The clade comprising the soricid tribes Blarinellini (Blarinella) and Blarinini (Blarina and Cryptotis) is notable within the Soricidae (Eulipotyphla) for the large proportion of reportedly semifossorial species. To better define locomotor modes among species in these two tribes, we quantified purported locomotor adaptations by calculating 23 functional indices from postcranial measurements obtained from museum specimens of Blarina and Blarinella and published measurements for 16 species of Cryptotis. We then analyzed relative ambulatory–fossorial function of each species using principal component analyses and mean percentile rank (MPR) analysis of the indices. Species within the Blarinellini–Blarinini clade exhibit a graded series of morphologies with four primary functional groupings that we classified as “ambulatory,” “intermediate,” “semifossorial,” and “fossorial.” To obtain a preliminary overview of evolution of locomotor modes in this group, we mapped MPRs on a composite phylogeny and examined the resulting patterns. That analysis revealed that the most recent common ancestor of the Blarinellini–Blarinini clade most likely had an intermediate or semifossorial locomotor morphology. Individual subclades subsequently evolved either more ambulatory or more fossorial morphologies. Hence, evolution of locomotor traits within this clade is complex. Multiple shifts in locomotor mode likely occurred, and no single directional tendency is apparent either among the major modes or in levels of complexity.
","language":"English","publisher":"Oxford Academic Press","doi":"10.1093/jmammal/gyz098","usgsCitation":"Woodman, N., and Wilken, A.T., 2019, Comparative functional skeletal morphology among three genera of shrews: Implications for the evolution of locomotor behavior in the Soricinae (Eulipotyphla: Soricidae): Journal of Mammalogy, v. 100, no. 6, p. 1750-1764, https://doi.org/10.1093/jmammal/gyz098.","productDescription":"15 p.","startPage":"1750","endPage":"1764","ipdsId":"IP-108146","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458923,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyz098","text":"Publisher Index Page"},{"id":370666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":778388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilken, Alec T.","contributorId":217703,"corporation":false,"usgs":false,"family":"Wilken","given":"Alec","email":"","middleInitial":"T.","affiliations":[{"id":39687,"text":"University of Missouri, Columbia","active":true,"usgs":false}],"preferred":false,"id":778389,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70205733,"text":"fs20193053 - 2019 - Assessment of coal resources and reserves in the Little Snake River coal field and Red Desert assessment area, Greater Green River Basin, Wyoming","interactions":[],"lastModifiedDate":"2022-04-19T21:19:35.302655","indexId":"fs20193053","displayToPublicDate":"2019-12-19T11:00:00","publicationYear":"2019","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":"2019-3053","displayTitle":"Assessment of Coal Resources and Reserves in the Little Snake River Coal Field and Red Desert Assessment Area, Greater Green River Basin, Wyoming","title":"Assessment of coal resources and reserves in the Little Snake River coal field and Red Desert assessment area, Greater Green River Basin, Wyoming","docAbstract":"The assessment of the Little Snake River coal field and Red Desert area covers approximately 2,300 square miles in the eastern portion of the Greater Green River Basin in south-central Wyoming. Coal-bearing formations are present throughout the Eocene, Paleocene, and Cretaceous strata in the assessment area. Paleogene-age coal beds are present in the Eocene Wasatch Formation and Paleocene Fort Union Formation. Cretaceous-age coal beds are present in the Lance, Almond, and Allen Ridge Formations. Utilizing over 4,000 data points, 55 individual coal beds were identified in the assessment area. Coal resources were calculated using geologic models generated from these data points, using criteria for minimum thickness and areal extent. The geologic modeling criteria indicated that 33 of the 55 individual coal beds had sufficient thickness and areal extent to be economically significant. Calculated original coal resources within the assessment area were approximately 73.2 billion short tons (BST). After excluding coal resources lost due to land use and technical restrictions, recoverable coal resources were approximately 19.37 BST, including 2.14 BST of coal resources that could be extracted using surface mining methods and 17.23 BST of coal resources that could be extracted using underground mining methods. Due to mining costs and projected low potential sales value of the coal resources, only approximately 167 million short tons (MST) can be classified as reserves, which is less than 1 percent of the recoverable coal resources
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193053","usgsCitation":"Shaffer, B.N., Pierce, P.E., Kinney, S.A., Olea, R., and Luppens, J.A., 2019, Assessment of coal resources and reserves in the Little Snake River coal field and Red Desert assessment area, Greater Green River Basin, Wyoming: U.S. Geological Survey Fact Sheet 2019–3053, 6 p., https://doi.org/10.3133/fs20193053.","productDescription":"6 p.","onlineOnly":"N","ipdsId":"IP-109360","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":370380,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3053/coverthb.jpg"},{"id":370382,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1836","text":"Coal Geology and Assessment of Resources and Reserves in the Little Snake River Coal Field and Red Desert Assessment Area, Greater Green River Basin, Wyoming"},{"id":370381,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3053/fs20193053.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3053"},{"id":399136,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109583.htm"}],"country":"United States","state":"Wyoming","otherGeospatial":"Little Snake River coal field, Red Desert assessment area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.35,\n 41\n ],\n [\n -107.3333,\n 41\n ],\n [\n -107.3333,\n 42.1078\n ],\n [\n -108.35,\n 42.1078\n ],\n [\n -108.35,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The U.S. Geological Survey is studying regional-scale assessments of resources and reserves of primary coal beds in the major coal bed basins in the United States to help formulate policy for Federal, State, and local energy and land use. This report summarizes the geology and coal resources and reserves in the Little Snake River coal field and Red Desert assessment area in the Greater Green River Basin, southwestern Wyoming. These areas are contiguous and referred to as the “assessment area” in this report. The assessment area covers about 2,300 square miles of the eastern section of the 15,400-square-mile Greater Green River Basin. This area was prioritized for assessment because no comprehensive resource assessment had previously been completed in the area; abundant, previously unavailable drill hole data from cooperators and stakeholders became available; and there are active coal mines in the Greater Green River Basin area producing from some of the same formations as those found in the assessment area.
Coal-bearing Eocene, Paleocene, and Upper Cretaceous formations have a composite thickness of more than 11,000 feet in the assessment area. Stratigraphic sequences that contain multiple coal beds within a formation or member are referred to as coal zones in this report. Paleogene coal beds are found within coal zones in the Eocene Wasatch Formation and the Paleocene Fort Union Formation. Cretaceous coal beds are within coal zones in the Lance, Almond, and Allen Ridge Formations.
A total of 4,214 drill holes and measured sections were used to construct a geologic database for this assessment. From these data, 7 coal zones containing 55 individual coal beds were identified. Not all 55 coal beds were assessed; only those beds that were at least 3 feet thick and had at least a 2-square-mile areal extent were considered. Using a geology-based assessment methodology, the U.S. Geological Survey estimated original, available, and recoverable coal resources for 33 coal beds that met those criteria.
An original resource of 73.2 billion short tons of coal was calculated for the 33 coal beds that met the criteria in the assessment area. To be considered extractable by surface mining methods, coal beds had to be equal to or greater than 3 feet thick and less than 300 feet deep. Of the 73.2 billion short tons (BST), 19.3 BST were determined to be recoverable resources, of which approximately 2.1 BST were considered as recoverable resources by surface mining methods at a stripping ratio of 10:1 or less. (defined as recoverable resources for this assessment, based on economic modeling and regional mining analogs). Recoverable resources for underground mining methods (coal 8 to 15 feet thick and between 300 and 3,000 feet deep) totaled 17.2 BST. Out of the 19.3 BST assessed as recoverable coal resources, approximately 167 million short tons (MST) were considered to be reserves.
Within the 7 coal zones, the Wasatch coal zone contains an original resource of about 6.8 BST billion short tons of coal, of which 2.6 BST are considered a recoverable resource and approximately 26.7 MST are considered reserves. The Overland coal zone, in the Fort Union Formation, contains an original resource of approximately 23 BST of coal, of which 8.4 BST are considered a recoverable resource and approximately 74 MST are considered reserves. The China Butte coal zone, in the Fort Union Formation, contains an original resource of 36.2 BST of coal, of which 6.3 BST are considered a recoverable resource and approximately 5.5 MST are considered reserves. The Almond coal zone, in the Almond Formation, contains an original resource of 7.0 BST, of which approximately 2.0 BST are considered a recoverable resource and 61 MST are considered reserves. Resources were not calculated for the coal zones within the Niland Tongue of the Wasatch Formation or the Cretaceous Lance and Allen Ridge Formations because the coal beds in those zones are relatively thin, discontinuous, and have a limited areal extent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1836","usgsCitation":"Scott, D.C., Shaffer, B.N., Haacke, J.E., Pierce, P.E., and Kinney, S.A., 2019, Coal geology and assessment of resources and reserves in the Little Snake River coal field and Red Desert assessment area, Greater Green River Basin, Wyoming: U.S. Geological Survey Professional Paper 1836, 169 p., https://doi.org/10.3133/pp1836.","productDescription":"xiii, 169 p.","onlineOnly":"Y","ipdsId":"IP-077210","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":370383,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20193053","text":"Assessment of Coal Resources and Reserves in the Little Snake River Coal Field and Red Desert Assessment Area, Greater Green River Basin, Wyoming"},{"id":356626,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1836/pp1836.pdf","text":"Report","size":"32.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1836"},{"id":356625,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1836/coverthb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.02783203125,\n 43.14909399920127\n ],\n [\n -111.07177734375,\n 41.02964338716638\n ],\n [\n -108.3251953125,\n 40.9964840143779\n ],\n [\n -106.8310546875,\n 41.02964338716638\n ],\n [\n -105.380859375,\n 41.04621681452063\n ],\n [\n -104.9853515625,\n 41.47566020027821\n ],\n [\n -107.24853515625,\n 42.90816007196054\n ],\n [\n -109.09423828125,\n 43.8028187190472\n ],\n [\n -110.9619140625,\n 43.8503744993026\n ],\n [\n -111.02783203125,\n 43.14909399920127\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Wildfires destabilize biocrust, requiring decades for most biological constituents to regenerate, but bacteria may recover quickly and mitigate the detrimental consequences of burnt soils. To evaluate the short-term recovery of biocrust bacteria, we tracked shifts in bacterial community form and function in Cyanobacteria/lichen-dominated (shrub interspaces) and Cyanobacteria/moss-dominated (beneath Artemisia tridentata) biocrusts 1 week, 2 months, and 1 year following a large-scale burn manipulations in a cold desert (Utah, USA). We found no evidence of the burned bacterial community recovering to a burgeoning biocrust. The foundational biocrust phyla, Cyanobacteria, dominated by Microcoleus viginatus (Microcoleaceae), disappeared from burned soils creating communities void of photosynthetic taxa. One year after the fire, the burned biocrust constituents had eroded away and the bare soils supported the formation of a convergent community of chemoheterotrophic copiotrophs regardless of location. The emergent community was dominated by a previously rare Planococcus species (family Planococcaceae, Firmicutes) and taxa in the Cellulomonadaceae (Actinobacteria), and Oxalobacteraceae (Betaproteobacteria). Previously burnt soils maintained similar levels of bacterial biomass, alpha diversity, and richness as unburned biocrusts, but supported diffuse, poorly-interconnected communities with 75% fewer species interactions. Nitrogen fixation declined at least 3.5-fold in the burnt soils but ammonium concentrations continued to rise through the year, suggesting that the exhaustion of organic C released from the fire, and not N, may diminish the longevity of the emergent community. Our results demonstrate that biocrust bacteria may recover rapidly after burning, albeit along a different community trajectory, as rare bacteria become dominant, species interconnectedness diminishes, and ecosystem services fail to rebound.
This report presents economic principles and applications as they pertain to the U.S. Geological Survey’s U.S. Coal Resources and Reserves Assessment Project. This report compares commercial and governmental applications of economic principles and evaluation techniques. Common practices are described for evaluating the commercial investment potential of coal properties and calculating the government reserve potential of major U.S. coal basins. This report discusses economic principles that are applicable to typical mining feasibility studies as well as those categories and cost items that are often misused.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191082","usgsCitation":"Pierce, P.E., 2019, Economic analysis for U.S. Geological Survey coal basin assessments: U.S. Geological Survey Open-File Report 2019–1082, 33 p., https://doi.org/10.3133/ofr20191082.","productDescription":"v, 33 p.","onlineOnly":"Y","ipdsId":"IP-090621","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":370384,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1082/coverthb.jpg"},{"id":370385,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1082/ofr20191082.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1082"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.958984375,\n 49.38237278700955\n ],\n [\n -123.48632812499999,\n 48.40003249610685\n ],\n [\n -124.98046874999999,\n 48.40003249610685\n ],\n [\n -124.27734374999999,\n 46.31658418182218\n ],\n [\n -124.892578125,\n 43.77109381775651\n ],\n [\n -124.71679687499999,\n 41.04621681452063\n ],\n [\n -123.74999999999999,\n 38.54816542304656\n ],\n [\n -122.08007812499999,\n 34.813803317113155\n ],\n [\n -119.267578125,\n 33.797408767572485\n ],\n [\n -117.42187500000001,\n 32.47269502206151\n ],\n [\n -115.13671875,\n 32.62087018318113\n ],\n [\n -110.830078125,\n 31.27855085894653\n ],\n [\n -107.9296875,\n 31.353636941500987\n ],\n [\n -106.5234375,\n 31.728167146023935\n ],\n [\n -103.35937499999999,\n 28.536274512989916\n ],\n [\n -102.568359375,\n 29.458731185355344\n ],\n [\n -101.25,\n 29.38217507514529\n ],\n [\n -99.228515625,\n 26.509904531413927\n ],\n [\n -96.591796875,\n 25.48295117535531\n ],\n [\n -97.03125,\n 26.509904531413927\n ],\n [\n -95.80078125,\n 28.459033019728043\n ],\n [\n -93.955078125,\n 28.76765910569123\n ],\n [\n -90.703125,\n 29.075375179558346\n ],\n [\n -88.24218749999999,\n 29.22889003019423\n ],\n [\n -87.978515625,\n 29.99300228455108\n ],\n [\n -84.111328125,\n 29.38217507514529\n ],\n [\n -82.265625,\n 26.352497858154024\n ],\n [\n -80.947265625,\n 24.926294766395593\n ],\n [\n -80.15625,\n 25.958044673317843\n ],\n [\n -80.419921875,\n 28.38173504322308\n ],\n [\n -81.03515625,\n 30.977609093348686\n ],\n [\n -79.453125,\n 32.47269502206151\n ],\n [\n -76.2890625,\n 35.24561909420681\n ],\n [\n -75.234375,\n 37.50972584293751\n ],\n [\n -73.65234375,\n 40.245991504199026\n ],\n [\n -69.697265625,\n 41.57436130598913\n ],\n [\n -70.57617187499999,\n 43.197167282501276\n ],\n [\n -66.796875,\n 44.653024159812\n ],\n [\n -68.02734375,\n 47.338822694822\n ],\n [\n -69.60937499999999,\n 47.39834920035926\n ],\n [\n -70.927734375,\n 45.1510532655634\n ],\n [\n -74.619140625,\n 44.96479793033101\n ],\n [\n -79.541015625,\n 43.644025847699496\n ],\n [\n -79.27734374999999,\n 42.74701217318067\n ],\n [\n -82.880859375,\n 41.902277040963696\n ],\n [\n -82.265625,\n 44.402391829093915\n ],\n [\n -84.111328125,\n 46.619261036171515\n ],\n [\n -89.12109375,\n 48.22467264956519\n ],\n [\n -94.5703125,\n 49.38237278700955\n ],\n [\n -95.2734375,\n 49.439556958940855\n ],\n [\n -95.2734375,\n 49.03786794532644\n ],\n [\n -122.958984375,\n 49.38237278700955\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Detailed geologic maps are the basis of nearly every Earth-science investigation and can be used for natural hazard mitigation, resource identification and exploration, infrastructure planning, and more. A component of the congressionally mandated National Cooperative Geologic Mapping Program, EDMAP is a partnership among the U.S. Geological Survey, the Association of American State Geologists, and participating colleges and universities that provides mentorship and training opportunities to geology students nationwide. Under the guidance of a faculty member, EDMAP supports upper level undergraduate and graduate students to gain meaningful experience working on 1-year geologic-mapping projects. Between 1996 and 2019, EDMAP funded research projects for more than 1,200 students at more than 160 universities. Every Federal dollar awarded through the EDMAP program is matched by the student’s university.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193059","usgsCitation":"Ackerman, A., and McPhee, D.K., 2019, U.S. Geological Survey EDMAP Program—Training the next generation of geologic mappers (ver. 1.1, July 2020): U.S. Geological Survey Fact Sheet 2019–3059, 4 p., https://doi.org/10.3133/fs20193059.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-098123","costCenters":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"links":[{"id":370408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3059/coverthb3.jpg"},{"id":370409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3059/fs20193059_v1.1.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2019-3059"},{"id":376389,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2019/3059/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: December 18, 2019; Version 1.1: July 14, 2020","contact":"Director
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The U.S. Geological Survey, in cooperation with the Puerto Rico Electric Power Authority, conducted a sedimentation survey of Lago Guayabal in 2017 to determine reservoir infill sedimentation rates, generate a bathymetric map of the bottom elevations of the reservoir, and create a stage-volume relation. The original (1913) capacity of Lago Guayabal was 11.82 million cubic meters, and efforts to increase the storage capacity were made in 1950 by the installation of flashboards. The 2017 survey indicated that storage capacity of Lago Guayabal is 4.98 million cubic meters. The estimated full sediment infill of Lago Guayabal is expected in 77 years, based on the long-term sedimentation rate of 0.065 million cubic meters per year determined for the 1972–2017 period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3442","collaboration":"Prepared in cooperation with the Puerto Rico Electric Power Authority","usgsCitation":"Gómez-Fragoso, J.M., and Rosario, M., 2019, Sedimentation survey of Lago Guayabal, Villalba, Puerto Rico, December 2017: U.S. Geological Survey Scientific Investigations Map 3442, 1 sheet, https://doi.org/10.3133/sim3442.","productDescription":"1 Plate: 29.00 x 32.00 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-099137","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":370191,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3442/sim3442.pdf","text":"Report","size":"7.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3442"},{"id":370190,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3442/coverthb.jpg"},{"id":370192,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/P9FD12Y5","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Sedimentation survey data for Lago Guayabal, December 2017"}],"otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.51569366455078,\n 18.082058622333665\n ],\n [\n -66.49080276489258,\n 18.082058622333665\n ],\n [\n -66.49080276489258,\n 18.104331760155084\n ],\n [\n -66.51569366455078,\n 18.104331760155084\n ],\n [\n -66.51569366455078,\n 18.082058622333665\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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The glacial kettle ponds in the Hyannis Ponds Wildlife Management Area in Barnstable, Massachusetts, support a community of rare and endangered plants. The ponds are hydraulically connected to the unconfined aquifer that underlies Cape Cod. The plants are adapted to the rise and fall of water levels in the ponds as the water table fluctuates in response to seasonal and year-to-year natural changes in recharge. Pumping from wells for public water supply and recharge of wastewater at water pollution control facilities and septic systems also affect groundwater levels. The Hyannis Water System has proposed to install two additional wells in the Hyannis Ponds Wildlife Management Area and adjust rates of withdrawals and recharge of wastewater return flows for the municipal system that serves the village of Hyannis in the town of Barnstable. The proposal has raised concerns that pumping from the proposed wells could cause long-term average changes in pond levels that could adversely affect the critical pond-shore plant habitat.
An available three-dimensional steady-state groundwater-flow model was used to simulate the hydrologic effects of nine pumping and wastewater return-flow scenarios prepared by the Hyannis Water System. These effects were quantified by comparison of water levels simulated for the scenarios to water levels simulated for a reference condition based on 2015 withdrawal and wastewater return-flow rates. Maps of water-level responses were prepared to show the effects of pumping from a single well at different locations in the Hyannis Ponds Wildlife Management Area on the water levels of six ponds. Steady-state simulations of the nine scenarios indicated that the shapes of the simulated water-table contours near the wildlife management area changed only slightly at the regional scale, with the largest shifts near the wildlife management area and the Barnstable Water Pollution Control Facility. The simulated changes in pond levels at 10 ponds of interest for the nine scenarios relative to the simulated pond levels for the 2015 reference condition ranged from small increases (less than 0.1 foot) in one pond each in two scenarios to declines (drawdowns) of 1.03–1.11 feet at three ponds in one scenario. Water levels at the Barnstable Water Pollution Control Facility increased because part of the increase in total withdrawals from the Hyannis Water System wells was recharged as wastewater at the water pollution control facility.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195121","collaboration":"Prepared in cooperation with the Town of Barnstable","usgsCitation":"LeBlanc, D.R., McCobb, T.D., and Barbaro, J.R., 2019, Simulated water-table and pond-level responses to proposed public water-supply withdrawals in the Hyannis Ponds Wildlife Management Area, Barnstable, Massachusetts: U.S. Geological Survey Scientific Investigations Report 2019–5121, 32 p., https://doi.org/10.3133/sir20195121.","productDescription":"Report: vii, 32 p.; Data Release","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-109032","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":370347,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5121/sir20195121.pdf","text":"Report","size":"3.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5121"},{"id":370346,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5121/coverthb.jpg"},{"id":370348,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U5AKLC","text":"USGS data release","linkHelpText":"MODFLOW2005 groundwater-flow model used to simulate water-supply pumping scenarios near the Hyannis Ponds Wildlife Management Area, Barnstable, Massachusetts"}],"country":"United States","state":"Massachusetts","city":"Barnstable","otherGeospatial":"Hyannis Ponds Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.28074264526367,\n 41.67297593102651\n ],\n [\n -70.26091575622559,\n 41.67297593102651\n ],\n [\n -70.26091575622559,\n 41.68771986229327\n ],\n [\n -70.28074264526367,\n 41.68771986229327\n ],\n [\n -70.28074264526367,\n 41.67297593102651\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Deformation associated with plate convergence at subduction zones is accommodated by a complex system involving fault slip and viscoelastic flow. These processes have proven difficult to disentangle. The 2010 Mw 8.8 Maule earthquake occurred close to the Chilean coast within a dense network of continuously recording Global Positioning System stations, which provide a comprehensive history of surface strain. We use these data to assemble a detailed picture of a structurally controlled megathrust fault frictional patchwork and the three-dimensional rheological and time-dependent viscosity structure of the lower crust and upper mantle, all of which control the relative importance of afterslip and viscoelastic relaxation during postseismic deformation. These results enhance our understanding of subduction dynamics including the interplay of localized and distributed deformation during the subduction zone earthquake cycle.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.aax6720","usgsCitation":"Weiss, J., Qiu, Q., Barbot, S., Wright, T.J., Foster, J.H., Saunders, A., Brooks, B.A., Bevis, M., Kendrick, E., Ericksen, T., Avery, J., Smalley, R., Cimbaro, S.R., Lenzano, L.E., Baron, J., Báez, J., and Echalar, A., 2019, Illuminating subduction zone rheological properties in the wake of a giant earthquake: Science Advances, v. 5, no. 12, eaax6720, 12 p., https://doi.org/10.1126/sciadv.aax6720.","productDescription":"eaax6720, 12 p.","ipdsId":"IP-106773","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":458931,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aax6720","text":"Publisher Index 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USA","active":true,"usgs":false}],"preferred":false,"id":804165,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Cimbaro, Sergio R.","contributorId":244559,"corporation":false,"usgs":false,"family":"Cimbaro","given":"Sergio","email":"","middleInitial":"R.","affiliations":[{"id":48942,"text":"Dirección de Geodesia, Instituto Geográfico Nacional, Buenos Aires, Argentina","active":true,"usgs":false}],"preferred":false,"id":804166,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lenzano, Luis E.","contributorId":244560,"corporation":false,"usgs":false,"family":"Lenzano","given":"Luis","email":"","middleInitial":"E.","affiliations":[{"id":48943,"text":"International Center for Earth Sciences, Universidad Nacional de Cuyo, Mendoza, Argentina","active":true,"usgs":false}],"preferred":false,"id":804167,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Baron, Jorge","contributorId":244561,"corporation":false,"usgs":false,"family":"Baron","given":"Jorge","email":"","affiliations":[{"id":48943,"text":"International Center for Earth Sciences, Universidad Nacional de Cuyo, Mendoza, Argentina","active":true,"usgs":false}],"preferred":false,"id":804168,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Báez, Juan Carlos","contributorId":244562,"corporation":false,"usgs":false,"family":"Báez","given":"Juan Carlos","affiliations":[{"id":48944,"text":"Centro Sismilógico Nacional, Universidad de Chile, Santiago, Chile","active":true,"usgs":false}],"preferred":false,"id":804169,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Echalar, Arturo","contributorId":244563,"corporation":false,"usgs":false,"family":"Echalar","given":"Arturo","email":"","affiliations":[{"id":48945,"text":"Instituto Geográfico Militar, La Paz, Bolivia","active":true,"usgs":false}],"preferred":false,"id":804170,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70207535,"text":"70207535 - 2019 - Influence of turbulence and in-stream structures on the transport and survival of grass carp eggs and larvae at various developmental stages","interactions":[],"lastModifiedDate":"2019-12-23T07:41:05","indexId":"70207535","displayToPublicDate":"2019-12-18T07:38:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":873,"text":"Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Influence of turbulence and in-stream structures on the transport and survival of grass carp eggs and larvae at various developmental stages","docAbstract":"Understanding the response of grass carp to flow and turbulence regimes during early life stages is fundamental to monitoring and controlling their spread. A comprehensive set of hydrodynamic experiments was conducted with live grass carp eggs and larvae, to better understand their drifting and swimming patterns with 3 different in-stream obstructions: (1) a gravel bump, (2) a single cylinder, and (3) submerged vegetation. The hydrodynamic behavior of eggs and larvae with each obstruction was continuously monitored for about 85 consecutive hours. Transient spatial distributions of the locations of eggs and larvae throughout the water column were generated for each flow scenario. Results show that the active swimming capabilities of larvae allow them to seek areas of low turbulence and low shear stresses, and that eggs are susceptible to damage by high levels of turbulence, which was further corroborated with tests in an oscillating grid-stirred turbulence tank. Our study seeks to better inform field collection of grass carp during early life stages, and to guide the design of alternative approaches to control the dispersal of this invasive species in North America.","language":"English","publisher":"Springer","doi":"10.1007/s00027-019-0689-1","usgsCitation":"Prada, A.F., George, A.E., Stahlschmidt, B.H., Jackson, P.R., Chapman, D., and Tinoco, R.O., 2019, Influence of turbulence and in-stream structures on the transport and survival of grass carp eggs and larvae at various developmental stages: Aquatic Sciences, v. 82, no. 1, 16, 16 p., https://doi.org/10.1007/s00027-019-0689-1.","productDescription":"16, 16 p.","ipdsId":"IP-108300","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":458934,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00027-019-0689-1","text":"Publisher Index Page"},{"id":437257,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P926SZLN","text":"USGS data release","linkHelpText":"Survival and hydrodynamic behavior of grass carp eggs and larvae in relation to turbulence and in-stream obstructions"},{"id":370628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Prada, Andres F.","contributorId":211778,"corporation":false,"usgs":false,"family":"Prada","given":"Andres","email":"","middleInitial":"F.","affiliations":[{"id":38317,"text":"Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL","active":true,"usgs":false}],"preferred":false,"id":778365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Amy E. 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":3950,"corporation":false,"usgs":true,"family":"George","given":"Amy","email":"ageorge@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":778364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stahlschmidt, Benjamin H. 0000-0001-6197-662X","orcid":"https://orcid.org/0000-0001-6197-662X","contributorId":211250,"corporation":false,"usgs":true,"family":"Stahlschmidt","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":778366,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, P. 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In this study, we investigate fossil diatoms in siliceous hydrothermal deposits of the Upper Geyser and Yellowstone Lake hydrothermal basins in Yellowstone National Park, and utilize preserved diatom assemblages to infer local environmental conditions. Siliceous sinter from both the Upper Geyser Basin and Yellowstone Lake contains evidence of in-situ diatom growth within these environments. At Upper Geyser Basin, the assemblage consisted of species that could grow on moist siliceous sinter and was dominated by Rhopalodia gibberula. Diatom valves were found in various preservation states, ranging from nearly pristine to highly diagenetically altered. Diatoms collected from siliceous spires in Yellowstone Lake consisted largely of tychoplanktonic and benthic species that were almost certainly growing on the outside of the structure, with an assemblage indicative of relatively shallow, alkaline waters. What remains unclear without access to material for high-resolution dating is whether diatoms colonized the spires during hydrothermal activity or after activity ceased. Our results indicate that diatom frustules can, to some extent, survive alteration in low-temperature (<76°C) hydrothermal environments.
The National Hydrography Dataset Plus High Resolution (NHDPlus HR) is a scalable geospatial hydrography framework built from the High Resolution (1:24,000-scale or better) National Hydrography Dataset (NHD), nationally complete Watershed Boundary Dataset (WBD), and ⅓-arc-second (10-meter ground spacing) 3D Elevation Program (3DEP) digital elevation model (DEM) data. The NHDPlus HR brings modeling and assessment to a local neighborhood level while nesting seamlessly into the national context.
NHDPlus HR is modeled after the highly successful NHDPlus version 2 (NHDPlus V2). Like the NHDPlus V2, the NHDPlus HR includes data for a nationally seamless network of stream reaches, elevation-based catchment areas, flow surfaces, and value-added attributes that enhance stream-network navigation, analysis, and data display. Users will find that the NHDPlus HR, however, provides much greater detail. This User’s Guide is intended to provide necessary information and guidance in the use of NHDPlus HR data.
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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP) is a long-term cooperative project designed to assess the quality of groundwater resources used for public and domestic drinking water supplies in the State of California, to monitor and evaluate changes to that quality, to investigate the human and natural factors controlling water quality, and to improve the availability of comprehensive groundwater quality data and information. Between May 18, 2004, and May 3, 2018, the GAMA-PBP collected 3001 groundwater samples for analysis of pesticide constituents by the U.S. Geological Survey (USGS) National Water Quality Laboratory (NWQL)(note that ‘pesticide constituents’ includes parent compounds and degradates). Of these samples, 2994 were analyzed for pesticide constituents on schedules 2003, 2032, or 2033 (65 to 84 constituents), and 840 were analyzed for pesticide constituents on schedule 2060 (58 constituents). The original dataset reported by the NWQL to the USGS National Water Information System (NWIS) database contained a total of 2,688 detections of 78 pesticide constituents and 253,825 non-detections. In this original dataset, 33 percent of the 3,001 samples analyzed had reported detections of one or more pesticide constituents.
This report describes the GAMA-PBP data-quality objectives for pesticide data, the procedures used to establish study reporting limits, and use of those reporting limits to censor the data from the NWQL so that the final data published by the GAMA-PBP meet these data-quality objectives. The final GAMA-PBP dataset for samples collected from May 2004 to May 2018, after censoring, had a total of 1,632 detections of 37 pesticide constituents. In the final GAMA-PBP dataset, 25 percent of the 3,001 samples analyzed had detections of one or more pesticide constituents.
The presence of pesticides in groundwater is commonly evaluated by calculating detection frequencies. Detection frequencies for pesticides are sensitive to detection limits and method performance for concentrations near those limits; therefore, the two primary data quality issues addressed in the GAMA-PBP data-quality objectives for pesticides are (1) establishing criteria for classifying data from the laboratory as detections or non-detections for the purpose of data reporting by the project and (2) accounting for changes in analytical methods or method performance over time. The GAMA-PBP addresses these issues by developing study reporting limits that are used as the boundary between detections and non-detections for the reporting of GAMA-PBP results. These reporting limits are defined from method detection limits (MDLs) provided by the NWQL, unless examination of results from laboratory set blanks (LSBs) and GAMA-PBP field blanks indicates that a higher concentration censoring limit is warranted. The GAMA-PBP selected the MDL as the primary choice for defining study reporting limits for consistency with U.S. Environmental Protection Agency (EPA) guidelines for reporting detections of pesticides and other organic constituents.
A five-step procedure is used to develop study reporting limits and censor the GAMA-PBP dataset accordingly. The effect of the censoring at each step is described to provide information about the relative effect of each step on the overall censoring of the dataset. Steps 1 and 2 can be implemented at the time the data are received, whereas steps 3−5 require information accumulated over an extended period.
As of 2019, the USGS NWIS database does not have the capability to store both the original value reported by the NWQL and the final value published by the GAMA-PBP that reflects application of the quality-control censoring described in this report. In the interim, while this capability is developed, the 1,031 results censored in steps 2−5 are blocked from public release in NWIS, and the GAMA-PBP has published the original and final values in a USGS data release accompanying this report. The entire GAMA-PBP final dataset for pesticide constituents on schedules 2003, 2032, or 2033, or on schedule 2060 is publicly available in that USGS data release, through the USGS GAMA-PBP public web portal, and through the California State Water Resources Control Board GAMA public groundwater information system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195107","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Fram, M.S., and Stork, S.V., 2019, Determination of study reporting limits for pesticide constituent data for the California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project, 2004–2018—Part 1: National Water Quality Schedules 2003, 2032, or 2033, and 2060: U.S. Geological Survey Scientific Investigations Report 2019–5107, 129 p., https://doi.org/10.3133/sir20195107.","productDescription":"Report: viii, 129 p.; Dataset","numberOfPages":"129","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101851","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":370195,"rank":3,"type":{"id":30,"text":"Data 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\"}}]}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The key to Thick-billed Longspur (Rhynchophanes mccownii) management is providing short, sparsely vegetated native grasslands of adequate size. Mixed-grass prairies can be made suitable for breeding Thick-billed Longspurs by implementing moderate-to-heavy or season-long grazing. Thick-billed Longspurs have been reported to use habitats with 5–42 centimeters (cm) average vegetation height, 3–7 cm visual obstruction reading, 15–67 percent grass cover, less than (<) 8 percent forb cover, <7 percent shrub cover, 2–60 percent bare ground, 10–63 percent litter cover, and <5 cm litter depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842Y","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Rabie, P.A., Wooten, T.L., and Euliss, B.R., 2019, The effects of management practices on grassland birds—Thick-billed Longspur (Rhynchophanes mccownii) (ver. 1.1, March 2022), chap. Y of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 10 p., https://doi.org/10.3133/pp1842Y.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095144","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":370325,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/y/coverthb2.jpg"},{"id":370326,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/y/pp1842y.pdf","text":"Report","size":"1.93 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–Y"},{"id":397826,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/pp/1842/y/versionhist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: December 17, 2019; Version 1.1: March 31, 2022","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Federal Select Agent Program regulations require laboratories to document a validated procedure for inactivating select agents prior to movement outside registered space. Avian influenza viruses and virulent Newcastle disease virus (vNDV) are cultured in chicken amnio-allantoic fluid (AAF), but the efficacy of commercial lysis buffers to inactivate viruses in protein-rich media has not been documented.
We assesses the efficacy of MagMAX™ lysis buffer for inactivating highly pathogenic avian influenza virus (HPAIV) and vNDV in chicken AAF and confirm the inactivation of avian influenza in serum using heat.
Low pathogenic avian influenza virus (LPAIV) and avian paramyxovirus subtype-1 (APMV-1) were incubated with lysis buffer and tested for viability. Known viable LPAIV and APMV-1 RNA was extracted from AAF using MagMAX™-96 AI/ND Viral RNA Isolation kit, and the eluate was tested for remaining infectious agent. Finally, inactivation of LPAIV in serum was examined over 3 combinations of temperature and incubation time.
MagMAX™ lysis buffer inactivated both LPAIV and APMV-1 in AAF when incubated for 30 minutes at room temperature. The full extraction process eliminated viable virus from the final RNA eluate. LPAIV in serum heated to 70°C for 30 minutes was rendered noninfectious.
The ability of a diagnostic laboratory to move samples from one space to another is critical to maintaining biosecurity as well as efficient laboratory workflow. Our study demonstrates a method to ensure the inactivation of viable avian influenza and avian paramyxoviruses in AAF, RNA eluate, and viable avian influenza virus in sera.
Newly emerging plants provide the best forage for herbivores. To exploit this fleeting resource, migrating herbivores align their movements to surf the wave of spring green-up. With new technology to track migrating animals, the Green Wave Hypothesis has steadily gained empirical support across a diversity of migratory taxa. This hypothesis assumes the green wave is controlled by variation in climate, weather, and topography, and its progression dictates the timing, pace, and extent of migrations. However, aggregate grazers that are also capable of engineering grassland ecosystems make some of the world’s most impressive migrations, and it is unclear how the green wave determines their movements. Here we show that Yellowstone’s bison (Bison bison) do not choreograph their migratory movements to the wave of spring green-up. Instead, bison modify the green wave as they migrate and graze. While most bison surfed during early spring, they eventually slowed and let the green wave pass them by. However, small-scale experiments indicated that feedback from grazing sustained forage quality. Most importantly, a 6-fold decadal shift in bison density revealed that intense grazing caused grasslands to green up faster, more intensely, and for a longer duration. Our finding broadens our understanding of the ways in which animal movements underpin the foraging benefit of migration. The widely accepted Green Wave Hypothesis needs to be revised to include large aggregate grazers that not only move to find forage, but also engineer plant phenology through grazing, thereby shaping their own migratory movements.