Large amounts of video images have been collected for decades by scientific and governmental organizations in deep (>1000 m) water using manned and unmanned submersibles and towed cameras. The collected images were analyzed individually or were mosaiced in small areas with great effort. Here, we provide a workflow for utilizing modern photogrammetry to construct virtual geological outcrops hundreds or thousands of meters in length from these archived video images. The photogrammetry further allows quantitative measurements of these outcrops, which were previously unavailable. Although photogrammetry had been carried out in recent years in the deep sea, it had been limited to small areas with pre-defined overlapping dive paths. Here, we propose a workflow for constructing virtual outcrops from archived exploration dives, which addresses the complicating factors posed by single non-linear and variable-speed vehicle paths. These factors include poor navigation, variable lighting, differential color attenuation due to variable distance from the seafloor, and variable camera orientation with respect to the vehicle. In particular, the lack of accurate navigation necessitates reliance on image quality and the establishment of pseudo-ground-control points to build the photogrammetry model. Our workflow offers an inexpensive method for analyzing deep-sea geological environments from existing video images, particularly when coupled with rock samples.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse12081250","usgsCitation":"Flores, C., and ten Brink, U.S., 2024, Photogrammetry of the deep seafloor from archived unmanned submersible exploration dives: Journal of Marine Science and Engineering, v. 12, no. 8, 1250, 19 p., https://doi.org/10.3390/jmse12081250.","productDescription":"1250, 19 p.","ipdsId":"IP-159627","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":439255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse12081250","text":"Publisher Index Page"},{"id":432271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Atlantic Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.1,\n 19.2\n ],\n [\n -68.1,\n 18.3\n ],\n [\n -66.8,\n 18.3\n ],\n [\n -66.8,\n 19.2\n ],\n [\n -68.1,\n 19.2\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Flores, Claudia 0000-0003-0676-7061 cflores@usgs.gov","orcid":"https://orcid.org/0000-0003-0676-7061","contributorId":304396,"corporation":false,"usgs":true,"family":"Flores","given":"Claudia","email":"cflores@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":909080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"ten Brink, Uri S. 0000-0001-6858-3001","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":201741,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri","email":"","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":909081,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70256095,"text":"fs20243026 - 2024 - The Native American Research Assistantship Program—Building capacity for Indigenous water-resources monitoring","interactions":[],"lastModifiedDate":"2024-07-23T20:16:33.355013","indexId":"fs20243026","displayToPublicDate":"2024-07-23T13:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-3026","displayTitle":"The Native American Research Assistantship Program: Building Capacity for Indigenous Water-Resources Monitoring","title":"The Native American Research Assistantship Program—Building capacity for Indigenous water-resources monitoring","docAbstract":"Intertribal networks for collecting and analyzing hydrologic and environmental data are growing. The U.S. Geological Survey can be a key partner with Tribal Nations in the further development of network capacity. A first step is the internship opportunity available through the partnership between the USGS and The Wildlife Society: The Native American Research Assistantship Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243026","usgsCitation":"Hare-Red Corn, E., Breault, R.F., and Sorenson, J.R., 2024, The Native American Research Assistantship Program—Building capacity for Indigenous water-resources monitoring: U.S. Geological Survey Fact Sheet 2024–3026, 2 p., https://doi.org/10.3133/fs20243026.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158895","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":431260,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3026/images/"},{"id":431259,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3026/fs20243026.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2024-3026 XML"},{"id":431258,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243026/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3026 HTML"},{"id":431257,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3026/fs20243026.pdf","text":"Report","size":"5.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3026 PDF"},{"id":431256,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3026/coverthb.jpg"}],"contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Seismic boundaries caused by phase transitions between olivine polymorphs in Earth's mantle provide thermal and compositional markers that inform mantle dynamics. Seismic studies of the mantle transition zone often use either global averaging with sparse arrays or regional sampling from a single dense array. The intermediate approach of this study utilizes many densely spaced seismic arrays distributed around the globe. We systematically compute teleseismic P-to-S receiver functions for each seismic array and invert for the 1-D seismic velocity structure of the mantle transition zone beneath each array to facilitate a comparison between densely sampled regions. We stack 3,600 receiver functions on average at 67 arrays in total. The stack is used in a probabilistic inversion to estimate the mantle transition zone interface depths and velocities beneath each array. We focus on the 410-km discontinuity (410) because it is a prominent seismic interface that is clearly linked to a single mineral phase transition between olivine and wadsleyite. The depths and velocity contrasts of the 410 are mapped to temperatures and compositions using mineral physics constraints. The depth of the 410 ranges from ∼405–440 km, which is consistent with a ∼360 K temperature range in a dry mantle and a ∼260 K temperature range in a wet mantle (2 wt. % water). The Vs contrast across the 410 ranges from ∼2.5–8 %, which is consistent with ∼20–70 vol. % olivine composition in a dry mantle and ∼25–80 vol. % in a wet mantle. The bulk composition of the upper mantle near the 410-km discontinuity is typically considered to be well-mixed because there is no thermodynamic impediment to convection at the olivine to wadsleyite phase transition. However, the wide range of inferred olivine content from our study suggests that there are large lateral variations in the bulk composition of the upper mantle near the 410-km discontinuity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2024.118889","usgsCitation":"Glasgow, M.E., Zhang, H.K., Schmandt, B., Zhou, W., and Zhang, J., 2024, Global variability of the composition and temperature at the 410-km discontinuity from receiver function analysis of dense arrays: Earth and Planetary Science Letters, v. 643, 118889, 12 p., https://doi.org/10.1016/j.epsl.2024.118889.","productDescription":"118889, 12 p.","ipdsId":"IP-162736","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489835,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2024.118889","text":"Publisher Index Page"},{"id":431352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"643","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glasgow, Margaret Elizabeth 0000-0001-5637-5918","orcid":"https://orcid.org/0000-0001-5637-5918","contributorId":340268,"corporation":false,"usgs":true,"family":"Glasgow","given":"Margaret","email":"","middleInitial":"Elizabeth","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":906784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Hankui K.","contributorId":211965,"corporation":false,"usgs":false,"family":"Zhang","given":"Hankui","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":906785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmandt, Brandon","contributorId":202750,"corporation":false,"usgs":false,"family":"Schmandt","given":"Brandon","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":906786,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhou, Wen-Yi","contributorId":340269,"corporation":false,"usgs":false,"family":"Zhou","given":"Wen-Yi","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":906787,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Jinchi","contributorId":191970,"corporation":false,"usgs":false,"family":"Zhang","given":"Jinchi","email":"","affiliations":[],"preferred":false,"id":906788,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261445,"text":"70261445 - 2024 - A semi-mechanistic model for partitioning evapotranspiration reveals transpiration dominates the water flux in drylands","interactions":[],"lastModifiedDate":"2024-12-10T14:41:05.274772","indexId":"70261445","displayToPublicDate":"2024-07-23T08:36:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"A semi-mechanistic model for partitioning evapotranspiration reveals transpiration dominates the water flux in drylands","docAbstract":"Popular evapotranspiration (ET) partitioning methods make assumptions that might not be well-suited to dryland ecosystems, such as high sensitivity of plant water-use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine-scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi-mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process-based models, and loosely constrains time-varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross-wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub-yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem-scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JG007914","usgsCitation":"Reich, E., Samuels-Crow, K., Bradford, J., Litvak, M., Schlaepfer, D.R., and Ogle, K., 2024, A semi-mechanistic model for partitioning evapotranspiration reveals transpiration dominates the water flux in drylands: Journal of Geophysical Research: Biogeosciences, v. 129, no. 7, e2023JG007914, 18 p., https://doi.org/10.1029/2023JG007914.","productDescription":"e2023JG007914, 18 p.","ipdsId":"IP-166030","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":464941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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Center","active":true,"usgs":true}],"preferred":true,"id":920585,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ogle, K.","contributorId":347032,"corporation":false,"usgs":false,"family":"Ogle","given":"K.","affiliations":[{"id":83043,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA; Center of Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":920586,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70259218,"text":"70259218 - 2024 - Evaluating distributed snow model resolution and meteorology parameterizations against streamflow observations: Finer Is not always better","interactions":[],"lastModifiedDate":"2024-10-02T13:35:21.858349","indexId":"70259218","displayToPublicDate":"2024-07-23T08:15:54","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating distributed snow model resolution and meteorology parameterizations against streamflow observations: Finer Is not always better","docAbstract":"Estimating snow conditions is often done using numerical snowpack evolution models at spatial resolutions of 500 m and greater; however, snow depth in complex terrain often varies on sub-meter scales. This study investigated how the spatial distribution of simulated snow conditions varied across seven model spatial resolutions from 30 to 1,000 m and over two meteorological data sets, coarser (≈12 km) and finer (4 km). Simulated snow covered area (SCA) was compared to remotely sensed SCA and simulated watershed mean peak snow water equivalent (SWE) was compared to four streamflow statistics representing different water management-relevant aspects of the hydrograph using non-parametric correlations. April 1 SWE tended to increase with model resolution, particularly below 4,000 masl. Finer meteorology simulations produced deeper April 1 SWE than coarser meteorology simulations. Finer resolution snow simulations tended to produce longer snowmelt durations and slower snowmelt rates than coarser resolution simulations. Finer resolution simulations had better agreement with SCA for both meteorology data sets, particularly at high and low elevations. However, finer resolution simulations did not generally outperform coarser simulations in snow versus streamflow statistic correlations. Snow versus streamflow correlations were most sensitive to meteorology, watershed properties, and then resolution. Watershed physiographic properties such as wetness index may increase snow versus streamflow metric correlations while elevation and slope may decrease correlations. At watershed scales, these results suggest that simulation resolution and choice of meteorology is less important than the physiographic properties of the watershed; however, if resolving snow distribution across the landscape is important, finer-resolution simulations are useful.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR035982","usgsCitation":"Barnhart, T.B., Putman, A.L., Heldmyer, A.J., Rey, D., Hammond, J., Driscoll, J.M., and Sexstone, G., 2024, Evaluating distributed snow model resolution and meteorology parameterizations against streamflow observations: Finer Is not always better: Water Resources Research, v. 60, no. 7, e2023WR035982, 21 p., https://doi.org/10.1029/2023WR035982.","productDescription":"e2023WR035982, 21 p.","ipdsId":"IP-154162","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":466979,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr035982","text":"Publisher Index Page"},{"id":462477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.35,\n 40\n ],\n [\n -107.5,\n 40\n ],\n [\n -107.5,\n 37.75\n ],\n [\n -105.35,\n 37.75\n ],\n [\n -105.35,\n 40\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, Theodore B. 0000-0002-9682-3217","orcid":"https://orcid.org/0000-0002-9682-3217","contributorId":219010,"corporation":false,"usgs":true,"family":"Barnhart","given":"Theodore","email":"","middleInitial":"B.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":914512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Putman, Annie L. 0000-0002-9424-1707","orcid":"https://orcid.org/0000-0002-9424-1707","contributorId":225134,"corporation":false,"usgs":true,"family":"Putman","given":"Annie","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":914513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heldmyer, Aaron Joseph 0000-0001-8608-4927","orcid":"https://orcid.org/0000-0001-8608-4927","contributorId":302944,"corporation":false,"usgs":true,"family":"Heldmyer","given":"Aaron","email":"","middleInitial":"Joseph","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":914514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rey, David M. 0000-0003-2629-365X","orcid":"https://orcid.org/0000-0003-2629-365X","contributorId":211848,"corporation":false,"usgs":true,"family":"Rey","given":"David M.","affiliations":[{"id":37277,"text":"WMA - 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2024 - Isotopic evidence against North Pacific Deep Water formation during late Pliocene warmth","interactions":[],"lastModifiedDate":"2024-08-13T14:40:37.63952","indexId":"70256166","displayToPublicDate":"2024-07-23T07:28:38","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Isotopic evidence against North Pacific Deep Water formation during late Pliocene warmth","docAbstract":"Several modelling and observational studies suggest deep water formation in the subpolar North Pacific as a possible alternative mode of thermohaline circulation that occurred in the warm Pliocene, a time when global atmospheric partial pressure of carbon dioxide was like the modern atmosphere (~400 ppm). We test this hypothesis by measuring the δ13C of the benthic foraminifer Cibicidoides wuellerstorfi collected from northernmost Pacific mid-Piacenzian Warm Period (3.264–3.025 Myr ago) sediments. The data reveal progressively more isotopically negative dissolved inorganic carbon along a northward Equator-to-pole transect, the opposite of the expected Pliocene Pacific meridional overturning circulation signal. C. wuellerstorfi δ13C is also often more positive at the deeper Ocean Drilling Program (ODP) site 887 compared with the shallower ODP site 883, suggesting ‘bottom-up’ ventilation of the deep Pacific Ocean. We then present alkenone sea surface temperature and export-productivity data from ODP site 883, which suggest that late Pliocene subarctic North Pacific carbonate sedimentation was, at least in part, probably due to higher coccolithophore export production, rather than North Pacific Deep Water formation as previously argued. Therefore, we suggest it is unlikely that North Pacific Deep Water formation occurred in the mid-Piacenzian Warm Period, although a shallower overturning cell cannot be ruled out.
In this paper, we review the derivation of the Gauss–Levenberg–Marquardt (GLM) algorithm and its extension to ensemble parameter estimation. We explore the use of graphical methods to provide insights into how the algorithm works in practice and discuss the implications of both algorithm tuning parameters and objective function construction in performance. Some insights include understanding the control of both parameter trajectory and step size for GLM as a function of tuning parameters. Furthermore, for the iterative Ensemble Smoother (iES), we discuss the importance of noise on observations and show how iES can cope with non-unique outcomes based on objective function construction. These insights are valuable for modelers using PEST, PEST++, or similar parameter estimation tools.
Due to the socioeconomic and environmental damages caused by invasive species, predicting the distribution of invasive plants is fundamental for effectively targeting management efforts. A habitat suitability model (HSM) is a powerful tool to predict potential habitat of invasive species to help guide the early detection of invasive plants. Despite numerous studies of the predictors used in HSMs, there is little consensus about the most appropriate predictors to use in creating ecologically realistic predictions from HSMs.
The contiguous United States.
We explore 220 invasive terrestrial plant species' existing HSMs constructed with consistent modelling algorithms, background generation methods, predictor resolution, and geographic extent, and calculate the relative importance of predictors for each species. We sort predictors into eight groups (topography, temperature, disturbance, atmospheric water, landscape water, substrate, biotic interaction, and radiation) and compare the importance of predictor groups by plant lifeforms and phylogenetic relatedness.
Human modification and minimum winter temperature were generally the two highest performing individual predictors across the species studied. The highest-performing predictor groups were disturbance, temperature, and atmospheric water. Across lifeforms, there were minimal differences in the influences of predictor groups, although woody plant models exhibited the largest differences in predictor importance when compared with non-woody plant models. Additionally, we found no significant relationship between the importance of predictor groups and phylogenetic relatedness.
This study has implications for informing predictor selection in invasive plant HSMs, leading to more reliable and accurate models of invasive terrestrial plants. Our results emphasize the need to critically select predictors included in HSMs, with special consideration to temperature and disturbance predictors, to accurately predict habitat of invasive plant for detection and response of invasive plant species. With more accurate predictions, managers will be better prepared to address invasive species and reduce their threats to landscapes.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13906","usgsCitation":"Williams, D.A., Shadwell, K.S., Pearse, I., Prevey, J.S., Engelstad, P., Henderson, G., and Jarnevich, C.S., 2024, Predictor importance in habitat suitability models for invasive terrestrial plants: Diversity and Distributions, v. 30, no. 9, e13906, 13 p., https://doi.org/10.1111/ddi.13906.","productDescription":"e13906, 13 p.","ipdsId":"IP-160521","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":439261,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13906","text":"Publisher Index Page"},{"id":432432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Post-fire aerial seeding treatments are commonly used to reduce runoff and soil erosion, but little is known about how seeding treatments affect native vegetation recovery over long periods of time, particularly in type-converted forests which have been dramatically transformed by the effects of repeated, high-severity fire. In this study, we analyze and report on a rare long-term (23-year) dataset that documents vegetation dynamics following a 1996 post-fire aerial seed treatment and subsequent 2011 high-severity reburn in a dry conifer forest of northern New Mexico in the southwestern United States. Repeated surveys between 1997 – 2019 of 49 permanent transects were used to test for differences in vegetation cover, richness, and diversity between seeded and unseeded areas, and to characterize the development of seeded and unseeded vegetation communities through time and across gradients of burn severity, elevation, and soil-available water capacity. Post-fire seeding led to a clear and sustained divergence in herbaceous community composition. Seeded plots had much higher cover of non-native graminoids, primarily Bromus inermis, a likely contaminant in the seed mix. High-severity reburning in all plots in 2011 reduced native graminoid cover by half at seeded plots compared to both pre-fire levels and to plots that were unseeded following the initial 1996 fire. In addition, increased fire severity was associated with increased non-native graminoid cover and reduced native graminoid cover, native species richness, and species diversity. This study documents a fire-driven ecosystem transformation from a former conifer forest into a shrub-grass system, reinforced by aerial seeding of grasses and high-severity reburning. This unique long-term dataset illustrates that post-fire seeding carries significant risk of unwanted non-native species invasions that persist through subsequent fires – indicating that alternative post-fire management actions merit consideration to better support native ecosystem resilience in the face of emergent climate change and increasing disturbance. Lastly, this study highlights the importance of long-term monitoring of post-fire vegetation dynamics, as short-term assessments will miss key elements of the full complexity of ecosystem responses to fire and post-fire management actions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.3008","usgsCitation":"Wion, A.P., Stevens, J., Beeley, K., Oertel, R., Margolis, E.Q., and Allen, C., 2024, Multi-decadal vegetation transformations of a New Mexico ponderosa pine landscape after severe fires and aerial seeding: Ecological Applications, v. 34, no. 6, e3008, 21 p., https://doi.org/10.1002/eap.3008.","productDescription":"e3008, 21 p.","ipdsId":"IP-158911","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":498298,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.3008","text":"Publisher Index Page"},{"id":431346,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jemez Mountains, San Miguel Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.61072300933778,\n 36.66992633929999\n ],\n [\n -107.61072300933778,\n 35.363708672581055\n ],\n [\n -105.69910191558768,\n 35.363708672581055\n ],\n [\n -105.69910191558768,\n 36.66992633929999\n ],\n [\n -107.61072300933778,\n 36.66992633929999\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"34","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Wion, Andreas Paul 0000-0002-0701-2843","orcid":"https://orcid.org/0000-0002-0701-2843","contributorId":335166,"corporation":false,"usgs":true,"family":"Wion","given":"Andreas","email":"","middleInitial":"Paul","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":906778,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevens, Jens T. 0000-0002-2234-1960","orcid":"https://orcid.org/0000-0002-2234-1960","contributorId":289230,"corporation":false,"usgs":false,"family":"Stevens","given":"Jens T.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":906779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beeley, Kay","contributorId":340264,"corporation":false,"usgs":false,"family":"Beeley","given":"Kay","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":906780,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oertel, Rebecca","contributorId":340265,"corporation":false,"usgs":false,"family":"Oertel","given":"Rebecca","email":"","affiliations":[{"id":81531,"text":"Fort Collins Science Center *retired","active":true,"usgs":false}],"preferred":false,"id":906781,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Margolis, Ellis Q. 0000-0002-0595-9005 emargolis@usgs.gov","orcid":"https://orcid.org/0000-0002-0595-9005","contributorId":173538,"corporation":false,"usgs":true,"family":"Margolis","given":"Ellis","email":"emargolis@usgs.gov","middleInitial":"Q.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":906782,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Craig D.","contributorId":289211,"corporation":false,"usgs":false,"family":"Allen","given":"Craig D.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":906783,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256109,"text":"70256109 - 2024 - Post-fire sediment yield from a central California watershed: Field measurements and validation of the WEPP model","interactions":[],"lastModifiedDate":"2024-07-22T11:47:51.294971","indexId":"70256109","displayToPublicDate":"2024-07-20T06:43:33","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire sediment yield from a central California watershed: Field measurements and validation of the WEPP model","docAbstract":"In a warming climate, an intensifying fire regime and higher likelihood of extreme rain are expected to increase watershed sediment yield in many regions. Understanding regional variability in landscape response to fire and post-fire rainfall is essential for managing water resources and infrastructure. We measured sediment yield resulting from sequential wildfire and extreme rain and flooding in the upper Carmel River watershed (116 km2), on the central California coast, USA, using changes in sediment volume mapped in a reservoir. We determined that the sediment yield after fire and post-fire flooding was 854–1,100 t/km2/yr, a factor of 3.5–4.6 greater than the long-term yield from this watershed and more than an order of magnitude greater than during severe drought conditions. In this first large-scale field validation test of the WEPPcloud/wepppy framework for the Water Erosion Prediction Project (WEPP) model on a burned landscape, WEPP predicted 81%–106% of the measured sediment yield. These findings will facilitate assessing and predicting future fire effects in steep watersheds with a Mediterranean climate and indicate that the increasingly widespread use of WEPP is appropriate for evaluating post-fire hillslope erosion even across 100-km2 scales under conditions without debris flows.
Remote sensing can be an effective tool for mapping river bathymetry, but the need for direct measurements to calibrate image-derived depth estimates impedes broader application of this approach. One way to circumvent the need for field campaigns dedicated to calibration is to capitalize upon existing data. In this study, we introduce a framework for Bathymetric Mapping using Gage Records and Image Databases (BaMGRID). This workflow involves retrieving depth measurements made during gaging station site visits, downloading archived multispectral images, and then combining these two data sets to establish a relationship between depth and reflectance. We developed a processing chain that involves using application programming interfaces to obtain both depth measurements made during site visits and images centered on the gage and then linking depth to reflectance via an optimal band ratio analysis (OBRA) algorithm modified for small sample sizes. Applying this workflow to selected gages within two river basins indicated that depth retrieval from multispectral satellite images could be highly accurate, but with variable results from one image to the next at a given site. High resolution aerial photography was less conducive to bathymetric mapping in one of the basin considered. Of the four predictors of depth retrieval performance we evaluated (mean and standard deviation of depth, width, and an index of water clarity), only width was consistently significantly correlated with OBRA R2 (p < 0.026). Currently, BaMGRID is best-suited for site-by-site analysis to support practical applications at the reach scale; continuous, basin-wide mapping of river bathymetry will require additional research.
To explain the drivers of historical water use in the public water systems (PWSs) that serve populations in Providence, Rhode Island, and surrounding areas, and to forecast future water use, a machine-learning model (cubist regression) was developed by the U.S. Geological Survey in cooperation with Providence Water to model daily per capita rates of domestic, commercial, and industrial water use. The PWSs in this area form a connected network that sources water from the Scituate Reservoir in Rhode Island. The cubist regression model was trained and tested on daily per capita rates for three categories of water use (domestic, commercial, and industrial) that were developed from quarterly water sales data and U.S. Census Bureau population estimates within each PWS service area from January 2005 through December 2021. The model was then used to make forecasts of future water use under varying scenarios of climate change, population growth, and economic growth for the years 2030 and 2040.
The resulting daily per capita rates, which were modeled from the historical data, had an r2 value of 0.94 and root mean square error of 6.7 gallons per capita daily. Results of the model were used to estimate total water use (the product of daily per capita rates and population) for all public water systems over the historical study period. Daily per capita rates in the study area decreased from 2005 to 2021, while population increased during that same period. “Category of water use” was the variable with the greatest explanatory power for modeling daily per capita rates. Overall, both daily per capita rates and total water use were projected to decrease in 2030 and 2040, in comparison to historical values from 2005 to 2021. Daily per capita rates and total water use were forecasted to decrease as economic growth rates increase. Daily per capita rates were expected to decrease as population growth rates increase; however, total water use was less sensitive to population growth rates than daily per capita rates. Effects of climate change were minimal over the 2030 and 2040 forecasting horizon for the scenarios tested.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245052","collaboration":"Prepared in cooperation with Providence Water","usgsCitation":"Chamberlin, C.A., 2024, A predictive analysis of water use for Providence, Rhode Island: U.S. Geological Survey Scientific Investigations Report 2024–5052, 36 p., https://doi.org/10.3133/sir20245052.","productDescription":"Report: viii, 36 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-152679","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":499474,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117188.htm","linkFileType":{"id":5,"text":"html"}},{"id":431062,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94XIQ7W","text":"USGS data release","linkHelpText":"Model archive, input data, modeled estimates of water use 2005-2021, and forecasts of water use in 2030 and 2040 in Providence, Rhode Island"},{"id":431061,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5052/sir20245052.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5052 XML"},{"id":431060,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5052/images/"},{"id":431059,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245052/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5052 HTML"},{"id":431058,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5052/sir20245052.pdf","text":"Report","size":"4.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5052 PDF"},{"id":431057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5052/coverthb.jpg"}],"country":"United States","state":"Rhode Island","city":"Providence","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.6320030327788,\n 41.56235835697041\n ],\n [\n -71.17676197086665,\n 41.56235835697041\n ],\n [\n -71.17676197086665,\n 42.025783641742635\n ],\n [\n -71.6320030327788,\n 42.025783641742635\n ],\n [\n -71.6320030327788,\n 41.56235835697041\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
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The Chesapeake Bay Partnership is implementing conservation practices (CPs) throughout the Chesapeake Bay watershed to reduce nutrient and sediment delivery to the Bay. This study intends to provide an integrated and detailed understanding of how local streams respond to these CP-driven management efforts.
Key issue: To what extent do CPs positively affect the health of local streams in the nontidal watershed (cobenefits)?
Critical unknown: How do CPs change water quality and the stressors that affect stream aquatic life? Which CPs improve stream health more effectively?
Critical knowledge to be delivered to stakeholders includes—
Chesapeake Bay Activities
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
The environmental ubiquity of tire and road wear particles (TRWP) underscores the need to understand the occurrence, persistence, and environmental effects of tire-related chemicals in aquatic ecosystems. One such chemical is 6PPD-quinone (6PPD-Q), a transformation product of the tire antioxidant 6PPD. In urban stormwater runoff 6PPD-Q can exceed acute toxicity thresholds for several salmonid species and is being implicated in significant coho salmon losses in the Pacific Northwest. There is a critical need to understand the prevalence of 6PPD-Q across watersheds to identify habitats heavily affected by TRWPs. We conducted a reconnaissance of 6PPD and 6PPD-Q in surface waters across the United States from sites (N = 94) with varying land use (urban, agricultural, and forested) and streamflow to better understand stream exposures. A rapid, low-volume direct-inject, liquid chromatography mass spectrometry method was developed for the quantitation of 6PPD-Q and screening for 6PPD. Laboratory holding times, bottle material, headspace, and filter materials were investigated to inform best practices for 6PPD-Q sampling and analysis. Glass bottles with PTFE-lined caps minimized sorption and borosilicate glass fiber filters provided the highest recovery. 6PPD-Q was stable for at least 5 months in pure laboratory solutions and for 75 days at 5 °C with minimal headspace in the investigated surface water and stormwaters. Results also indicated samples can be frozen to extend holding times. 6PPD was not detected in any of the 526 analyzed samples and there were no detections of 6PPD-Q at agricultural or forested sites. 6PPD-Q was frequently detected in stormwater (57%, N = 90) and from urban impacted sites (45%, N = 276) with concentrations ranging from 0.002 to 0.29 μg/L. The highest concentrations, above the lethal level for coho salmon, occurred during stormwater runoff events. This highlights the importance of capturing episodic runoff events in urban areas near ecologically relevant habitat or nursery grounds for sensitive species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2024.142830","usgsCitation":"Lane, R.F., Smalling, K., Bradley, P., Greer, J.B., Gordon, S.E., Hansen, J.D., Kolpin, D., Spanjer, A.R., and Masoner, J.R., 2024, Tire-derived contaminants 6PPD and 6PPD-Q: Analysis, sample handling, and reconnaissance of United States stream exposures: Chemosphere, v. 363, 142830, 12 p., https://doi.org/10.1016/j.chemosphere.2024.142830.","productDescription":"142830, 12 p.","ipdsId":"IP-165067","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science 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0000-0002-3006-2734","orcid":"https://orcid.org/0000-0002-3006-2734","contributorId":220725,"corporation":false,"usgs":true,"family":"Hansen","given":"John","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":910857,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":910858,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Spanjer, Andrew R. 0000-0002-7288-2722 aspanjer@usgs.gov","orcid":"https://orcid.org/0000-0002-7288-2722","contributorId":150395,"corporation":false,"usgs":true,"family":"Spanjer","given":"Andrew","email":"aspanjer@usgs.gov","middleInitial":"R.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":910859,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":910860,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70256391,"text":"70256391 - 2024 - Interactive effects of salinity and hydrology on radial growth of bald cypress (Taxodium distichum (L.) Rich.) in coastal Louisiana, USA","interactions":[],"lastModifiedDate":"2024-08-01T18:07:32.586696","indexId":"70256391","displayToPublicDate":"2024-07-19T06:52:52","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"Interactive effects of salinity and hydrology on radial growth of bald cypress (Taxodium distichum (L.) Rich.) in coastal Louisiana, USA","docAbstract":"Tidal freshwater forests are usually located at or above the level of mean high water. Some Louisiana coastal forests are below mean high water, especially bald cypress (Taxodium distichum (L.) Rich.) forests because flooding has increased due to the combined effects of global sea level rise and local subsidence. In addition, constructed channels from the coast inland act as conduits for saltwater. As a result, saltwater intrusion affects the productivity of Louisiana’s coastal bald cypress forests. To study the long-term effects of hydrology and salinity on the health of these systems, we fitted dendrometer bands on selected trees to record basal area increment as a measure of growth in permanent forest productivity plots established within six bald cypress stands. Three stands were in freshwater sites with low salinity rooting zone groundwater (0.1–1.3 ppt), while the other three had higher salinity rooting zone groundwater (0.2–4.9 ppt). Water level was logged continuously, and salinity was measured monthly to quarterly on the surface and in groundwater wells. Higher groundwater salinity levels were related to decreased bald cypress radial growth, while higher freshwater flooding increased radial growth. With these data, coastal managers can model rates of bald cypress forest change as a function of salinity and flooding.
","language":"English","publisher":"MDPI","doi":"10.3390/f15071258","usgsCitation":"Day, R., From, A., Johnson, D., and Krauss, K., 2024, Interactive effects of salinity and hydrology on radial growth of bald cypress (Taxodium distichum (L.) Rich.) in coastal Louisiana, USA: Forests, v. 15, no. 7, 1258, 16 p., https://doi.org/10.3390/f15071258.","productDescription":"1258, 16 p.","ipdsId":"IP-102177","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":439267,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3390/f15071258","text":"Publisher Index Page"},{"id":431608,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.19521095490502,\n 31.239460576333215\n ],\n [\n -94.19521095490502,\n 28.592602619005845\n ],\n [\n -88.87782814240524,\n 28.592602619005845\n ],\n [\n -88.87782814240524,\n 31.239460576333215\n ],\n [\n -94.19521095490502,\n 31.239460576333215\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Day, Richard 0000-0002-5959-7054","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":221895,"corporation":false,"usgs":true,"family":"Day","given":"Richard","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":907218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"From, Andrew 0000-0002-6543-2627","orcid":"https://orcid.org/0000-0002-6543-2627","contributorId":221935,"corporation":false,"usgs":true,"family":"From","given":"Andrew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":907219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Darren 0000-0002-0502-6045","orcid":"https://orcid.org/0000-0002-0502-6045","contributorId":203921,"corporation":false,"usgs":true,"family":"Johnson","given":"Darren","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":907220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":219804,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":907221,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257578,"text":"70257578 - 2024 - Mitigating risk: Predicting H5N1 avian influenza spread with an empirical model of bird movement","interactions":[],"lastModifiedDate":"2024-08-20T10:52:55.014462","indexId":"70257578","displayToPublicDate":"2024-07-18T12:51:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3849,"text":"Transboundary and Emerging Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Mitigating risk: Predicting H5N1 avian influenza spread with an empirical model of bird movement","docAbstract":"Understanding timing and distribution of virus spread is critical to global commercial and wildlife biosecurity management. A highly pathogenic avian influenza virus (HPAIv) global panzootic, affecting ~600 bird and mammal species globally and over 83 million birds across North America (Dec 2023), poses a serious global threat to animals and public health. We combined a large, long-term waterfowl GPS tracking dataset (16 species) with on-ground disease surveillance data (county-level HPAIv detections) to create a novel empirical model that evaluated spatiotemporal exposure and predicted future spread and potential arrival of HPAIv via GPS tracked migratory waterfowl through 2022. Our model was effective for wild waterfowl, but predictions lagged HPAIv detections in poultry facilities and among some highly impacted non-migratory species. Our results offer critical advance warning for applied biosecurity management and planning and demonstrate the importance and utility of extensive multi-species tracking to highlight potential high-risk disease spread locations and more effectively manage outbreaks.","language":"English","publisher":"Wiley","doi":"10.1155/2024/5525298","usgsCitation":"McDuie, F., Overton, C.T., Lorenz, A., Matchett, E., Mott, A., Mackell, D.A., Ackerman, J.T., De La Cruz, S.E., Patil, V.P., Prosser, D., Takekawa, J., Orthmeyer, D.L., Pitesky, M.E., Diaz-Munoz, S.L., Riggs, B.M., Gendreau, J., Reed, E.T., Petrie, M.J., Williams, C.K., Buler, J.J., Hardy, M., Ladman, B.S., Legagneux, P., Bety, J., Thomas, P.J., Rodrigue, J., Lefebvre, J., and Casazza, M.L., 2024, Mitigating risk: Predicting H5N1 avian influenza spread with an empirical model of bird movement: Transboundary and Emerging Diseases, 5525298, 15 p.; Data Release, https://doi.org/10.1155/2024/5525298.","productDescription":"5525298, 15 p.; Data Release","ipdsId":"IP-141980","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":439268,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/2024/5525298","text":"Publisher Index Page"},{"id":434927,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A6P2G1","text":"USGS data release","linkHelpText":"Timing of Occurrence of Waterfowl in U.S. Counties and Canadian Counties, Boroughs, Census Districts, and Other Populated Area Designations with Modeled Exposure Status to Highly Pathogenic Avian Influenza Virus in 2021-2022"},{"id":432890,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"McDuie, Fiona 0000-0002-1948-5613","orcid":"https://orcid.org/0000-0002-1948-5613","contributorId":222936,"corporation":false,"usgs":true,"family":"McDuie","given":"Fiona","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":910914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":910915,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenz, Austen 0000-0003-3657-5941","orcid":"https://orcid.org/0000-0003-3657-5941","contributorId":222610,"corporation":false,"usgs":true,"family":"Lorenz","given":"Austen","email":"","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":910916,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":910917,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mott, Andrea 0000-0001-9586-9590","orcid":"https://orcid.org/0000-0001-9586-9590","contributorId":299367,"corporation":false,"usgs":false,"family":"Mott","given":"Andrea","affiliations":[{"id":64822,"text":"USGS WERC (name not found)","active":true,"usgs":false}],"preferred":false,"id":910918,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mackell, Desmond Alexander 0000-0002-1682-2581","orcid":"https://orcid.org/0000-0002-1682-2581","contributorId":266036,"corporation":false,"usgs":true,"family":"Mackell","given":"Desmond","email":"","middleInitial":"Alexander","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":910919,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":910920,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":910921,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Patil, Vijay P. 0000-0002-9357-194X vpatil@usgs.gov","orcid":"https://orcid.org/0000-0002-9357-194X","contributorId":203676,"corporation":false,"usgs":true,"family":"Patil","given":"Vijay","email":"vpatil@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":910922,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":910923,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Takekawa, John Y. 0000-0003-0217-5907","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":203805,"corporation":false,"usgs":false,"family":"Takekawa","given":"John Y.","affiliations":[{"id":36724,"text":"Audubon California, Richardson Bay Audubon Center and Sanctuary, Tiburon, CA","active":true,"usgs":false}],"preferred":false,"id":910924,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Orthmeyer, Dennis L.","contributorId":343389,"corporation":false,"usgs":false,"family":"Orthmeyer","given":"Dennis","email":"","middleInitial":"L.","affiliations":[{"id":82080,"text":"USDA-APHIS-Wildlife Services","active":true,"usgs":false}],"preferred":false,"id":910925,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pitesky, Maurice E.","contributorId":176920,"corporation":false,"usgs":false,"family":"Pitesky","given":"Maurice","email":"","middleInitial":"E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":910926,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Diaz-Munoz, Samuel L.","contributorId":205103,"corporation":false,"usgs":false,"family":"Diaz-Munoz","given":"Samuel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":910927,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Riggs, Brock M.","contributorId":343390,"corporation":false,"usgs":false,"family":"Riggs","given":"Brock","email":"","middleInitial":"M.","affiliations":[{"id":12711,"text":"UC 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Unlimited","active":true,"usgs":false}],"preferred":false,"id":910931,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Williams, Chris K.","contributorId":343391,"corporation":false,"usgs":false,"family":"Williams","given":"Chris","email":"","middleInitial":"K.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":910932,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Buler, Jeffrey J.","contributorId":194648,"corporation":false,"usgs":false,"family":"Buler","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":910933,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Hardy, Matthew J.","contributorId":343392,"corporation":false,"usgs":false,"family":"Hardy","given":"Matthew J.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":910934,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Ladman, Brian S.","contributorId":337102,"corporation":false,"usgs":false,"family":"Ladman","given":"Brian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":910935,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Legagneux, Pierre","contributorId":337103,"corporation":false,"usgs":false,"family":"Legagneux","given":"Pierre","email":"","affiliations":[],"preferred":false,"id":910936,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Bety, Joel","contributorId":203661,"corporation":false,"usgs":false,"family":"Bety","given":"Joel","email":"","affiliations":[{"id":36676,"text":"Université du Québec à Rimouski","active":true,"usgs":false}],"preferred":false,"id":910937,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Thomas, Philippe J.","contributorId":343393,"corporation":false,"usgs":false,"family":"Thomas","given":"Philippe","email":"","middleInitial":"J.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":910938,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Rodrigue, Jean","contributorId":343394,"corporation":false,"usgs":false,"family":"Rodrigue","given":"Jean","email":"","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":910939,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Lefebvre, Josee","contributorId":343395,"corporation":false,"usgs":false,"family":"Lefebvre","given":"Josee","email":"","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":910940,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":910941,"contributorType":{"id":1,"text":"Authors"},"rank":28}]}} ,{"id":70256591,"text":"70256591 - 2024 - Risk of invasive waterfowl interaction with poultry production: Understanding potential for avian pathogen transmission via species distribution models","interactions":[],"lastModifiedDate":"2024-08-06T12:05:26.727184","indexId":"70256591","displayToPublicDate":"2024-07-18T07:02:10","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Risk of invasive waterfowl interaction with poultry production: Understanding potential for avian pathogen transmission via species distribution models","docAbstract":"Recent outbreaks of highly pathogenic avian influenza have devastated poultry production across the United States, with more than 77 million birds culled in 2022–2024 alone. Wild waterfowl, including various invasive species, host numerous pathogens, including highly pathogenic avian influenza virus (HPAIV), and have been implicated as catalysts of disease outbreaks among native fauna and domestic birds. In major poultry-producing states like Arkansas, USA, where the poultry sector is responsible for significant economic activity (>$4 billion USD in 2022), understanding the risk of invasive waterfowl interactions with domestic poultry is critical. Here, we assessed the risk of invasive waterfowl-poultry interaction in Arkansas by comparing the density of poultry production sites (chicken houses) to areas of high habitat suitability for two invasive waterfowl species, (Egyptian Goose [Alopochen aegyptiaca] and Mute Swan [Cygnus olor]), known to host significant pathogens, including avian influenza viruses. The percentage of urban land cover was the most important habitat characteristic for both invasive waterfowl species. At the 95% confidence interval, chicken house densities in areas highly suitable for both species (Egyptian Goose = 0.91 ± 0.11 chicken houses/km2; Mute Swan = 0.61 ± 0.03 chicken houses/km2) were three to five times higher than chicken house densities across the state (0.17 ± 0.01 chicken houses/km2). We show that northwestern and western Arkansas, both areas of high importance for poultry production, are also at high risk of invasive waterfowl presence. Our results suggest that targeted monitoring efforts for waterfowl-poultry contact in these areas could help mitigate the risk of avian pathogen exposure in Arkansas and similar regions with high poultry production.
The importance of fluvial systems in the transport of sediment, dissolved and suspended contaminants, nutrients, and bacteria through the environment is well established. The U.S. Environmental Protection Agency (EPA) identifies sediment as the single most widespread water contaminant affecting the beneficial uses of the Nation’s rivers and streams. The evaluation of water-quality as it relates to agriculture, urbanization, highway and residential construction, mining, industrial and human wastes, and other activities requires an extensive data and sample-collection effort. This is especially the case when studying urbanized river basins, where during hydrologic events, concentration of suspended sediment and contaminants can vary rapidly and over large ranges. Where synoptic studies of watersheds are called for, sampling may be needed at many sites throughout the basin; a complicated and difficult task in some settings. Automatic pumping samplers (autosamplers) are one method for conducting intensive time-varying sampling throughout watersheds.
This report presents guidelines for the use of autosamplers for collecting surface-water samples by the U.S. Geological Survey. An autosampler is an automatic, pump-based sampler that collects a prescribed volume of water from streams, lakes, reservoirs, storm drains, or other bodies of water after receiving a command from an internal or external control unit. It deposits this sample into a specified container for later analysis of physical, chemical, or biological constituents. This report provides a general background on types of autosamplers and how they work; guidance for designing, selecting, installing, servicing, and calibrating autosamplers; guidance on standardized operating procedures, and guidance on quality-assurance and quality-control efforts when using an autosampler.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm1D12","usgsCitation":"Wilson, T.P., Miller, C.V., and Lechner, E.A., 2024, Guidelines for the use of automatic samplers in collecting surface-water quality and sediment data: U.S. Geological Survey Techniques and Methods 1–D12, 89 p., https://doi.org/10.3133/tm1D12","productDescription":"ix, 89 p.","numberOfPages":"89","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-131202","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":430984,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/01/d12/images/"},{"id":430983,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/01/d12/tm1d12.XML","linkFileType":{"id":8,"text":"xml"},"description":"TM 1-D12 XML"},{"id":430982,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm1D12/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"TM 1-D12 HTML"},{"id":430980,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/01/d12/coverthb.jpg"},{"id":430981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/01/d12/tm1d12.pdf","text":"Report","size":"19.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 1-D12 PDF"}],"contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike Suite 110
Lawrenceville, New Jersey 08648
Compounding changes in climate and human activities stand to increase sediment input to rivers in many landscapes, including via discrete perturbations such as post-fire debris flows. Because sediment supply is a dominant control on river morphology, understanding mountain river responses to sediment regime perturbations is critical to predicting and addressing downstream effects to infrastructure, water security and aquatic habitat. A growing body of literature explores the causes, likelihood, size and composition of post-fire debris flows, but the channel response to these disturbances remains poorly studied. This study used repeat field surveys, time-lapse photographs and pre- and post-disturbance remote sensing datasets to document and analyse space- and time-varying channel response to post-fire debris flows along a steep mountain stream in the Upper Colorado River Basin, USA. Specifically, we evaluated channel morphology and bed composition changes, correlations between channel changes and valley and channel attributes, and the relative importance of spring snowmelt versus summer monsoon events. Several cross-sectional channel change types were observed from lidar a month after post-fire debris-flow events, including channelized and braided incision into deposits, incision into the pre-fire channel bed, bank erosion and no change. Channel changes were most correlated with pre-fire channel width, valley width and unit stream power, and these relationships could be tested in other burned locations to evaluate their transferability. Repeat channel surveys before and after snowmelt indicate rapid recovery and channel narrowing following major sediment disturbances, although sediment deposits remained in the channel margins. Together, these results highlight the importance of field and remote sensing-based channel surveys to improve understanding of, and potential to predict, mountain channel response to compounding climate disturbances.
Driven by the need for integrated management of groundwater (GW) and surface water (SW), quantification of GW–SW interactions and associated contaminant transport has become increasingly important. This is due to their substantial impact on water quantity and quality. In this review, we provide an overview of the methods developed over the past several decades to investigate GW–SW interactions. These methods include geophysical, hydrometric, and tracer techniques, as well as various modeling approaches. Different methods reveal valuable information on GW–SW interactions at different scales with their respective advantages and limitations. Interpreting data from these techniques can be challenging due to factors like scale effects, heterogeneous hydrogeological conditions, sediment variability, and complex spatiotemporal connections between GW and SW. To facilitate the selection of appropriate methods for specific sites, we discuss the strengths, weaknesses, and challenges of each technique, and we offer perspectives on knowledge gaps in the current science.
We recently developed a dynamically coupled hydrological-ocean modeling system that provides seamless coverage across the land-ocean continuum during hurricane-induced compound flooding. This study introduced a local inertial equation and a diagonal flow algorithm to the overland routing of the coupled system’s hydrology model (WRF-Hydro). Using Hurricane Florence (2018) as a test case, the performance of the coupled model was significantly improved, evidenced by its enhanced capability of capturing backwater and increased water level simulation accuracy and stability. With four model experiments, we present a framework to detangle, define, and quantify compound and nonlinear effects. The results revealed that the flood peaks in the lower Cape Fear River Basin and the coastal waters were contributed by inland flooding and storm surge, respectively. These two processes had comparable contributions to the flooding in the Cape Fear River Estuary. The compound effect was identified when the flood levels resulting from the combination of land and ocean processes surpassed those caused by an individual process alone. The compound effect during Hurricane Florence exhibited limited impact on flood peaks, primarily due to the time lag between the peaks of the storm surge and the inland flooding. In the period between the two peaks, the compound effect was salient and significantly impacted the magnitude and variation of the flood level. The nonlinear effect, defined as the difference between the compound flood level and the superposition of storm surge and inland flooding water levels, reduced flood levels in the river channels while increasing flood levels on the floodplain.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR036455","usgsCitation":"Bao, D., Xue, Z.G., and Warner, J.C., 2024, Quantifying compound and nonlinear effects of hurricane-induced flooding using a dynamically coupled hydrological-ocean model: Water Resources Research, v. 60, no. 7, e2023WR036455, 21 p., https://doi.org/10.1029/2023WR036455.","productDescription":"e2023WR036455, 21 p.","ipdsId":"IP-162739","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466982,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr036455","text":"Publisher Index Page"},{"id":465288,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Bao, Daoyang","contributorId":294534,"corporation":false,"usgs":false,"family":"Bao","given":"Daoyang","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":921432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xue, Z. George","contributorId":347342,"corporation":false,"usgs":false,"family":"Xue","given":"Z.","email":"","middleInitial":"George","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":921433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921434,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266310,"text":"70266310 - 2024 - Spatio-temporal distribution of adult Pacific lamprey Entosphenus tridentatus relative to habitat fragmentation","interactions":[],"lastModifiedDate":"2025-05-05T15:22:55.579935","indexId":"70266310","displayToPublicDate":"2024-07-17T10:15:31","publicationYear":"2024","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}},"displayTitle":"Spatio-temporal distribution of adult Pacific lamprey Entosphenus tridentatus relative to habitat fragmentation","title":"Spatio-temporal distribution of adult Pacific lamprey Entosphenus tridentatus relative to habitat fragmentation","docAbstract":"Pacific lamprey (Entosphenus tridentatus), a fish species native to the Pacific Northwest (USA), have distinctive cultural and ecological value but determining their spatial and temporal distribution is challenging due to a general lack systematic monitoring. In this study, we used counts of Pacific lamprey redds to model the probability of occurrence and abundance of Pacific lamprey based on environmental covariates including artificial barriers, assuming higher predicted lamprey redds translates to more suitable spawning habitats. Using generalized linear mixed zero-inflated models, results suggest that Pacific lamprey abundance was generally lower in high gradient streams, further from the ocean. Stream reaches with warmer spring water temperatures and greater historical median spring flows supported higher abundances. Lamprey occurrence was primarily influenced by spring water temperatures and distance from the ocean. We further observed that when streams warm beyond 18°C, confidence intervals around the abundance estimates widen and zero-inflation increases, indicating a decrease in occurrence. One objective of the study was to recommend where barrier removal or restoration should be prioritized to increase passage and thus access to upstream habitats. We considered artificial barriers to primarily influence the probability of occurrence through access. The barrier variable in this model had a negative effect on the probability of lamprey occurrence, but it was not a strong predictor in the model. While we are not able to suggest specific locations that would most benefit barrier removal or improvement based on these model results, we can identify the watersheds with a higher probability to support Pacific lamprey and provide potential additional habitats by improving habitat connectivity. Focusing restoration and/ or removal of barriers on watersheds in the Mid-South region of the Oregon Coast (i.e., Alsea, Siuslaw, Coos, Coquille, and Sixes rivers) with higher habitat suitability could prioritize use of limited funds, increase the probability of benefiting Pacific lamprey, and potentially other native lampreys and migratory (e.g., salmon, steelhead; Oncorhynchus) species. Although this manuscript focuses on the Oregon Coast region, the methods are transferrable to other regions where Pacific lamprey are present.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.4344","usgsCitation":"Anlauf-Dunn, K., Clemens, B.J., Falcy, M.R., and Zambory, C.L., 2024, Spatio-temporal distribution of adult Pacific lamprey Entosphenus tridentatus relative to habitat fragmentation: River Research and Applications, v. 40, no. 10, p. 1940-1953, https://doi.org/10.1002/rra.4344.","productDescription":"15 p.","startPage":"1940","endPage":"1953","ipdsId":"IP-151718","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.6594960692569,\n 46.176607066943575\n ],\n [\n -124.60365099466847,\n 46.176607066943575\n ],\n [\n -124.60365099466847,\n 42.5032728886724\n ],\n [\n -122.6594960692569,\n 42.5032728886724\n ],\n [\n -122.6594960692569,\n 46.176607066943575\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Anlauf-Dunn, Kara J.","contributorId":354379,"corporation":false,"usgs":false,"family":"Anlauf-Dunn","given":"Kara J.","affiliations":[{"id":36223,"text":"Oregon Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":935529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clemens, Benjamin J.","contributorId":195098,"corporation":false,"usgs":false,"family":"Clemens","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":935530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Falcy, Matthew Richard 0000-0002-3332-2239","orcid":"https://orcid.org/0000-0002-3332-2239","contributorId":288500,"corporation":false,"usgs":true,"family":"Falcy","given":"Matthew","email":"","middleInitial":"Richard","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zambory, Courtney L.","contributorId":264754,"corporation":false,"usgs":false,"family":"Zambory","given":"Courtney","email":"","middleInitial":"L.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":935532,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257651,"text":"70257651 - 2024 - New, dated small impacts on the South Polar Layered Deposits (SPLD), Mars, and implications for shallow subsurface properties","interactions":[],"lastModifiedDate":"2024-08-21T13:54:45.150993","indexId":"70257651","displayToPublicDate":"2024-07-17T08:52:47","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"New, dated small impacts on the South Polar Layered Deposits (SPLD), Mars, and implications for shallow subsurface properties","docAbstract":"The Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) imaged two newly formed impact craters on the South Polar Layered Deposits (SPLD) of Mars in 2018 and 2020. These two new craters, the first detected on the SPLD, measure ∼17 m and ∼48 m in diameter. Follow-up observations were conducted with the High Resolution Imaging Science Experiment (HiRISE), showing seasonal and interannual changes, and providing stereo coverage for the production of digital terrain models (DTMs). Mars Climate Sounder (MCS) data were obtained over the region of these new impacts, giving surface temperature information for the time interval before and after the impacts were detected. Taken together, the optical and infrared observations of these sites reveal craters largely consistent with the morphologies of other small, dated impact craters on Mars, and crater ejecta patterns that suggest a more dust/regolith-dominated upper few meters of the SPLD in contrast to mid-latitude buried ice and lobate debris aprons (LDAs). This supports previous conclusions that the SPLD may have an upper surface depleted in water ice relative to the North PLDs, possibly the result of a widespread deflation event.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2024.115977","usgsCitation":"Landis, M., Dundas, C., McEwen, A.S., Daubar, I.J., Hayne, P.O., Byrne, S., Sutton, S.S., Rangarajan, V.G., Tornabene, L.L., Britton, A., and Herkenhoff, K., 2024, New, dated small impacts on the South Polar Layered Deposits (SPLD), Mars, and implications for shallow subsurface properties: Icarus, v. 419, 115977, 14 p., https://doi.org/10.1016/j.icarus.2024.115977.","productDescription":"115977, 14 p.","ipdsId":"IP-153796","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":486917,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.icarus.2024.115977","text":"Publisher Index Page"},{"id":432996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"419","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Landis, Margaret E.","contributorId":176713,"corporation":false,"usgs":false,"family":"Landis","given":"Margaret E.","affiliations":[{"id":25655,"text":"Lunar and Planetary Laboratory, 1629 E. University Blvd., The University of Arizona, Tucson, AZ 85721, United States","active":true,"usgs":false}],"preferred":false,"id":911218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dundas, Colin M. 0000-0003-2343-7224","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":237028,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":911219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daubar, Ingrid J.","contributorId":204233,"corporation":false,"usgs":false,"family":"Daubar","given":"Ingrid","email":"","middleInitial":"J.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":911221,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hayne, Paul O.","contributorId":174125,"corporation":false,"usgs":false,"family":"Hayne","given":"Paul","email":"","middleInitial":"O.","affiliations":[{"id":27365,"text":"NASA Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":911222,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byrne, Shane","contributorId":53513,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911223,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sutton, Sarah S.","contributorId":203706,"corporation":false,"usgs":false,"family":"Sutton","given":"Sarah","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911224,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rangarajan, Vidhya Ganesh","contributorId":303377,"corporation":false,"usgs":false,"family":"Rangarajan","given":"Vidhya","email":"","middleInitial":"Ganesh","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911225,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tornabene, Livio L.","contributorId":203691,"corporation":false,"usgs":false,"family":"Tornabene","given":"Livio","email":"","middleInitial":"L.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911226,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Britton, Andrew","contributorId":343481,"corporation":false,"usgs":false,"family":"Britton","given":"Andrew","email":"","affiliations":[{"id":82100,"text":"Jacobs/NASA Johnson Space Center","active":true,"usgs":false}],"preferred":false,"id":911227,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":206170,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":911228,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70257650,"text":"70257650 - 2024 - Novel quantitative methods to enable multispectral identification of high-purity water ice exposures on Mars using High Resolution Imaging Science Experiment (HiRISE) images","interactions":[],"lastModifiedDate":"2024-08-21T13:50:08.297937","indexId":"70257650","displayToPublicDate":"2024-07-17T08:48:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Novel quantitative methods to enable multispectral identification of high-purity water ice exposures on Mars using High Resolution Imaging Science Experiment (HiRISE) images","docAbstract":"Reliable detection and characterization of water ice on the Martian surface is pivotal to not only understand its present and past climate, but to also provide valuable information on in-situ resource availability and distribution for future human exploration missions. Ice-rich features are currently identified with visible/near-IR (VNIR), thermal IR and radar data. However, their coarse spatial scale sometimes limits confident characterization of small (i.e., meter-scale) icy exposures resulting from recent activity like new impacts. Water ice bearing materials possess weaker spectral characteristics at wavelengths shorter than ∼1030 nm that may be resolved by VNIR imaging instruments like the High Resolution Imaging Science Experiment (HiRISE) and the Colour and Stereo Surface Imaging System (CaSSIS). Our study assesses the spectral capability of HiRISE colour observations to help distinguish high purity water ice exposures from ice-poor materials. We report detailed methodologies for reliable colour characterization of icy surface using unfiltered HiRISE images. We present the first quantitative approach to uniquely characterize high-purity ice-rich materials through spectral shape and spectral parameterization methods at high spatial resolution (∼50 cm/pixel). We also present three spectral parameters to aid detection of pure water ice features, while also providing statistical constraints to enable a quantitative interpretation scheme. Our methods are observed to work well in characterizing and separating ice-rich features uniquely from ice-poor and ferrous materials. However, we do observe that these methods have a lower grain size detection limit of ∼250–300 μm, and may not be able to uniquely separate frosts from ground ice exposures. We also apply these methods to better constrain the composition of bright materials exposed by recent impacts identified in previous surveys, where substantial evidence for ice-bearing materials was previously unavailable. Overall, our work proposes HiRISE colour-based methods as a novel approach for high-resolution multispectral characterization of ice-rich features on the Martian surface, which is of particular value since the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has ceased operations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2023.115849","usgsCitation":"Rangarajan, V.G., Tornabene, L.L., Osinski, G.R., Dundas, C., Beyer, R.A., Herkenhoff, K., Byrne, S., Heyd, R., Seelos, F.P., Munaretto, G., and Dapremont, A., 2024, Novel quantitative methods to enable multispectral identification of high-purity water ice exposures on Mars using High Resolution Imaging Science Experiment (HiRISE) images: Icarus, v. 419, 115849, 16 p., https://doi.org/10.1016/j.icarus.2023.115849.","productDescription":"115849, 16 p.","ipdsId":"IP-154753","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":432995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"419","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rangarajan, Vidhya Ganesh","contributorId":303377,"corporation":false,"usgs":false,"family":"Rangarajan","given":"Vidhya","email":"","middleInitial":"Ganesh","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tornabene, Livio L.","contributorId":203691,"corporation":false,"usgs":false,"family":"Tornabene","given":"Livio","email":"","middleInitial":"L.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osinski, G. 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New York, 347 U.S. 995), established the position of Delaware River Master within the U.S. Geological Survey. In addition, the Decree authorizes the diversion of water from the Delaware River Basin and requires compensating releases from reservoirs owned by New York City to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master provide reports to the Court not less frequently than annually. This report is the 63rd annual report of the River Master of the Delaware River. The report covers the 2016 River Master report year, which is the period from December 1, 2015, to November 30, 2016.
During the report year, precipitation in the upper Delaware River Basin was 38.6 inches or 87 percent of the long-term average. Combined storage remained high (above 80 percent of combined capacity) for much of the year and did not decline below 80 percent of combined capacity until August 2016. The lowest combined storage was 106.406 billion gallons or 39 percent of combined capacity on November 28, 2016. Delaware River Basin Commission Resolution 2016–07 necessitated a basinwide drought watch on November 23, 2016. The drought watch continued through the remainder of the 2016 report year. Delaware River Master operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program. New York City and New Jersey fully complied with the terms of the Decree and, during drought watch conditions, with the Delaware River Basin Commission Resolution 2016–07 terms. Diversions from the Delaware River Basin by New York City and New Jersey fully complied with the Decree. The reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey, on 126 days during the report year. Interim Excess Release Quantity and conservation releases, designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs, were also made during the report year.
Water quality in the Delaware River estuary between the streamgages at Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at several locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites.
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