Estimating the magnitude of historical earthquakes is crucial for assessing seismic hazard. Magnitudes of early‐instrumental earthquakes can be inferred using a combination of instrumental records, field observations, and the observed distribution of shaking intensity determined from macroseismic observations. For earthquakes before 1900, shaking intensity distributions often provide the only information to constrain earthquake magnitude. Considerable effort has been made to develop methods to estimate the magnitude of moderate‐to‐large historical earthquakes using shaking intensities derived from macroseismic data. In this study, we consider earthquakes in California with known instrumental magnitudes to explore uncertainties in estimating the magnitude of historical earthquakes from intensity information alone. We use three California‐specific intensity prediction equations (IPEs) and an IPE based on a global ground‐motion model (GMM) to determine optimum intensity‐based magnitudes for 33 moderate‐to‐large California earthquakes between 1979 and 2021. Intensity‐based magnitudes are close to instrumental magnitudes on average. However, intensity‐based magnitudes for individual events differ by as much as 2.2 magnitude units from instrumental magnitudes. This result reflects the weak dependence of ground motions and shaking intensities on moment magnitude and their strong dependence on stress drop. Considering the intensity distributions of the 1906 San Francisco and 1989 Loma Prieta earthquakes, we show that information that could constrain rupture length is discarded when considering only the 2D decay of intensity with distance. We also show that ground‐motion intensity conversion equations used in a GMM‐based approach may cause a systematic overestimation of large historical earthquake magnitudes. This study underscores both the reducible and potentially irreducible uncertainties associated with using intensity data to estimate magnitudes of historical earthquakes using IPEs and highlights the value of using additional information to constrain rupture dimensions. Using intensity observations alone, moment magnitude uncertainties are typically on the order of a full unit.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220230030","usgsCitation":"Lucas, M.C., Hough, S.E., Stein, S., Salditch, L.M., Gallahue, M.M., Neely, J.S., and Abrahamson, N., 2023, Uncertainties in intensity-based earthquake magnitude estimates: Seismological Research Letters, v. 94, no. 5, p. 2202-2214, https://doi.org/10.1785/0220230030.","productDescription":"13 p.","startPage":"2202","endPage":"2214","ipdsId":"IP-153047","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"94","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Lucas, Madeleine C.","contributorId":263451,"corporation":false,"usgs":false,"family":"Lucas","given":"Madeleine","email":"","middleInitial":"C.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stein, Seth","contributorId":263457,"corporation":false,"usgs":false,"family":"Stein","given":"Seth","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927609,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salditch, Leah Marschall 0000-0002-4478-1836","orcid":"https://orcid.org/0000-0002-4478-1836","contributorId":297144,"corporation":false,"usgs":true,"family":"Salditch","given":"Leah","email":"","middleInitial":"Marschall","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927610,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gallahue, Molly M.","contributorId":263448,"corporation":false,"usgs":false,"family":"Gallahue","given":"Molly","email":"","middleInitial":"M.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927611,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neely, James S.","contributorId":263454,"corporation":false,"usgs":false,"family":"Neely","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927612,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Abrahamson, Norman A.","contributorId":45202,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norman A.","affiliations":[{"id":13174,"text":"Pacific Gas & Electric","active":true,"usgs":false}],"preferred":false,"id":927613,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70244155,"text":"sir20235036 - 2023 - Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","interactions":[],"lastModifiedDate":"2026-03-06T21:18:08.428516","indexId":"sir20235036","displayToPublicDate":"2023-06-21T07:56:13","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5036","displayTitle":"Simulation of Future Streamflow and Irrigation Demand Based on Climate and Urban Growth Projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","title":"Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","docAbstract":"Water resources in the coastal region of North Carolina and South Carolina (Coastal Carolinas) are currently under stress from competing ecological and societal needs. Projected changes in climate and population are expected to place even more stress on water resources in the region. The Coastal Carolinas Focus Area Study was initiated by the U.S. Geological Survey Water Availability and Use Science Program’s National Water Census to investigate these stressors and their effects on water resources for the Coastal Carolinas. As part of that study, the Soil and Water Assessment Tool (SWAT) model was used to investigate future streamflow and irrigation demand under six scenarios for the Cape Fear and Pee Dee River Basins, which flow through the Coastal Carolinas and into the Atlantic Ocean.
For each river basin, historical (2000 through 2014) Soil and Water Assessment Tool models were minimally calibrated, and future (2055 through 2065) scenario models were developed based on three alternative global climate models, two alternative urban growth projections, and water-use projections that correspond to each global climate model and urban growth projection pair. The river basins were delineated into 2,928 and 5,678 subbasins for the Cape Fear and Pee Dee, respectively, each approximately 2.6 square miles (mi2) in size. The best available water-use and wastewater discharge data were used for historical model calibration. The models simulated monthly mean streamflow with median Nash-Sutcliffe efficiency values of 0.53 (n = 36) and 0.61 (n = 33) in the Cape Fear and Pee Dee River Basins, respectively. Average percent bias was −4.8 percent for the Cape Fear River Basin and −1.2 percent for the Pee Dee River Basin. Catchments for streamgages chosen for model calibration that were small (less than 100 mi2) to medium (100–1,000 mi2) in area tended to perform better than larger catchments (greater than 1,000 mi2).
Historical models were used to develop future model scenarios by replacing historical weather, land-use, and water-use input datasets with projected datasets. One small, gaged catchment was selected to illustrate how the models can be used to evaluate the relative differences in simulated streamflow resulting from alternative global climate models and urban growth projections. For the selected catchment, future climate projections had a much greater influence on simulated streamflow than urban growth projections. Simulated cumulative monthly mean streamflow results for this catchment differed by 26 percent under alternative global climate models and differed by 2.4 percent under alternative urban growth projections.
Irrigation demand was modeled for subbasins with cropland. Simulated differences in irrigation demand were more pronounced and widespread across the model domain under the alternative future climate scenarios compared to alternative urban growth scenarios.
The calibrated and future scenario models have the capability to run on a daily time step and simulate streamflow and irrigation demand for thousands of small subbasins in the Cape Fear and Pee Dee River Basins. The models and underlying datasets enable future analyses for large and small areas within the basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235036","issn":"2328-0328","programNote":"Water Availability and Use Science Program","usgsCitation":"Gurley, L.N., García, A.M., Pfeifle, C.A., and Sanchez, G.M., 2023, Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65: U.S. Geological Survey Scientific Investigations Report 2023–5036, 23 p., https://doi.org/10.3133/sir20235036.","productDescription":"Report: viii, 23 p.; 2 Data Releases","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-118241","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":417754,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P951VE5P","text":"USGS Data Release—Soil and Water Assessment Tool (SWAT) models for the Pee Dee River Basin used to simulate future streamflow and irrigation demand based on climate and urban growth projections"},{"id":417749,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5036/sir20235036.pdf","size":"12.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5036"},{"id":500906,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114934.htm","linkFileType":{"id":5,"text":"html"}},{"id":417753,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98PVDBW","text":"USGS Data Release—Soil and Water Assessment Tool (SWAT) models for the Cape Fear River Basin used to simulate future streamflow and irrigation demand based on climate and urban growth projections"},{"id":417752,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5036/images/"},{"id":417751,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235036/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5036 HTML"},{"id":417750,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5036/sir20235036.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5036 XML"},{"id":417748,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5036/coverthb.jpg"}],"country":"United States","state":"North Carolina, South Carolina","otherGeospatial":"Cape Fear and Pee Dee River Basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.57121892850378,\n 32.91032390352079\n ],\n [\n -79.1296411830063,\n 33.177656538712625\n ],\n [\n -78.78619182539771,\n 33.72348311575605\n ],\n [\n -77.91939106571822,\n 33.920494939888584\n ],\n [\n -77.52687751416516,\n 34.40766001221573\n ],\n [\n -76.77455987368852,\n 35.02604160967191\n ],\n [\n -78.54904822133423,\n 36.169665661169745\n ],\n [\n -79.23594693655193,\n 36.51875607367013\n ],\n [\n -80.06186086794473,\n 36.51218395574713\n ],\n [\n -81.09220894077154,\n 36.66976065554749\n ],\n [\n -81.87723604387764,\n 35.792485806453826\n ],\n [\n -80.6996953892185,\n 34.985853498019594\n ],\n [\n -80.79782377710687,\n 34.42115219807647\n ],\n [\n -80.72422748619073,\n 33.5123831107352\n ],\n [\n -79.57121892850378,\n 32.91032390352079\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"For more information about this publication, contact
Program Coordinator
U.S. Geological Survey
Water Availability and Use Science Program
National Water Quality Program
Email: wausp-info@usgs.gov
For additional information, visit
https://www.usgs.gov/programs/national-water-quality-program
How to identify the drivers of population connectivity remains a fundamental question in ecology and evolution. Answering this question can be challenging in aquatic environments where dynamic lake and ocean currents coupled with high levels of dispersal and gene flow can decrease the utility of modern population genetic tools. To address this challenge, we used RAD-Seq to genotype 959 yellow perch (Perca flavescens), a species with an ~40-day pelagic larval duration (PLD), collected from 20 sites circumscribing Lake Michigan. We also developed a novel, integrative approach that couples detailed biophysical models with eco-genetic agent-based models to generate “predictive” values of genetic differentiation. By comparing predictive and empirical values of genetic differentiation, we estimated the relative contributions for known drivers of population connectivity (e.g., currents, behavior, PLD). For the main basin populations (i.e., the largest contiguous portion of the lake), we found that high gene flow led to low overall levels of genetic differentiation among populations (FST = 0.003). By far the best predictors of genetic differentiation were connectivity matrices that were derived from periods of time when there were strong and highly dispersive currents. Thus, these highly dispersive currents are driving the patterns of population connectivity in the main basin. We also found that populations from the northern and southern main basin are slightly divergent from one another, while those from Green Bay and the main basin are highly divergent (FST = 0.11). By integrating biophysical and eco-genetic models with genome-wide data, we illustrate that the drivers of population connectivity can be identified in high gene flow systems.
Introduction: Animal movements are influenced by landscape features; disturbances to the landscape can alter movements, dispersal, and ultimately connectivity among populations. Faster or longer movements adjacent to a localized disturbance or within disturbed areas could indicate reduced habitat quality whereas slower or shorter movements and reduced movements may indicate greater availability of resources. The Mojave desert tortoise (Gopherus agassizii) is a threatened species that is challenged by anthropogenic disturbances.
Methods: We studied tortoise movements using Global Positioning System (GPS) loggers at multiple sites in the Mojave Desert of Nevada and California. Tortoises at our sites encountered localized, linear human infrastructure, including paved roads, dirt roads, and fences, as well as landscape-scale disturbances [wildfire, off highway vehicle use (OHV), livestock grazing area]. We fit two-state (moving and encamped) Hidden Markov models to GPS logger data to infer how tortoise movement behavior relates to anthropogenic and natural features.
Results: We found that temporal covariates, individual-level random effects (intercepts), and sex best explained state transition probability in all sites. We compared relationships between tortoise movement and linear disturbances, which varied depending on site and context. Tortoises made longer movements within the OHV recreation area, near most dirt roads, and near a low-traffic paved road, indicating that tortoises avoid these habitat disturbances. Conversely, tortoises made shorter movements in areas of higher slope and near highways, suggesting that these features may restrict movement or provide resources that result in prolonged use (e.g., forage or drinking locations). Tortoises that encountered fences around utility-scale solar installations were more active and made longer movements near fences, indicative of pacing behavior.
Discussion: These results provide insight into how different disturbances alter tortoise movement behavior and modify tortoise habitat use, providing information that can be used to manage tortoise habitat.
","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2023.971337","usgsCitation":"Hromada, S.J., Esque, T., Vandergast, A.G., Drake, K.K., Chen, F., Gottsacker, B.O., Swart, J.A., and Nussear, K., 2023, Linear and landscape disturbances alter Mojave desert tortoise movement behavior: Frontiers in Ecology and Evolution, v. 11, 971337, 14 p., https://doi.org/10.3389/fevo.2023.971337.","productDescription":"971337, 14 p.","ipdsId":"IP-144743","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.971337","text":"Publisher Index Page"},{"id":418620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.85708110970195,\n 36.70940504207991\n ],\n [\n -116.85708110970195,\n 34.67613588087687\n ],\n [\n -114.55094165903384,\n 34.67613588087687\n ],\n [\n -114.55094165903384,\n 36.70940504207991\n ],\n [\n -116.85708110970195,\n 36.70940504207991\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Hromada, Steven J.","contributorId":245147,"corporation":false,"usgs":false,"family":"Hromada","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":876504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":876505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876506,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876507,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":876508,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gottsacker, Benjamin O 0000-0002-9481-6267","orcid":"https://orcid.org/0000-0002-9481-6267","contributorId":315424,"corporation":false,"usgs":true,"family":"Gottsacker","given":"Benjamin","email":"","middleInitial":"O","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876509,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swart, Jordan Andrew 0000-0002-3348-4721","orcid":"https://orcid.org/0000-0002-3348-4721","contributorId":315425,"corporation":false,"usgs":true,"family":"Swart","given":"Jordan","email":"","middleInitial":"Andrew","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876510,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nussear, Ken E","contributorId":221816,"corporation":false,"usgs":false,"family":"Nussear","given":"Ken E","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":876511,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70246266,"text":"70246266 - 2023 - Putting down roots: Afforestation and bank cohesion of Icelandic Rivers","interactions":[],"lastModifiedDate":"2023-11-07T15:07:54.763698","indexId":"70246266","displayToPublicDate":"2023-06-21T07:04:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Putting down roots: Afforestation and bank cohesion of Icelandic Rivers","docAbstract":"Riparian vegetation is widely recognized as a critical component of functioning fluvial systems. Human pressures on woody vegetation including riparian areas have had lasting effects, especially at high latitude. In Iceland, prior to human settlement, native downy birch woodlands covered approximately 15%–40% of the land area compared to 1%–2% today. Afforestation efforts include planting seedlings, protecting native forest remnants, and acquiring land areas as national forests. The planted and protected nature of vegetation along rivers within forests provides a unique opportunity to evaluate the various taxa within riparian zones and the channel stabilizing characteristics of the vegetation used in afforestation. We investigated bank properties, sediment textures, and root characteristics within riparian zones along four rivers in forests in Iceland. Bank sediment textures are dominantly sandy loam overlying coarser textures. Undercut banks are common because of erosion of the less cohesive subsurface layer. Quantitative root data indicate that the woody taxa have greater root densities, rooting depths, and more complex root structures than forbs or graminoids. The native downy birch has the highest root densities, with <1 mm roots most abundant. Modeling of added bank cohesion indicates that willow provides up to six times and birch up to four times more added cohesion to the coarse sediment textures comprising stream banks compared to no vegetation. We conclude that planting and protecting the native birch and willow helps to reduce bank erosion, especially where long-term grazing exclusion can be maintained.
A central focus of modern fisheries management is eradicating invaders that threaten imperiled native fishes. However, vast landscapes and limited funding and personnel resources demand a prioritized approach to management. Brook Stickleback Culaea inconstans (Kirtland, 1840) is an aquatic invasive species in Wyoming, USA, that may pose a risk to native biodiversity. Our aim was to evaluate Brook Stickleback’s invasive potential in the North Platte River drainage. We updated the current distribution of Brook Stickleback, evaluated for possible range expansion, and determined landscape-level habitat drivers and occurrence potential for streams across the North Platte River drainage. Additionally, we examined Brook Stickleback’s spatial overlap with native nongame fishes. At the landscape scale, Brook Stickleback preferred low-gradient streams with moderate disturbance risk. Though we did not find evidence of current Brook Stickleback range expansion 61% of streams in the drainage have landscape-level environmental characteristics that are likely suitable for Brook Stickleback, creating potential for future expansion. Brook Stickleback overlapped spatially with 13 native nongame species, though spatial overlap was less common than expected for species with similar habitat preferences. Our work serves as a case study of the factors to consider when assessing a species’ invasive potential in a previously unstudied region.
Management regimes on publicly owned freshwater wetlands in the Mississippi Flyway of North America (i.e., Flyway) have historically emphasized waterfowl, but there is limited information on how waterfowl-focused wetland management affects other wetland-dependent wildlife. Secretive marsh birds (SMBs) depend on wetlands with emergent vegetation throughout their migratory life cycle and often encounter vegetation and water conditions resulting from waterfowl-focused management regimes. Thus, there is a need for better understanding of how SMBs are affected by wetland management and the extent to which waterfowl-focused management regimes provide habitat for SMBs. In this review, we identify the vegetation and water conditions resulting from typical management objectives on freshwater emergent wetlands in the Flyway, review and qualitatively synthesize results from studies that directly evaluate how wetland management practices affect SMBs or their habitat, and assess how the vegetation and water conditions being produced for target species (mainly waterfowl) align with SMB habitat requirements. We searched online databases and used Google Scholar to locate peer-reviewed literature, technical reports, and graduate theses that pertained to responses of SMBs or their habitat to water-level manipulation, herbicide application, prescribed fire, disking, mowing, and planting crops. There are several management strategies that complement SMBs and waterfowl, such as reducing cover of woody species and providing flooded emergent vegetation. We also highlight management strategies that may not currently align with SMB life-cycle needs and suggest adjustments that might promote habitat for SMBs while still achieving waterfowl population objectives. For example, adjusting the dates and duration of spring water-level drawdowns on a portion of wetlands within a larger complex can provide for spring migrating waterfowl and ensure habitat for migrating and nesting SMBs. Ideally, future studies would address how modifications to management practices affect SMBs and monitor potential effects on waterfowl, resulting in a more holistic approach to wetland management.
The demography of, and factors that influence these metrics, are largely unknown for most vultures in the Americas. Survivorship of Turkey Vultures (Cathartes aura) may be influenced by landscape heterogeneity and human disturbance. We quantified the effects of landscape composition (Shannon’s diversity index) and configuration (contagion, edge density, and largest patch index), and human disturbance (road density) on the annual and seasonal survival probabilities of the three North American breeding populations (western, central, and eastern) of Turkey Vultures that spend the nonbreeding season in the southeastern portion of the Nearctic and the northern Neotropics during a 17-year period. We used Cox’s proportional hazards models with time-varying covariates to estimate spatial and temporal changes in survival rates of adult Turkey Vultures. Road density, but not landscape composition or configuration, influenced survival rates in space and time. Overall annual survival averaged 0.87 (95% confidence interval [CI]: 0.74–0.98). Mortality risk was low in western and central populations (hazard ratio < 1) but was 3.7 times greater for vultures in the eastern population. Survival during the breeding (0.97, 95% CI: 0.96–0.98) and outbound migration (1.0, 95% CI: 1–1) seasons was significantly higher than the other seasons. Average survival tended to be higher for nonbreeding (0.81, 95% CI: 0.71–0.88) compared to return migration (0.69, 95% CI: 0.56–0.81) seasons. The risk of mortality for all vulture populations increased with road density, and this was greater during the nonbreeding and return migration seasons. The spatial variation in road density across the Americas may generate a network of ecological traps for Turkey Vultures induced to stop in areas of greater road-kill abundance. Road-killed animals acting as an attractant for vultures can increase the occurrence of vulture–vehicle collisions and potentially aggravate human–wildlife conflicts. Further analyses are needed to address survivorship and mortality factors for young birds. Our results may help the implementation of specific mitigation efforts to reduce human–vulture conflicts and vulture mortality. For instance, concentrating efforts to remove road-killed animals in areas where road density is highest can likely reduce vulture–vehicle collisions and associated mortalities of these birds.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duad024","usgsCitation":"Naveda-Rodriguez, A., Bildstein, K.L., Barber, D.R., Therrien, J., Avery, M., Kluever, B., Rush, S.A., and Vilella, F., 2023, Turkey Vulture survival is reduced in areas of greater road density, v. 125, no. 4, duad024, 9 p., https://doi.org/10.1093/ornithapp/duad024.","productDescription":"duad024, 9 p.","ipdsId":"IP-149701","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":498061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duad024","text":"Publisher Index Page"},{"id":432157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Naveda-Rodriguez, Adrian","contributorId":340683,"corporation":false,"usgs":false,"family":"Naveda-Rodriguez","given":"Adrian","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":907452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bildstein, Keith L.","contributorId":150854,"corporation":false,"usgs":false,"family":"Bildstein","given":"Keith","email":"","middleInitial":"L.","affiliations":[{"id":18119,"text":"Hawk Mountain Sanctuary, Acopian Center for Conservation Learning","active":true,"usgs":false}],"preferred":false,"id":907453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barber, David R.","contributorId":340686,"corporation":false,"usgs":false,"family":"Barber","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":81649,"text":"Acopian Center for Conservation Science","active":true,"usgs":false}],"preferred":false,"id":907454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Therrien, Jean-Francois","contributorId":336846,"corporation":false,"usgs":false,"family":"Therrien","given":"Jean-Francois","email":"","affiliations":[{"id":80885,"text":"Université de Moncton, Moncton, NB, Canada","active":true,"usgs":false}],"preferred":false,"id":907455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Avery, Michael L.","contributorId":48890,"corporation":false,"usgs":true,"family":"Avery","given":"Michael L.","affiliations":[],"preferred":false,"id":907456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kluever, Bryan M.","contributorId":340689,"corporation":false,"usgs":false,"family":"Kluever","given":"Bryan M.","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":907457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rush, Scott A.","contributorId":92139,"corporation":false,"usgs":true,"family":"Rush","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":907458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vilella, Francisco 0000-0003-1552-9989 fvilella@usgs.gov","orcid":"https://orcid.org/0000-0003-1552-9989","contributorId":171363,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907459,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70245601,"text":"70245601 - 2023 - A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","interactions":[],"lastModifiedDate":"2023-06-26T13:27:30.871321","indexId":"70245601","displayToPublicDate":"2023-06-20T08:23:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"displayTitle":"A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","title":"A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","docAbstract":"Climate warming is rapidly altering Arctic ecosystems. Polar bears (Ursus maritimus) need sea ice as a platform from which to hunt seals, but increased sea-ice loss is lengthening periods when bears are without access to primary hunting habitat. During periods of food scarcity, survival depends on the energy that a bear has stored in body reserves, termed storage energy, making this a key metric in predictive models assessing climate change impacts on polar bears. Here, we developed a body composition model for polar bears that estimates storage energy while accounting for changes in storage tissue composition. We used data of dissected polar bears (n = 31) to link routinely collected field measures of total body mass and straight-line body length to the body composition of individual bears, described in terms of structural mass and two storage compartments, adipose and muscle. We then estimated the masses of metabolizable proteins and lipids within these storage compartments, giving total storage energy. We tested this multi-storage model by using it to predict changes in the lipid stores from an independent dataset of wild polar bears (n = 36) that were recaptured 8–200 days later. Using length and mass measurements, our model successfully predicted direct measurements of lipid changes via isotopic dilutions (root mean squared error of 14.5 kg). Separating storage into two compartments, and allowing the molecular composition of storage to vary, provides new avenues for quantifying energy stores of individuals across their life cycle. The multi-storage body composition model thus provides a basis for further exploring energetic costs of physiological processes that contribute to individual survival and reproductive success. Given bioenergetic models are increasingly used as a tool to predict individual fitness and population dynamics, our approach for estimating individual energy stores could be applicable to a wide range of species.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/coad043","usgsCitation":"Penk, S.R., Sadana, P., Archer, L.C., Pagano, A.M., Cattet, M.R., Lunn, N.J., Thiemann, G.W., and Molnar, P.K., 2023, A body composition model with multiple storage compartments for polar bears (Ursus maritimus), v. 11, no. 1, coad043, 20 p., https://doi.org/10.1093/conphys/coad043.","productDescription":"coad043, 20 p.","ipdsId":"IP-142122","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":443007,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coad043","text":"Publisher Index Page"},{"id":418459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Penk, Stephanie R. 0000-0002-8027-4372","orcid":"https://orcid.org/0000-0002-8027-4372","contributorId":312472,"corporation":false,"usgs":false,"family":"Penk","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sadana, Pranav","contributorId":312473,"corporation":false,"usgs":false,"family":"Sadana","given":"Pranav","email":"","affiliations":[{"id":16930,"text":"University of Winnipeg","active":true,"usgs":false}],"preferred":false,"id":876208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archer, Louise C. 0000-0002-1983-3825","orcid":"https://orcid.org/0000-0002-1983-3825","contributorId":312474,"corporation":false,"usgs":false,"family":"Archer","given":"Louise","email":"","middleInitial":"C.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":876210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cattet, Marc R. L. 0000-0002-2318-1452","orcid":"https://orcid.org/0000-0002-2318-1452","contributorId":312475,"corporation":false,"usgs":false,"family":"Cattet","given":"Marc","email":"","middleInitial":"R. L.","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":876211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lunn, Nicholas J. 0000-0003-0189-5494","orcid":"https://orcid.org/0000-0003-0189-5494","contributorId":312476,"corporation":false,"usgs":false,"family":"Lunn","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":876212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thiemann, Gregory W.","contributorId":83023,"corporation":false,"usgs":false,"family":"Thiemann","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":876213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Molnar, Peter K. 0000-0001-7260-2674","orcid":"https://orcid.org/0000-0001-7260-2674","contributorId":312477,"corporation":false,"usgs":false,"family":"Molnar","given":"Peter","email":"","middleInitial":"K.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876214,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70245787,"text":"70245787 - 2023 - Ensemble estimation of historical evapotranspiration for the conterminous U.S.","interactions":[],"lastModifiedDate":"2023-06-27T11:48:52.454255","indexId":"70245787","displayToPublicDate":"2023-06-20T06:45:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Ensemble estimation of historical evapotranspiration for the conterminous U.S.","docAbstract":"Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall-to-wall explanatory variable maps to generate CONUS-wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national-scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.
Assessing the influence of marshes on mitigating flooding along estuarine shorelines under the pressures of sea level rise requires understanding wave transformation across the marsh. A numerical model was applied to investigate how vegetated marshes influence wave transformation. XBeach non-hydrostatic (XB-NH) was calibrated and validated with high frequency pressure data from the marsh at China Camp State Park in San Pablo Bay, California (USA). The model was used to examine how marsh and hydrodynamic characteristics change the potential for marshes to mitigate wave driven flooding. Model results demonstrate that hydrodynamics, vegetation, and marsh width influence wave transformation most, while marsh morphology parameters such as elevation and slope had least effect. Results suggest that in the range of settings explored here (incident wave heights ranging from 0.5 to 3 m and water levels ranging from current mean higher high water to 3 m above current mean higher high water), in comparison to wave propagation over an unvegetated mudflat, marsh vegetation reduces runup by a median of 40 cm and wave height by a median of 35 cm. Results illustrate how marshes can be strategically utilized to provide flood reduction benefits.
On 15 January 2022, Hunga Volcano in Tonga produced the most violent eruption in the modern satellite era, sending a water-rich plume at least 58 km high. Using a combination of satellite- and ground-based sensors, we investigate the astonishing rate of volcanic lightning (>2,600 flashes min−1) and what it reveals about the dynamics of the submarine eruption. In map view, lightning locations form radially expanding rings. We show that the initial lightning ring is co-located with an internal gravity wave traveling >80 m s−1 in the stratospheric umbrella cloud. Buoyant oscillations of the plume's overshooting top generated the gravity waves, which enhanced turbulent particle interactions and triggered high-current electrical discharges at unusually high altitudes. Our analysis attributes the intense lightning activity to an exceptional mass eruption rate (>5 × 109 kg s−1), rapidly expanding umbrella cloud, and entrainment of abundant seawater vaporized from magma-water interaction at the submarine vent.
Sea level rise is affecting reaches of coastal rivers by increasing water levels and propagating tides inland. The transition of river systems into tidal estuaries has been neglected in hydrogeomorphic studies. A better understanding of transitioning reaches is critical to understanding ecosystem dynamics, services, and developing predictive capabilities of change as sea levels rise. We hypothesized that river-floodplain morphology changes from fluvial to tidally dominated regimes, changing suspended sediment concentrations (SSC), sediment deposition, vegetation, and landforms. We tested this using lidar, satellite imagery, and SSC and conductivity measurements along two Coastal Plain rivers of Virginia, USA. Geomorphic channel and floodplain parameters indicated breakpoints into three regimes: fluvial, mixed, and tidal. Maximum channel width occurred with minimum floodplain widths in the mixed regime. Tidal freshwater forests had considerable elevational overlap with marshes but typically were 9.5 cm higher. SSC increased with shoal width through the mixed reaches, with maxima in the tidal reaches where estuarine influences increased. Channel erosion rates indicated that modern sediment loads and hydrology produce slow changes to channel planform and geomorphology that may not be apparent from visual comparisons. Our findings indicated that tidal floodplain forests and marshes in the mixed and tidal reaches are expected to convert to marshes or open water as sea levels rise as limited gradual sloping area exists between the active floodplain and terraces. Tidal floodplain surfaces along mixed hydrology reaches, inland of the estuarine turbidity maximum may be expected to convert to open water while inland sloping floodplains could support tidal wetland migration.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-023-01226-6","usgsCitation":"Kroes, D., Noe, G.E., Hupp, C.R., Doody, T.R., and Bukaveckas, P., 2023, Hydrogeomorphic changes along mid-Atlantic coastal plain rivers transitioning from non-tidal to tidal: Implications for a rising sea level: Estuaries and Coasts, v. 46, p. 1438-1458, https://doi.org/10.1007/s12237-023-01226-6.","productDescription":"21 p.","startPage":"1438","endPage":"1458","ipdsId":"IP-135089","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":435281,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B1UCFT","text":"USGS data release","linkHelpText":"Hydrogeomorphic data along transitioning Coastal Plain rivers (Mattaponi and Pamunkey Rivers): implications for a rising sea level"},{"id":418223,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Chesapeake Bay Watershed, Mattaponi River, Pamunkey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.65344171287853,\n 37.86125997466432\n ],\n [\n -77.48781222047384,\n 37.86125997466432\n ],\n [\n -77.48781222047384,\n 37.46887702495529\n ],\n [\n -76.65344171287853,\n 37.46887702495529\n ],\n [\n -76.65344171287853,\n 37.86125997466432\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","noUsgsAuthors":false,"publicationDate":"2023-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":875657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":875659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doody, Thomas Rossiter 0000-0002-2102-738X tdoody@contractor.usgs.gov","orcid":"https://orcid.org/0000-0002-2102-738X","contributorId":223569,"corporation":false,"usgs":true,"family":"Doody","given":"Thomas","email":"tdoody@contractor.usgs.gov","middleInitial":"Rossiter","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":875660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bukaveckas, P.A. 0000-0002-2636-7818","orcid":"https://orcid.org/0000-0002-2636-7818","contributorId":310428,"corporation":false,"usgs":false,"family":"Bukaveckas","given":"P.A.","affiliations":[{"id":38728,"text":"Virginia Commonwealth University","active":true,"usgs":false}],"preferred":false,"id":875661,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245161,"text":"70245161 - 2023 - High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia","interactions":[],"lastModifiedDate":"2023-06-19T17:12:31.329271","indexId":"70245161","displayToPublicDate":"2023-06-19T11:51:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia","docAbstract":"During a volcanic crisis, high-rate, localized deformation can indicate magma close to the surface, with important implications for eruption forecasting. However, only a few such examples have been reported, because frequent, dense monitoring is needed. High-resolution Synthetic Aperture Radar (SAR) is capable of achieving <1 m spatial resolution and sub-weekly revisit times, but is under-used. Here we use high-resolution satellite SAR imagery from COSMO-SkyMed, TerraSAR-X, and Sentinel-1 to detect intra-crater uplift preceding the November 2017 onset of eruptive activity at Agung, Indonesia. Processing the SAR imagery with an up-to-date, accurate, high-resolution digital elevation model was crucial for preventing aliasing of the deformation signal and for accurate georeferencing. We show that >15 cm of line-of-sight shortening occurred over a 400-by-400 m area on the crater floor in September-October 2017, accompanying a deep seismic swarm and flank dyke intrusion. We attribute the deformation to the pressurization of a shallow (<200 m deep) hydrothermal system by the injection of magmatic gases and fluids. We also observe a second pulse of intra-crater deformation of 3–5 cm within 4 days to 11 hr prior to the first phreatomagmatic eruption, which is consistent with interaction between the hydrothermal system and the ascending magma. This phreatomagmatic eruption created the central pathway used during the final stages of magma ascent. Our observations have important implications for understanding unrest and eruption forecasting, and demonstrate the potential of monitoring with high-resolution SAR.
","language":"English","publisher":"Wiley","doi":"10.1029/2022JB025669","usgsCitation":"Bemelmans, M., Biggs, J., Poland, M.P., Wookey, J., Ebmeier, S., Diefenbach, A., and Syahbana, D.D., 2023, High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia: Journal of Geophysical Research B: Solid Earth, v. 128, no. 5, e2022JB025669, 27 p., https://doi.org/10.1029/2022JB025669.","productDescription":"e2022JB025669, 27 p.","ipdsId":"IP-145594","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":443019,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jb025669","text":"Publisher Index Page"},{"id":418219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Agung Volcano, Bali","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 115.49507682936888,\n -8.406300591448016\n ],\n [\n 115.51391236474785,\n -8.425323602450476\n ],\n [\n 115.52198473705289,\n -8.44129377777513\n ],\n [\n 115.53026409326424,\n -8.430851814741729\n ],\n [\n 115.55944882390781,\n -8.390309758644221\n ],\n [\n 115.58221705348922,\n -8.367402141157967\n ],\n [\n 115.58263102130024,\n -8.335659853363467\n ],\n [\n 115.5604837434351,\n -8.30350536078592\n ],\n [\n 115.524675527824,\n -8.28425236518369\n ],\n [\n 115.48783239268414,\n -8.28793125803746\n ],\n [\n 115.44064006228348,\n -8.31005143321569\n ],\n [\n 115.42863499577669,\n -8.344867699330223\n ],\n [\n 115.44871243458851,\n -8.381933371662427\n ],\n [\n 115.49507682936888,\n -8.406300591448016\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Bemelmans, Mark","contributorId":310454,"corporation":false,"usgs":false,"family":"Bemelmans","given":"Mark","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":875718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biggs, Juliet","contributorId":206389,"corporation":false,"usgs":false,"family":"Biggs","given":"Juliet","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":875719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":875720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wookey, James","contributorId":310455,"corporation":false,"usgs":false,"family":"Wookey","given":"James","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":875721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ebmeier, Susanna","contributorId":174225,"corporation":false,"usgs":false,"family":"Ebmeier","given":"Susanna","affiliations":[{"id":7172,"text":"University of Bristol, U.K. and University of Oregon, Eugene","active":true,"usgs":false}],"preferred":false,"id":875722,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diefenbach, Angela K. 0000-0003-0214-7818","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":204743,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":875723,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Syahbana, Devy Damil","contributorId":243233,"corporation":false,"usgs":false,"family":"Syahbana","given":"Devy","email":"","middleInitial":"Damil","affiliations":[],"preferred":false,"id":875724,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70245153,"text":"70245153 - 2023 - A new DNA extraction method (HV-CTAB-PCI) for amplification of nuclear markers from open ocean-retrieved faeces of an herbivorous marine mammal, the dugong","interactions":[],"lastModifiedDate":"2023-06-19T16:38:44.155755","indexId":"70245153","displayToPublicDate":"2023-06-19T11:22:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"A new DNA extraction method (HV-CTAB-PCI) for amplification of nuclear markers from open ocean-retrieved faeces of an herbivorous marine mammal, the dugong","docAbstract":"Non-invasively collected faecal samples are an alternative source of DNA to tissue samples, that may be used in genetic studies of wildlife when direct sampling of animals is difficult. Although several faecal DNA extraction methods exist, their efficacy varies between species. Previous attempts to amplify mitochondrial DNA (mtDNA) markers from faeces of wild dugongs (Dugong dugon) have met with limited success and nuclear markers (microsatellites) have been unsuccessful. This study aimed to establish a tool for sampling both mtDNA and nuclear DNA (nDNA) from dugong faeces by modifying approaches used in studies of other large herbivores. First, a streamlined, cost-effective DNA extraction method that enabled the amplification of both mitochondrial and nuclear markers from large quantities of dugong faeces was developed. Faecal DNA extracted using a new ‘High Volume- Cetyltrimethyl Ammonium Bromide- Phenol-Chloroform-Isoamyl Alcohol’ (HV-CTAB-PCI) method was found to achieve comparable amplification results to extraction of DNA from dugong skin. As most prevailing practices advocate sampling from the outer surface of a stool to maximise capture of sloughed intestinal cells, this study compared amplification success of mtDNA between the outer and inner layers of faeces, but no difference in amplification was found. Assessment of the impacts of faecal age or degradation on extraction, however, demonstrated that fresher faeces with shorter duration of environmental (seawater) exposure amplified both markers better than eroded scats. Using the HV-CTAB-PCI method, nuclear markers were successfully amplified for the first time from dugong faeces. The successful amplification of single nucleotide polymorphism (SNP) markers represents a proof-of-concept showing that DNA from dugong faeces can potentially be utilised in population genetic studies. This novel DNA extraction protocol offers a new tool that will facilitate genetic studies of dugongs and other large and cryptic marine herbivores in remote locations.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0278792","usgsCitation":"Ooi, V., McMichael, L., Hunter, M., Takoukam Kamla, A., and Lanyon, J.M., 2023, A new DNA extraction method (HV-CTAB-PCI) for amplification of nuclear markers from open ocean-retrieved faeces of an herbivorous marine mammal, the dugong: PLoS ONE, v. 18, no. 6, e0278792, 29 p., https://doi.org/10.1371/journal.pone.0278792.","productDescription":"e0278792, 29 p.","ipdsId":"IP-147065","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":443024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0278792","text":"Publisher Index Page"},{"id":418217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","state":"Queensland","otherGeospatial":"Moreton Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 153.37192416070502,\n -27.859614592565208\n ],\n [\n 153.42962470601918,\n -27.687005800163497\n ],\n [\n 153.43511999604937,\n -27.504375776224627\n ],\n [\n 153.46534409121273,\n -27.406848872159316\n ],\n [\n 153.3939053208257,\n -27.204205934764204\n ],\n [\n 153.38566238578045,\n -27.050146132142267\n ],\n [\n 153.17134607461963,\n -27.050146132142267\n ],\n [\n 153.0422067589185,\n -27.106414779566876\n ],\n [\n 152.99824443867976,\n -27.194430673154535\n ],\n [\n 153.08891672417235,\n -27.23108348366104\n ],\n [\n 153.0202255988005,\n -27.297028138020522\n ],\n [\n 153.08616907915723,\n -27.362933646179656\n ],\n [\n 153.14661726948384,\n -27.38489343868985\n ],\n [\n 153.18233665467994,\n -27.492189631662583\n ],\n [\n 153.2345419099613,\n -27.51168681530772\n ],\n [\n 153.2867471652453,\n -27.601816322987915\n ],\n [\n 153.29224245527553,\n -27.711333458802045\n ],\n [\n 153.34994300058702,\n -27.786714713843168\n ],\n [\n 153.37192416070502,\n -27.859614592565208\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Ooi, Vicky","contributorId":310440,"corporation":false,"usgs":false,"family":"Ooi","given":"Vicky","email":"","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMichael, Lee","contributorId":310441,"corporation":false,"usgs":false,"family":"McMichael","given":"Lee","email":"","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":214742,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":875695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takoukam Kamla, Aristide","contributorId":204221,"corporation":false,"usgs":false,"family":"Takoukam Kamla","given":"Aristide","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":875696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lanyon, Janet M.","contributorId":204224,"corporation":false,"usgs":false,"family":"Lanyon","given":"Janet","email":"","middleInitial":"M.","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875697,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245143,"text":"70245143 - 2023 - Identifying hydrologic signatures associated with streamflow depletion caused by groundwater pumping","interactions":[],"lastModifiedDate":"2023-06-19T15:55:44.490498","indexId":"70245143","displayToPublicDate":"2023-06-19T10:45:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Identifying hydrologic signatures associated with streamflow depletion caused by groundwater pumping","docAbstract":"Groundwater pumping can reduce streamflow in nearby waterways (‘streamflow depletion’), a process which must be accounted for in integrated management of surface and groundwater resources. However, causal identification of streamflow depletion from hydrographs alone is challenging because pumping impacts are masked by other drivers of hydrologic variability. To identify potential indicators of streamflow depletion, we used synthetic hydrographs and an analytical streamflow depletion model to assess potential pumping impacts on specific hydrograph characteristics (‘hydrologic signatures’) for 215 streamgages spanning the conterminous United States (CONUS). We found that streamflow depletion commonly impacts signatures associated with seasonal and annual low flows and low flow recessions. The largest impacts occurred during dry years, suggesting streamflow depletion may be evident in dry years even where impacts are unmeasurable in wet years. Random forest models indicated that streamflow depletion could significantly impact Annual, Summer, and Fall signatures in most streams. Our finding that multiple hydrologic signatures are consistently responsive to streamflow depletion across CONUS suggests that the underlying hydrological processes linking pumping to streamflow reductions are consistent across diverse settings, information that will aid in identifying indicators of streamflow depletion from streamflow hydrographs.
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-117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"37","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Lapides, Dana A.","contributorId":310433,"corporation":false,"usgs":false,"family":"Lapides","given":"Dana","email":"","middleInitial":"A.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":875667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zipper, Samuel 0000-0002-8735-5757","orcid":"https://orcid.org/0000-0002-8735-5757","contributorId":225160,"corporation":false,"usgs":false,"family":"Zipper","given":"Samuel","email":"","affiliations":[{"id":41056,"text":"Kansas Geological Survey, University of Kansas, Lawrence KS 66047, USA","active":true,"usgs":false}],"preferred":false,"id":875668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875669,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70245145,"text":"70245145 - 2023 - Evaluating population trends of juvenile Atlantic Sturgeon at low abundance in a dynamic estuarine environment (Hudson River, New York)","interactions":[],"lastModifiedDate":"2023-09-20T16:18:28.999697","indexId":"70245145","displayToPublicDate":"2023-06-19T10:36:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating population trends of juvenile Atlantic Sturgeon at low abundance in a dynamic estuarine environment (Hudson River, New York)","docAbstract":"Evaluating population trends in dynamic estuarine environments can be challenging, especially when survey data include a high percentage of zero observations. In fishery-independent surveys, zeros that come from reduced susceptibility to sample gears and reduced availability of the population to the survey impact survey catchability and negatively bias relative abundance indices. A zero-inflated negative binomial model was used to standardize a juvenile Atlantic Sturgeon (Acipenser oxyrinchus oxyrinchus) relative abundance index (Hudson River, New York) that included a high proportion (42%) of zero observations and intra- and interannually variable covariates. Reduced susceptibility was related to low water temperature, with the percentage of zeroes increasing rapidly below 7°C. Availability was influenced by temperature and distance to salt front, as catch rates increased with temperature and peaked in mesohaline waters ~27 km downstream of the predicted salt front. An alternative index suggested significant population growth (r = 0.15; p-value = 0.007) occurred from 2004 to 2015. The zero-inflated model helped better understand Hudson River juvenile Atlantic Sturgeon ecology and relative trends in abundance, to better inform future management and monitoring decisions along the Atlantic Coast.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12638","usgsCitation":"Dufour, M.R., and Qian, S.S., 2023, Evaluating population trends of juvenile Atlantic Sturgeon at low abundance in a dynamic estuarine environment (Hudson River, New York): Fisheries Management and Ecology, v. 30, no. 5, p. 507-520, https://doi.org/10.1111/fme.12638.","productDescription":"14 p.","startPage":"507","endPage":"520","ipdsId":"IP-133677","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":499248,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fme.12638","text":"Publisher Index Page"},{"id":418213,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Haverstraw Bay, Hudson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.98965367137986,\n 41.27278785874276\n ],\n [\n -73.98810103364949,\n 41.21441540680195\n ],\n [\n -73.96481146769594,\n 41.172354958942265\n ],\n [\n -73.92754816217085,\n 41.15131460173012\n ],\n [\n -73.85923210204054,\n 41.15365275277256\n ],\n [\n -73.87010056615213,\n 41.1898834296822\n ],\n [\n -73.9042585962173,\n 41.222590688889795\n ],\n [\n -73.93686398855216,\n 41.24477558908072\n ],\n [\n -73.94152190174316,\n 41.26578591767401\n ],\n [\n -73.98965367137986,\n 41.27278785874276\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"30","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":875670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qian, Song S. 0000-0002-2346-4903","orcid":"https://orcid.org/0000-0002-2346-4903","contributorId":306033,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[{"id":62440,"text":"Department of Environmental Sciences, University of Toledo, Toledo, OH 43606","active":true,"usgs":false}],"preferred":false,"id":875671,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70245183,"text":"70245183 - 2023 - A hierarchical modelling framework for estimating individual- and population-level reproductive success from movement data","interactions":[],"lastModifiedDate":"2023-08-08T14:19:03.582056","indexId":"70245183","displayToPublicDate":"2023-06-19T07:06:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A hierarchical modelling framework for estimating individual- and population-level reproductive success from movement data","docAbstract":"Nearshore bathymetry is difficult to measure using survey methods when wave heights approach the breaking limit. Remote sensing using digital cameras offers a way to observe the surf zone and calculate water depths based on phase speed but comes with its challenges of potentially noisy data that can introduce error into estimates of frequency and wavenumber used in phase speed calculation. This study investigates the robustness of a new version of a bathymetric inversion algorithm (cBathy, version 2.0) in moderate to energetic wave conditions by comparing depth estimates from timeseries’ of pixel intensity with depth estimates from synthetic water level data. The synthetic data are generated by the phase-resolving numerical model, SWASH, and optical data were collected during a field experiment in 2015. Model results from SWASH computed with known bathymetry are used as input to cBathy, and depth estimates are compared to nearshore surveys. Argus camera observations are also used as input to cBathy for the same times as the SWASH simulations. The SWASH simulations resolve breaking waves and do not include (optical) changes to the relation between water surface slope and pixel intensity, termed modulation transfer function, that occur during wave breaking, enabling better estimates from bathymetric inversion algorithms near morphologic features like sand bars. The results indicate that improvements result from eliminating of disruptions to the modulation transfer function caused by wave breaking and residual foam. We show that the use of synthetic wave data is a valuable means of isolating errors in bathymetric inversion algorithms.
During much of the 21st century, natural runoff in the Colorado River basin has declined, while consumption has remained relatively constant, leading to historically low reservoir storage. Between January 2000 and April 2023, the amount of water stored in Lake Mead and Lake Powell, the two largest reservoirs in the United States, declined by 33.5 million acre feet (41.3 billion cubic meters). As of April 2023, total basin-wide storage was sufficient to support the 21st century average rate of basin-wide consumption for only 15 months. Runoff in spring 2023 is predicted to be large, providing a short-term reprieve. However, it will take four to five additional unusually wet years in succession to refill Lake Powell and Lake Mead if basin-wide water use remains unchanged. Increasing evapotranspiration and dry soils associated with global climate change makes such a scenario unlikely. To stabilize reservoir storage, basin-wide use needs to equal modern runoff. To recover reservoir storage, basin-wide use needs to decline even more. Based on 21st century average runoff, a 13%–20% decline in basin-wide use would allow for stabilization and some reservoir storage recovery. Future policy debate about reservoir operations will inevitably concern whether most, or all, reservoir storage should be in Lake Mead or in Lake Powell. The choice of one or the other will result in significantly different environmental and recreational outcomes for Glen Canyon and the Grand Canyon.
","language":"English","publisher":"Wiley Interdisciplinary Reviews","doi":"10.1002/wat2.1672","usgsCitation":"Schmidt, J.C., Yackulic, C., and Kuhn, E., 2023, The Colorado River water crisis: Its origin and the future: WIREs Water, v. 10, no. 6, e1672, 11 p., https://doi.org/10.1002/wat2.1672.","productDescription":"e1672, 11 p.","ipdsId":"IP-148177","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":443043,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wat2.1672","text":"Publisher Index Page"},{"id":418391,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, Baja California, California, Colorado, Nevada, New Mexico, Sonora, Utah, Wyoming","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.48421418796046,\n 31.35434215860566\n ],\n [\n -113.65259586662187,\n 32.23920414412936\n ],\n [\n -112.21089756604964,\n 31.90052568352887\n ],\n [\n -111.87558421754458,\n 32.20952085093056\n ],\n [\n -111.28541066018629,\n 32.11399667847604\n ],\n [\n -111.23279241837177,\n 31.437228609979257\n ],\n [\n -110.94817616136105,\n 30.97237021578711\n ],\n [\n -109.99614795253682,\n 31.0580658429583\n ],\n [\n -109.765123637271,\n 31.565815216207625\n ],\n [\n -109.2216186810205,\n 31.780902751508492\n ],\n [\n -108.70850128918396,\n 31.58004054549238\n ],\n [\n -107.23835863291889,\n 32.490078241661664\n ],\n [\n -106.730360119866,\n 34.66458922372419\n ],\n [\n -107.42958642929439,\n 35.07481907867975\n ],\n [\n -106.85826554201257,\n 35.61881061726045\n ],\n [\n -105.7061398095985,\n 37.33375003848154\n ],\n [\n -105.879787594186,\n 39.89096635274717\n ],\n [\n -106.74739533342402,\n 41.696412051333766\n ],\n [\n -106.68778798532564,\n 42.531437760880465\n ],\n [\n -108.38774334794128,\n 42.38607065176245\n ],\n [\n -110.40321867986886,\n 43.243504117137775\n ],\n [\n -111.01626499710237,\n 42.72084370600541\n ],\n [\n -111.07561236378847,\n 41.02050419347333\n ],\n [\n -112.02989616951957,\n 39.12042969242722\n ],\n [\n -113.30959508904654,\n 37.1563348714911\n ],\n [\n -114.37484829397191,\n 37.048946927772775\n ],\n [\n -114.7380747976792,\n 38.490173161398246\n ],\n [\n -116.45388765022786,\n 38.98493898775925\n ],\n [\n -116.41298707291212,\n 37.45745026322449\n ],\n [\n -115.37080488894956,\n 35.768178708278725\n ],\n [\n -115.16334164848244,\n 33.20321074731645\n ],\n [\n -116.48506247630979,\n 33.87016090096576\n ],\n [\n -116.22048705379954,\n 32.88635352395437\n ],\n [\n -115.44554171380956,\n 31.52088586510753\n ],\n [\n -114.48421418796046,\n 31.35434215860566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, John C.","contributorId":207751,"corporation":false,"usgs":false,"family":"Schmidt","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37627,"text":"Department of Watershed Sciences, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":876047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":876048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuhn, Eric","contributorId":311212,"corporation":false,"usgs":false,"family":"Kuhn","given":"Eric","email":"","affiliations":[{"id":67359,"text":"General Manager, Colorado River Water Conservation District (retired) Glenwood Springs, CO","active":true,"usgs":false}],"preferred":false,"id":876049,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70247935,"text":"70247935 - 2023 - Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary","interactions":[],"lastModifiedDate":"2023-08-24T12:02:06.018325","indexId":"70247935","displayToPublicDate":"2023-06-16T06:55:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary","docAbstract":"The effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine dominant estuary (Grand Bay, Alabama, U.S.A) are investigated using a two-dimensional model, the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM). Three restoration alternatives are simulated for present-day conditions, as well as under 0.5 m of sea level rise (SLR). Model results show that the restoration alternatives have no impact on tidal range within the estuary but change maximum tidal velocities by ±5 cm/s in the present-day scenarios and by ±7 cm/s in the scenarios with 0.5 m of SLR. Differences in average salinity concentrations for simulated tropical and frontal seasons show increases and decreases on the order of 2 pss in the embayments surrounding the restoration alternatives; differences were larger (on the order of ±4 pss) for the scenarios with 0.5 m of SLR. There were minimal changes in average salinity outside of the estuary and no changes offshore. The size and position of the alternatives played a role in the salinity response as a result of changing the estuarine shoreline geometry and affecting the fetch within the bay. SLR was more impactful in increasing exposure to low salinity values (i.e., less than 5 pss) than the presence of the restoration alternatives. Overall, the modeled results indicate that these large-scale restoration actions have limited and localized impacts on the hydrodynamics and salinity patterns in this open coast estuary. The results also demonstrate the nonlinear response of salinity to SLR, with increases and decreases in the maximum, mean and minimum daily salinity concentrations from present-day conditions. This nonlinear response was a result of changes in the directions of the residual currents, which affected salinity transport.
This report describes status and trends in watershed condition across the Northwest Forest Plan (NWFP) area over the first 25 years since its inception in 1994. The program charged with this task is the Aquatic and Riparian Effectiveness Monitoring Program (AREMP), which has assembled information from field data collection, spatial datasets, and a host of landscape models to evaluate the status and trends in aquatic resources in streams and watersheds. Field data included hydrologic measurements (stream wetted widths and temperatures), geomorphic responses (instream wood and sediment), and biological responses (macroinvertebrates and aquatic organism passage). Novel statistical models were used to estimate trends in these measured responses. A suite of complementary modeled results was also employed to describe hydrometeorological drivers (e.g., drought indices and stream discharge), forest cover (upslope and riparian vegetation), and geomorphic conditions (e.g., road-related estimates of chronic and shallow landslide sediment delivery risk). Collectively, information on these responses allowed us to rigorously evaluate instream responses and hypothesize watershed drivers of those responses across the NWFP area and over time. The majority of responses we observed indicated widespread and incremental improvements from active management of forests, forest roads, and road-stream crossings as envisioned by the aquatic conservation strategy of the NWFP. Additionally, many of the responses we observed were consistent with those expected under the influences of changing climates in the Pacific Northwest. Ultimately, the long-term, broad-scale information provided by AREMP is a critical foundation for evaluating the effectiveness of federal land management and the effects of changing climates on water resources that sustain the Pacific Northwest’s human and natural landscapes.
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