probabilistic estimation of tsunami amplitude from far-field earthquake sources","docAbstract":"<div class=\"article-section__content en main\"><p>Evaluation of tsunami disaster risk for a coastal region requires reliable estimation of tsunami hazard, for example, wave amplitude close to the shore. Observed tsunami data are scarce and have poor spatial coverage, and for this reason probabilistic tsunami hazard analysis (PTHA) traditionally relies on numerical simulation of “synthetic” tsunami generation and propagation toward the coast. Such an approach has been extensively studied in the past and it is widely recognized as an important disaster-risk mitigation tool. PTHA can not only provide less uncertain and spatially coherent hazard estimates in comparison with classical empirical data analysis which is restricted at the tide gauge stations, but also local inundation information. In this paper, we explore a purely statistical alternative to traditional PTHA for evaluation of tsunami amplitude hazard. Here, we use tide gauge measurements of tsunami amplitude along the western United States, specifically California and Oregon, and develop a spatial Bayesian hierarchical model (BHM) to assess tsunami hazard from far-field earthquake sources at various recurrence intervals. The configuration of our model incorporates latent Gaussian fields that utilize information on the distance between tide gauges as well as on the continental shelf width, that is, a covariate linked to potential dissipative effects on wave energy as the tsunami travels over shallow water. Through our BHM, we produce spatially continuous probabilistic maps of far-field tsunami hazard which can aid comprehensive tsunami disaster risk reduction and management.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JC020002","usgsCitation":"Boumis, G., Geist, E.L., and Lee, D., 2023, Bayesian hierarchical modeling for probabilistic estimation of tsunami amplitude from far-field earthquake sources: Journal of Geophysical Research: Oceans, v. 128, no. 12, e2023JC020002, 16 p., https://doi.org/10.1029/2023JC020002.","productDescription":"e2023JC020002, 16 p.","ipdsId":"IP-151939","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499265,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jc020002","text":"Publisher Index Page"},{"id":423956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.89613542356796,\n              48.497460056867624\n            ],\n            [\n              -126.0601979235679,\n              49.01892139292943\n            ],\n            [\n              -126.0601979235679,\n              44.94434930821649\n            ],\n            [\n              -126.41176042356773,\n              40.75865742539179\n            ],\n            [\n              -125.35707292356773,\n              38.45677055335565\n            ],\n            [\n              -123.24769792356778,\n              34.64558981782825\n            ],\n            [\n              -120.61097917356783,\n              33.0397043679928\n            ],\n            [\n              -118.32582292356796,\n              32.0767084901876\n            ],\n            [\n              -115.33754167356793,\n              32.37411455892672\n            ],\n            [\n              -120.17152604856793,\n              36.78614622387245\n            ],\n            [\n              -122.80824479856787,\n              39.95497361468907\n            ],\n            [\n              -122.80824479856787,\n              43.94038749428063\n            ],\n            [\n              -122.89613542356796,\n              48.497460056867624\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"128","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Boumis, Georgios 0000-0001-7825-5239","orcid":"https://orcid.org/0000-0001-7825-5239","contributorId":332846,"corporation":false,"usgs":false,"family":"Boumis","given":"Georgios","email":"","affiliations":[{"id":79664,"text":"Center for Complex Hydrosystems Research, University of Alabama","active":true,"usgs":false}],"preferred":false,"id":891060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geist, Eric L. 0000-0003-0611-1150","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":15543,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":891061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Danhyang","contributorId":332847,"corporation":false,"usgs":false,"family":"Lee","given":"Danhyang","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":891062,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250474,"text":"sir20235121 - 2023 - Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia","interactions":[],"lastModifiedDate":"2026-03-13T15:40:20.136121","indexId":"sir20235121","displayToPublicDate":"2023-12-14T07:40:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5121","displayTitle":"Hydrogeology, Karst, and Groundwater Availability of Monroe County, West Virginia","title":"Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia","docAbstract":"<p>Monroe County is in southeastern West Virginia, encompassing an area of 474 square miles. The area consists of karst and siliciclastic aquifers of Ordovician, Silurian, Devonian, and Mississippian age and is in parts of two physiographic provinces: the Valley and Ridge Province to the east of Peters Mountain, and the Appalachian Plateau Province to the west of Peters Mountain. This study was developed in response to inquiries from the Monroe County Commission requesting assessment of the water resources of the county to better understand the quantity of the county’s groundwater resources, for both current [2023] and future demand, and to provide information to support protection and management of the county’s valuable groundwater resources.</p><p>Various products were developed for this study that provide knowledge with respect to water availability and contamination susceptibility of the karst aquifers within the county. U.S. Geological Survey (USGS) geologists conducted extensive geologic mapping in support of the project, producing (1) a countywide bedrock geologic map, (2) a countywide hydrogeologic map, and (3) a light detection and ranging (lidar)-derived countywide digital elevation model and associated sinkhole map. A significant part of this work was to map in detail the Greenbrier Group at the formation level, which prior to this study had only partially been completed. The report also includes (4) a description of the lithologic units identified as part of the geologic mapping process.</p><p>U.S. Geological Survey hydrologists completed several additional products for the hydrology part of the effort, including development of (1) a countywide potentiometric surface (water-table) map, (2) a countywide base-flow stream assessment, (3) countywide water-budget estimates, (4) well log surveys for 15 wells to better understand subsurface controls on groundwater flow within the study area, (5) two groundwater tracer tests to better refine the groundwater divide from the northern and southern parts of the karst aquifer in Monroe County; and finally, based on all available data collected for the study including the potentiometric surface map, geologic map, current [2023] and legacy fluorometric groundwater tracer tests, and base-flow stream assessments, (6) groundwater-basin delineations were reassessed for principal groundwater basins within the Greenbrier aquifer.</p><p>In Monroe County, four principal hydrogeologic settings produce large yields of water for residential, agricultural, and other uses. The most relied upon water-bearing zone with respect to current [2023] public water supply is from springs along Peters Mountain. These springs are derived from intervals of fractured sandstone and resultant alluvial deposits. Groundwater flows downslope through these permeable alluvial deposits and discharges at the contact with less permeable strata, such as the Reedsville Shale. The second most relied upon water-bearing zone in Monroe County is within the karstic Greenbrier Group aquifer, in which the basal Hillsdale Limestone overlies the less permeable Maccrady Shale. This geologic contact between the Hillsdale Limestone and Maccrady Shale is not only targeted as a source of water for agricultural supply but also is targeted as a source of water for residential supply. The third most relied upon water-bearing zone is composed of shallow perched aquifers within the Greenbrier Group. The discontinuous nature of these perched aquifers makes mapping their extent impossible, but they are related to permeable geologic strata, such as karstified limestones with solutionally enhanced permeability that overlies less permeable shale or chert bedrock. During geologic mapping of the county, several of these perched aquifers were documented in the Pickaway, Union, and Alderson Limestones. A fourth zone consists of springs from Ordovician carbonates at the base of Peters Mountain, which are influenced by sinking streams as well as upwelling along faults. In terms of water quantity, the most sustainable springs are those having deeper-sourced flows.</p><p>Public supplies are a principal source of water used for residential and commercial supply in the region, accounting for 0.49 million gallons per day (Mgal/d) of fresh-water withdrawals (0.14 Mgal/d of groundwater and 0.35 Mgal/d of surface water) for residential and commercial use and serving 6,645 individuals (49.2 percent of the population). An estimated 6,861 people, (50.8 percent of the population) primarily rely on private wells or other unregulated sources, such as springs, and withdraw 0.55 Mgal/d of groundwater for their residential use. Public water supply in the region is primarily (71.4 percent) derived from springs and augmented by stream withdrawals (backup sources mainly during low-flow periods), with the remaining portion (28.6 percent) derived from groundwater withdrawals from wells. For rural residents, however, 100 percent of their withdrawals are derived from groundwater (wells or springs).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235121","isbn":"978-1-4113-4541-6","collaboration":"Prepared in cooperation with the West Virginia Department of Environmental Protection, the West Virginia Department of Health & Human Resources, and the Monroe County Commission","usgsCitation":"Kozar, M.D., Doctor, D.H., Jones, W.K., Chien, N., Cox, C.E., Orndorff, R.C., Weary, D.J., Weaver, M.R., McAdoo, M.A., and Parker, M., 2023, Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia: U.S. Geological Survey Scientific Investigations Report 2023–5121, 82 p., https://doi.org/10.3133/sir20235121.","productDescription":"Report: xii, 81 p.; 4 Appendixes, 5 Data Releases","numberOfPages":"81","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-153904","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":423493,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O85K6T","text":"USGS data release","linkHelpText":"Lidar-derived closed depression vector data and density raster in karst areas of Monroe County, West Virginia"},{"id":423494,"rank":12,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TKR3XJ","text":"USGS data release","linkHelpText":"Lidar-derived imagery and digital elevation model of Monroe County, West Virginia at 3-meter resolution"},{"id":423487,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5121/images/"},{"id":423483,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5121/coverthb.jpg"},{"id":423484,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121.pdf","text":"Report","size":"36.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5121"},{"id":423486,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121.XML"},{"id":423490,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix3.zip","text":"Appendix 3","size":"111 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Results of Monthly Hydrograph Analyses for Four Major Watersheds in Monroe County and for the Greenbrier River at Alderson, West Virginia"},{"id":423492,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92JLWRM","text":"USGS data release","linkHelpText":"Density raster of caves in Monroe County, West Virginia"},{"id":426143,"rank":15,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_fig04_plate.pdf","text":"Plate of Figure 4","size":"19.7 MB","linkHelpText":"- Hydrogeologic Map of Monroe County, West Virginia"},{"id":426144,"rank":16,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_fig05_plate.pdf","text":"Plate of Figure 5","size":"10.7 MB","linkHelpText":"- Geologic Map of Monroe County, West Virginia"},{"id":423485,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235121/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5121"},{"id":426145,"rank":17,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_fig25_plate.pdf","text":"Plate of Figure 25","size":"1.98 MB","linkHelpText":"- Potentiometric-Surface Map of Monroe County, West Virginia"},{"id":423488,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix1.csv","text":"Appendix 1","size":"15.6 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Well Depth, Casing, Yield, Water Level, and Specific Capacity Data From County Health Department Well Completion Reports"},{"id":423489,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix2.csv","text":"Appendix 2","size":"17.3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Base-flow Data for 83 Sites Measured in September 2019 in Monroe County, West Virginia"},{"id":501160,"rank":18,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115685.htm","linkFileType":{"id":5,"text":"html"}},{"id":423496,"rank":14,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TFAN5X","text":"USGS data release","linkHelpText":"Interpolated groundwater levels and altitudes for Monroe County, West Virginia, 2017–2019"},{"id":423495,"rank":13,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KF9FD2","text":"USGS data release","linkHelpText":"Fluorescein and Rhodamine WT concentration and recovery data for select samples collected in Monroe County, West Virginia, in August and September 2019"},{"id":423491,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix4.zip","text":"Appendix 4","size":"14.9 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Results of Annual Hydrograph Analyses for Four Major Watersheds in Monroe County and for the Greenbrier River at Alderson, West Virginia"}],"country":"United States","state":"West Virginia","county":"Monroe County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-80.3074,37.6895],[-80.2773,37.6581],[-80.2649,37.649],[-80.2215,37.6282],[-80.2248,37.6242],[-80.2295,37.6186],[-80.2365,37.6126],[-80.2479,37.6045],[-80.2611,37.5958],[-80.2751,37.5885],[-80.2828,37.5853],[-80.2959,37.5799],[-80.326,37.5667],[-80.3127,37.5463],[-80.3338,37.5368],[-80.307,37.5287],[-80.2946,37.54],[-80.2878,37.5371],[-80.2821,37.5344],[-80.2894,37.5228],[-80.2945,37.5159],[-80.2998,37.5103],[-80.3036,37.5072],[-80.3062,37.5053],[-80.3066,37.505],[-80.3125,37.502],[-80.3183,37.4997],[-80.3293,37.4964],[-80.3437,37.4927],[-80.3518,37.4909],[-80.3553,37.4895],[-80.3594,37.4881],[-80.3646,37.4849],[-80.3663,37.4822],[-80.3662,37.479],[-80.368,37.4768],[-80.3689,37.4759],[-80.3702,37.4749],[-80.3739,37.4731],[-80.3761,37.4722],[-80.3811,37.4703],[-80.3883,37.4676],[-80.4033,37.4617],[-80.4163,37.4559],[-80.4262,37.45],[-80.4357,37.443],[-80.4414,37.4394],[-80.4438,37.4378],[-80.4461,37.4362],[-80.4501,37.4333],[-80.4549,37.4317],[-80.4611,37.4302],[-80.4651,37.4293],[-80.4704,37.4275],[-80.4727,37.427],[-80.4761,37.4269],[-80.4802,37.4283],[-80.4831,37.4319],[-80.486,37.4333],[-80.4884,37.4356],[-80.4901,37.4374],[-80.4905,37.4379],[-80.4919,37.4396],[-80.4936,37.4419],[-80.4942,37.4446],[-80.4939,37.4467],[-80.4937,37.4487],[-80.4931,37.4528],[-80.4932,37.4596],[-80.4954,37.4666],[-80.4984,37.473],[-80.5002,37.4761],[-80.5026,37.4789],[-80.5054,37.4802],[-80.5083,37.481],[-80.5124,37.4806],[-80.5156,37.48],[-80.5182,37.4796],[-80.5309,37.4768],[-80.5407,37.4752],[-80.55,37.4729],[-80.5563,37.4707],[-80.5673,37.4661],[-80.5732,37.4628],[-80.5807,37.4583],[-80.5899,37.4523],[-80.5986,37.4473],[-80.603,37.445],[-80.6052,37.4439],[-80.6077,37.4427],[-80.613,37.4404],[-80.6176,37.4385],[-80.6219,37.4361],[-80.6276,37.4328],[-80.6363,37.4282],[-80.6518,37.4199],[-80.6696,37.4116],[-80.684,37.4056],[-80.7048,37.396],[-80.7052,37.3958],[-80.7198,37.3895],[-80.7248,37.3874],[-80.7307,37.3849],[-80.7423,37.3812],[-80.7507,37.3784],[-80.7531,37.3776],[-80.7629,37.3748],[-80.7709,37.3729],[-80.7757,37.382],[-80.7793,37.3878],[-80.7834,37.3923],[-80.7864,37.3936],[-80.7899,37.3945],[-80.7934,37.3945],[-80.7939,37.3946],[-80.7963,37.3948],[-80.7968,37.395],[-80.7986,37.3954],[-80.8004,37.3963],[-80.8021,37.3981],[-80.8051,37.4012],[-80.8097,37.4062],[-80.8157,37.4115],[-80.8244,37.4168],[-80.8321,37.4222],[-80.8367,37.4248],[-80.842,37.4257],[-80.8451,37.4257],[-80.8484,37.4256],[-80.853,37.4278],[-80.8575,37.4304],[-80.8547,37.4349],[-80.8467,37.4458],[-80.8404,37.4545],[-80.8399,37.4554],[-80.7965,37.5259],[-80.7559,37.5774],[-80.7467,37.5924],[-80.686,37.6798],[-80.6704,37.699],[-80.6688,37.7058],[-80.6625,37.7244],[-80.6631,37.728],[-80.6637,37.7303],[-80.6474,37.729],[-80.6253,37.7219],[-80.6159,37.7201],[-80.5401,37.7005],[-80.5104,37.6929],[-80.507,37.6925],[-80.5029,37.6948],[-80.5006,37.6952],[-80.4982,37.6943],[-80.4959,37.6921],[-80.4924,37.6939],[-80.4883,37.693],[-80.4849,37.6939],[-80.4808,37.6926],[-80.4756,37.6958],[-80.4721,37.6949],[-80.4674,37.694],[-80.4628,37.6927],[-80.4575,37.6877],[-80.4476,37.6868],[-80.4337,37.6928],[-80.4238,37.7005],[-80.4168,37.7019],[-80.414,37.7055],[-80.4093,37.7065],[-80.4053,37.7106],[-80.3971,37.716],[-80.3948,37.716],[-80.3925,37.7133],[-80.3953,37.7056],[-80.3942,37.7047],[-80.3878,37.7079],[-80.382,37.7034],[-80.3825,37.6997],[-80.3831,37.6925],[-80.3778,37.688],[-80.3743,37.6884],[-80.3697,37.6925],[-80.3679,37.693],[-80.3627,37.6907],[-80.3604,37.6921],[-80.354,37.6998],[-80.3523,37.7103],[-80.3518,37.7125],[-80.35,37.7121],[-80.3436,37.7067],[-80.3447,37.6994],[-80.347,37.6953],[-80.3406,37.6894],[-80.326,37.6868],[-80.3156,37.6872],[-80.3139,37.6878],[-80.3115,37.6886],[-80.3094,37.6891],[-80.3074,37.6895]]]},\"properties\":{\"name\":\"Monroe\",\"state\":\"WV\"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/va-wv-water\" data-mce-href=\"https://www.usgs.gov/centers/va-wv-water\">Virginia and West Virginia Water Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, Virginia 23228</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"https://pubs.er.usgs.gov/contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Hydrogeology</li><li>Karst Features</li><li>Groundwater Availability</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Well Depth, Casing, Yield, Water Level, and Specific Capacity Data From County Health Department Well Completion Reports</li><li>Appendix 2. Base-flow Data for 83 Sites Measured in September 2019 in Monroe County, West Virginia</li><li>Appendix 3. Results of Monthly Hydrograph Analyses for Four Major Watersheds in Monroe County and for the Greenbrier River at Alderson, West Virginia</li><li>Appendix 4. Results of Annual Hydrograph Analyses for Four Major Watersheds in Monroe County and for the Greenbrier River at Alderson, West Virginia</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-12-14","noUsgsAuthors":false,"publicationDate":"2023-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Kozar, Mark D. 0000-0001-7755-7657 mdkozar@usgs.gov","orcid":"https://orcid.org/0000-0001-7755-7657","contributorId":1963,"corporation":false,"usgs":true,"family":"Kozar","given":"Mark","email":"mdkozar@usgs.gov","middleInitial":"D.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":890052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":890053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, William K. 0009-0000-9851-3514","orcid":"https://orcid.org/0009-0000-9851-3514","contributorId":332334,"corporation":false,"usgs":false,"family":"Jones","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":79454,"text":"Environmental Data LLC, Warm Springs, VA","active":true,"usgs":false}],"preferred":false,"id":890054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chien, Nathan 0009-0001-2274-9085","orcid":"https://orcid.org/0009-0001-2274-9085","contributorId":332335,"corporation":false,"usgs":false,"family":"Chien","given":"Nathan","email":"","affiliations":[{"id":79455,"text":"Previous employee USGS VA-WV WSC","active":true,"usgs":false}],"preferred":false,"id":890055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cox, Cheyenne E. 0000-0002-5213-7880","orcid":"https://orcid.org/0000-0002-5213-7880","contributorId":332336,"corporation":false,"usgs":false,"family":"Cox","given":"Cheyenne","email":"","middleInitial":"E.","affiliations":[{"id":79456,"text":"former USGS Employee (Florence Bascom)","active":true,"usgs":false}],"preferred":false,"id":890056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":890057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weary, David J. 0000-0002-6115-6397 dweary@usgs.gov","orcid":"https://orcid.org/0000-0002-6115-6397","contributorId":545,"corporation":false,"usgs":true,"family":"Weary","given":"David","email":"dweary@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":890058,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weaver, Mitchell R. 0000-0003-3099-2285","orcid":"https://orcid.org/0000-0003-3099-2285","contributorId":329366,"corporation":false,"usgs":true,"family":"Weaver","given":"Mitchell","email":"","middleInitial":"R.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890059,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McAdoo, Mitchell A. 0000-0002-3895-0816 mmcadoo@usgs.gov","orcid":"https://orcid.org/0000-0002-3895-0816","contributorId":200287,"corporation":false,"usgs":true,"family":"McAdoo","given":"Mitchell","email":"mmcadoo@usgs.gov","middleInitial":"A.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":890060,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Parker, Mercer 0000-0001-6683-6458 mercerparker@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-6458","contributorId":203174,"corporation":false,"usgs":true,"family":"Parker","given":"Mercer","email":"mercerparker@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":890061,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70251283,"text":"70251283 - 2023 - Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon","interactions":[],"lastModifiedDate":"2024-02-02T12:42:56.771463","indexId":"70251283","displayToPublicDate":"2023-12-14T06:37:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17146,"text":"Frontiers Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon","docAbstract":"<div class=\"JournalAbstract\"><p><strong>Introduction:</strong><span>&nbsp;</span>Forecasting range shifts in response to climate change requires accurate species distribution models (SDMs), particularly at the margins of species' ranges. However, most studies producing SDMs rely on sparse species occurrence datasets from herbarium records and public databases, along with random pseudoabsences. While environmental covariates used to fit SDMS are increasingly precise due to satellite data, the availability of species occurrence records is still a large source of bias in model predictions. We developed distribution models for hybridizing sister species of western and eastern Joshua trees (<i>Yucca brevifolia</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Y. jaegeriana</i>, respectively), iconic Mojave Desert species that are threatened by climate change and habitat loss.</p><p><strong>Methods:</strong><span>&nbsp;</span>We conducted an intensive visual grid search of online satellite imagery for 672,043 0.25 km<sup>2</sup><span>&nbsp;</span>grid cells to identify the two species' presences and absences on the landscape with exceptional resolution, and field validated 29,050 cells in 15,001 km of driving. We used the resulting presence/absence data to train SDMs for each Joshua tree species, revealing the contemporary environmental gradients (during the past 40 years) with greatest influence on the current distribution of adult trees.</p><p><strong>Results:</strong><span>&nbsp;</span>While the environments occupied by<span>&nbsp;</span><i>Y. brevifolia</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Y. jaegeriana</i><span>&nbsp;</span>were similar in total aridity, they differed with respect to seasonal precipitation and temperature ranges, suggesting the two species may have differing responses to climate change. Moreover, the species showed differing potential to occupy each other's geographic ranges: modeled potential habitat for<span>&nbsp;</span><i>Y. jaegeriana</i><span>&nbsp;</span>extends throughout the range of<span>&nbsp;</span><i>Y. brevifolia</i>, while potential habitat for<span>&nbsp;</span><i>Y. brevifolia</i><span>&nbsp;</span>is not well represented within the range of<span>&nbsp;</span><i>Y. jaegeriana</i>.</p><p><strong>Discussion:</strong><span>&nbsp;</span>By reproducing the current range of the Joshua trees with high fidelity, our dataset can serve as a baseline for future research, monitoring, and management of this species, including an increased understanding of dynamics at the trailing and leading margins of the species' ranges and potential for climate refugia.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2023.1266892","usgsCitation":"Esque, T., Shryock, D., Berr, G.A., Chen, F., DeFalco, L., Lewicki, S.M., Cunningham, B.L., Gaylord, E.J., Poage, C.S., Gantz, G.E., Van Gaalen, R.A., Gottsacker, B.O., Mcdonald, A.M., Yoder, J., Smith, C., and Nussear, K., 2023, Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon: Frontiers Ecology and Evolution, v. 11, 1266892, 20 p., https://doi.org/10.3389/fevo.2023.1266892.","productDescription":"1266892, 20 p.","ipdsId":"IP-159615","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441412,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1266892","text":"Publisher Index Page"},{"id":425278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.58014768204356,\n              38.89373609553763\n            ],\n            [\n              -120.58014768204356,\n              32.02965081218825\n            ],\n            [\n              -111.08796018204377,\n              32.02965081218825\n            ],\n            [\n              -111.08796018204377,\n              38.89373609553763\n            ],\n            [\n              -120.58014768204356,\n              38.89373609553763\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shryock, Daniel F. 0000-0003-0330-9815 dshryock@usgs.gov","orcid":"https://orcid.org/0000-0003-0330-9815","contributorId":208659,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel F.","email":"dshryock@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berr, Gabrielle A. 0009-0004-1531-7761","orcid":"https://orcid.org/0009-0004-1531-7761","contributorId":333759,"corporation":false,"usgs":false,"family":"Berr","given":"Gabrielle","email":"","middleInitial":"A.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":893851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Felicia 0000-0002-7408-5946","orcid":"https://orcid.org/0000-0002-7408-5946","contributorId":210469,"corporation":false,"usgs":true,"family":"Chen","given":"Felicia","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893852,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeFalco, Lesley A. 0000-0002-7542-9261","orcid":"https://orcid.org/0000-0002-7542-9261","contributorId":208658,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893861,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lewicki, Sabrina Mae 0009-0005-3686-5123","orcid":"https://orcid.org/0009-0005-3686-5123","contributorId":333760,"corporation":false,"usgs":true,"family":"Lewicki","given":"Sabrina","email":"","middleInitial":"Mae","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893853,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cunningham, Brent Lee 0009-0001-3386-2980","orcid":"https://orcid.org/0009-0001-3386-2980","contributorId":333761,"corporation":false,"usgs":true,"family":"Cunningham","given":"Brent","email":"","middleInitial":"Lee","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893854,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gaylord, Eddie J.","contributorId":333770,"corporation":false,"usgs":false,"family":"Gaylord","given":"Eddie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":893875,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Poage, Caitlin Shannon 0009-0008-2256-6845","orcid":"https://orcid.org/0009-0008-2256-6845","contributorId":333762,"corporation":false,"usgs":true,"family":"Poage","given":"Caitlin","email":"","middleInitial":"Shannon","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893856,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gantz, Gretchen Elizabeth 0009-0004-5950-3777","orcid":"https://orcid.org/0009-0004-5950-3777","contributorId":333763,"corporation":false,"usgs":true,"family":"Gantz","given":"Gretchen","email":"","middleInitial":"Elizabeth","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893857,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Van Gaalen, Ross Adrian 0009-0009-4877-552X","orcid":"https://orcid.org/0009-0009-4877-552X","contributorId":333764,"corporation":false,"usgs":true,"family":"Van Gaalen","given":"Ross","email":"","middleInitial":"Adrian","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893858,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gottsacker, Benjamin O 0000-0002-9481-6267","orcid":"https://orcid.org/0000-0002-9481-6267","contributorId":315424,"corporation":false,"usgs":true,"family":"Gottsacker","given":"Benjamin","email":"","middleInitial":"O","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893859,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mcdonald, Amanda Marie 0009-0000-9484-8878","orcid":"https://orcid.org/0009-0000-9484-8878","contributorId":333765,"corporation":false,"usgs":true,"family":"Mcdonald","given":"Amanda","email":"","middleInitial":"Marie","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893860,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Yoder, J.B.","contributorId":333766,"corporation":false,"usgs":false,"family":"Yoder","given":"J.B.","affiliations":[{"id":7080,"text":"California State University, Northridge","active":true,"usgs":false}],"preferred":false,"id":893862,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Smith, C.I.","contributorId":333767,"corporation":false,"usgs":false,"family":"Smith","given":"C.I.","affiliations":[{"id":7268,"text":"Willamette University","active":true,"usgs":false}],"preferred":false,"id":893863,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Nussear, K.E. 0000-0002-3849-8911","orcid":"https://orcid.org/0000-0002-3849-8911","contributorId":333768,"corporation":false,"usgs":false,"family":"Nussear","given":"K.E.","email":"","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":893864,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70256559,"text":"70256559 - 2023 - Effect of straying, reproductive strategies, and ocean distribution on the structure of American shad populations","interactions":[],"lastModifiedDate":"2024-08-16T11:38:31.421824","indexId":"70256559","displayToPublicDate":"2023-12-14T06:17:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Effect of straying, reproductive strategies, and ocean distribution on the structure of American shad populations","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>The use of species distribution models has proliferated, providing insights for sustainable management of migratory species in a globally changing environment. However, many of these models are based on statistical relationships developed from historical conditions that may not perform well under changing or even analogous conditions caused by climate change. In this paper, we used a mechanistic species distribution model called GR3D (Global Repositioning Dynamics for Diadromous Fish Distribution) to examine the integrated dynamics of American shad (<i>Alosa sapidissima</i>) populations across their native range along the Eastern U.S. coast, where the species demonstrates latitudinal variations in life histories and reproductive strategies. The initial design of the model was adapted to incorporate region-specific parameterization to fit the species ecology. Then, a sensitivity analysis was performed to test the influences of uncertain processes regarding American shad distribution at sea, straying and reproduction on key characteristics of the species distribution. The sensitivity analysis showed the influence of the Allee effect (i.e., “depensatory” process) and the homing rate (i.e., fidelity to the breeding sites) on the probability of presence and abundances among catchments and metapopulations estimated by the model. Contrary to the homing rate, the distance of straying did not change the estimated number of metapopulations or abundances. Homing strength, however, was quite influential. The integration of complex migration patterns during the marine phase (i.e., wintering and summering offshore areas) provided more likely estimates of the species' overall distribution. Overall, our study illustrated the utility of incorporating factors governing the large-scale distribution of migratory species to improve local management.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4712","usgsCitation":"Poulet, C., Lassalle, G., Jordaan, A., Limburg, K., Nack, C.C., Nye, J.A., O’Malley, A., O’Malley-Barber, B., Stich, D.S., Waldman, J., Zydlewski, J.D., and Lambert, P., 2023, Effect of straying, reproductive strategies, and ocean distribution on the structure of American shad populations: Ecosphere, v. 14, no. 12, e4712, 21 p., https://doi.org/10.1002/ecs2.4712.","productDescription":"e4712, 21 p.","ipdsId":"IP-147500","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":441419,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4712","text":"Publisher Index Page"},{"id":432849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.25384275260296,\n              23.589986588351152\n            ],\n            [\n              -59.41399900260346,\n              23.589986588351152\n            ],\n            [\n              -59.41399900260346,\n              51.4169004286193\n            ],\n            [\n              -85.25384275260296,\n              51.4169004286193\n            ],\n            [\n              -85.25384275260296,\n              23.589986588351152\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  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Amherst","active":true,"usgs":false}],"preferred":false,"id":907980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Limburg, Karin E.","contributorId":341130,"corporation":false,"usgs":false,"family":"Limburg","given":"Karin E.","affiliations":[{"id":12623,"text":"State University of New York College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":907981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nack, Christopher C.","contributorId":341131,"corporation":false,"usgs":false,"family":"Nack","given":"Christopher","email":"","middleInitial":"C.","affiliations":[{"id":62153,"text":"Ramboll","active":true,"usgs":false}],"preferred":false,"id":907982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nye, Janet A.","contributorId":341132,"corporation":false,"usgs":false,"family":"Nye","given":"Janet","email":"","middleInitial":"A.","affiliations":[{"id":55603,"text":"University of North Carolina Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":907983,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Malley, Andrew","contributorId":341133,"corporation":false,"usgs":false,"family":"O’Malley","given":"Andrew","affiliations":[{"id":81706,"text":"Gomez and Sullivan Engineers","active":true,"usgs":false}],"preferred":false,"id":907984,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"O’Malley-Barber, Betsy","contributorId":341134,"corporation":false,"usgs":false,"family":"O’Malley-Barber","given":"Betsy","email":"","affiliations":[{"id":81706,"text":"Gomez and Sullivan Engineers","active":true,"usgs":false}],"preferred":false,"id":907985,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stich, Dan S.","contributorId":341135,"corporation":false,"usgs":false,"family":"Stich","given":"Dan","email":"","middleInitial":"S.","affiliations":[{"id":81707,"text":"State University of New York Oneonta","active":true,"usgs":false}],"preferred":false,"id":907986,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Waldman, John R.","contributorId":341136,"corporation":false,"usgs":false,"family":"Waldman","given":"John R.","affiliations":[{"id":32856,"text":"Queens College","active":true,"usgs":false}],"preferred":false,"id":907987,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":907988,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lambert, Patrick","contributorId":341137,"corporation":false,"usgs":false,"family":"Lambert","given":"Patrick","affiliations":[{"id":81705,"text":"INRAe","active":true,"usgs":false}],"preferred":false,"id":907989,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70266207,"text":"70266207 - 2023 - Examining the effect of environmental variability on the viability of endangered Steller sea lions using an integrated population model","interactions":[],"lastModifiedDate":"2025-04-30T15:45:29.630755","indexId":"70266207","displayToPublicDate":"2023-12-14T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Examining the effect of environmental variability on the viability of endangered Steller sea lions using an integrated population model","docAbstract":"Understanding spatio-temporal variability in demography and the influence of environmental conditions offers insight into the factors underlying population dynamics. This is particularly true for species with divergent demographic patterns across large geographic areas. The contrasting abundance trends observed across the range of Steller sea lions (Eumetopias jubatus) have been studied extensively, with research suggesting that the primary drivers of localized population dynamics vary over time and space. We developed a Bayesian integrated population model for the endangered western distinct population segment of Steller sea lions that combines mark-recapture and count data from 2000-2021 to estimate demographic rates, abundance trends, and the effects of environmental variability on population growth. Our results highlight subregional demographic differences, including reduced pup survival in the central Aleutian Islands and reduced yearling survival west of Samalga Pass. Range-wide abundance increased by 1.7% yr-1 (95% credible interval: 0.14; 3.4%) over the study period, with a positive annual growth rate of 3.0% (1.1; 5.1%) yr-1 east of Samalga Pass, a negative growth rate of -2.1% (-4.6; 0.5%) yr-1 west of Samalga Pass, and an overall low probability of local extirpation (<2%) in 100 years even in subregions experiencing continued decline. The effect of environmental variability on population growth varied depending on subpopulation size and vital rates and was strongest in the area of greatest decline. Our model improves upon existing approaches for estimating abundance, accounts for environmental variability within the viability analysis, and can facilitate evaluating the efficacy of conservation actions and progress toward recovery goals.","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01282","usgsCitation":"Warlick, A., Johnson, D., Sweeney, K., Gelatt, T., and Converse, S.J., 2023, Examining the effect of environmental variability on the viability of endangered Steller sea lions using an integrated population model: Endangered Species Research, v. 52, p. 343-361, https://doi.org/10.3354/esr01282.","productDescription":"19 p.","startPage":"343","endPage":"361","ipdsId":"IP-151798","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487889,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01282","text":"Publisher Index Page"},{"id":485208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -192.3038114894406,\n              57.51067207764723\n            ],\n            [\n              -192.3038114894406,\n              51.43442138881829\n            ],\n            [\n              -154.88087376804862,\n              51.43442138881829\n            ],\n            [\n              -154.88087376804862,\n              57.51067207764723\n            ],\n            [\n              -192.3038114894406,\n              57.51067207764723\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Warlick, Amanda J.","contributorId":353988,"corporation":false,"usgs":false,"family":"Warlick","given":"Amanda J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":934927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":353989,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin S.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweeney, Katie L.","contributorId":353990,"corporation":false,"usgs":false,"family":"Sweeney","given":"Katie L.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gelatt, Tom S.","contributorId":353991,"corporation":false,"usgs":false,"family":"Gelatt","given":"Tom S.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":934931,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70252647,"text":"70252647 - 2023 - Rapid Source Characterization of the 2023 Mw 6.8 Al Haouz, Morocco, Earthquake","interactions":[],"lastModifiedDate":"2024-04-02T12:00:15.557997","indexId":"70252647","displayToPublicDate":"2023-12-12T06:56:11","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17443,"text":"The Seismological Record","active":true,"publicationSubtype":{"id":10}},"title":"Rapid Source Characterization of the 2023 Mw 6.8 Al Haouz, Morocco, Earthquake","docAbstract":"<p><span>The U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) estimates source characteristics of significant damaging earthquakes, aiming to place events within their seismotectonic framework. Contextualizing the 8 September 2023, M</span><span class=\"inline-formula no-formula-id\">w</span><span>&nbsp;6.8 Al Haouz, Morocco, earthquake is challenging, because it occurred in an enigmatic region of active surface faulting, and low seismicity yet produced significant damage and loss of life. Here, we present the rapid earthquake source products produced by the USGS NEIC, describing how the source model was derived using both seismic and geodetic observations. Our analysis indicates that the earthquake was the result of oblique‐reverse faulting in the lower crust on either a steeply north‐dipping fault or a moderately south‐dipping fault. Finite‐slip models using seismic and geodetic data reveal a compact source, with slip occurring at depths of 15–35&nbsp;km. The causative fault is not apparent, because the rupture did not break the surface, and it is not possible to definitively attribute the earthquake to a known structure. The earthquake centroid depth of 25&nbsp;km is noteworthy, because it shows slip extending beyond common estimates of seismogenic depth. This earthquake highlights that the seismogenic processes associated with mountain building in this wide plate boundary region are poorly understood.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320230040","usgsCitation":"Yeck, W.L., Hatem, A.E., Goldberg, D.E., Barnhart, W.D., Jobe, J.A., Shelly, D.R., Villasenor, A., Benz, H., and Earle, P.S., 2023, Rapid Source Characterization of the 2023 Mw 6.8 Al Haouz, Morocco, Earthquake: The Seismological Record, v. 3, no. 4, p. 357-366, https://doi.org/10.1785/0320230040.","productDescription":"10 p.","startPage":"357","endPage":"366","ipdsId":"IP-159241","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":441434,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320230040","text":"Publisher Index Page"},{"id":427297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Morocco","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -13.149953743100866,\n              28.63195342730735\n            ],\n            [\n              -5.1958521806005535,\n              28.63195342730735\n            ],\n            [\n              -5.1958521806005535,\n              35.40622419194092\n            ],\n            [\n              -13.149953743100866,\n              35.40622419194092\n            ],\n            [\n              -13.149953743100866,\n              28.63195342730735\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"3","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatem, Alexandra Elise 0000-0001-7584-2235","orcid":"https://orcid.org/0000-0001-7584-2235","contributorId":225597,"corporation":false,"usgs":true,"family":"Hatem","given":"Alexandra","email":"","middleInitial":"Elise","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldberg, Dara Elyse 0000-0002-0923-3180","orcid":"https://orcid.org/0000-0002-0923-3180","contributorId":289891,"corporation":false,"usgs":true,"family":"Goldberg","given":"Dara","email":"","middleInitial":"Elyse","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, William D. 0000-0003-0498-1697 wbarnhart@usgs.gov","orcid":"https://orcid.org/0000-0003-0498-1697","contributorId":294678,"corporation":false,"usgs":true,"family":"Barnhart","given":"William","email":"wbarnhart@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":897812,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson Jobe, Jessica A. 0000-0001-5574-4523","orcid":"https://orcid.org/0000-0001-5574-4523","contributorId":295377,"corporation":false,"usgs":true,"family":"Thompson Jobe","given":"Jessica","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897813,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897814,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Villasenor, Antonio","contributorId":335226,"corporation":false,"usgs":false,"family":"Villasenor","given":"Antonio","affiliations":[{"id":80350,"text":"Institut de Ciències del Mar, Barcelona, Spain","active":true,"usgs":false}],"preferred":false,"id":897815,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Benz, Harley","contributorId":335227,"corporation":false,"usgs":false,"family":"Benz","given":"Harley","affiliations":[{"id":80353,"text":"Emmeritus USGS","active":true,"usgs":false}],"preferred":false,"id":897816,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Earle, Paul S. 0000-0002-3500-017X pearle@usgs.gov","orcid":"https://orcid.org/0000-0002-3500-017X","contributorId":173551,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","email":"pearle@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897817,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70253008,"text":"70253008 - 2023 - Do seeding and seedling planting result in similar restored plant communities?","interactions":[],"lastModifiedDate":"2024-04-16T15:31:55.690301","indexId":"70253008","displayToPublicDate":"2023-12-11T10:29:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Do seeding and seedling planting result in similar restored plant communities?","docAbstract":"<h3 id=\"avsc12758-sec-0001-title\" class=\"article-section__sub-title section1\">Aims</h3><p>Restoration practitioners often face a tradeoff between low cost but risky seeding vs expensive but more reliable seedling planting to meet revegetation goals. Knowing under what environmental and management conditions direct seeding vs seedling planting benefit different species could improve restoration practice.</p><h3 id=\"avsc12758-sec-0002-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We compared seed emergence to planted-seedling survival among perennial herbaceous species commonly used in restoration across eight experimental restoration sites on the Colorado Plateau, USA. We used linear models to assess relationships between emergence and survival among species, and to assess the effects of site climate and seeding pre-treatments on those relationships.</p><h3 id=\"avsc12758-sec-0003-title\" class=\"article-section__sub-title section1\">Results</h3><p>We found that among species, emergence was positively correlated with survival in the cooler sites, meaning that species with high emergence also had high survival and vice versa, but had no relationship in the hottest sites. Furthermore, pre-treatments to enhance soil moisture in seeded plots, specifically microtopography (pits) and mulch, also resulted in positive relationships between emergence and survival among species, while seeding without additional soil pre-treatments did not. Seedling planting cost 14 times as much as direct seeding alone, dropping to nine times as much when pre-treatments were combined with seeding.</p><h3 id=\"avsc12758-sec-0004-title\" class=\"article-section__sub-title section1\">Conclusions</h3><p>Taken together, these results suggest that investments in seedling planting at hotter dryland sites, or in creating microtopography or mulching prior to seeding across sites, are likely to promote establishment success compared to simple seeding methods in degraded dryland ecosystems. These findings also identify opportunities for hybrid seeding and planting approaches that balance tradeoffs between risk and cost, respectively.</p>","language":"English","publisher":"Wiley","doi":"10.1111/avsc.12758","usgsCitation":"Butterfield, B.J., and Munson, S.M., 2023, Do seeding and seedling planting result in similar restored plant communities?: Applied Vegetation Science, v. 26, no. 4, e12758, 8 p., https://doi.org/10.1111/avsc.12758.","productDescription":"e12758, 8 p.","ipdsId":"IP-152987","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":427815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":898908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898909,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70250482,"text":"70250482 - 2023 - Panel review of Ground Motion Characterization Model in 2023 NSHM","interactions":[],"lastModifiedDate":"2023-12-13T12:57:53.52112","indexId":"70250482","displayToPublicDate":"2023-12-11T06:56:26","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Panel review of Ground Motion Characterization Model in 2023 NSHM","docAbstract":"<div class=\"c-clientmarkup\"><p>The 2023 National Seismic Hazard Model (NSHM; Petersen et al., 2023) has two major components – a seismic source characterization (SSC) model and a ground motion characterization (GMC) model. The US Geological Survey (USGS) established separate panels to review and provide input on these two models. Both panels are advisory, meaning that they provide input on technical issues for consideration by the USGS NSHM team, but they do not have decision making authority. Here, we report on the activities and recommendations of the Ground Motion Characterization Panel, made up of the authors of this review. Final modeling decisions are presented in separate USGS documents, including Petersen et al., (2023) and Moschetti et al., (2023). Where modeling decisions depart from our recommendations, the rationale is explained in those publications.</p></div>","language":"English","publisher":"University of California","usgsCitation":"Stewart, J.P., Abrahamson, N., Atkinson, G.M., Anderson, J.G., Campbell, K.W., Cramer, C.H., Kolaj, M., and Parker, G.A., 2023, Panel review of Ground Motion Characterization Model in 2023 NSHM, 14 p.","productDescription":"14 p.","ipdsId":"IP-159764","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":423501,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://escholarship.org/uc/item/2546f8hw"},{"id":423512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":890094,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abrahamson, Norman A.","contributorId":45202,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norman A.","affiliations":[{"id":13174,"text":"Pacific Gas & Electric","active":true,"usgs":false}],"preferred":false,"id":890095,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atkinson, Gail M.","contributorId":60515,"corporation":false,"usgs":false,"family":"Atkinson","given":"Gail","email":"","middleInitial":"M.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":890096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, John G.","contributorId":140379,"corporation":false,"usgs":false,"family":"Anderson","given":"John","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":890097,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, Kenneth W.","contributorId":74391,"corporation":false,"usgs":false,"family":"Campbell","given":"Kenneth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":890098,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cramer, Chris H.","contributorId":194851,"corporation":false,"usgs":false,"family":"Cramer","given":"Chris","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":890099,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kolaj, Michael","contributorId":332357,"corporation":false,"usgs":false,"family":"Kolaj","given":"Michael","email":"","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":890100,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":890101,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70250464,"text":"70250464 - 2023 - Carbonate chemistry and carbon sequestration driven by inorganic carbon outwelling from mangroves and saltmarshes","interactions":[],"lastModifiedDate":"2023-12-12T12:54:46.139953","indexId":"70250464","displayToPublicDate":"2023-12-11T06:50:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Carbonate chemistry and carbon sequestration driven by inorganic carbon outwelling from mangroves and saltmarshes","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Mangroves and saltmarshes are biogeochemical hotspots storing carbon in sediments and in the ocean following lateral carbon export (outwelling). Coastal seawater pH is modified by both uptake of anthropogenic carbon dioxide and natural biogeochemical processes, e.g., wetland inputs. Here, we investigate how mangroves and saltmarshes influence coastal carbonate chemistry and quantify the contribution of alkalinity and dissolved inorganic carbon (DIC) outwelling to blue carbon budgets. Observations from 45 mangroves and 16 saltmarshes worldwide revealed that &gt;70% of intertidal wetlands export more DIC than alkalinity, potentially decreasing the&nbsp;pH of coastal waters. Porewater-derived DIC outwelling (81 ± 47 mmol m<sup>−2</sup><span>&nbsp;</span>d<sup>−1</sup><span>&nbsp;</span>in mangroves and 57 ± 104 mmol m<sup>−2</sup><span>&nbsp;</span>d<sup>−1</sup><span>&nbsp;</span>in saltmarshes) was the major term in blue carbon budgets. However, substantial amounts of fixed carbon remain unaccounted for. Concurrently, alkalinity outwelling was similar or higher than sediment carbon burial and is therefore a significant but often overlooked carbon sequestration mechanism.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41467-023-44037-w","usgsCitation":"Reithmaier, G., Cabral, A., Akhand, A., Bogard, M., Borges, A., Bouillon, S., Burdige, D.J., Call, M., Chen, N., Chen, X., , C., Eagle, M.J., Kristensen, E., Kroeger, K.D., Lu, Z., Maher, D., Perez-Llorens, L., Ray, R., Taillardat, P., Tamborski, J., Upstill-Goddard, R.C., Wang, F., Wang, Z., Xiao, K., Yau, Y., and Santos, I., 2023, Carbonate chemistry and carbon sequestration driven by inorganic carbon outwelling from mangroves and saltmarshes: Nature, v. 14, 8196, 8 p., https://doi.org/10.1038/s41467-023-44037-w.","productDescription":"8196, 8 p.","ipdsId":"IP-148223","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"links":[{"id":441438,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-023-44037-w","text":"Publisher Index Page"},{"id":423434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2023-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Reithmaier, Gloria","contributorId":332313,"corporation":false,"usgs":false,"family":"Reithmaier","given":"Gloria","email":"","affiliations":[{"id":12695,"text":"University of Gothenburg","active":true,"usgs":false}],"preferred":false,"id":890006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cabral, Alex","contributorId":332314,"corporation":false,"usgs":false,"family":"Cabral","given":"Alex","email":"","affiliations":[{"id":12695,"text":"University of Gothenburg","active":true,"usgs":false}],"preferred":false,"id":890007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Akhand, Anirban","contributorId":332315,"corporation":false,"usgs":false,"family":"Akhand","given":"Anirban","email":"","affiliations":[{"id":79448,"text":"Hong Kong University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":890008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bogard, Matthew","contributorId":272635,"corporation":false,"usgs":false,"family":"Bogard","given":"Matthew","affiliations":[{"id":16962,"text":"U. Washington","active":true,"usgs":false}],"preferred":false,"id":890009,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Borges, Alberto V.","contributorId":268443,"corporation":false,"usgs":false,"family":"Borges","given":"Alberto V.","affiliations":[{"id":55646,"text":"Université de Liège, Unité d’Océanographie Chimique, Liège, Belgium","active":true,"usgs":false}],"preferred":false,"id":890010,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bouillon, Steven","contributorId":332316,"corporation":false,"usgs":false,"family":"Bouillon","given":"Steven","email":"","affiliations":[{"id":49038,"text":"KU Leuven","active":true,"usgs":false}],"preferred":false,"id":890011,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burdige, David J.","contributorId":176963,"corporation":false,"usgs":false,"family":"Burdige","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":890012,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Call, Mitchel","contributorId":332317,"corporation":false,"usgs":false,"family":"Call","given":"Mitchel","email":"","affiliations":[{"id":40535,"text":"Southern Cross University","active":true,"usgs":false}],"preferred":false,"id":890013,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chen, Nengwang","contributorId":237803,"corporation":false,"usgs":false,"family":"Chen","given":"Nengwang","email":"","affiliations":[{"id":47617,"text":"Xiamen University, China","active":true,"usgs":false}],"preferred":false,"id":890014,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chen, Xiaogang","contributorId":332318,"corporation":false,"usgs":false,"family":"Chen","given":"Xiaogang","email":"","affiliations":[{"id":79449,"text":"Westlake University","active":true,"usgs":false}],"preferred":false,"id":890015,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":" Cotovicz","contributorId":332319,"corporation":false,"usgs":false,"given":"Cotovicz","email":"","affiliations":[{"id":79450,"text":"Leibniz Institute for Baltic Sea Research","active":true,"usgs":false}],"preferred":false,"id":890016,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science 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Zeyang","contributorId":332320,"corporation":false,"usgs":false,"family":"Lu","given":"Zeyang","email":"","affiliations":[{"id":63579,"text":"Xiamen University","active":true,"usgs":false}],"preferred":false,"id":890020,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Maher, Damien","contributorId":332322,"corporation":false,"usgs":false,"family":"Maher","given":"Damien","affiliations":[{"id":40535,"text":"Southern Cross University","active":true,"usgs":false}],"preferred":false,"id":890021,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Perez-Llorens, Lucas","contributorId":332324,"corporation":false,"usgs":false,"family":"Perez-Llorens","given":"Lucas","email":"","affiliations":[{"id":79451,"text":"University of Cadiz","active":true,"usgs":false}],"preferred":false,"id":890022,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Ray, Raghab","contributorId":332326,"corporation":false,"usgs":false,"family":"Ray","given":"Raghab","email":"","affiliations":[{"id":40674,"text":"The University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":890023,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Taillardat, Pierre","contributorId":242983,"corporation":false,"usgs":false,"family":"Taillardat","given":"Pierre","email":"","affiliations":[{"id":40151,"text":"University of Quebec Montreal","active":true,"usgs":false}],"preferred":false,"id":890024,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Tamborski, Joseph","contributorId":267856,"corporation":false,"usgs":false,"family":"Tamborski","given":"Joseph","email":"","affiliations":[{"id":55518,"text":"Department of Marine Chemistry & Geochemistry, Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":890025,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Upstill-Goddard, Robert 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Kai","contributorId":332328,"corporation":false,"usgs":false,"family":"Xiao","given":"Kai","email":"","affiliations":[{"id":78727,"text":"Southern University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":890029,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Yau, Yvonne","contributorId":332329,"corporation":false,"usgs":false,"family":"Yau","given":"Yvonne","email":"","affiliations":[{"id":12695,"text":"University of Gothenburg","active":true,"usgs":false}],"preferred":false,"id":890030,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Santos, Isaac","contributorId":332330,"corporation":false,"usgs":false,"family":"Santos","given":"Isaac","email":"","affiliations":[{"id":12695,"text":"University of Gothenburg","active":true,"usgs":false}],"preferred":false,"id":890031,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}}
,{"id":70262808,"text":"70262808 - 2023 - Bee species richness through time in an urbanizing landscape  of the southeastern United State","interactions":[],"lastModifiedDate":"2025-01-23T15:43:30.327723","indexId":"70262808","displayToPublicDate":"2023-12-11T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Bee species richness through time in an urbanizing landscape  of the southeastern United State","docAbstract":"<p><span>Compared to non-urban environments, cities host ecological communities with altered taxonomic diversity and functional trait composition. However, we know little about how these urban changes take shape over time. Using historical bee (Apoidea: Anthophila) museum specimens supplemented with online repositories and researcher collections, we investigated whether bee species richness tracked urban and human population growth over the past 118 years. We also determined which species were no longer collected, whether those species shared certain traits, and if collector behavior changed over time. We focused on Wake County, North Carolina, United States where human population size has increased over 16 times over the last century along with the urban area within its largest city, Raleigh, which has increased over four times. We estimated bee species richness with occupancy models, and rarefaction and extrapolation curves to account for imperfect detection and sample coverage. To determine if bee traits correlated with when species were collected, we compiled information on native status, nesting habits, diet breadth, and sociality. We used non-metric multidimensional scaling to determine if individual collectors contributed different bee assemblages over time. In total, there were 328 species collected in Wake County. We found that although bee species richness varied, there was no clear trend in bee species richness over time. However, recent collections (since 2003) were missing 195 species, and there was a shift in trait composition, particularly lost species were below-ground nesters. The top collectors in the dataset differed in how often they collected bee species, but this was not consistent between historic and contemporary time periods; some contemporary collectors grouped closer together than others, potentially due to focusing on urban habitats. Use of historical collections and complimentary analyses can fill knowledge gaps to help understand temporal patterns of species richness in taxonomic groups that may not have planned long-term data.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.17060","usgsCitation":"Ruzi, S., Youngsteadt, E., Cherveny, A., Kettenbach, J., Levenson, H., Carley, D., Collazo, J.A., and Irwin, R., 2023, Bee species richness through time in an urbanizing landscape  of the southeastern United State: Global Change Biology, v. 30, no. 1, e17060, 18 p., https://doi.org/10.1111/gcb.17060.","productDescription":"e17060, 18 p.","ipdsId":"IP-157583","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":481065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.17060","text":"Publisher Index Page"},{"id":480993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","county":"Wake County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-78.5465,36.0218],[-78.4307,35.9795],[-78.3969,35.9387],[-78.3567,35.9318],[-78.351,35.909],[-78.3385,35.9052],[-78.3347,35.8997],[-78.3302,35.896],[-78.3245,35.896],[-78.3177,35.8963],[-78.3137,35.8976],[-78.3081,35.8935],[-78.2948,35.8797],[-78.292,35.8792],[-78.2893,35.8741],[-78.2859,35.8713],[-78.2831,35.8681],[-78.2782,35.8631],[-78.2749,35.8567],[-78.2756,35.8494],[-78.2707,35.843],[-78.2657,35.8361],[-78.2652,35.8325],[-78.2613,35.8315],[-78.2591,35.826],[-78.2599,35.8183],[-78.3731,35.7523],[-78.4635,35.7072],[-78.4686,35.7087],[-78.4709,35.7078],[-78.4732,35.7046],[-78.4778,35.7011],[-78.5716,35.6255],[-78.708,35.5191],[-78.9196,35.5857],[-78.9956,35.6104],[-78.9796,35.6656],[-78.9439,35.7515],[-78.9421,35.756],[-78.9403,35.7615],[-78.9337,35.7859],[-78.9191,35.8216],[-78.9096,35.8506],[-78.9076,35.8678],[-78.89,35.8676],[-78.8298,35.8689],[-78.8056,35.9281],[-78.7609,35.9176],[-78.751,35.9307],[-78.7372,35.941],[-78.714,35.9729],[-78.7009,36.0068],[-78.6985,36.0131],[-78.7048,36.0091],[-78.7077,36.0087],[-78.7076,36.0132],[-78.7052,36.0223],[-78.7085,36.0287],[-78.7102,36.0287],[-78.713,36.0278],[-78.7164,36.0283],[-78.7232,36.0334],[-78.726,36.0343],[-78.7272,36.0334],[-78.7278,36.0289],[-78.7324,36.0267],[-78.7353,36.0199],[-78.7422,36.0209],[-78.75,36.026],[-78.7551,36.0283],[-78.7545,36.0301],[-78.7511,36.0323],[-78.7499,36.035],[-78.747,36.0395],[-78.7492,36.0427],[-78.7503,36.0468],[-78.7519,36.0491],[-78.7564,36.0532],[-78.7498,36.0718],[-78.7088,36.0768],[-78.6895,36.0752],[-78.5922,36.0378],[-78.5465,36.0218]]]},\"properties\":{\"name\":\"Wake\",\"state\":\"NC\"}}]}","volume":"30","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruzi, 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