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Butterflies and bees contribute significantly to grassland biodiversity and play important roles as pollinators and herbivores. Grassland conservation and management must be seen through the lens of insect conservation and management if these species are to thrive. In North America, grasslands are a product of climate and natural disturbances such as fire and grazing. These natural disturbances have changed considerably since European colonization and subsequent landscape fragmentation. The aim of this study was to better understand the impacts of fire and grazing management on butterfly and bee communities in tallgrass prairie, enabling land managers and conservationists to better protect and manage remnant prairie. We examined butterfly and bee abundance, species richness, and diversity in Minnesota tallgrass prairies managed by grazing or fire. In 2016 and 2017, we surveyed butterflies, bees, vegetation, and surrounding land use at 20 remnant prairies (10 burned and 10 grazed) with known management histories. Butterfly and bee abundance at our study sites were significantly negatively correlated. Butterfly abundance, but not species richness, was higher in burned than grazed prairies, and prairie-associated grass-feeding butterflies were more abundant at sites with higher plant species richness. Bee abundance was unrelated to management type but was higher at sites with sandier soils; bee species richness was positively associated with forb frequency. These findings highlight the challenges of designing management plans tailored to wide groups of pollinators and the potential pitfalls of using one group of pollinators as indicators for another. They also point to the importance of a mosaic of management practices across the prairie landscape.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9532","usgsCitation":"Leone, J.B., Pennarola, N.P., Larson, J., Oberhauser, K., and Larson, D., 2022, Divergent responses of butterflies and bees to burning and grazing management in tallgrass prairies: Ecology and Evolution, v. 12, no. 12, e9532, 32 p., https://doi.org/10.1002/ece3.9532.","productDescription":"e9532, 32 p.","ipdsId":"IP-124498","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":445717,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.9532","text":"Publisher Index Page"},{"id":416801,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.42587878349188,\n 43.50122649410929\n ],\n [\n -92.46980520060302,\n 43.819068952258306\n ],\n [\n -93.01888541449156,\n 44.19813376902931\n ],\n [\n -94.05115621660198,\n 44.84018463954041\n ],\n [\n -94.4684571791577,\n 45.04228562902125\n ],\n [\n -95.08342701871238,\n 45.6289381740921\n ],\n [\n -95.43483835560139,\n 46.05738039426899\n ],\n [\n -95.85213931815657,\n 46.85923603684219\n ],\n [\n -95.96195536093438,\n 47.486301099344615\n ],\n [\n -96.11569782082331,\n 48.091300551054246\n ],\n [\n -96.04980819515664,\n 48.761707145707646\n ],\n [\n -96.2474770721567,\n 49.00722990939005\n ],\n [\n -97.30171108282268,\n 49.021634894735\n ],\n [\n -97.08207899726705,\n 48.674764163690384\n ],\n [\n -97.14796862293373,\n 48.47131260604402\n ],\n [\n -97.21385824860043,\n 48.091300551054246\n ],\n [\n -96.90637332882254,\n 47.678892796347725\n ],\n [\n -96.9283365373781,\n 47.203545923237186\n ],\n [\n -96.81852049460082,\n 46.84421564630452\n ],\n [\n -96.75263086893413,\n 46.512703995805765\n ],\n [\n -96.59888840904517,\n 45.87416744467754\n ],\n [\n -96.88441012026698,\n 45.705705406457724\n ],\n [\n -96.48907236626737,\n 45.413526121018435\n ],\n [\n -96.44514594915624,\n 44.229613459306336\n ],\n [\n -96.59888840904517,\n 43.58083006859914\n ],\n [\n -92.42587878349188,\n 43.50122649410929\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Leone, Julia B.","contributorId":216121,"corporation":false,"usgs":false,"family":"Leone","given":"Julia","email":"","middleInitial":"B.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":871945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pennarola, Nora P.","contributorId":239528,"corporation":false,"usgs":false,"family":"Pennarola","given":"Nora","email":"","middleInitial":"P.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":871946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, Jennifer 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":216120,"corporation":false,"usgs":true,"family":"Larson","given":"Jennifer","email":"","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":871947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oberhauser, Karen","contributorId":231063,"corporation":false,"usgs":false,"family":"Oberhauser","given":"Karen","affiliations":[{"id":42832,"text":"Univ of Minnesota","active":true,"usgs":false}],"preferred":false,"id":871948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larson, Diane L. 0000-0001-5202-0634","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":260165,"corporation":false,"usgs":true,"family":"Larson","given":"Diane L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":871949,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256601,"text":"70256601 - 2022 - As the goose flies: Migration routes and timing influence patterns of genetic diversity in a circumpolar migratory herbivore","interactions":[],"lastModifiedDate":"2024-08-23T16:24:30.976426","indexId":"70256601","displayToPublicDate":"2022-12-03T11:08:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"As the goose flies: Migration routes and timing influence patterns of genetic diversity in a circumpolar migratory herbivore","docAbstract":"

Migration schedules and the timing of other annual events (e.g., pair formation and molt) can affect the distribution of genetic diversity as much as where these events occur. The greater white-fronted goose (Anser albifrons) is a circumpolar goose species, exhibiting temporal and spatial variation of events among populations during the annual cycle. Previous range-wide genetic assessments of the nuclear genome based on eight microsatellite loci suggest a single, largely panmictic population despite up to five subspecies currently recognized based on phenotypic differences. We used double digest restriction-site associated DNA (ddRAD-seq) and mitochondrial DNA (mtDNA) sequence data to re-evaluate estimates of spatial genomic structure and to characterize how past and present processes have shaped the patterns of genetic diversity and connectivity across the Arctic and subarctic. We uncovered previously undetected inter-population differentiation with genetic clusters corresponding to sampling locales associated with current management groups. We further observed subtle genetic clustering within each management unit that can be at least partially explained by the timing and directionality of migration events along with other behaviors during the annual cycle. The Tule Goose (A. a. elgasi) and Greenland subspecies (A. a. flavirostris) showed the highest level of divergence among all sampling locales investigated. The recovery of previously undetected broad and fine-scale spatial structure suggests that the strong cultural transmission of migratory behavior restricts gene flow across portions of the species’ range. Our data further highlight the importance of re-evaluating previous assessments conducted based on a small number of highly variable genetic markers in phenotypically diverse species.

","language":"English","publisher":"MDPI","doi":"10.3390/d14121067","usgsCitation":"Wilson, R., Sonsthagen, S.A., DaCost, J.M., Sorenson, M., Fox, A., Weaver, M., Skalos, D., Kondratyev, A., Scribner, K., Walsh, A., Ely, C.R., and Talbot, S.L., 2022, As the goose flies: Migration routes and timing influence patterns of genetic diversity in a circumpolar migratory herbivore: Diversity, v. 14, no. 12, 1067, 23 p., https://doi.org/10.3390/d14121067.","productDescription":"1067, 23 p.","ipdsId":"IP-145453","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445720,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d14121067","text":"Publisher Index Page"},{"id":433109,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Greenland, Russia, United States","otherGeospatial":"Circumpolar Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -179.9,\n 73.8\n ],\n [\n -179.9,\n 55\n ],\n [\n -44.563059444221864,\n 55\n ],\n [\n -44.563059444221864,\n 73.8\n ],\n [\n -179.9,\n 73.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 36.467721150184104,\n 73.8\n ],\n [\n 36.467721150184104,\n 60\n ],\n [\n 179.9,\n 60\n ],\n [\n 179.9,\n 73.8\n ],\n [\n 36.467721150184104,\n 73.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Robert E.","contributorId":341321,"corporation":false,"usgs":false,"family":"Wilson","given":"Robert E.","affiliations":[{"id":36892,"text":"University of 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Dan","contributorId":341326,"corporation":false,"usgs":false,"family":"Skalos","given":"Dan","email":"","affiliations":[{"id":81725,"text":"California Department of Fish and Wildlife,","active":true,"usgs":false}],"preferred":false,"id":908240,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kondratyev, Alexander V.","contributorId":341327,"corporation":false,"usgs":false,"family":"Kondratyev","given":"Alexander V.","affiliations":[{"id":81726,"text":"Institute of Biological Problems of the North, FEB RAS, Magadan","active":true,"usgs":false}],"preferred":false,"id":908241,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scribner, Kim T.","contributorId":341328,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim T.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":908242,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walsh, Alyn","contributorId":341329,"corporation":false,"usgs":false,"family":"Walsh","given":"Alyn","email":"","affiliations":[{"id":81727,"text":"National Parks and Wildlife Services, Ireland","active":true,"usgs":false}],"preferred":false,"id":908243,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ely, Craig R. 0000-0003-4262-0892 cely@usgs.gov","orcid":"https://orcid.org/0000-0003-4262-0892","contributorId":3214,"corporation":false,"usgs":true,"family":"Ely","given":"Craig","email":"cely@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":908244,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Talbot, Sandra L.","contributorId":341330,"corporation":false,"usgs":false,"family":"Talbot","given":"Sandra","email":"","middleInitial":"L.","affiliations":[{"id":63248,"text":"Far Northwestern Institute of Art and Science","active":true,"usgs":false}],"preferred":false,"id":908245,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70238881,"text":"70238881 - 2022 - Optimizing Landsat Next shortwave infrared bands for crop residue characterization","interactions":[],"lastModifiedDate":"2022-12-15T13:48:36.566374","indexId":"70238881","displayToPublicDate":"2022-12-03T07:44:55","publicationYear":"2022","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":"Optimizing Landsat Next shortwave infrared bands for crop residue characterization","docAbstract":"

This study focused on optimizing the placement of shortwave infrared (SWIR) bands for pixel-level estimation of fractional crop residue cover (fR) for the upcoming Landsat Next mission. We applied an iterative wavelength shift approach to a database of crop residue field spectra collected in Beltsville, Maryland, USA (n = 916) and computed generalized two- and three-band spectral indices for all wavelength combinations between 2000 and 2350 nm, then used these indices to model field-measured fR. A subset of the full dataset with a Normalized Difference Vegetation Index (NDVI) < 0.3 threshold (n = 643) was generated to evaluate green vegetation impacts on fR estimation. For the two-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized normalized difference using 2226 nm and 2263 nm bands produced the top fR estimation performance (R2 = 0.8222; RMSE = 0.1296). These findings were similar to the established two-band Shortwave Infrared Normalized Difference Residue Index (SINDRI) (R2 = 0.8145; RMSE = 0.1324). Performance of the two-band generalized normalized difference and SINDRI decreased for the full-NDVI dataset (R2 = 0.5865 and 0.4144, respectively). For the three-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized ratio-based index with a 2031–2085–2216 nm band combination, closely matching established Cellulose Absorption Index (CAI) bands, was top performing (R2 = 0.8397; RMSE = 0.1231). Three-band indices with CAI-type wavelengths maintained top fR estimation performance for the full-NDVI dataset with a 2036–2111–2217 nm band combination (R2 = 0.7581; RMSE = 0.1548). The 2036–2111–2217 nm band combination was also top performing in fR estimation (R2 = 0.8690; RMSE = 0.0970) for an additional analysis assessing combined green vegetation cover and surface moisture effects. Our results indicate that a three-band configuration with band centers and wavelength tolerances of 2036 nm (±5 nm), 2097 nm (±14 nm), and 2214 (±11 nm) would optimize Landsat Next SWIR bands for fR estimation.

","language":"English","publisher":"MDPI","doi":"10.3390/rs14236128","usgsCitation":"Lamb, B.T., Dennison, P., Hively, W.D., Kokaly, R.F., Serbin, G., Wu, Z., Dabney, P.W., Masek, J.G., Campbell, M., and Daughtry, C.S., 2022, Optimizing Landsat Next shortwave infrared bands for crop residue characterization: Remote Sensing, v. 14, no. 23, 6128, 29 p., https://doi.org/10.3390/rs14236128.","productDescription":"6128, 29 p.","ipdsId":"IP-144753","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":445721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14236128","text":"Publisher Index Page"},{"id":410537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"23","noUsgsAuthors":false,"publicationDate":"2022-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamb, Brian T. 0000-0001-7957-5488","orcid":"https://orcid.org/0000-0001-7957-5488","contributorId":291893,"corporation":false,"usgs":true,"family":"Lamb","given":"Brian","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennison, Phillip 0000-0002-0241-1917","orcid":"https://orcid.org/0000-0002-0241-1917","contributorId":266031,"corporation":false,"usgs":false,"family":"Dennison","given":"Phillip","email":"","affiliations":[{"id":54865,"text":"Dept. Geography, Utah State University","active":true,"usgs":false}],"preferred":false,"id":859053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":859055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Serbin, Guy 0000-0001-9345-1772","orcid":"https://orcid.org/0000-0001-9345-1772","contributorId":266030,"corporation":false,"usgs":false,"family":"Serbin","given":"Guy","email":"","affiliations":[{"id":54864,"text":"EOAnalytics","active":true,"usgs":false}],"preferred":false,"id":859056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":859057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dabney, Philip W.","contributorId":214572,"corporation":false,"usgs":false,"family":"Dabney","given":"Philip","email":"","middleInitial":"W.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":859058,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Masek, Jeffery G.","contributorId":294418,"corporation":false,"usgs":false,"family":"Masek","given":"Jeffery","email":"","middleInitial":"G.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":859059,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Campbell, Michael","contributorId":299937,"corporation":false,"usgs":false,"family":"Campbell","given":"Michael","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":859060,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Daughtry, Craig S. T.","contributorId":211093,"corporation":false,"usgs":false,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S. T.","affiliations":[{"id":38179,"text":"USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":859061,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70271307,"text":"70271307 - 2022 - Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits","interactions":[],"lastModifiedDate":"2025-09-08T14:03:52.052483","indexId":"70271307","displayToPublicDate":"2022-12-03T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2746,"text":"Mineralium Deposita","active":true,"publicationSubtype":{"id":10}},"title":"Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits","docAbstract":"

The North Australian Zinc Belt is the largest zinc-lead province in the world, containing three of the ten largest known individual deposits (HYC, Hilton-George Fisher, and Mount Isa). The Northern Cordillera in North America is the second largest zinc-lead province, containing a further two of the world’s top ten deposits (Red Dog and Howards Pass). Despite this world-class endowment, exploration in both mineral provinces during the past 2 decades has not been particularly successful, yielding only two significant discoveries (Teena, Australia, and Boundary, Canada). One of the most important aspects of exploration is to choose mineral provinces and districts within geological belts that have the greatest potential for discovery. Here, we present results from these two zinc belts that highlight previously unused datasets for area selection and targeting. Lead isotope mapping using analyses of mineralized material has identified gradients in μ (238U/204Pb) that coincide closely with many major deposits. Locations of these deposits also coincide with a gradient in the depth of the lithosphere-asthenosphere boundary determined from calibrated surface wave tomography models converted to temperature. Furthermore, gradients in upward-continued gravity anomalies and a step in Moho depth correspond to a pre-existing major crustal boundary in both zinc belts. A spatial association of deposits with a linear mid- to lower-crustal resistivity anomaly from magnetotelluric data is also observed in the North Australian Zinc Belt. The change from thicker to thinner lithosphere is interpreted to localize prospective basins for zinc-lead mineralization and to control the gradient in lead isotope and geophysical data. These data, when combined with data indicative of paleoenvironment and changes in plate motion at the time of mineralization, provide new exploration criteria that can be used to identify prospective mineralized basins and define the most favorable parts of these basins.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s00126-022-01153-9","usgsCitation":"Huston, D.L., Champion, D.C., Czarnota, K., Duan, J., Hutchens, M., Paradis, S., Hoggard, M., Ware, B., Gibson, G.M., Doublier, M.P., Kelley, K.D., McCafferty, A.E., Hayward, N., Richards, F., Tessalina, S., and Carr, G., 2022, Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits: Mineralium Deposita, v. 58, p. 707-729, https://doi.org/10.1007/s00126-022-01153-9.","productDescription":"23 p.","startPage":"707","endPage":"729","ipdsId":"IP-135613","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495149,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495180,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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applications","interactions":[],"lastModifiedDate":"2026-03-30T20:49:48.631242","indexId":"ofr20221100","displayToPublicDate":"2022-12-02T13:49:32","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1100","displayTitle":"Verification of Multiple Phosphorus Analyzers for Use in Surface-Water Applications","title":"Verification of multiple phosphorus analyzers for use in surface-water applications","docAbstract":"

The U.S. Geological Survey (USGS) completed a verification study of selected commercially available phosphorus analyzers for their applicability to scientific surface-water applications. In this study, the analyzers were the Hach EZ7800 TOPHO, Hach Phosphax sc, Sea-Bird Scientific HydroCycle-PO4, and the YSI Inc. Alyza IQ PO4. Verification tests included laboratory trials comparing analyzer results to known standards with several known concentrations of dissolved organic matter and waste production estimates. Field trials were completed at the Vermilion River near Danville, Illinois (U.S. Geological Survey station 03339000), where analyzer-measured concentrations were compared against discrete samples across a wide range of environmental conditions from November 2020 to August 2021. Data coverage was closely tracked for analyzer malfunctions and operator errors that caused missing data. Laboratory and field trials indicated that each analyzer is a viable option for scientific surface-water studies depending on environmental conditions. Because of the complexity of the analyzers, a substantial time investiture was required to get maximum data coverage including considerable site infrastructure investments and well-trained technicians. Data coverage was closely related to each analyzer’s ability to handle elevated turbidity levels.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221100","collaboration":"Prepared in cooperation with the Next Generation Water Observing System","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"Peake, C.S., 2022, Verification of multiple phosphorus analyzers for use in surface-water applications: U.S. Geological Survey Open-File Report 2022–1100, 23 p., https://doi.org/10.3133/ofr20221100.","productDescription":"Report: viii, 23 p.; Dataset","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-139337","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":410009,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221100/full","text":"Report"},{"id":409997,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1100/ofr20221100.XML"},{"id":409995,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1100/coverthb.jpg"},{"id":501839,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113882.htm","linkFileType":{"id":5,"text":"html"}},{"id":409998,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1100/images"},{"id":409996,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1100/ofr20221100.pdf","text":"Report","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1100"},{"id":409999,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"}],"country":"United States","state":"Illinois, Indiana","otherGeospatial":"Vermilion River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.41449158849616,\n 39.979211528524246\n ],\n [\n -87.41449158849616,\n 40.79889755055865\n ],\n [\n -88.38087805821512,\n 40.79889755055865\n ],\n [\n -88.38087805821512,\n 39.979211528524246\n ],\n [\n -87.41449158849616,\n 39.979211528524246\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-12-02","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Peake, Colin S. 0000-0001-9712-1623","orcid":"https://orcid.org/0000-0001-9712-1623","contributorId":268354,"corporation":false,"usgs":true,"family":"Peake","given":"Colin","email":"","middleInitial":"S.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858230,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70238668,"text":"ofr20221080 - 2022 - Summary of extreme water-quality conditions in Upper Klamath Lake, Oregon, 2005–19","interactions":[],"lastModifiedDate":"2026-03-30T20:36:11.952009","indexId":"ofr20221080","displayToPublicDate":"2022-12-02T13:21:26","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1080","displayTitle":"Summary of Extreme Water-Quality Conditions in Upper Klamath Lake, Oregon, 2005–19","title":"Summary of extreme water-quality conditions in Upper Klamath Lake, Oregon, 2005–19","docAbstract":"

This study used the complete set of continuous water-quality (WQ) data and discrete measurements of total ammonia collected by the U.S. Geological Survey from 2005 to 2019 at the four core sites in Upper Klamath Lake, Oregon, to examine relations between variables and extreme conditions that may be harmful for endemic Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris). Several graphical and tabular approaches were used to compare variables, sites, and years to better understand the factors contributing to and timing of extreme WQ in the lake. Extreme WQ thresholds were defined as the 1st or 99th percentiles of the daily average dataset of water temperature, pH, and dissolved oxygen (DO) concentration, and the weekly estimated un-ionized ammonia (NH3) from 2005 to 2019. Extreme WQ days were defined as those when at least 12 hours of measurements exceeded the extreme WQ threshold. The core site at Mid-Trench, which was also the deepest measurement site with a full-pool depth of 15 meters and at which water-quality sondes were deployed at the top and bottom of the water column, had the most extreme conditions of high water temperature, low DO, and high NH3. The upper sonde at Mid-Trench represented 40 percent of all days of extremely high water temperature (days with at least 12 hours exceeding 24.38 degrees Celsius) in the lake and 71 percent of all weekly estimates of extremely high NH3 (greater than 264 micrograms per liter) in the lake. The lower sonde at Mid-Trench represented 85 percent of all days of extremely low DO (days with at least 12 hours of DO concentrations less than 1.76 milligrams per liter) in the lake. In each of the study years, poor water quality at Mid-Trench, as represented by several metrics, lasted for multiple days. The shallowest site at the Williamson River outlet represented 54 percent of all days of extremely high pH (days with at least 12 hours of pH measurements exceeding 10.04) in the lake. The seasonality of extreme WQ during the summer sampling period (limited to June through September) was evaluated and most days of extremely high water temperature (83 percent) and extremely high pH (54 percent) occurred in July, whereas most days of extremely low DO (57 percent) and extremely high NH3 (57 percent) occurred in August. The years with the most days of extreme WQ accumulated for all variables (high water temperature, low DO, high pH, and high NH3) were 2012–15 and 2017, which all occurred in the latter half of the study period. The years with the fewest accumulated days of extreme WQ were 2010 and 2011.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221080","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Wherry, S.A., 2022, Summary of extreme water-quality conditions in Upper Klamath Lake, Oregon, 2005–19: U.S. Geological Survey Open-File Report 2022–1080, 29 p., https://doi.org/10.3133/ofr20221080.","productDescription":"vii, 29 p.","onlineOnly":"Y","ipdsId":"IP-128098","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":501831,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113883.htm","linkFileType":{"id":5,"text":"html"}},{"id":410005,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1080/ofr20221080.XML"},{"id":410002,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1080/ofr20221080.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1080"},{"id":410001,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1080/coverthb.jpg"},{"id":410004,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1080/images"},{"id":410003,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221080/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1080"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.11865576927013,\n 42.623699726465674\n ],\n [\n -122.11865576927013,\n 42.185824493728575\n ],\n [\n -121.73017939010751,\n 42.185824493728575\n ],\n [\n -121.73017939010751,\n 42.623699726465674\n ],\n [\n -122.11865576927013,\n 42.623699726465674\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201

","tableOfContents":"","publishedDate":"2022-12-02","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Wherry, Susan A. 0000-0002-6749-8697 swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":4952,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":858231,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70238785,"text":"70238785 - 2022 - BIA branch of tribal climate resilience regional assessment report","interactions":[],"lastModifiedDate":"2022-12-12T15:38:22.405397","indexId":"70238785","displayToPublicDate":"2022-12-02T09:16:34","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":12977,"text":"Regional Assessment Report","active":true,"publicationSubtype":{"id":1}},"title":"BIA branch of tribal climate resilience regional assessment report","docAbstract":"

The Bureau of Indian Affairs (BIA) Branch of Tribal Climate Resilience (TCR) was established in 2011 to enable Tribal and BIA Office of Trust Services Programs to incorporate climate considerations into their programs' planning and decision-making. The TCR’s purpose is to fulfill trust responsibility to Federally recognized Tribal Nations by supporting and building Tribal capacity for climate resilience efforts through both technical and financial assistance. That financial assistance includes the TCR Annual Awards Program in which over 700 awards have been distributed totaling more than $74 million as of September 24th, 2021. The TCR has funded over 250 adaptation plans and vulnerability and risk assessments over the last 11 years. Tribes can leverage TCR programs to further support their existing operations, program planning, project design, as well as incorporate Indigenous and Traditional Knowledges into their management and protection of Trust resources and Tribal economies.

Due to the availability of TCR awards and other funding, many Tribes now have climate adaptation plans. Thus, both TCR and Tribes are at a new stage compared to a decade ago and have new needs related to implementation of climate adaptation and resiliency projects. This assessment aims to evaluate the effectiveness of TCR’s Annual Awards Program and technical assistance and incorporate direct Tribal input to meet Tribal needs and priorities. To provide more effective assistance to Tribal communities moving forward; BIA staff, in partnership with staff from the United States Geological Survey (USGS), interviewed 16 Tribal employees to gather their feedback on their approaches to climate adaptation as well as their experiences with TCR services. This report aims to summarize guidance from participating Tribes to inform future changes to BIA TCR.

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Center","active":true,"usgs":true}],"preferred":true,"id":858701,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238880,"text":"70238880 - 2022 - GPS data from 2019 and 2020 campaigns in the Chesapeake Bay region towards quantifying vertical land motions","interactions":[],"lastModifiedDate":"2022-12-15T13:54:31.86052","indexId":"70238880","displayToPublicDate":"2022-12-02T07:49:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"GPS data from 2019 and 2020 campaigns in the Chesapeake Bay region towards quantifying vertical land motions","docAbstract":"

The Chesapeake Bay is a region along the eastern coast of the United States where sea-level rise is confounded with poorly resolved rates of land subsidence, thus new constraints on vertical land motions (VLM) in the region are warranted. In this paper, we provide a description of two campaign-style Global Positioning System (GPS) datasets, explain the methods used in data collection and validation, and present the experiment designed to quantify a new baseline of VLM in the Chesapeake Bay region of eastern North America. Data from GPS campaigns in 2019 and 2020 are presented as ASCII RINEX2.11 files and logsheets for each observation from the campaigns. Data were quality checked using the open-source program TEQC, resulting in average multipath 1 and 2 values of 0.68 and 0.57, respectively. All data are archived and publicly available for open access at the geodesy facility UNAVCO to abide by Findable, Accessible, Interoperable, Reusable (FAIR) data principles.

","language":"English","publisher":"Nature","doi":"10.1038/s41597-022-01864-8","usgsCitation":"Troia, G., Stamps, S., Lotspeich, R., Duda, J.M., McCoy, K., Moore, W., Hensel, P., Hippenstiel, R., McKenna, T., Andreasen, D.C., Geoghegan, C., Ulizo, T.P., Kronebusch, M., Carr, J., Walters, D., and Winn, N., 2022, GPS data from 2019 and 2020 campaigns in the Chesapeake Bay region towards quantifying vertical land motions: Scientific Data, v. 9, no. 1, 744, 9 p., https://doi.org/10.1038/s41597-022-01864-8.","productDescription":"744, 9 p.","ipdsId":"IP-122566","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":445723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-022-01864-8","text":"Publisher Index Page"},{"id":410538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.29568067904435,\n 40.12967557474843\n ],\n [\n -77.29568067904435,\n 36.768971760646394\n ],\n [\n -75.43832592966815,\n 36.768971760646394\n ],\n [\n -75.43832592966815,\n 40.12967557474843\n ],\n [\n -77.29568067904435,\n 40.12967557474843\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Troia, Gabrielle 0000-0001-6566-4623","orcid":"https://orcid.org/0000-0001-6566-4623","contributorId":299921,"corporation":false,"usgs":false,"family":"Troia","given":"Gabrielle","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":859036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stamps, Sarah 0000-0002-3531-1752","orcid":"https://orcid.org/0000-0002-3531-1752","contributorId":299923,"corporation":false,"usgs":false,"family":"Stamps","given":"Sarah","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":859037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lotspeich, R. 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2022 - Giant planet observations in NASA's Planetary Data System","interactions":[],"lastModifiedDate":"2022-12-05T13:09:44.103743","indexId":"70238672","displayToPublicDate":"2022-12-02T07:05:44","publicationYear":"2022","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":"Giant planet observations in NASA's Planetary Data System","docAbstract":"

While there have been far fewer missions to the outer Solar System than to the inner Solar System, spacecraft destined for the giant planets have conducted a wide range of fundamental investigations, returning data that continues to reshape our understanding of these complex systems, sometimes decades after the data were acquired. These data are preserved and accessible from national and international planetary science archives. For all NASA planetary missions and instruments the data are available from the science discipline nodes of the NASA Planetary Data System (PDS). Looking ahead, the PDS will be the primary repository for giant planets data from several upcoming missions and derived datasets, as well as supporting research conducted to aid in the interpretation of the remotely sensed giant planets data already archived in the PDS.

","language":"English","publisher":"MDPI","doi":"10.3390/rs14236112","usgsCitation":"Chanover, N.J., Bauer, J.M., Blalock, J.J., Gordon, M.K., Huber, L.F., Mace, M.J., Neakrase, L., Tiscareno, M.S., and Walker, R.J., 2022, Giant planet observations in NASA's Planetary Data System: Remote Sensing, v. 14, no. 23, 6112, 26 p., https://doi.org/10.3390/rs14236112.","productDescription":"6112, 26 p.","ipdsId":"IP-145743","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":445726,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14236112","text":"Publisher Index Page"},{"id":410048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Jupiter, Neptune, Saturn, Uranus","volume":"14","issue":"23","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Chanover, Nancy J. 0000-0002-9984-4670","orcid":"https://orcid.org/0000-0002-9984-4670","contributorId":299617,"corporation":false,"usgs":false,"family":"Chanover","given":"Nancy","email":"","middleInitial":"J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":858234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bauer, James M. 0000-0001-9542-0953","orcid":"https://orcid.org/0000-0001-9542-0953","contributorId":299619,"corporation":false,"usgs":false,"family":"Bauer","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":858235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blalock, John Joe Jeremiah 0000-0002-7460-1074","orcid":"https://orcid.org/0000-0002-7460-1074","contributorId":299621,"corporation":false,"usgs":true,"family":"Blalock","given":"John","email":"","middleInitial":"Joe Jeremiah","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":858236,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gordon, Mitchell K. 0000-0003-0985-2800","orcid":"https://orcid.org/0000-0003-0985-2800","contributorId":299625,"corporation":false,"usgs":false,"family":"Gordon","given":"Mitchell","email":"","middleInitial":"K.","affiliations":[{"id":37319,"text":"SETI Institute","active":true,"usgs":false}],"preferred":false,"id":858237,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huber, Lyle F. 0000-0002-1232-1982","orcid":"https://orcid.org/0000-0002-1232-1982","contributorId":299628,"corporation":false,"usgs":false,"family":"Huber","given":"Lyle","email":"","middleInitial":"F.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":858238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mace, Mia J. T. 0000-0002-9905-816X","orcid":"https://orcid.org/0000-0002-9905-816X","contributorId":299631,"corporation":false,"usgs":false,"family":"Mace","given":"Mia","email":"","middleInitial":"J. T.","affiliations":[{"id":37319,"text":"SETI Institute","active":true,"usgs":false}],"preferred":false,"id":858239,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neakrase, Lynn D. V.","contributorId":299634,"corporation":false,"usgs":false,"family":"Neakrase","given":"Lynn D. V.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":858240,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tiscareno, Matthew S. 0000-0002-2736-3667","orcid":"https://orcid.org/0000-0002-2736-3667","contributorId":299637,"corporation":false,"usgs":false,"family":"Tiscareno","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":37319,"text":"SETI Institute","active":true,"usgs":false}],"preferred":false,"id":858241,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walker, Raymond J. 0000-0002-5092-5699","orcid":"https://orcid.org/0000-0002-5092-5699","contributorId":299640,"corporation":false,"usgs":false,"family":"Walker","given":"Raymond","email":"","middleInitial":"J.","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":858242,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70240837,"text":"70240837 - 2022 - Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon","interactions":[],"lastModifiedDate":"2023-02-24T13:00:00.092972","indexId":"70240837","displayToPublicDate":"2022-12-02T06:57:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1430,"text":"Earth, Planets and Space","active":true,"publicationSubtype":{"id":10}},"title":"Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon","docAbstract":"

Laterally directed explosive eruptions are responsible for multiple fatalities over the past decade and are an increasingly important volcanology problem. To understand the energy dynamics for these events, we collected field-scale explosion data from nine acoustic sensors surrounding a tiltable cannon as part of an exploratory experimental design. For each cannon discharge, the blast direction was varied systematically at 0°, 12°, and 24° from vertical, capturing acoustic wavefield directivity related to the tilt angle. While each event was similar in energy discharge potential, the resulting acoustic signal features were variable event-to-event, producing non-repetitious waveforms and spectra. Systematic features were observed in a subset of individual events for vertical and lateral discharges. For vertical discharges, the acoustic energy had a uniform radiation pattern. The lateral discharges showed an asymmetric radiation pattern with higher frequencies in the direction of the blast and depletion of those frequencies behind the cannon. Results suggest that, in natural volcanic systems, near-field blast directionality may be elucidated from acoustic sensors in absence of visual data, with implications for volcano monitoring and hazard assessment.

","language":"English","publisher":"Springer","doi":"10.1186/s40623-022-01732-0","usgsCitation":"Jolly, A., Kennedy, B., Matoza, R.S., Iezzi, A., Christensen, B.W., Johnson, R., Sork, A., and Fee, D., 2022, Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon: Earth, Planets and Space, v. 74, 177, 16 p., https://doi.org/10.1186/s40623-022-01732-0.","productDescription":"177, 16 p.","ipdsId":"IP-138530","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40623-022-01732-0","text":"Publisher Index Page"},{"id":413396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Jolly, A.D. 0000-0003-1020-9062","orcid":"https://orcid.org/0000-0003-1020-9062","contributorId":296487,"corporation":false,"usgs":true,"family":"Jolly","given":"A.D.","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":865016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Benjamin","contributorId":302666,"corporation":false,"usgs":false,"family":"Kennedy","given":"Benjamin","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":865017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":865018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":196436,"corporation":false,"usgs":false,"family":"Iezzi","given":"Alexandra M.","affiliations":[],"preferred":false,"id":865019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Bruce W.","contributorId":196298,"corporation":false,"usgs":false,"family":"Christensen","given":"Bruce","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":865020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Richard","contributorId":190189,"corporation":false,"usgs":false,"family":"Johnson","given":"Richard","email":"","affiliations":[],"preferred":false,"id":865021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sork, Amilea","contributorId":302667,"corporation":false,"usgs":false,"family":"Sork","given":"Amilea","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":865022,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":865023,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238684,"text":"70238684 - 2022 - Can we avert an Amazon tipping point? The economic and environmental costs","interactions":[],"lastModifiedDate":"2022-12-05T12:37:03.967845","indexId":"70238684","displayToPublicDate":"2022-12-02T06:32:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Can we avert an Amazon tipping point? The economic and environmental costs","docAbstract":"

The Amazon biome is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer be possible. This degradation is the result of self-reinforcing interactions between deforestation, climate change and fire. We assess the economic, natural capital and ecosystem services impacts and trade-offs of scenarios representing movement towards an Amazon tipping point and strategies to avert one using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with spatial land use-land cover change and ecosystem services modeling (IEEM + ESM). Our approach provides the first approximation of the economic, natural capital and ecosystem services impacts of a tipping point, and evidence to build the economic case for strategies to avert it. For the five Amazon focal countries, namely, Brazil, Peru, Colombia, Bolivia and Ecuador, we find that a tipping point would create economic losses of US$256.6 billion in cumulative gross domestic product by 2050. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in intensifying agriculture in cleared lands, climate-adapted agriculture and improving fire management, would generate approximately US$339.3 billion in additional wealth and a return on investment of US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can support the design of regional development strategies for the Amazon biome, build the business case for action and catalyze global cooperation and financing to enable policy implementation.

","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/aca3b8","usgsCitation":"Banerjee, O., Cicowiez, M., Macedo, M., Malek, Z., Verburg, P.H., Goodwin, S., Vargas, R., Rattis, L., Bagstad, K.J., Brando, P.M., Coe, M.T., Neill, C., Damiani Marti, O., and Avila Murillo, J., 2022, Can we avert an Amazon tipping point? 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Josue","contributorId":299658,"corporation":false,"usgs":false,"family":"Avila Murillo","given":"Josue","email":"","affiliations":[{"id":64921,"text":"Interamerican Development Bank","active":true,"usgs":false}],"preferred":false,"id":858268,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70236050,"text":"70236050 - 2022 - Wetland ecosystem health and biodiversity","interactions":[],"lastModifiedDate":"2024-03-27T20:46:12.939206","indexId":"70236050","displayToPublicDate":"2022-12-01T15:45:15","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"chapter":"14","title":"Wetland ecosystem health and biodiversity","docAbstract":"

• Cropland expansion from 2008 to 2016 was mostly from losses of grassland (88%), with 3% losses from wetlands (a total of nearly 275,000 acres of wetlands, concentrated in the Prairie Pothole Region). Given the lack of national or regional datasets to track changes in RFS acreage, the extent of wetland losses directly attributable to the RFS cannot be more accurately estimated in the RtC3.

• Wetlands gains and losses are not distributed evenly across wetland types or sizes. Since 2007, the nation has lost 120.3 thousand acres of palustrine (marsh-like) wetlands and gained 205.9 thousand acres of lacustrine (lake-like) habitats in the conterminous United States. The diverse wetlands within these classes support different species and perform different ecosystem functions, including loss of functions that impact watershed hydrology, water quality, and water quantity.

• Small, seasonal wetlands are being lost at the fastest rate. The loss and consolidation of small wetlands to promote crop production has negatively impacted amphibians, invertebrates, and other aquatic species that depend on shallow water depths for reproduction. Shifts to longer hydroperiods in large or consolidated wetlands have more uniform (less diverse) invertebrate communities and can support fish that prey on insects and amphibians.

• Small wetlands and ponds are primary sources of water for aquifer recharge in the Northern Prairies. Recent studies in the Canadian portion of the Prairie Pothole Region found that while permanent ponds and wetlands are sources for recharge to aquifers, wetlands with surface water ponds that dry out every year play the dominant role in groundwater replenishment.

• While some Endangered Species Act-listed and other waterbirds have declined, waterfowl (ducks, geese, swans) as a group have not experienced declines over the past decade, possibly due to availability of food (grains), increased precipitation, and the interspersion of ponded waters and agricultural fields along migration routes.

• Shifts to corn and soybean production have resulted in more frequent application of chemicals, including pesticides and fertilizers. Increased usage of neonicotinoid insecticides is of particular concern because of their high toxicity to invertebrates, which are important food sources for wetland-dependent taxa.

• Evidence from the Prairie Pothole Region suggests that trends in larger wetland size, shifts to lakes and ponds (vs. vegetated wetlands), and prolonged and more frequent flooding are due to the combined effects of climate change and increased wetland ditching and consolidation. These trends are highly correlated with increased annual precipitation, which is projected to continue.

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Mitigating risk to migratory birds from energy development requires information on the distribution and abundance of seabirds in offshore waters. Seabirds are highly mobile, with species-specific seasonal migrations that result in variable patterns of distribution in space and time. In remote offshore marine areas, obtaining useful and current information on resources is difficult to achieve and maintain, both fiscally and logistically, necessitating collaborative effort (Danielson et al. 2022). We used seabird at-sea survey data (2007-2021) and new modeling techniques to develop spatio-temporal models of seasonal abundance and distribution of species in waters of the Pacific Arctic. For six species groups selected as model test cases, we identified fine-scale distributions for each year, using data collected during summer to early fall (June through September). Our approach uses the best available data and can be updated as new data are generated, providing up-to-date information for regions with existing or potential future oil and gas development.

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No abstract available.

","conferenceTitle":"3ECEES - Third European Conference on Earthquake Engineering & Seismology","conferenceDate":"September 4-9, 2022","conferenceLocation":"Bucharest, Romania","language":"English","publisher":"Conspress","usgsCitation":"Bent, A.L., Mayeda, K., Roman-Nieves, J., Shelly, D.R., and Barno, J., 2022, Progress and challenges toward the development of a uniform moment magnitude catalog for eastern Canada, 3ECEES - Third European Conference on Earthquake Engineering & Seismology, Bucharest, Romania, September 4-9, 2022, p. 5105-5111.","productDescription":"7 p.","startPage":"5105","endPage":"5111","ipdsId":"IP-139522","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":501501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bent, Allison L.","contributorId":239555,"corporation":false,"usgs":false,"family":"Bent","given":"Allison","email":"","middleInitial":"L.","affiliations":[{"id":47914,"text":"Canadian Hazards Information Service","active":true,"usgs":false}],"preferred":false,"id":894659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mayeda, Kevin","contributorId":289896,"corporation":false,"usgs":false,"family":"Mayeda","given":"Kevin","email":"","affiliations":[{"id":62278,"text":"Air Force Technical Applications Center, USA","active":true,"usgs":false}],"preferred":false,"id":894660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roman-Nieves, Jorge I.","contributorId":334069,"corporation":false,"usgs":false,"family":"Roman-Nieves","given":"Jorge I.","affiliations":[{"id":80057,"text":"Air Force Technical Applications Center","active":true,"usgs":false}],"preferred":false,"id":894661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":894662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barno, Justin","contributorId":289897,"corporation":false,"usgs":false,"family":"Barno","given":"Justin","email":"","affiliations":[{"id":62279,"text":"Lawrence Livermore National Laboratory, Livermore, CA, USA","active":true,"usgs":false}],"preferred":false,"id":894663,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70263604,"text":"70263604 - 2022 - Assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources of the United States","interactions":[],"lastModifiedDate":"2025-02-18T16:43:58.785838","indexId":"70263604","displayToPublicDate":"2022-12-01T10:38:16","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources of the United States","docAbstract":"

In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources that could be produced using current carbon dioxide enhanced oil recovery (CO2-EOR) technologies in amenable conventional oil reservoirs underlying onshore and State-owned offshore waters (herein after, onshore and State waters areas) of the conterminous United States. Our assessment also includes estimates of the mass of CO2 that could be stored (retained) in the assessed oil reservoirs following the application of the CO2-EOR process. The USGS assessment team evaluated more than 3,500 oil reservoirs that were amenable to miscible CO2 injection. The assessed reservoirs are located in 185 plays previously defined by a USGS National Oil and Gas Assessment in 33 petroleum provinces of seven national regions. The team estimated that the total technically recoverable oil resulting from the application of the CO2-EOR process ranges from approximately 25,000 million barrels (MMbbl) at the P5 probability percentile to as much as 32,000 MMbbl at the P95 probability percentile, with a mean of 29,000 MMbbl. The associated CO2 retention ranges from approximately 7,400 million metric tons (Mt) at the P5 percentile to as much as 9,500 Mt at the P95 percentile, with a mean of 8,400 Mt.

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0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":224150,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":927533,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":927534,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lohr, Celeste D. 0000-0001-6287-9047 clohr@usgs.gov","orcid":"https://orcid.org/0000-0001-6287-9047","contributorId":3866,"corporation":false,"usgs":true,"family":"Lohr","given":"Celeste D.","email":"clohr@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":927535,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Merrill, Matthew D. 0000-0003-3766-847X","orcid":"https://orcid.org/0000-0003-3766-847X","contributorId":205698,"corporation":false,"usgs":true,"family":"Merrill","given":"Matthew D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":927536,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":328734,"corporation":false,"usgs":false,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":false,"id":927537,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Shelton, Jenna L. 0000-0002-1377-0675 jlshelton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-0675","contributorId":5025,"corporation":false,"usgs":true,"family":"Shelton","given":"Jenna L.","email":"jlshelton@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":927538,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Slucher, Ernie R. 0000-0002-5865-5734 eslucher@usgs.gov","orcid":"https://orcid.org/0000-0002-5865-5734","contributorId":3966,"corporation":false,"usgs":true,"family":"Slucher","given":"Ernie","email":"eslucher@usgs.gov","middleInitial":"R.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":927539,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Varela, Brian A. 0000-0001-9849-6742 bvarela@usgs.gov","orcid":"https://orcid.org/0000-0001-9849-6742","contributorId":178091,"corporation":false,"usgs":true,"family":"Varela","given":"Brian","email":"bvarela@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":927540,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70242775,"text":"70242775 - 2022 - Supplemental vegetation monitoring plots at Little Bighorn Battlefield National Monument to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","interactions":[],"lastModifiedDate":"2024-03-05T16:34:42.657934","indexId":"70242775","displayToPublicDate":"2022-12-01T10:29:26","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":7577,"text":"Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Supplemental vegetation monitoring plots at Little Bighorn Battlefield National Monument to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","docAbstract":"The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains (NGP) working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.” The original ABAM model has little information about the effects of the herbicide indaziflam (Esplanade or Rejuvra, Bayer Environmental Sciences) on target invasive annual grasses and other components of the vegetation in conditions like those that frequently occur in ABAM parks (i.e., ungrazed). The purpose of this study is to provide some of that information in order to accelerate the rate of learning accomplished in the adaptive management cycle. This annual report to the partner provides that information as collected in 2022 in 3 plots at Little Bighorn Battlefield National Monument.","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., and Bekedam, S., 2022, Supplemental vegetation monitoring plots at Little Bighorn Battlefield National Monument to accelerate learning of the Annual Brome Adaptive Management (ABAM) model: Annual Report, 3 p.","productDescription":"3 p.","ipdsId":"IP-152074","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415840,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573321","linkFileType":{"id":5,"text":"html"}},{"id":426326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Little Bighorn Battlefield National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.42780937203189,\n 45.55613907753829\n ],\n [\n -107.41424157476726,\n 45.56297486244455\n ],\n [\n -107.42644541357662,\n 45.57478473659421\n ],\n [\n -107.44274112775177,\n 45.56674424099478\n ],\n [\n -107.44575619381031,\n 45.566543213856875\n ],\n [\n -107.44259755317754,\n 45.56327642203598\n ],\n [\n -107.43943891254428,\n 45.56151730159996\n ],\n [\n -107.4385056778117,\n 45.560763375980855\n ],\n [\n -107.44123359472226,\n 45.55814968884059\n ],\n [\n -107.43814674137612,\n 45.55679253410301\n ],\n [\n -107.43584954818878,\n 45.55789836636245\n ],\n [\n -107.43412665329791,\n 45.56016022820128\n ],\n [\n -107.43218839654568,\n 45.55855180246806\n ],\n [\n -107.43419844058504,\n 45.55593801245129\n ],\n [\n -107.43075265080329,\n 45.555586146818285\n ],\n [\n -107.42780937203189,\n 45.55613907753829\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekedam, Steven","contributorId":240924,"corporation":false,"usgs":false,"family":"Bekedam","given":"Steven","email":"","affiliations":[{"id":29837,"text":"National Park Service, Yellowstone National Park, WY","active":true,"usgs":false}],"preferred":false,"id":895966,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238432,"text":"sir20225101 - 2022 - Stormwater reduction and water budget for a rain garden on sandy soil, Gary, Indiana, 2016–18","interactions":[],"lastModifiedDate":"2022-12-01T16:34:22.21762","indexId":"sir20225101","displayToPublicDate":"2022-12-01T10:20:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5101","displayTitle":"Stormwater Reduction and Water Budget for a Rain Garden on Sandy Soil, Gary, Indiana, 2016–18","title":"Stormwater reduction and water budget for a rain garden on sandy soil, Gary, Indiana, 2016–18","docAbstract":"

Stormwater reduction measures, or green infrastructure, were implemented in the parking area at Gary City Hall, Gary, Indiana, with the intention of reducing stormwater discharge to the sewers. A study area, including a centrally located rain garden and the surrounding paved surfaces and green space, was instrumented during both a preconstruction and a postconstruction period to (1) develop water budgets to improve understanding of the rain garden hydrology and (2) determine the quantity of stormwater runoff that was diverted and retained by the green infrastructure instead of reaching the combined storm and sanitary sewer. The study was focused on warm-season precipitation and was monitored during spring, summer, and fall of 2016, 2017 and 2018.

Before construction of the rain garden in the parking lot of Gary City Hall in 2017, nearly all precipitation was conveyed away from the parking lot by underground drains, discharged to the sewer, and treated as sanitary waste at the Gary Sanitary District’s treatment plant or discharged directly to local waterways if stormflow exceeded capabilities of the sewage treatment plant. A goal of the Great Lakes Restoration Initiative is the reduction of sewer overflows to local waterways to improve the quality of water entering the Great Lakes. Cities such as Gary benefit financially and environmentally by reducing discharges of stormwater runoff to the sewer system, eliminating the need for treatment. Before implementation of green infrastructure at Gary City Hall, approximately 25 percent of precipitation (approximately 10,200 cubic feet) discharged as stormwater to the sewers through the parking lot drain. After implementation, 2 percent of precipitation discharged to the sewers. For the spring, summer, and fall seasons of 2017 and 2018, 21–24 percent (about 10,700–19,700 cubic feet) of precipitation was captured by the newly installed rain garden. Stormwater discharged to the rain garden infiltrated the sandy soil and was later evaporated from the soil surface, was transpired by plants, or recharged the underlying groundwater aquifer. The percent reduction in stormwater discharged to the storm sewer after the construction of the rain garden was 80.3 percent, equating to approximately 21,400 and 39,300 gallons of stormwater in 2017 and 2018, respectively.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225101","collaboration":"Prepared in cooperation with the Great Lakes Restoration Initiative","usgsCitation":"Lampe, D.C., Bayless, E.R., and Follette, D.D., 2022, Stormwater reduction and water budget for a rain garden on sandy soil, Gary, Indiana, 2016–18: U.S. Geological Survey Scientific Investigations Report 2022–5101, 39 p., https://doi.org/10.3133/sir20225101.","productDescription":"Report: viii, 39 p.; Data Release","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-126798","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":409550,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H5RNNE","text":"USGS data release","linkHelpText":"Groundwater recharge estimates for a green infrastructure installation at Gary City Hall, Gary, Indiana 2016–18"},{"id":409545,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5101/coverthb.jpg"},{"id":409546,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5101/sir20225101.pdf","text":"Report","size":"7.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5101"},{"id":409548,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5101/sir20225101.XML"},{"id":409549,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5101/images/"}],"country":"United States","state":"Indiana","city":"Gary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.33719284301965,\n 41.60392762249708\n ],\n [\n -87.33719284301965,\n 41.602552401500475\n ],\n [\n -87.33581350339763,\n 41.602552401500475\n ],\n [\n -87.33581350339763,\n 41.60392762249708\n ],\n [\n -87.33719284301965,\n 41.60392762249708\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-12-01","noUsgsAuthors":false,"publicationDate":"2022-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Lampe, David C. 0000-0002-8904-0337 dclampe@usgs.gov","orcid":"https://orcid.org/0000-0002-8904-0337","contributorId":2441,"corporation":false,"usgs":true,"family":"Lampe","given":"David","email":"dclampe@usgs.gov","middleInitial":"C.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":857479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bayless, E. Randall 0000-0002-0357-3635","orcid":"https://orcid.org/0000-0002-0357-3635","contributorId":42586,"corporation":false,"usgs":true,"family":"Bayless","given":"E.","email":"","middleInitial":"Randall","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":857480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Follette, Danielle D. 0000-0002-3203-813X","orcid":"https://orcid.org/0000-0002-3203-813X","contributorId":299291,"corporation":false,"usgs":true,"family":"Follette","given":"Danielle","email":"","middleInitial":"D.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":857481,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238110,"text":"70238110 - 2022 - Bivalves","interactions":[],"lastModifiedDate":"2026-03-18T15:25:15.112087","indexId":"70238110","displayToPublicDate":"2022-12-01T10:19:37","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":12617,"text":"IEP Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"98","chapter":"5","title":"Bivalves","docAbstract":"

Bivalves are important as consumers of pelagic and demersal food resources. With sufficient biomass, they can compete with and, in some cases, outcompete other members of the pelagic food web for food resources such as phytoplankton and zooplankton.  We include bivalves in the San Francisco Estuary (SFE) and Delta in the FLOAT MAST because they have been and continue to be an important member of the food web. Changes in the bivalves over the last 40 years have led us to hypothesize that bivalves may limit food resources for Delta Smelt and other pelagic fish species (Kimmerer and Thompson 2014, Sommer et al 2007).

We will discuss the two bivalves with the largest biomass, the estuarine bivalve Potamocorbula amurensis (hereafter Potamocorbula) and the freshwater bivalve Corbicula fluminea (hereafter Corbicula).  The distribution of these two species together covers the full range of salinities between the Golden Gate and the upstream reaches of the SR and SJR.  The species overlap in the region of X2.  Both species’ distributions expand or contract when the salinity distribution changes and do so in near synchrony with each other at a salinity of approximately 2.   It is this interaction of both bivalves at their threshold levels of salinity within the ecologically sensitive low salinity zone (LSZ) in addition to their distribution in the rest of the system that determines each species effect on the food web.  

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The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains (NGP) working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.”

The ABAM model includes treatments in which the herbicides indaziflam and imazapic are applied alone or in combination with or without a prescribed fire preceding or following their application. However, the original ABAM model did not have field data for the effects of those treatments on target invasive annual grasses and other components of the vegetation in conditions like those that frequently occur in ABAM parks (i.e., ungrazed). The purpose of this study is to increase the amount of information about these treatments and therefore accelerate the rate of learning accomplished in the adaptive management cycle.

","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., and Richardson, T., 2022, Supplemental vegetation monitoring plots at Wind Cave National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model: Annual Report, 4 p.","productDescription":"4 p.","ipdsId":"IP-152075","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415835,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573317","linkFileType":{"id":5,"text":"html"}},{"id":426321,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Wind Cave National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.49938816977327,\n 43.633694711675986\n ],\n [\n -103.5024470931983,\n 43.55944982284214\n ],\n [\n -103.52141241843475,\n 43.54383294926339\n ],\n [\n -103.52202420312013,\n 43.52023368800823\n ],\n [\n -103.45748091884613,\n 43.51534889803226\n ],\n [\n -103.45657280095472,\n 43.53372182682589\n ],\n [\n -103.43975828125109,\n 43.5356829718161\n ],\n [\n -103.44038918420713,\n 43.58528414983906\n ],\n [\n -103.41717960271762,\n 43.58473704935065\n ],\n [\n -103.41664429111844,\n 43.56545928494155\n ],\n [\n -103.38062546778514,\n 43.56346760240271\n ],\n [\n -103.38009015618593,\n 43.56812536845743\n ],\n [\n -103.36058951934952,\n 43.56694573600919\n ],\n [\n -103.3588306383801,\n 43.592360590123576\n ],\n [\n -103.34185361336944,\n 43.59180514516018\n ],\n [\n -103.33680638971731,\n 43.60876454212675\n ],\n [\n -103.33665344354603,\n 43.62660987781496\n ],\n [\n -103.3485832449052,\n 43.62505981511873\n ],\n [\n -103.35317163004311,\n 43.63059510828057\n ],\n [\n -103.43729202423958,\n 43.63170210623065\n ],\n [\n -103.45365726456492,\n 43.640225573499706\n ],\n [\n -103.48019342527975,\n 43.641830445497\n ],\n [\n -103.49938816977327,\n 43.633694711675986\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, Timm","contributorId":334581,"corporation":false,"usgs":false,"family":"Richardson","given":"Timm","email":"","affiliations":[],"preferred":false,"id":895967,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238720,"text":"70238720 - 2022 - PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate acid mine drainage treatment strategies for recovery of rare-earth elements","interactions":[],"lastModifiedDate":"2024-02-23T16:04:23.105819","indexId":"70238720","displayToPublicDate":"2022-12-01T09:55:30","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate acid mine drainage treatment strategies for recovery of rare-earth elements","docAbstract":"

The PHREEQ-N-AMDTreat+REYs water-quality modeling tools have the fundamental capability to simulate aqueous chemical reactions and predict the formation of metal-rich solids during the treatment of acid mine drainage (AMD). These new user-friendly, publicly available tools were expanded from the PHREEQ-N-AMDTreat tools to include the precipitation of rare-earth elements plus yttrium (REYs) and the adsorption of REYs onto hydrous Fe, Al, and Mn oxides. The tool set consists of a caustic titration model that indicates equilibrium surface and aqueous speciation of REYs as functions of pH and caustic agent, and a kinetics+adsorption model that simulates progressive changes in pH, major ions, and REYs in water and solids during sequential steps through passive and/or active treatment. Each model has a user interface (UI) that facilitates the input of water-quality data and adjustment to geochemical or treatment system variables; for example, retention time and aeration rate are adjustable parameters in the kinetics model. On-screen graphs display results of changes in metals and associated solute concentrations as functions of pH or retention time; details are summarized in output tables. A goal of such modeling is to identify strategies that could produce a concentrated REYs extract from AMD or mine waste leachate. For example, if REYs could be concentrated after first removing substantial Fe and Al, the final REYs-bearing phase(s) could be more efficiently processed for REYs recovery and, therefore, may represent a more valuable commodity. Preliminary modeling supports the hypothesis that Fe and Al can be removed at pH < 5.5 using conventional sequential oxidation and neutralization treatment processes without removing REYs, and that further increasing pH can promote the adsorption of REYs by hydrous Mn oxides. Alternatively, chemicals such as oxalate or phosphate may be added to precipitate REYs compounds following initial steps to decrease Fe and Al concentrations. The aqueous geochemical model framework is comprehensive and permits evaluation of effects from interactive chemical and physical variables. Field studies that demonstrate REYs attenuation from AMD and corresponding solid-phase formation during specific treatment steps plus laboratory studies of aqueous/solid interactions are helpful to corroborate, refine, and constrain modelin parameters.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th International Conference on Acid Mine Drainage","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th International Conference on Acid Mine Drainage","conferenceDate":"September 18-24, 2022","language":"English","publisher":"University of Queensland","usgsCitation":"Cravotta, C., 2022, PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate acid mine drainage treatment strategies for recovery of rare-earth elements, in Proceedings of the 12th International Conference on Acid Mine Drainage, September 18-24, 2022, p. 788-804.","productDescription":"7 p.","startPage":"788","endPage":"804","ipdsId":"IP-137202","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":410097,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://smi.uq.edu.au/conferences/international-conference-acid-rock-drainage-2022","linkFileType":{"id":5,"text":"html"}},{"id":425945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":207249,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858359,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70263323,"text":"70263323 - 2022 - Understory structure and heterospecifics influence the occupancy of a ground-nesting species of conservation concern, the Canada Warbler","interactions":[],"lastModifiedDate":"2025-02-06T16:00:27.11247","indexId":"70263323","displayToPublicDate":"2022-12-01T09:54:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Understory structure and heterospecifics influence the occupancy of a ground-nesting species of conservation concern, the Canada Warbler","docAbstract":"

Forest structure and composition in eastern U.S. forests are changing because of forest regeneration after farmland abandonment, less frequent occurrence of severe disturbances, and climate change. Some of these changes may disproportionally affect birds that rely on gap dynamics or other forest canopy disturbances to create understory habitat. The Canada Warbler (Cardellina canadensis) is one such understory specialist that has undergone consistent declines. We assessed environmental and interspecific factors associated with Canada Warbler space use in its southern breeding distribution to understand potential causes of population declines and inform conservation efforts. We evaluated Canada Warbler occupancy from 840 point count surveys conducted in 2017 and 2018 at 470 unique locations (79% of locations surveyed in both years) throughout Monongahela National Forest, West Virginia, USA. We modeled Canada Warbler occupancy probability as a function of environmental variables and included Black-throated Blue Warbler (Setophaga caerulescens) and Hermit Thrush (Catharus guttatus) as interacting species because all three species exhibit similar habitat preferences. Canada Warblers were most likely to occur in areas with rhododendron (Rhododendron maximum) density > 0.27 stems/m² and within 3 m of riparian areas (streams and wetlands). They were also more likely to occur in mid-elevation (highest occupancy at 930 m) northern hardwood forests when Black-throated Blue Warblers were also present. Black-throated Blue Warblers were most likely to occupy mid-elevation sites with high shrub density, whereas Hermit Thrushes were more likely to occupy high-elevation, old-age forests. Potential management actions could focus on conserving riparian areas in northern hardwood forests, especially those with dense rhododendron thickets. Such potential actions could also be beneficial across the entire elevation range we explored within the region (500–1300 m). Canada Warblers may be benefiting from the recent spread of rhododendron habitats and northern hardwood forest types within West Virginia.

","language":"English","publisher":"Resilience Alliance Publications","doi":"10.5751/ace-02079-170120","usgsCitation":"Dimmig, G., Rota, C., Wood, P.B., and Lituma, C., 2022, Understory structure and heterospecifics influence the occupancy of a ground-nesting species of conservation concern, the Canada Warbler: Avian Conservation and Ecology, v. 17, no. 1, 20, 16 p., https://doi.org/10.5751/ace-02079-170120.","productDescription":"20, 16 p.","ipdsId":"IP-123270","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":487031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02079-170120","text":"Publisher Index Page"},{"id":481747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United sTates","state":"West Virginia","otherGeospatial":"Monongahela National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.58889045378262,\n 37.463537077379684\n ],\n [\n -80.3485425975682,\n 37.51121532612136\n ],\n [\n -79.62749902892529,\n 38.552413228981266\n ],\n [\n -79.33707870266615,\n 38.442685588318085\n ],\n [\n -78.8463684962287,\n 39.0674460432719\n ],\n [\n -79.48729611280025,\n 39.1995023289459\n ],\n [\n -79.48729611280025,\n 39.455139390658985\n ],\n [\n -79.8978903671664,\n 39.37777230668391\n ],\n [\n -81.23983256436323,\n 37.88364086385796\n ],\n [\n -81.01951369616684,\n 37.54298391685913\n ],\n [\n -80.58889045378262,\n 37.463537077379684\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dimmig, Gordon W.","contributorId":350556,"corporation":false,"usgs":false,"family":"Dimmig","given":"Gordon W.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":926339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rota, Christopher T.","contributorId":350557,"corporation":false,"usgs":false,"family":"Rota","given":"Christopher T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":926340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":926338,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lituma, Christopher M.","contributorId":350558,"corporation":false,"usgs":false,"family":"Lituma","given":"Christopher M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":926341,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237132,"text":"70237132 - 2022 - Soils","interactions":[],"lastModifiedDate":"2023-01-13T15:59:55.675314","indexId":"70237132","displayToPublicDate":"2022-12-01T09:52:33","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"chapter":"V","title":"Soils","docAbstract":"Soils play a strong role in determining how New Mexico’s diverse landscapes will respond to climate change. Soil cover acts like a sponge, holding in water that falls as rain or snow. The presence of soil supports vegetation, and substantially reduces runoff and erosion. Soil enhances other processes such as infiltration of water and aquifer recharge. Soils can be damaged by a warming climate. Loss of vegetation in the Northwest High Desert and Eastern Plains, where soils are not well developed and easily damaged, will lead to dustier conditions in much of the state. On mountain hillslopes, the loss of vegetation cover in response to ongoing climate change will increase soil erosion, which then increases hillslope runoff. This, in turn, causes additional increases in soil erosion and bedrock exposure, which can largely prevent widespread recolonization by most plants, including trees. Soils on mountain hillslopes that face south, which are typically hotter and drier, will be damaged sooner by a warming climate than those on generally north-facing hillslopes that are slightly cooler and moister. Soils take many thousands of years to form, so these hillslopes will increasingly support sparse forests, or, in some circumstances, be entirely deforested. 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