We model the kinematic rupture process of the 2019
A method to estimate the probable high groundwater level in Massachusetts, excluding Cape Cod and the islands, was developed in 1981. The method uses a groundwater measurement from a test site, groundwater measurements from an index well, and a distribution of high groundwater levels from wells in similar geologic and topographic settings. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, conducted an update to the Frimpter method for estimating the probable high groundwater levels in Massachusetts. The study evaluated the potential changes to the method resulting from four decades of additional groundwater-level data and the expansion of the network of wells for monitoring groundwater levels. The differences and potential benefits of daily, as opposed to monthly, measurements in the application of the method were examined because of the increased availability of high-frequency (subdaily) groundwater-level data. The study also considered long-term trends in groundwater levels that may alter the accuracy of the method. Finally, the accuracy of the estimated high groundwater levels was evaluated, and improved implementation guidance was prepared.
For this study, groundwater levels in 153 wells in Massachusetts and surrounding States with records with lengths of 16 to 78 years were analyzed. The highest recorded groundwater levels ranged from 1.2 feet (ft) above land surface (flooded conditions) to 45.8 ft below land surface, with a median of 4.6 ft below land surface. The maximum annual groundwater-level range was 1.4 to 17.9 ft, with a median of 5.5 ft.
The within-month variation, maximum annual groundwater-level range, and highest recorded groundwater level were computed using daily mean groundwater-level values from 28 wells with continuous records. The use of daily data resulted in larger maximum annual groundwater-level ranges (0.02 to 2.94 ft larger, with a median of 0.58 ft larger) and shallower highest-recorded groundwater levels (0.0 to 1.60 ft shallower, with a median of 0.18 ft shallower) than computations based on monthly measurements in the same wells.
Statistical tests showed moderate to strong evidence of trends in measurements of both high and low groundwater levels within most of the periods during which water levels were analyzed. High groundwater levels rose beneath the land surface at most sites during four of the six periods used for analysis (1966–2015, 1986–2015, 1991–2010, and 1981–2010). Low groundwater levels also increased at many sites during most of the periods evaluated, but this trend was less widespread than the similar trends in high groundwater levels, and the trend was to deeper low groundwater levels at more sites than the trend to deeper high groundwater levels. There was no clear trend in annual groundwater-level ranges at most sites during the six periods analyzed.
In general, the Frimpter method predicted shallower (higher) high groundwater levels than were observed but correctly classified sites according to their suitabilities for unmounded septic systems. The mean error of the predictions (difference between the estimated and observed groundwater levels) ranged from −3.23 ft to −1.40 ft for various approaches to estimating the groundwater-level range and selecting an index well. The method correctly classified 83 to 86 percent of monitoring-well sites according to their suitability for an unmounded septic system for many approaches to estimating the annual groundwater-level range and selecting an index well. The approach selected for estimating the annual groundwater-level range and selecting an index well will depend upon the importance of an accurate estimate of the high groundwater level as compared to the importance of an estimated high groundwater level that is less likely to be exceeded.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205036","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Barclay, J.R., and Mullaney, J.R., 2020, Updating data inputs, assessing trends, and evaluating a method to estimate probable high groundwater levels in selected areas of Massachusetts: U.S. Geological Survey Scientific Investigations Report 2020–5036, 45 p., https://doi.org/10.3133/sir20205036.","productDescription":"Report: viii, 45 p.; Data Release","numberOfPages":"45","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-103689","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":375551,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NM2PHP","text":"USGS data release","linkHelpText":"Data on well characteristics and well-pair characteristics for estimating high groundwater levels in selected areas of Massachusetts"},{"id":375553,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5036/sir20205036.pdf","text":"Report","size":"7.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5036"},{"id":375554,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5036/coverthb2.jpg"}],"country":"United States","state":"Connecticut, Massachusetts, New Hampshire, Rhode Island, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.8343505859375,\n 42.90011265525328\n ],\n [\n -73.2952880859375,\n 42.9524020856897\n ],\n [\n -73.27880859375,\n 42.65820178455667\n ],\n [\n -73.5150146484375,\n 42.12267315117256\n ],\n [\n -73.5479736328125,\n 41.393294288784865\n ],\n [\n -73.54248046875,\n 41.29431726315258\n ],\n [\n -73.487548828125,\n 41.20345619205131\n ],\n [\n -73.7347412109375,\n 41.10005163093046\n ],\n [\n -73.65234375,\n 41.000629848685385\n ],\n [\n -72.9547119140625,\n 41.14143302653628\n ],\n [\n -72.0538330078125,\n 41.17451935556443\n ],\n [\n -71.43310546875,\n 41.29431726315258\n ],\n [\n -70.6475830078125,\n 41.21585377825921\n ],\n [\n -69.7686767578125,\n 41.16211393939692\n ],\n [\n -69.8785400390625,\n 41.87774145109676\n ],\n [\n -70.1806640625,\n 42.17968819665961\n ],\n [\n -70.57617187499999,\n 42.718768102606326\n ],\n [\n -70.8343505859375,\n 42.90011265525328\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Acid deposition has declined across eastern North America and northern Europe due to reduced emissions of sulfur and nitrogen oxides. Ecosystem recovery has been slow with limited improvement in surface water chemistry. Delayed recovery has encouraged acid-neutralization strategies to accelerate recovery of impaired biological communities. Lime application has been shown to increase pH and dissolved organic carbon (DOC), which could also drive increased mobilization of mercury (Hg) to surface waters. A four-year study was conducted within Honnedaga Lake’s watershed in the Adirondack region of New York to compare the effects of watershed and direct channel lime additions on Hg in stream water and macroinvertebrates. All treatments sharply increased stream pH and DOC concentrations, but large differences in the duration of impacts were apparent. The watershed treatment resulted in multi-year increases in concentrations and loads of total Hg (150%; 390%), DOC (190%; 350%) and nutrients, whereas total Hg and DOC increased for short periods (72–96 h) after channel treatments. No response of Hg in macroinvertebrates was evident following the watershed treatment, but a potential short-term and spatially constrained increase occurred after the channel treatment. Our observations indicate that both treatment approaches mobilize Hg, but that direct channel liming mobilizes considerably less than watershed liming over any period longer than a few days. During the final study year, increased methyl Hg concentrations were observed across reference and treated streams, which may reflect an extended dry period, highlighting that climate variation may also affect Hg dynamics.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10646-020-02224-1","usgsCitation":"Millard, G., Riva-Murray, K., Burns, D., Montesdeoca, M.S., and Driscoll, C., 2020, The impact of lime additions on mercury dynamics in stream chemistry and macroinvertebrates: A comparison of watershed and direct stream addition management strategies: Ecotoxicology, v. 29, p. 1627-1643, https://doi.org/10.1007/s10646-020-02224-1.","productDescription":"17 p.","startPage":"1627","endPage":"1643","ipdsId":"IP-109979","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":436928,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C17PA0","text":"USGS data release","linkHelpText":"Methylmercury and associated data in macroinvertebrates from tributaries of Honnedaga Lake and from the Middle Branch Black River in New York."},{"id":378508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Honnedaga Lake watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.89448547363281,\n 43.469864270218416\n ],\n [\n -74.74754333496092,\n 43.469864270218416\n ],\n [\n -74.74754333496092,\n 43.56496912804994\n ],\n [\n -74.89448547363281,\n 43.56496912804994\n ],\n [\n -74.89448547363281,\n 43.469864270218416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","noUsgsAuthors":false,"publicationDate":"2020-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Millard, Geoffrey D.","contributorId":240873,"corporation":false,"usgs":false,"family":"Millard","given":"Geoffrey D.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":799038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":168876,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":799039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":799041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Montesdeoca, Mario S.","contributorId":240877,"corporation":false,"usgs":false,"family":"Montesdeoca","given":"Mario","email":"","middleInitial":"S.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":799042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Driscoll, Charles T.","contributorId":240874,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":799040,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210674,"text":"70210674 - 2020 - Dietary fat concentrations influence fatty acid assimilation patterns in Atlantic pollock (Pollachius virens)","interactions":[],"lastModifiedDate":"2020-06-16T14:58:09.969044","indexId":"70210674","displayToPublicDate":"2020-06-15T09:56:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3048,"text":"Philosophical Transactions of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Dietary fat concentrations influence fatty acid assimilation patterns in Atlantic pollock (Pollachius virens)","docAbstract":"A key aspect in the use of fatty acids (FA) to estimate predator diets using Quantitative FA Signature Analysis (QFASA) is the ability to account for FA assimilation through the use of calibration coefficients (CC). Here, we tested the assumption that CC are independent of dietary fat concentrations by feeding Atlantic pollock (Pollachius virens) three formulated diets with very similar FA proportions but different fat concentrations (5 – 9 % of diet) for 20 weeks. CC calculated using FA profiles of diet and triacylglycerols in pollock liver were significantly different for the three diets. To test the robustness of diet estimates to these differences, we used the CC set derived from feeding the diet with the lowest fat concentration, published prey FA profiles and realistic diet estimates of pollock to construct ‘pseudo-predators’. Application of QFASA to each pseudo-predator using the three sets of CC and the same prey FA profiles resulted in diet estimate biases of 2-fold for major prey items and ~ 5-fold for minor prey items. This work illustrates the importance of incorporating diets with fat concentrations that are similar to natural prey when conducting feeding experiments to calculate CC.","language":"English","publisher":"Royal Society Publishing","doi":"10.1098/rstb.2019.0649","usgsCitation":"Budge, S.M., Townsend, K., Lall, S.P., and Bromaghin, J.F., 2020, Dietary fat concentrations influence fatty acid assimilation patterns in Atlantic pollock (Pollachius virens): Philosophical Transactions of the Royal Society B: Biological Sciences, v. 375, no. 1804, 20190649, 9 p., https://doi.org/10.1098/rstb.2019.0649.","productDescription":"20190649, 9 p.","ipdsId":"IP-112457","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":456387,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2019.0649","text":"Publisher Index Page"},{"id":375619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"375","issue":"1804","noUsgsAuthors":false,"publicationDate":"2020-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Budge, Suzanne M.","contributorId":92168,"corporation":false,"usgs":false,"family":"Budge","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":790903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Townsend, Katherine","contributorId":225363,"corporation":false,"usgs":false,"family":"Townsend","given":"Katherine","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":790904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lall, Santosh P","contributorId":225364,"corporation":false,"usgs":false,"family":"Lall","given":"Santosh","email":"","middleInitial":"P","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":790905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":790906,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210700,"text":"70210700 - 2020 - Snow processes in mountain forests: Interception modeling for coarse-scale applications","interactions":[],"lastModifiedDate":"2020-06-18T14:54:10.16543","indexId":"70210700","displayToPublicDate":"2020-06-15T09:50:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Snow processes in mountain forests: Interception modeling for coarse-scale applications","docAbstract":"Snow interception by the forest canopy controls the spatial heterogeneity of subcanopy snow accumulation leading to significant differences between forested and nonforested areas at a variety of scales. Snow intercepted by the forest canopy can also drastically change the surface albedo. As such, accurately modeling snow interception is of importance for various model applications such as hydrological, weather, and climate predictions. Due to difficulties in the direct measurements of snow interception, previous empirical snow interception models were developed at just the point scale. The lack of spatially extensive data sets has hindered the validation of snow interception models in different snow climates, forest types, and at various spatial scales and has reduced the accurate representation of snow interception in coarse-scale models. We present two novel empirical models for the spatial mean and one for the standard deviation of snow interception derived from an extensive snow interception data set collected in an evergreen coniferous forest in the Swiss Alps. Besides open-site snowfall, subgrid model input parameters include the standard deviation of the DSM (digital surface model) and/or the sky view factor, both of which can be easily precomputed. Validation of both models was performed with snow interception data sets acquired in geographically different locations under disparate weather conditions. Snow interception data sets from the Rocky Mountains, US, and the French Alps compared well to the modeled snow interception with a normalized root mean square error (NRMSE) for the spatial mean of ≤10 % for both models and NRMSE of the standard deviation of ≤13 %. Compared to a previous model for the spatial mean interception of snow water equivalent, the presented models show improved model performances. Our results indicate that the proposed snow interception models can be applied in coarse land surface model grid cells provided that a sufficiently fine-scale DSM is available to derive subgrid forest parameters.
","language":"English","doi":"10.5194/hess-24-2545-2020","usgsCitation":"Helbig, N., Moeser, C.D., Teich, M., Vincent, L., Lejeune, Y., Sicart, J., and Monnet, J., 2020, Snow processes in mountain forests: Interception modeling for coarse-scale applications: Hydrology and Earth System Sciences, v. 24, p. 2545-2560, https://doi.org/10.5194/hess-24-2545-2020.","productDescription":"16 p.","startPage":"2545","endPage":"2560","ipdsId":"IP-111174","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":456397,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-24-2545-2020","text":"Publisher Index Page"},{"id":375684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"France, United States","state":"Utah","otherGeospatial":"French Alps, Rocky Mountains","volume":"24","noUsgsAuthors":false,"publicationDate":"2020-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Helbig, N. 0000-0002-8663-7306","orcid":"https://orcid.org/0000-0002-8663-7306","contributorId":225392,"corporation":false,"usgs":false,"family":"Helbig","given":"N.","email":"","affiliations":[{"id":41093,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland","active":true,"usgs":false}],"preferred":false,"id":791020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":791021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teich, M. 0000-0002-8850-9279","orcid":"https://orcid.org/0000-0002-8850-9279","contributorId":225393,"corporation":false,"usgs":false,"family":"Teich","given":"M.","email":"","affiliations":[{"id":41094,"text":"Austrian Research Centre for Forests (BFW), Innsbruck, Austria","active":true,"usgs":false}],"preferred":false,"id":791022,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vincent, L.","contributorId":225394,"corporation":false,"usgs":false,"family":"Vincent","given":"L.","email":"","affiliations":[{"id":41095,"text":"University Grenoble Alpes, University Toulouse, Météo-France, CNRS, CNRM, Centre d’Etudes de la Neige, Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":791023,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lejeune, Y.","contributorId":225395,"corporation":false,"usgs":false,"family":"Lejeune","given":"Y.","email":"","affiliations":[{"id":41095,"text":"University Grenoble Alpes, University Toulouse, Météo-France, CNRS, CNRM, Centre d’Etudes de la Neige, Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":791024,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sicart, J.-E.","contributorId":225396,"corporation":false,"usgs":false,"family":"Sicart","given":"J.-E.","email":"","affiliations":[{"id":41096,"text":"Université Grenoble Alpes, CNRS, IRD, Grenoble INP, Institut des Géosciences de l’Environnement (IGE) - UMR 5001,","active":true,"usgs":false}],"preferred":false,"id":791025,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Monnet, J.-M.","contributorId":225397,"corporation":false,"usgs":false,"family":"Monnet","given":"J.-M.","email":"","affiliations":[{"id":41097,"text":"Univ. Grenoble Alpes, Irstea, LESSEM, 38000 Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":791026,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70210859,"text":"70210859 - 2020 - Baseline conditions and projected future hydro-climatic change in National Parks in the conterminous United States","interactions":[],"lastModifiedDate":"2020-06-30T13:29:12.764279","indexId":"70210859","displayToPublicDate":"2020-06-15T08:24:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Baseline conditions and projected future hydro-climatic change in National Parks in the conterminous United States","docAbstract":"The National Park Service (NPS) manages hundreds of parks in the United States, and many contain important aquatic ecosystems and/or threatened and endangered aquatic species vulnerable to hydro-climatic change. Effective management of park resources under future hydro-climatic uncertainty requires information on both baseline conditions and the range of projected future conditions. A monthly water balance model was used to assess baseline (1981-1999) conditions and a range of projected future hydro-climatic conditions in 374 NPS parks. General circulation model outputs representing 214 future climate simulations were used to drive the model. Projected future changes in temperature (T), precipitation (P), and runoff (R) are expressed as departures from historical baselines. Climate simulations indicate increasing T in 2030 for all parks with 50th percentile simulations projecting increases of 1.67 oC or more in 50% of parks. Departures in 2030 P indicate a mix of mostly increases and some decreases, with 50th percentile simulations projecting increases in P in more than 70% of parks. Departures in R for 2030 are mostly decreases , with the 50th percentile simulations projecting decreases in R in more than 50% of parks in all seasons except winter. Hence in many parks, R is projected to decrease even when P is projected to increase because of increasing T in all NPS parks. Projected changes in future hydro-climatic conditions can also be assessed for individual parks, and Rocky Mountain National Park and Congaree National Park are used as examples.","language":"English","publisher":"MDPI","doi":"10.3390/w12061704","usgsCitation":"Battaglin, W., Hay, L., Lawrence, D.J., McCabe, G.J., and Norton, P.A., 2020, Baseline conditions and projected future hydro-climatic change in National Parks in the conterminous United States: Water, v. 6, no. 12, 1704, 24 p., https://doi.org/10.3390/w12061704.","productDescription":"1704, 24 p.","ipdsId":"IP-117255","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":456399,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12061704","text":"Publisher Index Page"},{"id":376013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n 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ecosystem","interactions":[],"lastModifiedDate":"2020-07-10T13:20:01.000249","indexId":"70211015","displayToPublicDate":"2020-06-15T08:16:44","publicationYear":"2020","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":"Conceptualizing alternate regimes in a large floodplain-river ecosystem","docAbstract":"Regime shifts –persistent changes in the structure and function of an ecosystem - are well-documented in many ecosystems but remain poorly understood in floodplain-river ecosystems. We apply a resilience perspective to large floodplain-river ecosystems by presenting three examples of plausible sets of alternate regimes that are relevant to natural resource management interests within the Upper Mississippi River and Illinois River. These alternate regimes include: 1) a clear water and abundant vegetation regime vs. a turbid water and sparse vegetation regime in lentic, off-channel areas, 2) a diverse native fish community regime vs. an invasive-dominated fish community regime, and 3) a regime characterized by a diverse and dynamic mosaic of floodplain vegetation types vs. one characterized as a persistent invasive wet meadow monoculture. For each set of potential alternate regimes, we synthesize known or hypothesized feedback mechanisms that reinforce regimes, controlling variables that drive regime transitions, and restoration pathways. The conceptual models presented here provide a framework for synthesizing our understanding of the dynamics of this ecosystem and are relevant to other large floodplain-river ecosystems that face similar human pressures across the world. The models are currently being used to prioritize future research, test hypotheses, and inform restoration and management on the Upper Mississippi River and Illinois River. Through sharing our approach, we provide a case study in which we document an important step in operationalizing resilience concepts for the management of natural resources.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2020.110516","usgsCitation":"Bouska, K.L., Houser, J.N., De Jager, N.R., Drake, D.C., Collins, S.F., Gibson-Reniemer, C.K., and Thomsen, M.A., 2020, Conceptualizing alternate regimes in a large floodplain-river ecosystem: Journal of Environmental Management, v. 264, 110516, 15 p., https://doi.org/10.1016/j.jenvman.2020.110516.","productDescription":"110516, 15 p.","ipdsId":"IP-108847","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":376247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin, Iowa, Illinois, Missouri","otherGeospatial":"Upper Mississippi River, Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.58154296875,\n 37.020098201368114\n ],\n [\n -88.22021484375,\n 37.020098201368114\n ],\n [\n -88.22021484375,\n 45.27488643704891\n ],\n [\n -93.58154296875,\n 45.27488643704891\n ],\n [\n -93.58154296875,\n 37.020098201368114\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"264","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":792430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":792431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":792432,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drake, Deanne C.","contributorId":207846,"corporation":false,"usgs":false,"family":"Drake","given":"Deanne","email":"","middleInitial":"C.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":792433,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collins, Scott F.","contributorId":172292,"corporation":false,"usgs":false,"family":"Collins","given":"Scott","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":792434,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gibson-Reniemer, Caniel K.","contributorId":228874,"corporation":false,"usgs":false,"family":"Gibson-Reniemer","given":"Caniel","email":"","middleInitial":"K.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":792435,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thomsen, Meredith A.","contributorId":228875,"corporation":false,"usgs":false,"family":"Thomsen","given":"Meredith","email":"","middleInitial":"A.","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":792436,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70225148,"text":"70225148 - 2020 - Using a bayesian multistate occupancy model to assess seabird and shorebird status in Glacier Bay, Alaska","interactions":[],"lastModifiedDate":"2021-10-14T12:44:11.60355","indexId":"70225148","displayToPublicDate":"2020-06-15T07:41:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Using a bayesian multistate occupancy model to assess seabird and shorebird status in Glacier Bay, Alaska","docAbstract":"The U.S. Department of Interior National Park Service is charged with both monitoring avian communities and evaluating the influence of visitors to National Parks on sensitive species; however, this task is challenging considering that sampling programs often involve multiple species, each with differing behavior, habitat requirements, and detectability. Our objectives were to build a model to describe the status of waterbirds in Glacier Bay National Park, Alaska, USA, and assess effects of area closures on these species. We used a Bayesian multistate occupancy model to describe the status of multiple species and make the best possible use of existing survey data. We modeled up to 5 states per species and evaluated predictors of occupancy, nesting, and abundance, as well as survey-related predictors of state-dependent detection probability. We found that occupancy probability varied across species and habitats (islands vs. glacial outwashes). For most species, occupancy probability was substantially greater at sites occupied in the year previous (site persistence). We found weak evidence that area closures affected the occurrence of species in the study, but this was largely because most sites were closed for the entirety of the study period. The probability of detecting occurrence, nesting, and abundance varied across species and survey methods (ground vs. vessel). Detection parameters provided valuable information for enhancing the efficiency of future surveys, by identifying preferred survey methods and sampling periods for specific waterbird species. © 2020 The Wildlife Society.
Dynamically triggered offshore aftershocks, caused by passing seismic waves from main shocks located on land, are currently not considered in tsunami warnings. The M7.0 2010 Haiti earthquake epicenter was located on land 27 km north of the Caribbean Sea and its focal mechanism was oblique strike-slip. Nevertheless, a tsunami recorded on a Caribbean Deep-Ocean Assessment and Reporting of Tsunami (DART) buoy and a tide gauge produced runup heights of 1–3 m along Haiti southeast coast. Earthquake finite-fault model inversions of the DART waveform suggest that a reverse fault doublet with magnitudes of M6.8 and M6.5 located 85 km southwest of the epicenter may have excited the tsunami. This doublet collocates with dynamically triggered aftershocks, derived from back-projection analysis, that occurred 20-60 s after the main shock of the Haiti earthquake. The aftershocks are within a region of maximum dynamic strain predicted by the main shock, on a possibly tectonically active submarine ridge southwest of Haiti's Southern Peninsula. The agreement between the tsunami finite-fault source models and the seismic and tectonic evidence suggests that earthquakes on land, even strike-slip faults, can generate tsunamis by dynamically triggering offshore aftershocks.
Environmental change associated with anthropogenic disturbance can lower habitat quality, especially for sensitive species such as many amphibians. Variation in environmental quality may affect an organism’s physiological health and, ultimately, survival and fitness. Using multiple health measures can aid in identifying populations at increased risk of declines. Our objective was to measure environmental variables at multiple spatial scales and their effect on three indicators of health in ornate chorus frog (Pseudacris ornata) tadpoles to identify potential correlates of population declines. To accomplish this, we measured a glucocorticoid hormone (corticosterone; CORT) profile associated with the stress response, as well as the skin mucosal immune function (combined function of skin secretions and skin bacterial community) and bacterial communities of tadpoles from multiple ponds. We found that water quality characteristics associated with environmental variation, including higher water temperature, conductivity and total dissolved solids, as well as percent developed land nearby, were associated with elevated CORT release rates. However, mucosal immune function, although highly variable, was not significantly associated with water quality or environmental factors. Finally, we examined skin bacterial diversity as it aids in immunity and is affected by environmental variation. We found that skin bacterial diversity differed between ponds and was affected by land cover type, canopy cover and pond proximity. Our results indicate that both local water quality and land cover characteristics are important determinants of population health for ornate chorus frogs. Moreover, using these proactive measures of health over time may aid in early identification of at-risk populations that could prevent further declines and aid in management decisions.
","language":"English","publisher":"The Society for Experimental Biology","doi":"10.1093/conphys/coaa047","usgsCitation":"Goff, C.B., Walls, S., Rodriguez, D., and Gabor, C.S., 2020, Changes in physiology and microbial diversity in larval ornate chorus frogs are associated with habitat quality: Conservation Physiology, v. 8, no. 1, coaa047, 19 p., https://doi.org/10.1093/conphys/coaa047.","productDescription":"coaa047, 19 p.","ipdsId":"IP-109179","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456407,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coaa047","text":"Publisher Index Page"},{"id":436929,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UBF9SM","text":"USGS data release","linkHelpText":"Corticosterone release rates, water quality, microbiome, and mucosome data for analysis of Pseudacris ornata sites"},{"id":411709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Goff, Cory B.","contributorId":300720,"corporation":false,"usgs":false,"family":"Goff","given":"Cory","email":"","middleInitial":"B.","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":861287,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walls, Susan C. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":216235,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":861288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriguez, David","contributorId":300721,"corporation":false,"usgs":false,"family":"Rodriguez","given":"David","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":861289,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gabor, Caitlin S.","contributorId":300722,"corporation":false,"usgs":false,"family":"Gabor","given":"Caitlin","email":"","middleInitial":"S.","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":861290,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274789,"text":"70274789 - 2020 - Reassessing particulate organic carbon dynamics in the highly disturbed San Francisco Bay Estuary","interactions":[],"lastModifiedDate":"2026-04-09T15:01:46.432427","indexId":"70274789","displayToPublicDate":"2020-06-15T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23798,"text":"Frontiers Earth Science - Biogeoscience","active":true,"publicationSubtype":{"id":10}},"title":"Reassessing particulate organic carbon dynamics in the highly disturbed San Francisco Bay Estuary","docAbstract":"Environmental research has been shifting toward a new normal in which a primary focus is to capture change that may be accelerating. In this study, we collected particulate samples in the northern San Francisco Bay Estuary (SFBE) in the fall of 2011 through the spring of 2012 in order to assess vascular plant contributions across both time and space and to compare our findings with a similar set of samples from 1990 to 1992. Across the ∼20-year span, we detected (1) decreasing C:Na ratios (averages ± SD of 12.5 ± 2.5 vs. 8.8 ± 1.4, significant t-test with p < 0.0001); (2) distinct shifts in chlorophyll vs. salinity, with higher chlorophyll concentrations shifting toward freshwater; and (3) greater relative proportions of vascular plant carbon that also appears less degraded (as indicated by lignin measurements) shifting from freshwater toward higher salinities. Lignin compositional data (syringyl:vanillyl and cinnamyl:vanillyl) suggest that increased lignin content in the more saline samples could be derived from wetland materials, while a two-endmember mixing model indicates that a significant portion of the particulate organic carbon (POC) in the western sites (50–60% as an upper bound, 13–15% as a lower bound) could be wetland-derived. This has potential implications for the lower food web, given recent work that demonstrates selective feeding by copepods on wetland detrital material in the northern SFBE. The latter has ramifications for proposed wetland restoration within the SFBE and Sacramento River/San Joaquin River Delta system, namely, that restored wetlands could confer important benefits toward the food web. Equally important is to prioritize continued monitoring of particulate organic matter cycling in the SFBE system to make sure that changing conditions are accounted for in any management decision.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2020.00185","usgsCitation":"Hernes, P.J., Dyda, R.Y., and Bergamaschi, B.A., 2020, Reassessing particulate organic carbon dynamics in the highly disturbed San Francisco Bay Estuary: Frontiers Earth Science - Biogeoscience, v. 8, 185, 13 p., https://doi.org/10.3389/feart.2020.00185.","productDescription":"185, 13 p.","ipdsId":"IP-117634","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":502493,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2020.00185","text":"Publisher Index Page"},{"id":502352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin River Delta, San Francisco Bay Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.2443083713161,\n 38.39872273873195\n ],\n [\n -122.2443083713161,\n 37.81288212710655\n ],\n [\n -121.45817059994386,\n 37.81288212710655\n ],\n [\n -121.45817059994386,\n 38.39872273873195\n ],\n [\n -122.2443083713161,\n 38.39872273873195\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2020-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Hernes, Peter J.","contributorId":139730,"corporation":false,"usgs":false,"family":"Hernes","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":12894,"text":"Department of Land, Air, and Water Resources, University of California, One Shields Avenue, Davis, CA, 95616, USA","active":true,"usgs":false}],"preferred":false,"id":959148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dyda, Rachael Y. 0000-0002-4616-7231","orcid":"https://orcid.org/0000-0002-4616-7231","contributorId":369567,"corporation":false,"usgs":false,"family":"Dyda","given":"Rachael","middleInitial":"Y.","affiliations":[{"id":28024,"text":"UCDavis","active":true,"usgs":false}],"preferred":false,"id":959149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959150,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260130,"text":"70260130 - 2020 - Geology and eruptive history of Bogoslof volcano","interactions":[],"lastModifiedDate":"2024-10-29T11:58:39.677486","indexId":"70260130","displayToPublicDate":"2020-06-14T06:53:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Geology and eruptive history of Bogoslof volcano","docAbstract":"Bogoslof volcano is a shallow submarine/subaerial volcano in the southern Bering Sea about 100 km west of the community of Dutch Harbor, Alaska. The subaerial parts of the volcano consist of two small islands, Bogoslof Island and Fire Island, that together have a total area of about 1.6 km2. Bogoslof was first depicted on a Russian map in 1772 and since then has been observed and visited occasionally. The volcano has had at least nine periods of eruptive activity since 1796 and all of its historical eruptions have been similar in style. Historical Bogoslof eruptions involved the effusion of basalt, trachybasalt, basaltic trachyandesite, and trachyandesite lava domes with above sea level relief of 100–200 m. Many of the eruptions are accompanied by the formation of tuff rings and ejection of ballistic particles. Historical observations suggest that eruption clouds are relatively ash-poor. Minor ash fallout has typically occurred within about 100 km of the volcano. Many of the historical eruptions began at vents that were below sea level, and thus, seawater has played an important role in the style of eruptive activity exhibited by the volcano. At times, eruptive activity has been characterized by Surtseyan style eruptions and magma interaction with wet vent-fill deposits. At other times, the eruptive style has been more magmatically driven and has resulted in the formation of pyroclastic flows and small ash clouds. Preliminary studies of the deposits produced during the 2016–2017 eruption indicate vertical sequences of coarse-grained, horizontally bedded pyroclastic flow and fall deposits with numerous blocks, bombs, and lapilli of dense juvenile and accidental lithic material. These deposits were emplaced by near-vent pyroclastic flows, surges, and explosions some of which originated from shallow, highly crystalline cryptodomes.
To better understand the Earth system, it is important to investigate the interactions between precipitation, land use/land cover (LULC), and the land surface, especially vegetation. An improved understanding of these land-atmosphere interactions can aid understanding of the climate system and modeling of time series satellite data. Here, we investigate the effect of precipitation and LULC on the reflectance of the land surface in the northern U.S. Great Plains. We utilize time series satellite data from the 45 year Landsat archive. The length of the Landsat record allows for analysis of multiple periods of drought and wet conditions (reflecting climate, as well as weather), such that the precipitation-reflectance relationship can be investigated robustly for every individual pixel in the study area. The high spatial resolution of Landsat (30 m) allows for investigation of spatial patterns in weather (i.e., precipitation extremes) interactions with land surface reflectance at the scale of individual fields. Weather history is represented by a drought index that describes effective moisture availability, the Standardized Precipitation and Evaporation Index (SPEI). We find that effective moisture has a robust and consistent effect on reflectance over many types of land cover, with ∼90% of all pixels having significantly (
In the Northern Gulf of Mexico, salt marshes are threatened by sea level rise, erosion, and loss of protective barrier islands. These barrier islands provide critical habitat for wildlife, including globally significant populations of marsh and shorebirds. We investigated salt marsh restoration on two Louisiana barrier islands using presence of 8 marsh bird species as an index to evaluate restoration success. Land loss was extensive for both islands prior to restoration, with submerged marsh restored by backfilling sediment into the marsh platform. Restoration methods were similar between the two islands, although Raccoon Island was built to a higher elevation (1.1 m) than Whiskey Island (0.8m). Avian presence was estimated via passive acoustic monitoring and point counts. To evaluate restoration success, we modeled influence of habitat covariates on index species presence in restored and reference (intact) sites over three breeding seasons and modeled occupancy for 6 species. On Whiskey Island, index richness was higher in restored sites. Marsh specialists Seaside Sparrows (Ammospiza maritima ) and Least Bitterns (Ixobrychus exilis ) had higher occupancy in restored areas on Whiskey, while generalist species showed no response to site. These results are likely due to a strong association between habitat and vegetation type, with restored sites dominated by Spartina alterniflora and reference sites by Avicennia germinans . On Raccoon Island, species richness was low across all sites. Our results suggest that restoration efforts were successful in creating salt marsh habitat on Whiskey but not Raccoon as of the time of our study.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13222","usgsCitation":"Byerly, P.A., Waddle, H., Premeaux, A.R., and Leberg, P.L., 2020, Effects of barrier island salt marsh restoration on marsh bird occurrence in the Northern Gulf of Mexico: Restoration Ecology, v. 28, no. 6, p. 1610-1620, https://doi.org/10.1111/rec.13222.","productDescription":"11 p.","startPage":"1610","endPage":"1620","ipdsId":"IP-118357","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":377330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Isles Derniers, Raccoon Island, Whiskey Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.96954345703125,\n 29.014745722129636\n ],\n [\n -90.65711975097656,\n 29.014745722129636\n ],\n [\n -90.65711975097656,\n 29.09517707913941\n ],\n [\n -90.96954345703125,\n 29.09517707913941\n ],\n [\n -90.96954345703125,\n 29.014745722129636\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Byerly, Paige A.","contributorId":237930,"corporation":false,"usgs":false,"family":"Byerly","given":"Paige","email":"","middleInitial":"A.","affiliations":[{"id":36864,"text":"University of Louisiana Lafayette","active":true,"usgs":false}],"preferred":false,"id":795563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":222187,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":795564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Premeaux, Alexis R.","contributorId":237932,"corporation":false,"usgs":false,"family":"Premeaux","given":"Alexis","email":"","middleInitial":"R.","affiliations":[{"id":36864,"text":"University of Louisiana Lafayette","active":true,"usgs":false}],"preferred":false,"id":795565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leberg, Paul L.","contributorId":237934,"corporation":false,"usgs":false,"family":"Leberg","given":"Paul","email":"","middleInitial":"L.","affiliations":[{"id":36864,"text":"University of Louisiana Lafayette","active":true,"usgs":false}],"preferred":false,"id":795566,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210797,"text":"70210797 - 2020 - Annual adult survival drives trends in Arctic-breeding shorebirds but knowledge gaps in other vital rates remain","interactions":[],"lastModifiedDate":"2020-06-25T15:19:50.029027","indexId":"70210797","displayToPublicDate":"2020-06-13T09:25:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Annual adult survival drives trends in Arctic-breeding shorebirds but knowledge gaps in other vital rates remain","docAbstract":"Conservation status and management priorities are often informed by population trends. Trend estimates can be derived from population surveys or models, but both methods are associated with sources of uncertainty. Many Arctic-breeding shorebirds are thought to be declining based on migration and/or overwintering population surveys, but data are lacking to estimate the trends of some shorebird species. In addition, for most species, little is known about the stage(s) at which population bottlenecks occur, such as breeding vs. nonbreeding periods. We used previously published and unpublished estimates of vital rates to develop the first large-scale population models for 6 species of Arctic-breeding shorebirds in North America, including separate estimates for 3 subspecies of Dunlin. We used the models to estimate population trends and identify life stages at which population growth may be limited. Our model for the arcticola subspecies of Dunlin agreed with previously published information that the subspecies is severely declining. Our results also linked the decline to the subspecies’ low annual survival rate, thus potentially implicating factors during the nonbreeding period in the East Asian-Australasian Flyway. However, our trend estimates for all species showed high uncertainty, highlighting the need for more accurate and precise estimates of vital rates. Of the vital rates, annual survival had the strongest influence on population trend in all taxa. Improving the accuracy, precision, and spatial and temporal coverage of estimates of vital rates, especially annual survival, would improve demographic model-based estimates of population trends and help direct management to regions or seasons where birds are subject to higher mortality.","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duaa026","usgsCitation":"Weiser, E.L., Lanctot, R., Brown, S.C., Gates, H., Bety, J., Boldenow, M.L., Brook, R.W., Brown, G.S., English, W.B., Flemming, S.A., Franks, S., Gilchrist, H.G., Giroux, M., Johnson, A.C., Kendall, S., Kennedy, L.V., Koloski, L., Kwon, E., Lamarre, J., Lank, D.B., Latty, C.J., Lecomte, N., Liebezeit, J.R., McGuire, R., McKinnon, L., Nol, E., Payer, D.C., Perz, J., Rausch, J., Robards, M.D., Saalfeld, S.T., Senner, N.R., Smith, P., Soloviev, M., Solovyeva, D.V., Ward, D.H., Wood, P., and Sandercock, B., 2020, Annual adult survival drives trends in Arctic-breeding shorebirds but knowledge gaps in other vital rates remain: The Condor, v. 1222, duaa026, 14 p., https://doi.org/10.1093/condor/duaa026.","productDescription":"duaa026, 14 p.","ipdsId":"IP-114598","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":456413,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duaa026","text":"Publisher Index Page"},{"id":436931,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DZZ1OB","text":"USGS data release","linkHelpText":"Arctic Shorebird Population Model"},{"id":375919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1222","noUsgsAuthors":false,"publicationDate":"2020-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":213770,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":791464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lanctot, Richard B.","contributorId":77879,"corporation":false,"usgs":false,"family":"Lanctot","given":"Richard B.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":791470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Stephen C.","contributorId":38457,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":791471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gates, H. River","contributorId":84256,"corporation":false,"usgs":true,"family":"Gates","given":"H. River","affiliations":[],"preferred":false,"id":791472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bêty, Joël","contributorId":169335,"corporation":false,"usgs":false,"family":"Bêty","given":"Joël","affiliations":[],"preferred":false,"id":791473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boldenow, Megan L.","contributorId":203662,"corporation":false,"usgs":false,"family":"Boldenow","given":"Megan","email":"","middleInitial":"L.","affiliations":[{"id":36677,"text":"Department of Biology and Wildlife, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":791474,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brook, Rodney W.","contributorId":92083,"corporation":false,"usgs":false,"family":"Brook","given":"Rodney","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":791475,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brown, Glen S.","contributorId":216260,"corporation":false,"usgs":false,"family":"Brown","given":"Glen","email":"","middleInitial":"S.","affiliations":[{"id":39382,"text":"Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":791476,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"English, Willow B.","contributorId":169341,"corporation":false,"usgs":false,"family":"English","given":"Willow","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":791477,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Flemming, Scott A.","contributorId":207034,"corporation":false,"usgs":false,"family":"Flemming","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":791478,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Franks, Samantha E.","contributorId":92979,"corporation":false,"usgs":true,"family":"Franks","given":"Samantha E.","affiliations":[],"preferred":false,"id":791479,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gilchrist, H. Grant","contributorId":177911,"corporation":false,"usgs":false,"family":"Gilchrist","given":"H.","email":"","middleInitial":"Grant","affiliations":[],"preferred":false,"id":791480,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Giroux, Marie-Andree","contributorId":169343,"corporation":false,"usgs":false,"family":"Giroux","given":"Marie-Andree","email":"","affiliations":[],"preferred":false,"id":791481,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Johnson, Andrew C.","contributorId":169346,"corporation":false,"usgs":false,"family":"Johnson","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":true,"id":791482,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Kendall, Steve","contributorId":213517,"corporation":false,"usgs":false,"family":"Kendall","given":"Steve","affiliations":[],"preferred":false,"id":791483,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Kennedy, Lisa V.","contributorId":201905,"corporation":false,"usgs":false,"family":"Kennedy","given":"Lisa","email":"","middleInitial":"V.","affiliations":[{"id":36284,"text":"Western Ontario University, London, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":791484,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Koloski, Laura","contributorId":203665,"corporation":false,"usgs":false,"family":"Koloski","given":"Laura","email":"","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":791485,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kwon, 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proposal, which does not adequately consider the lessons learnt from the 2020 Aichi Biodiversity Targets. Whilst having a single simple overarching target is appealing, we believe a positively-framed target will garner support, rather than one that aims to, at best, limit negative impacts. The Convention on Biological Diversity’s zero draft states that future targets should be clear, consistent and SMART (Specific, Measurable, Achievable, Relevant and Timely). Extinction is problematic as a standalone target: it can take decades to demonstrate and therefore cannot be measured over a relevant time-period, and is biased towards terrestrial vertebrates. The proposal is not scalable across nations, nor is it equitable,one of the key aspirations of the zero draft. Many industrialised countries are unlikely to find the targets challenging because their most vulnerable species have largely gone extinct; tropical species-rich countries, where much biodiversity is yet to be catalogued, will find the targets demanding and unachievable in the short- or medium-term. Despite the authors’ statement to the contrary, species extinction is not necessarily relevant to other aspects of biodiversity, such as ecosystems or genetic diversity. A species may be reduced to a small fraction of its former extent without going extinct. However, its ecosystem will be altered, and its contribution to ecosystem functions and the socio-economic benefits it provided will be lost. The focus on extinction is not novel and has not been particularly successful to date, as demonstrated by the decline of emblematic species such as rhinoceroses. Alternatively, composite indicators can be used to capture biodiversity’s three fundamental components (ecosystems, species and genetic diversity). In conclusion, we cannot support a target that fails to represent the diversity in biodiversity and, in the authors’ words, could be met despite “wholesale and damaging changes to life on Earth.”","language":"English","publisher":"AAAS","doi":"10.1126/science.aba6592","usgsCitation":"O'Brien, D., Hunter, M., Breed, M., Bertola, L., Ogden, R., Palma da Silva, C., Paz-Vinas, I., Segelbacher, G., Hoban, S.M., and Jaffe, R., 2020, Proposed species extinction target fails to capture the diversity in biodiversity: Science, v. 368, no. 6496, p. 1193-1195, https://doi.org/10.1126/science.aba6592.","productDescription":"3 p.","startPage":"1193","endPage":"1195","ipdsId":"IP-120746","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456416,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://discovery.ucl.ac.uk/id/eprint/10099553/","text":"External Repository"},{"id":377939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"368","issue":"6496","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Brien, David","contributorId":192192,"corporation":false,"usgs":false,"family":"O'Brien","given":"David","affiliations":[],"preferred":false,"id":797386,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":207584,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":797387,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breed, Martin","contributorId":239609,"corporation":false,"usgs":false,"family":"Breed","given":"Martin","affiliations":[{"id":47928,"text":"College of Science and Engineering, Flinders University","active":true,"usgs":false}],"preferred":false,"id":797388,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bertola, Laura","contributorId":239610,"corporation":false,"usgs":false,"family":"Bertola","given":"Laura","affiliations":[{"id":38178,"text":"City College of New York","active":true,"usgs":false}],"preferred":false,"id":797389,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ogden, Rob","contributorId":239611,"corporation":false,"usgs":false,"family":"Ogden","given":"Rob","email":"","affiliations":[{"id":47931,"text":"Royal (Dick) School of Veterinary Studies & the Roslin Institute, University of Edinburgh","active":true,"usgs":false}],"preferred":false,"id":797390,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Palma da Silva, Clarisse","contributorId":239613,"corporation":false,"usgs":false,"family":"Palma da Silva","given":"Clarisse","email":"","affiliations":[{"id":47933,"text":"Departamento de Biologia Vegetal, Instituto de Biologia, Universidade Estadual de Campinas – Unicamp","active":true,"usgs":false}],"preferred":false,"id":797392,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Paz-Vinas, Ivan","contributorId":239614,"corporation":false,"usgs":false,"family":"Paz-Vinas","given":"Ivan","email":"","affiliations":[{"id":47934,"text":"Laboratoire Ecologie Fonctionnelle et Environnement, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":797393,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Segelbacher, Gernot","contributorId":206584,"corporation":false,"usgs":false,"family":"Segelbacher","given":"Gernot","email":"","affiliations":[{"id":37345,"text":"University of Freiburg, Germany","active":true,"usgs":false}],"preferred":false,"id":797394,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hoban, Sean M. 0000-0002-0348-8449","orcid":"https://orcid.org/0000-0002-0348-8449","contributorId":206582,"corporation":false,"usgs":false,"family":"Hoban","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":37343,"text":"The Morton Arboretum","active":true,"usgs":false}],"preferred":false,"id":797395,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jaffe, Rodolfo","contributorId":239612,"corporation":false,"usgs":false,"family":"Jaffe","given":"Rodolfo","email":"","affiliations":[{"id":47932,"text":"Instituto Tecnológico Vale; Department of Ecology, University of São Paulo","active":true,"usgs":false}],"preferred":false,"id":797391,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70213314,"text":"70213314 - 2020 - Historical museum collections and contemporary population studies implicate roads and introduced predatory bullfrogs in the decline of western pond turtles","interactions":[],"lastModifiedDate":"2020-09-17T15:59:49.96803","indexId":"70213314","displayToPublicDate":"2020-06-12T10:46:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Historical museum collections and contemporary population studies implicate roads and introduced predatory bullfrogs in the decline of western pond turtles","docAbstract":"The western pond turtle (WPT), recently separated into two paripatrically distributed species (Emys pallida and Emys marmorata), is experiencing significant reductions in its range and population size. In addition to habitat loss, two potential causes of decline are female-biased road mortality and high juvenile mortality from non-native predatory bullfrogs (Rana catesbeiana). However, quantitative analyses of these threats have never been conducted for either species of WPT. We used a combination of historical museum samples and published and unpublished field studies shared with us through personal communications with WPT field researchers (B. Shaffer, P. Scott, R. Fisher, C. Brown, R. Dagit, L. Patterson, T. Engstrom, 2019, personal communications) to quantify the effect of roads and bullfrogs on WPT populations along the west coast of the United States. Both species of WPT shift toward increasingly male biased museum collections over the last century, a trend consistent with increasing, female-biased road mortality. Recent WPT population studies revealed that road density and proximity were significantly associated with increasingly male-biased sex ratios, further suggesting female-biased road mortality. The mean body size of museum collections of E. marmorata, but not E. pallida, has increased over the last 100 years, consistent with reduced recruitment and aging populations that could be driven by invasive predators. Contemporary WPT population sites that co-occur with bullfrogs had significantly greater average body sizes than population sites without bullfrogs, suggesting strong bullfrog predation on small WPT hatchlings and juveniles. Overall, our findings indicate that both species of WPT face demographic challenges which would have been difficult to document without the use of both historical data from natural history collections and contemporary demographic field data. Although correlational, our analyses suggest that female-biased road mortality and predation on small turtles by non-native bullfrogs are occurring, and that conservation strategies reducing both may be important for WPT recovery.
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These data also contain valuable information concerning dens, nests, roosts, and other central places that are often associated with important life history events and may exhibit unique characteristics; however, using satellite telemetry data to study central places is complicated by common nuances like locational error and animal movement. We coupled a novel modeling framework that accounts for these nuances with an Argos satellite telemetry dataset to examine the spatiotemporal behavior associated with harbor seal haul-out sites on Kodiak Island, Alaska, USA. The methodology incorporates an observation model that accommodates multiple sources of uncertainty in telemetry data and a flexible Bayesian nonparametric model to uncover latent clustering in the telemetry locations. We also contribute extensions to examine the effect of covariates on site selection and to obtain population-level inference concerning central place use. Harbor seal haul-out sites generally occurred in inlets and bays, areas that are isolated from the open water of the Gulf of Alaska. Most individuals selected haul-out sites that were protected from wave exposure. The effects of bathymetry and shoreline complexity on haul-out site selection were variable among individual seals, as were the effects of time of day, time since low tide, and day of year on temporal patterns of haul-out use. As repositories of satellite telemetry data on a wide variety of species accumulate, so do opportunities for using this information to learn about the locations of central places, as well as the temporal patterns in their use. The model-based approach we describe offers a practical and rigorous means for gaining insight concerning these sensitive locations, knowledge of which is important for the effective management and conservation of many species.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3123","usgsCitation":"Brost, B.M., Hooten, M., and Small, R., 2020, Model-based clustering reveals patterns in central place use of a marine top predator: Ecosphere, e03123, 15 p., https://doi.org/10.1002/ecs2.3123.","productDescription":"e03123, 15 p.","ipdsId":"IP-079248","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":456420,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3123","text":"Publisher Index Page"},{"id":394975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kodiak Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.171142578125,\n 56.32262930069559\n ],\n [\n -151.885986328125,\n 57.76865857271793\n ],\n [\n -152.479248046875,\n 58.019737000187305\n ],\n [\n -153.74267578125,\n 58.04300405858762\n ],\n [\n -155.115966796875,\n 57.320589769167135\n ],\n [\n -154.171142578125,\n 56.32262930069559\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Brost, Brian M.","contributorId":272252,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":831864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":831863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Small, Robert J.","contributorId":272253,"corporation":false,"usgs":false,"family":"Small","given":"Robert J.","affiliations":[{"id":56329,"text":"akfg","active":true,"usgs":false}],"preferred":false,"id":831865,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211234,"text":"70211234 - 2020 - Book review of \"Tsunami Propagation in Tidal Rivers\", by Elena Tolkova","interactions":[],"lastModifiedDate":"2020-07-21T15:00:14.144557","indexId":"70211234","displayToPublicDate":"2020-06-12T09:59:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Book review of \"Tsunami Propagation in Tidal Rivers\", by Elena Tolkova","docAbstract":"No abstract available.
","language":"English","publisher":"Springer","doi":"10.1007/s00024-020-02524-x","usgsCitation":"Geist, E.L., 2020, Book review of \"Tsunami Propagation in Tidal Rivers\", by Elena Tolkova: Pure and Applied Geophysics, v. 177, p. 3057-3058, https://doi.org/10.1007/s00024-020-02524-x.","productDescription":"2 p.","startPage":"3057","endPage":"3058","ipdsId":"IP-117481","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":376535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"177","noUsgsAuthors":false,"publicationDate":"2020-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":793346,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70210718,"text":"70210718 - 2020 - Regional patterns in hydrologic response, a new three-component metric for hydrograph analysis and implications for ecohydrology, Northwest Volcanic Aquifer Study Area, USA","interactions":[],"lastModifiedDate":"2020-08-06T19:30:06.543616","indexId":"70210718","displayToPublicDate":"2020-06-12T09:48:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Regional patterns in hydrologic response, a new three-component metric for hydrograph analysis and implications for ecohydrology, Northwest Volcanic Aquifer Study Area, USA","docAbstract":"Oregon, California, Idaho, Nevada and Utah
Spatial patterns of hydrologic response were examined for the Northwest Volcanic Aquifer Study Area (NVASA). The utility of established hydrograph-separation methods for assessing hydrologic response in permeable volcanic terranes was assessed and a new three-component metric for hydrograph analysis was developed. The new metric, which partitions streamflow into subcomponents defined by the timescales of hydrologic response (e.g., fast-runoff, intermediate-interflow and slow-baseflow), was used to gain a fundamental understanding of the regional hydrology, investigate sub-regional differences, influencing factors, and ecohydrological implications.
The combined effects of NVASA’s physiography, climate and geology create a strongly coupled surface-groundwater system that produces copious baseflow and limited quantities of runoff and interflow. Patterns of hydrologic response are influenced by the type and rate of precipitation and permeability of the underlying geology. Under variable precipitation conditions the hydrologic response of volcanic terranes with similar permeability and subsurface-storage capacity can be significantly different. From a water management and ecohydrology perspective, understanding regional patterns of hydrologic response and sub-regional differences is fundamental. Results indicate that minimum-flow methods provide the most conservative estimate of baseflow and may be the most robust for filtering out snowmelt bias in baseflow estimates. Baseflow contributes ∼75% of the perennial streamflow across the NVASA and represents a critical component of the regional water supply that provides critical cold-water habitat.
Karst is a landscape formed from the dissolution of soluble rock or rock containing minerals that are easily dissolved from within the rock. The landscape is characterized by sinkholes, caves, losing streams, springs, and underground drainage systems, which rapidly move water through the karst. The two forms of karst in New York State include carbonate karst, which forms in carbonate rock (limestone, marble, and dolostone), and evaporite karst, which forms in rock that contains the evaporite minerals gypsum and halite.
Past and recent studies of karst across the State have shown that areas of focused recharge in karstic carbonate rock allow contaminants to enter aquifer systems with little attenuation. Focused areas of recharge need to be identified to help prevent such contamination from sources on or adjacent to the karst. The New York State Departments of Environmental Conservation and Health are collaborating with the agricultural community to make farmers and farm-planning advisors more aware of karst and how to manage daily farming activities to reduce their impact on surface water and groundwater resources, especially in karst areas. There is also a need to make regulators, planners, and the general public aware of New York’s karst resources and to properly protect and manage these resources to protect the quality of groundwater and surface water that can flow into, through, and from karst bedrock.
Using publicly available geospatial data, karst bedrock and closed depressions over or near karst rock were identified across New York. Carbonate, evaporite, and marble geologic units were selected from a statewide 1:250,000-scale bedrock geology dataset. The selected geologic units were intersected with 7.5-minute quadrangle maps to define the study area.
The U.S. Geological Survey has compiled an inventory of closed depressions from statewide digital contour data, scanned 7.5-minute topographic maps known as a digital raster graphics, and light detection and ranging (lidar) digital elevation models. Analysis of the data resulted in the identification of 5,023 closed depressions statewide. The inventory was conducted to eliminate duplication of results from analysis of the three data sources. A series of overlay analyses was conducted using the closed depressions and thematic data known to be key factors in determining the probability of a closed depression contributing to focused groundwater recharge; the thematic data include bedrock geology, soil type, soil infiltration rate, and land cover.
Though the extent of karst development is important in understanding the interaction between surface water and groundwater in karst terrains, some of the worst cases of groundwater contamination in karst can occur where only minor karst features might be present. The presence of karst—be it a short section of a solutioned fracture or an extensive cave system—requires careful consideration, forward-looking environmental planning, and consistent water-quality protection to preserve New York State’s water resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205030","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Kappel, W.M., Reddy, J.E., and Root, J.C., 2020, Statewide assessment of karst aquifers in New York with an inventory of closed-depression and focused-recharge features: U.S. Geological Survey Scientific Investigations Report 2020–5030, 74 p., https://doi.org/10.3133/sir20205030.","productDescription":"Report: viii, 74 p.","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090019","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":375401,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5030/coverthb.jpg"},{"id":375404,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGN5IJ","text":"USGS data release","linkHelpText":"Data for statewide assessment of New York’s karst aquifers with an inventory of closed-depression and focused-recharge features"},{"id":375534,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5030/sir20205030.pdf","text":"Report","size":"19.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5030"},{"id":375482,"rank":2,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5030/sir20205030_table1.pdf","text":"Table 1","size":"140 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Stratigraphic column of New York State bedrock indicating those units in which karst features might be present"}],"country":"United States","state":"New 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York\",\"nation\":\"USA \"}}]}","contact":"Director, New York Water Science Center
U.S. Geological Survey
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Troy, NY 12180–8349
Hydraulic fracturing (HF) is a technique that is used for extracting petroleum resources from impermeable host rocks. In this process, fluid injected under high pressure causes fractures to propagate. This technique has been transformative for the hydrocarbon industry, unlocking otherwise stranded resources; however, environmental concerns make HF controversial. One concern is HF‐induced seismicity, since fluids driven under high pressure also have the potential to reactivate faults. Controversy has inevitably followed these HF‐induced earthquakes, with economic and human losses from ground shaking at one extreme and moratoriums on resource development at the other. Here, we review the state of knowledge of this category of induced seismicity. We first cover essential background information on HF along with an overview of published induced earthquake cases to date. Expanding on this, we synthesize the common themes and interpret the origin of these commonalities, which include recurrent earthquake swarms, proximity to well bore, rapid response to stimulation, and a paucity of reported cases. Next, we discuss the unanswered questions that naturally arise from these commonalities, leading to potential research themes: consistent recognition of cases, proposed triggering mechanisms, geologically susceptible conditions, identification of operational controls, effective mitigation efforts, and science‐informed regulatory management. HF‐induced seismicity provides a unique opportunity to better understand and manage earthquake rupture processes; overall, understanding HF‐induced earthquakes is important in order to avoid extreme reactions in either direction.