The lower shoreface, a transitional subaqueous region extending from the seaward limit of the surf zone to beyond the closure depth, serves as a sediment reservoir and pathway in sandy beach environments over annual to millennial time scales. Despite the important role this region plays in shoreline dynamics, the morphodynamics of the lower shoreface remain poorly quantified and understood. To better understand controls on shoreface morphology, here we combine energetics-based suspended sediment transport formulae (Ortiz & Aston 2016) with empirical wave climate data to incorporate temporal complexity in modeled equilibrium profiles and sediment flux rates. The equilibrium shoreface shape computed using a full wave climate is steeper in shallower water and less steep in the deeper reaches compared to profiles computed using single wave characteristics. Using a full wave climate to simulate steady-state morphology will yield steeper profiles in shallow water. Suspended sediment transport rates also vary in direction and magnitude at different equilibrium profile depths and can potentially inform the location of morphodynamic boundaries in the shoreface. Our results reveal how infrequent storm waves affect shoreface slopes, with large events tending to drive sediment onshore in the deeper portions of the profile. This work explores a few ways to add complexity to simple energetics-based frameworks to reproduce empirical bathymetric data more accurately and provides insight toward refining coastal source-to-sink models.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal Sediments 2023, proceedings of the 10th international conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2023","conferenceDate":"April 11-15, 2023","conferenceLocation":"New Orleans, Louisiana, United States","language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0260","usgsCitation":"Gillen, M., Ashton, A.D., Miselis, J.L., Ciarletta, D.J., Wei, E.A., and Sherwood, C.R., 2023, Incorporating wave climate complexity into modeling lower shoreface morphology and transport, in Coastal Sediments 2023, proceedings of the 10th international conference, New Orleans, Louisiana, United States, April 11-15, 2023, p. 2862-2874, https://doi.org/10.1142/9789811275135_0260.","productDescription":"13 p.","startPage":"2862","endPage":"2874","ipdsId":"IP-147824","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":417085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"editors":[{"text":"Wang, Ping","contributorId":78646,"corporation":false,"usgs":false,"family":"Wang","given":"Ping","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":872817,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Royer, Elizabeth","contributorId":305463,"corporation":false,"usgs":false,"family":"Royer","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":872818,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Rosati, Julie D.","contributorId":112486,"corporation":false,"usgs":false,"family":"Rosati","given":"Julie D.","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":872819,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Gillen, Megan 0000-0002-2375-6519","orcid":"https://orcid.org/0000-0002-2375-6519","contributorId":267190,"corporation":false,"usgs":false,"family":"Gillen","given":"Megan","email":"","affiliations":[{"id":55436,"text":"MIT-WHOI Joint Program in Oceanography/Applied Ocean Science & Engineering, Cambridge and Woods Hole, MA, USA","active":true,"usgs":false}],"preferred":false,"id":872692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashton, Andrew D.","contributorId":300047,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":872693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ciarletta, Daniel J. 0000-0002-8555-2239","orcid":"https://orcid.org/0000-0002-8555-2239","contributorId":256700,"corporation":false,"usgs":true,"family":"Ciarletta","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872695,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wei, Emily A. 0000-0003-4008-0933","orcid":"https://orcid.org/0000-0003-4008-0933","contributorId":223488,"corporation":false,"usgs":true,"family":"Wei","given":"Emily","email":"","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872696,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872697,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70244217,"text":"70244217 - 2023 - Guidance for parameterizing post-fire hydrologic models with in situ infiltration measurements","interactions":[],"lastModifiedDate":"2024-06-18T13:52:44.245324","indexId":"70244217","displayToPublicDate":"2023-05-16T07:20:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Guidance for parameterizing post-fire hydrologic models with in situ infiltration measurements","docAbstract":"Wildfire can alter soil-hydraulic properties, often resulting in an increased prevalence of infiltration-excess overland flow and greater potential for debris-flow hazards. Mini disk tension infiltrometers (MDIs) can be used to estimate soil hydraulic properties, such as field-saturated hydraulic conductivity (Kfs) and wetting front potential (Hf), and their spatial variability following wildfire. However, the small (point-scale) footprint of MDI measurements makes it challenging to use these data to parameterize hydrologic models at the hillslope and watershed scales where hydrologic hazards, such as debris flows, initiate. Here, we designed numerical experiments to estimate spatially constant or watershed-scale effective hydrologic parameters (EHPs) that approximate the response of spatially variable hydrologic parameters with distributions derived from MDI measurements at five sites in the southwestern United States. We found that it is possible to define EHPs for both Kfs and Hf based on the MDI measurements that lead to reasonable approximations of run-off hydrographs at the outlets of small watersheds (<1 km2). We found that watershed EHPs are functions of rainfall characteristics, although they are most sensitive to rainfall intensity and relatively less sensitive to the temporal distribution of rainfall. EHPs are lower than the arithmetic mean of the MDI measurements and are better approximated by the median or geometric mean of the MDI measurements, particularly for storms with recurrence intervals of approximately 1 year or less that commonly initiate post-fire debris flows. This work demonstrated that using the proposed upscaling method to estimate watershed-scale EHPs, as opposed to approximating EHPs based on the arithmetic mean of the MDI measurements, improved the ability of a hydrologic model to identify storms that are likely to produce debris flows. Results improved our ability to link point-scale MDI measurements and watershed-scale EHPs in post-fire settings and helped guide our ability to use MDI data to parameterize post-fire hydrologic models.
Since their introduction to North America in the 1980s, research to develop effective control tools for invasive mussels (Dreissena polymorpha and D. rostriformis bugensis) has been ongoing across various research institutions using a range of testing methods. Inconsistencies in experimental methods and reporting present challenges for comparing data, repeating experiments, and applying results. The Invasive Mussel Collaborative established the Toxicity Testing Work Group (TTWG) in 2019 to identify “best practices” and guide development of a standard framework for dreissenid mussel toxicity testing protocols. We reviewed the literature related to laboratory-based dreissenid mussel toxicity tests and determined the degree to which standard guidelines have been used and their applicability to dreissenid mussel testing. We extracted detailed methodology from 99 studies from the peer-reviewed and gray literature and conducted a separate analysis for studies using presettlement and postsettlement mussels. We identified specific components of methods and approaches that could be refined or standardized for dreissenid mussels. These components included species identification, collection methods, size/age class distinction, maintenance practices, testing criteria, sample size, response measures, reporting parameters, exposure methods, and mortality criteria. We consulted experts in the field of aquatic toxicology and dreissenid mussel biology on our proposed. The final recommendations contained in the present review are based on published standard guidelines, methods reported in the published and gray literature, and the expertise of TTWG members and an external panel. In addition, our review identifies research needs for dreissenid mussel testing including improved methods for early–life stage testing, comparative data on life stages and between dreissenid mussel species, inclusion of a reference toxicant, and additional testing of nontarget species (i.e., other aquatic organisms). Environ Toxicol Chem 2023;42:1649–1666. © 2023 His Majesty the King in Right of Canada. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
We trapped, anesthetized, and fit 16 female feral swine (Sus scrofa) with Global Positioning System (GPS) collars in Great Smoky Mountains National Park (GRSM) to develop predictive summer and winter models for more effective population control efforts. Given the highly diverse habitat and topography in GRSM and the spatial extent of our dataset, we employed Step Selection Function (SSF) to evaluate resource selection at the 3rd-order level and Resource Selection Function (RSF) models at the 2nd-order level for both summer and winter seasons. The summer SSF and RSF models suggested relatively similar levels of selection, whereas the winter models differed by method. We created a straightforward consensus model to better visualize the agreement and constraints of each set of models. In summer, feral swine used lower slopes regardless of elevation, especially those closer to human-dominated spaces such as along paved and gravel roadways. In winter, feral swine maintained preference for lower slopes but preferred oak-dominated forest areas and selection for human development was less than in summer. Wildlife managers can use these models to better focus feral swine surveillance and management in GRSM. Managers can identify areas of high use by season and plan control activities that are both accessible and highly efficient. The combination and consensus framework presented here can be applied to other systems where species’ habitat selection may result in incongruous results across different levels of selection or seasons of interest.
During the economic boom of the mid part of the first decade of the 2000s in northwestern Nevada, municipal and housing growth increased use of the water resources of this semi-arid region. In 2008, when the economy slowed, new housing development stopped, and immediate pressure on groundwater resources abated. The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, began a hydrogeologic study of the middle Carson River Basin. The first half of the study reviewed and synthesized previous geologic studies and contributed new datasets that served as a foundation for a three-dimensional, transient numerical model of groundwater and surface-water flow for the middle Carson River Basin extending from Eagle Valley to Churchill Valley. The model can be used to evaluate the effects of proposed alternative management strategies on groundwater sustainability, flows in the Carson River, and routine operation of Lahontan Reservoir and can also provide a basis for basin-wide investigations seeking to quantitatively evaluate the effects of climate change or yet-to-be-determined alternative management strategies.
The middle Carson model was constructed using the U.S. Geological Survey groundwater modeling software MODFLOW-NWT. MODFLOW is widely used groundwater modeling software and is well-suited for evaluating groundwater and surface-water interactions. The model uses 550-feet square grid cells that align with the previously published model for Carson Valley (adjacent upstream valley). Six grid layers with more finely resolved vertical resolution near the perimeter of the active model domain and near surface-water features, compared to other areas of the active model domain, hone the simulated groundwater and surface-water exchanges. In addition to simulating groundwater and surface-water interaction, crop and phreatophyte evapotranspiration, lake evaporation, mountain-front recharge, recharge from irrigation return flows, and groundwater pumping are also simulated. Surface-water flow entering the model domain, including the Carson River, tributary inflow from perennial streams in Eagle Valley, and trans-basin imports through the Truckee Canal (surface water diverted from the Truckee River) are specified according to U.S. Geological Survey streamgage records. Groundwater pumpage and surface-water diversions to 10 agricultural ditches and the managed release from Lahontan Reservoir, at the end of the middle Carson River Basin, are specified according to water-manager records.
The model simulation period extended from 2000 through 2010 (January 1, 2000, to December 31, 2010) using 574 weekly stress periods, with a single steady-state stress period at the beginning of the simulation that establishes initial conditions by approximating average conditions during the transient simulation period. All available observations for this period were used during the model calibration process, performed using automated parameter-estimation software. Calibration targets included observations of groundwater elevations in wells, streamflow, differences in observed streamflow between successive streamgages and actual evapotranspiration from irrigated lands. Among all 5,296 simulated and observed groundwater level pairs, the mean error was 1.42 feet; the mean absolute error, 7.71 feet; and the percent bias was −0.1 percent.
Three alternative management scenarios, run using the entire period of analysis (2000–10), were simulated to improve understanding of the potential effects of (1) loss of irrigated agricultural lands following conversion of water-rights to municipal groundwater rights; (2) reclaiming treated wastewater with induction wells; and (3) exercising permitted but under-utilized groundwater rights. Scenarios 2 and 3 were further explored using two and four subscenarios, respectively. Simulated scenario results ranged from having little effect on the groundwater system relative to a baseline simulation to having spatially extensive and large groundwater-level declines (10 to 20 feet) compared to the baseline simulation. None of the simulated scenarios increased delivery of river flows to Lahontan Reservoir. On the contrary, one of the subscenarios under alternative management scenario 3 led to surface-water delivery shortfalls of more than 10,000 acre-feet per year.
Future model improvements may include an extension of the model simulation period backward and forward in time and directly linking it to the upstream Carson Valley groundwater model. Furthermore, converting this MODFLOW model to a GSFLOW model, which fully integrates groundwater and surface-water flows including precipitation runoff and infiltration, may provide an improved tool for comprehensive management of water-resources in the middle Carson River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235008","collaboration":"Prepared in cooperation withv the Bureau of Reclamation","usgsCitation":"Morway, E.D., Buto, S.G., Niswonger, R.G., and Huntington, J.L., 2023, Assessing potential effects of changes in water use in the middle Carson River Basin with a numerical groundwater-flow model, Eagle, Dayton, and Churchill Valleys, west-central Nevada: U.S. Geological Survey Scientific Investigations Report 2023–5008, 112 p., https://doi.org/10.3133/sir20235008.","productDescription":"Report: xiii, 112 p.; 3 Data Releases","numberOfPages":"112","onlineOnly":"Y","ipdsId":"IP-034336","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":416912,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D3XO1U","text":"Data for the report assessing potential effects of changes in water use in the middle Carson River Basin with a numerical groundwater-flow model, Eagle, Dayton, and Churchill Valleys, west-central Nevada","description":"Morway, E.D., Buto, S.G., and Medina, R.L., 2023, Data for the report assessing potential effects of changes in water use in the middle Carson River Basin with a numerical groundwater-flow model, Eagle, Dayton, and Churchill Valleys, west-central Nevada: U.S. Geological Survey data release, https://doi.org/10.5066/P9D3XO1U."},{"id":416913,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N9FNQZ","text":"MODFLOW-NWT model used to simulate potential effects of changes in water use in the middle Carson River Basin, Eagle, Dayton, and Churchill Valleys, west-central, Nevada","description":"Morway, E.D., Niswonger, R.G., and Buto, S.G., 2023, MODFLOW-NWT model used to simulate potential effects of changes in water use in the middle Carson River Basin, Eagle, Dayton, and Churchill Valleys, west-central, Nevada: U.S. Geological Survey data release, https://doi.org/10.5066/P9N9FNQZ."},{"id":416907,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5008/covrthb.jpg"},{"id":416908,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5008/sir20235008.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":416909,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5008/sir20235008.xml"},{"id":416910,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5008/images"},{"id":416911,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235008/full"},{"id":416921,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P5LJ3P","text":"Data for the report Geologic Framework and Hydrogeology of the middle Carson River basin, Eagle, Dayton, and Churchill Valleys, West-Central Nevada","description":"Maurer, D.K., and Medina, R.L., 2020, Data for the report Geologic Framework and Hydrogeology of the middle Carson River basin, Eagle, Dayton, and Churchill Valleys, West-Central Nevada: U.S. Geological Survey data release, https://doi.org/10.5066/P9P5LJ3P."}],"country":"United States","state":"Nevada","otherGeospatial":"Middle Carson River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120,\n 40.5\n ],\n [\n -120,\n 38\n ],\n [\n -118,\n 38\n ],\n [\n -118,\n 40.5\n ],\n [\n -120,\n 40.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
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Carson City, Nevada 89701
The Middle Rio Grande (MRG) is a dynamic and complex fluvial system where flow and sediment transported from the Upper Rio Grande and MRG tributaries influence the form of the river. How sediment is transported through the MRG is an important planning question as it addresses a wide range of concerns including flood control and river rehabilitation, thus continuous sediment measurements are needed to develop accurate sediment budgets.
Sediment measurement techniques have continued to improve and the advent of sediment surrogates, such as acoustic technology, have proven to be effective options at obtaining more complete spatial and temporal sediment data in larger fluvial systems. Measurements of sediment in shallow, sand bed rivers, like the Rio Grande, are more difficult because of the changing channel morphology and often limited water depth in which to install instrumentation. During the 2019 spring snow-melt runoff season two acoustic techniques were employed on the Rio Grande to evaluate sediment movement. Sediment movement near the bed was calculated by the Integrated Section Surface Difference Over Time version 2 (ISSDOTv2) using swath data collected from a multi-beam sonar. Measurements were made adjacent to U.S. Geological Survey (USGS) gaging stations where near simultaneous measurements were made by the USGS for streamflow, suspended-sediment concentration and gradation, and bed-material gradations. These measurements were conducted at two locations on the Rio Grande, one of the locations was co-located with two side-profiling suspended-sediment acoustic Doppler profilers that had been installed in the fall of 2016. Both a 1 MegaHertz (MHz) and 2 MHz side-profiling suspended-sediment acoustic Doppler instrument were installed on a fixed platform that was co-located with a USGS sediment gage.
The ISSDOTv2 method using multi-beam sonar and the side-profiling acoustic Doppler profilers proved successful in collecting sediment information and compared well with the more traditional sediment measurements, while providing insight into the sediment transport on the MRG because of the increase in spatial and temporal resolution. Overall, there are some limitations of these acoustical techniques, but the additional information gleaned is beneficial in understanding sediment transport in a shallow, sand-bed river, such as the Rio Grande.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","publisher":"SEDHYD","usgsCitation":"AuBuchon, J., Abraham, D., Posner, A., Brown, J., Jackson, T., and Griffiths, R.E., 2023, Acoustic measurements on a shallow, sand-bed river: A case study from the Rio Grande, in Proceedings of SEDHYD 2023, St. Louis, MO, May 8-12, 2023, 15 p.","productDescription":"15 p.","ipdsId":"IP-151841","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":430004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":430003,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/s82.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Mexico","otherGeospatial":"Middle Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.97063461050324,\n 35.069496774475496\n ],\n [\n -106.97063461050324,\n 34.001955073356385\n ],\n [\n -106.52537665281139,\n 34.001955073356385\n ],\n [\n -106.52537665281139,\n 35.069496774475496\n ],\n [\n -106.97063461050324,\n 35.069496774475496\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"AuBuchon, Jonathan","contributorId":256772,"corporation":false,"usgs":false,"family":"AuBuchon","given":"Jonathan","email":"","affiliations":[{"id":51859,"text":"Albuquerque District, United States Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":903437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abraham, David","contributorId":338662,"corporation":false,"usgs":false,"family":"Abraham","given":"David","email":"","affiliations":[{"id":81187,"text":"U.S. Army Corps of Engineers, reitred","active":true,"usgs":false}],"preferred":false,"id":903438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Posner, Ari","contributorId":338663,"corporation":false,"usgs":false,"family":"Posner","given":"Ari","email":"","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":903439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Jeb E. 0000-0001-7671-2379","orcid":"https://orcid.org/0000-0001-7671-2379","contributorId":225088,"corporation":false,"usgs":true,"family":"Brown","given":"Jeb E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":903440,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, Tony","contributorId":338664,"corporation":false,"usgs":false,"family":"Jackson","given":"Tony","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":903441,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Griffiths, Ronald E. 0000-0003-3620-2926 rgriffiths@usgs.gov","orcid":"https://orcid.org/0000-0003-3620-2926","contributorId":162,"corporation":false,"usgs":true,"family":"Griffiths","given":"Ronald","email":"rgriffiths@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":903442,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70251083,"text":"70251083 - 2023 - Named landforms of the World: A geomorphological and physiographic compilation","interactions":[],"lastModifiedDate":"2024-01-22T12:40:58.278113","indexId":"70251083","displayToPublicDate":"2023-05-15T06:37:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17131,"text":"Annals of the AAG","active":true,"publicationSubtype":{"id":10}},"title":"Named landforms of the World: A geomorphological and physiographic compilation","docAbstract":"Prior to the current era of digital geomorphological mapping, global and regional-scale land surface characterization was advanced by qualitative interpretations that relied on human visualization aided by disciplinary knowledge of geophysical processes combined with extensive field study. In the early twentieth century, Fenneman proposed to devise systematic physiographic divisions of the United States and in 1916 produced what is still regarded as an authoritative map of these divisions. His physiographic regions were developed to provide context when describing land surface characteristics of smaller areas using well-known regional characteristics and descriptors. In 1968, geographer Richard E. Murphy published a large-format map of the “Landforms of the World” to fill a gap in the suite of standard classroom maps. In 1990, the British geomorphologist E. M. Bridges published World Geomorphology, providing the first global treatment and description of divisions, provinces, and sections—the same hierarchical land partitioning concepts that Fenneman used decades earlier. In the twenty-first century, geographic information systems (GIS) technologies are nearly ubiquitous, yet neither Murphy’s nor Bridges’s work existed as GIS data. To further illuminate their pioneering work, we (1) recompiled Murphy’s landforms as a spatial combination of modern existing data layers, and (2) used the recompiled Murphy’s landforms as a basis for the boundaries of the divisions, provinces, and sections described by Bridges. Our aggregation yields a new resource, Named Landforms of the World, version 2.0, which provides a reference-level, basemap-quality data layer that can significantly facilitate mapping, assessing, and understanding Earth surface features.
The U.S. Geological Survey Colorado Water Science Center conducts water resource activities in Colorado in cooperation with different entities throughout the State. These activities include extensive data-collection efforts and interpretive studies to address many different issues of concern to Colorado water resource planners, managers, and others. Results are documented in report products and as information served on the internet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/gip223","usgsCitation":"Oden, J.H., 2023, USGS Colorado Water Science Center bookmark: U.S. Geological Survey General Information Product 223, https://doi.org/10.3133/gip223.","productDescription":"1 Plate: 7.01 x 4.30 inches","onlineOnly":"N","ipdsId":"IP-152161","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":416927,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0223/coverthb.jpg"},{"id":416928,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0223/gip223_cropped.pdf","text":"Bookmark","size":"6.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 223"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.0104552084493,\n 40.98555224333222\n ],\n [\n -109.0104552084493,\n 36.95190952352803\n ],\n [\n -102.05476160072392,\n 36.95190952352803\n ],\n [\n -102.05476160072392,\n 40.98555224333222\n ],\n [\n -109.0104552084493,\n 40.98555224333222\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
Timing of seasonal bird migrations is broadly determined by internal biological clocks, which are synchronized by photoperiod, but individuals often refine their migratory timing decisions in response to external factors. Using 11 years of satellite telemetry data, we show that Pacific Barrow’s Goldeneye (Bucephala islandica), at higher latitudes, initiated spring and molt migrations later and fall migration earlier than individuals at lower latitudes. We further show that individuals refined migratory timing in response to interannual variation in environmental conditions. Individual Barrow’s Goldeneye initiated spring migration earlier in years with warmer springs at their overwintering locations and concluded spring migration earlier in years with earlier annual snow melt on their breeding grounds. Because individuals respond to conditions both where they initiate and where they conclude spring migration, our results suggest that Barrow’s Goldeneye update their migratory decisions en route. For all three migrations in their annual cycle, birds delayed initiating migration if they had been captured and tagged prior to that migration. Birds that initiated migration late for their latitude were less likely to include a stopover and completed that migration faster, partially compensating for delayed departures. Our results are consistent with the hypothesis that Barrow’s Goldeneye use a combination of endogenous cues and environmental cues in migratory decision making. Sensitivity to environmental cues suggests that Barrow’s Goldeneye may have behavioural plasticity that is adaptive when faced with ongoing climate change.
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Three genetic diversity indicators, two of which do not require DNA-based assessment, have been proposed for reporting to the Convention on Biological Diversity and other conservation and policy initiatives. These indicators allow an approximation of the status and trends of genetic diversity to inform policy, using existing demographic and geographic information. Application of these indicators has been initiated and here we describe ongoing efforts in calculating these indicators with examples. We specifically describe a project underway to apply these indicators in nine countries, provide example calculations, address concerns of policy makers and implementation challenges, and describe a roadmap for further development and deployment, incorporating feedback from the broader community. We also present guidance documents and data collection tools for calculating indicators. We demonstrate that Parties can successfully and cost-effectively report these genetic diversity indicators with existing biodiversity observation data, and, in doing so, better conserve the Earth's biodiversity.","language":"English","publisher":"Wiley","doi":"10.1111/conl.12953","usgsCitation":"Hoban, S.M., da Silva, J.M., Mastretta-Yanes, A., Grueber, C.E., Heuertz, M., Hunter, M., Mergeay, J., Paz-Vinas, I., Fukaya, K., Ishihama, F., Jordan, R., Koppa, V., Latorre-Cardenas, M.C., MacDonald, A.J., Rincon-Parra, V., Sjogren-Gulve, P., Tani, N., Thurfjell, H., and Laikre, L., 2023, Monitoring status and trends in genetic diversity for the Convention on Biological Diversity: An ongoing assessment of genetic indicators in nine countries: Conservation Letters, v. 16, no. 3, e12953, 12 p., https://doi.org/10.1111/conl.12953.","productDescription":"e12953, 12 p.","ipdsId":"IP-145577","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research 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demography of coastal Cactus Wrens (Campylorhynchus brunneicapillus) in San Diego County, California—2022 data summary","docAbstract":"We surveyed for coastal Cactus Wren (Campylorhynchus brunneicapillus) in 507 established plots in San Diego County in 2022, encompassing 4 genetic clusters (Otay, Lake Jennings, Sweetwater/Encanto, and San Pasqual). Two surveys were completed at each plot between March 1 and July 31. Cactus Wrens were detected in 214 plots (42 percent of plots). Cactus Wrens were detected in 31 percent of plots that have been consistently surveyed since 2020, indicating less plot occupancy than in 2021 (34 percent) and 2020 (35 percent). There were 202 Cactus Wren territories detected across all survey plots in 2022. In plots that have been consistently surveyed since 2020, we documented 94 territories, which is a decrease from 113 territories in 2021 and 109 in 2020. The number of territories declined from 2021 to 2022 in the Lake Jennings and Otay genetic clusters but remained virtually the same in the Sweetwater/Encanto genetic cluster. At least 78 percent of Cactus Wren territories were occupied by pairs, and 134 fledglings were observed in 2022.
We observed 24 banded Cactus Wrens in 2022, 20 of which we could identify individually by band combination. Adults of known age ranged from 3 to at least 7 years old. All individually identifiable adult Cactus Wrens remained on the same territory in 2022 that they occupied in 2021, and we detected no movement of banded Cactus Wrens between genetic clusters.
Vegetation at Cactus Wren survey plots was dominated by coastal sage scrub shrubs, such as California sagebrush (Artemisia californica), California buckwheat (Eriogonum fasciculatum), lemonadeberry (Rhus integrifolia), jojoba (Simmondsia chinensis), and San Diego sunflower (Bahiopsis laciniata). No definitive signs of fungal pathogens were observed on cactus within and around survey plots. Blue elderberry (Sambucus nigra ssp. caerulea) was detected at 39 percent of plots, and Cactus Wrens occupied proportionally more plots with elderberry than plots without elderberry. Very little dead or unhealthy cactus was observed within all survey plots, and the plots that were occupied by Cactus Wrens were likely to contain fewer dead cactus than plots that were not occupied by Cactus Wrens. Almost 80 percent of plots had more than 5 percent of cactus crowded or overtopped by vines and shrubs. Similar to 2020, Cactus Wrens occupied proportionally more plots with 5 percent or less of cactus crowded or overtopped by vines and shrubs, although this pattern was not observed in 2021. Non-native annual cover was less prevalent in survey plots in 2022 than in 2021, and Cactus Wrens did not preferentially occupy survey plots with 5 percent or less non-native annual cover than plots with more non-native cover.
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Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Knowing subsurface drainage (tile-drain) extent is integral to understanding how landscapes respond to precipitation events and subsequent days of drying, as well as how soil characteristics and land management influence stream response. Consequently, a time series of tile-drain extent would inform one aspect of land management that complicates our ability to explain streamflow and water-quality as a function of climate variability or conservation management. We trained a UNet machine-learning model, a convolutional neural network designed to highlight objects of interest within an image, to delineate tile-drain networks in panchromatic satellite imagery without additional data on soils, topography, or historical tile-drain extent. This was done by training the model to match the accuracy of human experts manually tracing the surface representation of tile drains in satellite imagery. Our approach began with a library of images that were used to train and quantify the accuracy of the model, with model performance tested on imagery from two areas that were not used to train the model. Satellite imagery included acquisition dates from 2008 to 2020. Training imagery was from agricultural areas within the US Great Lakes basin. Validation imagery was from the upper Maumee River, tributary to western Lake Erie, and an Indiana, Ohio-River headwater tributary. Our analysis of the satellite imagery paired with meteorological and soil data found that during spring, a combination of relatively high solar radiation, intermediate soil-water content and bare fields enabled the best model performance. Each area of interest was heavily tile-drained, where better understanding the movement of water, nutrients, and sediment from fields to downstream water bodies is key to managing harmful algal blooms and hypoxia. The trained UNet model successfully identified tile drains visible in the validation imagery with an accuracy of 93%–96% and balanced accuracy of 52%–54%, similar to performance for training data (95% and 63%, respectively). Model performance will benefit from ongoing contributions to the training library.
This paper describes the results of a study that was done by the USGS to assess recent (2017) water availability, forecast long-term trends in water availability, assess changes in water availability, and forecast future water availability in the Trinity River Basin in Texas. The Trinity River Basin surface water model and Trinity River alluvium aquifer (TRAA) groundwater model were created to evaluate future conditions under different global climate models (GCM). The results of this study show minimal overall changes in water availability for both surface water and groundwater. Trend analyses using historical data (1900–2017) indicated an increase of annual precipitation on the watersheds that drain into the reservoirs in Regional Water Planning Group C. However, the Trinity River Basin surface water model GCM ensemble mean annual precipitation indicates a downward trend, resulting in a downward trend in surface runoff. Additionally, the GCM ensemble mean for the Trinity River Basin surface water model and the TRAA groundwater model both indicate a downward trend in recharge while the TRAA model GCM ensemble mean indicates an upward trend in the amount of groundwater leaving the aquifer to rivers and streams resulting in an upward trend of cumulative storage change.
","language":"English","publisher":"Texas Water Journal","doi":"10.21423/twj.v14i1.7146","usgsCitation":"Milmo, M.J., McDowell, J., Yesildirek, M.V., and Harwell, G.R., 2023, The use of historical data and global climate models to assess historical and future surface water and groundwater availability in the Trinity River Basin in Texas: Texas Water Journal, v. 14, p. 34-61, https://doi.org/10.21423/twj.v14i1.7146.","productDescription":"28 p.","startPage":"34","endPage":"61","ipdsId":"IP-126619","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":443587,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.21423/twj.v14i1.7146","text":"Publisher Index Page"},{"id":435342,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BVOEJ3","text":"USGS data release","linkHelpText":"Hydrologic simulations using projected climate data as input to the Precipitation-Runoff Modeling System (PRMS) for the Trinity River Basin Integrated Water Availability Assessment, Texas, 2023"},{"id":435341,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XO5F9G","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to assess historical and future trends in groundwater availability in the Trinity River alluvium aquifer, Texas"},{"id":416955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Trinity River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.0568823566713,\n 29.605130308347057\n ],\n [\n -94.82111695509118,\n 29.47268831477325\n ],\n [\n -94.56341988824927,\n 29.61102156169673\n ],\n [\n -94.98560444456466,\n 31.578939128932277\n ],\n [\n -95.40230608456515,\n 32.304435780613815\n ],\n [\n -95.72579814719658,\n 32.762064472265905\n ],\n [\n -95.93963188351171,\n 33.33195284298357\n ],\n [\n -96.42212851930111,\n 33.574406176811095\n ],\n [\n -97.90799884087924,\n 33.77061473287188\n ],\n [\n -98.1218325771938,\n 33.49213956579713\n ],\n [\n -97.53516053140494,\n 32.558961831908476\n ],\n [\n -96.68530850245952,\n 32.141316395990245\n ],\n [\n -96.30698727667026,\n 31.217473563861276\n ],\n [\n -95.89576855298657,\n 30.48316869632812\n ],\n [\n -95.23781859509266,\n 29.709952489208263\n ],\n [\n -95.0568823566713,\n 29.605130308347057\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","edition":"1","noUsgsAuthors":false,"publicationDate":"2023-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Milmo, Molly J. 0000-0001-9074-0982","orcid":"https://orcid.org/0000-0001-9074-0982","contributorId":245854,"corporation":false,"usgs":true,"family":"Milmo","given":"Molly","email":"","middleInitial":"J.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDowell, Jeremy 0000-0002-8132-9806","orcid":"https://orcid.org/0000-0002-8132-9806","contributorId":221296,"corporation":false,"usgs":true,"family":"McDowell","given":"Jeremy","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872224,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yesildirek, Monica Veale 0000-0002-0320-8531","orcid":"https://orcid.org/0000-0002-0320-8531","contributorId":228880,"corporation":false,"usgs":true,"family":"Yesildirek","given":"Monica","email":"","middleInitial":"Veale","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872225,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harwell, Glenn R. 0000-0003-4265-2296","orcid":"https://orcid.org/0000-0003-4265-2296","contributorId":205197,"corporation":false,"usgs":true,"family":"Harwell","given":"Glenn","email":"","middleInitial":"R.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872226,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70243602,"text":"70243602 - 2023 - Plant migration due to winter climate change: Range expansion of tropical invasive plants in response to warming winters","interactions":[],"lastModifiedDate":"2023-07-24T16:51:21.074256","indexId":"70243602","displayToPublicDate":"2023-05-10T09:46:45","publicationYear":"2023","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":"Plant migration due to winter climate change: Range expansion of tropical invasive plants in response to warming winters","docAbstract":"Warming winters due to climate change can facilitate the range expansion of invasive non-native species. In the southeastern United States, the frequency and intensity of extreme winter temperatures determines the northern range limits of many tropical organisms including many species of invasive non-native plants. However, the effects of winter climate change on invasive species’ range limits have been understudied. Here, we used temperature and species occurrence data to examine the sensitivity of invasive tropical plant species to freezing temperatures. We also examined the potential for northward range expansion of these species due to winter climate change. From an initial group of 81 invasive plant species selected due to their ability to transform native plant communities, our analyses identify and quantify species-specific temperature thresholds for 40 tropical, cold sensitive species. Future winter warming scenarios indicate that these tropical invasive plant species have the potential for northward range expansion across the southeastern United States in response to small changes in the severity of winter cold temperature extremes. The potential for range expansion is greatest in coastal areas, which typically have warmer temperatures than inland counterparts. Thus, coastal regions are likely to serve as biological invasion hotspots from which invasive species expand into inland areas. The state of Florida has become a global hotspot for biological invasions, with tens of millions of dollars (US) spent annually to control the ecological and societal impacts of invasive plants on publicly held conservation lands. Collectively, our results underscore the need to better anticipate and prepare for the northward range expansion of invasive plants from Florida into the southeastern United States in response to winter climate change.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-023-03075-7","usgsCitation":"Osland, M., Chivoiu, B., Feher, L., Dale, L., Lieurance, D., Daniel, W., and Spencer, J.E., 2023, Plant migration due to winter climate change: Range expansion of tropical invasive plants in response to warming winters: Biological Invasions, v. 25, p. 2813-2830, https://doi.org/10.1007/s10530-023-03075-7.","productDescription":"18 p.","startPage":"2813","endPage":"2830","ipdsId":"IP-145305","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":417030,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, South 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data","interactions":[],"lastModifiedDate":"2023-05-17T13:49:27.788978","indexId":"70243688","displayToPublicDate":"2023-05-10T08:48:03","publicationYear":"2023","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":"Exploring the influence of input feature space on CNN-based geomorphic feature extraction from digital terrain data","docAbstract":"Many studies of Earth surface processes and landscape evolution rely on having accurate and extensive data sets of surficial geologic units and landforms. Automated extraction of geomorphic features using deep learning provides an objective way to consistently map landforms over large spatial extents. However, there is no consensus on the optimal input feature space for such analyses. We explore the impact of input feature space for extracting geomorphic features from land surface parameters (LSPs) derived from digital terrain models (DTMs) using convolutional neural network (CNN)-based semantic segmentation deep learning. We compare four input feature space configurations: (a) a three-layer composite consisting of a topographic position index (TPI) calculated using a 50 m radius circular window, square root of topographic slope, and TPI calculated using an annulus with a 2 m inner radius and 10 m outer radius, (b) a single illuminating position hillshade, (c) a multidirectional hillshade, and (d) a slopeshade. We test each feature space input using three deep learning algorithms and four use cases: two with natural features and two with anthropogenic features. The three-layer composite generally provided lower overall losses for the training samples, a higher F1-score for the withheld validation data, and better performance for generalizing to withheld testing data from a new geographic extent. Results suggest that CNN-based deep learning for mapping geomorphic features or landforms from LSPs is sensitive to input feature space. Given the large number of LSPs that can be derived from DTM data and the variety of geomorphic mapping tasks that can be undertaken using CNN-based methods, we argue that additional research focused on feature space considerations is needed and suggest future research directions. We also suggest that the three-layer composite implemented here can offer better performance in comparison to using hillshades or other common terrain visualization surfaces and is, thus, worth considering for different mapping and feature extraction tasks.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023EA002845","usgsCitation":"Maxwell, A.E., Odom, W.E., Shobe, C.M., Doctor, D.H., Bester, M.S., and Ore, T., 2023, Exploring the influence of input feature space on CNN-based geomorphic feature extraction from digital terrain data: Earth and Space Science, v. 10, no. 5, e2023EA002845, 25 p., https://doi.org/10.1029/2023EA002845.","productDescription":"e2023EA002845, 25 p.","ipdsId":"IP-150908","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":443593,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023ea002845","text":"Publisher Index Page"},{"id":417130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Maxwell, Aaron E.","contributorId":305483,"corporation":false,"usgs":false,"family":"Maxwell","given":"Aaron","email":"","middleInitial":"E.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":872914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Odom, William E. 0000-0001-8577-5056","orcid":"https://orcid.org/0000-0001-8577-5056","contributorId":292616,"corporation":false,"usgs":true,"family":"Odom","given":"William","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":872915,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shobe, Charles M.","contributorId":305484,"corporation":false,"usgs":false,"family":"Shobe","given":"Charles","email":"","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":872917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":872918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bester, Michelle S.","contributorId":305485,"corporation":false,"usgs":false,"family":"Bester","given":"Michelle","email":"","middleInitial":"S.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":872920,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ore, Tobi","contributorId":305487,"corporation":false,"usgs":false,"family":"Ore","given":"Tobi","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":872921,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70243953,"text":"70243953 - 2023 - Evaluation of Copernicus DEM and comparison to the DEM used for Landsat collection-2 processing","interactions":[],"lastModifiedDate":"2023-06-12T21:50:00.086818","indexId":"70243953","displayToPublicDate":"2023-05-10T07:04:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of Copernicus DEM and comparison to the DEM used for Landsat collection-2 processing","docAbstract":"High interannual variability of forage production in semiarid grasslands leads to uncertainties when livestock producers make decisions, such as buying additional feed, relocating animals, or using flexible stocking. Within-season predictions of annual forage production (i.e., yearly production) can provide specific boundaries for producers to make these decisions with more information and possibly with higher confidence. In this study, we use a recently developed forage production model, ForageAhead, that uses environmental and seasonal climate variables to estimate the annual forage production as approximated by remotely sensed vegetation data. Because, among other variables, this model uses observed summer climate data, the model output cannot be produced early enough in the year (e.g., spring months) to inform within-season management decisions. To address this issue, we developed summer climate scenarios (e.g., extremely warm and dry and moderately cool and wet) that serve as an input in the model in combination with observed winter and spring climate data from a particular year. The summer climate scenarios used historical summer precipitation and temperature data (1950–2018) categorized into three, five, and seven percentile categories. These percentile values were then combined to represent summer climate scenarios, which were further used as the ForageAhead model input. We tested the optimal number of percentile categories to be used as the model input to obtain accurate prediction of forage production while also minimizing the number of possible temperature and precipitation combinations, which increases with the number of percentile categories. For the 19-year period analysis (2000–2018), we also determined the most and least common scenarios that occurred in the western United States. When using five percentile categories for summer precipitation and temperature, we were able to capture the interannual variability in the spatial extent of abnormally low and high biomass production. The ForageAhead predictions captured similar spatial patterns of forage anomalies as another similar model (Grass-Cast). This method can be made available in a user-friendly automated system that can be used by livestock producers and rangeland managers to inform within-season management decisions. This method can be especially valuable for flexible stocking as it provides a range of possible annual forage production scenarios by the end of May.
Sex ratio, and the extent to which it varies over time, is an important factor in the demography, management, and conservation of wildlife populations. Greater sage-grouse Centrocercus urophasianus populations in western North America are monitored using counts of males at leks in spring. Population estimates derived from lek-count data typically assume a constant, female-biased sex ratio, yet few rigorous, empirically derived estimates of sex ratio are available to test that assumption. We estimated pre-breeding sex ratio of greater sage-grouse in a peripheral, geographically isolated population in northwestern Colorado during two consecutive winters using closed-population, robust-design, multi-state, genetic mark–recapture models in program MARK. Sex ratio varied markedly between years, with estimates of 3.29 (95% CI: 2.36–4.59) females per male in winter 2012–2013 and 1.54 (95% CI: 1.22–1.95) females per male in winter 2013–2014. Rather than assuming a constant sex ratio, biologists should consider the potential for large annual variation in sex ratio of greater sage-grouse populations when estimating population size or trend from male lek-count data.
The idea of mining the Moon, once purely science-fiction, is now on the verge of becoming reality. Taking advantage of the resources on the Moon is part of the plans of many nations and some enterprising commercial entities; demonstrating in-situ (in place) resource utilization near the lunar south pole is an explicit goal of the United States’ Artemis program. Economic extraction and sustainable management of these resources require understanding the nature, quantity, and quality of each resource. This publication aims to provide a relatively simple, but technically rigorous, assessment of the status of lunar resource exploration in 2022.
Building on the experience of the U.S. Geological Survey in conducting resource assessments for Earth, we propose a general methodology for quantitative lunar resources assessments. Lunar resources can be categorized as energy, mineral, and water and classified with respect to their certainty and their recoverability. The portion of the technically recoverable resource that can be converted to a commodity within budgetary and other mission constraints can be classified as a “reserve.”
For energy resources, solar energy is known to be especially abundant along some high ridges near the lunar poles and the technology to exploit it is mature. Mineral resources, largely in the form of loose rock powder that covers the surface of the Moon, are also widely accessible in large quantities. Many different technologies to convert this material into useful commodities (such as landing pads and oxygen) are currently being developed and are likely to be available for industrial-scale application within 30 years. Water ice almost certainly exists in the polar regions of the Moon but there are fundamental unanswered questions about when and how the ice formed—leaving us without knowledge of the form, quantity, quality, and distribution of lunar ice. Until rover missions bring new ground truth data, lunar ice will remain a highly speculative resource that may be both limited and non-renewable.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1507","usgsCitation":"Keszthelyi, L.P., Coyan, J.A., Bennett, K.A., Ostrach, L.R., Gaddis, L.R., Gabriel, T.S.J., and Hagerty, J., 2023, Assessment of lunar resource exploration in 2022: U.S. Geological Survey Circular 1507, 23 p., https://doi.org/10.3133/cir1507.","productDescription":"iv, 23 p.","numberOfPages":"23","onlineOnly":"N","ipdsId":"IP-132347","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":416826,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1507/cir1507.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":416825,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1507/covrthb.jpg"}],"contact":"Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
The recent development of animal-borne sensors coupled with location data can provide insights into how individuals modify their behaviour with respect to specific habitat features. Animals can express a diverse array of behaviours as they navigate heterogenous landscapes, yet few studies have specifically evaluated the interaction of behaviours with habitat characteristics. We used a novel broadcast acoustic transmitter to investigate the interaction between vocal behaviours of an endemic Hawaiian thrush, the ʻōmaʻo, Myadestes obscurus, and habitat features across a naturally fragmented forest landscape. Through the development of behavioural landscape models that link specific vocalizations with space use, we found that the use of different vocalization types (calls, songs, whisper songs) were highly variable across the landscape but were associated with distinct habitat features. The likelihood of calls increased in an open lava matrix between forest patches, while whisper songs were more strongly associated with the dense interior areas of forest fragments. In contrast, the rate of ʻōmaʻo vocalizations overall decreased in the open lava matrix, suggesting that ʻōmaʻo may shift behaviours from territory defence to foraging as they transition through different habitats. Our study revealed context-specific changes in behaviour across ʻōmaʻo home ranges, including courtship, aggression and social interactions between individuals. Combining the use of a novel acoustic tool with automated radiotelemetry allowed us to overcome challenges associated with detection and analysis of variation in behaviour and resource selection across a highly heterogeneous landscape that would have been otherwise difficult to impossible.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.anbehav.2023.04.006","usgsCitation":"Netoskie, E.C., Paxton, K.L., Paxton, E.H., Asner, G.P., and Hart, P.J., 2023, Linking vocal behaviours to habitat structure to create behavioural landscapes: Animal Behaviour, v. 201, p. 1-11 p., https://doi.org/10.1016/j.anbehav.2023.04.006.","productDescription":"11 p.","startPage":"1","endPage":"11 p.","ipdsId":"IP-136322","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":443605,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.anbehav.2023.04.006","text":"Publisher Index Page"},{"id":420907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Hawaii, Mauna Loa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.58292548105314,\n 19.5421499770886\n ],\n [\n -155.58292548105314,\n 19.33132215765302\n ],\n [\n -155.42705047437903,\n 19.33132215765302\n ],\n [\n -155.42705047437903,\n 19.5421499770886\n ],\n [\n -155.58292548105314,\n 19.5421499770886\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"201","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Netoskie, Erin C","contributorId":329790,"corporation":false,"usgs":false,"family":"Netoskie","given":"Erin","email":"","middleInitial":"C","affiliations":[{"id":37485,"text":"University of Hawai‘i - Hilo","active":true,"usgs":false}],"preferred":false,"id":883317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paxton, Kristina L. 0000-0003-2321-5090","orcid":"https://orcid.org/0000-0003-2321-5090","contributorId":41917,"corporation":false,"usgs":false,"family":"Paxton","given":"Kristina","email":"","middleInitial":"L.","affiliations":[{"id":12981,"text":"Department of Biological Sciences, University of Southern Mississippi","active":true,"usgs":false},{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":883318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":883319,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Asner, Gregory P.","contributorId":25393,"corporation":false,"usgs":false,"family":"Asner","given":"Gregory","email":"","middleInitial":"P.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":883320,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hart, Patrick J.","contributorId":147728,"corporation":false,"usgs":false,"family":"Hart","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":883321,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70246240,"text":"70246240 - 2023 - Geology along the Yuba Pass and Highway 70 corridors: A complex history of tectonics and magmatism in the northern Sierra Nevada","interactions":[],"lastModifiedDate":"2023-06-28T15:02:00.624756","indexId":"70246240","displayToPublicDate":"2023-05-09T10:01:09","publicationYear":"2023","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geology along the Yuba Pass and Highway 70 corridors: A complex history of tectonics and magmatism in the northern Sierra Nevada","docAbstract":"This field trip traverses a cross section of northern Sierra Nevada geology and landscape along two major corridors, Highway 49 (Yuba Pass) and Highway 70. These highways, and adjacent roadways, offer roadcuts, outcrops, and overviews through diverse pre-Cenozoic metamorphic rocks along the Laurentian margin, Mesozoic batholithic rocks, and Miocene volcanic rocks. Observing this array of rocks on a single trip provides an opportunity to examine the progression of tectonic forces in this region since the Paleozoic Era. Inspiration for this trip is a 1:100,000-scale geologic map and geophysical maps of the Portola 30′ × 60′ quadrangle that integrate decades of published and unpublished mapping with new geophysical data. The quadrangle map will seamlessly depict a geologically complex region along the boundary between the Sierra Nevada and Basin and Range provinces, dominated by transtensional tectonics of the Walker Lane. This field trip highlights many of the major units of the geologic map and will also feature new geochronological data on plutonic rocks.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Field excursions to the northern Sierra Nevada of California, the mining districts of the Sierra Nevada, and Cretaceous and Paleocene sediments in Maryland, USA","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2023.0065(02)","usgsCitation":"Roberts, M., Langenheim, V., Schweickert, R.A., and Hanson, R., 2023, Geology along the Yuba Pass and Highway 70 corridors: A complex history of tectonics and magmatism in the northern Sierra Nevada, chap. of Field excursions to the northern Sierra Nevada of California, the mining districts of the Sierra Nevada, and Cretaceous and Paleocene sediments in Maryland, USA, v. 65, p. 21-35, https://doi.org/10.1130/2023.0065(02).","productDescription":"15 p.","startPage":"21","endPage":"35","ipdsId":"IP-148535","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":418588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"northern Sierra Nevada, Yuba Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121,\n 40\n ],\n [\n -121,\n 39.5\n ],\n [\n -120,\n 39.5\n ],\n [\n -120,\n 40\n ],\n [\n -121,\n 40\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"65","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, Michelle 0000-0003-4387-6574","orcid":"https://orcid.org/0000-0003-4387-6574","contributorId":216218,"corporation":false,"usgs":true,"family":"Roberts","given":"Michelle","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":876374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langenheim, Victoria 0000-0003-2170-5213","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":221236,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":876375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schweickert, Richard A.","contributorId":310423,"corporation":false,"usgs":false,"family":"Schweickert","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":876376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Richard E.","contributorId":315377,"corporation":false,"usgs":false,"family":"Hanson","given":"Richard E.","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":876377,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255245,"text":"70255245 - 2023 - Diverse migratory portfolios drive inter-annual switching behavior of elk across the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2024-06-13T12:25:42.960467","indexId":"70255245","displayToPublicDate":"2023-05-09T07:15:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Diverse migratory portfolios drive inter-annual switching behavior of elk across the Greater Yellowstone Ecosystem","docAbstract":"A growing body of evidence shows that some ungulates alternate between migratory and nonmigratory behaviors over time. Yet it remains unclear whether such short-term behavioral changes can help explain reported declines in ungulate migration worldwide, as opposed to long-term demographic changes. Furthermore, advances in tracking technology reveal that a simple distinction between migration and nonmigration may not sufficiently describe all individual behaviors. To better understand the dynamics and drivers of ungulate switching behavior, we investigated 14 years of movement data from 361 elk in 20 herds across the Greater Yellowstone Ecosystem (GYE). First, we categorized yearly individual behaviors using a clustering algorithm that identified similar migratory tactics across a continuum of behaviors. Then, we tested seven hypotheses to explain why some ungulates switch behaviors, and we evaluated how behavioral changes affected the proportions of different behaviors across the system. We identified four distinct behavioral tactics: residents (4.8% of elk-years), short-distance migrants (53.7%), elevational migrants (21.9%) and long-distance migrants (19.6%). Of the 20 herds, 18 were partially migratory, and 5 had all four movement tactics present. We observed switches between migratory tactics in all sets of consecutive years during our study period, with an average of 22.5% of individual elk changing movement tactics from one year to the next. Elk in herds with higher movement tactic diversity were significantly more likely to switch tactics and often responded more effectively to adverse environmental conditions, compared to those in herds with low movement tactic diversity. During our study period, switching increased the prevalence of both short- and long-distance migrants, decreased the prevalence of elevational migrants, and had no effect on the prevalence of residents. Our findings suggest that rather than contributing to the declining migratory behavior found in the GYE, switching behavior may enable greater resiliency to continuously changing environmental and anthropogenic conditions.
Accurate knowledge of the speed at which water moves along a river is essential for understanding ecohydraulic processes and managing natural resources. Measuring flow velocity via remote sensing can be more efficient than conventional field methods, and powerful computational techniques for inferring velocity fields from videos or image time series have been developed. The development of dedicated software tools for particle image velocimetry (PIV) could facilitate greater use of these methods by the river community. This paper introduces a standalone app designed for this exact purpose: the Toolbox for River Velocimetry using Images from Aircraft, or TRiVIA. The program provides a complete workflow for producing spatially distributed velocity vectors from a video or sequence of images, all within an accessible graphical user interface. TRiVIA includes modules for extracting and resampling frames, stabilization and geo-referencing images, defining a region of interest, enhancing images, performing PIV with an efficient ensemble correlation algorithm, visualizing results, assessing accuracy assessment, and exporting PIV output. We illustrate the software's capabilities using an example data set from a large river in Alaska. The initial release of the toolbox is now freely available. Augmenting TRiVIA to incorporate bathymetric information could enable discharge calculation functionality.