Freshwater ecosystems are some of the most affected by biological invasions due, in part, to the introduction of invasive carp worldwide. Where carp have become established, management programs often seek to limit further range expansion into new areas by reducing their movement through interconnected rivers and waterways. Lock and dams are important locations for non-physical deterrents, such as carbon dioxide (CO2), to reduce unwanted fish passage without disrupting human use. The purpose of this study was to evaluate the behavioral responses of common carp (Cyprinus carpio) to non-physical deterrents within a navigation structure on the Fox River, Wisconsin. Acoustic telemetry combined with hidden Markov models (HMMs) was used to analyze variation in carp responses to treatments. Outcomes may inform CO2 effectiveness at preventing invasive carp movement through movement pinch-points.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-023-00396-z","usgsCitation":"Raboin, M.J., Plumb, J., Sholtis, M.D., Smith, D., Jackson, P.R., Rivera, J., Suski, C., and Cupp, A.R., 2023, Movement and behavioral states of common carp (Cyprinus carpio) in response to a behavioral deterrent in a navigational lock: Movement Ecology, v. 11, 42, 16 p., https://doi.org/10.1186/s40462-023-00396-z.","productDescription":"42, 16 p.","ipdsId":"IP-148214","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":442636,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-023-00396-z","text":"Publisher Index Page"},{"id":435240,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B8SRMW","text":"USGS data release","linkHelpText":"Acoustic Telemetry Evaluation of Invasive Carp in Kaukauna, Wisconsin (Summer 2019)"},{"id":419500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Fox River, Kaukauna locks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.2903788929823,\n 44.27679879835844\n ],\n [\n -88.30570324899331,\n 44.27679879835844\n ],\n [\n -88.30570324899331,\n 44.270866037921394\n ],\n [\n -88.2903788929823,\n 44.270866037921394\n ],\n [\n -88.2903788929823,\n 44.27679879835844\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Raboin, Maggie Jo 0000-0002-1475-7253","orcid":"https://orcid.org/0000-0002-1475-7253","contributorId":317839,"corporation":false,"usgs":true,"family":"Raboin","given":"Maggie","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":879428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":223236,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":879429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sholtis, Matthew D. 0000-0003-1904-8250","orcid":"https://orcid.org/0000-0003-1904-8250","contributorId":317840,"corporation":false,"usgs":true,"family":"Sholtis","given":"Matthew","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":879430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, David","contributorId":261251,"corporation":false,"usgs":false,"family":"Smith","given":"David","affiliations":[{"id":52784,"text":"U.S. Department of Agriculture, Economic Research Service","active":true,"usgs":false}],"preferred":false,"id":879431,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, P. 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D.","contributorId":190151,"corporation":false,"usgs":false,"family":"Suski","given":"C.","middleInitial":"D.","affiliations":[],"preferred":false,"id":879434,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":879435,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70246554,"text":"70246554 - 2023 - Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards","interactions":[],"lastModifiedDate":"2023-10-23T14:41:47.420879","indexId":"70246554","displayToPublicDate":"2023-07-07T09:56:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards","docAbstract":"The steep, tectonically active terrain along the Central California (USA) coast is well known to produce deadly and destructive debris flows. However, the extent to which fire affects debris-flow susceptibility in this region is an open question. We documented the occurrence of postfire debris floods and flows following the landfall of a storm that delivered intense rainfall across multiple burn areas. We used this inventory to evaluate the predictive performance of the US Geological Survey M1 likelihood model, a tool that presently underlies the emergency assessment of postfire debris-flow hazards in the western USA. To test model performance, we used the threat score skill statistic and found that the rainfall thresholds estimated by the M1 model for the Central California coast performed similarly to training (Southern California) and testing (Intermountain West) data associated with the original model calibration. Model performance decreased when differentiating between “minor” and “major” postfire hydrologic response types, which weigh effects on human life and infrastructure. Our results underscore that the problem of false positives is a major challenge for developing accurate rainfall thresholds for the occurrence of postfire debris flows. As wildfire activity increases throughout the western USA, so too will the demand for the assessment of postfire debris-flow hazards. We conclude that additional collection of field-verified inventories of postfire hydrologic response will be critical to prioritize which model variables may be suitable candidates for regional calibration or replacement.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-023-02106-7","usgsCitation":"Thomas, M.A., Kean, J.W., McCoy, S., Lindsay, D.N., Kostelnik, J., Cavagnaro, D.B., Rengers, F.K., East, A.E., Schwartz, J., Smith, D.P., and Collins, B.D., 2023, Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards: Landslides, v. 20, p. 2421-2436, https://doi.org/10.1007/s10346-023-02106-7.","productDescription":"16 p.","startPage":"2421","endPage":"2436","ipdsId":"IP-139528","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442830,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index 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Center","active":true,"usgs":true}],"preferred":true,"id":877144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Scott W.","contributorId":267182,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":877145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsay, Donald N.","contributorId":216337,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","email":"","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":877146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards 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aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":877150,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schwartz, Jonathan","contributorId":312505,"corporation":false,"usgs":false,"family":"Schwartz","given":"Jonathan","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":877151,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Douglas P.","contributorId":201716,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","email":"","middleInitial":"P.","affiliations":[{"id":35924,"text":"California State University, Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":877152,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":877153,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70246616,"text":"70246616 - 2023 - A detailed view of the 2020-2023 southwestern Puerto Rico seismic sequence with deep learning","interactions":[],"lastModifiedDate":"2023-12-04T16:59:36.832347","indexId":"70246616","displayToPublicDate":"2023-07-06T08:36:24","publicationYear":"2023","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":"A detailed view of the 2020-2023 southwestern Puerto Rico seismic sequence with deep learning","docAbstract":"The 2020–2023 southwestern Puerto Rico seismic sequence, still ongoing in 2023, is remarkable for its multiple‐fault rupture complexity and elevated aftershock productivity. We applied an automatic workflow to continuous data from 43 seismic stations in Puerto Rico to build an enhanced earthquake catalog with ∼180,000 events for the 3+ yr sequence from 28 December 2019 to 1 January 2023. This workflow contained the EQTransformer (EQT) deep learning model for event detection and phase picking, the EikoNet‐Hypocenter Inversion with Stein Variational Inference probabilistic earthquake location approach with a neural network trained to solve the eikonal wave equation, and relocation with event‐pair waveform cross correlation. EQT increased the number of catalog events in the sequence by about seven times, though its performance was not quite as good as thorough analyst review. The enhanced catalog revealed new structural details of the sequence space–time evolution, including sudden changes in activity, on a complex system of many small normal and strike‐slip faults. This sequence started on 28 December 2019 with an M 4.7 strike‐slip earthquake followed by 10 days of shallow strike‐slip foreshocks, including several M 5+ earthquakes, in a compact region. The oblique normal fault
Environmental DNA (eDNA) sampling provides sensitive early detection capabilities for recently introduced taxa. However, natural resource managers struggle with how to integrate eDNA results into an early detection rapid response program because positive eDNA detections are not always indicative of an eventual infestation. We used a structured decision making (SDM) framework to evaluate appropriate response actions to hypothetical eDNA early detections of an introduced aquatic plant in Sebago Lake (Maine, USA). The results were juxtaposed to a recent study that used a similar SDM approach to evaluate response actions to hypothetical eDNA early detections of introduced mussels in Jordanelle Reservoir (Utah, USA). We found that eDNA early detections were not actionable in Sebago Lake because the plant's invasion potential was spatially constrained and the current management activities provided acceptable levels of mitigation. In Jordanelle Reservoir, eDNA detections were actionable due to high invasion potential and analyses supported management actions to contain the invasion. The divergent outcomes of the two case studies are related to the unique attributes of the habitats and species, highlighting the utility of the SDM approach when considering an eDNA monitoring program. We use these two case studies to present a general SDM framework and a set of heuristics that can be efficiently applied to eDNA early detection rapid response scenarios and other instances associated with indeterminant eDNA detections, especially when there is an imperative to make decisions as quickly as possible.
Biodiversity and human well-being strategies are only as good as the set of ideas that people think about. This article evaluates value-focused thinking (VFT), a framework that focuses on creating objectives and strategy ideas that are responsive to the objectives. We performed a proof-of-concept study of VFT on six planning teams at a global conservation organization. We developed a package of support materials, including session agendas, a virtual facilitation template, facilitator's guide, and evaluation questionnaires. The study tested whether VFT resulted in a set of quality strategies, resulted in participant satisfaction, and was scalable, meaning that it could be facilitated by someone newly trained in VFT and result in quality strategies and participant satisfaction, as compared to an experienced facilitator. Net response indicated positive quality ratings for the set of strategies per team. Respondents indicated positive satisfaction overall, though it was higher for objectives than for strategies. Among the participants with previous experience, all were at least as satisfied with their VFT strategies compared to previously developed strategies, and none were less satisfied (P = 0.001). Changes in participant satisfaction were not related to facilitator type (P > 0.10). In addition, we found that some participants had a premature sense of shared understanding of important values and interests before entering the study, which VFT strengthened. This study highlights the advantages of structuring the development and evaluation of conservation planning frameworks.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.14109","usgsCitation":"Martin, D.M., Goldstein, J., Smith, D.R., Musengezi, J., Rountree, J.G., Galgamuwe, P.G., Craig, A., Dietz, M., and Kerr, C., 2023, Creating conservation strategies with value-focused thinking: Conservation Biology, v. 37, no. 5, e14109, 14 p., https://doi.org/10.1111/cobi.14109.","productDescription":"e14109, 14 p.","ipdsId":"IP-147268","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443640,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cobi.14109","text":"Publisher Index Page"},{"id":417534,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, David M. 0000-0002-1514-5734","orcid":"https://orcid.org/0000-0002-1514-5734","contributorId":210575,"corporation":false,"usgs":false,"family":"Martin","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":873969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Joshua","contributorId":197267,"corporation":false,"usgs":false,"family":"Goldstein","given":"Joshua","affiliations":[],"preferred":false,"id":873970,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":873971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Musengezi, Jessica","contributorId":305916,"corporation":false,"usgs":false,"family":"Musengezi","given":"Jessica","email":"","affiliations":[],"preferred":false,"id":874082,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rountree, Jessie G.","contributorId":305917,"corporation":false,"usgs":false,"family":"Rountree","given":"Jessie","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":874083,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Galgamuwe, Pabodha G. A.","contributorId":305918,"corporation":false,"usgs":false,"family":"Galgamuwe","given":"Pabodha","email":"","middleInitial":"G. A.","affiliations":[],"preferred":false,"id":874084,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Craig, Aileen","contributorId":305919,"corporation":false,"usgs":false,"family":"Craig","given":"Aileen","email":"","affiliations":[],"preferred":false,"id":874085,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dietz, Michelle","contributorId":305920,"corporation":false,"usgs":false,"family":"Dietz","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":874086,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kerr, Caitlin","contributorId":305921,"corporation":false,"usgs":false,"family":"Kerr","given":"Caitlin","email":"","affiliations":[],"preferred":false,"id":874087,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70262166,"text":"70262166 - 2023 - Environmental correlates of walleye spawning movements in an Appalachian hydropower reservoir","interactions":[],"lastModifiedDate":"2025-01-15T20:01:12.656734","indexId":"70262166","displayToPublicDate":"2023-03-01T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3909,"text":"Journal of the Southeastern Association of Fish and Wildlife Agencies","active":true,"publicationSubtype":{"id":10}},"title":"Environmental correlates of walleye spawning movements in an Appalachian hydropower reservoir","docAbstract":"Understanding walleye (Sander vitreus) spawning behavior is important for managing walleye fisheries, but such information is limited for Appalachian reservoirs. We assessed spawning movements and spawning locations for a reestablished walleye population in Cheat Lake, West Virginia. We tagged fifty-two walleye with acoustic telemetry transmitters to evaluate environmental correlates associated with pre-spawn movements and to deter- mine spawning locations. Using an information-theoretic approach, we compared candidate logistic regression models to determine which environmental variables best explained upstream movements to spawning areas. The two models with the most support both included additive effects of year and water temperature, with sex also included in the second of these models. Water temperature had a significant positive relationship with pre-spawn movements in each model. Other environmental covariates such as river discharge and water elevation were not significant predictors of upstream pre-spawn move- ments. Walleye made pre-spawn upstream movements in late winter/early spring to spawning areas in the headwaters of Cheat Lake during periods of el- evated water temperatures (75 % of movement events occurred at water temperatures >4.1 C) where spawning occurred in shallow (<1.5 m), rocky habitat. Male walleye generally made upstream pre-spawn movements earlier than females. Our results also suggested the timing of walleye spawning with respect to water-level fluctuations could influence reproductive success due to stranding of eggs or reducing suitable spawning habitat. Knowledge of pre-spawn movement patterns and spawning locations could aid management of this recovering population. Benefits to management may include the prediction of spawning timing and locations for broodstock surveys and influences of water-level fluctuations and other environmental stressors on spawning success.
","language":"English","publisher":"Southeastern Association of Fish and Wildlife Agencies","usgsCitation":"Smith, D., Welsh, S.A., and Hilling, C.D., 2023, Environmental correlates of walleye spawning movements in an Appalachian hydropower reservoir: Journal of the Southeastern Association of Fish and Wildlife Agencies, v. 10, p. 36-44.","productDescription":"9 p.","startPage":"36","endPage":"44","ipdsId":"IP-145288","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466453,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://seafwa.org/journal/2023/environmental-correlates-walleye-spawning-movements-appalachian-hydropower-reservoir"}],"country":"United States","state":"Pennsylvania, West Virginia","otherGeospatial":"Cheat Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.90059403320035,\n 39.7348398274502\n ],\n [\n -79.90059403320035,\n 39.665062724725885\n ],\n [\n -79.82498808610146,\n 39.665062724725885\n ],\n [\n -79.82498808610146,\n 39.7348398274502\n ],\n [\n -79.90059403320035,\n 39.7348398274502\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Dustin M.","contributorId":272979,"corporation":false,"usgs":false,"family":"Smith","given":"Dustin M.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":923331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":1483,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"swelsh@usgs.gov","middleInitial":"A.","affiliations":[{"id":205,"text":"Cooperative Research Units","active":false,"usgs":true}],"preferred":false,"id":923332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hilling, Corbin David 0000-0003-4040-9516","orcid":"https://orcid.org/0000-0003-4040-9516","contributorId":298946,"corporation":false,"usgs":true,"family":"Hilling","given":"Corbin","email":"","middleInitial":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":923333,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242017,"text":"70242017 - 2023 - Six years of fluvial response to a large dam removal on the Carmel River, California, USA","interactions":[],"lastModifiedDate":"2023-06-27T16:51:13.29324","indexId":"70242017","displayToPublicDate":"2023-02-07T08:17:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Six years of fluvial response to a large dam removal on the Carmel River, California, USA","docAbstract":"Measuring river response to dam removal affords a rare, important opportunity to study fluvial response to sediment pulses on a large field scale. We present a before–after/control–impact study of the Carmel River, California, measuring fluvial geomorphic and grain-size evolution over 8 years, six of which postdated removal of a 32 m-high dam (one of the largest dams removed worldwide) and included 11 flow events exceeding the 2-year flood magnitude. We find that the reservoir-sediment pulse following dam removal was relatively small (97 000 ± 24 000 t over 4 years), owing to deliberate reservoir-sediment stabilization. Scaled to the size of the Carmel River watershed and compared against long-term bedrock denudation rates, the post-dam-removal sediment release was slightly less than the annualized long-term sediment export from this basin. New sediment transited >30 km to the river mouth in less than 2 years, assisted by floods 2 and 4 years after dam removal. The sediment pulse fined the downstream riverbed while causing mostly low-magnitude bed-elevation changes: commonly 0.5 to 1 m or smaller, occurring as discontinuous sediment patches or interstitial deposits, aside from the filling and subsequent partial scour of deep pools. There was no major geomorphic reset downstream from the dam site. Geomorphic changes were driven almost entirely by flow rather than by the modest increase in sediment supply, in contrast to recent examples from other large dam removals. The relatively minor disturbance caused by dam removal on the Carmel River is likely analogous to many future dam removals: a relatively small sediment pulse after deliberate limitation of reservoir-sediment erosion, and with an upstream dam remaining in place. Thus, a large dam removal need not lead to major downstream impacts.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.5561","usgsCitation":"East, A.E., Harrison, L.R., Smith, D.P., Logan, J.B., and Bond, R., 2023, Six years of fluvial response to a large dam removal on the Carmel River, California, USA: Earth Surface Processes and Landforms, v. 48, no. 8, p. 1487-1501, https://doi.org/10.1002/esp.5561.","productDescription":"15 p.","startPage":"1487","endPage":"1501","ipdsId":"IP-146182","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444561,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.5561","text":"Publisher Index Page"},{"id":415160,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Carmel River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.62577522165773,\n 36.36105374788829\n ],\n [\n -121.58724434610056,\n 36.40905968854021\n ],\n [\n -121.61843600726598,\n 36.46293870830412\n ],\n [\n -121.750541866319,\n 36.53594773620604\n ],\n [\n -121.8532908678046,\n 36.61551540625254\n ],\n [\n -121.90741757394426,\n 36.588265345279865\n ],\n [\n -121.93261880515863,\n 36.54806169091083\n ],\n [\n -121.88413981443409,\n 36.520771377870034\n ],\n [\n -121.79850327393265,\n 36.50047233869989\n ],\n [\n -121.7839886060512,\n 36.469663631874326\n ],\n [\n -121.74712134963194,\n 36.40894399256348\n ],\n [\n -121.68209557572075,\n 36.36804816657221\n ],\n [\n -121.62606895769773,\n 36.3610353099688\n ],\n [\n -121.62577522165773,\n 36.36105374788829\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":868544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Lee R.","contributorId":174322,"corporation":false,"usgs":false,"family":"Harrison","given":"Lee","email":"","middleInitial":"R.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":868545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Douglas P.","contributorId":201716,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","email":"","middleInitial":"P.","affiliations":[{"id":35924,"text":"California State University, Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":868546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":868547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bond, Rosealea","contributorId":201717,"corporation":false,"usgs":false,"family":"Bond","given":"Rosealea","affiliations":[{"id":12520,"text":"NOAA National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":868548,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239772,"text":"70239772 - 2023 - Incorporating temperature into seepage loss estimates for a large unlined irrigation canal","interactions":[],"lastModifiedDate":"2025-05-14T17:36:22.285243","indexId":"70239772","displayToPublicDate":"2023-01-18T06:52:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating temperature into seepage loss estimates for a large unlined irrigation canal","docAbstract":"Quantifying seepage losses from unlined irrigation canals is necessary to improve water use and conservation. The use of heat as a tracer is widely used in quantifying seepage rates across the sediment–water interface. In this study, field observations and two-dimensional numerical models were used to simulate seepage losses during the 2018 and 2019 irrigation season in the Truckee Canal system. Nineteen transects were instrumented with temperature probes and stage recording devices for inverse modeling to derive seepage flux and volumetric losses over the 39 km length of canal. The numerical models for each transect were calibrated and validated using the two-year dataset. Soil zones and observation data were used in each numerical model to help guide calibration of vertical and lateral heat and fluid fluxes. Model simulations were used to derive multivariable regression equations that consider stage, temperature, and hydraulic gradient. The results demonstrate the value of long-term datasets that illustrate the seasonality of groundwater levels, siltation, stage, and temperature on seepage rates. Seepage rates estimated by the numerical models range from 0.16 to 4.6 m3/d m−1. Total annual volumetric losses estimated for 2018 and 2019 were 1.6 × 10-2 to 1.2 × 10-2 km3, respectively. The seepage losses estimated by this study account for 32 % to 41 % of the inflow volumes. Regression models were able to reproduce seepage time-series simulated by the numerical models reasonably well. In arid environments, water diverted into irrigation canals may be influenced by seasonal variations in temperature sufficient to influence the water accounting of conveyed surface flows.
We used automatic sound recorders to study spontaneous vocalizations of wild wolves during the pup-rearing season around rendezvous sites from 24 wolf packs in six study areas across North America, Asia, and Europe. Between 2018 and 2021, for a total of 1225 pack-days, we recorded 605 spontaneous wolf chorus howls and 224 solo-howl series. Howling occurrence varied across areas, from 12.50 to 94.12% days with howling. Daily howling ranged from 0.00 to 3.47 solo howls/day and 0.13 to 5.29 chorus howls/day. Generally, spontaneous chorus howls peaked between sunset and sunrise. Howling rate depended on area, pack size, and density of people living nearby, being greater where fewer people lived. High rates in Yellowstone National Park, (800,000+ visitors during the study) could reflect accommodation to human activities such as wolf watching. One to six automatic recorders per site within 1000 m of rendezvous sites needed 4–15 days to detect the pack (average 9.5) and 5–21 days (average 11.3) to detect pups, both with a probability of 95%. Our results may guide wolf-monitoring programs using automatic sound recorders, a promising method offering advantages over howling surveys, especially in human-dominated landscapes.
Despite substantial progress in understanding global biodiversity loss, major taxonomic and geographic knowledge gaps remain. Decision makers often rely on expert judgement to fill knowledge gaps, but are rarely able to engage with sufficiently large and diverse groups of specialists. To improve understanding of the perspectives of thousands of biodiversity experts worldwide, we conducted a survey and asked experts to focus on the taxa and freshwater, terrestrial, or marine ecosystem with which they are most familiar. We found several points of overwhelming consensus (for instance, multiple drivers of biodiversity loss interact synergistically) and important demographic and geographic differences in specialists’ perspectives and estimates. Experts from groups that are underrepresented in biodiversity science, including women and those from the Global South, recommended different priorities for conservation solutions, with less emphasis on acquiring new protected areas, and provided higher estimates of biodiversity loss and its impacts. This may in part be because they disproportionately study the most highly threatened taxa and habitats.
","language":"English","publisher":"Wiley","doi":"10.1002/fee.2536","usgsCitation":"Isbell, F., Balvanera, P., Mori, A.S., He, J., Bullock, J.M., Regmi, G.R., Seabloom, E.W., Ferrier, S., Sala, O.E., Guerrero-Ramirez, N.R., Tavella, J., Larkin, D.J., Schmid, B., Outhwaite, C.L., Pramua, P., Borer, E.T., Loreau, M., Omotoriogun, T.C., Obura, D.O., Anderson, M., Portales-Reyes, C., Kirkman, K., Vergara, P.M., Clark, A.T., Komatsu, K.J., Petchey, O.L., Weiskopf, S.R., Williams, L.J., Collins, S., Eisenhauer, N., Trisos, C.H., Renard, D., Wright, A.J., Tripathi, P., Cowles, J., Byrnes, J.E., Reich, P.B., Purvis, A., Sharip, Z., O’Connor, M.I., Kazanski, C.E., Haddad, N.M., Soto, E.H., Dee, L.E., Díaz, S., Zirbel, C., Avolio, M.L., Wang, S., Ma, Z., Liang, J., Farah, H.C., Johnson, J.A., Miller, B.W., Hautier, Y., Smith, M.D., Knops, J., Myers, B., Harmáčková, Z., Cortes, J., Harfoot, M., Gonzalez, A., Newbold, T., Oehri, J., Mazon, M., Dobbs, C., and Palmer, M., 2023, Expert perspectives on global biodiversity loss and its drivers and impacts on people: Frontiers in Ecology and the Environment, v. 21, no. 2, p. 94-103, https://doi.org/10.1002/fee.2536.","productDescription":"10 p.","startPage":"94","endPage":"103","ipdsId":"IP-124429","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":445488,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.2536","text":"Publisher Index Page"},{"id":404110,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Isbell, Forest 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Withdrawal Structure in Lake Billy Chinook, Oregon, 2021","title":"Evaluation of fish behavior at the entrances to a Selective Water Withdrawal structure in Lake Billy Chinook, Oregon, 2021","docAbstract":"Imaging sonar was used to assess the behavior, abundance, and timing of fish at the entrances to the Selective Water Withdrawal (SWW) intake structure located in the forebay of Round Butte Dam, Oregon during the spring of 2021. The purposes of the SWW are (1) to direct surface currents in the forebay to attract and collect downriver migrating juvenile salmonid smolts (Chinook salmon [Oncorhynchus tshawytscha], sockeye salmon [O. nerka], and steelhead [O. mykiss]) from Lake Billy Chinook and (2) to enable operators of the SWW to withdraw water from surface and benthic elevations in the reservoir to manage downriver water temperatures. Part of the evaluation, to determine how well the structure performs at collecting juvenile salmonids, needs (A) to regularly assess how fish are approaching the entrance, and (B) to determine if operational flows could be optimized to increase the attraction of smolts present in the forebay of Lake Billy Chinook. The primary goals of this study were (1) to assess the abundance and behaviors of smolt-size fish observed near the SWW and (2) to provide data of the effect of two-night generation operation timing conditions on movements and behaviors of fish near the entrance to the SWW structure. The purpose of this assessment is to improve downstream passage solutions.
Two imaging sonar units were deployed during the spring 2021 smolt out-migration period. One unit monitored fish movements near the south entrance and one unit monitored movements near the north entrance of the SWW. Both smolt and bull trout (Salvelinus confluentus)-size fish were regularly observed near the entrances with greater abundances observed during night, corresponding with greater discharge through the SWW than during the day when discharge was reduced. Differences in fish abundance were observed between the night generation operation timing conditions, with increased fish counts observed when elevated discharge was extended to 6:00 a.m., rather than when discharges have been traditionally reduced in the early morning at 4:00 a.m. Fish of all size groups were primarily observed near the center of the SWW, and greater abundances of fish were observed at the south entrance. Increased counts of bull trout-size fish coincided with the increased abundances of smolt-size fish. Overall, the results indicate that (A) smolt-size fish were more abundant near the entrance of the SWW during periods of increased discharge, (B) bull trout-size fish were present at the SWW, and (C) fish were more numerous at the SWW when night generation operation timing was extended later into the morning hours rather than the traditional operation timing flow reduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221098","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., and Hatton, T.W., 2022, Evaluation of fish behavior at the entrances to a Selective Water Withdrawal structure in Lake Billy Chinook, Oregon, 2021: U.S. Geological Survey Open-File Report 2022–1098, 28 p., https://doi.org/10.3133/ofr20221098.","productDescription":"viii, 28 p.","onlineOnly":"Y","ipdsId":"IP-139510","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409425,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1098/images"},{"id":409424,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221098/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1098"},{"id":409423,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1098/ofr20221098.pdf","text":"Report","size":"36.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1098"},{"id":409422,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1098/coverthb.jpg"},{"id":409426,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1098/ofr20221098.XML"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Billy Chinook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.5557866634069,\n 44.75388913871075\n ],\n [\n -121.5557866634069,\n 44.38885839267408\n ],\n [\n -121.07886358532556,\n 44.38885839267408\n ],\n [\n -121.07886358532556,\n 44.75388913871075\n ],\n [\n -121.5557866634069,\n 44.75388913871075\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Helminth infections are cryptic and can be difficult to study in wildlife species. Helminth research in wildlife hosts has historically required invasive animal handling and necropsy, while results from noninvasive parasite research, like scat analysis, may not be possible at the helminth species or individual host levels. To increase the utility of noninvasive sampling, individual hosts can be identified by applying molecular methods. This allows for longitudinal sampling of known hosts and can be paired with individual-level covariates. Here we evaluate a combination of methods and existing long-term monitoring data to identify patterns of cestode infections in gray wolves in Yellowstone National Park. Our goals were: (1) Identify the species and apparent prevalence of cestodes infecting Yellowstone wolves; (2) Assess the relationships between wolf biological and social characteristics and cestode infections; (3) Examine how wolf samples were affected by environmental conditions with respect to the success of individual genotyping. We collected over 200 wolf scats from 2018–2020 and conducted laboratory analyses including individual wolf genotyping, sex identification, cestode identification, and fecal glucocorticoid measurements. Wolf genotyping success rate was 45%, which was higher in the winter but decreased with higher precipitation and as more time elapsed between scat deposit and collection. One cestode species was detected in 28% of all fecal samples, and 38% of known individuals. The most common infection was Echinococcus granulosus sensu lato (primarily E. canadensis). Adult wolves had 4x greater odds of having a cestode infection than pups, as well as wolves sampled in the winter. Our methods provide an alternative approach to estimate cestode prevalence and to linking parasites to known individuals in a wild host system, but may be most useful when employed in existing study systems and when field collections are designed to minimize the time between fecal deposition and collection.
Multispecies risk assessments have developed within many international conservation programs, reflecting a widespread need for efficiency. Under the United States Endangered Species Act (ESA), multispecies assessments ultimately lead to species-level listing decisions. Although this approach provides opportunities for improved efficiency, it also risks overwhelming or biasing the assessment process and would benefit from clear guidance for practitioners. We reviewed multispecies assessments conducted between 1993 and 2019 for ESA listing decisions to identify the ecological basis for combining species, the assessment approach used, and the policy factors influencing their efficacy. We identified 42 cases covering 359 species. Most assessments (81%) included two to five species, although the maximum was 82. A common theme involved grouping narrow endemics or habitat specialists based on taxonomic relatedness, similar distributions, and common threats to persistence. All assessments included a combined threats analysis, but few employed a common species' response model or expert elicitation process. Although ESA risk assessments are distinct from policy decisions, most assessments (50%) supported decisions that all species warranted endangered status. Available guidance has generally emphasized ecological similarity as the key attribute leading to successful multispecies assessments. The challenge with consistently selecting species based on qualitative proxies such as common distributions or threats to persistence is that ecological patterns and processes are scale dependent. Focusing instead on the assessment methods and their potential for bias and increased efficiency may provide a stronger basis for developing consistent and transparent guidance.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12825","usgsCitation":"Fitzgerald, D.B., Freeman, M., Maloney, K.O., Young, J.A., Rosenberger, A.E., Kazyak, D., and Smith, D.R., 2022, Multispecies approaches to status assessments in support of endangered species classifications: Conservation Science and Practice, v. 4, no. 11, e12825, 11 p., https://doi.org/10.1111/csp2.12825.","productDescription":"e12825, 11 p.","ipdsId":"IP-127956","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12825","text":"Publisher Index Page"},{"id":408261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzgerald, Daniel Bruce 0000-0002-3254-7428","orcid":"https://orcid.org/0000-0002-3254-7428","contributorId":245718,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Daniel","email":"","middleInitial":"Bruce","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":854455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854458,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854459,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854460,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70235865,"text":"sir20175070C - 2022 - Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota—Water resources","interactions":[{"subject":{"id":70235865,"text":"sir20175070C - 2022 - Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota—Water resources","indexId":"sir20175070C","publicationYear":"2022","noYear":false,"chapter":"C","displayTitle":"Potential Effects of Energy Development on Environmental Resources of the Williston Basin in Montana, North Dakota, and South Dakota—Water Resources","title":"Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota—Water resources"},"predicate":"IS_PART_OF","object":{"id":70191166,"text":"sir20175070 - 2022 - Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota","indexId":"sir20175070","publicationYear":"2022","noYear":false,"title":"Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota"},"id":1}],"isPartOf":{"id":70191166,"text":"sir20175070 - 2022 - Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota","indexId":"sir20175070","publicationYear":"2022","noYear":false,"title":"Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota"},"lastModifiedDate":"2026-04-01T15:49:03.755037","indexId":"sir20175070C","displayToPublicDate":"2022-09-13T06:05:15","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5070","chapter":"C","displayTitle":"Potential Effects of Energy Development on Environmental Resources of the Williston Basin in Montana, North Dakota, and South Dakota—Water Resources","title":"Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota—Water resources","docAbstract":"The Williston Basin has been a leading oil and gas producing area for more than 50 years. While oil production initially peaked within the Williston Basin in the mid-1980s, production rapidly increased in the mid-2000s, largely because of improved horizontal (directional) drilling and hydraulic fracturing methods. In 2012, energy development associated with the Bakken Formation was identified as a priority requiring collaboration toward improved timeliness of issuing permits for new wells combined with reasonable measures to maintain environmental quality. Shortly thereafter, the Bakken Federal Executive Group was created to address common challenges associated with energy development. The Bakken Federal Executive Group partner agencies identified a gap in current understanding of the cumulative environmental challenges attributed to energy development throughout the area, resulting in an effort to aggregate scientific data and identify additional research and information needs related to natural resources within areas of energy development in the Williston Basin. As part of this effort, water resources in the area (including groundwater; streams and rivers; and lakes, reservoirs, and wetlands) were characterized and described in terms of physical occurrence, flow characteristics, recharge, water quality, and water use. Similarly, waters produced during energy-development activities also were characterized even though these waters are not considered usable resources within the area. Groundwater resources were characterized by the major hydrogeologic units, or aquifers, identifying the units that supply most groundwater used for domestic, stock, agricultural, and industrial purposes. The groundwater characterization included other deeper hydrogeologic units in the Williston Basin that may be a useable source of water with treatment, have utility as a reservoir for reinjection of produced waters, or be a source of minerals and energy resources. A generalized groundwater budget and flow system identifying the sources of recharge (stream infiltration, precipitation, and movement [leakage] from other aquifers) and the general groundwater flow direction is included for each of the major hydrogeologic units. Rivers and streams within the Williston Basin with 10 or more years of continuous streamflow data were identified. For a subset of these sites, streamflow characteristics, including the monthly and annual mean flow, were generated to identify seasonal and interannual changes in streamflow and thus provide information on the drivers and reliability of streamflow at the seasonal or multiyear scale. Daily streamflow and annual extreme flows (peak and low flow) also were estimated for the subset of sites. The daily streamflow and annual extreme flow values provide information on short-term or extreme events that are relevant to infrastructure design and evaluating spills, leaks, or accidental discharges of water or petroleum products. Surface-water features (lakes, ponds, and wetlands) were classified using the Cowardin system and identified on the National Wetlands Inventory maps generated by the U.S. Fish and Wildlife Service. The spatial distribution of the surface-water features was analyzed by State, county, and specifically in comparison to the Prairie Pothole Region. The proximity of the surface-water features to energy development infrastructure (specifically oil or gas well pads) was evaluated. It was determined that, although oil or gas wells are often near a surface-water feature, most surface-water features do not have wells nearby, with the exception of wells in the Prairie Pothole Region. Water-quality data were aggregated from two data sources: (1) the Water-Quality Portal, sponsored by the U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (EPA), and National Water Quality Monitoring Council; and (2) a data compilation completed as part of the USGS National Water-Quality Assessment project. The Water-Quality Portal integrates publicly available water-quality data from databases maintained by the USGS, EPA, and U.S. Department of Agriculture, including water-quality data from Tribal, State, and local databases. Water-quality data for 15 commonly measured water-quality constituents were aggregated for groundwater, rivers and streams, and lakes and reservoirs. For each aggregated dataset (groundwater, rivers and streams, and lakes and reservoirs), analyses of the water-quality data included summary statistics, maps of spatial distribution of constituent values, boxplots of constituent values by timeframe or hydrogeologic unit, spatial comparisons of site locations and constituent values to petroleum well density, and comparisons of the constituent values measured to EPA drinking-water standards/guidelines. Produced water includes all fluids brought to the surface along with the targeted hydrocarbons as part of the oil and gas exploration and extraction processes. These fluids may include formation water (waters that co-exist with rock/oil/gas), hydraulic fracturing fluids, and other combinations of water and chemicals used during oil and gas well drilling, development, treatments, recompletions, and workovers. Produced water datasets were aggregated from two sources: the USGS National Produced Waters Geochemical database (ver. 2.1) and a series of projects focused specifically on sampling produced water in the Williston Basin from 2010 to 2014. The National Produced Waters Geochemical database was useful for a general understanding of produced-water chemistry. Produced waters are characterized by extreme salinity and contain elevated concentrations of other constituents (including arsenic, barium, cadmium, lead, zinc, radium-226/radium-228, and ammonium) that could negatively affect water and aquatic resources if released. Produced waters also have a generally unique chemical (isotopic) signature that may be useful in tracking water from different geologic units; for example, the oxygen/deuterium and strontium ratio values measured in brine waters from the Bakken Formation are distinct from brines collected from other geologic units in the Williston Basin.
Water-use information related to energy production in the area also was aggregated and summarized. The summary of water use is not limited to oil and gas production but includes water used to produce all types of energy resources in the Williston Basin, including coal/lignite, thermoelectric power, oil and gas, hydropower, biomass and biofuels, wind, geothermal, and solar. Each State has its own methods for regulating and reporting water usage within its jurisdiction. These methods can introduce problems when examining water use from sources, such as the Missouri River or Fox Hills aquifer, that are shared across political boundaries. Without the one-to-one match for usage types and amounts used from a water source, it is difficult to develop a comprehensive water budget for the water source being evaluated. A large amount of freshwater is required to prepare a well for oil and gas well production; in some cases, 3 to 7 million gallons of water are needed per well. The EPA estimates that hydraulic fracturing in the Williston Basin uses between 70 to 140 billion gallons per year. Water also is used for myriad other purposes related to ancillary oil and gas extraction. In addition to water used for immediate energy development, the expanded human workforce migrating into the area and other support staff who have moved into the area during the development also use water.
Research and information needs were identified that could be relevant in the evaluation of the effects of energy development on water resources. Information needs related to the evaluation of groundwater resources include the following: improved potentiometric-surface maps for glacial units; availability of a uniform stream network digital geographic coverage that spans the international boundary with Canada; enhanced surface-water use information with regards to the gain and loss of streamflow to shallow groundwater, which would increase understanding groundwater and surface-water interactions; and expanded geophysical assessments. Gaps in the availability of streamflow data include the lack of information on ice-jam flooding despite potential for effects to infrastructure (pipelines, roads, and facilities) and an understanding of the cumulative effects of largely undocumented stock and diversion dams. Although this study resulted in the aggregation of a large quantity of water-quality data, the availability of consistently collected, systematically processed and reported data over large parts of the Williston Basin is sparse. Few samples have been analyzed for constituents that may indicate the effect of energy development on water resources. Constituents that could be considered include boron, chloride, bromide, iodine, fluoride, manganese, lithium, radium, strontium isotopes, volatile organic compounds, and isotopes of inorganic ions (such as hydrogen and carbon). Collaboration between Tribal, Federal, State, and local entities to identify a common study design, common monitoring constituents, and consistent sampling locations would generate datasets with broad utility and would likely result in overall cost savings for monitoring over time. Similarly, there is a need for standardized sample collection, processing, laboratory analytical methods, and the collection of ancillary data for produced waters sampling. Additional characterization of the range of chemical, microbial, and isotopic compositions and quantities of “end-member” produced waters, and the collection of time-series datasets to document the changes in produced waters during and after well development also were needs identified during this study. Water-use estimates would be improved through the implementation of comprehensive studies of water use from groundwater and surface-water sources using consistent methodologies across the Williston Basin. The submission of chemical and water data related to hydraulic fracturing collected by the oil and gas industry would add to the quantity of available data. Consistent implementation of regulations and monitoring controls across political boundaries (State, county, and international) would further improve the consistency of data available for the estimates of water use.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Potential Effects of Energy Development on Environmental Resources of the Williston Basin in Montana, North Dakota, and South Dakota","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175070C","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Bartos, T.T., Sando, S.K., Preston, T.M., Delzer, G.C., Lundgren, R.F., Nustad, R.A., Caldwell, R.R., Peterman, Z.E., Smith, B.D., Macek-Rowland, K.M., Bender, D.A., Frankforter, J.D., and Galloway, J.M., 2022, Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota—Water resources (ver. 1.1, October 2022): U.S. Geological Survey Scientific Investigations Report 2017–5070–C, 159 p., https://doi.org/10.3133/sir20175070C.","productDescription":"Report: xv, 159 p.; 1 Figure: 8.50 × 11.00 inches; Data Release","numberOfPages":"180","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082945","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":405463,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5070/c/coverthb2.jpg"},{"id":408159,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5070/c/sir20175070c.pdf","text":"Report","size":"25.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5070–C"},{"id":408160,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5070/c/versionHist.txt","text":"Version History","size":"2.88 kB","linkFileType":{"id":2,"text":"txt"}},{"id":405466,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77080B9","text":"USGS data release","linkHelpText":"Results of water resource data aggregations within areas of energy development in the Williston Basin in Montana, North Dakota, and South Dakota"},{"id":501945,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113506.htm","linkFileType":{"id":5,"text":"html"}},{"id":405465,"rank":2,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2017/5070/c/sir20175070c_fig09.pdf","text":"Figure 9 (layered)","size":"5.97 MB","linkFileType":{"id":1,"text":"pdf"}}],"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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.5,\n 45.120052841530544\n ],\n [\n -96.94335937499999,\n 45.120052841530544\n ],\n [\n -96.94335937499999,\n 49.009050809382046\n ],\n [\n -108.5,\n 49.009050809382046\n ],\n [\n -108.5,\n 45.120052841530544\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: September 13, 2022; Version 1.1: October 18, 2022","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Malheur Lake is a large, shallow, turbid lake in southeastern Oregon that fluctuates widely in surface area in response to yearly precipitation and climatic cycles. High suspended-sediment concentrations (SSCs) likely are negatively affecting the survival of aquatic plants by reducing the intensity of solar radiation reaching the plants, thus inhibiting photosynthesis. This study was designed to determine the types of suspended material, the erodibility of the lakebed, the attenuation of photosynthetically active radiation (PAR) through the water column, and the effects of wind and precipitation on SSC.
Two sites in the lake were monitored for approximately 5 months during the summer growing season each year (2017–19). At these sites, turbidity, chlorophyll a fluorescence (a surrogate for concentration), and underwater PAR measurements were collected continuously, and discrete samples were collected every 2 weeks and analyzed for SSC, loss on ignition, and chlorophyll a concentration. Underwater PAR profile measurements were collected during site visits, and a nearby meteorological station recorded terrestrial PAR and wind speeds.
About 18 percent of suspended material in the water was organic and mostly detrital. Nearly 100 percent of all suspended material was fine material (less than 63 micrometers), and more than 90 percent of the surficial lakebed material was fine material. The high concentrations of fine material in the water column can be expected to strongly attenuate light.
SSC was significantly higher at both sites in 2018 compared to 2017 and 2019; the interannual differences were mostly due to the lower amount of precipitation in 2018, which resulted in shallower lake depths. Three years of SSC values multiplied by water depth showed a seasonal pattern: concentrations were often highest in early spring, lowest in summer, and intermediate in autumn.
Episodic wind events with speeds of 5–10 meters per second caused rapid increases in turbidity above background that lasted for a few days. However, a baseline SSC value multiplied by water depth (estimated to be 0.11 kilograms per square meter) was present between wind events and even under ice, suggesting a persistent suspension of very fine, highly erodible material. Terrestrial and underwater PAR measurements were used to develop a relation between PAR attenuation and turbidity that can be used in modeling restoration scenarios. Calculated bottom shear stress caused by wind-generated waves ranged from 0 to 0.4 pascals (Pa). Erosion experiments indicated variability in the bottom sediments from the two lake sites, but much of the lakebed is highly erodible at a threshold of 0.05 to 0.1 Pa.
Restoration actions may target the persistent turbidity (for example, the use of flocculation) or transient turbidity (for example, construction of wave-reduction barriers), with a goal of attaining approximately 36 micromoles photons per square meter per second of PAR at the lakebed to promote emergence of sago pondweed and other desirable plants. Currently, that threshold often is reached from 4 to 34 centimeters (cm) below the water surface in 1 meter water depth, depending on wind conditions, but halving persistent turbidity would increase the upper end of the range to 55 cm. Additional studies regarding the effects of (1) sediment drying on resuspension and (2) nutrient inputs and internal cycling on phytoplankton populations would help determine the most appropriate restoration strategies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225056","usgsCitation":"Wood, T.M., and Smith, C.D., 2022, Light attenuation and erosion characteristics of fine sediments in a highly turbid, shallow, Great Basin Lake—Malheur Lake, Oregon, 2017–18: U.S. Geological Survey Scientific Investigations Report 2022–5056, 51 p., https://doi.org/10.3133/sir20225056.","productDescription":"Report: x, 51 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-123319","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":503371,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113310.htm","linkFileType":{"id":5,"text":"html"}},{"id":404302,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5056/sir20225056.XML"},{"id":404301,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5056/images"},{"id":404298,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225056/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5056"},{"id":404296,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5056/coverthb.jpg"},{"id":404297,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5056/sir20225056.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5056"},{"id":404299,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92ZBWJ5","text":"USGS data release","description":"USGS data release","linkHelpText":"Phytoplankton data for Malheur Lake, Oregon, 2018-20"},{"id":404300,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95FMN8F","text":"USGS data release","description":"USGS data release","linkHelpText":"Photosynthetically active radiation measurements collected at Malheur Lake, Oregon, 2017-18"}],"country":"United States","state":"Oregon","otherGeospatial":"Malheur Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.08218383789062,\n 43.113014204188914\n ],\n [\n -118.42300415039062,\n 43.113014204188914\n ],\n [\n -118.42300415039062,\n 43.49178653083377\n ],\n [\n -119.08218383789062,\n 43.49178653083377\n ],\n [\n -119.08218383789062,\n 43.113014204188914\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 92701
In this study we examine the potential effects of three predicted sea level rise (SLR) scenarios on the nearshore eelgrass (Zostera marina L.) and surf smelt (Hypomesus pretiosus) spawning habitats along a beach on Bainbridge Island, Washington. Baseline bathymetric, geomorphological, and biological surveys were conducted to determine the existing conditions at the study site. The results of these surveys were coupled with a predictive model that estimates SLR-induced changes to coastal ecosystems based upon local topography and land-cover data. This model simulates the changes in nearshore habitat through time. The model inputs for SLR are probable values reported by the Intergovernmental Panel on Climate Change, and by user-defined values. The predicted effects of SLR are presented as (1) habitat type change and (2) the graphic response of developed dry land depicting the influence of shoreline armoring. This report describes the geophysical and biological characteristics at the Bainbridge Island study site, the modeling methods used to produce depictions of habitat changes, and a possible decrease in surf smelt spawning and an increase in eelgrass habitat availability in response to increases in sea level.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221054","usgsCitation":"Smith, C.D., and Liedtke, T.L., 2022, Potential effects of sea level rise on nearshore habitat availability for surf smelt (Hypomesus pretiosus) and eelgrass (Zostera marina), Puget Sound, Washington: U.S. Geological Survey Open-File Report 2022–1054, 17 p., https://doi.org/10.3133/ofr20221054.","productDescription":"Report: v, 17 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-117971","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":402574,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGJ3ZH","text":"USGS data release","description":"USGS Data Release.","linkHelpText":"Data collected in 2010 to evaluate habitat availability for surf smelt and eelgrass in response to sea level rise on Bainbridge Island, Puget Sound, Washington State, USA"},{"id":402572,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1054/coverthb.jpg"},{"id":402573,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1054/ofr20221054.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1054"},{"id":402619,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221054/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1054"},{"id":402575,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1054/images"},{"id":402576,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1054/ofr20221054.XML"},{"id":501780,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113219.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6678466796875,\n 47.487513008956554\n ],\n [\n -122.23937988281251,\n 47.487513008956554\n ],\n [\n -122.23937988281251,\n 47.964180715412276\n ],\n [\n -122.6678466796875,\n 47.964180715412276\n ],\n [\n -122.6678466796875,\n 47.487513008956554\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Environmental (e)DNA tools are sensitive and cost-effective for early detection of invasive species. However, the uncertainty associated with the interpretation of positive eDNA detections makes it challenging to determine appropriate natural resource management responses. Multiple sources of error can give rise to positive detections of eDNA in a sample when individuals of that species are not present at the site or a widespread infestation is not imminent. Acting on an erroneous eDNA inference could result in needless costs or reductions in desirable resources. Alternatively, failure to rapidly act on eDNA results that truly indicate invader presence could compound negative impacts and lead to high, long-term costs to manage infestations. We used a structured decision making (SDM) process, which incorporates tradeoffs and uncertainties, to evaluate appropriate response actions following hypothetical eDNA detections of invasive dreissenid mussel (Dreissena spp.) eDNA in Jordanelle Reservoir, Utah (USA). We worked with decision-makers and stakeholders to identify objectives and discrete management action alternatives to assess consequences and tradeoffs. Alternatives ranged from no action to intensive and expensive control efforts. The best performing alternative was delayed containment described by immediate attempts to confirm the eDNA detections using non-molecular sampling techniques followed by mandatory watercraft exit inspections to prevent dreissenid mussel spread to regional water bodies. Non-molecular sampling increased public support for management by demonstrating a commitment to monitor the invasion state before action, whereas containment decreased likelihood of regional spread to other waters. Delayed containment had the lowest downside risk, and the highest upside gains relative to other alternative actions. Sensitivity analyses showed our results to be robust to parameter and outcome uncertainty.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2022.13.2.06","usgsCitation":"Sepulveda, A., Smith, D.R., O'Donnell, K., Owens, N., White, B., Richter, C.A., Merkes, C.M., Wolf, S., Rau, M., Neilson, M., Daniel, W., Dumoulin, C.E., and Hunter, M., 2022, Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA: Management of Biological Invasions, v. 13, no. 2, p. 344-368, https://doi.org/10.3391/mbi.2022.13.2.06.","productDescription":"25 p.","startPage":"344","endPage":"368","ipdsId":"IP-133646","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447583,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2022.13.2.06","text":"Publisher Index Page"},{"id":435831,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y2IQTS","text":"USGS data release","linkHelpText":"Predicted consequences of detecting dreissenid mussel eDNA in Jordanelle Reservoir Utah, 2021"},{"id":408476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Adam 0000-0001-7621-7028 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Mike","contributorId":297993,"corporation":false,"usgs":false,"family":"Rau","given":"Mike","email":"","affiliations":[],"preferred":false,"id":854804,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Neilson, Matthew 0000-0002-5139-5677","orcid":"https://orcid.org/0000-0002-5139-5677","contributorId":219310,"corporation":false,"usgs":true,"family":"Neilson","given":"Matthew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":854806,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Daniel, Wesley M. 0000-0002-7656-8474","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":219320,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":854805,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dumoulin, Christine E. 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