The Tragedy of the Commons is a well studied problem in the literature of ecology, economics, and environmental policy which illustrates the deleterious consequences of managing common pool resources when individual and social incentives are misaligned. In this work, we apply a simple model of carbon sequestration in a deep saline aquifer by two neighboring geologic CO2 storage (GCS) operators to begin investigating if a Tragedy of the Commons framework applies to GCS. Specifically, we consider the pressure space as a “commons” because the injection by each firm at its own well increases the downhole injection pressure at both wells. We assume that a firm will decrease its injection rate if the downhole pressure at its well exceeds a predefined maximum (i.e., exceeds the “pressure limit”). With this assumption in place, we find that the same injection flowrates are optimal for both wells, regardless of whether they are owned by the same firm or competing firms. This suggests that GCS may not be best represented by a pure Tragedy of the Commons framework under our initial assumptions. However, there could be economic incentives or contractual obligations that may result in either or both GCS operators being unwilling to reduce their injection rates. Thus, we conclude the conference paper with a discussion of future extensions of our approach that may demonstrate closer alignment with the Tragedy of the Commons, including explicit definitions of pore-space rights, firm uncertainty regarding the parameters of the Theis equation, and the potential role of unitization.
","conferenceTitle":"17th Greenhouse Gas Control Technologies Conference (GHGT-17)","conferenceDate":"October 20-24, 2024","conferenceLocation":"Calgary, Alberta, Canada","language":"English","publisher":"Social Sciences Research Network (SSRN)","doi":"10.2139/ssrn.5030762","usgsCitation":"Duggan, J.E., Ogland-Hand, J.D., Anderson, S.T., and Middleton, R.S., 2024, Managing basin-scale carbon sequestration: A tragedy of the commons approach, 17th Greenhouse Gas Control Technologies Conference (GHGT-17), Calgary, Alberta, Canada, October 20-24, 2024, 7 p., https://doi.org/10.2139/ssrn.5030762.","productDescription":"7 p.","ipdsId":"IP-171979","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":494428,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2139/ssrn.5030762","text":"Publisher Index Page"},{"id":464691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Duggan, Joseph E. Jr.","contributorId":346879,"corporation":false,"usgs":false,"family":"Duggan","given":"Joseph","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[{"id":83005,"text":"Department of Economics and Finance, University of Dayton","active":true,"usgs":false}],"preferred":false,"id":920092,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ogland-Hand, Jonathan D.","contributorId":346880,"corporation":false,"usgs":false,"family":"Ogland-Hand","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[{"id":83006,"text":"Carbon Solutions, LLC","active":true,"usgs":false}],"preferred":false,"id":920093,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":920094,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Middleton, Richard S.","contributorId":297513,"corporation":false,"usgs":false,"family":"Middleton","given":"Richard","email":"","middleInitial":"S.","affiliations":[{"id":64420,"text":"Carbon Solutions LLC","active":true,"usgs":false}],"preferred":false,"id":920095,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262019,"text":"70262019 - 2024 - The effects of spatio-temporal variation in marine resources on the occupancy dynamics of a terrestrial avian predator","interactions":[],"lastModifiedDate":"2025-01-10T15:38:35.090413","indexId":"70262019","displayToPublicDate":"2024-11-24T08:32:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"The effects of spatio-temporal variation in marine resources on the occupancy dynamics of a terrestrial avian predator","docAbstract":"Identifying how species respond to system drivers such as weather, climate, habitat, and resource availability is critical in understanding population change. In coastal areas, the transfer of nutrients across the marine and terrestrial interface increases complexity. Nesting populations of bald eagles (Haliaeetus leucocephalus) along the Pacific coast of North America, although terrestrial, are largely dependent on marine resources during the breeding season and therefore represent a good focal species for understanding linkages of nutrients between terrestrial and marine systems. Due to their location, coastal eagle populations are susceptible to a variety of climate-induced perturbations, from both land and sea. The northeast Pacific Marine Heatwave (PMH) of 2014-2016 had wide-ranging impacts on the marine ecosystem and provided an opportunity to explore how marine conditions can impact terrestrial wildlife populations. We used a spatially-explicit multi-state occupancy modeling framework to analyze >30yrs of bald eagle nest occupancy data collected in four large national parks along a coastal-interior gradient in Alaska, USA. We assessed occupancy state in relation to weather conditions, salmon abundance, access to alternate prey resources, and the PMH event to help elucidate the factors affecting bald eagle occupancy dynamics over time. We found that occupancy probability was higher in areas where prey resources were concentrated (e.g., near seabird colonies, where bears facilitate access to salmon carcasses). We also found that the probability of reproductive success was higher during warmer, drier springs with higher-than-average salmon abundance. After the onset of the marine heatwave, success declined in the areas most dependent on non-salmon marine resources. These findings confirm the importance of spring weather conditions and access to salmon resources during the critical chick-rearing period, but also reveal that marine heatwaves may have important secondary effects through a reduction in the overall quantity or quality of prey available to bald eagles. Given ongoing warming at high latitudes and the expectation that marine heatwaves will become more common, our findings are useful for understanding ongoing and future changes in the transfer of nutrients from marine to terrestrial ecosystems and how such changes may impact terrestrial species such as bald eagles.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.70078","usgsCitation":"Schmidt, J., Coletti, H.A., Cutting, K., Wilson, T.L., Mangipane, B.A., Schultz, C., and Schertz, D., 2024, The effects of spatio-temporal variation in marine resources on the occupancy dynamics of a terrestrial avian predator: Ecosphere, v. 15, no. 11, e70078, 20 p., https://doi.org/10.1002/ecs2.70078.","productDescription":"e70078, 20 p.","ipdsId":"IP-160904","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466745,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70078","text":"Publisher Index Page"},{"id":465985,"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 -155.87303317749726,\n 58.10488388072105\n ],\n [\n -142.06303742386143,\n 59.18556482485508\n ],\n [\n -141.20302314317152,\n 60.18220860178873\n ],\n [\n -141.93448222543984,\n 61.62146548769948\n ],\n [\n -155.82554040260186,\n 60.581802907191815\n ],\n [\n -156.66072744660838,\n 59.58828360613053\n ],\n [\n -155.87303317749726,\n 58.10488388072105\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, Joshua H.","contributorId":167772,"corporation":false,"usgs":false,"family":"Schmidt","given":"Joshua H.","affiliations":[{"id":24828,"text":"Central Alaska Network, National Park Service, Fairbanks, Alaska","active":true,"usgs":false}],"preferred":false,"id":922723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coletti, Heather A.","contributorId":187561,"corporation":false,"usgs":false,"family":"Coletti","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":922724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cutting, Kyle A.","contributorId":328692,"corporation":false,"usgs":false,"family":"Cutting","given":"Kyle A.","affiliations":[{"id":78459,"text":"U.S. Fish & Wildlife Service, Red Rock Lakes NWR","active":true,"usgs":false}],"preferred":false,"id":922725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Tammy L. 0000-0002-3672-8277","orcid":"https://orcid.org/0000-0002-3672-8277","contributorId":293684,"corporation":false,"usgs":true,"family":"Wilson","given":"Tammy","email":"","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922726,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mangipane, Buck A.","contributorId":288781,"corporation":false,"usgs":false,"family":"Mangipane","given":"Buck","email":"","middleInitial":"A.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":922727,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schultz, Carlene N.","contributorId":347883,"corporation":false,"usgs":false,"family":"Schultz","given":"Carlene N.","affiliations":[{"id":36976,"text":"U.S. National Park Service","active":true,"usgs":false}],"preferred":false,"id":922728,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schertz, Dylan T.","contributorId":347885,"corporation":false,"usgs":false,"family":"Schertz","given":"Dylan T.","affiliations":[{"id":36976,"text":"U.S. National Park Service","active":true,"usgs":false}],"preferred":false,"id":922729,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261468,"text":"70261468 - 2024 - Modeling the responses of blue carbon fluxes in Mississippi River Deltaic Plain brackish marshes to climate change induced hydrologic conditions","interactions":[],"lastModifiedDate":"2024-12-11T17:24:00.833987","indexId":"70261468","displayToPublicDate":"2024-11-23T11:17:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the responses of blue carbon fluxes in Mississippi River Deltaic Plain brackish marshes to climate change induced hydrologic conditions","docAbstract":"Carbon fluxes in tidal brackish marshes play a critical role in determining coastal wetland carbon sequestration and storage, thus affecting carbon crediting of coastal wetland restoration. In this study, a process-driven wetland biogeochemistry model, Wetland Carbon Assessment Tool DeNitrification-DeComposition was applied to nine brackish marsh sites in Mississippi River (MR) Deltaic Plain to examine the responses of gross primary productivity (GPP), ecosystem respiration (ER), net ecosystem exchange (NEE), and emissions of methane (CH4) and nitrous oxide (N2O) to climate change. Simulations of a normal hydrologic year (2013), dry year (2011) and wet year (2021), and a hypothetical sea level rise (SLR) case were conducted as climate change scenarios. These climate change scenarios were determined by the Palmer Drought Severity Index (PDSI) for the Northeast Division of Coastal Louisiana during 2001–2021. Model results showed that GPP, ER, NEE, CH4, and N2O vary with site, and these brackish marshes lost carbon (net CO2 emission) due to large reduction in primary productivity under the climate scenarios, as well as even during the normal hydrologic year. Average cross-site NEE were 148, 140 and 132 g C m−2 yr−1 in the dry, wet, and normal years (all net loss of wetland C). Under the hypothetical SLR, NEE were reduced by -25% compared to the normal year, but GPP and NPP were declined by -40% and -70%, respectively. These results suggest that climate change induced changes in soil salinity and water table depth will exacerbate carbon loss from tidal brackish marshes.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-024-01881-w","usgsCitation":"Wang, H., Krauss, K., Dai, Z., Noe, G.E., and Trettin, C.C., 2024, Modeling the responses of blue carbon fluxes in Mississippi River Deltaic Plain brackish marshes to climate change induced hydrologic conditions: Wetlands, v. 44, no. 8, 122, 19 p., https://doi.org/10.1007/s13157-024-01881-w.","productDescription":"122, 19 p.","ipdsId":"IP-168330","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":489083,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.mtu.edu/michigantech-p2/1205","text":"External Repository"},{"id":465027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":" Mississippi River Deltaic Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.15,\n 29.6667\n ],\n [\n -91.7,\n 29.6667\n ],\n [\n -91.7,\n 29.15\n ],\n [\n -90.15,\n 29.15\n ],\n [\n -90.15,\n 29.6667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":215079,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":920660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":219804,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":920661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dai, Zhaohua 0000-0002-0941-8345","orcid":"https://orcid.org/0000-0002-0941-8345","contributorId":290409,"corporation":false,"usgs":false,"family":"Dai","given":"Zhaohua","email":"","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":920662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":920663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trettin, Carl C. 0000-0003-0279-7191","orcid":"https://orcid.org/0000-0003-0279-7191","contributorId":293476,"corporation":false,"usgs":false,"family":"Trettin","given":"Carl","email":"","middleInitial":"C.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":920664,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266575,"text":"70266575 - 2024 - Effects of trap funnel and finger design on Sea Lamprey entrance and retention","interactions":[],"lastModifiedDate":"2025-05-09T15:28:26.367683","indexId":"70266575","displayToPublicDate":"2024-11-23T10:24:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Effects of trap funnel and finger design on Sea Lamprey entrance and retention","docAbstract":"Traps are used to catch adult sea lampreys during their upstream migration to estimate their abundance in streams and, in turn, provide a measure of the Sea Lamprey Control Program’s effectiveness. During 2015 and 2016, we experimentally compared two components of sea lamprey trap design: trap entrance funnel type and the presence of retention devices, using side-by-side instream test chambers as well as laboratory flumes. We modeled how likelihoods of entrance and retention were influenced by funnel type, retention fingers, water temperature, and lamprey sex. Likelihood of entrance was highest with bottom-oriented funnels and no retention fingers. As water temperature increased, the likelihood of entrance generally increased, but funnel type and retention fingers determined the magnitude of the increase. Likelihood of retention was highest with bottom-oriented funnels and retention fingers and was also influenced by water temperature. Overall, the likelihood of capture (result of entrance + retention) was highest for bottom-oriented funnels and varied by water temperature and lamprey sex but not retention fingers. Further testing on other components of trap design is needed. This type of controlled experimental design can help guide future work to improve trap exploitation rates.
","language":"English","publisher":"MDPI","doi":"10.3390/w16233365","usgsCitation":"Hrodey, P.J., Bravener, G., and Miehls, S.M., 2024, Effects of trap funnel and finger design on Sea Lamprey entrance and retention: Water, v. 16, no. 23, 3365, 8 p., https://doi.org/10.3390/w16233365.","productDescription":"3365, 8 p.","ipdsId":"IP-169595","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":490108,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w16233365","text":"Publisher Index Page"},{"id":485652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"23","noUsgsAuthors":false,"publicationDate":"2024-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Hrodey, Peter J.","contributorId":205578,"corporation":false,"usgs":false,"family":"Hrodey","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6599,"text":"U.S. Fish and Wildlife Service, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":936582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bravener, Gale","contributorId":150995,"corporation":false,"usgs":false,"family":"Bravener","given":"Gale","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":936583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":936584,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70261157,"text":"70261157 - 2024 - Visual interpretation of high-resolution aerial imagery: A tool for land managers","interactions":[],"lastModifiedDate":"2024-11-26T16:16:39.184937","indexId":"70261157","displayToPublicDate":"2024-11-23T10:14:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Visual interpretation of high-resolution aerial imagery: A tool for land managers","docAbstract":"Remotely sensed imagery from various collection platforms (e.g., satellites, crewed and uncrewed aircraft) are used by biologists and other conservation personnel to support management activities ranging from monitoring invasive species to assessing land cover and vegetation characteristics. Although remote sensing–based vegetation indices and models have been developed and used for some management applications, straightforward visual interpretation of imagery by on-the-ground personnel may be a pragmatic approach for obtaining time-sensitive and spatially relevant information to support and guide local management activities. Our primary objective was to qualitatively assess our ability to identify patches of target invasive plant species based on simple visual interpretation of high-resolution aerial imagery. We also sought to compare the high-resolution imagery to widely available imagery (e.g., National Agriculture Imagery Program) to determine the efficacy of each for assessing vegetation communities and land-cover features in support of management activities. To accomplish these objectives, we obtained high-resolution imagery and visually scanned and assessed the imagery by using standard geographic information system software. We were able to differentiate patches of crownvetch Securigera varia (L.) Lassen and wild parsnip Pastinaca sativa L., but not spotted knapweed Centaurea stoebe L. or leafy spurge Euphorbia esula L. The relative success in identifying these species had a relationship to plant characteristics (e.g., flower color and morphology, height), time of year (phenology), patch size and density, and potentially site characteristics such density of the underlying vegetation (e.g., grasses), substrate color characteristics (i.e., color contrast with flowers), and physical disturbance. Our straightforward, qualitative assessment suggests that visual interpretation of high-resolution imagery, but not some lower-resolution imagery, may be an efficient and effective tool for supporting local invasive species management through activities such as monitoring known patches, identifying undetected infestations, assessing management actions, guiding field work, or prioritizing on-the-ground monitoring activities.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-23-048","usgsCitation":"Tangen, B., Esser, R.L., and Walker, B.A., 2024, Visual interpretation of high-resolution aerial imagery: A tool for land managers: Journal of Fish and Wildlife Management, v. 15, no. 1, p. 312-326, https://doi.org/10.3996/JFWM-23-048.","productDescription":"15 p.","startPage":"312","endPage":"326","ipdsId":"IP-156928","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":466746,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-23-048","text":"Publisher Index Page"},{"id":464528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":919459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esser, Rebecca L.","contributorId":346527,"corporation":false,"usgs":false,"family":"Esser","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":919460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walker, Benjamin A.","contributorId":169057,"corporation":false,"usgs":false,"family":"Walker","given":"Benjamin","email":"","middleInitial":"A.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":919461,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263921,"text":"70263921 - 2024 - Stopover population estimate and migration ecology of Red Knots C. c. rufa at Delaware Bay, USA, 2024","interactions":[],"lastModifiedDate":"2026-03-17T15:06:47.161953","indexId":"70263921","displayToPublicDate":"2024-11-23T10:03:08","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"displayTitle":"Stopover population estimate and migration ecology of Red Knots C. c. rufa at Delaware Bay, USA, 2024","title":"Stopover population estimate and migration ecology of Red Knots C. c. rufa at Delaware Bay, USA, 2024","docAbstract":"Red Knots (Calidris canutus rufa) stop at Delaware Bay on the mid-Atlantic coast of North America during northward migration to feed on eggs of horseshoe crabs (Limulus polyphemus). Horseshoe crabs have been harvested for use as bait in eel (Anguilla rostrata) and whelk (Busycotypus canaliculatus and Busycon carica) fisheries since at least 1990. In the late 1990s and early 2000s, the number of Red Knots counted during aerial surveys at Delaware Bay declined, leading to conservation concern for Red Knots and shorebirds at Delaware Bay. In 2013, the Atlantic States Marine Fisheries Commission began using an Adaptive Resource Management (ARM) framework to manage the harvest of horseshoe crabs in the Delaware Bay region. The objective of the ARM framework is to manage sustainable harvest of Delaware Bay horseshoe crabs while maintaining ecosystem integrity and supporting Red Knot recovery with adequate stopover habitat. The ARM framework thus requires annual estimates of horseshoe crab population size and Red Knot stopover population size to recommend annual harvest quotas. We estimated the passage population of Red Knots at Delaware Bay in 2024 using a mark-recapture-resight investigation. We used a Bayesian analysis of a Jolly-Seber model, which accounts for turnover in the population and the probability of detection during surveys. The estimated passage population size in 2024 was 46,127 (95% credible interval: 39,286–57,799), an increase from 2023 (39,361 [33,724–47,556]). Since 2019, the stopover population has fluctuated between approximately 39,000 and 46,000, and appears stable given the broad overlap in the confidence intervals of the annual population estimates. The 2024 Red Knot stopover population estimate will inform decision making in the next horseshoe crab management cycle of the Atlantic States Marine Fisheries Commission.
","language":"English","publisher":"Delaware Division of Fish and Wildlife","usgsCitation":"Lyons, J.E., 2024, Stopover population estimate and migration ecology of Red Knots C. c. rufa at Delaware Bay, USA, 2024, 16 p.","productDescription":"16 p.","ipdsId":"IP-172353","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":482621,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://dnrec.delaware.gov/fish-wildlife/conservation/shorebirds/research/"},{"id":501216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey","otherGeospatial":"Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.10844894246691,\n 38.71094419142639\n ],\n [\n -74.84547301245848,\n 39.09891530924247\n ],\n [\n -74.90299899714816,\n 39.19451507998161\n ],\n [\n -75.48099817664571,\n 39.50167475761344\n ],\n [\n -75.52756683091825,\n 39.65791141521865\n ],\n [\n -75.60974680904543,\n 39.66423790391954\n ],\n [\n -75.65905479592207,\n 39.60516815618203\n ],\n [\n -75.60974680904543,\n 39.429772303548646\n ],\n [\n -75.44812618539433,\n 39.24332702987286\n ],\n [\n -75.45360485060331,\n 39.05638485196263\n ],\n [\n -75.2810268965351,\n 38.82841171381057\n ],\n [\n -75.10844894246691,\n 38.71094419142639\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":929098,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70261898,"text":"70261898 - 2024 - Using structural causal modeling to infer the effects of wildfire on foothill yellow-legged frog occurrence","interactions":[],"lastModifiedDate":"2025-03-25T15:52:29.353037","indexId":"70261898","displayToPublicDate":"2024-11-23T09:19:33","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Using structural causal modeling to infer the effects of wildfire on foothill yellow-legged frog occurrence","docAbstract":"Sierra Nevada ecosystems have been influenced by fire for millennia; however, increasing wildfire size and frequency may yield unforeseen consequences on wildlife populations and their distribution. Foothill yellow-legged frogs Rana boylii have declined in portions of their range and are considered a species of conservation concern. We surveyed streams for foothill yellow legged frogs in and near the 2021 Dixie Fire footprint using double-observer visual encounter surveys that incorporated time-to-detection methods, and used structural causal modeling to improve post-fire inference while lacking pre-fire data. We found that foothill yellow-legged frog probability of occurrence was 4.93 (95% equal-tailed interval = 0.52 – 160) times higher outside the footprint of the Dixie Fire than within it, though probability of occurrence was generally low within our sampling frame (ψunburned = 0.21 [0.08 – 0.49]; ψburned = 0.05 [0.002 – 0.28]). Measured environmental characteristics, however, were similar within and outside the fire footprint, and observed occupancy patterns might reflect the recent historical distribution of the frogs. Our study emphasizes the importance of site-specific pre-disturbance data when attempting to evaluate the causal effects of disturbances on wildlife. Although it remains to be seen how this species will fare in an increasingly frequent and intense fire regime, foothill yellow-legged frogs may tolerate some level of fire disturbance.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-24-037","usgsCitation":"Halstead, B., Kleeman, P.M., and Rose, J.P., 2024, Using structural causal modeling to infer the effects of wildfire on foothill yellow-legged frog occurrence: Journal of Fish and Wildlife Management, v. 15, no. 2, p. 419-431, https://doi.org/10.3996/JFWM-24-037.","productDescription":"13 p.","startPage":"419","endPage":"431","ipdsId":"IP-169208","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488311,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-24-037","text":"Publisher Index Page"},{"id":465610,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.47069694179848,\n 41.046727577050234\n ],\n [\n -122.47069694179848,\n 39.95131798630993\n ],\n [\n -120.09752429348453,\n 39.95131798630993\n ],\n [\n -120.09752429348453,\n 41.046727577050234\n ],\n [\n -122.47069694179848,\n 41.046727577050234\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922197,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922198,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922199,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70269374,"text":"70269374 - 2024 - Nonnative Smallmouth Bass in the Snake River, Idaho: Population dynamics, demographics, and management options","interactions":[],"lastModifiedDate":"2025-07-21T14:05:05.801926","indexId":"70269374","displayToPublicDate":"2024-11-23T08:54:33","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Nonnative Smallmouth Bass in the Snake River, Idaho: Population dynamics, demographics, and management options","docAbstract":"The Snake River in Idaho, USA, supports a popular sport fishery for nonnative Smallmouth Bass Micropterus dolomieu, but there are limited studies on the population dynamics of this introduced species in Idaho and other water systems in the western United States. The purpose of this study was to describe the population dynamics and demographics of Smallmouth Bass in the Snake River, Idaho. In total, we sampled 4,929 Smallmouth Bass during electrofishing surveys on the Snake River (separated into nine segments) and three major tributaries (Boise, Payette, and Weiser rivers). We estimated age for 1,869 Smallmouth Bass sampled from the Snake River (n = 1,433) and three tributaries (n = 436). Catch-per-unit-effort for all nine segments combined on the Snake River was 36.6 fish/h (±4.4 SE). In the tributaries, catch-per-unit-effort varied from 43.6 to 125.0 fish/h. Relative weight of all Smallmouth Bass varied from 86 to 107, indicating that fish were in relatively good body condition. Fish in the system grew fast, with relative growth index values often near or exceeding 100 for all age classes. Total annual mortality for the Snake River was 45.1 ± 0.7%, and it was 36.8–40.5% in the tributaries. Furthermore, we estimated exploitation to be 5.3% (90% CI; ±2.2%) for the Snake River and tributaries combined. We used a yield-per-recruit population model to evaluate the effects of varying minimum length limits on the fishery. With the observed population demographics and exploitation rates, increasing the current minimum length limit from 305 mm to 356 or 406 mm would probably have little influence on the number of Smallmouth Bass available to anglers. However, increasing the length limit would result in reduced biomass available for harvest. The potential for recruitment overfishing was minimal for all minimum length limits and levels of exploitation. As such, changes to current harvest regulations do not appear warranted. Our findings provide important information on the population dynamics of Smallmouth Bass that can be useful in evaluating their management across Idaho and in similar systems in western North America.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/jfwm-23-022","usgsCitation":"McClure, C., Quist, M.C., Kozfkay, J., and Schill, D., 2024, Nonnative Smallmouth Bass in the Snake River, Idaho: Population dynamics, demographics, and management options: Journal of Fish and Wildlife Management, v. 15, no. 1, p. 3-16, https://doi.org/10.3996/jfwm-23-022.","productDescription":"14 p.","startPage":"3","endPage":"16","ipdsId":"IP-097797","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":492869,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-23-022","text":"Publisher Index Page"},{"id":492610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.10963406513551,\n 43.158779317239436\n ],\n [\n -116.4180390307447,\n 44.97151977841676\n ],\n [\n -117.30591484918756,\n 44.896844314128515\n ],\n [\n -117.09312056286396,\n 43.167784786405036\n ],\n [\n -116.10963406513551,\n 43.158779317239436\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n -116.324,\n 43.236576\n ],\n \"type\": \"Point\"\n }\n }\n ]\n}","volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"McClure, Conor","contributorId":275013,"corporation":false,"usgs":false,"family":"McClure","given":"Conor","email":"","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":943604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":943605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kozfkay, Joseph R.","contributorId":358373,"corporation":false,"usgs":false,"family":"Kozfkay","given":"Joseph R.","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":943606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schill, Daniel J.","contributorId":288577,"corporation":false,"usgs":false,"family":"Schill","given":"Daniel J.","affiliations":[{"id":61802,"text":"Fisheries Management Solutions","active":true,"usgs":false}],"preferred":false,"id":943607,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262816,"text":"70262816 - 2024 - Using stable oxygen isotope dual-inlet isotope-ratio mass spectrometry to elucidate uranium transport and mixed 230Th/U calcite formation ages at the seminal Devils Hole, Nevada, natural laboratory","interactions":[],"lastModifiedDate":"2025-01-23T15:53:44.145465","indexId":"70262816","displayToPublicDate":"2024-11-23T08:46:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3233,"text":"Rapid Communications in Mass Spectrometry","active":true,"publicationSubtype":{"id":10}},"title":"Using stable oxygen isotope dual-inlet isotope-ratio mass spectrometry to elucidate uranium transport and mixed 230Th/U calcite formation ages at the seminal Devils Hole, Nevada, natural laboratory","docAbstract":"Rationale
Vein calcite in Devils Hole has been precipitating continuously in oxygen-isotope equilibrium at a constant temperature for over 500 000 years, providing an unmatched δ18O paleoclimate time series. A substantial issue is that coeval calcite (based on matching δ18O values) has uranium-series ages differing by 12 000 years.
Methods
An unparalleled high-accuracy δ18O chronology series from continuously submerged calcite was used to correct the published uranium-series ages of non-continuously formed calcite in two cores, cyclically exposed by water-table decline during glacial–interglacial transitions. This method relies on the premise that the δ18O values of coevally precipitated calcite are identical, allowing matching calcite δ18O values to establish formation ages.
Results
Exposed calcite can have apparent ages that are 12 000 years too young due to unrecognized uranium mobility and resulting mixed ages identified in over 50 mixed uranium-series ages from previous studies. Secondary uranium in fluids, sourced from the formation or dissolution of porous carbonate deposits (folia) with high uranium-238 (238U) concentrations, has migrated up to 10 mm into vein calcite.
Conclusions
The continuously submerged Devils Hole δ18O chronology is not explained by orbital forcing. Rather, this chronology represents a regional climate record in the southern Great Basin of sea-surface-temperature (SST) variations off California, variations that preceded the last and penultimate deglaciations by 5000 to approximately 10 000 years. Temporal discrepancies between the continuously submerged Devils Hole chronology and other regional δ18O records (e.g., the Leviathan chronology) can be explained by unrecognized cryptic, pernicious uranium mobility, leading to model estimations that may be thousands of years younger than actual ages. Consequently, paleo-moisture availability, water-table, and groundwater recharge models based on these mixed uranium-series ages are too young by as much as 12 000 years. The potential for post-formation uranium addition in subaerial cores and speleothems underscores the need for caution in uranium-series dating, highlighting δ18O time-series comparisons as a method for identifying mixed ages.
","language":"English","publisher":"Wiley","doi":"10.1002/rcm.9926","usgsCitation":"Coplen, T.B., Seal,, R., Reid, L.T., Jordan, J., and Mumford, A.C., 2024, Using stable oxygen isotope dual-inlet isotope-ratio mass spectrometry to elucidate uranium transport and mixed 230Th/U calcite formation ages at the seminal Devils Hole, Nevada, natural laboratory: Rapid Communications in Mass Spectrometry, v. 39, no. 3, e9926, 18 p., https://doi.org/10.1002/rcm.9926.","productDescription":"e9926, 18 p.","ipdsId":"IP-094999","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":481048,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/rcm.9926","text":"External Repository"},{"id":480997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Great Basin, Devils Hole","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.79795852135467,\n 40.12275342984714\n ],\n [\n -116.79795852135467,\n 35.9796450622334\n ],\n [\n -113.93379652706551,\n 35.9796450622334\n ],\n [\n -113.93379652706551,\n 40.12275342984714\n ],\n [\n -116.79795852135467,\n 40.12275342984714\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":924884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seal,, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":141204,"corporation":false,"usgs":true,"family":"Seal,","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":924885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reid, Lauren T 0000-0003-3872-9596","orcid":"https://orcid.org/0000-0003-3872-9596","contributorId":243302,"corporation":false,"usgs":true,"family":"Reid","given":"Lauren","email":"","middleInitial":"T","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":924886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jordan, James A 0000-0002-7419-8465","orcid":"https://orcid.org/0000-0002-7419-8465","contributorId":349815,"corporation":false,"usgs":true,"family":"Jordan","given":"James A","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":924887,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mumford, Adam C. 0000-0002-8082-8910 amumford@usgs.gov","orcid":"https://orcid.org/0000-0002-8082-8910","contributorId":171791,"corporation":false,"usgs":true,"family":"Mumford","given":"Adam","email":"amumford@usgs.gov","middleInitial":"C.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":924888,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261073,"text":"dr1197 - 2024 - Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona","interactions":[],"lastModifiedDate":"2025-12-22T21:15:45.225154","indexId":"dr1197","displayToPublicDate":"2024-11-22T15:45:17","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1197","displayTitle":"Hydrodynamic Model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona","title":"Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona","docAbstract":"The U.S. Geological Survey constructed a two-dimensional hydrodynamic model that was applied to a 15.8-mile tailwater reach of the Colorado River in Glen Canyon that begins 0.25 mile downstream from Glen Canyon Dam and extends to Lees Ferry in Glen Canyon National Recreation Area, Arizona. The model used the Flow and Sediment Transport with Morphological Evolution of Channels (FaSTMECH) solver in the International River Interface Cooperative (iRIC) modeling interface. The model grid was developed from a full channel digital elevation model derived by combining bathymetric and topographic data collected from March 2013 to February 2016. The model was used to predict water-surface elevations, depths, depth-averaged flow velocities, and bed shear stresses for discharges ranging from 1,000 to 70,000 cubic feet per second. Modeled water-surface elevations matched well with measured values at cross sections throughout the reach, with a mean absolute error of 0.14 meter over the range of typical discharge releases from Glen Canyon Dam. The mean error on discharge, a measure of how well the model solution converged, averaged 0.6 percent and did not exceed 2 percent over the range of discharges modeled. These results indicate that model predictions of hydraulic parameters are reasonably accurate and suitable for use for a variety of purposes, such as ecological and geomorphic modeling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1197","usgsCitation":"Wright, S.A., Kaplinski, M.A., and Grams, P.E., 2024, Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona: U.S. Geological Survey Data Report 1197, 9 p., https://doi.org/10.3133/dr1197.","productDescription":"Report: v, 9 p.; Data Release","numberOfPages":"9","onlineOnly":"Y","ipdsId":"IP-161399","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":464434,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1197/dr1197.XML"},{"id":464432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1197/coverthb.jpg"},{"id":497908,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117828.htm","linkFileType":{"id":5,"text":"html"}},{"id":464437,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1QTRNEB","text":"USGS Data Release","description":"Wright, S.A., Kaplinski, M., and Grams, P.E., 2024, Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona—Tables of model results and accuracy assessment: U.S. Geological Survey data release, https://doi.org/10.5066/P1QTRNEB.","linkHelpText":"Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona—Tables of model results and accuracy assessment"},{"id":464436,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1197/full"},{"id":464435,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1197/images"},{"id":464433,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1197/dr1197.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Glen Canyon Dam, Lees Ferry","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.45495155269207,\n 36.96381776712943\n ],\n [\n -111.62114273826977,\n 36.96381776712943\n ],\n [\n -111.62114273826977,\n 36.820663467737276\n ],\n [\n -111.45495155269207,\n 36.820663467737276\n ],\n [\n -111.45495155269207,\n 36.96381776712943\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Southwest Biological Science Center
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Population estimates are often required for identifying relationships between predators and their prey and to inform conservation and management actions. The random encounter model (REM) estimates population density of wildlife lacking individually unique markings, based on photographs or videos from remote camera-traps. However, the REM has strict sampling and input requirements that can be problematic, particularly for predators and other species which use landscapes non-randomly. Using data from a predator and its co-occurring prey, we found that placing cameras to target the predator, which may be implemented to achieve minimum sample sizes, inflated both predator and prey density estimates. Further, borrowing movement velocity (day range) values from other studies, species, or time periods caused substantial changes in density estimates. A comprehensive literature review revealed that 91% of REM density estimates in published predator–prey studies used data from non-random cameras or borrowed movement velocities and therefore did not satisfy REM requirements. Consequently, most REM density estimates from predator–prey ecology studies are likely not of the quality or reliability necessary for informing effective wildlife conservation or management.
","language":"English","publisher":"MDPI","doi":"10.3390/ani14233361","usgsCitation":"Murphy, S.M., Nolan, B., Chen, F., Longshore, K., Simes, M., Berr, G.A., and Esque, T., 2024, Most random-encounter-model density estimates in camera-based predator-prey studies are unreliable: Animals, v. 14, no. 23, 3361, 24 p., https://doi.org/10.3390/ani14233361.","productDescription":"3361, 24 p.","ipdsId":"IP-161802","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":489906,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani14233361","text":"Publisher Index Page"},{"id":481261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","city":"Boulder City","otherGeospatial":"Boulder City Conservation Easement","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.22729018400342,\n 35.97057404887106\n ],\n [\n -115.22729018400342,\n 35.82849801220463\n ],\n [\n -114.84083854402814,\n 35.82849801220463\n ],\n [\n -114.84083854402814,\n 35.97057404887106\n ],\n [\n -115.22729018400342,\n 35.97057404887106\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"23","noUsgsAuthors":false,"publicationDate":"2024-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Sean M. 0000-0002-9404-8878","orcid":"https://orcid.org/0000-0002-9404-8878","contributorId":346967,"corporation":false,"usgs":true,"family":"Murphy","given":"Sean","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":925093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nolan, Benjamin S.","contributorId":347691,"corporation":false,"usgs":false,"family":"Nolan","given":"Benjamin S.","affiliations":[],"preferred":false,"id":925094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":925095,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Longshore, Kathleen 0000-0001-6621-1271","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":216374,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":925096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simes, Matthew T.","contributorId":349895,"corporation":false,"usgs":false,"family":"Simes","given":"Matthew T.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":925097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":925098,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":925099,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70270927,"text":"70270927 - 2024 - Using crustal-scale refraction data of joint inversions of Rayleigh-wave dispersion curves and H/V spectral ratios for Atlantic Coastal Plain velocity structure, eastern U.S.","interactions":[],"lastModifiedDate":"2025-08-27T15:34:26.143803","indexId":"70270927","displayToPublicDate":"2024-11-22T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Using crustal-scale refraction data of joint inversions of Rayleigh-wave dispersion curves and H/V spectral ratios for Atlantic Coastal Plain velocity structure, eastern U.S.","docAbstract":"Shallow shear‐wave velocities (Vs) sometimes are estimated from joint inversions of horizontal‐to‐vertical (H/V) spectral ratios and surface‐wave dispersion curves derived from ambient noise or small active sources. Here, we evaluate carrying out these inversions using Rayleigh‐wave dispersion curves computed from crustal‐scale P‐wave seismic refraction data. We use data from the 2014–2015 Eastern North American Margin (ENAM) experiment in Virginia and North Carolina, but similar seismic refraction data sets have been acquired over sedimentary basins of interest for seismic hazard studies, including in major urban areas. The ENAM project deployed a pair of ∼215 km long, northwest–southeast linear arrays with ∼300 m receiver spacing to record 11 dynamite shots, and 80 continuously recording seismometers with 5–6 km spacing along the same arrays to record offshore airguns. The arrays crossed the onland portion of the Atlantic Coastal Plain sediments, which are a seaward‐thickening wedge of Cretaceous and younger sediments deposited mostly on crystalline bedrock. We compute Rayleigh‐wave dispersion curves from 3 to 9 km long portions of the receiver arrays on each side of the dynamite shots, and we compute ambient‐noise H/V ratios from the continuously recording seismometers. We use a genetic inversion algorithm in which forward velocity models in each “generation” are evaluated for misfits compared to the observed data, with subsequent generations constructed from the models with the smallest misfits. Velocities to depths of 500 m are defined well, as shown by a narrow range of velocities in the best‐fit models, by the consistency between multiple inversion runs at a site, and by forward modeling of site responses. The resulting velocity cross‐section of the Coastal Plain strata has seaward‐dipping contours in the thinner portions of the Coastal Plain but smaller dips in the deeper portions. We interpret these results as showing that velocity contours in the ACP strata are influenced by a combination of lithology and overburden pressure. Results demonstrate that existing seismic refraction data have the potential for determining detailed shallow shear‐wave velocity profiles.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230241","usgsCitation":"Pratt, T., Parolai, S., Poggi, V., and Dreossi, I., 2024, Using crustal-scale refraction data of joint inversions of Rayleigh-wave dispersion curves and H/V spectral ratios for Atlantic Coastal Plain velocity structure, eastern U.S.: Bulletin of the Seismological Society of America, v. 115, no. 1, p. 270-295, https://doi.org/10.1785/0120230241.","productDescription":"26 p.","startPage":"270","endPage":"295","ipdsId":"IP-167122","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":494950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"eastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.88300039003173,\n 39.731394919591565\n ],\n [\n -90.88300039003173,\n 24.876206992183768\n ],\n [\n -74.40455609054004,\n 24.876206992183768\n ],\n [\n -74.40455609054004,\n 39.731394919591565\n ],\n [\n -90.88300039003173,\n 39.731394919591565\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"115","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":201084,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":947394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parolai, Stefano 0000-0002-9084-7488","orcid":"https://orcid.org/0000-0002-9084-7488","contributorId":296105,"corporation":false,"usgs":false,"family":"Parolai","given":"Stefano","email":"","affiliations":[{"id":63989,"text":"Instituto Nazionale di Oceonografia","active":true,"usgs":false}],"preferred":false,"id":947395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poggi, Valerio","contributorId":360682,"corporation":false,"usgs":false,"family":"Poggi","given":"Valerio","affiliations":[{"id":86081,"text":"Trieste, Italy","active":true,"usgs":false}],"preferred":false,"id":947396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dreossi, Ilaria","contributorId":296107,"corporation":false,"usgs":false,"family":"Dreossi","given":"Ilaria","email":"","affiliations":[{"id":63991,"text":"National Institute of Oceanography and Applied Geophysics – OGS, Udine, Italy","active":true,"usgs":false}],"preferred":false,"id":947397,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261070,"text":"cir1544 - 2024 - U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33","interactions":[],"lastModifiedDate":"2024-12-02T19:00:36.118426","indexId":"cir1544","displayToPublicDate":"2024-11-21T15:57:46","publicationYear":"2024","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":"1544","displayTitle":"U.S. Geological Survey Earthquake Hazards Program Decadal Science Strategy, 2024–33","title":"U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33","docAbstract":"Earthquakes represent one of our Nation’s most significant and costly natural hazards, with estimated annual loses from earthquakes close to $15 billion in 2023. Over the past two centuries, 37 U.S. States have experienced an earthquake exceeding a magnitude of 5, and 50 percent of States have a significant potential for future damaging shaking; these statistics speak to the need for nationwide interest and investment in earthquake hazard characterization and risk reduction.
Authorized under the Earthquake Hazards Reduction Authorization Act, the U.S. Geological Survey (USGS) Earthquake Hazards Program (EHP) provides the scientific information, situational awareness, and knowledge necessary to reduce deaths, injuries, and economic losses from earthquakes and earthquake-induced tsunamis, landslides, and soil liquefaction. The EHP supports activities in three focused topical areas: (1) earthquake monitoring, (2) hazard assessment, and (3) applied research, using the results of each—and the coordination among them—to further support risk translation and communication in regions at risk nationwide.
For earthquake monitoring, the Advanced National Seismic System (ANSS), a cooperative effort of USGS networks, university partner regional seismic networks, and real-time geodetic networks, collects and analyzes data on earthquakes; issues timely, reliable notifications of their occurrence and impacts; and provides data for earthquake research, hazard, and risk assessment as a foundation for building an earthquake-resilient Nation. The USGS-operated ShakeAlert Earthquake Early Warning system is a recent addition to EHP’s ANSS infrastructure.
In the realm of earthquake hazard assessment, the EHP contributes to earthquake risk mitigation strategies by developing the National Seismic Hazard Model and maps, and other related products, that describe the likelihood and potential effects of earthquakes nationwide, especially in the urban areas of highest risk. The EHP also conducts research on the causes, characteristics, and effects of earthquakes and prioritizes work that directly increases the accuracy and precision of earthquake hazards assessments, earthquake forecasts, and earthquake monitoring and situational-awareness products and that supports the Nation’s earthquake mitigation practices.
Bridging the EHP’s efforts across research, hazard assessments, and earthquake monitoring is a broad and comprehensive collection of earthquake information products, including the National Seismic Hazard Model, ShakeAlert, and other products describing impact, such as ShakeMap and PAGER (Prompt Assessment of Global Earthquakes for Response), which have been developed and integrated into EHP’s real-time monitoring systems.
EHP funds external partners to carry out many important collaborative activities through an active external grants program—one of the largest in the USGS—and through cooperative agreements with other partners such as the university-operated regional seismic networks, funded as part of the ANSS.
To continue its support of earthquake hazard characterization and risk reduction, the EHP aims to strengthen its foundational products and practices while positioning itself to respond to the evolving needs of the Nation and follow best practices of the scientific community. This document describes a strategy for the program to ensure it can meet these demands. The foundational priorities outlined in this strategy represent those activities that remain critical to the core functionality of the program and those that can be supported under current fiscal year 2024-level appropriations. Priorities described as aspirational are important for future growth, and to maintain the program’s position as a leading global resource in earthquake science, but would require increases in appropriated funding to be fully realized.
Across the program’s portfolio of activities, several major themes have been identified as the most critical activities to advance EHP science over the coming decade. Together, these activities provide the framework necessary to integrate critical hazard characterization and risk reduction activities across the program. They provide the structure for research to advance the understanding of where, when, and why earthquakes occur and how we can use improved knowledge to drive short-term and actionable forecasts of seismic activity. They expand the usefulness of critical earthquake products and advance the sophistication of those products to keep pace with the rapidly evolving needs of an ever-expanding user base while maintaining the position of the USGS as a global leader in earthquake science.
This science strategy is organized into three primary sections. The first section provides an overview of the EHP and its budget, governance, and program council. Readers familiar with the program may wish to focus on the second section, which describes the core of the science strategy, including priorities across each of the EHP’s major program activities in monitoring, hazard assessment, and targeted research. The third section outlines science priorities that cut across program activities, including those involving collaborations external to the EHP.
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U.S. Geological Survey
Mail Stop 905
12201 Sunrise Valley Drive
Reston, VA 20192
Anadromous fishes play important roles in nutrient dynamics for freshwater ecosystems; however, the trophic pathways have been less documented for iteroparous species like river herring (Alosa pseudoharengus and A. aestivalis) compared to semelparous species like Pacific salmon (Oncorhynchus spp.). Given recent increases in restoration activities to improve connectivity, an understanding of how anadromous river herring influence the morphology, physiology, and life history of predatory fishes can help predict restoration responses. We aimed to quantify the trophic influence of juvenile anadromous river herring on predatory white perch (Morone americana) and yellow perch (Perca flavescens) using a combination of stable isotopes, growth rates, and condition indices. We sampled six lakes in coastal Massachusetts—three lakes with anadromous river herring and three similar lakes without river herring. Bayesian mixing models of δ13C and δ15N indicated white perch consumed juvenile river herring in higher proportions (69–75%) compared to co-occurring prey fishes (11–16%). Lakes with juvenile river herring contained perch with significantly higher condition values, higher immature growth rates (age 1 and 2), lower mature growth rates (> age 3), significantly smaller mature lengths, and lower mortality rates compared to perch in lakes without river herring. These divergent life history traits of perch in response to consumption of juvenile river herring are consistent with observations in other predatory fishes. Direct links between river herring and predator condition, growth, and life history trajectories suggest broad influences on ecosystem structure across trophic levels through physiological, morphometric, and life history modifications.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10641-024-01595-2","usgsCitation":"Mattocks, S., Bittner, S., Luzanau, V., Mohammadi, H., Roy, A.H., Staudinger, M., and Jordaan, A., 2024, River herring influence perch morphology, physiology, and life history: Environmental Biology of Fishes, v. 107, p. 1179-1201, https://doi.org/10.1007/s10641-024-01595-2.","productDescription":"23 p.","startPage":"1179","endPage":"1201","ipdsId":"IP-103045","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.03687326915752,\n 42.873848597989394\n ],\n [\n -71.03687326915752,\n 42.047149016365864\n ],\n [\n -70.5974201441574,\n 42.047149016365864\n ],\n [\n -70.5974201441574,\n 42.873848597989394\n ],\n [\n -71.03687326915752,\n 42.873848597989394\n ]\n ]\n ],\n \"type\": \"Polygon\"\n },\n \"id\": 0\n }\n ]\n}","volume":"107","noUsgsAuthors":false,"publicationDate":"2024-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mattocks, Steven","contributorId":349651,"corporation":false,"usgs":false,"family":"Mattocks","given":"Steven","affiliations":[{"id":83496,"text":"Massachusetts Division of Fisheries and Widlife","active":true,"usgs":false}],"preferred":false,"id":924535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bittner, Steven","contributorId":349652,"corporation":false,"usgs":false,"family":"Bittner","given":"Steven","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luzanau, Vasili","contributorId":349653,"corporation":false,"usgs":false,"family":"Luzanau","given":"Vasili","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mohammadi, Habibollah","contributorId":349654,"corporation":false,"usgs":false,"family":"Mohammadi","given":"Habibollah","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924534,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Staudinger, Michelle D.","contributorId":349655,"corporation":false,"usgs":false,"family":"Staudinger","given":"Michelle D.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924539,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jordaan, Adrian","contributorId":349656,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924540,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261527,"text":"70261527 - 2024 - Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D","interactions":[],"lastModifiedDate":"2025-05-13T15:59:07.445123","indexId":"70261527","displayToPublicDate":"2024-11-20T09:00:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D","docAbstract":"Numerical simulation of sediment transport and subsequent morphological evolution rely on accurate parameterizations of sediment characteristics. However, these data are often not available or are spatially and/or temporally limited. This study approaches the problem of limited sediment grain-size data with a series of simulations assessing model sensitivity to sediment parameters and initial bed composition configurations in Delft3D, leading to improved modeling practices. A previously validated Delft3D sediment transport and morphology model for Dauphin Island, Alabama, USA, is used as the benchmark case. A method for the generation of representative sediment grain sizes and their spatially varying distributions is presented via end-member analysis of in situ surficial sediment samples. Derived sediment classes and their spatial distributions are applied to two sensitivity case simulations with increasing bed composition complexity. First, multiple sediment classes are applied in a single fully mixed layer, regardless of sediment type. Second, multiple sediment classes are applied in a thin, fully mixed transport layer with underlayers containing only the non-cohesive sediment classes below. Simulations were carried out in a probabilistic, Delft3D MorMerge configuration to capture long-term morphology change for 10 years. We found there is sensitivity to the inclusion of additional sediment classes and sediment distribution made evident in bed level and morphology change. Inclusion of highly mobile fine sediments altered model results in each sensitivity case. The model was also found to be sensitive to initial bed composition in terms of bed level and morphology change, with notable differences between sensitivity cases on decadal timescales, indicating an armoring effect in the second sensitivity case, which used the transport and underlayer bed configuration. The results of this study offer guidance for numerical modelers concerned with sediment behavior in coastal and estuarine environments.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse12112108","usgsCitation":"Jenkins, R., Smith, C., Passeri, D., and Ellis, A.M., 2024, Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D: Journal of Marine Science and Engineering, v. 12, no. 11, 2108, 29 p., https://doi.org/10.3390/jmse12112108.","productDescription":"2108, 29 p.","ipdsId":"IP-170386","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466755,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse12112108","text":"Publisher Index Page"},{"id":465109,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.39043742176105,\n 30.854668400719234\n ],\n [\n -88.39043742176105,\n 30.17648303472457\n ],\n [\n -87.49364396321667,\n 30.17648303472457\n ],\n [\n -87.49364396321667,\n 30.854668400719234\n ],\n [\n -88.39043742176105,\n 30.854668400719234\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, Robert L. III 0000-0003-2078-4618","orcid":"https://orcid.org/0000-0003-2078-4618","contributorId":202181,"corporation":false,"usgs":true,"family":"Jenkins","given":"Robert L.","suffix":"III","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Passeri, Davina L. 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellis, Alisha M. 0000-0002-1785-020X aellis@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-020X","contributorId":192957,"corporation":false,"usgs":true,"family":"Ellis","given":"Alisha","email":"aellis@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920898,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70275335,"text":"70275335 - 2024 - Economic losses to inland recreational fisheries from harmful algal blooms","interactions":[],"lastModifiedDate":"2026-04-29T14:46:48.519661","indexId":"70275335","displayToPublicDate":"2024-11-19T09:31:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Economic losses to inland recreational fisheries from harmful algal blooms","docAbstract":"This paper presents research on the recreational impacts of harmful algal blooms (HABs) and other water quality changes in the U.S. heartland. We examine the link between recreational fishing and water quality using a random utility model of reservoir choices, and data on effort and health-based advisories for reservoirs in Nebraska. We find that advisories linked specifically to algal blooms affect the demand for and value of fishing, and that these effects are heterogeneous. The estimated welfare loss at HAB-afflicted reservoirs is approximately $12 per trip, with larger losses experienced by gamefish-oriented and college-educated fishers.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2024.123238","usgsCitation":"Jayasekera, D.H., Melstrom, R., and Pope, K.L., 2024, Economic losses to inland recreational fisheries from harmful algal blooms: Journal of Environmental Management, v. 372, 123238, 8 p., https://doi.org/10.1016/j.jenvman.2024.123238.","productDescription":"123238, 8 p.","ipdsId":"IP-170673","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":503780,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2024.123238","text":"Publisher Index Page"},{"id":503622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"372","noUsgsAuthors":false,"publicationDate":"2024-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Jayasekera, D. Harshanee","contributorId":370631,"corporation":false,"usgs":false,"family":"Jayasekera","given":"D.","middleInitial":"Harshanee","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":960595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melstrom, Richard","contributorId":370632,"corporation":false,"usgs":false,"family":"Melstrom","given":"Richard","affiliations":[{"id":88053,"text":"Loyola University-Chicago","active":true,"usgs":false}],"preferred":false,"id":960596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":960597,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273866,"text":"70273866 - 2024 - Fine-scale surficial soil moisture mapping using UAS-based L-band remote sensing in a mixed oak-grassland landscape","interactions":[],"lastModifiedDate":"2026-02-10T15:13:38.843978","indexId":"70273866","displayToPublicDate":"2024-11-19T08:03:14","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17157,"text":"Frontiers in Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Fine-scale surficial soil moisture mapping using UAS-based L-band remote sensing in a mixed oak-grassland landscape","docAbstract":"Soil moisture maps provide quantitative information that, along with climate and energy balance, is critical to integrate with hydrologic processes for characterizing landscape conditions. However, soil moisture maps are difficult to produce for natural landscapes because of vegetation cover and complex topography. Satellite-based L-band microwave sensors are commonly used to develop spatial soil moisture data products, but most existing L-band satellites provide only coarse scale (one to tens of kilometers grid size), information that is unsuitable for measuring soil moisture variation at hillslope or watershed-scales. L-band sensors are typically deployed on satellite platforms and aircraft but have been too large to deploy on small uncrewed aircraft systems (UAS). There is a need for greater spatial resolution and development of effective measures of soil moisture across a variety of natural vegetation types. To address these challenges, a novel UAS-based L-band radiometer system was evaluated that has recently been tested in agricultural settings. In this study, L-band UAS was used to map soil moisture at 3–50-m (m) resolution in a 13 square kilometer (km2) mixed grassland-forested landscape in Sonoma County, California. The results represent the first application of this technology in a natural landscape with complex topography and vegetation. The L-band inversion of the radiative transfer model produced soil moisture maps with an average unbiased root mean squared error (ubRMSE) of 0.07 m3/m3 and a bias of 0.02 m3/m3. Improved fine-scale soil moisture maps developed using UAS-based systems may be used to help inform wildfire risk, improve hydrologic models, streamflow forecasting, and early detection of landslides.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frsen.2024.1337953","usgsCitation":"Stern, M.A., Ferrell, R., Flint, L.E., Kozanitas, M., Ackerly, D., Elston, J., Stachura, M., Dai, E., and Thorne, J.H., 2024, Fine-scale surficial soil moisture mapping using UAS-based L-band remote sensing in a mixed oak-grassland landscape: Frontiers in Remote Sensing, v. 5, 1337953, 12 p., https://doi.org/10.3389/frsen.2024.1337953.","productDescription":"1337953, 12 p.","ipdsId":"IP-159618","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499941,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frsen.2024.1337953","text":"Publisher Index Page"},{"id":499713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Sonoma County","city":"Santa Rosa","otherGeospatial":"Mayacamas Mountains, Pepperwood Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.71354880264356,\n 38.57616137564548\n ],\n [\n -122.71354880264356,\n 38.565372954642044\n ],\n [\n -122.68982536456959,\n 38.565372954642044\n ],\n [\n -122.68982536456959,\n 38.57616137564548\n ],\n [\n -122.71354880264356,\n 38.57616137564548\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationDate":"2024-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferrell, Ryan","contributorId":366124,"corporation":false,"usgs":false,"family":"Ferrell","given":"Ryan","affiliations":[{"id":37798,"text":"Pepperwood Preserve","active":true,"usgs":false}],"preferred":false,"id":955320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Lorraine E. 0000-0002-7868-441X","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":306090,"corporation":false,"usgs":false,"family":"Flint","given":"Lorraine","email":"","middleInitial":"E.","affiliations":[{"id":66369,"text":"Earth Knowledge, Inc.","active":true,"usgs":false}],"preferred":false,"id":955321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kozanitas, Melina","contributorId":366125,"corporation":false,"usgs":false,"family":"Kozanitas","given":"Melina","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":955322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ackerly, David","contributorId":139541,"corporation":false,"usgs":false,"family":"Ackerly","given":"David","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":955323,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elston, Jack","contributorId":334719,"corporation":false,"usgs":false,"family":"Elston","given":"Jack","affiliations":[{"id":80215,"text":"Black Swift Technologies","active":true,"usgs":false}],"preferred":false,"id":955324,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stachura, Maciej","contributorId":334720,"corporation":false,"usgs":false,"family":"Stachura","given":"Maciej","affiliations":[{"id":80215,"text":"Black Swift Technologies","active":true,"usgs":false}],"preferred":false,"id":955325,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dai, Eryan","contributorId":366129,"corporation":false,"usgs":false,"family":"Dai","given":"Eryan","affiliations":[{"id":87362,"text":"Weather Stream Inc.","active":true,"usgs":false}],"preferred":false,"id":955326,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thorne, James H.","contributorId":173762,"corporation":false,"usgs":false,"family":"Thorne","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":955327,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260969,"text":"ofr20241063 - 2024 - High-Flow Experimental Outcomes to Inform Everglades Restoration, 2010–22","interactions":[],"lastModifiedDate":"2024-12-02T18:42:31.825148","indexId":"ofr20241063","displayToPublicDate":"2024-11-18T13:52:27","publicationYear":"2024","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":"2024-1063","displayTitle":"High-flow experimental outcomes to inform Everglades restoration, 2010–22","title":"High-Flow Experimental Outcomes to Inform Everglades Restoration, 2010–22","docAbstract":"The Decompartmentalization Physical Model (DPM) was an experimental facility in the central Everglades operated between 2010 and 2022 to release high flows through a levee-enclosed area of degraded ridge and slough wetland that had been isolated from flow for sixty years. The purpose of DPM experimental program was to make measurements before, during, and after seasonal high-flow releases that could help guide the Congressionally authorized Everglades restoration project known as the Decompartmentalization and Sheet Flow Enhancement Project.
The DPM facility was operated by the South Florida Water Management District, with the U.S. Geological Survey (USGS) and several universities participating in experimental design and leading aspects of the research. The USGS research at DPM focused on measuring high-flow hydraulics and its sedimentary and ecological responses in downstream wetlands. USGS investigated interactions between flow and vegetation and microtopography that influenced flow velocity and water depth, bed shear stress, sediment entrainment, and the resulting downstream transport of suspended sediment and fate of particle-associated phosphorus. USGS also investigated high-flow changes in water-column mixing and gas exchange and resulting effects on metabolism of the aquatic ecosystem (primary productivity and respiration). USGS also investigated effects of built structures such as levee gaps that were constructed to reconnect levee-enclosed basins. This report describes the methods and results of the USGS-led data collection at DPM.
The USGS studies at DPM have identified factors that influence effectiveness of restoration, specifically how high-flow releases maximize sheet flow and affect sediment and nutrient dynamics while minimizing undesirable outcomes caused by past management that bypassed wetlands by conveying polluted water through canals to ecologically sensitive downstream areas. The DPM high-flow experiments reconnected the Water Conservation Area 3A and Water Conservation Area 3B basins, and it therefore has become a central feature of the restoration’s Decompartmentalization and Sheet Flow Enhancement Project. DPM’s scientific findings have already influenced the adaptive management of Everglades restoration in guiding elements of the final design and implementation of the Central Everglades Planning Project-South. In addition to serving Everglades restoration, the DPM has the potential to influence similar adaptive management programs throughout the nation’s network of federal and state-managed river corridors, floodplains, and riparian ecosystems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20241063","usgsCitation":"Harvey, J., Choi, J., Larsen, L., Skalak, K., Maglio, M., Quion, K., Swartz, A., Lin, J.T.Y., Gomez-Velez, J., and Schmadel, N., 2024, High-flow experimental outcomes to inform Everglades restoration, 2010–22: U.S. Geological Survey Open-File Report 2024–1063, 72 p., https://doi.org/10.3133/ofr20241063.","productDescription":"Report: xi, 72 p.; 3 Data Releases","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-148372","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":464267,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1063/coverthb.jpg"},{"id":464268,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1063/ofr20241063.pdf","text":"Report","size":"5.4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":464271,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241063/full"},{"id":464270,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1063/images"},{"id":464269,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1063/ofr20241063.XML"},{"id":464274,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A9SQ85","text":"USGS Data Release","description":"Harvey, J.W., Choi, J., Quion, K., Lin, J.T., Swartz, A., Larsen, L.G., Haase, K., and Schmadel, N., 2024, High-flow Experimental Outcomes for Everglades Hydraulics and Aquatic Metabolism: U.S. Geological Survey, data release, https://doi.org/10.5066/P9A9SQ85.","linkHelpText":"- High-flow Experimental Outcomes for Everglades Hydraulics and Aquatic Metabolism"},{"id":464272,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQYB1O","text":"USGS Data Release","description":"Harvey, J.W., and Choi, J., 2022, Biophysical Data for Simulating Overland Flow in the Everglades: U.S. Geological Survey data release, https://doi.org/10.5066/P9DQYB1O.","linkHelpText":"- Biophysical Data for Simulating Overland Flow in the Everglades"},{"id":464273,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SP0HM1","text":"USGS Data Release","description":"Harvey, J.W., Choi, J., Larsen, L., Skalak, K., Maglio, M.M., Quion, K.M., Lin, T., Psaltakis, J.W., Buskirk, B.A., Swartz, A.G., Lewis, J.M., Gomez-Velez, J.D., and Schmadel, N.M., 2022, High-Flow Field Experiments to Inform Everglades Restoration: Experimental Data 2010 to 2022 (ver. 2.0, October 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9SP0HM1.","linkHelpText":"- High-Flow Field Experiments to Inform Everglades Restoration: Experimental Data 2010 to 2022 (ver. 2.0, October 2023)"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.1076224101966,\n 26.691819233104567\n ],\n [\n -82.1076224101966,\n 24.751056659514802\n ],\n [\n -79.55347920896048,\n 24.751056659514802\n ],\n [\n -79.55347920896048,\n 26.691819233104567\n ],\n [\n -82.1076224101966,\n 26.691819233104567\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Water Resources Mission Area
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The loss of phosphorous (P) from the land to aquatic systems has polluted waters and threatened food production worldwide. Systematic trend analysis of P, a nonrenewable resource, has been challenging, primarily due to sparse and inconsistent historical data. Here, we leveraged intensive hydrometeorological data and the recent renaissance of deep learning approaches to fill data gaps and reconstruct temporal trends. We trained a multitask long short-term memory model for total P (TP) using data from 430 rivers across the contiguous United States (CONUS). Trend analysis of reconstructed daily records (1980–2019) shows widespread decline in concentrations, with declining, increasing, and insignificantly changing trends in 60%, 28%, and 12% of the rivers, respectively. Concentrations in urban rivers have declined the most despite rising urban population in the past decades; concentrations in agricultural rivers however have mostly increased, suggesting not-as-effective controls of nonpoint sources in agriculture lands compared to point sources in cities. TP loss, calculated as fluxes by multiplying concentration and discharge, however exhibited an overall increasing rate of 6.5% per decade at the CONUS scale over the past 40 y, largely due to increasing river discharge. Results highlight the challenge of reducing TP loss that is complicated by changing river discharge in a warming climate.
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W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":920320,"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":920321,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shenk, Gary W. 0000-0001-6451-2513","orcid":"https://orcid.org/0000-0001-6451-2513","contributorId":225440,"corporation":false,"usgs":true,"family":"Shenk","given":"Gary","email":"","middleInitial":"W.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920322,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Xiaofeng 0000-0002-8296-7076","orcid":"https://orcid.org/0000-0002-8296-7076","contributorId":317075,"corporation":false,"usgs":false,"family":"Liu","given":"Xiaofeng","email":"","affiliations":[{"id":68932,"text":"Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA, USA","active":true,"usgs":false}],"preferred":false,"id":920323,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Li, Li","contributorId":223548,"corporation":false,"usgs":false,"family":"Li","given":"Li","affiliations":[],"preferred":false,"id":920324,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70261271,"text":"70261271 - 2024 - Awakening of Maunaloa linked to melt shared from Kilauea’s mantle source","interactions":[],"lastModifiedDate":"2024-12-04T15:22:55.307538","indexId":"70261271","displayToPublicDate":"2024-11-16T08:12:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Awakening of Maunaloa linked to melt shared from Kilauea’s mantle source","docAbstract":"Maunaloa—the largest active volcano on Earth—erupted in 2022 after its longest known repose period (~38 years) and two decades of volcanic unrest. This eruptive hiatus at Maunaloa encompasses most of the ~35-year-long Puʻuʻōʻō eruption of neighboring Kīlauea, which ended in 2018 with a collapse of the summit caldera and an unusually voluminous (~1 km3) rift eruption. A long-term pattern of such anticorrelated eruptive behavior suggests that a magmatic connection exists between these volcanoes within the asthenospheric mantle source and melting region, the lithospheric mantle, and/or the volcanic edifice. The exact nature of this connection is enigmatic. In the past, the distinct compositions of lavas from Kīlauea and Maunaloa were thought to require completely separate magma pathways from the mantle source of each volcano to the surface. Here, we use a nearly 200-yr record of lava chemistry from both volcanoes to demonstrate that melt from a shared mantle source within the Hawaiian plume may be transported alternately to Kīlauea or Maunaloa on a timescale of decades. This process led to a correlated temporal variation in 206Pb/204Pb and 87Sr/86Sr at these volcanoes since the early 19th century with each becoming more active when it received melt from the shared source. Ratios of highly over moderately incompatible trace elements (e.g., Nb/Y) at Kīlauea reached a minimum from ~2000 to 2010, which coincides with an increase in seismicity and inflation at the summit of Maunaloa. Thereafter, a reversal in Nb/Y at Kīlauea signals a decline in the degree of mantle partial melting at this volcano and suggests that melt from the shared source is now being diverted from Kīlauea to Maunaloa for the first time since the early to mid-20th century. These observations link a mantle-related shift in melt generation and transport at Kīlauea to the awakening of Maunaloa in 2002 and its eruption in 2022. Monitoring of lava chemistry is a potential tool that may be used to forecast the behavior (e.g., eruption rate and frequency) of these adjacent volcanoes on a timescale of decades. A future increase in eruptive activity at Maunaloa is likely if the temporal increase in Nb/Y continues at Kīlauea.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/petrology/egae121","usgsCitation":"Pietruszka, A., Heaton, D.E., Marske, J.P., Norman, M.D., Robbins, M.G., Mershon, R.B., Lynn, K.J., Downs, D.T., Steiner, A.R., Rhodes, J.M., and Garcia, M.O., 2024, Awakening of Maunaloa linked to melt shared from Kilauea’s mantle source: Journal of Petrology, v. 65, no. 12, egae121, 9 p., https://doi.org/10.1093/petrology/egae121.","productDescription":"egae121, 9 p.","ipdsId":"IP-169683","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egae121","text":"Publisher Index Page"},{"id":464749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano, Maunaloa volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.62647011347312,\n 19.636068332660543\n ],\n [\n -155.62647011347312,\n 19.326511618337022\n ],\n [\n -155.16252314077784,\n 19.326511618337022\n ],\n [\n -155.16252314077784,\n 19.636068332660543\n ],\n [\n -155.62647011347312,\n 19.636068332660543\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"65","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Pietruszka, Aaron J.","contributorId":346909,"corporation":false,"usgs":false,"family":"Pietruszka","given":"Aaron J.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":920179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heaton, Daniel E.","contributorId":172800,"corporation":false,"usgs":false,"family":"Heaton","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":920180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marske, Jared P.","contributorId":172801,"corporation":false,"usgs":false,"family":"Marske","given":"Jared","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":920181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norman, Marc D.","contributorId":344700,"corporation":false,"usgs":false,"family":"Norman","given":"Marc","email":"","middleInitial":"D.","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":920182,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robbins, Mahinaokalani G.","contributorId":346912,"corporation":false,"usgs":false,"family":"Robbins","given":"Mahinaokalani","email":"","middleInitial":"G.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":920183,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mershon, Reed B.","contributorId":346915,"corporation":false,"usgs":false,"family":"Mershon","given":"Reed","email":"","middleInitial":"B.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":920184,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":920185,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Downs, Drew T. 0000-0002-9056-1404 ddowns@usgs.gov","orcid":"https://orcid.org/0000-0002-9056-1404","contributorId":173516,"corporation":false,"usgs":true,"family":"Downs","given":"Drew","email":"ddowns@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":920186,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steiner, Arron R.","contributorId":346918,"corporation":false,"usgs":false,"family":"Steiner","given":"Arron","email":"","middleInitial":"R.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":920187,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rhodes, J. Michael","contributorId":215130,"corporation":false,"usgs":false,"family":"Rhodes","given":"J.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":920188,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Garcia, Michael O.","contributorId":225524,"corporation":false,"usgs":false,"family":"Garcia","given":"Michael","email":"","middleInitial":"O.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":920189,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70260970,"text":"70260970 - 2024 - Three-dimensional temperature maps of the Williston Basin, USA: Implications for deep hot sedimentary and enhanced geothermal resources","interactions":[],"lastModifiedDate":"2024-11-27T16:09:53.482598","indexId":"70260970","displayToPublicDate":"2024-11-15T11:29:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Three-dimensional temperature maps of the Williston Basin, USA: Implications for deep hot sedimentary and enhanced geothermal resources","docAbstract":"As part of U.S. Geological Survey's (USGS) efforts to identify and assess geothermal energy resources of the US, a three-dimensional (3D) geologic and thermal model has been constructed for the Williston Basin, USA. The geologic model consists of all sedimentary units above the Proterozoic and Archean crystalline rock (called basement herein), with a total sedimentary thickness of up to 5 km near the basin center. Twenty-nine geologic units were mapped from interpreted formation tops from 16,465 wells. A 3D temperature model was constructed to a depth of 7 km by constructing a 3D heat flow model for the sedimentary units, followed by estimating underlying temperature using a one-dimensional (1D) analytic solution for heat flow within the underlying crystalline basement. Using the sedimentary basin model, heat flow was simulated in 3D and was calibrated using three temperature datasets: 1) 24 high-confidence static temperature logs (equilibrium thermal profiles), 2) more than15,000 drill stem test (DST) measurements from >7,000 wells, and 3) more than 45,000 bottomhole temperature (BHT) measurements from >14,000 wells. The DST and BHT datasets provide broad spatial coverage, but are lower confidence, primarily because measurements were made prior to attaining thermal equilibrium. DST and BHT measurements were binned regionally to develop representative thermal profiles that generally agree with these lower quality data (hereafter called pseudowell temperature profiles). Layer properties (primarily thermal conductivity and compaction curves) were set to best estimate values, then the heat flow model was calibrated to fit pseudowell and static temperature logs primarily by adjusting basal heat flow to approximate the overall temperature profile. Minor adjustments to thermal conductivity allowed adjusting changes in slope at lithologic contacts. Resulting maps include 3D temperature and basal (bottom of sedimentary units) heat flow estimates, which are used as input for the temperature model of the basement. The crystalline basement temperature model uses an analytic 1D solution to the heat flow equation that requires estimates of heat flow and temperature at the upper boundary (i.e., the sediment/basement contact), radiogenic heat production within the crystalline basement, and reference thermal conductivity (i.e., uncorrected for temperature). Two regions of high heat flow are identified: 1) in western North Dakota along the North American Central Plains Conductivity Anomaly and 2) in eastern Montana near the Poplar dome. Within the sedimentary column in the center of the basin of the basin, an area of approximately 100,000 km2 is predicted to have moderate- to high-temperature geothermal resources (>90 °C) under the thickest sequences of sediments. Where thick insulation and high heat flow coincide, electric-grade resources can be less than 4 km deep. Assuming a maximum feasible drilling depth of 7 km, temperatures are predicted to be as high as 175 °C. The geologic model may be used to identify strata at sufficient temperatures that may have natural permeability or that may have conditions that favor development of enhanced/engineered geothermal systems resources.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2024.103196","usgsCitation":"Gelman, S.E., and Burns, E.R., 2024, Three-dimensional temperature maps of the Williston Basin, USA: Implications for deep hot sedimentary and enhanced geothermal resources: Geothermics, v. 125, 103196, 9 p., https://doi.org/10.1016/j.geothermics.2024.103196.","productDescription":"103196, 9 p.","ipdsId":"IP-165645","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":466763,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2024.103196","text":"Publisher Index Page"},{"id":464292,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.05487036081263,\n 49.09401622161886\n ],\n [\n -107.05487036081263,\n 45.9204646960259\n ],\n [\n -100.81731222757732,\n 45.9204646960259\n ],\n [\n -100.81731222757732,\n 49.09401622161886\n ],\n [\n -107.05487036081263,\n 49.09401622161886\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"125","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gelman, Sarah E. 0000-0003-2549-9509","orcid":"https://orcid.org/0000-0003-2549-9509","contributorId":270004,"corporation":false,"usgs":true,"family":"Gelman","given":"Sarah","email":"","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":918758,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70270062,"text":"70270062 - 2024 - Differentiating cheatgrass and medusahead phenological characteristics in western United States rangelands","interactions":[],"lastModifiedDate":"2025-08-08T15:24:31.376369","indexId":"70270062","displayToPublicDate":"2024-11-15T10:19:32","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Differentiating cheatgrass and medusahead phenological characteristics in western United States rangelands","docAbstract":"Expansions in the extent and infestation levels of exotic annual grass (EAG) within the rangelands of the western United States are well documented. Land managers are tasked with developing plans to limit EAG spread and prevent irreversible ecosystem deterioration. The most common EAG species and the subject of extensive study is Bromus tectorum (cheatgrass). Cheatgrass has spread rapidly in western rangelands since its initial invasion more than 100 years ago. Another concerning aggressive EAG, Taeniatherum caput-medusae (medusahead), is also commonly found in some of these areas. To control the spread of EAGs, researchers have investigated applying several control methods during different developmental stages of cheatgrass and medusahead. These control strategies require accurate maps of the timing and spatial patterns of the developmental stages to apply mitigation strategies in the correct areas at the right time. In this study, we developed annual phenological datasets for cheatgrass and medusahead with two objectives. The first objective was to determine if cheatgrass and medusahead can be differentiated at 30 m resolution using their phenological differences. The second objective was to establish an annual phenology metric regression tree model used to map the growing seasons of cheatgrass and medusahead. Harmonized Landsat and Sentinel-2 (HLS)-derived predicted weekly cloud-free 30 m normalized difference vegetation index (NDVI) images were used to develop these metric maps. The result of this effort was maps that identify the start and end of sustained growing season time for cheatgrass and medusahead at 30 m for the Snake River Plain and Northern Basin and Range ecoregions. These phenological datasets also identify the start and end-of-season NDVI values, along with maximum NDVI throughout the study period. These metrics may be utilized to characterize annual growth patterns for cheatgrass and medusahead. This approach can be utilized to plan time-sensitive control measures such as herbicide applications or cattle grazing.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16224258","usgsCitation":"Benedict, T.D., Boyte, S., and Dahal, D., 2024, Differentiating cheatgrass and medusahead phenological characteristics in western United States rangelands: Remote Sensing, v. 16, no. 22, 4258, 21 p., https://doi.org/10.3390/rs16224258.","productDescription":"4258, 21 p.","ipdsId":"IP-171996","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":494184,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16224258","text":"Publisher Index Page"},{"id":493848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -100.28187929406397,\n 48.82060636906533\n ],\n [\n -124.99361768794509,\n 48.88697493321598\n ],\n [\n -124.99361768794509,\n 30.85327470627726\n ],\n [\n -99.69664006714606,\n 30.849197853937767\n ],\n [\n -100.28187929406397,\n 48.82060636906533\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"22","noUsgsAuthors":false,"publicationDate":"2024-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Benedict, Trenton David 0000-0001-8672-2204","orcid":"https://orcid.org/0000-0001-8672-2204","contributorId":346111,"corporation":false,"usgs":true,"family":"Benedict","given":"Trenton","middleInitial":"David","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":945268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyte, Stephen P. 0000-0002-5462-3225","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":205374,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":945269,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dahal, Devendra 0000-0001-9594-1249","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":192023,"corporation":false,"usgs":false,"family":"Dahal","given":"Devendra","affiliations":[],"preferred":false,"id":945270,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260977,"text":"70260977 - 2024 - Advancing sustainable groundwater management with a hydro-economic system model: Investigations in the Harney Basin, Oregon","interactions":[],"lastModifiedDate":"2024-11-19T19:40:18.336461","indexId":"70260977","displayToPublicDate":"2024-11-14T13:32:20","publicationYear":"2024","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":"Advancing sustainable groundwater management with a hydro-economic system model: Investigations in the Harney Basin, Oregon","docAbstract":"Groundwater resources frequently trend toward unsustainable levels because, absent effective institutions, individual water users generally act independently without considering the impacts on other users. Hydro-economic models (HEMs) of human-natural systems can play a positive role toward successful groundwater management by yielding valuable knowledge and insight. The current study explores how an HEM that captures essential physical and economic characteristics of a system can shed light on the system's processes and dynamics to benefit stakeholders, managers, and also researchers. These propositions are illustrated using the Harney Basin, Oregon, which has seen large groundwater declines in the past 20 years. The HEM shows that: (a) although current groundwater pumping rates will gradually raise costs and reduce well yields, irrigators gain the highest aggregate economic return by continuing current pumping; (b) lowland areas of the basin are hydrologically connected, which limits the efficacy of remedies focused on regulations only in some portions of the basin; (c) community expectations regarding the efficacy of several proposed solutions are overly optimistic; and (d) the study's scenarios identify interventions that would stabilize the groundwater system and prevent additional adverse impacts on residential and livestock wells and groundwater-dependent ecosystems. These interventions would require limiting groundwater pumping by nearly half and reducing annual profits by $7.5–$9.0M. The HEM also demonstrated its value to researchers: its insights shifted attention toward questions about Oregon's existing groundwater institutions and their inability to adaptively manage the transition from abundant groundwater to scarce groundwater in a timely manner.","language":"English","publisher":"Wiley","doi":"10.1029/2023WR036972","usgsCitation":"Jaeger, W.K., Antle, J.M., Gingerich, S.B., and Bigelow, D., 2024, Advancing sustainable groundwater management with a hydro-economic system model: Investigations in the Harney Basin, Oregon: Water Resources Research, v. 60, e2023WR036972, 26 p., https://doi.org/10.1029/2023WR036972.","productDescription":"e2023WR036972, 26 p.","ipdsId":"IP-159409","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":466765,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr036972","text":"Publisher Index Page"},{"id":464300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","county":"Harney","otherGeospatial":"Harney Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.44430319880412,\n 44.965776942074626\n ],\n [\n -121.44430319880412,\n 42.262073209475204\n ],\n [\n -117.31344382380401,\n 42.262073209475204\n ],\n [\n -117.31344382380401,\n 44.965776942074626\n ],\n [\n -121.44430319880412,\n 44.965776942074626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","noUsgsAuthors":false,"publicationDate":"2024-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Jaeger, William K.","contributorId":338398,"corporation":false,"usgs":false,"family":"Jaeger","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":918781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Antle, John M.","contributorId":197804,"corporation":false,"usgs":false,"family":"Antle","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":918782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gingerich, Stephen B. 0000-0002-4381-0746 sbginger@usgs.gov","orcid":"https://orcid.org/0000-0002-4381-0746","contributorId":1426,"corporation":false,"usgs":true,"family":"Gingerich","given":"Stephen","email":"sbginger@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bigelow, Daniel 0000-0002-1154-2302","orcid":"https://orcid.org/0000-0002-1154-2302","contributorId":346353,"corporation":false,"usgs":false,"family":"Bigelow","given":"Daniel","email":"","affiliations":[{"id":82838,"text":"Oregon State University Applied Economics Department","active":true,"usgs":false}],"preferred":false,"id":918784,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267760,"text":"70267760 - 2024 - Evaluating spatially explicit management alternatives for an invasive species in a riverine network","interactions":[],"lastModifiedDate":"2025-05-30T15:47:18.945176","indexId":"70267760","displayToPublicDate":"2024-11-14T10:37:09","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating spatially explicit management alternatives for an invasive species in a riverine network","docAbstract":"Invasive species have substantial ecological and economic costs and removing them can require large investments by management agencies. Optimal spatial allocation of removal effort is critical for efficient and effective management of invasive species. Using a series of ecologically informed model simulations, we evaluated and compared different spatially explicit removal strategies for invasive rusty crayfish (Faxonius rusticus) in the John Day River, USA. We assessed strategies in terms of their performance on three likely management objectives: suppression (minimise overall population abundance), containment (minimise the spatial extent of invasion) and prevention (minimise spread into a specific area). We developed five spatial removal strategies to achieve those objectives, denoted as: Target Abundance (removal at locations with the highest population abundance), Target Growth (removal at locations with the highest population growth), Target Edges (removal at the most distant locations in the river), Target Downstream (removal at the most downstream invaded segments on the Mainstem), and Target Random (removal at randomly selected locations). Each strategy was assessed at various effort levels, referring to the number of spatial segments in the river in which removals were conducted, after seven years of management. We identified the alternative that best achieved each objective, based on decision criteria for risk-neutral and risk-averse decision-makers and further evaluated strategies based on Pareto efficiency, which identifies the set of alternatives for which an improvement on one objective cannot be had without a decline in performance on another. We found that Target Abundance and Target Growth strategies best achieved the suppression objective, for risk neutral and risk averse decision-makers, respectively and Target Downstream was always best in achieving the prevention objective across both types of decision-makers. No single strategy consistently performed best in terms of the containment objective. In terms of all three objectives, Target Downstream was consistently Pareto efficient across all levels of management effort and both decision criteria. The modelling framework we provided is adaptable to a variety of riverine invasive species to help assess and compare spatial management strategies.
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","language":"English","publisher":"Springer Nature","doi":"10.1007/s10530-024-03450-y","usgsCitation":"Coulter, A., Moore, M.J., Golcher-Benavides, J., Rahel, F.J., Walters, A.W., Brewer, S., and Wildhaber, M.L., 2024, A synthesis of the characteristics and drivers of introduced fishes in prairie streams: Can we manage introduced harmful fishes in these dynamic environments?: Biological Invasions, v. 26, p. 4011-4033, https://doi.org/10.1007/s10530-024-03450-y.","productDescription":"23 p.","startPage":"4011","endPage":"4033","ipdsId":"IP-160187","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-024-03450-y","text":"Publisher Index Page"},{"id":480749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"North American Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.30865918818435,\n 51.00019043175968\n ],\n [\n -108.8244372572745,\n 47.17125929409586\n ],\n [\n -106.13072410712726,\n 42.33953855703288\n ],\n [\n -104.22086600055933,\n 40.10613156257109\n ],\n [\n -104.39837770581909,\n 36.40878493463546\n ],\n [\n -104.26570852411,\n 33.836825487233355\n ],\n [\n -102.59989428051855,\n 31.991484684655916\n ],\n [\n -98.85669537584786,\n 31.98987602981056\n ],\n [\n -94.06006847133565,\n 38.705570253107695\n ],\n [\n -94.4212804260574,\n 43.37128007692609\n ],\n [\n -96.14739688752542,\n 48.2616932328075\n ],\n [\n -96.41979434976253,\n 50.75373398643449\n ],\n [\n -96.92898991711421,\n 51.5227386971378\n ],\n [\n -99.57727818526257,\n 52.66077258131\n ],\n [\n -107.3372532002433,\n 51.958499229615185\n ],\n [\n -111.30865918818435,\n 51.00019043175968\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","noUsgsAuthors":false,"publicationDate":"2024-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Coulter, A. A.","contributorId":348595,"corporation":false,"usgs":false,"family":"Coulter","given":"A. A.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":923644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Michael J. 0000-0002-5495-7049","orcid":"https://orcid.org/0000-0002-5495-7049","contributorId":304258,"corporation":false,"usgs":true,"family":"Moore","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golcher-Benavides, Jimena","contributorId":348598,"corporation":false,"usgs":false,"family":"Golcher-Benavides","given":"Jimena","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":923646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rahel, Frank J.","contributorId":171824,"corporation":false,"usgs":false,"family":"Rahel","given":"Frank","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":923647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":923648,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brewer, Shannon K. 0000-0002-1537-3921","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":340552,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":923649,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":923650,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}