The natal environment can have long-term fitness consequences for individuals, particularly via ‘silver spoon’ or ‘environmental matching’ effects. Invasive species could alter natal effects on native species by changing species interactions, but this potential remains unknown. Using 17 years of data on 2588 individuals across the entire US breeding range of the endangered snail kite (Rostrhamus sociabilis), a wetland raptor that feeds entirely on Pomacea snails, we tested for silver spoon and environmental matching effects on survival and movement and whether the invasion of a non-native snail may alter outcomes. We found support for silver spoon effects, not environmental matching, on survival that operated through body condition at fledging, explained by hydrology in the natal wetland. When non-native snails were present at the natal site, kites were in better condition, individual condition was less sensitive to hydrology, and kites fledged across a wider range of hydrologic conditions, leading to higher survival that persisted for at least 10 years. Movement between wetlands was driven by the current (adult) environment, and birds born in both invaded and uninvaded wetlands preferred to occupy invaded wetlands post-fledging. These results illustrate that species invasions may profoundly impact the role of natal environments on native species.
There are numerous global ocean wave reanalysis and hindcast products currently being distributed and used across different scientific fields. However, there is not a consistent dataset that can sample across all existing products based on a standardized framework. Here, we present and describe the first coordinated multi-product ensemble of present-day global wave fields available to date. This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, includes general and extreme statistics of significant wave height (Hs), mean wave period (Tm) and mean wave direction (θm) computed across 1980–2014, at different frequency resolutions (monthly, seasonally, and annually). This coordinated global ensemble has been derived from fourteen state-of-the-science global wave products obtained from different atmospheric reanalysis forcing and downscaling methods. This data set has been processed, under a specific framework for consistency and quality, following standard Data Reference Syntax, Directory Structures and Metadata specifications. This new comprehensive dataset provides support to future broad-scale analysis of historical wave climatology and variability as well as coastal risk and vulnerability assessments across offshore and coastal engineering applications.
Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July–December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July–December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July–December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, although may have had even greater impacts, considering the underestimated resurgence magnitude from the model.
","language":"English","publisher":"eLife Sciences Publications, Ltd","doi":"10.7554/eLife.73584","usgsCitation":"Truelove, S., Smith, C.P., Qin, M., Mullany, L., Borchering, R.K., Lessler, J., Shea, K., Howerton, E., Contamin, L., Levander, J., Kerr, J., Hochheiser, H., Kinsey, M., Tallaksen, K., Wilson, S., Shin, L., Rainwater-Lovett, K., Lemaitre, J., Dent, J., Kaminsky, J., Lee, E.C., Perez-Saez, J., Hill, A., Karlen, D., Chinazzi, M., Davis, J., Mu, K., Xiong, X., Pastore y Piontti, A., Vespignani, A., Srivastava, A., Porebski, P., Venkatramanan, S., Adiga, A., Lewis, B., Klahn, B., Outten, J., Orr, M., Harrison, G., Hurt, B., Chen, J., Vullikanti, A., Marathe, M., Hoops, S., Bhattacharya, P., Machi, D., Chen, S., Paul, R., Janies, D., Thill, J., Galanti, M., Yamana, T., Pei, S., Shaman, J.L., Healy, J., Slayton, R.B., Biggerstaff, M., Johansson, M.A., Runge, M.C., and Viboud, C., 2022, Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the 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Decades of mine development of the J-M Reef have revealed that a distinct discontinuity in rock fabric marks the top of the rock unit that hosts economic-grade sulfide mineralization. Mine geologists refer to this discontinuity as the hanging wall contact. This contact is the top of the Reef Package and is always locatable—either by the change in rock fabric or by distinctive hanging wall textures of silicate minerals—even when the reef sulfide mineralization is absent. This rather subtle textural feature is used reliably by mine geologists to follow the Reef during exploration and mine development. Although some high tenor sulfides (>1000 ppm Pd in 100% sulfide) are found sporadically in the hanging wall cumulates, these accumulations are too small to be economically viable. We present quantitative rock fabric data for four Reef Package and hanging wall intersections collected by electron back-scattered diffraction (EBSD). Plagioclase fabrics in the hanging wall are characterized by low variance in grain sizes and a strong point maximum concentration of (010) and a perpendicular girdle distribution of [100] consistent with an axial B-type fabric. These fabrics are indicative of either compaction of the crystal mush or crystal settling of nucleated crystals, the bulk magma in a chamber. Conversely, the fabrics of the Reef Package show higher variance grain in size distributions and weak to undeveloped preferred orientation of plagioclase crystals that did not undergo significant alignment or textural equilibration of plagioclase grains. The absence of foliation in the Reef Package stands in contrast both to hanging wall fabrics and to other reported EBSD datasets of plagioclase crystals orientations from the Bushveld Complex, the Skaergaard Intrusion, and the Rum Intrusion. Furthermore, plagioclase crystal size distributions for the Reef Package show flatter slopes and convex profiles with fewer crystals at small size fractions indicating the dissolution of small crystals during partial melting and textural coarsening (i.e. Ostwald ripening) and crystal growth. Crystal growth was favored over the nucleation of new crystals during prolonged interaction with a hot infiltrating melt into the resident mush resulting in the coarse-grained textures of the Reef Package cumulates. The hanging wall contact represents a boundary between partially remelted crystal mush of the Reef Package, where sulfide mineralization formed and accumulated, and an overlying essentially barren cumulate pile. The hanging wall cumulates formed following the cessation of footwall erosion and the resumption of crystal accumulation by normal magma chamber processes.
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Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
The Yellowstone Volcano Observatory (YVO) is a consortium of nine Federal, State, and academic agencies that: (1) provides timely monitoring and hazards assessment of volcanic, hydrothermal, and earthquake activity in and around Yellowstone National Park, and (2) conducts research to develop new approaches to volcano monitoring and better understand volcanic activity in the Yellowstone region and elsewhere. The U.S. Geological Survey (USGS) arm of YVO is also responsible for monitoring and reporting on volcanic activity in the Intermountain West of the United States.
The previous YVO monitoring plan for the Yellowstone region spanned 2006–2015 and focused on strengthening the region-wide coverage, or backbone, of monitoring systems (Yellowstone Volcano Observatory, 2006). The goals of that plan have largely been achieved thanks to significant investments in instrumentation and infrastructure, especially by the National Science Foundation EarthScope Plate Boundary Observatory (now known as the Network Of The Americas, or NOTA) and the American Reinvestment and Recovery Act. This revision of the monitoring plan, covering 2022–2032, builds upon these improvements to monitoring systems in the Yellowstone region while also accounting for new insights into the dynamics of the area’s seismic, volcanic, and hydrothermal activity. These additional improvements are designed to fill gaps in the monitoring network and to better understand and track hazards associated with hydrothermal processes. These improvements include:
The 2022–2032 monitoring plan for the Yellowstone volcanic system also proposes to improve monitoring of hydrothermal areas to better understand these dynamic systems and their associated hazards. To date, only a single seismometer has been placed within one of Yellowstone National Park’s geyser basins because seismic noise associated with boiling water can hinder interpretation of overall seismic and magmatic activity, but this concern has been mitigated by improvements to backbone monitoring. Deployment of geophysical, geochemical, hydrological, and geological monitoring instruments in geyser basins will be accompanied by campaigns to measure gas and water chemistry and flux, as well as aerial and satellite surveys of gas and thermal emissions.
Close collaboration between YVO member institutions and other research agencies is needed to achieve these monitoring goals and to use the derived data to advance understanding of how Yellowstone Caldera and similar volcanic systems work. At the same time, attention must be paid to minimize the impact of monitoring efforts and infrastructure on the environment. YVO thus commits to serving as stewards of the natural, cultural, and historical resources in and around Yellowstone National Park while maximizing scientific gain for the betterment of society.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225032","collaboration":"Prepared in cooperation with Yellowstone National Park, University of Utah, UNAVCO, University of Wyoming, Montana Bureau of Mines and Geology, Idaho Geological Survey, Wyoming State Geological Survey, and Montana State University","usgsCitation":"Yellowstone Volcano Observatory, 2022, Volcano and earthquake monitoring plan for the Yellowstone Caldera system, 2022–2032: U.S. Geological Survey Scientific Investigations Report 2022–5032, 23 p., https://doi.org/10.3133/sir20225032.","productDescription":"v, 23 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-120517","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":402338,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5032/sir20225032.pdf","text":"Report","size":"23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5032"},{"id":402337,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5032/covrthb.jpg"},{"id":502390,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113201.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Caldera, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.04156494140625,\n 44.24716652494939\n ],\n [\n -110.20111083984375,\n 44.24716652494939\n ],\n [\n -110.20111083984375,\n 44.77111175531263\n ],\n [\n -111.04156494140625,\n 44.77111175531263\n ],\n [\n -111.04156494140625,\n 44.24716652494939\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Yellowstone Volcano Observatory
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
The young of some altricial bird species hatch asynchronously, which can lead to considerable size differences among siblings. Nestling traits such as body mass, moreover, can carry over and influence post-fledging survival. Despite the potential importance of nestling mass for reproductive outcomes, however, variation in nestling mass and relationships with brood size has been described and quantified rarely. We weighed 453 nestlings from 148 nests of 3 sympatric, sagebrush-associated songbird species in Wyoming, USA, to describe the range of intrabrood mass differences. Intrabrood differences in nestling mass were greatest for the largest species, the Sage Thrasher (Oreoscoptes montanus), for which the smallest nestling in a brood was on average 26.2% smaller than the largest. The smaller Vesper Sparrow (Pooecetes gramineus) and Brewer's Sparrow (Spizella breweri) exhibited similar intrabrood mass ratios, with the smallest nestling being 17.4% and 18.4% smaller on average than the largest for the 2 species, respectively. For each additional nestling within a brood, the smallest nestling was an additional 6.6–13.6% smaller than the largest nestling, depending on species. Understanding the extent of intrabrood variation in nestling traits has important implications for the productivity of species facing unpredictable environments.
","language":"English","publisher":"BioOne","doi":"10.1676/21-00047","usgsCitation":"Rhea, A.M., Carlisle, J., and Chalfoun, A.D., 2022, Intrabrood variation in nestling mass among three sagebrush-associated songbirds: The Wilson Journal of Ornithology, v. 134, no. 2, p. 345-351, https://doi.org/10.1676/21-00047.","productDescription":"7 p.","startPage":"345","endPage":"351","ipdsId":"IP-128963","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"134","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rhea, Ashleigh M.","contributorId":339524,"corporation":false,"usgs":false,"family":"Rhea","given":"Ashleigh","email":"","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":904555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Jason D.","contributorId":339525,"corporation":false,"usgs":false,"family":"Carlisle","given":"Jason D.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":904556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":904557,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232261,"text":"70232261 - 2022 - Rare window into an ancient struggle","interactions":[],"lastModifiedDate":"2022-06-20T17:06:47.751169","indexId":"70232261","displayToPublicDate":"2022-06-20T12:06:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2093,"text":"International Wolf","active":true,"publicationSubtype":{"id":10}},"title":"Rare window into an ancient struggle","docAbstract":"No abstract available.
","language":"English","publisher":"International Wolf Center","usgsCitation":"Petersohn, M.C., and Barber-Meyer, S., 2022, Rare window into an ancient struggle: International Wolf, v. 2022, no. Summer, p. 26-27.","productDescription":"2 p.","startPage":"26","endPage":"27","ipdsId":"IP-135095","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":402379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":402378,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://wolf.org/wolf-info/wolf-magazine/current-issue/"}],"volume":"2022","issue":"Summer","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Petersohn, Megan Carolyn 0000-0002-8955-9980","orcid":"https://orcid.org/0000-0002-8955-9980","contributorId":292501,"corporation":false,"usgs":true,"family":"Petersohn","given":"Megan","email":"","middleInitial":"Carolyn","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barber-Meyer, Shannon 0000-0002-3048-2616","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":217939,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844877,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232260,"text":"70232260 - 2022 - Evaluating the paleoenvironmental significance of sediment grain size in Bering Sea sediments during Marine Isotope Stage 11","interactions":[],"lastModifiedDate":"2023-11-20T16:59:28.105602","indexId":"70232260","displayToPublicDate":"2022-06-20T11:54:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the paleoenvironmental significance of sediment grain size in Bering Sea sediments during Marine Isotope Stage 11","docAbstract":"Grain size is an important textural property of sediments and is widely used in paleoenvironmental studies as a means to infer changes in the sedimentary environment. However, grain size parameters are not always easy to interpret without a full understanding of the factors that influence grain size. Here, we measure grain size in sediment cores from the Bering slope and the Umnak Plateau, and review the effectiveness of different grain size parameters as proxies for sediment transport, current strength, and primary productivity, during a past warm interval (Marine Isotope Stage 11, 424-374 ka). \n\nIn general, sediments in the Bering Sea are hemipelagic, making them ideal deposits for paleoenvironmental reconstructions, but there is strong evidence in the grain size distribution for contourite deposits between ~408-400 ka at the slope sites, suggesting a change in bottom current transport at this time. We show that the grain size of coarse (>150 µm) terrigenous sediment can be used effectively as a proxy for ice rafting, although it is not possible to distinguish between iceberg and sea ice rafting processes, based on grain size alone. We find that the mean grain size of bulk sediments can be used to infer changes in productivity on glacial-interglacial timescales, but the size and preservation of diatom valves also exert a control on mean grain size. Lastly, we show that the mean size of sortable silt (10-63 µm) is not a valid proxy for bottom current strength in the Bering Sea, because the input of ice-rafted silt confounds the sortable silt signal.","language":"English","publisher":"Micropaleontology Press","doi":"10.29041/strat.19.2.03","usgsCitation":"Thompson, N., and Caissie, B.E., 2022, Evaluating the paleoenvironmental significance of sediment grain size in Bering Sea sediments during Marine Isotope Stage 11: Stratigraphy, v. 19, no. 2, p. 119-139, https://doi.org/10.29041/strat.19.2.03.","productDescription":"21 p.","startPage":"119","endPage":"139","ipdsId":"IP-130205","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":402377,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Bering Sea, Bering Sea Green Belt, Bering Slope, Umnak Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.76171875,\n 55.1286490684888\n ],\n [\n -177.2314453125,\n 62.24746627771428\n ],\n [\n -182.548828125,\n 60.823494332539646\n ],\n [\n -171.03515625,\n 53.27835301753182\n ],\n [\n -165.76171875,\n 55.1286490684888\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Natalie 0000-0001-5924-6599","orcid":"https://orcid.org/0000-0001-5924-6599","contributorId":292499,"corporation":false,"usgs":false,"family":"Thompson","given":"Natalie","email":"","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":844874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caissie, Beth Elaine 0000-0001-9587-1842","orcid":"https://orcid.org/0000-0001-9587-1842","contributorId":292500,"corporation":false,"usgs":true,"family":"Caissie","given":"Beth","email":"","middleInitial":"Elaine","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":844875,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232259,"text":"70232259 - 2022 - Predictive models of phosphorus concentration and load in stormwater runoff from small urban residential watersheds in fall season","interactions":[],"lastModifiedDate":"2022-06-20T16:34:49.404382","indexId":"70232259","displayToPublicDate":"2022-06-20T11:04:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Predictive models of phosphorus concentration and load in stormwater runoff from small urban residential watersheds in fall season","docAbstract":"Urban street trees are a key part of public green infrastructure in many cities, however, leaf litter on streets is a critical biogenic source of phosphorus (P) in urban stormwater runoff during Fall. This study identified mass of street leaf litter (Mleaf) and antecedent dry days (ADD) as the top two explanatory parameters that have significant predictive power of event end-of-pipe P concentrations through multiple linear regression (MLR) analysis. Mleaf and volume of runoff (Vol) were the top two key explanatory parameters of event end-of-pipe P loads. Two-predictor MLR models were developed with these explanatory parameters using a 40-storm dataset derived from six small urban residential watersheds in Wisconsin, USA, and evaluated using storms specific to each study basin. The MLR model validation results indicated sensitivity to storm composition in the datasets. Our analysis shows selected parameters can be used by environmental managers to facilitate end-of-pipe P prediction in urban areas. This information can be used to reduce the amount of P in stormwater runoff by adjusting the timing and frequency of municipal leaf collection and street cleaning programs in urban areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2022.115171","usgsCitation":"Wang, Y., Thompson, A., and Selbig, W.R., 2022, Predictive models of phosphorus concentration and load in stormwater runoff from small urban residential watersheds in fall season: Journal of Environmental Management, v. 315, 115171, 8 p., https://doi.org/10.1016/j.jenvman.2022.115171.","productDescription":"115171, 8 p.","ipdsId":"IP-122605","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":447380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2022.115171","text":"Publisher Index Page"},{"id":402375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Fond du Lac, Madison, Oshkosh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.58389282226561,\n 42.97752543508356\n ],\n [\n -89.25018310546875,\n 42.97752543508356\n ],\n [\n -89.25018310546875,\n 43.206176810164784\n ],\n [\n -89.58389282226561,\n 43.206176810164784\n ],\n [\n -89.58389282226561,\n 42.97752543508356\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.62533569335938,\n 43.94042832696309\n ],\n [\n -88.48251342773438,\n 43.94042832696309\n ],\n [\n -88.48251342773438,\n 44.11125397357155\n ],\n [\n -88.62533569335938,\n 44.11125397357155\n ],\n [\n -88.62533569335938,\n 43.94042832696309\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.51066589355469,\n 43.72694838956604\n ],\n [\n -88.36578369140625,\n 43.72694838956604\n ],\n [\n -88.36578369140625,\n 43.823629034783124\n ],\n [\n -88.51066589355469,\n 43.823629034783124\n ],\n [\n -88.51066589355469,\n 43.72694838956604\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"315","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Yi 0000-0003-3638-7940","orcid":"https://orcid.org/0000-0003-3638-7940","contributorId":236843,"corporation":false,"usgs":false,"family":"Wang","given":"Yi","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":844871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Anita 0000-0002-6202-1742","orcid":"https://orcid.org/0000-0002-6202-1742","contributorId":236844,"corporation":false,"usgs":false,"family":"Thompson","given":"Anita","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":844872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844873,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232258,"text":"70232258 - 2022 - Demonstration of a novel quantitative microscopy technique for automated characterization of in situ particulate matter in coal miners with progressive massive fibrosis","interactions":[],"lastModifiedDate":"2022-06-28T13:56:28.826441","indexId":"70232258","displayToPublicDate":"2022-06-20T10:55:33","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Demonstration of a novel quantitative microscopy technique for automated characterization of in situ particulate matter in coal miners with progressive massive fibrosis","docAbstract":"Rationale: Increasing exposure to respirable crystalline silica (RCS) linked to changes in mining production processes has been implicated in the resurgence of severe lung disease in U.S. coal miners. Lung mineralogy can provide insight into particle pathogenesis. However, standard approaches to characterizing in situ particulate matter (PM) by pulmonary pathologists have poor inter-rater comparability, and consensus agreement is time consuming. Scanning electron microscopy/energy-dispersive spectroscopy (SEM/EDX) is technically complex and labor intensive. We developed a method for quantitative in situ PM characterization using conventional polarized light microscopy (PLM) and explored PM features in lung tissue of coal miners with progressive massive fibrosis (PMF). \nMethods: With institutional review board approval, PLM images were obtained from 30 miners with PMF, classified by pathologists consensus based on PM profusion; 10 from each profusion group (mild/moderate/severe) were selected. Automated PM counting and characterization (including dimensions and grayscale intensity of PM > 0.3 m diameter) was performed on image samples using PLM with modified cell-counting software (BZ-X800 light microscope, Keyence Corporation, Osaka, Japan) (Figure 1). Quantitative PM density loge(PM count)/mm3 tissue was calculated for each sample and compared to pathologist PM profusion groups. PMF lesion type using consensus pathologist classification (13 coal-type, 9 mixed-type, and 8 silicotic-type) was compared to automated PM birefringence level (% particles with mean grayscale intensity <65, range 0-255). RCS particles are expected to be weakly birefringent (lower intensity) relative to other common minerals (e.g., silicates) contained in coal mine dust. PM features were analyzed in R 4.0.3 using one-way ANOVA for between-group comparisons.\nResults: Measured PM log-density increased significantly with higher qualitative profusion group (mild=10.480.98/mm3, moderate=11.460.81/mm3, severe=12.520.86/mm3, p<0.0001). Prevalence of weakly birefringent particles was significantly higher among silicotic-type PMF samples (31.57.9%) compared to either coal-type (21.510.1%, p=0.022) or mixed-type lesions (21.510.5%, p=0.025). \nConclusion: This pilot study demonstrates the feasibility of a novel quantitative microscopy technique for counting and characterizing in situ lung PM in coal miners with PMF. Quantitative PM burden was comparable to pulmonary pathologists consensus profusion classification, but this method was substantially less time consuming and labor intensive and provided additional information about relevant PM features. The higher prevalence of weakly birefringent particles seen in silicotic-type PMF lesions may help inform mineralogic pathogenesis of RCS. Future efforts will expand the number of PMF cases analyzed, further validate our mineralogic findings using data from SEM/EDX and lung tissue digestate methods, and compare findings in historical versus contemporary coal miners with PMF.","largerWorkTitle":"American Thoracic Society 2022 proceedings","language":"English","publisher":"American Thoracic Society","doi":"10.1164/ajrccm-conference.2022.205.1_MeetingAbstracts.A2489","usgsCitation":"Hua, J.T., Zell-Baran, L.M., Go, L.H., Cool, C.D., Lowers, H.A., Almberg, K.S., Sarver, E.A., Majka, S.M., Pang, K.D., Cohen, R.A., and Rose, C.S., 2022, Demonstration of a novel quantitative microscopy technique for automated characterization of in situ particulate matter in coal miners with progressive massive fibrosis, in American Thoracic Society 2022 proceedings, 2 p., https://doi.org/10.1164/ajrccm-conference.2022.205.1_MeetingAbstracts.A2489.","productDescription":"2 p.","ipdsId":"IP-133920","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":402374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-05-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Hua, Jeremy T.","contributorId":292496,"corporation":false,"usgs":false,"family":"Hua","given":"Jeremy","email":"","middleInitial":"T.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":844860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zell-Baran, Lauren M.","contributorId":265756,"corporation":false,"usgs":false,"family":"Zell-Baran","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":844861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Go, L. H.","contributorId":190733,"corporation":false,"usgs":false,"family":"Go","given":"L.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":844862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cool, Carlyne D.","contributorId":265746,"corporation":false,"usgs":false,"family":"Cool","given":"Carlyne","email":"","middleInitial":"D.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":844863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":844864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Almberg, K. S.","contributorId":265745,"corporation":false,"usgs":false,"family":"Almberg","given":"K.","email":"","middleInitial":"S.","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":844865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sarver, Emily A.","contributorId":265758,"corporation":false,"usgs":false,"family":"Sarver","given":"Emily","email":"","middleInitial":"A.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":844866,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Majka, Susan M.","contributorId":292497,"corporation":false,"usgs":false,"family":"Majka","given":"Susan","email":"","middleInitial":"M.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":844867,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pang, Kathy D.","contributorId":292498,"corporation":false,"usgs":false,"family":"Pang","given":"Kathy","email":"","middleInitial":"D.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":844868,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cohen, R. A.","contributorId":290338,"corporation":false,"usgs":false,"family":"Cohen","given":"R.","email":"","middleInitial":"A.","affiliations":[{"id":18133,"text":"University of Illinois Chicago","active":true,"usgs":false}],"preferred":false,"id":844869,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rose, Cecil S.","contributorId":265751,"corporation":false,"usgs":false,"family":"Rose","given":"Cecil","email":"","middleInitial":"S.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":844870,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70262364,"text":"70262364 - 2022 - Special section overview: Effects of ecosystem change on North American percid populations.","interactions":[],"lastModifiedDate":"2025-01-23T16:53:41.316862","indexId":"70262364","displayToPublicDate":"2022-06-20T10:46:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Special section overview: Effects of ecosystem change on North American percid populations.","docAbstract":"Walleye Sander vitreus, Sauger S. canadensis, and Yellow Perch Perca flavescens (referred to as percids herein) are collectively among the most culturally and ecologically important fish species in North America. As ecosystems change in response to environmental drivers, such as climate change, nutrient loading, and invasive species, there is a need to understand how percid populations respond to these changes. To address this need, a symposium was held during the 81st Annual Midwest Fish and Wildlife Conference to bring fishery scientists and managers together to describe and discuss percid population responses to ecosystem change. Prevailing symposium themes included the challenge of identifying mechanisms responsible for population-level changes, developing strategies to adaptively manage for resilient fisheries, and consideration of scale, context, and methods when interpreting variable results. Given the uncertainty of how ecosystem changes affect percid populations, participants emphasized the importance of communicating uncertainties to stakeholders, implementing data-driven management strategies, setting realistic goals, and revising management actions in an adaptive framework. There was universal agreement on both the challenge and necessity of facilitating constructive engagement among stakeholders in cooperative decision making. Symposium participants identified knowledge gaps and discussed future efforts to build on our current understanding of percid populations, including continuation of long-term monitoring, improved standardization of evaluation metrics, implementing adaptive management experiments to identify causal relationships, development of more robust analytical methods, use of historical data sources, and refining techniques to realistically convey management options to stakeholders.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10791","usgsCitation":"Boehm, H., Isermann, D.A., Ermer, M., Eslinger, L., Hansen, G., and Logsdon, D., 2022, Special section overview: Effects of ecosystem change on North American percid populations.: North American Journal of Fisheries Management, v. 42, no. 3, p. 477-483, https://doi.org/10.1002/nafm.10791.","productDescription":"7 p.","startPage":"477","endPage":"483","ipdsId":"IP-138666","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Boehm, Hadley I. A.","contributorId":349025,"corporation":false,"usgs":false,"family":"Boehm","given":"Hadley I. A.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":923938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ermer, Mark J.","contributorId":349026,"corporation":false,"usgs":false,"family":"Ermer","given":"Mark J.","affiliations":[{"id":81859,"text":"South Dakota Department of Game","active":true,"usgs":false}],"preferred":false,"id":923940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eslinger, Lawrence D.","contributorId":349027,"corporation":false,"usgs":false,"family":"Eslinger","given":"Lawrence D.","affiliations":[{"id":81673,"text":"Wisconsin Department of Natural Resources, Bureau of Fisheries Management","active":true,"usgs":false}],"preferred":false,"id":923941,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Gretchen J. A.","contributorId":349029,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen J. A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":923942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Logsdon, Dale E.","contributorId":349031,"corporation":false,"usgs":false,"family":"Logsdon","given":"Dale E.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923943,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232353,"text":"70232353 - 2022 - The Prairie Pothole Region: A duck factory, and a bee factory too","interactions":[],"lastModifiedDate":"2022-06-30T13:23:35.021179","indexId":"70232353","displayToPublicDate":"2022-06-20T08:17:07","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":10945,"text":"Prairie Pothole Joint Venture News","active":true,"publicationSubtype":{"id":30}},"title":"The Prairie Pothole Region: A duck factory, and a bee factory too","docAbstract":"No abstract available.
","language":"English","publisher":"Prairie Pothole Joint Venture","usgsCitation":"Simanonok, S.C., and Otto, C., 2022, The Prairie Pothole Region: A duck factory, and a bee factory too: Prairie Pothole Joint Venture News, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-142016","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":402737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":402658,"type":{"id":15,"text":"Index Page"},"url":"https://ppjv.org/the-prairie-pothole-region-a-duck-factory-and-a-bee-factory-too/"}],"country":"Canada, United States","otherGeospatial":"Prairie Potholes Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.08203125,\n 49.1242192485914\n ],\n [\n -113.115234375,\n 47.754097979680026\n ],\n [\n -111.4892578125,\n 47.724544549099676\n ],\n [\n -109.248046875,\n 47.57652571374621\n ],\n [\n -106.34765625,\n 48.019324184801185\n ],\n [\n -102.9638671875,\n 48.16608541901253\n ],\n [\n -101.0302734375,\n 47.57652571374621\n ],\n [\n -100.634765625,\n 46.58906908309182\n ],\n [\n -100.32714843749999,\n 44.62175409623324\n ],\n [\n -99.052734375,\n 43.100982876188546\n ],\n [\n -96.591796875,\n 42.84375132629021\n ],\n [\n -95.6689453125,\n 42.32606244456202\n ],\n [\n -93.9990234375,\n 40.81380923056958\n ],\n [\n -91.97753906249999,\n 41.07935114946899\n ],\n [\n -91.3623046875,\n 42.52069952914966\n ],\n [\n -95.8447265625,\n 48.83579746243093\n ],\n [\n -96.85546875,\n 49.97948776108648\n ],\n [\n -99.1845703125,\n 50.54136296522161\n ],\n [\n -103.3154296875,\n 51.536085601784755\n ],\n [\n -106.9189453125,\n 51.699799849741936\n ],\n [\n -109.951171875,\n 52.82932091031373\n ],\n [\n -112.1484375,\n 52.9883372533954\n ],\n [\n -114.2138671875,\n 53.30462107510271\n ],\n [\n -114.9169921875,\n 52.696361078274485\n ],\n [\n -114.08203125,\n 49.1242192485914\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Simanonok, Stacy C. 0000-0002-0287-3871","orcid":"https://orcid.org/0000-0002-0287-3871","contributorId":229607,"corporation":false,"usgs":true,"family":"Simanonok","given":"Stacy","email":"","middleInitial":"C.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":845324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":845325,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232552,"text":"70232552 - 2022 - Controlling skewness in MOVE3 peak-flow record extensions","interactions":[],"lastModifiedDate":"2022-07-07T11:49:15.249922","indexId":"70232552","displayToPublicDate":"2022-06-20T06:47:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Controlling skewness in MOVE3 peak-flow record extensions","docAbstract":"Streamgage record extension methods such as the maintenance of variance Type 3 (MOVE3) method improve flood frequency estimates at a target streamgage by incorporating information from a nearby, hydrologically similar index streamgage. Bulletin 17C recommends using a variation of the MOVE3 method to estimate values at the target streamgage for only a subset of the available data at the index streamgage to account for uncertainty in values estimated using MOVE3. Bulletin 17C recommends the most recent index streamgage data be used for the subset unless these data misrepresent the skewness of the extended record. However, no method is provided to select the subset if the most recent data are inappropriate. The objective of this study is to develop such a method to select the subset of peaks by extending Bulletin 17C’s MOVE3 methodology to control the skewness of the extended streamgage record. The new method allows the extended record skewness to be informed by all available peak-flow data at the index streamgage while accurately computing the variance and resulting confidence intervals for flood frequency estimates. An example is presented comparing three different variations of MOVE3 record extension, which produce extended streamgage records with the same mean and variance, but different values of skewness. In the example, the difference in skewness between the three methods causes the results of flood frequency analysis for the 1% annual exceedance probability flood to differ by about 15%, illustrating the importance of considering skewness when using MOVE3 record extension.
Radium (Ra) is a geogenic contaminant that occurs at high levels in the Midwestern Cambrian-Ordovician aquifer system (MCOAS), a regionally important sandstone and carbonate drinking water aquifer. Water utilities using the MCOAS often must adopt treatment methods or use alternative water sources to maintain high-quality drinking water. Here, we show that Ra in water obtained from a municipal well in Wisconsin remains consistent despite variation in pumping conditions. However, widely used analytical methods (e.g., scintillation counting) for measuring Ra are less precise for quantifying Ra variability given the site conditions. Although not currently used for EPA compliance, mass spectrometry improves the precision of Ra measurements by an order of magnitude over the currently used counting method (e.g., 95 ± 3 mBq/L vs. 110 ± 30 mBq/L) at the concentrations observed in this study. The use of more precise analytical methods will increase understanding of trends in Ra levels important for operating public water systems.
The transition of sagebrush-dominated (Artemisia spp.) shrublands to pinyon (Pinus spp.) and juniper (Juniperus spp.) woodlands markedly alters resource-conserving vegetation structure typical of these landscapes. Land managers and scientists in the western United States need knowledge and predictive tools for assessment and effective targeting of tree-removal treatments to conserve or restore sagebrush vegetation and associated hydrologic function. This study developed modeling approaches to quantify the hydrologic vulnerability and erosion potential of sagebrush rangelands in the later stages of woodland encroachment and in response to commonly applied tree-removal treatments. Using experimental data from multiple sites in the Great Basin Region, USA, and process-based knowledge from decade-long vegetation and rainfall simulation studies at those sites, we (1) assessed the capability of the Rangeland Hydrology and Erosion Model (RHEM) to accurately predict patch-scale (12 m2) measured runoff and erosion from tree canopy and intercanopy hydrologic functional units in untreated and burned woodlands 9 years postfire, and (2) developed and evaluated multiple RHEM approaches/frameworks to model aggregated effects of tree canopy and intercanopy areas on patch- and hillslope-scale (50 m length) runoff and erosion processes in untreated and treated (burned, cut, and masticated) woodlands. The RHEM accurately predicted measured runoff and sediment yield from patch-scale rainfall simulations as partitioned on untreated and treated tree canopy and intercanopy areas and effectively parameterized the dominant controls on runoff and erosion process in woodlands. With few exceptions, evaluated hillslope-scale RHEM frameworks similarly predicted reduced hydrologic vulnerability and erosion potential for conditions 9 years following tree removal by burning, cutting, and mastication treatments. Regressions of RHEM-predicted hillslope runoff, sediment, and hydraulic/erosion parameters with bare ground and ground cover attributes indicate all RHEM frameworks effectively represented the dominant controls on hydrologic and erosion processes for rangelands and woodlands. The results provide RHEM frameworks and recommendations for assessing hydrologic vulnerability and erosion potential on woodland-encroached sites and predicting the effectiveness of tree removal to reestablish a water and soil resource-conserving vegetation structure on sagebrush rangelands. We anticipate our RHEM or similar modeling approaches may be applicable to analogous water-limited landscapes elsewhere subject to woody plant encroachment.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4145","usgsCitation":"Williams, C.J., Pierson, F.B., Al-Hamdan, O.Z., Nouwakpo, S.K., Johnson, J.C., Polyakov, V.O., Kormos, P.R., Shaff, S., and Spaeth, K.E., 2022, Assessing runoff and erosion on woodland-encroached sagebrush steppe using the Rangeland Hydrology and Erosion Model: Ecosphere, v. 13, no. 6, e4145, 32 p., https://doi.org/10.1002/ecs2.4145.","productDescription":"e4145, 32 p.","ipdsId":"IP-137960","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":447392,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecs2.4145","text":"External Repository"},{"id":402401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.14427185058592,\n 39.44679856427205\n ],\n [\n -115.10032653808594,\n 39.44679856427205\n ],\n [\n -115.10032653808594,\n 39.47807557129829\n ],\n [\n -115.14427185058592,\n 39.47807557129829\n ],\n [\n -115.14427185058592,\n 39.44679856427205\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.47871398925781,\n 40.20824570152502\n ],\n [\n -112.46429443359375,\n 40.20824570152502\n ],\n [\n -112.46429443359375,\n 40.2203056748532\n ],\n [\n -112.47871398925781,\n 40.2203056748532\n ],\n [\n -112.47871398925781,\n 40.20824570152502\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, C. 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Kossi","contributorId":292514,"corporation":false,"usgs":false,"family":"Nouwakpo","given":"S.","email":"","middleInitial":"Kossi","affiliations":[{"id":62926,"text":"Agricultural Research Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":844922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Justin C.","contributorId":261635,"corporation":false,"usgs":false,"family":"Johnson","given":"Justin","email":"","middleInitial":"C.","affiliations":[{"id":47959,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":844923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Polyakov, Viktor O.","contributorId":292516,"corporation":false,"usgs":false,"family":"Polyakov","given":"Viktor","email":"","middleInitial":"O.","affiliations":[{"id":62926,"text":"Agricultural Research Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":844924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kormos, Patrick R.","contributorId":292517,"corporation":false,"usgs":false,"family":"Kormos","given":"Patrick","email":"","middleInitial":"R.","affiliations":[{"id":62927,"text":"National Oceanic and Atmospheric Administration - National Weather Service, US Department of Commerce","active":true,"usgs":false}],"preferred":false,"id":844925,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shaff, Scott 0000-0001-8978-9260 sshaff@usgs.gov","orcid":"https://orcid.org/0000-0001-8978-9260","contributorId":5126,"corporation":false,"usgs":true,"family":"Shaff","given":"Scott","email":"sshaff@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844926,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spaeth, Kenneth E.","contributorId":9387,"corporation":false,"usgs":true,"family":"Spaeth","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":844927,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70232264,"text":"70232264 - 2022 - What is a biocrust? A refined, contemporary definition for a broadening research community","interactions":[],"lastModifiedDate":"2022-09-01T14:40:41.902044","indexId":"70232264","displayToPublicDate":"2022-06-18T11:20:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1023,"text":"Biological Reviews","active":true,"publicationSubtype":{"id":10}},"title":"What is a biocrust? A refined, contemporary definition for a broadening research community","docAbstract":"Studies of biological soil crusts (biocrusts) have proliferated over the last few decades. The biocrust literature has broadened, with more studies assessing and describing the function of a variety of biocrust communities in a broad range of biomes and habitats and across a large spectrum of disciplines, and also by the incorporation of biocrusts into global perspectives and biogeochemical models. As the number of biocrust researchers increases, along with the scope of soil communities defined as ‘biocrust’, it is worth asking whether we all share a clear, universal, and fully articulated definition of what constitutes a biocrust. In this review, we synthesize the literature with the views of new and experienced biocrust researchers, to provide a refined and fully elaborated definition of biocrusts. In doing so, we illustrate the ecological relevance and ecosystem services provided by them. We demonstrate that biocrusts are defined by four distinct elements: physical structure, functional characteristics, habitat, and taxonomic composition. We describe outgroups, which have some, but not all, of the characteristics necessary to be fully consistent with our definition and thus would not be considered biocrusts. We also summarize the wide variety of different types of communities that fall under our definition of biocrusts, in the process of highlighting their global distribution. Finally, we suggest the universal use of the Belnap, Büdel & Lange definition, with minor modifications: Biological soil crusts (biocrusts) result from an intimate association between soil particles and differing proportions of photoautotrophic (e.g. cyanobacteria, algae, lichens, bryophytes) and heterotrophic (e.g. bacteria, fungi, archaea) organisms, which live within, or immediately on top of, the uppermost millimetres of soil. Soil particles are aggregated through the presence and activity of these often extremotolerant biota that desiccate regularly, and the resultant living crust covers the surface of the ground as a coherent layer. With this detailed definition of biocrusts, illustrating their ecological functions and widespread distribution, we hope to stimulate interest in biocrust research and inform various stakeholders (e.g. land managers, land users) on their overall importance to ecosystem and Earth system functioning.
","language":"English","publisher":"Wiley","doi":"10.1111/brv.12862","usgsCitation":"Weber, B., Belnap, J., Budel, B., Antoninka, A.J., Barger, N.N., Chaudhary, V., Darrouzet-Nardi, A., Eldridge, D.J., Faist, A.M., Ferrenberg, S., Havrilla, C., Huber-Sannwald, E., Issa, O.M., Maestre, F.T., Reed, S., Rodriguez-Caballero, E., Tucker, C.L., Young, K., Zhang, Y., Zhao, Y., Zhou, X., and Bowker, M.A., 2022, What is a biocrust? A refined, contemporary definition for a broadening research community: Biological Reviews, v. 97, no. 5, p. 1768-1785, https://doi.org/10.1111/brv.12862.","productDescription":"18 p.","startPage":"1768","endPage":"1785","ipdsId":"IP-139133","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":447393,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/brv.12862","text":"External Repository"},{"id":402399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Weber, Bettina","contributorId":196800,"corporation":false,"usgs":false,"family":"Weber","given":"Bettina","email":"","affiliations":[],"preferred":false,"id":844885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 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0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844899,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Rodriguez-Caballero, Emilio","contributorId":292504,"corporation":false,"usgs":false,"family":"Rodriguez-Caballero","given":"Emilio","affiliations":[{"id":62918,"text":"Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany; Departamento de Agronomía and Centro de Investigación de Colecciones Científicas de la Universidad de Almería, Almería, Spain","active":true,"usgs":false}],"preferred":false,"id":844900,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Tucker, Colin 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China","active":true,"usgs":false}],"preferred":false,"id":844903,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Zhao, Yunge","contributorId":224390,"corporation":false,"usgs":false,"family":"Zhao","given":"Yunge","email":"","affiliations":[],"preferred":false,"id":844904,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Zhou, Xiaobing","contributorId":181757,"corporation":false,"usgs":false,"family":"Zhou","given":"Xiaobing","email":"","affiliations":[],"preferred":false,"id":844905,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Bowker, Matthew A.","contributorId":196428,"corporation":false,"usgs":false,"family":"Bowker","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":844906,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70266740,"text":"70266740 - 2022 - Cryptic population decrease due to invasive species predation in a long-lived seabird supports need for eradication","interactions":[],"lastModifiedDate":"2025-05-12T14:55:29.381762","indexId":"70266740","displayToPublicDate":"2022-06-18T09:44:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic population decrease due to invasive species predation in a long-lived seabird supports need for eradication","docAbstract":"The presence of vitrinite in sedimentary rocks of post-Silurian age allows its reflectance to be used to estimate the thermal maturation of organic matter in petroleum systems. Increasing reflectance of vitrinite, which is primarily driven by aromaticity, depends primarily on the time and temperature attributes of its evolutionary pathway. This study evaluated carbonaceous shales proximal to coal measures and coal samples via isothermal hydrous pyrolysis (HP) to compare differences in the maturation pathways of vitrinite. Sample residues were analysed via vitrinite reflectance (VRo), geochemical screening tests (organic carbon and programmed temperature pyrolysis), and infrared spectroscopy. The study included samples from Indian and North American basins, to observe differences in vitrinite evolution with respect to enclosing mineral matrix, starting degree of aromaticity, organic matter types, stratigraphic age, and depositional environment. The organic content of HP residues shows an intuitive response to the thermal stress of HP, e.g., a general depletion of total organic carbon (TOC) content, pyrolyzate (S2), and hydrogen index with increasing HP temperature. Infrared proxies including C-factor and CH2/CH3 generally decrease with increasing thermal maturity indicating loss of O via CO2 generation and the thermal cracking of aliphatic organic matter. Tmax, production index (PI), and VRo show intuitive increasing values with respect to HP temperature. The least mature sample (0.48 ± 0.05% VRo) generally experienced the maximum change in these parameters during maturation, whereas the most mature sample (0.99 ± 0.06% VRo) generally showed the least change. This observation is consistent with higher kinetic barriers to reaction in more aromatic vitrinite which contains higher bond dissociation energies. Devolatilization of vitrinite during HP causes formation of gas evacuation vacuoles and contraction cracks in the vitrinite grains of both coal and carbonaceous shale. Similarities in vitrinite response to HP between coal and carbonaceous shale suggest that thermal evolution of the vitrinite maceral is principally controlled by inherent rate-limiting kinetic parameters related to its molecular structure. Whereas, the stratigraphic age, sedimentary environment, surrounding organic matter, lithology, and catalysis by mineral composition have less effect. To further improve our understanding of vitrinite aromatization and kinetic parameters, future studies of vitrinite reflectance thermal evolution with temperature should include coal and carbonaceous shale from the same stratigraphic section and extant woody tissue from modern vascular plants.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2022.104044","usgsCitation":"Mishra, D.K., Hackley, P.C., Jubb, A., Sanders, M.M., Agrawal, S., and Varma, A.K., 2022, Maturation study of vitrinite in carbonaceous shales and coals: Insights from hydrous pyrolysis: International Journal of Coal Geology, v. 259, 104044, 13 p., https://doi.org/10.1016/j.coal.2022.104044.","productDescription":"104044, 13 p.","ipdsId":"IP-138029","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":408530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"259","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mishra, Divya K.","contributorId":290218,"corporation":false,"usgs":false,"family":"Mishra","given":"Divya","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":855038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":855039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":855040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanders, Margaret M. 0000-0003-3505-874X","orcid":"https://orcid.org/0000-0003-3505-874X","contributorId":248709,"corporation":false,"usgs":true,"family":"Sanders","given":"Margaret","email":"","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":855041,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agrawal, Shailesh","contributorId":261453,"corporation":false,"usgs":false,"family":"Agrawal","given":"Shailesh","email":"","affiliations":[],"preferred":false,"id":855042,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Varma, Atul K.","contributorId":290219,"corporation":false,"usgs":false,"family":"Varma","given":"Atul","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":855043,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70254718,"text":"70254718 - 2022 - Reproductive indices and observations of mass ovarian follicular atresia in hatchery-origin pallid sturgeon","interactions":[],"lastModifiedDate":"2024-06-10T16:05:35.788952","indexId":"70254718","displayToPublicDate":"2022-06-17T10:59:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"title":"Reproductive indices and observations of mass ovarian follicular atresia in hatchery-origin pallid sturgeon","docAbstract":"The Pallid Sturgeon (Scaphirhynchus albus) Conservation Propagation and Stocking Program began stocking in the Missouri River above Fort Peck Reservoir in 1998 with 1997-year-class pallid sturgeon. Within the 1997-year class, all hatchery-origin pallid sturgeon females that reached reproductive maturation by 2016 underwent mass ovarian follicular atresia. Using combined historical and contemporary data, we described the spawning periodicity for female and male pallid sturgeon, characterized age- and size-at-first spawning, and evaluated what proportion of females experience mass ovarian follicular atresia during the first and subsequent reproductive cycles. Pallid sturgeon reached their first reproductive cycle at older ages and larger sizes than described for other populations. Females were functionally and physiologically capable of spawning at 21 years and males at 15 years. Immature pallid sturgeon as old as 20 years were documented. We found that more female pallid sturgeon underwent mass ovarian follicular atresia during the presumed-first reproductive cycle or known-first reproductive cycle than females during subsequent reproductive cycles (62.5% compared to 33.3%) indicating that effects related to reproductive maturation may be occurring. Nonetheless, mass ovarian follicular atresia appears to also occur for reasons not related to reproductive maturation. Females had biennial reproductive cycles, and males had annual and biennial reproductive cycles. Population models should account for females undergoing mass ovarian follicular atresia in their first reproductive cycle and subsequent cycles thereby increasing the age at first-successful spawning and reducing the estimated size of the spawning stock.
","language":"English","publisher":"Wiley","doi":"10.1111/jai.14339","usgsCitation":"Cox, T., Guy, C.S., Holmquist, L., and Webb, M., 2022, Reproductive indices and observations of mass ovarian follicular atresia in hatchery-origin pallid sturgeon: Journal of Applied Ichthyology, v. 38, p. 391-402, https://doi.org/10.1111/jai.14339.","productDescription":"12 p.","startPage":"391","endPage":"402","ipdsId":"IP-137205","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":447396,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.14339","text":"Publisher Index Page"},{"id":429772,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Cox, Tanner L.","contributorId":337305,"corporation":false,"usgs":false,"family":"Cox","given":"Tanner L.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmquist, Luke M.","contributorId":337306,"corporation":false,"usgs":false,"family":"Holmquist","given":"Luke M.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":902342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Molly A. H.","contributorId":337308,"corporation":false,"usgs":false,"family":"Webb","given":"Molly A. H.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":902343,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232218,"text":"sir20215143 - 2022 - Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019","interactions":[],"lastModifiedDate":"2026-04-08T16:38:21.182332","indexId":"sir20215143","displayToPublicDate":"2022-06-17T10:44:25","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":"2021-5143","displayTitle":"Application of a Soil-Water-Balance Model to Estimate Annual Groundwater Recharge for Long Island, New York, 1900–2019","title":"Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019","docAbstract":"A soil-water-balance (SWB) model was developed for Long Island, New York, to estimate the potential amount of annual groundwater recharge to the Long Island aquifer system from 1900 to 2019. The SWB model program is a computer code based on a modified Thornthwaite-Mather SWB approach and uses spatially and temporally distributed meteorological, land-cover, and soil properties as input to compute potential daily groundwater recharge. Simulated outputs indicate that island-wide potential groundwater recharge trends, as a percentage of precipitation, have increased approximately 3 percent during the 120-year period. The simulated results account for both climatic and land-cover changes that have occurred during the period. A change from undeveloped (forested land cover) to low- and medium-density residential land cover or land use increased potential groundwater recharge because of a decrease in evapotranspiration. During the 30-year period from 1900 to 1930, the simulated potential average groundwater recharge rate on Long Island was estimated to be 18.50 inches per year (in/yr), or a total of 1,243 million gallons per day, during the 30-year period from 1985 to 2015, the simulated potential average groundwater recharge rate estimate increased to 20.73 in/yr (a total of around 1,393 million gallons per day).
During the 1900–2019 simulation period, the potential average annual groundwater recharge rate was about 19.24 in/yr. The data for that period included values for a 3-year meteorological drought from 1963 to 1965, where the mean precipitation was about 26.5 percent lower than the long-term average of 46.7 in/yr, and the potential groundwater recharge rate was about 12.3 in/yr. During a 3-year wet period from 1982 to 1984, where mean precipitation was about 19.6 percent higher than the long-term average, the estimated potential groundwater recharge rate was about 26.8 in/yr.
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U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349