{"pageNumber":"576","pageRowStart":"14375","pageSize":"25","recordCount":184660,"records":[{"id":70215714,"text":"70215714 - 2020 - Modeling population dynamics with count data","interactions":[],"lastModifiedDate":"2020-10-29T11:44:51.667646","indexId":"70215714","displayToPublicDate":"2020-10-19T08:53:41","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"2","title":"Modeling population dynamics with count data","docAbstract":"In this chapter, we describe models of open populations that are subject to change over time due to additions and subtractions. Additions may be in the form of recruitment and immigration, and subtractions may be in the form of mortality, emigration, or both. Conceptually, these models are described by the Birth-Immigration-Death-Emigration (BIDE) model of population dynamics (Conroy and Carroll, 2009). In most cases, we will not formally distinguish between the two types of additions or of subtractions (birth/immigration or death/emigration), although sometimes this may be possible depending on the timescale of the study, spatial structure, and specific model assumptions (Zhao et al., 2017; see Section 2.10). In addition, distinguishing the different dynamic processes may also become possible in the presence of auxiliary data on some demographic rates, in the context of integrated population models (IPMs, Besbeas et al., 2002; see also Chapter 10). One type of open model, which allows for temporal variation in abundance but not explicit dynamics, is the simple model of temporary emigration (Kendall et al., 1997), which supposes that population size Nt changes randomly among open (primary) periods t, as a Binomial realization from some larger superpopulation. Over short timescales, this simple model may provide a sensible description of variation in population size over time.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Applied hierarchical modeling in ecology: Analysis of distribution, abundance and species richness in R and BUGS","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Academic Press","usgsCitation":"Kery, M., and Royle, A., 2020, Modeling population dynamics with count data, chap. 2 <i>of</i> Applied hierarchical modeling in ecology: Analysis of distribution, abundance and species richness in R and BUGS, v. 2, p. 65-156.","productDescription":"92 p.","startPage":"65","endPage":"156","ipdsId":"IP-101801","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":379903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379844,"type":{"id":15,"text":"Index Page"},"url":"https://www.elsevier.com/books/applied-hierarchical-modeling-in-ecology-analysis-of-distribution-abundance-and-species-richness-in-r-and-bugs/kery/978-0-12-809585-0"}],"volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kery, Marc","contributorId":38680,"corporation":false,"usgs":true,"family":"Kery","given":"Marc","affiliations":[],"preferred":false,"id":803279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":803186,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215717,"text":"70215717 - 2020 - Modeling false positives","interactions":[],"lastModifiedDate":"2020-10-29T11:45:30.1053","indexId":"70215717","displayToPublicDate":"2020-10-19T08:48:46","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"Modeling false positives","docAbstract":"Many of the models we are concerned with included explicit descriptions of false negative errors. However, false positive errors can also be commin in practice, especially in citizen science applications where observer skill is highly variable. In addition, new methods which determine detection based on statistical classification or machine learning methods are also prone to false positive errors which must be accounted for. \n An early treatment of the false positive detection problem by Royle & Link (2006) recognized that false positive errors can be accommodated by a mixture model for detection probability: one value of detection at occupied sites and another non-zero value at unoccupied sites. This model has been extended greatly in recent years to include more informative data about false positives including validation or confirmation data (Miller et al. 2011) and multiple detection methods, among others.  \n A new frontier for the application of false positives models lies in the use of modern technologies such as bioacoustics for efficient automated monitoring. For these technologies to realize their promise there must be improvements in automated processing of the vast quantities of output produced. Statistical classification methods (machine learning) are fallible and necessarily produce false positive detections. Therefore models which account for this process are necessary (Chambert et al. 2017). It stands to reason that false positives will need to be accounted for in other new technologies that rely on automated digital processing, including eDNA, genetic barcoding, and automated detection in remote camera studies.\n We devise a new occupancy model that integrates data from bioacoustics sampling with an occupancy model. This integrated model allows occupancy probability to inform species classification of samples and vice versa  bioacoustics detection data inform occupancy. We provide a proof of concept for this new model in this chapter. \n As the core hierarchical model for the false positives models covered in this chapter are just ordinary occupancy models, extension of the ideas to open systems poses no technical challenges. We provide a suite of illustrations of these extensions. \n Perhaps the most prominent mechanism that leads to false positive errors it he mis-classification of species detections, or the confusion of one species for another. Very little work has been done on developing models based on this mechanistic understanding although Chambert et al. (2018) develop this idea as a 2-species occupancy model with error. We believe one important area of future research is to extend these ideas to truly multi-species systems.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Applied hierarchical modeling in ecology: Analysis of distribution, abundance and species richness in R and BUGS","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Academic Press","usgsCitation":"Kery, M., and Royle, A., 2020, Modeling false positives, chap. 7 <i>of</i> Applied hierarchical modeling in ecology: Analysis of distribution, abundance and species richness in R and BUGS, v. 2, p. 401-454.","productDescription":"54 p.","startPage":"401","endPage":"454","ipdsId":"IP-104271","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":379868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379846,"type":{"id":15,"text":"Index Page"},"url":"https://www.elsevier.com/books/applied-hierarchical-modeling-in-ecology-analysis-of-distribution-abundance-and-species-richness-in-r-and-bugs/kery/978-0-12-809585-0"}],"volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kery, Marc","contributorId":168361,"corporation":false,"usgs":false,"family":"Kery","given":"Marc","affiliations":[{"id":12551,"text":"Swiss Ornithological Institute, Sempach, Switzerland","active":true,"usgs":false}],"preferred":false,"id":803278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":803191,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70216466,"text":"70216466 - 2020 - Diurnal timing of nonmigratory movement by birds: The importance of foraging spatial scales","interactions":[],"lastModifiedDate":"2020-12-29T21:55:39.324174","indexId":"70216466","displayToPublicDate":"2020-10-19T08:27:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Diurnal timing of nonmigratory movement by birds: The importance of foraging spatial scales","docAbstract":"<p>Timing of activity can reveal an organism's efforts to optimize foraging either by minimizing energy loss through passive movement or by maximizing energetic gain through foraging. Here, we assess whether signals of either of these strategies are detectable in the timing of activity of daily, local movements by birds. We compare the similarities of timing of movement activity among species using six temporal variables: start of activity relative to sunrise, end of activity relative to sunset, relative speed at midday, number of movement bouts, bout duration, and proportion of active daytime hours. We test for the influence of flight mode and foraging habitat on the timing of movement activity across avian guilds. We used 64570 days of GPS movement data collected between 2002 and 2019 for local (non‐migratory) movements of 991 birds from 49 species, representing 14 orders. Dissimilarity among daily activity patterns was best explained by flight mode. Terrestrial soaring birds began activity later and stopped activity earlier than pelagic soaring or flapping birds. Broad‐scale foraging habitat explained less of the clustering patterns because of divergent timing of active periods of pelagic surface and diving foragers. Among pelagic birds, surface foragers were active throughout the day while diving foragers matched their active hours more closely to daylight hours. Pelagic surface foragers also had the greatest daily foraging distances, which was consistent with their daytime activity patterns. This study demonstrates that flight mode and foraging habitat influence temporal patterns of daily movement activity of birds.</p>","language":"English","publisher":"Wiley","doi":"10.1111/jav.02612","usgsCitation":"Mallon, J.M., Tucker, M.A., Beard, A., Bierregaard, R.O., Bildstein, K.L., Böhning-Gaese, K., Brzorad, J.N., Buechley, E., Bustamante, J., Carrapato, C., Castillo-Guerrero, J.A., Clingham, E., Desholm, M., DeSorbo, C.R., Domenech, R., Douglas, H., Duriez, O., Enggist, P., Farwig, N., Fiedler, W., Gagliardo, A., García‐Ripollés, C., Gil Gallus, J.A., Gilmour, M., Harel, R., Harrison, A., Henry, L., Katzner, T., Kays, R., Kleyheeg, E., Limiñana, R., Lopez-Lopez, P., Lucia, G., Maccarone, A., Mallia, E., Mellone, U., Mojica, E., Nathan, R., Newman, S., Oppel, S., Orchan, Y., Prosser, D.J., Riley, H., Rösner, S., Schabo, D.G., Schulz, H., Shaffer, S.A., Shreading, A., Silva, J., Sim, J., Skov, H., Spiegel, O., Stuber, M.J., Takekawa, J.Y., Urios, V., Vidal-Mateo, J., Warner, K., Watts, B.D., Weber, N., Weber, S., Wikelski, M., Zydelis, R., Mueller, T., and Fagan, W., 2020, Diurnal timing of nonmigratory movement by birds: The importance of foraging spatial scales: Journal of Avian Biology, v. 51, no. 12, e02612, 11 p., https://doi.org/10.1111/jav.02612.","productDescription":"e02612, 11 p.","ipdsId":"IP-115942","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":455018,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/jav.02612","text":"External Repository"},{"id":380648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Mallon, Julie 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Paulo","contributorId":245114,"corporation":false,"usgs":false,"family":"Silva","given":"João Paulo","affiliations":[],"preferred":false,"id":805355,"contributorType":{"id":1,"text":"Authors"},"rank":49},{"text":"Sim, Jolene","contributorId":245115,"corporation":false,"usgs":false,"family":"Sim","given":"Jolene","email":"","affiliations":[],"preferred":false,"id":805356,"contributorType":{"id":1,"text":"Authors"},"rank":50},{"text":"Skov, Henrik","contributorId":245116,"corporation":false,"usgs":false,"family":"Skov","given":"Henrik","email":"","affiliations":[],"preferred":false,"id":805357,"contributorType":{"id":1,"text":"Authors"},"rank":51},{"text":"Spiegel, Orr","contributorId":205125,"corporation":false,"usgs":false,"family":"Spiegel","given":"Orr","email":"","affiliations":[],"preferred":false,"id":805358,"contributorType":{"id":1,"text":"Authors"},"rank":52},{"text":"Stuber, Matthew J.","contributorId":213765,"corporation":false,"usgs":false,"family":"Stuber","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":805359,"contributorType":{"id":1,"text":"Authors"},"rank":53},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":196611,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":805360,"contributorType":{"id":1,"text":"Authors"},"rank":54},{"text":"Urios, Vicente","contributorId":220945,"corporation":false,"usgs":false,"family":"Urios","given":"Vicente","email":"","affiliations":[],"preferred":false,"id":805361,"contributorType":{"id":1,"text":"Authors"},"rank":55},{"text":"Vidal-Mateo, Javier","contributorId":245117,"corporation":false,"usgs":false,"family":"Vidal-Mateo","given":"Javier","email":"","affiliations":[],"preferred":false,"id":805362,"contributorType":{"id":1,"text":"Authors"},"rank":56},{"text":"Warner, Kevin","contributorId":245118,"corporation":false,"usgs":false,"family":"Warner","given":"Kevin","affiliations":[],"preferred":false,"id":805363,"contributorType":{"id":1,"text":"Authors"},"rank":57},{"text":"Watts, Bryan D.","contributorId":112075,"corporation":false,"usgs":true,"family":"Watts","given":"Bryan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":805364,"contributorType":{"id":1,"text":"Authors"},"rank":58},{"text":"Weber, Nicola","contributorId":245119,"corporation":false,"usgs":false,"family":"Weber","given":"Nicola","email":"","affiliations":[],"preferred":false,"id":805365,"contributorType":{"id":1,"text":"Authors"},"rank":59},{"text":"Weber, Sam","contributorId":245120,"corporation":false,"usgs":false,"family":"Weber","given":"Sam","email":"","affiliations":[],"preferred":false,"id":805366,"contributorType":{"id":1,"text":"Authors"},"rank":60},{"text":"Wikelski, Martin","contributorId":76451,"corporation":false,"usgs":true,"family":"Wikelski","given":"Martin","affiliations":[],"preferred":false,"id":805367,"contributorType":{"id":1,"text":"Authors"},"rank":61},{"text":"Zydelis, Ramunas","contributorId":203738,"corporation":false,"usgs":false,"family":"Zydelis","given":"Ramunas","email":"","affiliations":[{"id":35135,"text":"DHI, Hørsholm, Denmark","active":true,"usgs":false}],"preferred":false,"id":805368,"contributorType":{"id":1,"text":"Authors"},"rank":62},{"text":"Mueller, Thomas","contributorId":91393,"corporation":false,"usgs":true,"family":"Mueller","given":"Thomas","affiliations":[],"preferred":false,"id":805369,"contributorType":{"id":1,"text":"Authors"},"rank":63},{"text":"Fagan, William F.","contributorId":108239,"corporation":false,"usgs":true,"family":"Fagan","given":"William F.","affiliations":[],"preferred":false,"id":805370,"contributorType":{"id":1,"text":"Authors"},"rank":64}]}}
,{"id":70215554,"text":"70215554 - 2020 - Modeling three-dimensional flow over spur-and-groove morphology","interactions":[],"lastModifiedDate":"2020-11-30T16:06:18.953016","indexId":"70215554","displayToPublicDate":"2020-10-19T08:24:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"Modeling three-dimensional flow over spur-and-groove morphology","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Spur-and-groove (SAG) morphology characterizes the fore reef of many coral reefs worldwide. Although the existence and geometrical properties of SAG have been well documented, an understanding of the hydrodynamics over them is limited. Here, the three-dimensional flow patterns over SAG formations, and a sensitivity of those patterns to waves, currents, and SAG geometry were characterized using the physics-based Delft3D-FLOW and SWAN models. Shore-normal shoaling waves over SAG formations were shown to drive two circulation cells: a cell on the lower fore reef with offshore flow over the spurs and onshore flow over the grooves, except near the seabed where velocities were always onshore, and a cell on the upper fore reef with offshore surface velocities and onshore bottom currents, which result in depth-averaged onshore and offshore flow over the spurs and grooves, respectively. The mechanism driving this flow results from the net of the radiation stress gradients and pressure gradient, which is balanced by the Reynolds stress gradients and bottom friction that differ over the spur and over the groove. Waves were the primary driver of variations in modelled flow over SAG, with the flow strength increasing for increasing wave heights and periods. Spur height, SAG wavelength, and the water depth at peak spur height were the dominant influences on the hydrodynamics, with spur heights directly proportional to the strength of SAG circulation cells. SAG formations with shorter SAG wavelengths only presented one circulation cell on the shallower portion of the reef, as opposed to the two circulation cells for longer SAG wavelengths. SAG formations with peak spur heights occurring in shallower water had stronger circulation than those with peak spur heights occurring in deeper water. These hydrodynamic patterns also likely affect coral and reef development through sediment and nutrient fluxes.</p></div></div><div id=\"Sec1-section\" class=\"c-article-section\"><br></div>","language":"English","publisher":"Springer","doi":"10.1007/s00338-020-02011-8","usgsCitation":"da Silva, R., Storlazzi, C., Rogers, J.S., Reyns, J., and McCall, R.T., 2020, Modeling three-dimensional flow over spur-and-groove morphology: Coral Reefs, v. 39, p. 1841-1858, https://doi.org/10.1007/s00338-020-02011-8.","productDescription":"18 p.","startPage":"1841","endPage":"1858","ipdsId":"IP-111695","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":436751,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZRJ9H8","text":"USGS data release","linkHelpText":"Database to model three-dimensional flow over coral reef spur-and-groove morphology"},{"id":379645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","noUsgsAuthors":false,"publicationDate":"2020-10-19","publicationStatus":"PW","contributors":{"authors":[{"text":"da Silva, Renan","contributorId":243607,"corporation":false,"usgs":false,"family":"da Silva","given":"Renan","affiliations":[{"id":48753,"text":"Deltares and UWA","active":true,"usgs":false}],"preferred":false,"id":802702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":229614,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rogers, Justin S.","contributorId":208527,"corporation":false,"usgs":false,"family":"Rogers","given":"Justin","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":802704,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reyns, Johan","contributorId":224304,"corporation":false,"usgs":false,"family":"Reyns","given":"Johan","email":"","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":802705,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCall, Robert T.","contributorId":148986,"corporation":false,"usgs":false,"family":"McCall","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":802706,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70215539,"text":"70215539 - 2020 - Modeling population dynamics with multinomial count data","interactions":[],"lastModifiedDate":"2020-10-22T13:01:28.905423","indexId":"70215539","displayToPublicDate":"2020-10-19T07:59:04","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"2","title":"Modeling population dynamics with multinomial count data","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Applied hierarchical modeling in ecology: Analysis of distribution, abundance and species richness in R and BUGS","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Academic Press","usgsCitation":"Royle, A., and Kery, M., 2020, Modeling population dynamics with multinomial count data, chap. 2 <i>of</i> Applied hierarchical modeling in ecology: Analysis of distribution, abundance and species richness in R and BUGS, p. 65-156.","productDescription":"92 p.","startPage":"65","endPage":"156","ipdsId":"IP-101095","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":379643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379628,"type":{"id":15,"text":"Index Page"},"url":"https://www.elsevier.com/books/applied-hierarchical-modeling-in-ecology-analysis-of-distribution-abundance-and-species-richness-in-r-and-bugs/kery/978-0-12-809585-0"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":802622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kery, Marc","contributorId":168361,"corporation":false,"usgs":false,"family":"Kery","given":"Marc","affiliations":[{"id":12551,"text":"Swiss Ornithological Institute, Sempach, Switzerland","active":true,"usgs":false}],"preferred":false,"id":802707,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70216504,"text":"70216504 - 2020 - Injection‐induced earthquakes near Milan, Kansas, controlled by Karstic Networks","interactions":[],"lastModifiedDate":"2020-11-24T13:38:00.985824","indexId":"70216504","displayToPublicDate":"2020-10-19T07:34:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Injection‐induced earthquakes near Milan, Kansas, controlled by Karstic Networks","docAbstract":"<div class=\"article-section__content en main\"><p>Induced earthquakes from waste disposal operations in otherwise tectonically stable regions significantly increases seismic hazard. It remains unclear why injections induce large earthquakes on non‐optimally oriented faults kilometers below the injection horizon, particularly since fluids are not injected under pressure, but rather poured, into the well as observed in the Milan, Kansas area. Here we propose a mechanism for induced earthquakes whereby the karstic lower Arbuckle provides the short‐circuit that establishes a tens of MPa stepwise fluid pressure increase within the basement upon arrival of the hydraulic connection to the free surface and ultimately induce slip on the deeper fault. We investigate this scenario through modeling and mechanical analysis and show that earthquakes near Milan are likely induced by large (and sudden) fluid pressure changes when the karst network links two previously isolated hydrological systems.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL088326","usgsCitation":"Joubert, C., Sohrabi, R., Rubinstein, J., Jansen, G., and Miller, S., 2020, Injection‐induced earthquakes near Milan, Kansas, controlled by Karstic Networks: Geophysical Research Letters, v. 47, no. 21, e2020GL088326, 9 p., https://doi.org/10.1029/2020GL088326.","productDescription":"e2020GL088326, 9 p.","ipdsId":"IP-104948","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":380736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","county":"Sumner County","city":"Milan","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-97.1514,37.4764],[-97.1468,37.0001],[-97.1978,36.9995],[-97.271,36.9997],[-97.4111,37.0001],[-97.4597,37.0002],[-97.4624,37.0002],[-97.5354,37.0002],[-97.7424,37.0003],[-97.802,37.0004],[-97.8041,37.3867],[-97.807,37.3867],[-97.8068,37.4746],[-97.1514,37.4764]]]},\"properties\":{\"name\":\"Sumner\",\"state\":\"KS\"}}]}","volume":"47","issue":"21","noUsgsAuthors":false,"publicationDate":"2020-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Joubert, Charlene","contributorId":245164,"corporation":false,"usgs":false,"family":"Joubert","given":"Charlene","email":"","affiliations":[{"id":49105,"text":"University of Neuchatel","active":true,"usgs":false}],"preferred":false,"id":805498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sohrabi, Reza","contributorId":245165,"corporation":false,"usgs":false,"family":"Sohrabi","given":"Reza","email":"","affiliations":[{"id":49105,"text":"University of Neuchatel","active":true,"usgs":false}],"preferred":false,"id":805499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubinstein, Justin 0000-0003-1274-6785","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":215341,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":805500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jansen, Gunnar","contributorId":245167,"corporation":false,"usgs":false,"family":"Jansen","given":"Gunnar","email":"","affiliations":[],"preferred":false,"id":805502,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Stephen A","contributorId":245166,"corporation":false,"usgs":false,"family":"Miller","given":"Stephen A","affiliations":[{"id":49105,"text":"University of Neuchatel","active":true,"usgs":false}],"preferred":false,"id":805501,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70215547,"text":"70215547 - 2020 - Application of the RSPARROW modeling tool to estimate total nitrogen sources to streams and evaluate source reduction management scenarios in the Grande River Basin, Brazil","interactions":[],"lastModifiedDate":"2020-10-22T14:32:56.742491","indexId":"70215547","displayToPublicDate":"2020-10-18T09:24:54","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":"Application of the RSPARROW modeling tool to estimate total nitrogen sources to streams and evaluate source reduction management scenarios in the Grande River Basin, Brazil","docAbstract":"<p><span>Large-domain hydrological models are increasingly needed to support water-resource assessment and management in large river basins. Here, we describe results for the first Brazilian application of the SPAtially Referenced Regression On Watershed attributes (SPARROW) model using a new open-source modeling and interactive decision support system tool (RSPARROW) to quantify the origin, flux, and fate of total nitrogen (TN) in two sub-basins of the Grande River Basin (GRB; 43,000 km</span><sup>2</sup><span>). Land under cultivation for sugar cane, urban land, and point source inputs from wastewater treatment plants was estimated to each contribute approximately 30% of the TN load at the outlet, with pasture land contributing about 10% of the load. Hypothetical assessments of wastewater treatment plant upgrades and the building of new facilities that could treat currently untreated urban runoff suggest that these management actions could potentially reduce loading at the outlet by as much as 20–25%. This study highlights the ability of SPARROW and the RSPARROW mapping tool to assist with the development and evaluation of management actions aimed at reducing nutrient pollution and eutrophication. The freely available RSPARROW modeling tool provides new opportunities to improve understanding of the sources, delivery, and transport of water-quality contaminants in watersheds throughout the world.&nbsp;</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w12102911","usgsCitation":"Miller, M., de Souza, M.L., Alexander, R.B., Gorman Sanisaca, L.E., de Amorim Teixeira, A., and Appling, A.P., 2020, Application of the RSPARROW modeling tool to estimate total nitrogen sources to streams and evaluate source reduction management scenarios in the Grande River Basin, Brazil: Water, v. 12, no. 10, 2911, 20 p., https://doi.org/10.3390/w12102911.","productDescription":"2911, 20 p.","ipdsId":"IP-122604","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":455023,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12102911","text":"Publisher Index Page"},{"id":436752,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FZV0Z0","text":"USGS data release","linkHelpText":"RSPARROW Model Archive Files for the Grande River Basin TN SPARROW Model"},{"id":379649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Grande River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -50.95458984374999,\n              -20.324023603422507\n            ],\n            [\n              -49.32861328125,\n              -21.46329344189928\n            ],\n            [\n              -48.284912109375,\n              -22.451648819126202\n            ],\n            [\n              -46.73583984375,\n              -23.29181053244191\n            ],\n            [\n              -45.37353515625,\n              -22.61401087437028\n            ],\n            [\n              -44.05517578124999,\n              -21.881889807629257\n            ],\n            [\n              -43.5498046875,\n              -21.125497636606266\n            ],\n            [\n              -45.736083984375,\n              -20.33432561683554\n            ],\n            [\n              -46.35131835937499,\n              -20.478481600090554\n            ],\n            [\n              -46.966552734375,\n              -20.014645445341355\n            ],\n            [\n              -47.647705078125,\n              -19.797717490704724\n            ],\n            [\n              -48.944091796875,\n              -19.9526963975442\n            ],\n            [\n              -49.32861328125,\n              -19.652934210612436\n            ],\n            [\n              -50.28442382812499,\n              -19.425153718960143\n            ],\n            [\n              -50.86669921875,\n              -19.756364230752375\n            ],\n            [\n              -50.95458984374999,\n              -20.324023603422507\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":802665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Souza, Marcelo L","contributorId":243598,"corporation":false,"usgs":false,"family":"de Souza","given":"Marcelo","email":"","middleInitial":"L","affiliations":[{"id":48748,"text":"Brazilian National Water and Sanitation Agency","active":true,"usgs":false}],"preferred":false,"id":802666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Richard B 0000-0001-9166-0626","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":243599,"corporation":false,"usgs":false,"family":"Alexander","given":"Richard","email":"","middleInitial":"B","affiliations":[{"id":38108,"text":"NA","active":true,"usgs":false}],"preferred":false,"id":802667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorman Sanisaca, Lillian E. 0000-0003-1711-3864","orcid":"https://orcid.org/0000-0003-1711-3864","contributorId":210381,"corporation":false,"usgs":true,"family":"Gorman Sanisaca","given":"Lillian","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Amorim Teixeira, Alexandre","contributorId":243600,"corporation":false,"usgs":false,"family":"de Amorim Teixeira","given":"Alexandre","email":"","affiliations":[{"id":48748,"text":"Brazilian National Water and Sanitation Agency","active":true,"usgs":false}],"preferred":false,"id":802669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":802670,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70227625,"text":"70227625 - 2020 - Estimating population-specific predation effects on Chinook salmon via data integration","interactions":[],"lastModifiedDate":"2022-01-21T14:54:34.2629","indexId":"70227625","displayToPublicDate":"2020-10-18T08:33:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating population-specific predation effects on Chinook salmon via data integration","docAbstract":"<ol class=\"\"><li>Recent success in the conservation of many marine mammals has resulted in new management challenges due to increasing conflict with fisheries. Increasing predation by pinnipeds on threatened salmon is of particular concern. Seemingly, pinniped conservation is now in conflict with the recovery of threatened salmon, creating a dilemma for managers.</li><li>We use the Lower Columbia River as a case study for examining the relationship between seasonal California sea lion<span>&nbsp;</span><i>Zalophus californianus</i><span>&nbsp;</span>abundance and survival of threatened salmon. To quantify mortality associated with increasing sea lion abundance, we examined the effect of seasonal sea lion abundance on adult Chinook salmon<span>&nbsp;</span><i>Oncorhynchus tshawytscha</i><span>&nbsp;</span>survival during migrations through the Lower Columbia River. We integrated data on survival with data on population-specific migration timing, allowing quantification of the relationship between sea lion abundance and survival in 18 populations of spring–summer Chinook salmon listed as Threatened or Endangered under the U.S. Endangered Species Act.</li><li>Of the 18 populations examined, earlier migrating populations experienced lower survival in association with increased exposure to higher sea lion abundance. We estimated that in years with high sea lion abundance, the nine earliest-migrating populations experienced an additional 21.1% (95% CI&nbsp;=&nbsp;16.3–26.1) mortality compared to years with baseline sea lion abundance, while the nine latest migrating populations experienced an additional 10.1% (7.5–13.0).</li><li><i>Synthesis and applications</i>. Integrating datasets on seasonal survival and migration timing made it possible for us to estimate population-specific mortality associated with increased sea lion abundance in the Lower Columbia River. This information could not be produced from any one dataset, highlighting the utility of data integration approaches. The mortality experienced by early migrating Chinook salmon suggests the potential for demographic and evolutionary consequences. Management actions such as hazing, relocating, or removing individuals that are frequent predators on salmon have been proposed. Identifying the management actions that will allow for socially and legally acceptable trade-offs between multiple conservation and other social values will be facilitated by development of explicit multi-species management frameworks. Continued monitoring will help to reduce the substantial uncertainty about the effect of pinnipeds on salmon and the predicted outcomes of alternative management actions.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.13772","usgsCitation":"Sorel, M.H., Zabel, R.W., Johnson, D.S., Wargo Rub, A., and Converse, S.J., 2020, Estimating population-specific predation effects on Chinook salmon via data integration: Journal of Applied Ecology, v. 58, no. 2, p. 372-381, https://doi.org/10.1111/1365-2664.13772.","productDescription":"10 p.","startPage":"372","endPage":"381","ipdsId":"IP-116070","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":455024,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13772","text":"Publisher Index Page"},{"id":394656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394655,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.5281/zenodo.4037280"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Columbia River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.67584228515625,\n              46.14368574598159\n            ],\n            [\n              -123.4808349609375,\n              46.14368574598159\n            ],\n            [\n              -123.4808349609375,\n              46.31089291474789\n            ],\n            [\n              -123.67584228515625,\n              46.31089291474789\n            ],\n            [\n              -123.67584228515625,\n              46.14368574598159\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"58","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-10-18","publicationStatus":"PW","contributors":{"editors":[{"text":"McCallum, Hamish","contributorId":174852,"corporation":false,"usgs":false,"family":"McCallum","given":"Hamish","affiliations":[],"preferred":false,"id":831409,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Sorel, Mark H.","contributorId":171739,"corporation":false,"usgs":false,"family":"Sorel","given":"Mark","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":831434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zabel, Richard W.","contributorId":272049,"corporation":false,"usgs":false,"family":"Zabel","given":"Richard","email":"","middleInitial":"W.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":831406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Devin S.","contributorId":167773,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin","email":"","middleInitial":"S.","affiliations":[{"id":24829,"text":"National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service, NOAA, Seattle, Washington","active":true,"usgs":false}],"preferred":false,"id":831435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wargo Rub, A. 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,{"id":70208918,"text":"cir1464 - 2020 - Estimated groundwater withdrawals from principal aquifers in the United States, 2015","interactions":[],"lastModifiedDate":"2020-10-19T11:35:18.292013","indexId":"cir1464","displayToPublicDate":"2020-10-16T15:20:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1464","displayTitle":"Estimated Groundwater Withdrawals from Principal Aquifers in the United States, 2015","title":"Estimated groundwater withdrawals from principal aquifers in the United States, 2015","docAbstract":"<p>In 2015, about 84,600 million gallons per day (Mgal/d) of groundwater were withdrawn in the United States for various uses including public supply, self-supplied domestic, industrial, mining, thermoelectric power, aquaculture, livestock, and irrigation. Of this total, about 94 percent (79,200 Mgal/d) was withdrawn from principal aquifers, which are defined as regionally extensive aquifers or aquifer systems that have the potential to be used as sources of water of suitable quality and quantity to meet various needs. The remaining 6 percent (5,400 Mgal/d) was withdrawn from other, nonprincipal aquifers in the United States.</p><p>Sixty-six principal aquifers belonging to 5 major lithologic groups have been identified and delineated in the United States, including Puerto Rico and the U.S. Virgin Islands. Of the water withdrawn from principal aquifers in 2015, 81 percent (63,900 Mgal/d) was from the unconsolidated and semiconsolidated sand and gravel lithologic group, 7.1 percent (5,630 Mgal/d) was from the igneous and metamorphic-rock lithologic group, 6.8 percent (5,360 Mgal/d) was from the carbonate-rock lithologic group, 3.4 percent (2,680 Mgal/d) was from the sandstone lithologic group, and 2.2 percent (1,710 Mgal/d) was from the sandstone and carbonate-rock lithologic group.</p><p>The most heavily pumped of the 24 principal aquifers and aquifer systems within the unconsolidated and semiconsolidated sand and gravel lithologic group were the High Plains aquifer (12,300 Mgal/d), Mississippi River Valley alluvial aquifer (12,100 Mgal/d), Central Valley aquifer system (11,100 Mgal/d), and Basin and Range basin-fill aquifers (7,390 Mgal/d). Withdrawals for irrigation were 48,100 Mgal/d and accounted for 75 percent of the total withdrawals from this lithologic group. Although unconsolidated sand and gravel aquifers are widely distributed and were used as sources of water in all States except Hawaii and the U.S. Virgin Islands, 56 percent of the total withdrawn from unconsolidated and semiconsolidated sand and gravel aquifers was in just four States: California (15,600 Mgal/d), Arkansas (9,560 Mgal/d), Nebraska (5,570 Mgal/d), and Texas (4,830 Mgal/d).</p><p>The most heavily pumped of the seven principal aquifers within the igneous and metamorphic-rock lithologic group were the Snake River Plain (2,930 Mgal/d) and Columbia Plateau basaltic-rock aquifers (1,080 Mgal/d), which are located in the northwestern United States and together accounted for 71 percent of the water withdrawn from this lithologic group. Withdrawals for irrigation were 4,190 Mgal/d and accounted for more than 74 percent of the total withdrawals from this lithologic group. Seventy-eight percent of the withdrawals from igneous and metamorphic-rock aquifers were in three States: Idaho (3,230 Mgal/d), Washington (614 Mgal/d), and Oregon (528 Mgal/d).</p><p>The most heavily pumped of the 15 principal aquifers and aquifer systems within the carbonate-rock lithologic group were the Floridan aquifer system (3,180 Mgal/d) and the Biscayne aquifer (679 Mgal/d), which are in the southeastern United States and together accounted for almost 72 percent of the withdrawals from this lithologic group. Withdrawals for public supply (2,440 Mgal/d) and irrigation (1,610 Mgal/d) together accounted for almost 76 percent of the total withdrawals from this lithologic group. Although water was withdrawn from carbonate-rock aquifers in 35 States, 71 percent of the total withdrawn was in Florida (3,020 Mgal/d) and Georgia (785 Mgal/d).</p><p>The most heavily pumped of the 15 principal aquifers within the sandstone lithologic group was the Cambrian-Ordovician aquifer system (921 Mgal/d), which is in the north-central United States and accounted for 34 percent of the water withdrawn from this lithologic group. Withdrawals for public supply were 1,030 Mgal/d and accounted for 38 percent of the total withdrawals from this lithologic group. Although sandstone aquifers were used as sources of water in 32 States, 45 percent of the total withdrawn from sandstone aquifers was in five States: Minnesota (321 Mgal/d), Wisconsin (319 Mgal/d), Kansas (193 Mgal/d), Illinois (187 Mgal/d), and Pennsylvania (179 Mgal/d).</p><p>The most heavily pumped of the five principal aquifers and aquifer systems within the sandstone and carbonate-rock lithologic group were the Edwards-Trinity aquifer system (661 Mgal/d) in the south-central United States and the Valley and Ridge aquifers (551 Mgal/d) of the eastern United States, which together accounted for 71 percent of total withdrawals from this lithologic group. Withdrawals from sandstone and carbonate-rock aquifers for public-supply (713 Mgal/d), irrigation (469 Mgal/d), and self-supplied domestic (253 Mgal/d) uses accounted for about 84 percent of the total withdrawals from this lithologic group. Although water was withdrawn from sandstone and carbonate-rock aquifers in 25 States, 65 percent of the total withdrawn was in Texas (651 Mgal/d), Pennsylvania (238 Mgal/d), and Florida (223 Mgal/d).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1464","usgsCitation":"Lovelace, J.K., Nielsen, M.G., Read, A.L., Murphy, C.J., and Maupin, M.A., 2020, Estimated groundwater withdrawals from principal aquifers in the United States, 2015 (ver. 1.2, October 2020): U.S. Geological Survey Circular 1464, 70 p., https://doi.org/10.3133/cir1464.","productDescription":"Report: vii, 70 p.; Data Release","numberOfPages":"82","onlineOnly":"N","ipdsId":"IP-107784","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science 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Scope</li><li>Water-Use Terminology</li><li>Sources of Data and Methods</li><li>Aquifer Terminology</li><li>Estimated Groundwater Withdrawals from Principal Aquifers</li><li>Withdrawals by Major Lithologic Group</li><li>Withdrawals by Category of Use</li><li>Estimated Withdrawals from Selected Principal Aquifers</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. Summary of Sources of Information and Methods Used to Estimate Water Withdrawals from Principal Aquifers for Each Category of Use in Each State</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-04-27","revisedDate":"2020-10-16","noUsgsAuthors":false,"publicationDate":"2020-04-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Lovelace, John K. 0000-0002-8532-2599 jlovelac@usgs.gov","orcid":"https://orcid.org/0000-0002-8532-2599","contributorId":999,"corporation":false,"usgs":true,"family":"Lovelace","given":"John","email":"jlovelac@usgs.gov","middleInitial":"K.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nielsen, Martha G. 0000-0003-3038-9400 mnielsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3038-9400","contributorId":4169,"corporation":false,"usgs":true,"family":"Nielsen","given":"Martha","email":"mnielsen@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Amy L. 0000-0003-2296-5500","orcid":"https://orcid.org/0000-0003-2296-5500","contributorId":216515,"corporation":false,"usgs":true,"family":"Read","given":"Amy","email":"","middleInitial":"L.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Chid J. 0000-0001-9675-8382","orcid":"https://orcid.org/0000-0001-9675-8382","contributorId":223073,"corporation":false,"usgs":false,"family":"Murphy","given":"Chid","email":"","middleInitial":"J.","affiliations":[{"id":40665,"text":"U.S. Bureau of Indian Affairs","active":true,"usgs":false}],"preferred":false,"id":784010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maupin, Molly A. 0000-0002-2695-5505 mamaupin@usgs.gov","orcid":"https://orcid.org/0000-0002-2695-5505","contributorId":951,"corporation":false,"usgs":true,"family":"Maupin","given":"Molly","email":"mamaupin@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784011,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70216657,"text":"70216657 - 2020 - From pools to flow: The PROMISE framework for new insights on soil carbon cycling in a changing world","interactions":[],"lastModifiedDate":"2020-11-27T17:04:13.695051","indexId":"70216657","displayToPublicDate":"2020-10-16T11:01:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"From pools to flow: The PROMISE framework for new insights on soil carbon cycling in a changing world","docAbstract":"<p><span>Soils represent the largest terrestrial reservoir of organic carbon, and the balance between soil organic carbon (SOC) formation and loss will drive powerful carbon‐climate feedbacks over the coming century. To date, efforts to predict SOC dynamics have rested on pool‐based models, which assume classes of SOC with internally homogenous physicochemical properties. However, emerging evidence suggests that soil carbon turnover is not dominantly controlled by the chemistry of carbon inputs, but rather by restrictions on microbial access to organic matter in the spatially heterogeneous soil environment. The dynamic processes that control the physicochemical protection of carbon translate poorly to pool‐based SOC models; as a result, we are challenged to mechanistically predict how environmental change will impact movement of carbon between soils and the atmosphere. Here, we propose a novel conceptual framework to explore controls on belowground carbon cycling:&nbsp;</span><strong>P</strong><span>robabilistic&nbsp;</span><strong>R</strong><span>epresentation of&nbsp;</span><strong>O</strong><span>rganic&nbsp;</span><strong>M</strong><span>atter&nbsp;</span><strong>I</strong><span>nteractions within the&nbsp;</span><strong>S</strong><span>oil&nbsp;</span><strong>E</strong><span>nvironment (PROMISE). In contrast to traditional model frameworks, PROMISE does not attempt to define carbon pools united by common thermodynamic or functional attributes. Rather, the PROMISE concept considers how SOC cycling rates are governed by the stochastic processes that influence the proximity between microbial decomposers and organic matter, with emphasis on their physical location in the soil matrix. We illustrate the applications of this framework with a new biogeochemical simulation model that traces the fate of individual carbon atoms as they interact with their environment, undergoing biochemical transformations and moving through the soil pore space. We also discuss how the PROMISE framework reshapes dialogue around issues related to SOC management in a changing world. We intend the PROMISE framework to spur the development of new hypotheses, analytical tools, and model structures across disciplines that will illuminate mechanistic controls on the flow of carbon between plant, soil, and atmospheric pools.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15365","usgsCitation":"Waring, B.G., Sulman, B.N., Reed, S., Smith, A.P., Averill, C., Creamer, C., Cusack, D.F., Hall, S.J., Jastrow, J., Kemner, K.M., Kleber, M., Liu, X.A., Pett-Ridge, J., and Schulz, M., 2020, From pools to flow: The PROMISE framework for new insights on soil carbon cycling in a changing world: Global Change Biology, v. 26, no. 12, p. 6631-6643, https://doi.org/10.1111/gcb.15365.","productDescription":"13 p.","startPage":"6631","endPage":"6643","ipdsId":"IP-112861","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455027,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1782302","text":"External Repository"},{"id":380844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Waring, Bonnie G. 0000-0002-8457-5164","orcid":"https://orcid.org/0000-0002-8457-5164","contributorId":245284,"corporation":false,"usgs":false,"family":"Waring","given":"Bonnie","email":"","middleInitial":"G.","affiliations":[{"id":49130,"text":"Utah State University, Department of Biology and Ecology Center, Logan UT 84322","active":true,"usgs":false}],"preferred":false,"id":805742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sulman, Benjamin N. 0000-0002-3265-6691","orcid":"https://orcid.org/0000-0002-3265-6691","contributorId":209890,"corporation":false,"usgs":false,"family":"Sulman","given":"Benjamin","email":"","middleInitial":"N.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":805743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, A. Peyton","contributorId":245298,"corporation":false,"usgs":false,"family":"Smith","given":"A.","email":"","middleInitial":"Peyton","affiliations":[],"preferred":false,"id":805745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Averill, Colin","contributorId":245299,"corporation":false,"usgs":false,"family":"Averill","given":"Colin","email":"","affiliations":[],"preferred":false,"id":805746,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Creamer, Courtney 0000-0001-8270-9387","orcid":"https://orcid.org/0000-0001-8270-9387","contributorId":201952,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":805747,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cusack, Daniela F. 0000-0003-4681-7449","orcid":"https://orcid.org/0000-0003-4681-7449","contributorId":245300,"corporation":false,"usgs":false,"family":"Cusack","given":"Daniela","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":805822,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hall, Steven J. 0000-0002-7841-2019","orcid":"https://orcid.org/0000-0002-7841-2019","contributorId":244336,"corporation":false,"usgs":false,"family":"Hall","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":805823,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jastrow, Julie","contributorId":243114,"corporation":false,"usgs":false,"family":"Jastrow","given":"Julie","affiliations":[{"id":17946,"text":"Argonne National Laboratory","active":true,"usgs":false}],"preferred":false,"id":805824,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kemner, Kenneth M.","contributorId":245301,"corporation":false,"usgs":false,"family":"Kemner","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":805825,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kleber, Markus","contributorId":92182,"corporation":false,"usgs":true,"family":"Kleber","given":"Markus","email":"","affiliations":[],"preferred":false,"id":805826,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Liu, Xiao-Jun Allen","contributorId":245302,"corporation":false,"usgs":false,"family":"Liu","given":"Xiao-Jun","email":"","middleInitial":"Allen","affiliations":[],"preferred":false,"id":805827,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pett-Ridge, Jennifer","contributorId":6726,"corporation":false,"usgs":true,"family":"Pett-Ridge","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":805828,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":3720,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie S.","email":"mschulz@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":805829,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70215294,"text":"sir20205082 - 2020 - Delineation of flood-inundation areas in Grapevine Canyon near Scotty’s Castle, Death Valley National Park, California","interactions":[],"lastModifiedDate":"2024-06-05T14:01:50.726878","indexId":"sir20205082","displayToPublicDate":"2020-10-16T10:48:16","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5082","displayTitle":"Delineation of Flood-Inundation Areas in Grapevine Canyon Near Scotty’s Castle, Death Valley National Park, California","title":"Delineation of flood-inundation areas in Grapevine Canyon near Scotty’s Castle, Death Valley National Park, California","docAbstract":"<p><span>On October 18, 2015, a large flood caused considerable damage in Grapevine Canyon near Death Valley Scotty Historic District, in Death Valley National Park, California. Significant channel changes had limited the applicability of previously created flood-inundation maps to current conditions. Predicted flood-inundation maps for Scotty’s Castle were updated using one-dimensional hydraulic models. A digital terrain model was created for the study area using a terrestrial laser scanner for use in the hydraulic models. Estimations of the 4, 2, 1, 0.5, and 0.2-percent annual exceedance probability flood streamflows (previously known as the 25, 50, 100, 250, and 500-year floods) were computed from regional flood regression equations. The estimated flood streamflows were used with the hydraulic models to compute water surface elevations that were mapped on the digital terrain model. The results indicate inundation of the visitor center and park offices occurs by the 4-percent annual exceedance probability flood. Bridge and embankment overtopping occurs by the 2-percent annual exceedance probability flood. Sections of Grapevine Canyon Road and the parking lot are inundated by the 4-percent annual exceedance probability flood and above streamflows. None of the computed streamflows reach Scotty’s Castle main building.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205082","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Morris, C.M., Welborn, T.L., and Minear, J.T., 2020, Delineation of flood-inundation areas in Grapevine Canyon near Scotty’s Castle, Death Valley National Park, California: U.S. Geological Survey Scientific Investigations Report 2020–5082, 27 p., https://doi.org/10.3133/sir20205082.","productDescription":"Report: vi, 27 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-091560","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":379474,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IPKW55","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial Data, Tabular Data, and Surface-Water Model Archive for Delineation of Flood-Inundation Areas in Grapevine Canyon Near Scotty's Castle, Death Valley National Park, California"},{"id":379390,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5082/sir20205082.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5082"},{"id":379389,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5082/coverthb2.jpg"}],"country":"United States","state":"California","otherGeospatial":"Death Valley National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.960205078125,\n              36.5670120564234\n            ],\n            [\n              -116.8670654296875,\n              36.5670120564234\n            ],\n            [\n              -116.8670654296875,\n              37.19095471582605\n            ],\n            [\n              -117.960205078125,\n              37.19095471582605\n            ],\n            [\n              -117.960205078125,\n              36.5670120564234\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nv@usgs.gov\" data-mce-href=\"mailto:dc_nv@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/nv-water \" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/nv-water\">Nevada Water Science Center</a><br>U.S. Geological Survey<br>2730 N. Deer Run Road<br>Carson City, Nevada 95819</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Data Acquisition and Processing</li><li>Hydraulic Modeling</li><li>Results</li><li>Discussion</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishedDate":"2020-10-16","noUsgsAuthors":false,"publicationDate":"2020-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Morris, Christopher M. 0000-0002-0477-7605 cmmorris@usgs.gov","orcid":"https://orcid.org/0000-0002-0477-7605","contributorId":243176,"corporation":false,"usgs":true,"family":"Morris","given":"Christopher M.","email":"cmmorris@usgs.gov","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":801650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welborn, Toby L. 0000-0003-4839-2405 tlwelbor@usgs.gov","orcid":"https://orcid.org/0000-0003-4839-2405","contributorId":2295,"corporation":false,"usgs":true,"family":"Welborn","given":"Toby","email":"tlwelbor@usgs.gov","middleInitial":"L.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":801651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minear, J. Toby","contributorId":9938,"corporation":false,"usgs":true,"family":"Minear","given":"J. Toby","affiliations":[],"preferred":false,"id":801652,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70230033,"text":"70230033 - 2020 - A comparison of the CMIP6 midHolocene and lig127k simulations in CESM2","interactions":[],"lastModifiedDate":"2022-03-25T14:09:52.471224","indexId":"70230033","displayToPublicDate":"2020-10-16T08:59:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A comparison of the CMIP6 <i>midHolocene</i> and <i>lig127k</i> simulations in CESM2","title":"A comparison of the CMIP6 midHolocene and lig127k simulations in CESM2","docAbstract":"<p><span>Results are presented and compared for the Community Earth System Model version 2 (CESM2) simulations of the middle Holocene (MH, 6&nbsp;ka) and Last Interglacial (LIG, 127&nbsp;ka). These simulations are designated as Tier 1 experiments (</span><i>midHolocene</i><span>&nbsp;and&nbsp;</span><i>lig127k</i><span>) for the Coupled Model Intercomparison Project phase 6 (CMIP6) and the Paleoclimate Modeling Intercomparison Project phase 4 (PMIP4). They use the low-top, standard 1° version of CESM2 contributing to CMIP6 DECK, historical, and future projection simulations, and to other modeling intercomparison projects. The&nbsp;</span><i>midHolocene</i><span>&nbsp;and&nbsp;</span><i>lig127k</i><span>&nbsp;provide the opportunity to examine the responses in CESM2 to the orbitally induced changes in the seasonal and latitudinal distribution of insolation. The insolation anomalies result in summer warming over the Northern Hemisphere continents, reduced Arctic summer minimum sea ice, and increased areal extent of the North African monsoon. The Arctic remains warm throughout the year. These changes are greater in the&nbsp;</span><i>lig127k</i><span>&nbsp;than&nbsp;</span><i>midHolocene</i><span>&nbsp;simulation. Other notable changes are reduction of the Niño3.4 variability and Drake Passage transport and a small increase in the Atlantic Meridional Overturning Circulation from the&nbsp;</span><i>piControl</i><span>&nbsp;to&nbsp;</span><i>midHolocene</i><span>&nbsp;to&nbsp;</span><i>lig127k</i><span>&nbsp;simulation. Comparisons to paleo-data and to simulations from previous model versions are discussed. Possible reasons for mismatches with the paleo-observations are proposed, including missing processes in CESM2, simplifications in the CMIP6 protocols for these experiments, and dating and calibration uncertainties in the data reconstructions.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020PA003957","usgsCitation":"Otto-Bliesner, B., Brady, E.C., Tomas, R.A., Albani, S., Bartlein, P.J., Mahowald, N.M., Shafer, S., Kluzek, E., Lawrence, P.J., Leguy, G., Rothstein, M., and Sommers, A., 2020, A comparison of the CMIP6 midHolocene and lig127k simulations in CESM2: Paleoceanography and Paleoclimatology, v. 35, e2020PA003957, 30 p., https://doi.org/10.1029/2020PA003957.","productDescription":"e2020PA003957, 30 p.","ipdsId":"IP-116661","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":455028,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020pa003957","text":"Publisher Index Page"},{"id":436753,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D9S4EY","text":"USGS data release","linkHelpText":"Biomes simulated by BIOME4 using CESM2 lig127k, midHolocene, and piControl climate data on a global 0.5-degree grid"},{"id":397601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationDate":"2020-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Otto-Bliesner, Bette L.","contributorId":279720,"corporation":false,"usgs":false,"family":"Otto-Bliesner","given":"Bette L.","affiliations":[{"id":57353,"text":"Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":838791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brady, Esther C. 0000-0001-7833-2249","orcid":"https://orcid.org/0000-0001-7833-2249","contributorId":289169,"corporation":false,"usgs":false,"family":"Brady","given":"Esther","email":"","middleInitial":"C.","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tomas, Robert A","contributorId":289243,"corporation":false,"usgs":false,"family":"Tomas","given":"Robert","email":"","middleInitial":"A","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Albani, Samuel","contributorId":289245,"corporation":false,"usgs":false,"family":"Albani","given":"Samuel","email":"","affiliations":[{"id":35744,"text":"University of Milano-Bicocca","active":true,"usgs":false}],"preferred":false,"id":838794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bartlein, Patrick J. 0000-0001-7657-5685","orcid":"https://orcid.org/0000-0001-7657-5685","contributorId":211587,"corporation":false,"usgs":false,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":33397,"text":"U of Oregon","active":true,"usgs":false}],"preferred":false,"id":838795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mahowald, Natalie M","contributorId":289246,"corporation":false,"usgs":false,"family":"Mahowald","given":"Natalie","email":"","middleInitial":"M","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":838796,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shafer, Sarah 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":149866,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838797,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kluzek, Erik 0000-0002-1606-9219","orcid":"https://orcid.org/0000-0002-1606-9219","contributorId":289172,"corporation":false,"usgs":false,"family":"Kluzek","given":"Erik","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838798,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lawrence, Peter J","contributorId":289248,"corporation":false,"usgs":false,"family":"Lawrence","given":"Peter","email":"","middleInitial":"J","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838799,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Leguy, Gunter 0000-0002-9963-8076","orcid":"https://orcid.org/0000-0002-9963-8076","contributorId":289175,"corporation":false,"usgs":false,"family":"Leguy","given":"Gunter","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838800,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rothstein, Matthew","contributorId":289250,"corporation":false,"usgs":false,"family":"Rothstein","given":"Matthew","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838801,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sommers, Aleah 0000-0001-8718-0603","orcid":"https://orcid.org/0000-0001-8718-0603","contributorId":289162,"corporation":false,"usgs":false,"family":"Sommers","given":"Aleah","email":"","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":838802,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70216781,"text":"70216781 - 2020 - Variables affecting resource subsidies from streams and rivers to land and their susceptibility to global change stressors","interactions":[],"lastModifiedDate":"2020-12-07T14:50:09.483403","indexId":"70216781","displayToPublicDate":"2020-10-16T08:48:08","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Variables affecting resource subsidies from streams and rivers to land and their susceptibility to global change stressors","docAbstract":"<p id=\"Par1\" class=\"Para\">Stream and river ecosystems provide subsidies of emergent adult aquatic insects and other resources to terrestrial food webs, and this lotic–land subsidy has garnered much attention in recent research. Here, we critically examine a list of biotic and abiotic variables—including productivity, dominant taxa, geomorphology, and weather—that should be important in affecting the nature of these subsidy dynamics between lotic and terrestrial ecosystems, especially the pathway from emergent aquatic insects to terrestrial predators. We also explore how interactions between these variables can lead to otherwise unexpected patterns in the importance of aquatic subsidies to terrestrial food webs. Utilizing a match-mismatch framework developed previously, we identify how these variables and interactions may be affected by a broad suite of stressors in addition to contaminants: climate change, land-use conversion, damming and water abstraction, and species invasions and extinctions. These stressors may all act to modify and potentially exacerbate the effects of contaminants on subsidies. The available literature on many variables is sparse, despite strong theoretical underpinnings supporting their importance for lotic–land subsidies. Notably, these understudied variables include those related to physical geomorphology and the structure of the stream/river and floodplain/riparian zone as well as species-specific interactions between aquatic and terrestrial organisms. We suggest that more explicit characterization of these variables and more research directly linking broad-scale stressors to subsidy resource–consumer interactions can help provide a more mechanistic understanding to lotic–land subsidy dynamics within a changing environment.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Contaminants and ecological subsidies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-49480-3_7","usgsCitation":"Muehlbauer, J., Larsen, S., Jonsson, M., and Emilson, E.J., 2020, Variables affecting resource subsidies from streams and rivers to land and their susceptibility to global change stressors, chap. <i>of</i> Contaminants and ecological subsidies, p. 129-155, https://doi.org/10.1007/978-3-030-49480-3_7.","productDescription":"27 p.","startPage":"129","endPage":"155","ipdsId":"IP-090826","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":381024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Muehlbauer, Jeffrey 0000-0003-1808-580X","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":221739,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":806231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larsen, Stefano","contributorId":169188,"corporation":false,"usgs":false,"family":"Larsen","given":"Stefano","email":"","affiliations":[{"id":13099,"text":"German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany","active":true,"usgs":false}],"preferred":false,"id":806232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jonsson, Micael","contributorId":245462,"corporation":false,"usgs":false,"family":"Jonsson","given":"Micael","email":"","affiliations":[{"id":49198,"text":"Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden","active":true,"usgs":false}],"preferred":false,"id":806233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Emilson, Erik J.S.","contributorId":245463,"corporation":false,"usgs":false,"family":"Emilson","given":"Erik","email":"","middleInitial":"J.S.","affiliations":[{"id":49199,"text":"Natural Resources Canada, Canadian Forest ServiceGreat Lakes Forestry Centre, Sault Ste. Marie, Canada","active":true,"usgs":false}],"preferred":false,"id":806234,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70216147,"text":"70216147 - 2020 - Metamorphosis and the impact of contaminants on ecological subsidies","interactions":[],"lastModifiedDate":"2020-11-06T14:36:25.684398","indexId":"70216147","displayToPublicDate":"2020-10-16T08:30:29","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Metamorphosis and the impact of contaminants on ecological subsidies","docAbstract":"<p id=\"Par1\" class=\"Para\">Animals with complex life histories such as aquatic insects and amphibians link freshwater and terrestrial ecosystems when they transition from water to land during development. This transition requires metamorphosis from juvenile to adult life stages. Metamorphosis is a stressful and ecologically sensitive life history event. Exposure to contaminants during juvenile development (before or during metamorphosis) can disrupt the complex process of metamorphosis, thereby altering the flow of organisms from water to land. This chapter reviews how ecological stressors impact the timing and success of metamorphosis. Key ideas include: (1) metamorphosis is a key event in the movement of subsidies from water to land, (2) mortality during metamorphosis is enhanced in the presence of contaminants, and (3) juvenile responses to contaminants may not predict adult responses, due to death during metamorphosis. Metamorphosis is a critical life history stage that should be accounted for in ecotoxicological studies.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Contaminants and ecological subsidies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-49480-3_6","usgsCitation":"Wesner, J., Kraus, J.M., Henry, B.L., and Kerby, J., 2020, Metamorphosis and the impact of contaminants on ecological subsidies, chap. <i>of</i> Contaminants and ecological subsidies, p. 111-125, https://doi.org/10.1007/978-3-030-49480-3_6.","productDescription":"15 p.","startPage":"111","endPage":"125","ipdsId":"IP-113160","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":380261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Wesner, Jeff","contributorId":211583,"corporation":false,"usgs":false,"family":"Wesner","given":"Jeff","affiliations":[{"id":16684,"text":"University of South Dakota","active":true,"usgs":false}],"preferred":false,"id":804230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henry, Brianna L.","contributorId":239984,"corporation":false,"usgs":false,"family":"Henry","given":"Brianna","email":"","middleInitial":"L.","affiliations":[{"id":48079,"text":"Natural Resources Conservation Service, Beltsville, MD","active":true,"usgs":false}],"preferred":false,"id":804232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kerby, Jacob","contributorId":244593,"corporation":false,"usgs":false,"family":"Kerby","given":"Jacob","affiliations":[{"id":16684,"text":"University of South Dakota","active":true,"usgs":false}],"preferred":false,"id":804233,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70216144,"text":"70216144 - 2020 - Introduction: Ecological subsidies as a framework for understanding contaminant fate, exposure, and effects at the land-water interface","interactions":[],"lastModifiedDate":"2020-11-06T14:28:58.413961","indexId":"70216144","displayToPublicDate":"2020-10-16T08:25:06","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Introduction: Ecological subsidies as a framework for understanding contaminant fate, exposure, and effects at the land-water interface","docAbstract":"<p><span>Ecologists have long recognized that ecological subsidies (the flow of organic matter, nutrients, and organisms between ecosystems) can strongly affect ecosystem processes and community structure in the recipient ecosystem. Animal movements, organic matter flows, and food web dynamics between linked aquatic and terrestrial systems can also influence contaminant fate, exposure, and effects at the land-water interface. Here and in this book, we develop a broad framework that highlights two important ways that ecological subsidies and contaminants interact. Ecological subsidies from the donor system can drive exposure to recipient systems, and contaminant exposures in the donor system can control subsidies and contaminant fluxes to the recipient systems. In the case of prey movement between ecosystems, subsidies drive exposure when contaminants present in aquatic environments bioaccumulate in the tissues of prey organisms at levels that are relatively non-toxic to the prey themselves. Conversely, exposure in the aquatic system can limit subsidies when pollutants are relatively toxic to prey organisms themselves and the magnitude of the subsidy (i.e., biomass of aquatic insects emerging to the terrestrial environment) is reduced. These effects of contaminants on subsidies are shaped by other global stressors that are ubiquitous in aquatic-riparian ecosystems (e.g., climate and land use change, species extinction and invasion, and eutrophication). As our understanding of these ecological and toxicological processes advances, there are increasing opportunities to make landscape-scale predictions of contaminant and animal fluxes and to integrate this knowledge of aquatic-riparian linkages into managing contaminant risks. Through these efforts to integrate the fields of ecology and ecotoxicology on this subject, we expect to gain greater insight on the ecological effects of contaminants on linked ecosystems as well as the ways in which food web dynamics and ecosystem processes can themselves govern the fate, transport, and exposure to contaminants in the environment.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Contaminants and Ecological Subsidies: The Land-Water Interface","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-49480-3_1","usgsCitation":"Walters, D., Kraus, J.M., and Mills, M.A., 2020, Introduction: Ecological subsidies as a framework for understanding contaminant fate, exposure, and effects at the land-water interface, chap. <i>of</i> Contaminants and Ecological Subsidies: The Land-Water Interface, p. 1-14, https://doi.org/10.1007/978-3-030-49480-3_1.","productDescription":"14 p.","startPage":"1","endPage":"14","ipdsId":"IP-116208","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":380259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Walters, David 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":147135,"corporation":false,"usgs":true,"family":"Walters","given":"David","email":"waltersd@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":804227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mills, Marc A.","contributorId":141085,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":804229,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70216153,"text":"70216153 - 2020 - Practical considerations for the incorporation of insect-mediated contaminant flux into ecological risk assessments","interactions":[],"lastModifiedDate":"2020-11-06T14:23:46.681124","indexId":"70216153","displayToPublicDate":"2020-10-16T08:21:22","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Practical considerations for the incorporation of insect-mediated contaminant flux into ecological risk assessments","docAbstract":"<p id=\"Par1\" class=\"Para\">Insect-mediated contaminant flux is truly an interdisciplinary concept that merges ideas from many technical areas of science (e.g., environmental chemistry, landscape ecology, and entomology). This chapter introduces risk assessors to this emerging and ecologically relevant concept by distilling the main mechanisms that drive insect-mediated contaminant flux and integrating them together so that more informed decisions can be made on whether the phenomenon presents a potential risk at a site.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Contaminants and ecological subsidies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-49480-3_9","usgsCitation":"Otter, R.R., Beaubien, G.B., Olson, C.I., Walters, D., and Mills, M.A., 2020, Practical considerations for the incorporation of insect-mediated contaminant flux into ecological risk assessments, chap. <i>of</i> Contaminants and ecological subsidies, p. 179-195, https://doi.org/10.1007/978-3-030-49480-3_9.","productDescription":"17 p.","startPage":"179","endPage":"195","ipdsId":"IP-103787","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":380258,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Otter, Ryan R.","contributorId":205916,"corporation":false,"usgs":false,"family":"Otter","given":"Ryan","email":"","middleInitial":"R.","affiliations":[{"id":37193,"text":"Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":804238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beaubien, Gale B.","contributorId":244596,"corporation":false,"usgs":false,"family":"Beaubien","given":"Gale","email":"","middleInitial":"B.","affiliations":[{"id":37193,"text":"Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":804239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olson, Connor I.","contributorId":244597,"corporation":false,"usgs":false,"family":"Olson","given":"Connor","email":"","middleInitial":"I.","affiliations":[{"id":37193,"text":"Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":804240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":205915,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills, Marc A.","contributorId":141085,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":804242,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70216156,"text":"70216156 - 2020 - Synthesis: A framework for predicting the dark side of ecological subsidies","interactions":[],"lastModifiedDate":"2020-11-06T14:20:09.778211","indexId":"70216156","displayToPublicDate":"2020-10-16T08:17:35","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Synthesis: A framework for predicting the dark side of ecological subsidies","docAbstract":"<p id=\"Par1\" class=\"Para\">In this chapter, we synthesize the state of the science regarding ecological subsidies and contaminants at the land-water interface and suggest research and management approaches for linked freshwater-terrestrial ecosystems. Specifically, we focus on movements of animals with complex life histories and the detrital inputs associated with animal and plant matter delivered to freshwaters. We present a framework based on the physicochemical parameters of contaminants and how they shape the relationship between contaminant persistence within resource subsidies (“dark side” of subsidies) and movement of resource subsidies (“bright side” of subsidies) across ecosystem boundaries. This relationship between the “dark side” and “bright side” of subsidies defines an important parameter space that allows researchers and practitioners to predict the potential impacts of aquatic contaminants on resource subsidies and their interaction with other stressors on consumers. Ecological factors such as ecosystem productivity, community composition, and consumer prey preference shape the ecotoxicological outcomes of aquatic contamination on subsidies. Landscape factors such as lithology, hydrogeomorphology, hydroperiod, and land use underlie chemical, toxicological, and ecological patterns and provide the context within which effects of contaminants play out. Finally, effects of contaminants combine with effects of other global stressors on timing, quality, and quantity of subsidies that drive responses to contaminants at the land-water interface. Understanding the “dark side” of ecological subsidies requires expertise from multiple disciplines. We attempt to synthesize current knowledge from those disciplines and generate conceptual models that ecologists can use to guide future research in understanding cross-ecosystem subsidies and contaminant fate and effects.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Contaminants and ecological subsidies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-49480-3_14","usgsCitation":"Kraus, J.M., Wessner, J., and Walters, D., 2020, Synthesis: A framework for predicting the dark side of ecological subsidies, chap. <i>of</i> Contaminants and ecological subsidies, p. 343-372, https://doi.org/10.1007/978-3-030-49480-3_14.","productDescription":"30 p.","startPage":"343","endPage":"372","ipdsId":"IP-114721","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":380257,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wessner, Jeff","contributorId":244602,"corporation":false,"usgs":false,"family":"Wessner","given":"Jeff","email":"","affiliations":[{"id":16684,"text":"University of South Dakota","active":true,"usgs":false}],"preferred":false,"id":804244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":205915,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":804245,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70216141,"text":"70216141 - 2020 - Cross-ecosystem linkages and trace metals at the land-water interface","interactions":[],"lastModifiedDate":"2020-11-06T14:16:25.956662","indexId":"70216141","displayToPublicDate":"2020-10-16T08:12:20","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Cross-ecosystem linkages and trace metals at the land-water interface","docAbstract":"<p id=\"Par1\" class=\"Para\">At low concentrations, trace metals are critical for sustaining life on Earth. However, at high concentrations, they become a global contaminant with particularly strong effects on freshwater communities. These effects can propagate to terrestrial ecosystems in part by altering production and community structure of adult aquatic insect emergence and aquatic insect-mediated metal fluxes to terrestrial insectivores. Here we highlight mechanisms driving effects of trace metals on aquatic organisms in general, aquatic insects specifically, and insectivorous consumers at the land-water interface. Specifically, we focus on how trace metals impact and bioaccumulate in aquatic organisms and communities and how these changes propagate through aquatic food web interactions and insect metamorphosis to alter fluxes of aquatically derived prey and trace metals to terrestrial consumers. Ultimately, trace metals impact food webs at the land-water interface by altering aquatic insect prey composition and availability for aquatic insectivores and by reducing aquatic insect subsidies to terrestrial consumers, and not by increasing exposure to trace metals in prey. Exposure of terrestrial insectivores to trace metals in prey is decoupled from aqueous concentrations due to high rates of metal excretion during insect metamorphosis from aquatic larvae to terrestrial adult. These effects increase reliance of aquatic insectivores on terrestrial insect prey subsidies and/or lead to declines and behavioral changes in terrestrial insectivore populations.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Contaminants and ecological subsidies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-49480-3_5","usgsCitation":"Kraus, J.M., and Pomeranz, J., 2020, Cross-ecosystem linkages and trace metals at the land-water interface, chap. <i>of</i> Contaminants and ecological subsidies, p. 91-109, https://doi.org/10.1007/978-3-030-49480-3_5.","productDescription":"19 p.","startPage":"91","endPage":"109","ipdsId":"IP-109559","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":380256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":804225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pomeranz, Justin F.","contributorId":149789,"corporation":false,"usgs":false,"family":"Pomeranz","given":"Justin F.","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":804226,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215275,"text":"ofr20201108 - 2020 - Aquifer transmissivity in Nassau, Queens, and Kings Counties, New York, estimated from specific-capacity tests at production wells","interactions":[],"lastModifiedDate":"2020-10-16T12:33:17.218141","indexId":"ofr20201108","displayToPublicDate":"2020-10-15T15:50:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1108","displayTitle":"Aquifer Transmissivity in Nassau, Queens, and Kings Counties, New York, Estimated From Specific-Capacity Tests at Production Wells","title":"Aquifer transmissivity in Nassau, Queens, and Kings Counties, New York, estimated from specific-capacity tests at production wells","docAbstract":"<p>As part of a cooperative effort between the U.S. Geological Survey and the New York State Department of Environmental Conservation to evaluate the sustainability of Long Island’s sole-source aquifer system, the transmissivities of four aquifers were estimated from specific-capacity tests at 447 production wells in Nassau, Queens, and Kings Counties on Long Island, New York. The specific-capacity test data, which included pumping rate, pumping duration, and drawdown, were obtained from published and unpublished records of driller-reported acceptance tests collected at production wells screened in the upper glacial, Jameco, Magothy, or Lloyd aquifers. Pumping rates from the production wells during the tests generally were greater than 400 gallons per minute and ranged up to 1,800 gallons per minute. Pumping duration generally was 8 hours or more. Transmissivities were estimated from the specific-capacity data by the Cooper-Jacob approximation of the Theis equation. The transmissivity estimates are considered rough approximations because the aquifers do not meet the ideal assumptions of the method, well losses and partial penetration were not accounted for, and aquifer storage coefficients were not known but were only estimated from available data.</p><p>The transmissivities estimated from production wells screened in the upper glacial aquifer in the outwash plain south of the moraine generally were greater than those of the aquifer north of the moraine. The transmissivities estimated from the wells screened in the upper glacial aquifer south of the moraine typically ranged (as defined by the 10th and 90th percentiles) from 3,800 to 15,000 feet squared per day (ft<sup>2</sup>/d), with a median value of 7,300 ft<sup>2</sup>/d. The transmissivities estimated from the wells screened in the upper glacial aquifer north of the moraine typically ranged from 2,100 to 7,400 ft<sup>2</sup>/d, with a median value of 4,400 ft<sup>2</sup>/d. The Jameco aquifer generally had the highest estimated transmissivities of all the aquifers analyzed. The estimated transmissivities for the Jameco aquifer typically ranged from 5,500 to 43,000 ft<sup>2</sup>/d, with a median value of 16,000 ft<sup>2</sup>/d. The Magothy and Lloyd aquifers had similar estimated transmissivities. The transmissivities estimated for the Magothy aquifer typically ranged from 2,700 to 13,000 ft<sup>2</sup>/d, with a median of 7,100 ft<sup>2</sup>/d. The estimated transmissivities of the Lloyd typically ranged from 3,000 to 14,000 ft<sup>2</sup>/d, with a median of 7,200 ft<sup>2</sup>/d.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201108","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Williams, J.H., Woodley, M., and Finkelstein, J.S., 2020, Aquifer transmissivity in Nassau, Queens, and Kings Counties, New York, estimated from specific-capacity tests at production wells: U.S. Geological Survey Open-File Report 2020–1108, 7 p., https://doi.org/10.3133/ofr20201108.","productDescription":"Report: iv, 7 p.; Dataset; Application Site","numberOfPages":"7","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108170","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":379362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1108/coverthb.jpg"},{"id":379363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1108/ofr20201108.pdf","text":"Report","size":"1.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1108"},{"id":379365,"rank":4,"type":{"id":4,"text":"Application Site"},"url":"https://ny.water.usgs.gov/maps/aq-test/","text":"Aquifer Test Locator","linkFileType":{"id":5,"text":"html"}},{"id":379364,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System database","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","county":"Nassau County, Queens County, Kings County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.0972900390625,\n              40.43858586704331\n            ],\n            [\n              -73.388671875,\n              40.43858586704331\n            ],\n            [\n              -73.388671875,\n              41.000629848685385\n            ],\n            [\n              -74.0972900390625,\n              41.000629848685385\n            ],\n            [\n              -74.0972900390625,\n              40.43858586704331\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ ny@usgs.gov\" data-mce-href=\"mailto:dc_ ny@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/ny-water\" data-mce-href=\"https://www.usgs.gov/centers/ny-water\">New York Water Science Center</a><br>U.S. Geological Survey<br>425 Jordan Road<br>Troy, NY 12180–8349</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Hydrogeologic Setting</li><li>Previous Estimates of Hydraulic Properties</li><li>Description of Specific-Capacity Tests and Wells</li><li>Estimation Method and Limitations</li><li>Estimated Transmissivities of Selected Production Wells</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-10-15","noUsgsAuthors":false,"publicationDate":"2020-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, John H. 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","middleInitial":"H.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":801449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodley, Madison","contributorId":243054,"corporation":false,"usgs":false,"family":"Woodley","given":"Madison","email":"","affiliations":[],"preferred":false,"id":801473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finkelstein, Jason S. 0000-0002-7496-7236","orcid":"https://orcid.org/0000-0002-7496-7236","contributorId":202452,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Jason S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":801450,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70228259,"text":"70228259 - 2020 - Trophic structure of apex fish communities in closed versus leaky lakes of arctic Alaska","interactions":[],"lastModifiedDate":"2022-02-08T17:54:29.288876","indexId":"70228259","displayToPublicDate":"2020-10-15T11:46:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Trophic structure of apex fish communities in closed versus leaky lakes of arctic Alaska","docAbstract":"<p><span>Despite low species diversity and primary production, trophic structure (e.g., top predator species, predator size) is surprisingly variable among Arctic lakes. We investigated trophic structure in lakes of arctic Alaska containing arctic char&nbsp;</span><i>Salvelinus alpinus</i><span>&nbsp;using stomach contents and stable isotope ratios in two geographically-close but hydrologically-distinct lake clusters to investigate how these fish may interact and compete for limited food resources. Aside from different lake connectivity patterns (‘leaky’ versus ‘closed’), differing fish communities (up to five versus only two species) between lake clusters allowed us to test trophic hypotheses including: (1) arctic char are more piscivorous, and thereby grow larger and obtain higher trophic positions, in the presence of other fish species; and, (2) between arctic char size classes, resource polymorphism is more prominent, and thereby trophic niches are narrower and overlap less, in the absence of other predators. Regardless of lake cluster, we observed little direct evidence of arctic char consuming other fishes, but char were larger (mean TL = 468 vs 264&nbsp;mm) and trophic position was higher (mean TP = 4.0 vs 3.8 for large char) in lakes with other fishes. Further, char demonstrated less intraspecific overlap when other predators were present whereas niche overlap was up to 100% in closed, char only lakes. As hydrologic characteristics (e.g., lake connectivity, water temperatures) will change across the Arctic owing to climate change, our results provide insight regarding potential concomitant changes to fish interactions and increase our understanding of lake trophic structure to guide management and conservation goals.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00442-020-04776-9","usgsCitation":"Klobucar, S.L., and Budy, P., 2020, Trophic structure of apex fish communities in closed versus leaky lakes of arctic Alaska: Oecologia, v. 194, p. 491-504, https://doi.org/10.1007/s00442-020-04776-9.","productDescription":"14 p.","startPage":"491","endPage":"504","ipdsId":"IP-109849","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Brooks Range, Toolik Field Station","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -149.69558715820312,\n              68.3996855982224\n            ],\n            [\n              -149.20257568359375,\n              68.3996855982224\n            ],\n            [\n              -149.20257568359375,\n              68.64455609820665\n            ],\n            [\n              -149.69558715820312,\n              68.64455609820665\n            ],\n            [\n              -149.69558715820312,\n              68.3996855982224\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"194","noUsgsAuthors":false,"publicationDate":"2020-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Klobucar, Stephen L.","contributorId":274993,"corporation":false,"usgs":false,"family":"Klobucar","given":"Stephen","email":"","middleInitial":"L.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833549,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70216540,"text":"70216540 - 2020 - Experimental warming changes phenology and shortens growing season of the dominant invasive plant Bromus tectorum (cheatgrass)","interactions":[],"lastModifiedDate":"2020-11-25T16:59:26.09685","indexId":"70216540","displayToPublicDate":"2020-10-15T10:53:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5725,"text":"Frontiers in Plant Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Experimental warming changes phenology and shortens growing season of the dominant invasive plant <i>Bromus tectorum</i> (cheatgrass)","title":"Experimental warming changes phenology and shortens growing season of the dominant invasive plant Bromus tectorum (cheatgrass)","docAbstract":"<p><i>Bromus tectorum</i><span>&nbsp;(cheatgrass) has successfully invaded and established throughout the western United States.&nbsp;</span><i>Bromus tectorum</i><span>&nbsp;grows early in the season and this early growth allows&nbsp;</span><i>B. tectorum</i><span>&nbsp;to outcompete native species, which has led to dramatic shifts in ecosystem function and plant community composition after&nbsp;</span><i>B. tectorum</i><span>&nbsp;invades. If the phenology of native species is unable to track changing climate as effectively as&nbsp;</span><i>B. tectorum</i><span>’s phenology then climate change may facilitate further invasion. To better understand how&nbsp;</span><i>B. tectorum</i><span>&nbsp;phenology will respond to future climate, we tracked the timing of&nbsp;</span><i>B. tectorum</i><span>&nbsp;germination, flowering, and senescence over a decade in three&nbsp;</span><i>in situ</i><span>&nbsp;climate manipulation experiments with treatments that increased temperatures (2°C and 4°C above ambient), altered precipitation regimes, or applied a combination of each. Linear mixed-effects models were used to analyze treatment effects on the timing of germination, flowering, senescence, and on the length of the vegetative growing season (time from germination to flowering) in each experiment. Altered precipitation treatments were only applied in early years of the study and neither precipitation treatments nor the treatments’ legacies significantly affected&nbsp;</span><i>B. tectorum</i><span>&nbsp;phenology. The timing of germination did not significantly vary between any warming treatments and their respective ambient plots. However, plots that were warmed had advances in the timing of&nbsp;</span><i>B. tectorum</i><span>&nbsp;flowering and senescence, as well as shorter vegetative growing seasons. The phenological advances caused by warming increased with increasing degrees of experimental warming. The greatest differences between warmed and ambient plots were seen in the length of the vegetative growing season, which was shortened by approximately 12 and 7 days in the +4°C and +2°C warming levels, respectively. The effects of experimental warming were small compared to the effects of interannual climate variation, suggesting that interactive controls and the timing of multiple climatic factors are important in determining&nbsp;</span><i>B. tectorum</i><span>&nbsp;phenology. Taken together, these results help elucidate how&nbsp;</span><i>B. tectorum</i><span>&nbsp;phenology may respond to future climate, increasing our predictive capacity for estimating when to time&nbsp;</span><i>B. tectorum</i><span>&nbsp;control efforts and how to more effectively manage this exotic annual grass.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fpls.2020.570001","usgsCitation":"Howell, A.J., Winkler, D.E., Phillips, M.L., McNellis, B., and Reed, S., 2020, Experimental warming changes phenology and shortens growing season of the dominant invasive plant Bromus tectorum (cheatgrass): Frontiers in Plant Science, v. 11, 570001, 15 p., https://doi.org/10.3389/fpls.2020.570001.","productDescription":"570001, 15 p.","ipdsId":"IP-122205","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fpls.2020.570001","text":"Publisher Index Page"},{"id":380789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","city":"Moab","otherGeospatial":"Castle Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.69848632812499,\n              38.50948995925553\n            ],\n            [\n              -109.33868408203125,\n              38.50948995925553\n            ],\n            [\n              -109.33868408203125,\n              38.74123075381228\n            ],\n            [\n              -109.69848632812499,\n              38.74123075381228\n            ],\n            [\n              -109.69848632812499,\n              38.50948995925553\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2020-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Howell, Armin J. 0000-0003-1243-0238 ahowell@usgs.gov","orcid":"https://orcid.org/0000-0003-1243-0238","contributorId":196798,"corporation":false,"usgs":true,"family":"Howell","given":"Armin","email":"ahowell@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Michala Lee 0000-0001-7005-8740","orcid":"https://orcid.org/0000-0001-7005-8740","contributorId":245186,"corporation":false,"usgs":true,"family":"Phillips","given":"Michala","email":"","middleInitial":"Lee","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805559,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNellis, Brandon","contributorId":245187,"corporation":false,"usgs":false,"family":"McNellis","given":"Brandon","affiliations":[{"id":49106,"text":"Department of Forest, Rangeland, and Fire Sciences, University of Idaho, Moscow, Idaho, USA","active":true,"usgs":false}],"preferred":false,"id":805560,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805561,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70216544,"text":"70216544 - 2020 - Climate sensitivity of water use by riparian woodlands at landscape scales","interactions":[],"lastModifiedDate":"2020-12-14T16:56:03.212697","indexId":"70216544","displayToPublicDate":"2020-10-15T10:46:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Climate sensitivity of water use by riparian woodlands at landscape scales","docAbstract":"<p><span>Semi‐arid riparian woodlands face threats from increasing extractive water demand and climate change in dryland landscapes worldwide. Improved landscape‐scale understanding of riparian woodland water use (evapotranspiration, ET) and its sensitivity to climate variables is needed to strategically manage water resources, as well as to create successful ecosystem conservation and restoration plans for potential climate futures. In this work, we assess the spatial and temporal variability of Cottonwood (</span><i>Populus fremontii</i><span>)‐Willow (</span><i>Salix gooddingii</i><span>) riparian gallery woodland ET and its relationships to vegetation structure and climate variables for 80 km of the San Pedro River corridor in southeastern Arizona, USA, between 2014 and 2019. We use a novel combination of publicly available remote sensing, climate and hydrological datasets: cloud‐based Landsat thermal remote sensing data products for ET (Google Earth Engine EEFlux), Landsat multispectral imagery and field data‐based calibrations to vegetation structure (leaf‐area index, LAI), and open‐source climate and hydrological data. We show that at landscape scales, daily ET rates (6–10 mm day</span><sup>−1</sup><span>) and growing season ET totals (400–1,400 mm) matched rates of published field data, and modelled reach‐scale average LAI (0.80–1.70) matched lower ranges of published field data. Over 6 years, the spatial variability of total growing season ET (CV = 0.18) exceeded that of temporal variability (CV = 0.10), indicating the importance of reach‐scale vegetation and hydrological conditions for controlling ET dynamics. Responses of ET to climate differed between perennial and intermittent‐flow stream reaches. At perennial‐flow reaches, ET correlated significantly with temperature, whilst at intermittent‐flow sites ET correlated significantly with rainfall and stream discharge. Amongst reaches studied in detail, we found positive but differing logarithmic relationships between LAI and ET. By documenting patterns of high spatial variability of ET at basin scales, these results underscore the importance of accurately accounting for differences in woodland vegetation structure and hydrological conditions for assessing water‐use requirements. Results also suggest that the climate sensitivity of ET may be used as a remote indicator of subsurface water resources relative to vegetation demand, and an indicator for informing conservation management priorities.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13942","usgsCitation":"Mayes, M., Caylor, K.K., Singer, M.B., Stella, J., Roberts, D., and Nagler, P.L., 2020, Climate sensitivity of water use by riparian woodlands at landscape scales: Hydrological Processes, v. 34, no. 25, p. 4884-4903, https://doi.org/10.1002/hyp.13942.","productDescription":"10 p.","startPage":"4884","endPage":"4903","ipdsId":"IP-120214","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455038,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://orca.cardiff.ac.uk/id/eprint/135647/","text":"External Repository"},{"id":380788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"San Pedro River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.58563232421875,\n              31.3348710339506\n            ],\n            [\n              -109.79461669921875,\n              31.3348710339506\n            ],\n            [\n              -109.79461669921875,\n              32.15468722002481\n            ],\n            [\n              -110.58563232421875,\n              32.15468722002481\n            ],\n            [\n              -110.58563232421875,\n              31.3348710339506\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"25","noUsgsAuthors":false,"publicationDate":"2020-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Mayes, Marc","contributorId":245241,"corporation":false,"usgs":false,"family":"Mayes","given":"Marc","email":"","affiliations":[],"preferred":false,"id":805665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caylor, Kelly K.","contributorId":245242,"corporation":false,"usgs":false,"family":"Caylor","given":"Kelly","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":805666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singer, Michael B.","contributorId":168369,"corporation":false,"usgs":false,"family":"Singer","given":"Michael","email":"","middleInitial":"B.","affiliations":[{"id":25268,"text":"University of St Andrews, UK","active":true,"usgs":false}],"preferred":false,"id":805667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stella, John C","contributorId":149423,"corporation":false,"usgs":false,"family":"Stella","given":"John C","affiliations":[{"id":17732,"text":"Professor, Dept of Forest & Natural Resources Mgmt, SUNY at ESF","active":true,"usgs":false}],"preferred":false,"id":805668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, Dar","contributorId":13721,"corporation":false,"usgs":true,"family":"Roberts","given":"Dar","affiliations":[],"preferred":false,"id":805669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805569,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70215434,"text":"70215434 - 2020 - Principles and mechanisms of wildlife population persistence in the face of disease","interactions":[],"lastModifiedDate":"2020-10-20T14:56:37.868938","indexId":"70215434","displayToPublicDate":"2020-10-15T09:53:40","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5993,"text":"Frontiers in Ecology and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Principles and mechanisms of wildlife population persistence in the face of disease","docAbstract":"<p><span>Emerging infectious diseases can result in species declines and hamper recovery efforts for at-risk populations. Generalizing considerations for reducing the risk of pathogen introduction and mitigating the effects of disease remains challenging and inhibits our ability to provide guidance for species recovery planning. Given the growing rates of emerging pathogens globally, we identify key principles and mechanisms for maintaining sustainable populations in the face of emerging diseases (including minimizing the risk of pathogen introductions and their future effects on hosts). Our synthesis serves as a reference for minimizing the risk of future disease outbreaks, mitigating the deleterious effects of future disease outbreaks on species extinction risk, and a review of the theoretical and/or empirical examples supporting these considerations.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2020.569016","usgsCitation":"Russell, R., DiRenzo, G.V., Szymanski, J., Alger, K.E., and Campbell Grant, E.H., 2020, Principles and mechanisms of wildlife population persistence in the face of disease: Frontiers in Ecology and Environment, v. 8, 569016, 11 p., https://doi.org/10.3389/fevo.2020.569016.","productDescription":"569016, 11 p.","ipdsId":"IP-119389","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":455040,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2020.569016","text":"Publisher Index Page"},{"id":379545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2020-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":802202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":802203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Szymanski, J. 0000-0001-8378-6501","orcid":"https://orcid.org/0000-0001-8378-6501","contributorId":243405,"corporation":false,"usgs":false,"family":"Szymanski","given":"J.","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":802204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alger, Katrina E. 0000-0001-7708-0203","orcid":"https://orcid.org/0000-0001-7708-0203","contributorId":228815,"corporation":false,"usgs":true,"family":"Alger","given":"Katrina","email":"","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":802205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":802206,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70216886,"text":"70216886 - 2020 - Sediment connectivity: A framework for analyzing coastal sediment transport pathways","interactions":[],"lastModifiedDate":"2020-12-14T14:53:07.559848","indexId":"70216886","displayToPublicDate":"2020-10-15T08:48:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Sediment connectivity: A framework for analyzing coastal sediment transport pathways","docAbstract":"<div class=\"article-section__content en main\"><p>Connectivity provides a framework for analyzing coastal sediment transport pathways, building on conceptual advances in graph theory from other scientific disciplines. Connectivity schematizes sediment pathways as a directed graph (i.e., a set of nodes and links). This study presents a novel application of graph theory and connectivity metrics like modularity and centrality to coastal sediment dynamics, exemplified here using Ameland Inlet in the Netherlands. We divide the study site into geomorphic cells (i.e., nodes) and then quantify sediment transport between these cells (i.e., links) using a numerical model. The system of cells and fluxes between them is then schematized in a network described by an adjacency matrix. Network metrics like link density, asymmetry, and modularity quantify system‐wide connectivity. The degree, strength, and centrality of individual nodes identify key locations and pathways throughout the system. For instance, these metrics indicate that under strictly tidal forcing, sand originating near shore predominantly bypasses Ameland Inlet via the inlet channels, whereas sand on the deeper foreshore mainly bypasses the inlet via the outer delta shoals. Connectivity analysis can also inform practical management decisions about where to place sand nourishments, the fate of nourishment sand, or how to monitor locations vulnerable to perturbations. There are still open challenges associated with quantifying connectivity at varying space and time scales and the development of connectivity metrics specific to coastal systems. Nonetheless, connectivity provides a promising technique for predicting the response of our coasts to climate change and the human adaptations it provokes.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JF005595","usgsCitation":"Pearson, S., van Prooijen, B.C., Elias, E., Vitousek, S., and Bing Wang, Z., 2020, Sediment connectivity: A framework for analyzing coastal sediment transport pathways: Journal of Geophysical Research: Earth Surface, v. 125, no. 10, e2020JF005595, 25 p., https://doi.org/10.1029/2020JF005595.","productDescription":"e2020JF005595, 25 p.","ipdsId":"IP-116959","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":455042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jf005595","text":"Publisher Index Page"},{"id":381251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Netherlands","otherGeospatial":"Ameland Inlet","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              5.23773193359375,\n              53.3653041111989\n            ],\n            [\n              5.7733154296875,\n              53.3653041111989\n            ],\n            [\n              5.7733154296875,\n              53.48967969477544\n            ],\n            [\n              5.23773193359375,\n              53.48967969477544\n            ],\n            [\n              5.23773193359375,\n              53.3653041111989\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"125","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Pearson, Stuart 0000-0002-3986-4469","orcid":"https://orcid.org/0000-0002-3986-4469","contributorId":245646,"corporation":false,"usgs":false,"family":"Pearson","given":"Stuart","email":"","affiliations":[{"id":49245,"text":"Delft University of Technology; Deltares","active":true,"usgs":false}],"preferred":false,"id":806734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Prooijen, Bram C.","contributorId":245647,"corporation":false,"usgs":false,"family":"van Prooijen","given":"Bram","email":"","middleInitial":"C.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":806735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elias, Edwin P.L.","contributorId":245648,"corporation":false,"usgs":false,"family":"Elias","given":"Edwin P.L.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":806736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":806737,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bing Wang, Zheng","contributorId":245649,"corporation":false,"usgs":false,"family":"Bing Wang","given":"Zheng","email":"","affiliations":[{"id":49246,"text":"Deltares; Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":806738,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70216492,"text":"70216492 - 2020 - Getting to the root of plant‐mediated methane emissions and oxidation in a thermokarst bog","interactions":[],"lastModifiedDate":"2020-11-23T13:44:52.455254","indexId":"70216492","displayToPublicDate":"2020-10-15T07:40:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7359,"text":"Journal of Geophysical Research Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Getting to the root of plant‐mediated methane emissions and oxidation in a thermokarst bog","docAbstract":"<div class=\"article-section__content en main\"><p>Vascular plants are important in the wetland methane cycle, but their effect on production, oxidation, and transport has high uncertainty, limiting our ability to predict emissions. In a permafrost‐thaw bog in Interior Alaska, we used plant manipulation treatments, field‐deployed planar optical oxygen sensors, direct measurements of methane oxidation, and microbial DNA analyses to disentangle mechanisms by which vascular vegetation affect methane emissions. Vegetation operated on top of baseline methane emissions, which varied with proximity to the thawing permafrost margin. Emissions from vegetated plots increased over the season, resulting in cumulative seasonal methane emissions that were 4.1–5.2&nbsp;g&nbsp;m<sup>−2</sup><span>&nbsp;</span>season<sup>−1</sup><span>&nbsp;</span>greater than unvegetated plots. Mass balance calculations signify these greater emissions were due to increased methane production (3.0–3.5&nbsp;g&nbsp;m<sup>−2</sup><span>&nbsp;</span>season<sup>−1</sup>) and decreased methane oxidation (1.1–1.6&nbsp;g&nbsp;m<sup>−2</sup><span>&nbsp;</span>season<sup>−1</sup>). Minimal oxidation occurred along the plant‐transport pathway, and oxidation was suppressed outside the plant pathway. Our data indicate suppression of methane oxidation was stimulated by root exudates fueling competition among microbes for electron acceptors. This contention is supported by the fact that methane oxidation and relative abundance of methanotrophs decreased over the season in the presence of vegetation, but methane oxidation remained steady in unvegetated treatments; oxygen was not detected around plant roots but was detected around silicone tubes mimicking aerenchyma; and oxygen injection experiments suggested that oxygen consumption was faster in the presence of vascular vegetation. Root exudates are known to fuel methane production, and our work provides evidence they also decrease methane oxidation.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JG005825","usgsCitation":"Turner, J.C., Moorberg, C.J., Wong, A., Shea, K., Waldrop, M., Turetsky, M.R., and Neumann, R.B., 2020, Getting to the root of plant‐mediated methane emissions and oxidation in a thermokarst bog: Journal of Geophysical Research Biogeosciences, v. 125, no. 111, e2020JG005825, 18 p., https://doi.org/10.1029/2020JG005825.","productDescription":"e2020JG005825, 18 p.","ipdsId":"IP-107999","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467275,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1771151","text":"External Repository"},{"id":380678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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              -160.48828125,\n              61.689872200460016\n            ],\n            [\n              -141.328125,\n              61.689872200460016\n            ],\n            [\n              -141.328125,\n              69.56522590149099\n            ],\n            [\n              -160.48828125,\n              69.56522590149099\n            ],\n            [\n              -160.48828125,\n              61.689872200460016\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"125","issue":"111","noUsgsAuthors":false,"publicationDate":"2020-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Turner, Jesse C","contributorId":245133,"corporation":false,"usgs":false,"family":"Turner","given":"Jesse","email":"","middleInitial":"C","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":805413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moorberg, Colby J","contributorId":245134,"corporation":false,"usgs":false,"family":"Moorberg","given":"Colby","email":"","middleInitial":"J","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":805414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wong, Andrea","contributorId":245135,"corporation":false,"usgs":false,"family":"Wong","given":"Andrea","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":805415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shea, Kathleen","contributorId":245138,"corporation":false,"usgs":false,"family":"Shea","given":"Kathleen","email":"","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":805418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216780,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":805419,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Turetsky, Merritt R.","contributorId":169398,"corporation":false,"usgs":false,"family":"Turetsky","given":"Merritt","email":"","middleInitial":"R.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":805420,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neumann, Rebecca B.","contributorId":216775,"corporation":false,"usgs":false,"family":"Neumann","given":"Rebecca","email":"","middleInitial":"B.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":805421,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
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