This report is an instructional reference document that describes methods developed and used by the U.S. Geological Survey (USGS) New Jersey Water Science Center (NJWSC) to assure the quality and completeness of water-use data as provided by the New Jersey Department of Environmental Protection (NJDEP) Bureau of Water Allocation. These data are owned wholly by the State of New Jersey. The role of the USGS NJWSC is to assure the quality of these data by compiling, reviewing, and checking the datasets before uploading them into the New Jersey Water Transfer Data System (NJWaTr) database on an annual basis. The complete uploaded version of the NJWaTr database serves as the repository for New Jersey’s approved and published water-use data. The State of New Jersey maintains a public-facing version of the NJWaTr database (available online at https://www.nj.gov/dep/njgs/geodata/dgs10-3.htm) that contains monthly water-use data at the municipality and 14-digit Hydrologic Unit Code subwatershed level. The protected version of the NJWaTr database that contains monthly site-specific water-use data is available from the NJDEP upon request.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201085","collaboration":"Prepared in cooperation with New Jersey Department of Environmental Protection","usgsCitation":"Shourds, J.L., 2020, Quality assurance/quality control procedure for New Jersey’s water-use data for the New Jersey Water Transfer Data System (NJWaTr): U.S. Geological Survey Open-File Report 2020–1085, 26 p., https://doi.org/10.3133/ofr20201085.","productDescription":"viii, 26 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112307","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":380203,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1085/coverthb.jpg"},{"id":380204,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1085/ofr20201085.pdf","text":"Report","size":"2.09 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Jersey\",\"nation\":\"USA \"}}]}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Understanding recent historical and projected trends in precipitation and temperature in the Colorado River Basin, and estimating what the projected changes in these climate parameters may mean for groundwater resources in the region, is important for water managers and policymakers to sustainably manage water resources in the basin. Historical (1896–2019) precipitation and temperature data for the upper and lower Colorado River Basins were analyzed to better understand recent trends in climate data that may affect groundwater resources in the area. Historical data indicate multidecadal-scale cyclical patterns in precipitation in both the upper and lower basins. Although upper basin precipitation had no statistical trend over the recent historical period, the lower basin had a weak negative trend over this period. Multidecadal-scale cyclical patterns in temperature also are observed in historical climate data in both the upper and lower basins, at least until the early 1970s. Beginning at that time, both the upper and lower basins experienced strong, monotonic positive trends in temperature. Basic principles of hydrology indicate that periods of decreasing precipitation as well as increasing temperature would have a negative effect, that is, reduction in groundwater infiltration and hence, reduced recharge of aquifer systems.
Projected climate data from 97 Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble members across the full range of Representative Concentration Pathway (RCPs) from water years 1951 through 2099 were evaluated to understand what current global climate models are projecting about future conditions in the Colorado River Basin, and what this might mean for groundwater systems in the region. Precipitation in the upper basin is projected to increase throughout the rest of the century, rising to 6 percent above the 1951–2015 historical period by mid-century and to 9 percent above the historical period by the end of the century. Temperature in the upper basin also is projected to be above the recent historical median throughout the rest of the century, with steady warming in decadal average temperatures expected until the last quarter of this century. In contrast to projected precipitation in the upper basin, precipitation in the lower basin is projected to be the same as, or slightly less than, the historical period throughout most of the rest of this century. Like projected temperature in the upper basin, temperature in the lower basin also is projected to be above the recent historical median throughout the rest of the century. Comparing median projections for all future decades with median results from all historical decades, future precipitation is expected to be greater than that of the past in the upper basin, though no significant difference is projected for precipitation in the lower basin. Significant increases (p-value<0.05) are expected in temperature in both the upper and lower basins.
To estimate the effects of projected precipitation and temperature on groundwater systems in the region, results from the 97 member CMIP5 climate projection ensemble were used as input in a Soil-Water Balance (SWB) groundwater infiltration model for the Colorado River Basin. SWB simulation results indicate that the upper Colorado River Basin is expected to experience decades of above-historical-average groundwater infiltration through the end of the century. For the lower Colorado River Basin, simulated groundwater infiltration is projected to be consistently less than the recent (1951–2015) historical period for most of the remaining century. A comparison of the distribution of all median simulated groundwater infiltration results between recent historical and future periods indicates projected groundwater infiltration in the upper basin is significantly (p-value<0.05) greater over the combined 2020–2099 future period than the recent (1951–2015) historical period. Moreover, in 41 of 71 (58 percent) possible future decades in this century, groundwater infiltration is projected to be greater than the 75th percentile of historical simulated groundwater infiltration. Projected groundwater infiltration in the lower Colorado River Basin across all future decades is significantly less than in the historical period. Of the 71 future decades in the century, projected groundwater infiltration in the lower basin is expected to be less than the 25th percentile of historical infiltration in 55 (77 percent) of the 10-year periods. Important differences in projected precipitation between the upper (increasing precipitation) and lower (decreasing precipitation) basins largely drive the different responses of simulated groundwater infiltration in the upper (increasing infiltration) and lower (decreasing infiltration) basins. It will be useful to revisit projections in groundwater infiltration in the Colorado River Basin when more up-to-date projections of precipitation become available from the next Coupled Model Intercomparison Project phases or by using climate input developments through Regional Climate Modeling efforts and stochastic weather generators.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205107","collaboration":"Prepared in cooperation with Bureau of Reclamation","usgsCitation":"Tillman, F.D., Gangopadhyay, S., and Pruitt, T., 2020, Trends in recent historical and projected climate data for the Colorado River Basin and potential effects on groundwater availability: U.S. Geological Survey Scientific Investigations Report 2020–5107, 24 p., https://doi.org/10.3133/sir20205107.","productDescription":"Report: vii, 24 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-117191","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":380358,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5107/coverthb.jpg"},{"id":380361,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7ST7MX7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Soil-water balance groundwater recharge model results for the Upper Colorado River Basin (ver. 2.0, April 2017)"},{"id":380359,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5107/sir20205107.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5107"},{"id":380360,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VLU0O6","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Soil-water balance groundwater infiltration model results for the Lower Colorado River Basin"}],"country":"Mexico, United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5,\n 30.088107753367257\n ],\n [\n -108.984375,\n 30.221101852485987\n ],\n [\n -108.21533203125,\n 31.39115752282472\n ],\n [\n -107.16064453125,\n 35.08395557927643\n ],\n [\n -105.35888671875,\n 36.12012758978146\n ],\n [\n -104.6337890625,\n 36.40359962073253\n ],\n [\n -104.96337890625,\n 37.735969208590504\n ],\n [\n -105.3369140625,\n 38.58252615935333\n ],\n [\n -104.83154296875,\n 39.027718840211605\n ],\n [\n -104.87548828125,\n 41.19518982948959\n ],\n [\n -105.05126953124999,\n 41.934976500546604\n ],\n [\n -106.3916015625,\n 43.16512263158296\n ],\n [\n -110.91796875,\n 43.100982876188546\n ],\n [\n -111.09374999999999,\n 40.64730356252251\n ],\n [\n -111.533203125,\n 39.07890809706475\n ],\n [\n -113.04931640625,\n 37.405073750176925\n ],\n [\n -114.14794921875,\n 37.10776507118514\n ],\n [\n -114.54345703125,\n 37.54457732085582\n ],\n [\n -115.46630859375,\n 38.839707613545144\n ],\n [\n -116.806640625,\n 38.805470223177466\n ],\n [\n -116.19140625,\n 37.3002752813443\n ],\n [\n -115.3564453125,\n 36.421282443649496\n ],\n [\n -116.1474609375,\n 35.55010533588552\n ],\n [\n -115.4443359375,\n 32.491230287947594\n ],\n [\n -114.93896484374999,\n 31.3348710339506\n ],\n [\n -114.2578125,\n 31.57853542647338\n ],\n [\n -113.291015625,\n 31.316101383495624\n ],\n [\n -113.04931640625,\n 30.732392734006083\n ],\n [\n -112.7197265625,\n 30.012030680358613\n ],\n [\n -112.47802734375,\n 30.012030680358613\n ],\n [\n -112.5,\n 30.088107753367257\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
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520 N. Park Avenue
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This report summarizes the primary characteristics of alkalic-type epithermal gold (Au) deposits and provides an updated descriptive model. These deposits, primarily of Mesozoic to Neogene age, are among the largest epithermal gold deposits in the world. Considered a subset of low-sulfidation epithermal deposits, they are spatially and genetically linked to small stocks or clusters of intrusions containing high alkali-element contents. Deposits occur as disseminations, breccia-fillings, and veins and may be spatially and genetically related to skarns and low-grade porphyry copper (Cu) or molybdenum (Mo) systems. Gold commonly occurs as native gold, precious metal tellurides, and as sub-micron gold in arsenian pyrite. Quartz, carbonate, fluorite, adularia, and vanadian muscovite/roscoelite are the most common gangue minerals. Alkalic-type gold deposits form in a variety of geological settings including continent-arc collision zones and back-arc or post-subduction rifts that are invariably characterized by a transition from convergent to extensional or transpressive tectonics.
The geochemical compositions of alkaline igneous rocks spatially linked with these deposits span the alkaline-subalkaline transition. Their alkali enrichment may be masked by potassic alteration, but the unaltered or least altered rocks (1) have chondrite normalized patterns that are commonly light rare earth element (LREE) enriched, (2) are heavy rare earth element (HREE) depleted, and (3) have high large ion lithophile contents and variable enrichment of high-field strength elements. Radiogenic isotopes suggest a mantle derivation for the alkalic magmas but allow crustal contamination.
Oxygen and hydrogen isotope compositions show that the fluids responsible for deposit formation are dominantly magmatic, although meteoric or other external fluids (seawater, evolved groundwater) also contributed to the ore-forming fluids responsible for these deposits. Carbon and sulfur isotope compositions in vein-hosted carbonates and sulfide gangue minerals, respectively, coincide with magmatic values, although a sedimentary source of carbon and sulfur is evident in several deposits.
Deep-seated structures are critical for the upwelling of hydrous alkalic magmas and for focusing magmatic-hydrothermal fluids to the site of precious metal deposition. The source of gold, silver (Ag), tellurium (Te), vanadium (V), and fluorine (F) was probably the alkalic igneous rocks themselves, and the coexistence of native gold, gold tellurides, and roscoelite in several deposits is primarily a function of similar physicochemical conditions during deposition (for example, overlapping pH and oxygen fugacity (fO2).
Potential environmental impacts related to the mining and processing of alkalic-type epithermal gold deposits include acid mine drainage with high levels of metals, especially zinc (Zn), copper, lead (Pb), and arsenic. However, because alkalic-type gold deposits typically contain carbonates, which contribute calcium and magnesium ions that increase water hardness, aquatic life may be afforded some protection. Impacts vary widely as a function of host rocks, climate, topography, and mining methods.
Geologic mapping to (1) highlight the distribution of potassic alteration; (2) define fault density and orientation of structures; (3) determine the distribution of alkaline rocks and hydrothermal breccias; and (4) identify uniquely colored gangue minerals, such as fluorite and roscoelite, will be critical to exploration and future discoveries. Geophysical techniques that identify potassium (K) anomalies (for example, radiometric and spectroscopic surveys), as well as magnetic, resistivity, aeromagnetic, and gravity surveys, may help locate zones of high-permeability that control advecting hydrothermal fluids. Geochemical surveys that include analyses for Au, Ag, barium, Te, K, F, V, Mo, and mercury, which are key elements in these deposits, should be undertaken along with the measurement of other pathfinder elements such as arsenic, bismuth, Cu, iron, nickel, Pb, antimony, selenium, and Zn.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070R","issn":"2328-0328","usgsCitation":"Kelley, K.D., Spry, P.G., McLemore, V.T., Fey, D.L., and Anderson, E.D., 2020, Alkalic-type epithermal gold deposit model: U.S. Geological Survey Scientific Investigations Report 2010–5070–R, 74 p., https://doi.org/ 10.3133/ sir20105070R.","productDescription":"x, 74 p.","onlineOnly":"Y","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":380198,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/r/sir20105070r.pdf","text":"Report","size":"11.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010–5070–R"},{"id":380197,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5070/r/coverthb.jpg"}],"contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS–973
Denver, CO 80225
The U.S. Geological Survey (USGS), a bureau within the U.S. Department of the Interior, has valued and used a scientific peer review and approval process since its creation in 1879. Bureau approval, formerly called Director’s approval, has been described in several USGS documents since 1900, and peer review has been codified in policy since 1959. Peer review of USGS manuscripts is intended to ensure the accuracy of data, the scientific validity of interpretations, and the consideration of alternative interpretations. This rigorous quality assurance process is considered deliberative because of the iterative exchange of ideas and opinions among the involved parties.
Peer review practices differed between USGS organizational units until implementation of USGS Fundamental Science Practices (FSP) in 2006, which formalized Bureau-wide science practices, including peer review and approval, for all Bureau scientific information products released to the public or other Federal agencies. FSP policies also address review and approval requirements pertaining to the release of USGS-funded data and software and endorse quality-control standards for USGS laboratories. Bureau approval signifies the scientific excellence of information products, validates and ensures that all necessary reviews have been conducted, and confirms that information products meet USGS science quality standards and have the full backing of the Bureau. The extent, scope, and history of the peer review and approval process within the USGS are documented herein, so future USGS scientists and the public understand how consistent approaches in developing, reviewing, and publishing USGS scientific information have been and continue to be essential in maintaining the reputation of the Bureau for reliable and impartial Earth science research and data collection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203050","usgsCitation":"Kirk, K.G., Reid, C.L., Cooper, S.C., 2020, History of U.S. Geological Survey scientific peer review and approval, 1879–2019: U.S. Geological Survey Fact Sheet 2020–3050, 4 p., https://doi.org/10.3133/fs20203050","productDescription":"4 p.","ipdsId":"IP-110012","costCenters":[{"id":5066,"text":"Office of the Director USGS","active":true,"usgs":true}],"links":[{"id":380355,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3050/fs20203050.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3050"},{"id":380354,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3050/coverthb.jpg"}],"contact":"Contacts, Office of Scientific Quality and Integrity
This study evaluated the spatial variability of trends in simulated snowpack properties across the Rio Grande headwaters of Colorado using the SnowModel snow evolution modeling system. SnowModel simulations were performed using a grid resolution of 100 m and 3-hourly time step over a 34-yr period (1984–2017). Atmospheric forcing was provided by phase 2 of the North American Land Data Assimilation System, and the simulations accounted for temporal changes in forest canopy from bark beetle and wildfire disturbances. Annual summary values of simulated snowpack properties [snow metrics; e.g., peak snow water equivalent (SWE), snowmelt rate and timing, and snow sublimation] were used to compute trends across the domain. Trends in simulated snow metrics varied depending on elevation, aspect, and land cover. Statistically significant trends did not occur evenly within the basin, and some areas were more sensitive than others. In addition, there were distinct trend differences between the different snow metrics. Upward trends in mean winter air temperature were 0.3°C decade−1, and downward trends in winter precipitation were −52 mm decade−1. Middle elevation zones, coincident with the greatest volumetric snow water storage, exhibited the greatest sensitivity to changes in peak SWE and snowmelt rate. Across the Rio Grande headwaters, snowmelt rates decreased by 20% decade−1, peak SWE decreased by 14% decade−1, and total snowmelt quantity decreased by 13% decade−1. These snow trends are in general agreement with widespread snow declines that have been reported for this region. This study further quantifies these snow declines and provides trend information for additional snow variables across a greater spatial coverage at finer spatial resolution.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-20-0077.1","usgsCitation":"Sexstone, G., Penn, C.A., Liston, G., Gleason, K., Moeser, C.D., and Clow, D.W., 2020, Spatial variability in seasonal snowpack trends across the Rio Grande headwaters (1984 - 2017): Journal of Hydrometeorology, v. 21, no. 11, p. 2713-2733, https://doi.org/10.1175/JHM-D-20-0077.1.","productDescription":"21 p.","startPage":"2713","endPage":"2733","ipdsId":"IP-114071","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":454846,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-20-0077.1","text":"Publisher Index Page"},{"id":436725,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q8PYX1","text":"USGS data release","linkHelpText":"SnowModel simulations and supporting observations for the Rio Grande Headwaters, southwestern Colorado, United States, 1984 - 2017"},{"id":380501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rio Grande headwaters","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.65777587890625,\n 37.267495764381856\n ],\n [\n -105.83404541015625,\n 37.267495764381856\n ],\n [\n -105.83404541015625,\n 37.91603433975963\n ],\n [\n -107.65777587890625,\n 37.91603433975963\n ],\n [\n -107.65777587890625,\n 37.267495764381856\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sexstone, Graham A. 0000-0001-8913-0546","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":203850,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Penn, Colin A. 0000-0002-5195-2744","orcid":"https://orcid.org/0000-0002-5195-2744","contributorId":203851,"corporation":false,"usgs":true,"family":"Penn","given":"Colin","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liston, Glen","contributorId":244889,"corporation":false,"usgs":false,"family":"Liston","given":"Glen","affiliations":[{"id":36729,"text":"Cooperative Institute for Research in the Atmosphere","active":true,"usgs":false}],"preferred":false,"id":804853,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gleason, Kelly","contributorId":244890,"corporation":false,"usgs":false,"family":"Gleason","given":"Kelly","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":804854,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moeser, C. David 0000-0003-0154-9110","orcid":"https://orcid.org/0000-0003-0154-9110","contributorId":214563,"corporation":false,"usgs":true,"family":"Moeser","given":"C.","email":"","middleInitial":"David","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804855,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804856,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217232,"text":"70217232 - 2020 - A synthesis of patterns of environmental mercury inputs, exposure and effects in New York State","interactions":[],"lastModifiedDate":"2021-01-13T14:19:18.133975","indexId":"70217232","displayToPublicDate":"2020-11-10T08:16:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"A synthesis of patterns of environmental mercury inputs, exposure and effects in New York State","docAbstract":"Mercury (Hg) pollution is an environmental problem that adversely affects human and ecosystem health at local, regional, and global scales—including within New York State. More than two-thirds of the Hg currently released to the environment originates, either directly or indirectly, from human activities. Since the early 1800s, global atmospheric Hg concentrations have increased by three- to eight-fold over natural levels. In the U.S., atmospheric emissions and point-source releases to waterways increased following industrialization into the mid-1980s. Since then, water discharges have largely been curtailed. As a result, Hg emissions, atmospheric concentrations, and deposition over the past few decades have declined across the eastern U.S. Despite these decreases, Hg pollution persists. To inform policy efforts and to advance public understanding, the New York State Energy Research and Development Authority (NYSERDA) sponsored a scientific synthesis of information on Hg in New York State. This effort includes 23 papers focused on Hg in atmospheric deposition, water, fish, and wildlife published in Ecotoxicology. New York State experiences Hg contamination largely due to atmospheric deposition. Some landscapes are inherently sensitive to Hg inputs driven by the transport of inorganic Hg to zones of methylation, the conversion of inorganic Hg to methylmercury, and the bioaccumulation and biomagnification along food webs. Mercury concentrations exceed human and ecological risk thresholds in many areas of New York State, particularly the Adirondacks, Catskills, and parts of Long Island. Mercury concentrations in some biota have declined in the Eastern Great Lakes Lowlands and the Northeastern Highlands over the last four decades, concurrent with decreases in water releases and air emissions from regional and U.S. sources. However, widespread changes have not occurred in other ecoregions of New York State. While the timing and magnitude of the response of Hg levels in biota varies, policies expected to further diminish Hg emissions should continue to decrease Hg concentrations in food webs, yielding benefits to the fish, wildlife, and people of New York State. Anticipated improvements in the Hg status of aquatic ecosystems are likely to be greatest for inland surface waters and should be roughly proportional to declines in atmospheric Hg deposition. Efforts that advance recovery from Hg pollution in recent years have yielded significant progress, but Hg remains a pollutant of concern. Indeed, due to this extensive compilation of Hg observations in biota, it appears that the extent and intensity of the contamination on the New York landscape and waterscape is greater than previously recognized. Understanding the extent of Hg contamination and recovery following decreases in atmospheric Hg deposition will require further study, underscoring the need to continue existing monitoring efforts.
Human interference with the nitrogen cycle has doubled reactive nitrogen inputs to the global biosphere over the past century, leading to changes across multiple environmental issues that require urgent action. Nitrogen fertilizers and biological nitrogen fixation have allowed benefits of increased crop harvest and livestock production, while in some areas there is insufficient nitrogen to fertilize crops. Whether in excess or deficit, nitrogen losses from its inefficient use are causing a combination of freshwater and marine pollution, air pollution, alteration of climate balance, stratospheric ozone loss, biodiversity loss and reduction of soil quality. The resulting nitrogen pollution affects human health, well-being and livelihoods. Scientific efforts have begun to bring these issues together. However, there is still a high degree of fragmentation between research on the different benefits and threats of reactive nitrogen and between the respective policy frameworks, especially at the global scale. We argue that a more joined-up approach to managing the global nitrogen cycle is needed to develop the ‘gravity of common cause’ between nitrogen issues and to avoid policy trade-offs. We describe how a coherent system for science evidence provision is being developed to support policy development through the ‘International Nitrogen Management System’ (INMS). There is now a matching challenge to bring together the multiple policy agreements relevant for nitrogen as a foundation to address synergies/trade-offs and to set priorities. Based on review of existing frameworks, we outline the concept for an Interconvention nitrogen coordination mechanism. This could make a major contribution to multiple Sustainable Development Goals by stimulating the next generation of international nitrogen strategies: maximizing the benefits of efficient nitrogen use, while minimizing its many environmental threats.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Just enough nitrogen","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-58065-0_36","usgsCitation":"Sutton, M.A., Howard, C.M., Brownlie, W.J., Kanter, D., de Vries, W., Adhya, T., Jean Ometto, Baron, J., Winiwarter, W., Ju, X., Masso, C., Oenema, O., Raghuram, N., van Grinsven, H.J., Van der Beck, I., Cox, C.J., Hansen, S., Ramachandran, R., and Hicks, W.K., 2020, Global challenges for nitrogen science-policy interactions: Towards the International Nitrogen Management System (INMS) and improved coordination between multi-lateral environmental agreements, chap. of Just enough nitrogen, p. 517-560, https://doi.org/10.1007/978-3-030-58065-0_36.","productDescription":"43 p.","startPage":"517","endPage":"560","ipdsId":"IP-108605","costCenters":[{"id":291,"text":"Fort Collins Science 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M.","contributorId":245729,"corporation":false,"usgs":false,"family":"Howard","given":"Clare","email":"","middleInitial":"M.","affiliations":[{"id":49299,"text":"Cenver for Ecology and Hydrology, Edinburgh UK","active":true,"usgs":false}],"preferred":false,"id":806931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brownlie, Will J.","contributorId":245730,"corporation":false,"usgs":false,"family":"Brownlie","given":"Will","email":"","middleInitial":"J.","affiliations":[{"id":49299,"text":"Cenver for Ecology and Hydrology, Edinburgh UK","active":true,"usgs":false}],"preferred":false,"id":806932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kanter, David","contributorId":245731,"corporation":false,"usgs":false,"family":"Kanter","given":"David","email":"","affiliations":[{"id":40508,"text":"New York University","active":true,"usgs":false}],"preferred":false,"id":806933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Vries, 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Trihalomethanes (THMs) are one of the major classes of regulated disinfection byproducts, formed when a specific fraction of the organic carbon pool—referred to as THM precursors—reacts with chorine and/or bromine during treatment. Understanding the source, fate, timing and duration of the organic compounds that react to form THMs will allow identification of targeted and effective management actions. In this study we evaluated THM precursor contributions from multiple land use categories and hydrologic contexts, including novel data for urban land uses that demonstrate strong potential to release water with high THM formation potential (THMFP; median 618 μg L−1): greater than storm runoff integrated across a mixed-use (1/3 natural, 2/3 agricultural) watershed (median 460 μg L−1), irrigation runoff from agricultural systems (357 μg L−1), or runoff from a natural forested (median 123 μg L−1) and shrubland/grassland (median 259 μg L−1) watersheds. While individual storm events released high THM precursor concentrations over short periods, dry season agricultural irrigation as well as urban landscapes have the potential to release water high in THM precursors for several months. Experimental bioassays and sampling along 333 miles of the California Aqueduct confirmed bioavailability and photooxidation potential of less than 10% for THM precursors, suggesting that rivers with residence times of days to weeks may act as THM precursor conduits, shuttling THM precursors from hundreds of miles away to drinking water intakes with minimal degradation. This finding has considerable implications for water managers, who may therefore consider THM precursor management strategies that target even sources located far upstream.
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A recent decline in yellow perch Perca flavescens (Mitchill) abundance within the Lake Winnebago System, Wisconsin, USA, prompted an assessment of cormorant diets to evaluate potential effects of cormorant predation on the sportfish community. Diets were collected from 883 cormorants (417 from Lake Winnebago and 466 from Lake Butte des Morts) between 2015 and 2017. Cormorant diets on both waterbodies consisted mostly of freshwater drum Aplodinotus grunniens Rafinesque and gizzard shad Dorosoma cepedianum (Lesueur). Yellow perch and walleye Sander vitreus (Mitchill) observations were infrequent and represented < 5% of cormorant diets by weight each year. Under current conditions, cormorant predation likely has minimal impact on the Lake Winnebago sportfish community, but more research is needed to assess potential impacts on Lake Butte des Morts.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12466","usgsCitation":"Koenigs, R.P., Dembkowski, D., Lovell, C., Isermann, D.A., and Nickel, A., 2020, Diets of double-crested cormorants in the Winnebago System, Wisconsin: Fisheries Management and Ecology, v. 28, no. 2, p. 183-193, https://doi.org/10.1111/fme.12466.","productDescription":"11 p.","startPage":"183","endPage":"193","ipdsId":"IP-110241","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":488962,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.unl.edu/icwdm_usdanwrc/2436","text":"External Repository"},{"id":395654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Benedict's Island, Garlic Island, Fraction Islands Lake Butte des Morts ,Lake Winnebago, Long Point Island Monkey Island,,Terrell's Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.95492553710938,\n 43.78695837311561\n ],\n [\n -88.2366943359375,\n 43.78695837311561\n ],\n [\n -88.2366943359375,\n 44.24421523567905\n ],\n [\n -88.95492553710938,\n 44.24421523567905\n ],\n [\n -88.95492553710938,\n 43.78695837311561\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Koenigs, Ryan P.","contributorId":275008,"corporation":false,"usgs":false,"family":"Koenigs","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":56696,"text":"Wisconson Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":833573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dembkowski, Daniel J.","contributorId":275009,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":833574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovell, Charles D.","contributorId":275010,"corporation":false,"usgs":false,"family":"Lovell","given":"Charles D.","affiliations":[{"id":40821,"text":"U. 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Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":833575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":833572,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nickel, Adam","contributorId":275011,"corporation":false,"usgs":false,"family":"Nickel","given":"Adam","email":"","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":833576,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216216,"text":"70216216 - 2020 - Shorebird reproductive response to exceptionally early and late springs varies across sites in Arctic Alaska","interactions":[],"lastModifiedDate":"2020-11-10T12:45:10.570893","indexId":"70216216","displayToPublicDate":"2020-11-09T06:40:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Shorebird reproductive response to exceptionally early and late springs varies across sites in Arctic Alaska","docAbstract":"While increases in overall temperatures are widely reported in the Arctic, large inter-annual variation in spring weather, with extreme early and late conditions, is also occurring. Using data collected from three sites in Arctic Alaska, we explored how shorebird breeding density, nest initiation, nest synchrony, nest survival, and phenological mismatch varied between two exceptionally early (2015 and 2016) and late (2017 and 2018) springs. We assessed these differences in the context of long-term data from each site and whether species exhibited conservative or opportunistic reproductive strategies. Conservative shorebirds typically display nest-site fidelity and territoriality, consistent population densities, relatively even individual spacing, and monogamous mating systems with bi-parental incubation. In contrast, opportunistic shorebirds display the opposite traits, and a polygamous mating system with uniparental incubation. In this study, we evaluated 2,239 nests from 13 shorebird species, 2015–2018, and found that shorebirds of both strategies bred earlier and in higher numbers in early, warm springs relative to historic levels (based on 3,789 nests, 2005–2014); opposite trends were observed in late springs. In early springs, nests were initiated less synchronously than in late springs. Nest survival was unrelated to spring type, but was greater in earlier laid nests overall. Invertebrate food resources emerged earlier in early springs, resulting in a greater temporal asynchrony between invertebrate emergence and chick hatching in early than late springs. However, invertebrate abundance was quite variable among sites and years regardless of spring type. Overall, our results were generally consistent with predicted relationships between spring conditions and reproductive parameters. However, we detected differences among sites that could not be explained by other ecological factors (e.g., predators or alternative prey). Differences in shorebird community composition and other subtler methodological/ecological differences among sites highlight the difficulty of understanding the complex nature of these ecological systems and the importance of evaluating questions at multiple sites across multiple years. Our study demonstrates that shorebirds exhibit a high degree of behavioral flexibility in response to variable Arctic conditions, but whether this flexibility is enough to allow them to optimally track changing environmental conditions or if evolutionary adjustments will be necessary is unknown.
The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.
","language":"English","publisher":"AAAS","doi":"10.1126/science.abb7080","usgsCitation":"Davidson, S., Bohrer, G., Gurarie, E., LaPoint, S., Mahoney, P.J., Boelman, N., Eitel, J.U., Prugh, L.R., Vierling, L.A., Jennewein, J., Grier, E., Couriot, O., Kelly, A.P., Meddens, A.J., Oliver, R.Y., Kays, R., Wikelski, M., Aarvak, T., Ackerman, J.T., Almeida e Silva, M., Alves, J., Bayne, E., Bedrosian, B., Belant, J.L., Berdahl, A.M., Berlin, A., Berteaux, D., Bety, J., Boiko, D., Booms, T.L., Borg, B.L., Boutin, S., Boyd, W., Brides, K., Brown, S.C., Bulyuk, V.N., Burnham, K., Cabot, D., Casazza, M.L., Christie, K.S., Craig, E.H., Davis, S.E., Davison, T., Demma, D., DeSorbo, C.R., Dixon, A.E., Domenech, R., Eichhorn, G., Elliott, K., Evenson, J.R., Exo, K., Ferguson, S., Fiedler, W., Fisk, A.T., Fort, J., Franke, A., Fuller, M.R., Garthe, S., Gauthier, G., Gilchrist, G., Glazov, P., Gray, C., Gremillet, D., Griffin, L., Hallworth, M., Harrison, A., Hennin, H., Hipfner, J.M., Hodson, J., Johnson, J.A., Joly, K., Jones, K., Katzner, T., Kidd, J., Knight, E., Kochert, M.N., Kolzsch, A., Kruckenberg, H., Lagassé, B., Lai, S., Lamarre, J., Lanctot, R., Larter, N.C., Latham, A.D., Latty, C.J., Lawler, J.P., Leandri-Breton, D., Lee, H., Lewis, S.B., Love, O.P., Madsen, J., Maftei, M., Mallory, M.L., Mangipane, B., Markovets, M.Y., Marra, P.P., McGuire, R., McIntyre, C., McKinnon, E.A., Miller, T.A., Moonen, S., Mu, T., Muskens, G.J., Ng, J., Nicholson, K.L., Jostein Oien, I., Overton, C.T., Owen, P.A., Patterson, A.G., Petersen, A., Pokrovsky, I., Powell, L.L., Prieto, R., Quillfeldt, P., Rausch, J., Russell, K., Saalfeld, S.T., Schekkerman, H., Schmutz, J.A., Schwemmer, P., Seip, D.R., Shreading, A., Silva, M., Smith, B.W., Smith, F., Smith, J.P., Snell, K.R., Sokolov, A., Sokolov, V., Solovyeva, D.V., Sorum, M.S., Tertitski, G., Therrien, J.F., Thorup, K., Tibbitts, T., Tulp, I., Uher-Koch, B.D., van Bemmelen, R., Van Wilgenburg, S., Von Duyke, A.L., Watson, J., Watts, B.D., Williams, J.A., Wilson, M., Wright, J., Yates, M., Yurkowski, D., Žydelis, R., and Hebblewhite, M., 2020, Ecological insights from three decades of animal movement tracking across a changing Arctic: Science, v. 370, no. 6517, p. 712-715, https://doi.org/10.1126/science.abb7080.","productDescription":"4 p.","startPage":"712","endPage":"715","ipdsId":"IP-114828","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":454859,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pure.au.dk/portal/en/publications/8b4d3d53-e9d5-4fdd-9bd7-7952c62b7f07","text":"External Repository"},{"id":382521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"370","issue":"6517","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Davidson, Sarah 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These units range in age from late(?) Proterozoic through Devonian and can be divided into two distinct facies belts: (1) a southern facies of dominantly shallow-water platform carbonate and minor siliciclastic rocks (including Early Ordovician–Early Devonian platform edge algal buildups) with subordinate transgressive tongues of deeper-water platy carbonates; and (2) a northern facies belt of approximately age equivalent deep-water carbonate and siliciclastic rocks deposited in slope and basinal environments. Both facies belts belong to the Farewell terrane of Decker and others (1994). Two structural provinces are also recognized, which correspond directly with these belts. The Farewell terrane is interpreted as a continental margin sequence that rifted from Siberia. Many of the bedrock units recognized in the Sleetmute A-2 quadrangle are equivalent to units previously recognized to the east and northeast in the Lime Hills, McGrath, and Medfra quadrangles. Shallow-water carbonate platform rocks make up the majority of the southern facies and occur primarily along the crest and north side (and to a lesser degree along the south side) of a prominent crescentic-shaped, east-west trending anticlinal axis exposed in the southern part of the Sleetmute A-2 quadrangle. Because of the relatively low thermal alteration indices of the rocks of this area and the presence of highly porous dolostone intervals of good reservoir quality in the platform facies, this region elicited interest for petroleum exploration in the 1980s. However, low total organic carbon (TOC) content of potential source rocks within the Ordovician–Silurian basinal facies belt indicates low petroleum resource potential for this area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3450","usgsCitation":"Blodgett, R.B., Wilson, F.H., Shew, N.B., and Clough, J.G., 2020, Bedrock geologic map of the 15' Sleetmute A-2 quadrangle, southwestern Alaska: U.S. Geological Survey Scientific Investigations Map 3450, 18 p., 1 map sheet, scale 1:63,360, https://doi.org/10.3133/sim3450.","productDescription":"Pamphlet: iv, 18 p.; 1 Sheet: 23.20 x 26.17 inches; Table; Spatial Data","onlineOnly":"Y","ipdsId":"IP-098211","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":380271,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3450/sim3450.pdf","text":"Sheet 1","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3450"},{"id":380272,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3450/sim3450_pamphlet.pdf","text":"Pamphlet","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3450 Pamphlet"},{"id":380270,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3450/coverthb.jpg"},{"id":380273,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3450/sim3450_table.csv","text":"Table 1","size":"10 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIM 3450 Table csv"},{"id":380274,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3450/sim3450_table.xls","text":"Table 1","size":"39 KB xls","description":"SIM 3450 Table xls"},{"id":380275,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3450/sim3450_spatial_data.zip","text":"SIM 3450 spatial data","size":"2.2 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3450 Spatial Data"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.45,\n 61.000\n ],\n [\n -156.2230,\n 61.000\n ],\n [\n -156.2230,\n 61.15\n ],\n [\n -156.45,\n 61.15\n ],\n [\n -156.45,\n 61.000\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
North America has more than 4000 bee species, yet we have little information on the health, distribution, and population trends of most of these species. In the United States, what information is available is distributed across multiple institutions, and efforts to track bee populations are largely uncoordinated on a national scale. An overarching framework for monitoring U.S. native bees could provide a system that is responsive to national needs, resources, and capacities. Five major action areas and priorities for structuring a coordinated effort include: (1) Defining the scope, aims, and cost of a national native bee monitoring program; (2) Improving the national capacity in bee taxonomy and systematics; (3) Gathering and cataloging data that are standardized, accessible, and sustainable; (4) Identifying survey methods and prioritizing taxa to monitor; and (5) Prioritizing geographic areas to be monitored. Here, we detail the needs, challenges, and opportunities associated with developing a multi-layered U.S. national plan for native bee monitoring.
This report provides the best estimates of riparian area evapotranspiration (ET) on the rivers and streams of the Navajo Nation by (1) quantifying the natural riparian vegetation water use within the Little Colorado River watershed using a literature search for comparable riparian ET estimates, and (2) in conjunction with the given area of stream-side plant cover on the Navajo Nation, provides the best estimate of consumptive use, the total water requirement (in acre-feet). This report includes riparian water use information only from the literature for riparian areas that are in similar dryland ecosystems in the Southwest, and not specific to the perennial tributaries and springs on the Navajo Nation within the Little Colorado River watershed. The report also includes any information found regarding the location of Navajo Nation weather station variables, such as where we can derive required data inputs from the Navajo Nation to estimate actual ET rates (in millimeters per day or millimeters per year). We provide estimates of annual riparian plant water use and calculations that include reference ET (potential ET or ETo), precipitation (in millimeters), and the calculations of consumptive water requirements of riparian vegetation. We cite our data sources and provide references used to determine the consumptive water requirement (acre-feet).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201129","collaboration":"Prepared in cooperation with Fred Phillips Consulting","usgsCitation":"Nagler, P.L., 2020, Literature reviewed estimates of riparian consumptive water use in the drylands of Northeast Arizona, USA: U.S. Geological Survey Open-File Report 2020–1129, 9 p., https://doi.org/10.3133/ofr20201129.","productDescription":"v, 9 p.","onlineOnly":"Y","ipdsId":"IP-122975","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":380268,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1129/coverthb.jpg"},{"id":380269,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1129/ofr20201129.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1129"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.26855468749999,\n 32.30570601389429\n ],\n [\n -113.51074218749999,\n 32.30570601389429\n ],\n [\n -113.51074218749999,\n 35.71083783530009\n ],\n [\n -115.26855468749999,\n 35.71083783530009\n ],\n [\n -115.26855468749999,\n 32.30570601389429\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.90673828125,\n 34.45221847282654\n ],\n [\n -108.984375,\n 34.45221847282654\n ],\n [\n -108.984375,\n 36.96744946416934\n ],\n [\n -111.90673828125,\n 36.96744946416934\n ],\n [\n -111.90673828125,\n 34.45221847282654\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC Staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Shorebirds—which include sandpipers, plovers, and oystercatchers—are perhaps best known by their presence on sandy beaches, running along the water’s edge while they probe for food. But they are probably less recognized for their impressive long-distance migrations. Millions of individuals travel from across the globe to breed throughout Alaska each spring, making these birds a familiar and important part of local wildlife communities and Alaska Native cultures. Unfortunately, many shorebird populations have steeply declined worldwide. Because shorebirds use the same coastal habitats as humans, anthropogenic development can lead to habitat loss that degrades the extent and quality of coastal sites important to these species. However, Alaska has an abundance of intact coastal ecosystems that provide important breeding and migratory stopover sites for shorebirds, making the State one of the world’s most critical sites for shorebirds. The focus of shorebird research at the U.S. Geological Survey Alaska Science Center is to help identify important breeding and migratory sites, and to investigate the causes of the declines in many shorebird populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203056","usgsCitation":"Ruthrauff, D.R., Tibbitts, T.L., and Pearce, J.M., 2020, Shorebird research at the U.S. Geological Survey Alaska Science Center: U.S. Geological Survey Fact Sheet 2020-3056, 4 p., https://doi.org/10.3133/fs20203056.","productDescription":"4 p.","onlineOnly":"Y","ipdsId":"IP-118225","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":380242,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3056/fs20203056.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3056"},{"id":380241,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3056/coverthb2.jpg"}],"contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The 2018 summit and flank eruption of Kīlauea Volcano was one of the largest volcanic events in Hawaiʻi in 200 years. Data suggest that a backup in the magma plumbing system at the long-lived Puʻu ʻŌʻō eruption site caused widespread pressurization in the volcano, driving magma into the lower flank. The eruption evolved, and its impact expanded, as a sequence of cascading events, allowing relatively minor changes at Puʻu ʻŌʻō to cause major destruction and historic changes across the volcano. Eruption forecasting is inherently challenging in cascading scenarios where magmatic systems may prime gradually and trigger on small events.
","language":"English","publisher":"Nature Research","doi":"10.1038/s41467-020-19190-1","usgsCitation":"Patrick, M.R., Houghton, B.F., Anderson, K.R., Poland, M.P., Montgomery-Brown, E.K., Johanson, I.A., Thelen, W., and Elias, T., 2020, The cascading origin of the 2018 Kīlauea eruption and implications for future forecasting: Nature Communications, v. 11, no. 5646, 13 p., https://doi.org/10.1038/s41467-020-19190-1.","productDescription":"13 p.","ipdsId":"IP-118822","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":454864,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-020-19190-1","text":"Publisher Index Page"},{"id":384244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Hawai'i, Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.39886474609375,\n 19.147762846204802\n ],\n [\n -154.67376708984375,\n 19.147762846204802\n ],\n [\n -154.67376708984375,\n 20.06109122960637\n ],\n [\n -155.39886474609375,\n 20.06109122960637\n ],\n [\n -155.39886474609375,\n 19.147762846204802\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"5646","noUsgsAuthors":false,"publicationDate":"2020-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false},{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":811534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Montgomery-Brown, Emily K. 0000-0001-6787-2055","orcid":"https://orcid.org/0000-0001-6787-2055","contributorId":214074,"corporation":false,"usgs":true,"family":"Montgomery-Brown","given":"Emily","email":"","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811537,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johanson, Ingrid A. 0000-0002-6049-2225","orcid":"https://orcid.org/0000-0002-6049-2225","contributorId":215613,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811538,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thelen, Weston 0000-0003-2534-5577","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":215530,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811539,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Elias, Tamar 0000-0002-9592-4518 telias@usgs.gov","orcid":"https://orcid.org/0000-0002-9592-4518","contributorId":3916,"corporation":false,"usgs":true,"family":"Elias","given":"Tamar","email":"telias@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811540,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216204,"text":"70216204 - 2020 - The firn meltwater Retention Model Intercomparison Project (RetMIP): Evaluation of nine firn models at four weather station sites on the Greenland ice sheet","interactions":[],"lastModifiedDate":"2020-11-10T13:04:01.696787","indexId":"70216204","displayToPublicDate":"2020-11-06T06:51:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3554,"text":"The Cryosphere","active":true,"publicationSubtype":{"id":10}},"title":"The firn meltwater Retention Model Intercomparison Project (RetMIP): Evaluation of nine firn models at four weather station sites on the Greenland ice sheet","docAbstract":"Perennial snow, or firn, covers 80 % of the Greenland ice sheet and has the capacity to retain surface meltwater, influencing the ice sheet mass balance and contribution to sea-level rise. Multilayer firn models are traditionally used to simulate firn processes and estimate meltwater retention. We present, intercompare and evaluate outputs from nine firn models at four sites that represent the ice sheet's dry snow, percolation, ice slab and firn aquifer areas. The models are forced by mass and energy fluxes derived from automatic weather stations and compared to firn density, temperature and meltwater percolation depth observations. Models agree relatively well at the dry-snow site while elsewhere their meltwater infiltration schemes lead to marked differences in simulated firn characteristics. Models accounting for deep meltwater percolation overestimate percolation depth and firn temperature at the percolation and ice slab sites but accurately simulate recharge of the firn aquifer. Models using Darcy's law and bucket schemes compare favorably to observed firn temperature and meltwater percolation depth at the percolation site, but only the Darcy models accurately simulate firn temperature and percolation at the ice slab site. Despite good performance at certain locations, no single model currently simulates meltwater infiltration adequately at all sites. The model spread in estimated meltwater retention and runoff increases with increasing meltwater input. The highest runoff was calculated at the KAN_U site in 2012, when average total runoff across models (±2σ) was 353±610 mm w.e. (water equivalent), about 27±48 % of the surface meltwater input. We identify potential causes for the model spread and the mismatch with observations and provide recommendations for future model development and firn investigation.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/tc-14-3785-2020","usgsCitation":"Vandecrux, B., Mottram, R., Langen, P., Fausto, R., Olesen, M., Stevens, C.M., Verjans, V., Lee, A., Ligtenberg, S., Kuipers Munneke, P., Marchenko, S., van Pelt, W., Meyer, C.R., Simonsen, S.B., Heilig, A., Samimi, S., Marshall, S.J., Machguth, H., MacFerrin, M.J., Niwano, M., Miller, O.L., Voss, C.I., and Box, J.E., 2020, The firn meltwater Retention Model Intercomparison Project (RetMIP): Evaluation of nine firn models at four weather station sites on the Greenland ice sheet: The Cryosphere, v. 14, p. 3785-3810, https://doi.org/10.5194/tc-14-3785-2020.","productDescription":"26 p.","startPage":"3785","endPage":"3810","ipdsId":"IP-118335","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":454868,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-14-3785-2020","text":"Publisher Index Page"},{"id":380331,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -42.1875,\n 61.438767493682825\n ],\n [\n -22.8515625,\n 69.41124235697256\n ],\n [\n -18.984375,\n 76.01609366420995\n ],\n [\n -14.0625,\n 81.56996820323275\n ],\n [\n -66.796875,\n 80.70399666821143\n ],\n [\n -71.015625,\n 78.83606545333527\n ],\n [\n -70.3125,\n 76.9206135182968\n ],\n [\n -58.35937499999999,\n 73.92246884621463\n ],\n [\n -57.30468749999999,\n 69.16255790810501\n ],\n [\n -50.2734375,\n 60.23981116999893\n ],\n [\n -41.8359375,\n 59.17592824927136\n ],\n [\n -42.1875,\n 61.438767493682825\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2020-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Vandecrux, Baptiste","contributorId":244723,"corporation":false,"usgs":false,"family":"Vandecrux","given":"Baptiste","email":"","affiliations":[{"id":48961,"text":"Geological Survey of Denmark and Greenland, Copenhagen, Denmark.","active":true,"usgs":false}],"preferred":false,"id":804456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mottram, Ruth","contributorId":244738,"corporation":false,"usgs":false,"family":"Mottram","given":"Ruth","email":"","affiliations":[],"preferred":false,"id":804486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langen, Peter","contributorId":244739,"corporation":false,"usgs":false,"family":"Langen","given":"Peter","email":"","affiliations":[],"preferred":false,"id":804487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fausto, Robert","contributorId":220400,"corporation":false,"usgs":false,"family":"Fausto","given":"Robert","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":804488,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olesen, Martin","contributorId":244740,"corporation":false,"usgs":false,"family":"Olesen","given":"Martin","email":"","affiliations":[],"preferred":false,"id":804489,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stevens, C. 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Western Branch","active":true,"usgs":true}],"preferred":true,"id":804506,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Box, Jason E.","contributorId":198809,"corporation":false,"usgs":false,"family":"Box","given":"Jason","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":804507,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70217122,"text":"70217122 - 2020 - Phasing of millennial-scale climate variability in the Pacific and Atlantic Oceans","interactions":[],"lastModifiedDate":"2021-01-06T12:47:55.504011","indexId":"70217122","displayToPublicDate":"2020-11-06T06:40:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Phasing of millennial-scale climate variability in the Pacific and Atlantic Oceans","docAbstract":"New radiocarbon and sedimentological results from the Gulf of Alaska document recurrent millennial-scale episodes of reorganized Pacific Ocean ventilation synchronous with rapid Cordilleran Ice Sheet discharge, indicating close coupling of ice-ocean dynamics spanning the past 42,000 years. Ventilation of the intermediate-depth North Pacific tracks strength of the Asian monsoon, supporting a role for moisture and heat transport from low latitudes in North Pacific paleoclimate. Changes in carbon-14 age of intermediate waters are in phase with peaks in Cordilleran ice-rafted debris delivery, and both consistently precede ice discharge events from the Laurentide Ice Sheet, known as Heinrich events. This timing precludes an Atlantic trigger for Cordilleran Ice Sheet retreat and instead implicates the Pacific as an early part of a cascade of dynamic climate events with global impact.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.aba7096","usgsCitation":"Walczak, M., Mix, A., Cowan, E., Fallon, S., Fitfield, K., Alder, J.R., Du, J., Haley, B., Hobern, T., Padman, J., Praetorius, S.K., Schmittner, A., Stoner, J., and Zellers, S., 2020, Phasing of millennial-scale climate variability in the Pacific and Atlantic Oceans: Science, v. 370, no. 6517, p. 716-720, https://doi.org/10.1126/science.aba7096.","productDescription":"5 p.","startPage":"716","endPage":"720","ipdsId":"IP-120777","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":381934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"370","issue":"6517","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walczak, Maureen 0000-0002-4123-6998","orcid":"https://orcid.org/0000-0002-4123-6998","contributorId":206972,"corporation":false,"usgs":false,"family":"Walczak","given":"Maureen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":807650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mix, Alan","contributorId":184163,"corporation":false,"usgs":false,"family":"Mix","given":"Alan","affiliations":[],"preferred":false,"id":807651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cowan, Ellen 0000-0001-6512-5769","orcid":"https://orcid.org/0000-0001-6512-5769","contributorId":247312,"corporation":false,"usgs":false,"family":"Cowan","given":"Ellen","email":"","affiliations":[{"id":36626,"text":"Appalachian State University","active":true,"usgs":false}],"preferred":false,"id":807652,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fallon, Stewart 0000-0002-8064-5903","orcid":"https://orcid.org/0000-0002-8064-5903","contributorId":152573,"corporation":false,"usgs":false,"family":"Fallon","given":"Stewart","email":"","affiliations":[],"preferred":false,"id":807653,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitfield, Keith 0000-0003-2866-4944","orcid":"https://orcid.org/0000-0003-2866-4944","contributorId":247314,"corporation":false,"usgs":false,"family":"Fitfield","given":"Keith","email":"","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":807654,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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2020 - High prevalence of biliary neoplasia in white perch Morone americana: Potential roles of bile duct parasites and environmental contaminants","interactions":[],"lastModifiedDate":"2021-01-22T19:45:45.226167","indexId":"70211649","displayToPublicDate":"2020-11-05T08:56:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"displayTitle":"High prevalence of biliary neoplasia in white perch Morone americana: Potential roles of bile duct parasites and environmental contaminants","title":"High prevalence of biliary neoplasia in white perch Morone americana: Potential roles of bile duct parasites and environmental contaminants","docAbstract":"Recent surveys of white perch Morone americana from Chesapeake Bay, USA, revealed a high prevalence of hepatic and biliary lesions, including neoplasia, and bile duct parasites. Here, we describe lesions in the liver and gallbladder and evaluate for statistical associations among lesions, parasites, and biomarkers of chemical exposure in fish from 2 tributaries of Chesapeake Bay. Fish were collected from an estuarine site in the Choptank River (n = 122, ages 3-11), a tributary with extensive agriculture within the watershed, and the Severn River (n = 131, ages 2-16), a tributary with extensive urban development. Passive integrative samplers were deployed at the fish collection site and an upstream, non-tidal site in each river for 30 d. Intrahepatic biliary lesions observed in fish from both rivers included neoplasia (23.3%), dysplasia (16.2%), hyperplasia (46.6%), cholangitis (24.9%), and dilated ducts containing plasmodia of Myxidium sp. (24.9%). Hepatocellular lesions included foci of hepatocellular alteration (FHA, 15.8%) and neoplasia in 4 Severn River fish (2.3%). Age of fish and Myxidium sp. infections were significant risk factors for proliferative and neoplastic biliary lesions, age alone was a risk factor for FHA, and Goussia bayae infections were associated with cholangitis and cholecystitis. Lesion prevalence was higher in fish from the Severn River, which contained higher concentrations of PAHs, organochlorine pesticides, and brominated diphenyl ethers. Metabolite biomarkers indicated higher PAH exposures in Severn River fish. This study suggests Myxidium sp. as a promoter of bile duct tumors, but more data are needed to evaluate the biological effects of environmental contaminants in this species.
","language":"English","publisher":"Inter Research Science Publisher","doi":"10.3354/dao03510","usgsCitation":"Matsche, M.A., Blazer, V., Pulster, E., and Mazik, P.M., 2020, High prevalence of biliary neoplasia in white perch Morone americana: Potential roles of bile duct parasites and environmental contaminants: Diseases of Aquatic Organisms, v. 141, p. 195-224, https://doi.org/10.3354/dao03510.","productDescription":"20 p.","startPage":"195","endPage":"224","ipdsId":"IP-119255","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":377084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.2666015625,\n 36.58024660149866\n ],\n [\n -74.92675781249999,\n 36.58024660149866\n ],\n [\n -74.92675781249999,\n 39.757879992021756\n ],\n [\n -78.2666015625,\n 39.757879992021756\n ],\n [\n -78.2666015625,\n 36.58024660149866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"141","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Matsche, Mark A","contributorId":194275,"corporation":false,"usgs":false,"family":"Matsche","given":"Mark","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":794927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pulster, Erin","contributorId":236999,"corporation":false,"usgs":false,"family":"Pulster","given":"Erin","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":794929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":794930,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217299,"text":"70217299 - 2020 - Short-term impact of sediment addition on plants and invertebrates in a southern California salt marsh","interactions":[],"lastModifiedDate":"2021-01-18T13:48:26.23386","indexId":"70217299","displayToPublicDate":"2020-11-05T07:44:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Short-term impact of sediment addition on plants and invertebrates in a southern California salt marsh","docAbstract":"The implementation and monitoring of management strategies is integral to protect coastal marshes from increased inundation and submergence under sea-level rise. Sediment addition is one such strategy in which sediment is added to marshes to raise relative elevations, decrease tidal inundation, and enhance ecosystem processes. This study looked at the plant and invertebrate community responses over 12 months following a sediment addition project on a salt marsh located in an urbanized estuary in southern California, USA. This salt marsh is experiencing local subsidence, is sediment-limited from landscape modifications, has resident protected species, and is at-risk of submergence from sea-level rise. Abiotic measurements, invertebrate cores, and plant parameters were analyzed before and after sediment application in a before-after-control-impact (BACI) design. Immediately following the sediment application, plant cover and invertebrate abundance decreased significantly, with smothering of existing vegetation communities without regrowth, presumably creating resulting harsh abiotic conditions. At six months after the sediment application treatment, Salicornia bigelovii minimally colonized the sediment application area, and Spartina foliosa spread vegetatively from the edges of the marsh; however, at 12 months following sediment application overall plant recovery was still minimal. Community composition of infaunal invertebrates shifted from a dominance of marsh-associated groups like oligochaetes and polychaetes to more terrestrial and more mobile dispersers like insect larvae. In contrast to other studies, such as those with high organic deposition, that showed vegetation and invertebrate community recovery within one year of sediment application, our results indicated a much slower recovery following a sediment addition of 32 cm which resulted in a supratidal elevation with an average of 1.62 m (NAVD88) at our sampling locations. Our results indicate that the site did not recover after one year and that recovery may take longer which illustrates the importance of long-term monitoring to fully understand restoration trajectories and inform adaptive management. Testing and monitoring sea-level rise adaptation strategies like sediment addition for salt marshes is important to prevent the loss of important coastal ecosystems.
GRACE satellite data are widely used to estimate groundwater storage (GWS) changes in aquifers globally; however, comparisons with GW monitoring and modeling data are limited. Here we compared GWS changes from GRACE over 15 yr (2002–2017) in 14 major U.S. aquifers with groundwater-level (GWL) monitoring data in ~23,000 wells and with regional and global hydrologic and land surface models. Results show declining GWS trends from GRACE data in the six southwestern and south-central U.S. aquifers, totaling −90 km3 over 15 yr, related to long-term (5–15 yr) droughts, and exceeding Lake Mead volume by ~2.5×. GWS trends in most remaining aquifers were stable or slightly rising. GRACE-derived GWS changes agree with GWL monitoring data in most aquifers (correlation coefficients, R = 0.52–0.95), showing that GRACE satellites capture groundwater (GW) dynamics. Regional GW models (eight models) generally show similar or greater GWS trends than those from GRACE. Large discrepancies in the Mississippi Embayment aquifer, with modeled GWS decline approximately four times that of GRACE, may reflect uncertainties in model storage parameters, stream capture, pumpage, and/or recharge rates. Global hydrologic models (2003–2014), which include GW pumping, generally overestimate GRACE GWS depletion (total: approximately −172 to −186 km3) in heavily exploited aquifers in southwestern and south-central U.S. by ~2.4× (GRACE: −74 km3), underscoring needed modeling improvements relative to anthropogenic impacts. Global land surface models tend to track GRACE GWS dynamics better than global hydrologic models. Intercomparing remote sensing, monitoring, and modeling data underscores the importance of considering all data sources to constrain GWS uncertainties.
Hurricane Michael (2018) was the first Category 5 storm on record to make landfall on the Florida panhandle since at least 1851 CE (Common Era), and it resulted in the loss of 59 lives and $25 billion in damages across the southeastern U.S. This event placed a spotlight on recent intense (exceeding Category 4 or 5 on the Saffir-Simpson Hurricane Wind Scale) hurricane landfalls, prompting questions about the natural range in variability of hurricane activity that the instrumental record is too short to address. Of particular interest is determining whether the frequency of recent intense hurricane landfalls in the northern Gulf of Mexico (GOM) is within or outside the natural range of intense hurricane activity prior to 1851 CE. In this study, we identify intense hurricane landfalls in northwest Florida during the past 2000 years based on coarse anomaly event detection from two coastal lacustrine sediment archives. We identified a historically unprecedented period of heightened storm activity common to four Florida panhandle localities from 650 to 1250 CE and a shift to a relatively quiescent storm climate in the GOM spanning the past six centuries. Our study provides long-term context for events like Hurricane Michael and suggests that the observational period 1851 CE to present may underrepresent the natural range in landfalling hurricane activity.
New, non-invasive methods for detecting and monitoring species presence are being developed to aid in fisheries and wildlife conservation management. The use of environmental DNA (eDNA) samples for detecting macrobiota is one such group of methods that is rapidly becoming popular and being implemented in national management programs. Here we focus on the development of species-specific targeted assays for probe-based quantitative PCR (qPCR) applications. Using probe-based qPCR offers greater specificity than is possible with primers alone. Furthermore, the ability to quantify the amount of DNA in a sample can be useful in our understanding of the ecology of eDNA and the interpretation of eDNA detection patterns in the field. Careful consideration is needed in the development and testing of these assays to ensure the sensitivity and specificity of detecting the target species from an environmental sample. In this protocol we will delineate the steps needed to design and test probe-based assays for the detection of a target species; including creation of sequence databases, assay design, assay selection and optimization, testing assay performance, and field validation. Following these steps will help achieve an efficient, sensitive, and specific assay that can be used with confidence. We demonstrate this process with our assay designed for populations of the mucket (Actinonaias ligamentina), a freshwater mussel species found in the Clinch River, USA.
","language":"English","publisher":"JoVE Journal","doi":"10.3791/61825","usgsCitation":"Klymus, K.E., Ruiz-Ramos, D.V., Thompson, N., and Richter, C.A., 2020, Development and testing of species-specific quantitative PCR assays for environmental DNA applications: JOVE Journal Of Visualized Experiments, v. 165, e61825, 25 p., https://doi.org/10.3791/61825.","productDescription":"e61825, 25 p.","ipdsId":"IP-120373","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":454875,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3791/61825","text":"Publisher Index Page"},{"id":436727,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BIGOS5","text":"USGS data release","linkHelpText":"Mucket eDNA detection in Wallen's Bend, Clinch river, Tennessee, September 2019"},{"id":381495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"165","noUsgsAuthors":false,"publicationDate":"2020-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":807105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruiz-Ramos, Dannise Vannesa 0000-0001-7282-0380","orcid":"https://orcid.org/0000-0001-7282-0380","contributorId":245827,"corporation":false,"usgs":true,"family":"Ruiz-Ramos","given":"Dannise","email":"","middleInitial":"Vannesa","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":807106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Nathan 0000-0002-1372-6340 nthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-1372-6340","contributorId":196133,"corporation":false,"usgs":true,"family":"Thompson","given":"Nathan","email":"nthompson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":807107,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richter, Catherine A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":138994,"corporation":false,"usgs":true,"family":"Richter","given":"Catherine","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":807108,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}