The Zero Ascend Omnispecies (ZAO) fish passage attraction module “ZAO Attractor” is a novel system designed to facilitate upstream passage for a broad spectrum of fish species, with a particular focus on American shad and river herring (alewife and/or blueback herring). Combining the use of prefabricated, modular components with advanced manufacturing, the ZAO aims to provide a cost-effective and scalable solution for fish passage attractions across various hydropower sites. The system features a surface level entry, so fish do not need to climb. In addition, it is designed to be adjusted and repositioned to create the most effective attraction flows by managing the outflows from hydropower turbines.
Budget Period 1 (BP1) focused on the design and modeling of the ZAO Attractor and demonstrated the engineering feasibility of a modular, prefabricated, hydrodynamically efficient structure with surface level entry and passage. During BP1, the hypothesis was that certain structural adaptations, such as the addition of long fins, could direct turbine outflows to create a desirable downstream flow. Simulations, however, were inconclusive, revealing the complex nature of fish preferences for hydraulic conditions. It was discovered that there were limited published studies on the direct correlation between quantified flow patterns and fish attraction, emphasizing the need for controlled studies to observe and measure these effects.
In Budget Period 2 (BP2), controlled studies with live fish were prioritized to address these complexities. A partially scaled ZAO Attractor was evaluated in laboratory conditions using native river water to assess its capability to attract and guide fish. Despite challenges with flume flow conditions and the impact of flume dimensions on flow directionality and velocity, the studies provided insights into fish behavior and preferences, particularly the requirement for a consistent flow stream for migration cues. Adjustments to the fin structure demonstrated potential effectiveness in guiding fish toward the module. However, the hydraulic conditions within the flume environment did not accurately reflect typical in-river scenarios, therefore the results were inconclusive with respect to the optimal system configuration for in-river use.
In the future, conducting comprehensive field studies can enhance understanding of the interactions between fish behavior and flow conditions created by the ZAO Attractor. Additionally, a design review is advised, particularly regarding the load scenarios throughout the seasons and positioning of the ZAO Attractor. These studies should continue to refine the design to achieve its intended benefits: economical and effective fish attraction and passage that can be adapted to specific site conditions while allowing for continued energy generation at sites up for re-licensure and adding hydropower generation to previously untapped resources in non-powered dams and new stream reaches.
In conclusion, the ZAO fish passage attraction module presents a promising approach to fish passage at hydropower stations, with the potential to balance environmental concerns with renewable energy development. However, further field validation and optimization are necessary to ensure its effectiveness and practicality in real-world applications.
","language":"English","publisher":"Littoral Power Systems, Inc.","doi":"10.2172/3001800","usgsCitation":"Leighton, K., Bryan, J., Mulligan, K., Stewart, K., Jacobson, P., Duquette, D., and Challa, R., 2024, Prefabricated Zero Ascend Omnispecies (ZAO) modular fish passage modules using advanced manufacturing techniques: Final Technical Report, 187 p., https://doi.org/10.2172/3001800.","productDescription":"187 p.","ipdsId":"IP-165273","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":497302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Leighton, Katherine","contributorId":363650,"corporation":false,"usgs":false,"family":"Leighton","given":"Katherine","affiliations":[],"preferred":false,"id":951898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bryan, Janine","contributorId":245811,"corporation":false,"usgs":false,"family":"Bryan","given":"Janine","email":"","affiliations":[{"id":49332,"text":"Whooshh Innovations","active":true,"usgs":false}],"preferred":false,"id":951871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mulligan, Kevin 0000-0002-3534-4239 kmulligan@usgs.gov","orcid":"https://orcid.org/0000-0002-3534-4239","contributorId":177024,"corporation":false,"usgs":true,"family":"Mulligan","given":"Kevin","email":"kmulligan@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":951872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stewart, Kevin G.","contributorId":352583,"corporation":false,"usgs":false,"family":"Stewart","given":"Kevin G.","affiliations":[{"id":84275,"text":"University of North Carolina-Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":951873,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jacobson, Paul","contributorId":363601,"corporation":false,"usgs":false,"family":"Jacobson","given":"Paul","affiliations":[{"id":80850,"text":"Electric Power Research Institute","active":true,"usgs":false}],"preferred":false,"id":951874,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duquette, David","contributorId":363651,"corporation":false,"usgs":false,"family":"Duquette","given":"David","affiliations":[],"preferred":false,"id":951899,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Challa, Ravi","contributorId":363603,"corporation":false,"usgs":false,"family":"Challa","given":"Ravi","affiliations":[{"id":86732,"text":"Littoral Power Systems, Inc.,","active":true,"usgs":false}],"preferred":false,"id":951875,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70251818,"text":"sir20245002 - 2024 - Streamflow, base flow, and precipitation trends and simulated effects of Rush Springs aquifer groundwater withdrawals on base flows upgradient from Fort Cobb Reservoir, western Oklahoma","interactions":[],"lastModifiedDate":"2026-01-30T20:06:15.927647","indexId":"sir20245002","displayToPublicDate":"2024-03-04T08:04:05","publicationYear":"2024","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":"2024-5002","displayTitle":"Streamflow, Base Flow, and Precipitation Trends and Simulated Effects of Rush Springs Aquifer Groundwater Withdrawals on Base Flows Upgradient From Fort Cobb Reservoir, Western Oklahoma","title":"Streamflow, base flow, and precipitation trends and simulated effects of Rush Springs aquifer groundwater withdrawals on base flows upgradient from Fort Cobb Reservoir, western Oklahoma","docAbstract":"To better understand the relation between groundwater use in the Rush Springs aquifer and inflows to the Fort Cobb Reservoir, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, used a previously published numerical groundwater-flow model and historical streamflow records to evaluate four scenarios to investigate how changing groundwater withdrawals could affect base flows in streams that flow into Fort Cobb Reservoir. These scenarios consisted of observing simulated base-flow response by (1) scaling the 20-year equal-proportionate-share groundwater-withdrawal rate by various percentages over a 50-year period; (2) scaling the historical groundwater-withdrawal rates by various percentages across the entire Rush Springs aquifer; (3) scaling the historical groundwater-withdrawal rates within various subareas (zones) of the Fort Cobb Reservoir surface watershed; and (4) simulating a base-flow-depletion scenario. Cobb, Lake, and Willow Creeks are the major streams upgradient from the Fort Cobb Reservoir (listed from highest to lowest mean annual base flow). The results of scenarios 1 and 2 indicated that Willow Creek is the most susceptible to drying, but Cobb Creek was the most likely to have reduced base flow. Scenarios 3 and 4 indicated that groundwater withdrawals affect Cobb Creek base flows over a broader watershed area compared to Lake and Willow Creeks. In scenario 4, Cobb Creek base-flow depletion was higher across a larger area than Lake Creek and Willow Creek. Groundwater withdrawals in the Cobb Creek watershed tended to affect total inflows into Fort Cobb Reservoir more than other areas in the extent of the Rush Springs aquifer.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
The ability to sex individuals is an important component of many behavioural and ecological investigations and provides information for demographic models used in conservation and species management. However, many birds are difficult to sex using morphological characters or traditional molecular sexing methods. In this study, we developed probabilistic models for sexing birds using quantitative PCR (qPCR) data. First, we quantified distributions of gene copy numbers at a set of six sex-linked genes, including the sex-determining gene DMRT1, for individuals across 17 species and seven orders of birds (n = 150). Using these data, we built predictive logistic models for sex identification and tested their performance with independent samples from 51 species and 13 orders (n = 209). Models using the two loci most highly correlated with sex had greater accuracy than models using the full set of sex-linked loci, across all taxonomic levels of analysis. Sex identification was highly accurate when individuals to be assigned were of species used in model building. Our analytical approach was widely applicable across diverse neognath bird lineages spanning millions of years of evolutionary divergence. Unlike previous methods, our probabilistic framework incorporates uncertainty around qPCR measurements as well as biological variation within species into decision-making rules. We anticipate that this method will be useful for sexing birds, including those of high conservation concern and/or subsistence value, that have proven difficult to sex using traditional approaches. Additionally, the general analytical framework presented in this paper may also be applicable to other organisms with sex chromosomes.
We evaluated the Virgin, Verde, Salt, and Gila Rivers in the Lower Colorado River Basin. The watersheds have extents in Arizona, Utah, New Mexico, US and Sonora, MX.
We calculated trends in total dissolved solids (TDS) concentrations and fluxes with the Weighted Regressions on Time, Discharge and Season model. The modeling framework leverages daily streamflow and discrete water quality observations at specific monitoring sites. We evaluated trends for a common period (1976–2008) and the whole period of record at each monitoring site in terms of climate and anthropogenic controls.
Three rivers had persistent TDS concentrations exceeding the EPA secondary drinking water standard. All were associated with a geologic source of TDS. We observed increases and decreases in TDS concentrations at our monitoring sites, contrasting with global freshwater salinization and declining TDS concentrations in the Upper Colorado River Basin (UCRB). We attributed concentration variability to wintertime hydroclimatic forcing, with secondary influences of human water use. Reservoirs may decrease TDS concentrations by 50%. Efficiency improvements in irrigation and mining water uses may decrease TDS concentrations, while municipal growth increases TDS concentrations. We observed TDS flux declines at most monitoring sites. We attributed up to 85% of the TDS flux trend to changes in streamflow arising from drought and groundwater use. This study informs salinity dynamics in arid and aridifying locations, including the UCRB.
Wildlife disease management decisions often require rapid responses to situations that are fraught with uncertainty. By recognizing that management is implemented to achieve specific objectives, resource managers and science partners can identify an analysis technique and develop a monitoring plan to evaluate management effectiveness. For emerging infectious diseases, objectives may take several distinct forms, dependent on the perceived stage of disease emergence (i.e., pre-epidemic, early outbreak, mid-epidemic, and endemic), the expected rate of spread, and the anticipated effect of the disease on host populations. Identifying modeling techniques and metrics that are linked to management objectives will require early and consistent communication between managers and science partners. We link modeling approaches that can be used to forecast and evaluate the performance of intervention strategies with a range of disease management objectives. Our aim is to help scientists recognize alternative modeling approaches which may better align with different forms of disease management objectives, and to help managers evaluate the relevance of proposed modeling approaches to their specified objectives for disease management. Recognizing that disease management objectives can take different forms, and thus require different modeling approaches, can help wildlife disease response teams (i.e., natural resource managers, scientists, and stakeholders working collaboratively) better prepare and respond to disease threats.
Fluvial landscape analysis is an essential part of geomorphology, hydrology, ecology, and cartography. It is traditionally focused on the transition between hillslopes and channel domain, in which the network drainage is represented by static flow lines. However, the natural fluctuations of the processes occurring in the watershed induce lateral and longitudinal expansions and contractions in the drainage patterns and variations of stream surface area. These dynamics can be better understood by introducing a two-dimensional (2D) view of catchment hydrography, in which river width and floodplain are included in the analysis.
The novelty introduced in this work is the development of a hydrodynamic hierarchical framework (HHF) to analyse the transitions among geomorphic and hydrographic features of the fluvial landscape, distinguishing hillslope, unchanneled valleys, floodplains, and single/multithreads channels. HHF is based on the estimation of nested inundation pattern domains (IPDs) from digital elevation models and 2D hydrodynamic modeling. IPDs are defined by scaling laws that characterize log–log relations between watershed drainage density and unit discharge thresholds extracted from a 2D direct rainfall method (DRM) under steady state solutions.
The physical significance of the IPDs is analysed within the context of both the physiographic features of the fluvial landscape and the rainfall rates employed as input for the modeling approach. Initially, the spatial heterogeneity of the IPDs is used to derive stream width metrics as a function of the rainfall rate. Then, a spatial index, representative of the IPDs' heterogeneity, is introduced as a measure of the susceptibility of the drainage network surface area to expansion and contraction. Finally, the consistency of the results is assessed in comparison to another hydrodynamic-based method for fluvial landscape analysis recently proposed in the literature.
The proposed approach is analysed using challenging mountain and low-relief environments, characterized by multithread channels, meander cut-offs, oxbow lakes, and extreme landscapes that feature glacial outwash, permafrost, and peatlands.
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Bari","active":true,"usgs":false}],"preferred":false,"id":925352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":925353,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":925354,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70252589,"text":"70252589 - 2024 - Seasonal and decadal subsurface thaw dynamics of an Aufeis feature investigated through numerical simulations","interactions":[],"lastModifiedDate":"2024-03-29T11:55:55.292733","indexId":"70252589","displayToPublicDate":"2024-03-03T06:54:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal and decadal subsurface thaw dynamics of an Aufeis feature investigated through numerical simulations","docAbstract":"Aufeis (also known as icings) are large sheet-like masses of layered ice that form in river channels in arctic environments in the winter as groundwater discharges to the land surface and subsequently freezes. Aufeis are important sources of water for Arctic river ecosystems, bolstering late summer river discharge and providing habitat for caribou escaping insect harassment. The aim of this research is to use numerical simulations to evaluate a conceptual model of subsurface hydrogeothermal conditions that can lead to the formation of aufeis. We used a conceptual model based on geophysical data from the Kuparuk aufeis field on the North Slope of Alaska to develop a two-dimensional heterogeneous vertical profile model of groundwater flow, heat transport, and freeze/thaw dynamics. Modelling results showed that groundwater can flow to the land surface through subvertical high permeability pathways during winter months when the lower permeability soils near the land surface are frozen. The groundwater discharge can freeze on the surface, contributing to aufeis formation throughout the winter. We performed sensitivity analyses on subsurface properties and surface temperature and found that aufeis formation is most sensitive to the volume of unfrozen water available in the subsurface and the rate at which the subsurface water travels to the land surface. Although a trend of warming air temperatures will lead to a greater volume of unfrozen subsurface water, the aufeis volume can be reduced under warming conditions if the period of time for which air temperatures are below freezing is reduced.
As part of a multi-year project, funded by the California Energy Commission, annual magnetotelluric (MT) surveys have been collected at The Geysers geothermal field in northern California with the goal of measuring temporal changes within the steam field. The repeat surveys started in 2021 and repeated a 2017 survey (Peacock et al., 2020) with further extension to the southern part of the geothermal field. Temporal variations in the MT transfer functions are observed to be spatially coherent and compartmentalized. Mapping residual phase tensor ellipses demonstrates the direction of maximum change is often aligned with existing fracture orientations. Three dimensional inversion of the MT data, using the inversion results from previous years as the starting model, indicates that the steam reservoir has generally become more resistive over time (~10%), suggesting more steam in the field. A few pockets within the steam field have become more electrically conductive over time and are collocated with injection wells, suggesting either more fluid content in those zones, less steam, or more saline fluids.
","conferenceTitle":"49th Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 12-14, 2024","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford University","usgsCitation":"Peacock, J.R., Alumbaugh, D., Mitchell, M.A., and Hartline, C., 2024, Summary of annual repeat magnetotelluric surveys of the Geysers geothermal field, 49th Workshop on Geothermal Reservoir Engineering, Stanford, CA, February 12-14, 2024, 6 p.","productDescription":"6 p.","ipdsId":"IP-161861","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":501541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501540,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pangea.stanford.edu/ERE/db/IGAstandard/record_detail.php?id=36417","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Geysers geothermal field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.9167,\n 38.9\n ],\n [\n -122.9167,\n 38.7333\n ],\n [\n -122.667,\n 38.7333\n ],\n [\n -122.667,\n 38.9\n ],\n [\n -122.9167,\n 38.9\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peacock, Jared R. 0000-0002-0439-0224 jpeacock@usgs.gov","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":4996,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared","email":"jpeacock@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":899089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alumbaugh, David 0000-0002-6975-7197","orcid":"https://orcid.org/0000-0002-6975-7197","contributorId":299109,"corporation":false,"usgs":false,"family":"Alumbaugh","given":"David","email":"","affiliations":[{"id":64775,"text":"Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":899090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, Michael Albert 0000-0001-5070-8793","orcid":"https://orcid.org/0000-0001-5070-8793","contributorId":299110,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"","middleInitial":"Albert","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":899091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hartline, C.","contributorId":335661,"corporation":false,"usgs":false,"family":"Hartline","given":"C.","affiliations":[{"id":38755,"text":"Calpine","active":true,"usgs":false}],"preferred":false,"id":899092,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263100,"text":"70263100 - 2024 - Southern fox squirrel and eastern gray squirrel interactions in a fire-maintained ecosystem","interactions":[],"lastModifiedDate":"2025-01-29T16:39:26.167514","indexId":"70263100","displayToPublicDate":"2024-03-01T10:33:52","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3909,"text":"Journal of the Southeastern Association of Fish and Wildlife Agencies","active":true,"publicationSubtype":{"id":10}},"title":"Southern fox squirrel and eastern gray squirrel interactions in a fire-maintained ecosystem","docAbstract":"Southern fox squirrels (Sciurus niger niger) have been declining due to habitat fragmentation, cover type conversion, and fire suppression in the Southeast. A decrease in growing season burns has led to hardwood encroachment and forest mesophication that benefit the competing eastern gray squirrels (S. carolinensis). In the southern Coastal Plain and Piedmont of Virginia, these pattern raises the question of whether gray squirrels are competitively excluding southern fox squirrels in these altered landscapes. From October 2019 to October 2020, we conducted continual camera trapping for southern fox squirrels and gray squirrels on the Big Woods/Piney Grove Complex (BWPGC) and at Fort Barfoot (FB) in the Coastal Plain and lower Piedmont of Virginia, respectively. Both sites are among the few areas that still contain large, intact pine savanna and mixed-pine hardwood forests in southeastern Virginia. We used two-species occupancy modeling to investigate occupancy estimates of southern fox squirrels and possible competition with gray squirrels, based on detection histories collected from camera traps on BWPGC and FB. We then conducted informed single-species occupancy modeling to estimate the necessary level-of-effort (LOE) required to determine the probable absence of southern fox squirrels at sampling sites in the region. No fox squirrels were observed at FB. Our top, two-species occupancy model showed that gray squirrel occupancy increased with increasing time since last burn. However, southern fox squirrel occupancy, in the absence of gray squirrels, decreased with increasing time since last burn. Gray squirrels typically inhabited hardwood-dominant closed canopy areas whereas southern fox squirrels did so at BWPGC only in the absence of gray squirrels. This suggests that southern fox squirrels are selecting areas on BWPGC based on resource needs and possibly competition with gray squirrels. A single-season occupancy model confirmed that southern fox squirrel occupancy decreased with time since the last burn. Our LOE analysis indicated that seven consecutive days of camera trapping without a detection would provide 90% confidence of the subspecies’ absence in areas burned two or more years prior to sampling. Southern fox squirrels may benefit from increased short-rotation burns to maintain or enhance pine-hardwood savannas and pine-hardwood savanna ecotones in southeastern Virginia.
","language":"English","publisher":"Southeastern Association of Fish and Wildlife Agencies","usgsCitation":"Guill, M., De La Cruz, J., Puckett, M., Klopfer, S., Martin, B., and Ford, W., 2024, Southern fox squirrel and eastern gray squirrel interactions in a fire-maintained ecosystem: Journal of the Southeastern Association of Fish and Wildlife Agencies, v. 11, p. 215-222.","productDescription":"8 p.","startPage":"215","endPage":"222","ipdsId":"IP-142691","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481441,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://seafwa.org/journal/2024/southern-fox-squirrel-and-eastern-gray-squirrel-interactions-fire-maintained-ecosystem"},{"id":481465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78,\n 37.1\n ],\n [\n -78,\n 36.9\n ],\n [\n -77,\n 36.9\n ],\n [\n -77,\n 37.1\n ],\n [\n -78,\n 37.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Guill, M.H.","contributorId":350233,"corporation":false,"usgs":false,"family":"Guill","given":"M.H.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":925510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De La Cruz, J.L.","contributorId":349847,"corporation":false,"usgs":false,"family":"De La Cruz","given":"J.L.","affiliations":[{"id":81893,"text":"Virginia Polytechnic and State University","active":true,"usgs":false}],"preferred":false,"id":925511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Puckett, M.","contributorId":350236,"corporation":false,"usgs":false,"family":"Puckett","given":"M.","affiliations":[{"id":56188,"text":"Virginia Department of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":925512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klopfer, S.D.","contributorId":350239,"corporation":false,"usgs":false,"family":"Klopfer","given":"S.D.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":925513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, B.","contributorId":350241,"corporation":false,"usgs":false,"family":"Martin","given":"B.","affiliations":[{"id":83699,"text":"Fort Pickett","active":true,"usgs":false}],"preferred":false,"id":925514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"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":925515,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70257538,"text":"70257538 - 2024 - Seasonal activity patterns of northern long-eared bats on the coastal Mid-Atlantic","interactions":[],"lastModifiedDate":"2024-09-09T11:12:12.04529","indexId":"70257538","displayToPublicDate":"2024-03-01T10:09:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3909,"text":"Journal of the Southeastern Association of Fish and Wildlife Agencies","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal activity patterns of northern long-eared bats on the coastal Mid-Atlantic","docAbstract":"Conservation of bats declining from white-nose syndrome (WNS) impacts requires an understanding of both temporal and landscape-level habitat relationships. Traditionally, much of the research on bat ecology has focused on behavior of summer maternity colonies within species’ distribution cores, including that of the endangered northern long-eared bat (Myotis septentrionalis). To further our knowledge of this species, we evaluated multi-season activity patterns in eastern North Carolina and Virginia, including areas where populations were recently discovered. We used passive acoustic monitoring to assess relative and probable activity of northern long-eared bats from October 2016 to August 2021. Northern long-eared bat relative activity was greatest in areas containing greater proportions of woody wetlands and upland pine-dominated evergreen forests. However, the likelihood of recording northern long-eared bats was associated with smaller proportions of woody wetlands and open water resources. Furthermore, we observed a higher probability of recording northern long-eared bats during non-winter seasons. Probable activity was greatest at temperatures between 10 and 25 C, potentially highlighting an optimal thermoneutral zone for the species regionally. Relative activity of northern long-eared bats on the Coastal Plain of Virginia and North Carolina was primarily driven by cover features, whereas probable activity was driven by a combination of cover features, seasonality, and temperature. Therefore, acoustical surveys for this species may be most effective when targeting woody wetlands adjacent to upland forests, particularly upland pine-dominated evergreen stands, during moderate temperatures of non-winter seasons (1 April–15 November). Moreover, conservation of a diverse mosaic of woody wetlands juxtaposed by upland forests may promote both roosting and overwintering habitat, thereby enhancing overwintering survival, maternity colony establishment, and ultimately, successful reproduction of northern long-eared bats.
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Resources","active":true,"usgs":false}],"preferred":false,"id":910654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"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":910655,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70264589,"text":"70264589 - 2024 - Surface elevation trends in North Carolina's coastal wetlands","interactions":[],"lastModifiedDate":"2025-03-17T14:31:11.336488","indexId":"70264589","displayToPublicDate":"2024-03-01T09:22:04","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Surface elevation trends in North Carolina's coastal wetlands","docAbstract":"Coastal wetlands exist in the narrow fringe between uplands and open water and consequently, are uniquely vulnerable to the impacts of sea level rise (SLR). Predictive models suggest that in the coming decades sea level rise will lead to substantial losses of coastal wetland habitat in North Carolina. Empirical measurements of wetland response to SLR are vital for understanding which wetland complexes are most immediately threatened, so that mitigation, adaptation, and conservation efforts can be prioritized accordingly. Surface Elevation Tables (SETs) provide high resolution measures of wetland elevation change that can meet this need.
The North Carolina SET Community of Practice (NC SET COP) is a voluntary and unfunded partnership among stakeholders who have either installed Surface Elevation Tables (SETs) in North Carolina coastal wetlands, or who rely on SET data. The NC SET COP was formed in 2018 to identify and map the locations of all SETs installed within North Carolina, increase collaboration among SET users, and support efforts to identify regional trends in North Carolina coastal wetland response to sea level rise. The data presented here represent the first synoptic analysis of elevation trend data collected by NC SET COP partners.
Of 132 SETs installed across North Carolina (NC), 33 recorded net losses in elevation over the entire record of measurement. Among the 99 SETs that recorded positive elevation change, 79 (80%) did not build elevation fast enough to keep pace with the average rate of SLR over the past 30 years. The story these data tell is clear: the majority of NC’s coastal wetlands are not keeping pace with SLR. These data also provide a spatially explicit understanding of which wetlands are most at risk, and as a result, the SET data can help guide the use of restoration efforts for maximum effectiveness.
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","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"HydroVisions","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Groundwater Resources Association","usgsCitation":"Bedekar, V., Hatch, T., Traum, J.A., Tolley, G., Singh, A., and Faunt, C., 2024, Models: Tools for estimating and predicting subsidence, in HydroVisions, v. 33, no. Spring, p. 14-17.","productDescription":"4 p.","startPage":"14","endPage":"17","ipdsId":"IP-162649","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":481259,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.grac.org/page/hydrovisions","linkFileType":{"id":5,"text":"html"}},{"id":481260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"Spring","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bedekar, Vivek","contributorId":349887,"corporation":false,"usgs":false,"family":"Bedekar","given":"Vivek","affiliations":[{"id":83526,"text":"S.S. Papadopulos & Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":925065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatch, Tyler","contributorId":349888,"corporation":false,"usgs":false,"family":"Hatch","given":"Tyler","affiliations":[{"id":63339,"text":"Intera","active":true,"usgs":false}],"preferred":false,"id":925066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":925067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tolley, Gus","contributorId":349889,"corporation":false,"usgs":false,"family":"Tolley","given":"Gus","affiliations":[{"id":83527,"text":"Geo-Logic Associates","active":true,"usgs":false}],"preferred":false,"id":925068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singh, Abhishek","contributorId":349890,"corporation":false,"usgs":false,"family":"Singh","given":"Abhishek","affiliations":[{"id":63339,"text":"Intera","active":true,"usgs":false}],"preferred":false,"id":925069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Faunt, Claudia C. 0000-0001-5659-7529 ccfaunt@usgs.gov","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":150147,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia C.","email":"ccfaunt@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":925070,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70257410,"text":"70257410 - 2024 - occupancyTuts: Occupancy modelling tutorials with RPresence","interactions":[],"lastModifiedDate":"2024-08-30T16:17:48.478518","indexId":"70257410","displayToPublicDate":"2024-03-01T09:07:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"occupancyTuts: Occupancy modelling tutorials with RPresence","docAbstract":"1. The occupancy modelling framework offers tremendous flexibility in estimating species abundance and distribution patterns while accounting for imperfect detection, and has seen rapid growth and adoption since its introduction at the beginning of the century.
2. At the same time, in an era of big data, there are increasing demands on developing quantitative skills and proficiency in young ecologists, many of whom lack the quantitative training needed to conduct research professionally.
3. We introduce occupancyTuts, an R package that features 28 learnr tutorials that teach the statistical underpinnings of several occupancy models. The tutorials include written content, instructional videos, R exercises, and quiz elements, covering a range of topics including statistical underpinnings, single- and dynamic-occupancy models, study design and several of the ‘spin-off’ models that extend the basic framework.
4. We plan for development of new tutorials that use RPresence as the analysis engine, and welcome new tutorial contributions that use other R packages as the analysis engine as well.
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.14285","usgsCitation":"Donovan, T.M., Hines, J.E., and MacKenzie, D., 2024, occupancyTuts: Occupancy modelling tutorials with RPresence: Methods in Ecology and Evolution, v. 15, no. 3, p. 477-483, https://doi.org/10.1111/2041-210X.14285.","productDescription":"7 p.","startPage":"477","endPage":"483","ipdsId":"IP-156509","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":440251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14285","text":"Publisher Index Page"},{"id":433381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-01-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hines, James E. 0000-0002-3927-9411 jhines@usgs.gov","orcid":"https://orcid.org/0000-0002-3927-9411","contributorId":342662,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":910266,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacKenzie, Darryl","contributorId":342664,"corporation":false,"usgs":false,"family":"MacKenzie","given":"Darryl","affiliations":[{"id":81910,"text":"Proteus Consulting","active":true,"usgs":false}],"preferred":false,"id":910267,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70259731,"text":"70259731 - 2024 - Determining the distribution, status, and linkages of Agassiz's desert tortoise populations in the uplands surrounding the Coachella Valley","interactions":[],"lastModifiedDate":"2024-10-22T12:28:52.510945","indexId":"70259731","displayToPublicDate":"2024-03-01T07:27:37","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Determining the distribution, status, and linkages of Agassiz's desert tortoise populations in the uplands surrounding the Coachella Valley","docAbstract":"In support of the goals of the Coachella Valley Conservation Commission and the Bureau of Land Management, we performed surveys to determine the status, distribution, demographics, and possible genetic linkages of Agassiz’s desert tortoise (Gopherus agassizii) populations within the Coachella Valley Multiple Species Habitat Conservation Plan (CVMSHCP) area during a multi-decadal megadrought. Federal, state, and numerous parcels of privately owned conservation lands in the uplands around the periphery of the Coachella Valley were surveyed. Desert tortoise distribution data collected will be used to develop a species habitat model. These data will be overlaid with location data of flammable invasive plant species to inform fuels management and invasive plant control efforts in sensitive species habitat, as well as continue to identify high quality habitat and important desert tortoise linkage areas around the Coachella Valley. We also surveyed two established G. agassizii study plots – one at the Mesa Wind Energy Facility near Palm Springs, California and one at the Boyd Deep Canyon Desert Research Center. At those locations, we used resurveys and radio telemetry to assess habitat use, demography, and population status. We also used camera trapping at Deep Canyon to observe tortoise activities and behaviors in an unusual low elevation tortoise habitat.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2023 CVCC Annual Report","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Coachella Valley Conservation Commission","collaboration":"Coachella Valley Conservation Commission, Bureau of Land Management, UCR Boyd Deep Canyon Desert Research Center, Joshua Tree National Park, University of California Riverside, California State University at Fullerton, California Department of Fish and Wildlife","usgsCitation":"Puffer, M.R., Lovich, J.E., and Cummings, K.L., 2024, Determining the distribution, status, and linkages of Agassiz's desert tortoise populations in the uplands surrounding the Coachella Valley, 77 p.","productDescription":"77 p.","startPage":"177","endPage":"253","ipdsId":"IP-150045","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":463075,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cvmshcp.org/annual-reports/Annual-Report-2023.pdf"},{"id":463092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Coachella Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.83577301985537,\n 34.107460375171385\n ],\n [\n -116.83577301985537,\n 33.31867102335272\n ],\n [\n -115.76010558997707,\n 33.31867102335272\n ],\n [\n -115.76010558997707,\n 34.107460375171385\n ],\n [\n -116.83577301985537,\n 34.107460375171385\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Puffer, Michele R. 0000-0003-4957-0963","orcid":"https://orcid.org/0000-0003-4957-0963","contributorId":225575,"corporation":false,"usgs":true,"family":"Puffer","given":"Michele","email":"","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":916494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":916495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cummings, Kristy L. 0000-0002-8316-5059","orcid":"https://orcid.org/0000-0002-8316-5059","contributorId":202061,"corporation":false,"usgs":true,"family":"Cummings","given":"Kristy","email":"","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":916496,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70251962,"text":"70251962 - 2024 - Analysis adapted from text mining quantitively reveals abrupt and gradual plant-community transitions after fire in sagebrush steppe","interactions":[],"lastModifiedDate":"2024-03-08T12:45:44.617355","indexId":"70251962","displayToPublicDate":"2024-03-01T06:44:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Analysis adapted from text mining quantitively reveals abrupt and gradual plant-community transitions after fire in sagebrush steppe","docAbstract":"Plant communities vary both abruptly and gradually over time but differentiating between types of change can be difficult with existing classification and ordination methods. Structural topic modeling (STRUTMO), a text mining analysis, offers a flexible methodology for analyzing both types of temporal trends.
Our objectives were to (1) identify post-fire dominant sagebrush steppe plant association types and ask how they vary with time at a landscape (multi-fire) scale and (2) ask how often major association changes are apparent at the plot-level scale.
We used STRUTMO and plant species cover collected between 2002–2022 across six large burn areas (1941 plots) in the Great Basin, USA to characterize landscape change in dominant plant association up to 14 years post-fire. In a case study, we assessed frequency of large annual changes (≥ 10% increase in one association and decrease in another) between associations at the plot-level scale.
STRUTMO revealed 10 association types dominated by either perennial bunchgrasses, mixed perennial or annual grasses and forbs, or exotic annual grasses. Across all study fires, associations dominated by large-statured perennial bunchgrasses increased then stabilized, replacing the Sandberg bluegrass (Poa secunda)-dominated association. The cheatgrass (Bromus tectorum)-dominant association decreased and then increased. At the plot-level, bidirectional changes among associations occurred in ~ 75% of observations, and transitions from annual invaded to perennial associations were more common than the reverse.
The analysis revealed that associations dominated by some species (i.e. crested wheatgrass, Agropyron cristatum, Siberian wheatgrass, Agropyron fridgida, or medusahead, Taeniatherum caput-medusae) were more stable than associations dominated by others (i.e. Sandberg bluegrass or cheatgrass). Strong threshold-like transitions were not observed at the multi-fire scale, despite frequent ephemeral plot-level changes.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10980-024-01824-0","usgsCitation":"Applestein, C., Anthony, C.R., and Germino, M., 2024, Analysis adapted from text mining quantitively reveals abrupt and gradual plant-community transitions after fire in sagebrush steppe: Landscape Ecology, v. 39, 64, 16 p., https://doi.org/10.1007/s10980-024-01824-0.","productDescription":"64, 16 p.","ipdsId":"IP-155006","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":440260,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1007/s10980-024-01824-0","text":"Publisher Index Page"},{"id":426445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.0478683572567,\n 45.37400249120009\n ],\n [\n -122.0478683572567,\n 38.46464355773841\n ],\n [\n -113.71058234080544,\n 38.46464355773841\n ],\n [\n -113.71058234080544,\n 45.37400249120009\n ],\n [\n -122.0478683572567,\n 45.37400249120009\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","noUsgsAuthors":false,"publicationDate":"2024-03-01","publicationStatus":"PW","contributors":{"authors":[{"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":896180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anthony, Christopher R. 0000-0003-0968-224X","orcid":"https://orcid.org/0000-0003-0968-224X","contributorId":296314,"corporation":false,"usgs":true,"family":"Anthony","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":896181,"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":896182,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252084,"text":"70252084 - 2024 - River control points for algal productivity revealed by transport analysis","interactions":[],"lastModifiedDate":"2024-03-13T11:45:21.970555","indexId":"70252084","displayToPublicDate":"2024-03-01T06:43:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"River control points for algal productivity revealed by transport analysis","docAbstract":"Measurement of planktonic chlorophyll-a—a proxy for algal biomass—in rivers may represent local production or algae transported from upstream, confounding understanding of algal bloom development in flowing waters. We modeled 3 years of chlorophyll-a transport through a 394-km portion of the Illinois River and found that although algal biomass is longitudinally widespread, most net production occurs at river control points in the upper reaches (up to 3.7 Mg chlorophyll-a y−1 km−1). Up to 69% of the algal biomass in the upper river was a result of within-reach production, with the remainder recruited from headwaters and tributaries. High chlorophyll-a measured farther downstream was largely because of transport from source-area control points, with substantial net losses of algal biomass occurring in the lower river. Modeling the often-overlooked river transport component is necessary to characterize where, when, and why planktonic algae grow and predict how far and fast they move downstream.
Snow avalanches are a hazard and ecological disturbance across mountain landscapes worldwide. Understanding how avalanche frequency affects forests and vegetation improves infrastructure planning, risk management, and avalanche forecasting. We implemented a novel approach using lidar, aerial imagery, and a random forest model to classify imagery-observed vegetation within avalanche paths in southern Glacier National Park, Montana, USA. We calculated spatially explicit avalanche return periods using a physically based spatial interpolation method and characterized the vegetation within those return period zones. The automated vegetation classification model differed slightly between avalanche paths, but the combination of lidar and spectral signature metrics provided the best accuracy (88–92 percent) for predicting vegetation classes within complex avalanche terrain rather than lidar or spectral signature metrics alone. The highest frequency avalanche return periods were broadly characterized by grassland and shrubland, but the influence of topography greatly influences the vegetation classes as well as the return periods. Furthermore, statistically significant differences in lidar-derived vegetation canopy height exist between categorical return periods. The ability to characterize vegetation within various avalanche return periods using remote sensing data provides land use planners and avalanche forecasters a tool for assessing the spatial extent of large-magnitude avalanches in individual avalanche paths.
As part of the periodic update of the geothermal energy assessments for the USA (e.g., last update by Williams and others, 2008), a new three-dimensional temperature map has been constructed for the Great Basin, USA. Williams and DeAngelo (2011) identified uncertainty in estimates of conductive heat flow near land surface as the largest contributor to uncertainty in previously published temperature maps. The new temperature maps incorporate new conductive heat flow estimates developed by DeAngelo and others (2023). Predicted temperatures at depth are compared with representative measurements (for conductively dominated conditions), showing good agreement under relatively simple uniform conditions. Inputs included radiogenic heat production for all layers of 1.89 μW/m3, effective bulk thermal conductivity of 2.7 W/m/°C for all rocks underlying sedimentary basins, and a previously published (Williams and DeAngelo, 2011) empirically driven estimate of increasing thermal conductivity with depth in sedimentary sequences. The resulting three-dimensional temperature model is published in a USGS data release associated with this manuscript (Burns and others, 2023).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 49th workshop on geothermal reservoir engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"49th Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 12-14, 2024","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford Geothermal Workshop","usgsCitation":"Burns, E.R., DeAngelo, J., and Williams, C.F., 2024, Updated three-dimensional temperature maps for the Great Basin, USA, in Proceedings of the 49th workshop on geothermal reservoir engineering, Stanford, CA, February 12-14, 2024, 12 p.","productDescription":"12 p.","ipdsId":"IP-158036","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":426556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":426549,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pangea.stanford.edu/ERE/db/IGAstandard/record_detail.php?id=36304"}],"country":"United States","state":"Arizona, California, Idaho, Nevada, Oregon, Utah","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.1678252423948,\n 34.95930930933167\n ],\n [\n -112.13481296270123,\n 36.38011070446173\n ],\n [\n -110.41839315886372,\n 39.724144797392114\n ],\n [\n -111.71560833919142,\n 41.53235529739101\n ],\n [\n -111.42411871894447,\n 43.51066554918043\n ],\n [\n -114.37594318706135,\n 43.98121176013663\n ],\n [\n -116.31862299441079,\n 42.72836632941687\n ],\n [\n -119.85738414099404,\n 43.39318722988335\n ],\n [\n -121.46376336575122,\n 42.21714661857473\n ],\n [\n -121.06118635706744,\n 39.6313773486587\n ],\n [\n -118.96617577098581,\n 37.07912459245523\n ],\n [\n -115.1678252423948,\n 34.95930930933167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":896488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":896489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Colin F. 0000-0003-2196-5496 colin@usgs.gov","orcid":"https://orcid.org/0000-0003-2196-5496","contributorId":274,"corporation":false,"usgs":true,"family":"Williams","given":"Colin","email":"colin@usgs.gov","middleInitial":"F.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":896490,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252064,"text":"70252064 - 2024 - Sea turtle density surface models along the United States Atlantic coast","interactions":[],"lastModifiedDate":"2024-03-12T14:58:09.654368","indexId":"70252064","displayToPublicDate":"2024-02-29T09:38:46","publicationYear":"2024","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":"Sea turtle density surface models along the United States Atlantic coast","docAbstract":"Spatially explicit estimates of marine species distribution and abundance are required to quantify potential impacts from human activities such as military training and testing, fisheries interactions, and offshore energy development. There are 4 protected species of sea turtle (loggerhead, green, Kemp’s ridley, and leatherback) commonly found along the east coast of the USA, our study area, and which require impact assessments. Data from 7 different survey organizations were used to create density surface models for the 4 sea turtle species utilizing 1.2 million km of line-transect surveys. A substantial portion (29.7%) of available sightings were not identified to the species level. Not including these sightings would underestimate density, so a conditional random forest model was used to assign unidentified sightings to species. Higher densities of loggerhead, green, and Kemp’s ridley sea turtles were predicted south of the Outer Banks in cool months, transitioning northwards in late spring to occupy seasonal neritic habitats. The highest leatherback densities were predicted off the coasts of Georgia and Florida. Leatherbacks were also predicted throughout offshore areas. The predicted distribution patterns generally matched satellite tracking and strandings data, indicating the models reproduced established seasonal movements. Surveys rarely detect sea turtles smaller than 40 cm, so these age classes are not represented. The models are the first for the study area to apply availability bias estimates developed in or near the study area and attempt to classify unidentified sightings to the species level, providing an updated, critical tool for conservation management along the eastern seaboard.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01298","usgsCitation":"DiMatteo, A., Roberts, J.J., Jones-Farrand, D.T., Garrison, L., Hart, K., Kenney, R.D., McLellan, W.A., Lomac-MacNair, K., Palka, D., Rickard, M.E., Roberts, K., Zoidis, A.M., and Sparks, L., 2024, Sea turtle density surface models along the United States Atlantic coast: Endangered Species Research, v. 53, p. 227-245, https://doi.org/10.3354/esr01298.","productDescription":"19 p.","startPage":"227","endPage":"245","ipdsId":"IP-154482","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":440271,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01298","text":"Publisher Index Page"},{"id":426553,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, Florida, Georgia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, North Carolina, Rhode Island, South Carolina, Virginia","otherGeospatial":"Atlantic Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -57.93627018077767,\n 46.35190712057363\n ],\n [\n -63.06317767562888,\n 48.071961216623635\n ],\n [\n -71.30344277897166,\n 43.13946856546261\n ],\n [\n -71.80832999327407,\n 41.862600860703395\n ],\n [\n -74.50295610940375,\n 40.814804466010116\n ],\n [\n -76.87672546434797,\n 39.666220426927055\n ],\n [\n -77.10004487486839,\n 35.93970224582324\n ],\n [\n -81.71588138883396,\n 31.544829146262018\n ],\n [\n -80.60117913786426,\n 26.310207631307307\n ],\n [\n -81.06912455364952,\n 25.83857941124684\n ],\n [\n -82.70465928026937,\n 29.11226261565656\n ],\n [\n -83.63137912414963,\n 30.41405891714605\n ],\n [\n -87.16972564675274,\n 30.306755223785572\n ],\n [\n -83.87424700132446,\n 27.063066500883522\n ],\n [\n -82.83132577671518,\n 23.770525785543356\n ],\n [\n -80.574320123905,\n 24.06588592956416\n ],\n [\n -79.30071206924853,\n 26.25623333516093\n ],\n [\n -79.48694740536136,\n 31.343635783809773\n ],\n [\n -74.30210816483918,\n 34.877155333197436\n ],\n [\n -57.93627018077767,\n 46.35190712057363\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","noUsgsAuthors":false,"publicationDate":"2024-02-29","publicationStatus":"PW","contributors":{"authors":[{"text":"DiMatteo, Andrew","contributorId":334722,"corporation":false,"usgs":false,"family":"DiMatteo","given":"Andrew","email":"","affiliations":[{"id":80216,"text":"McLaughlin Research Corporation","active":true,"usgs":false}],"preferred":false,"id":896411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, Jason J.","contributorId":334723,"corporation":false,"usgs":false,"family":"Roberts","given":"Jason","email":"","middleInitial":"J.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":896412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones-Farrand, D. Todd","contributorId":217894,"corporation":false,"usgs":false,"family":"Jones-Farrand","given":"D.","email":"","middleInitial":"Todd","affiliations":[{"id":39711,"text":"Gulf-Coastal Plains and Ozarks Landscape Conservation Cooperative, U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":896413,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garrison, Lance","contributorId":244391,"corporation":false,"usgs":false,"family":"Garrison","given":"Lance","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":896414,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":896415,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kenney, Robert D.","contributorId":334724,"corporation":false,"usgs":false,"family":"Kenney","given":"Robert","email":"","middleInitial":"D.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":896416,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McLellan, William A.","contributorId":334725,"corporation":false,"usgs":false,"family":"McLellan","given":"William","email":"","middleInitial":"A.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":896417,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lomac-MacNair, Kate","contributorId":334726,"corporation":false,"usgs":false,"family":"Lomac-MacNair","given":"Kate","email":"","affiliations":[{"id":80218,"text":"Tetra Tech and Cetos Research Organization","active":true,"usgs":false}],"preferred":false,"id":896418,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Palka, Debra","contributorId":334727,"corporation":false,"usgs":false,"family":"Palka","given":"Debra","email":"","affiliations":[{"id":80220,"text":"National Marine Fisheries Service, Northeast Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":896419,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rickard, Meghan E.","contributorId":334728,"corporation":false,"usgs":false,"family":"Rickard","given":"Meghan","email":"","middleInitial":"E.","affiliations":[{"id":80221,"text":"New York Natural Heritage Program, College of Environmental Science and Forestry, State University of New York","active":true,"usgs":false}],"preferred":false,"id":896420,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Roberts, Kelsey E. 0000-0001-8422-632X","orcid":"https://orcid.org/0000-0001-8422-632X","contributorId":176734,"corporation":false,"usgs":false,"family":"Roberts","given":"Kelsey E.","affiliations":[],"preferred":false,"id":896421,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zoidis, Ann M.","contributorId":334729,"corporation":false,"usgs":false,"family":"Zoidis","given":"Ann","email":"","middleInitial":"M.","affiliations":[{"id":80218,"text":"Tetra Tech and Cetos Research Organization","active":true,"usgs":false}],"preferred":false,"id":896422,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sparks, L.","contributorId":334730,"corporation":false,"usgs":false,"family":"Sparks","given":"L.","email":"","affiliations":[{"id":65980,"text":"Naval Undersea Warfare Center","active":true,"usgs":false}],"preferred":false,"id":896423,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70262167,"text":"70262167 - 2024 - Bird-habitat associations and local-scale vegetation structure in lowland brushlands","interactions":[],"lastModifiedDate":"2025-01-15T16:01:49.99293","indexId":"70262167","displayToPublicDate":"2024-02-29T08:50:21","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Bird-habitat associations and local-scale vegetation structure in lowland brushlands","docAbstract":"Brushlands support a diverse suite of bird species, including species of conservation concern in the western Great Lakes region of central North America. Information on how to effectively manage lowland brushlands for birds and associations between breeding birds and local-scale vegetation structure and composition is lacking. We surveyed lowland brushlands from 2016–2018 in Minnesota, USA, to assess bird-habitat associations using avian point-count surveys and fixed-radius vegetation plots. We used Poisson regression models to assess the associations between breeding bird species richness, total abundance, and abundance of frequently detected species (using counts as an index for abundance) to woody stem density and height, patchiness of woody stem density, variation of woody stem height, and number of woody plant species. Sedge wrens (Cistothorus stellaris), the most abundant species, were negatively associated with multiple woody plant metrics and positively associated with patchiness. Common yellowthroats (Geothlypis trichas) were the second-most abundant species and associated with low-stature woody plants (<1 m based on average heights in study sites). Bird species richness, alder flycatchers (Empidonax alnorum), chestnut-sided warblers (Setophaga pensylvanica), swamp sparrows (Melospiza georgiana), veeries (Catharus fuscescens), and yellow warblers (Setophaga petechia) increased with woody vegetation height. Chestnut-sided warbler and Nashville warbler (Leiothlypis ruficapilla) abundances also increased with woody stem density. We suggest that managing lowland brushlands to promote diverse woody plant structure, including tall shrubs and areas with patchy, open herbaceous cover, by implementing temporally and spatially variable disturbance regimes, may benefit bird species that rely on lowland brushlands with a range of vegetation structure requirements.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22568","usgsCitation":"Hawkinson, A., Montgomery, R.A., Roy, C.L., Shartell, L., Andersen, D.E., Stevens, T.K., Knosalla, L., and Frelich, L.E., 2024, Bird-habitat associations and local-scale vegetation structure in lowland brushlands: Journal of Wildlife Management, v. 88, no. 4, e22568, 24 p., https://doi.org/10.1002/jwmg.22568.","productDescription":"e22568, 24 p.","ipdsId":"IP-141848","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467027,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22568","text":"Publisher Index Page"},{"id":466421,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","county":"Aitkin County, Carlton County, St. Louis County","otherGeospatial":"east-central Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.55095209733292,\n 47.81578189067989\n ],\n [\n -93.55095209733292,\n 46.62374994560324\n ],\n [\n -92.13724027549586,\n 46.62374994560324\n ],\n [\n -92.13724027549586,\n 47.81578189067989\n ],\n [\n -93.55095209733292,\n 47.81578189067989\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"88","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-02-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Hawkinson, Annie J","contributorId":348300,"corporation":false,"usgs":false,"family":"Hawkinson","given":"Annie J","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":923334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Montgomery, Rebecca A.","contributorId":328437,"corporation":false,"usgs":false,"family":"Montgomery","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":923335,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, Charlotte L.","contributorId":274613,"corporation":false,"usgs":false,"family":"Roy","given":"Charlotte","email":"","middleInitial":"L.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923336,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shartell, Lindsey M.","contributorId":348301,"corporation":false,"usgs":false,"family":"Shartell","given":"Lindsey M.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923337,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923338,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stevens, Thomas K.","contributorId":333873,"corporation":false,"usgs":false,"family":"Stevens","given":"Thomas","email":"","middleInitial":"K.","affiliations":[{"id":38051,"text":"Western EcoSystems Technology, Inc.","active":true,"usgs":false}],"preferred":false,"id":923593,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Knosalla, Lori J.","contributorId":348574,"corporation":false,"usgs":false,"family":"Knosalla","given":"Lori J.","affiliations":[],"preferred":false,"id":923594,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Frelich, Lee E.","contributorId":179338,"corporation":false,"usgs":false,"family":"Frelich","given":"Lee","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":923339,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70258807,"text":"70258807 - 2024 - Influence of inherited structure on flexural extension in foreland basin systems: Evidence from the northern Arkoma basin and southern Ozark dome, USA","interactions":[],"lastModifiedDate":"2024-09-26T13:54:59.26177","indexId":"70258807","displayToPublicDate":"2024-02-29T08:48:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14252,"text":"Earth Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Influence of inherited structure on flexural extension in foreland basin systems: Evidence from the northern Arkoma basin and southern Ozark dome, USA","docAbstract":"Extensional faults are key components of foreland basin systems. They form within the upper crust in response to flexure of the lithosphere and accommodate subsidence within the foredeep and forebulge depozones. Such faults are excellent proxies for orogenic system evolution and control the distribution of natural resources and hazards. However, the spatiotemporal evolution of flexural extension has not been documented previously at a regional scale, thereby limiting our understanding of underlying geodynamic controls. Here, we resolve late Paleozoic flexural extension in the northern Arkoma basin and southern Ozark dome, USA. We synthesize a large database of previous mapping, existing research, subsurface data, and geophysical data into 3D geologic and 2D kinematic models. Mesh surfaces representing several key horizons from the Carboniferous Period (ca. 335-306 Ma) were constructed. These surfaces were built from oil and gas well tops (n = ∼10,000) and surface geologic map contacts using an advanced kriging method. The mesh surfaces are offset by a complex 3D fault network, allowing detailed analysis of along-strike and down-dip variations in fault displacement. Analysis of the 3D model reveals a regular and repeated fault segmentation pattern wherein E-W striking, left- and foreland-stepping en échelon normal faults are segmented by inherited NE striking basement faults. Maximum vertical separation along the E-W normal faults is generally focused between the inherited NE-trending faults. This suggests that the inherited basement faults delocalized extensional strain during late Paleozoic normal faulting. Maximum vertical separation and fault localization may correlate to areas with high-amplitude positive magnetic anomalies interpreted as Mesoproterozoic granitic rocks. Speculative covariance of magnetic anomalies and fault displacements implies that the relatively strong basement granite concentrated stress, leading to localized faulting within the relatively thin sedimentary cover. Lastly, we show that flexural extension migrated southeast to northwest from the Chesterian-Morrowan (ca. 335-319 Ma) to the Desmoinesian (ca. 306 Ma). The migratory flexural extension may be explained by diachronous loading during Pangean assembly, or by synchronous loading but variable load compensation due to inherent factors.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2024.104715","usgsCitation":"Lutz, B.M., Hudson, M.R., Smith, T.M., Dechesne, M., Spangler, L.R., McCafferty, A.E., Amaral, C.M., Griffis, N.P., and Hirtz, J.A., 2024, Influence of inherited structure on flexural extension in foreland basin systems: Evidence from the northern Arkoma basin and southern Ozark dome, USA: Earth Science Reviews, v. 251, 104715, 34 p., https://doi.org/10.1016/j.earscirev.2024.104715.","productDescription":"104715, 34 p.","ipdsId":"IP-158572","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":467028,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.earscirev.2024.104715","text":"Publisher Index 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The update includes the use of new ground-motion models (GMMs) in the Cascadia subduction zone; an adjustment to the central and eastern United States (CEUS) GMMs to reduce misfits with observed data; an updated boundary for the application of GMMs for shallow, crustal earthquakes in active tectonic regions (i.e. western United States (WUS)) and stable continental regions (i.e. CEUS); and the use of improved models for the site response of deep sedimentary basins in the WUS and CEUS. Site response updates include basin models for the California Great Valley and for the Portland and Tualatin basins, Oregon, as well as long-period basin effects from three-dimensional simulations in the Greater Los Angeles region and in the Seattle basin; in the CEUS, we introduce a broadband (0.01- to 10-s period) amplification model for the effects of the passive-margin basins of the Atlantic and Gulf Coastal Plains. In addition, we summarize progress on implementing rupture directivity models into seismic hazard models, although they are not incorporated in the 2023 NSHM. We implement the ground-motion characterization for the 2023 NSHM in the US Geological Survey’s code for probabilistic seismic hazard analysis, nshmp-haz-v2, and present the sensitivity of hazard to these changes. Hazard calculations indicate widespread effects from adjustments to the CEUS GMMs, from the incorporation of Coastal Plain amplification effects, and from the treatment of shallow-basin and out-of-basin sites in the San Francisco Bay Area and Los Angeles region, as well as locally important changes from subduction-zone GMMs, and from updated and new WUS basins.
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0000-0001-7863-3930","orcid":"https://orcid.org/0000-0001-7863-3930","contributorId":203492,"corporation":false,"usgs":true,"family":"Withers","given":"Kyle","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927397,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70251920,"text":"70251920 - 2024 - Allochthonous marsh subsidies enhances food web productivity in an estuary and its surrounding ecosystem mosaic","interactions":[],"lastModifiedDate":"2026-02-10T19:26:32.121354","indexId":"70251920","displayToPublicDate":"2024-02-29T06:51:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Allochthonous marsh subsidies enhances food web productivity in an estuary and its surrounding ecosystem mosaic","docAbstract":"Terrestrial organic matter is believed to play an important role in promoting resilient estuarine food webs, but the inherent interconnectivity of estuarine systems often obscures the origins and importance of these terrestrial inputs. To determine the relative contributions of terrestrial (allochthonous) and aquatic (autochthonous) organic matter to the estuarine food web, we analyzed carbon, nitrogen, and sulfur stable isotopes from multiple trophic levels, environmental strata, and habitats throughout the estuarine habitat mosaic. We used a Bayesian stable isotope mixing model (SIMM) to parse out relationships among primary producers, invertebrates, and a pelagic and demersal fish species (juvenile Chinook salmon and sculpin, respectively). The study was carried out in the Nisqually River Delta (NRD), Washington, USA, a recently-restored, macrotidal estuary with a diverse habitat mosaic. Plant groupings of macroalgae, eelgrass, and tidal marsh plants served as the primary base components of the NRD food web. About 90% of demersal sculpin diets were comprised of benthic and pelagic crustaceans that were fed by autochthonous organic matter contributions from aquatic vegetation. Juvenile salmon, on the other hand, derived their energy from a mix of terrestrial, pelagic, and benthic prey, including insects, dipterans, and crustaceans. Consequently, allochthonous terrestrial contributions of organic matter were much greater for salmon, ranging between 26 and 43%. These findings demonstrate how connectivity among estuarine habitat types and environmental strata facilitates organic matter subsidies. This suggests that management actions that improve or restore lateral habitat connectivity as well as terrestrial-aquatic linkages may enhance allochthonous subsidies, promoting increased prey resources and ecosystem benefits in estuaries.