Drinking water supply wells can be contaminated by a broad range of waterborne pathogens. However, groundwater assessments frequently measure microbial indicators or a single pathogen type, which provides a limited characterization of potential health risk. This study assessed contamination of wells by testing for viral, bacterial, and protozoan pathogens and fecal markers. Wells supplying groundwater to community and noncommunity public water systems in Minnesota, USA (n = 145) were sampled every other month over one or two years and tested using 23 qPCR assays. Eighteen genetic targets were detected at least once, and microbiological contamination was widespread (96% of 145 wells, 58% of 964 samples). The sewage-associated microbial indicators HF183 and pepper mild mottle virus were detected frequently. Human or zoonotic pathogens were detected in 70% of wells and 21% of samples by qPCR, with Salmonella and Cryptosporidium detected more often than viruses. Samples positive by qPCR for adenovirus (HAdV), enterovirus, or Salmonella were analyzed by culture and for genotype or serotype. qPCR-positive Giardia and Cryptosporidium samples were analyzed by immunofluorescent assay (IFA), and IFA and qPCR concentrations were correlated. Comparisons of indicator and pathogen occurrence at the time of sampling showed that total coliforms, HF183, and Bacteroidales-like HumM2 had high specificity and negative predictive values but generally low sensitivity and positive predictive values. Pathogen-HF183 ratios in sewage have been used to estimate health risks from HF183 concentrations in surface water, but in our groundwater samples Cryptosporidium oocyst:HF183 and HAdV:HF183 ratios were approximately 10,000 times higher than ratios reported for sewage. qPCR measurements provided a robust characterization of microbiological water quality, but interpretation of qPCR data in a regulatory context is challenging because few studies link qPCR measurements to health risk.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2020.115814","collaboration":"","usgsCitation":"Stokdyk, J.P., Firnstahl, A.D., Walsh, J.F., Spencer, S.K., de Lambert, J.R., Anderson, A., Rezania, L.W., Kieke, B.A., and Borchardt, M.A., 2020, Viral, bacterial, and protozoan pathogens and fecal markers in wells supplying groundwater to public water systems in Minnesota, USA: Water Research, v. 178, 115814, 10 p., https://doi.org/10.1016/j.watres.2020.115814.","productDescription":"115814, 10 p.","ipdsId":"IP-114409","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":374158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, James F.","contributorId":214333,"corporation":false,"usgs":false,"family":"Walsh","given":"James","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":787508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spencer, Susan K.","contributorId":210972,"corporation":false,"usgs":false,"family":"Spencer","given":"Susan","email":"","middleInitial":"K.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":787509,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Lambert, Jane R.","contributorId":214334,"corporation":false,"usgs":false,"family":"de Lambert","given":"Jane","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":787510,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Anita C.","contributorId":214336,"corporation":false,"usgs":false,"family":"Anderson","given":"Anita C.","affiliations":[],"preferred":false,"id":787511,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rezania, Lih-in W.","contributorId":214337,"corporation":false,"usgs":false,"family":"Rezania","given":"Lih-in","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":787512,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kieke, Burney A","contributorId":195802,"corporation":false,"usgs":false,"family":"Kieke","given":"Burney","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":787513,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Borchardt, Mark A. 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and fluvial processes on riparian vegetation dynamics","docAbstract":"Plant community responses to biocontrol of invasive plants are understudied, despite the strong influence of the composition of replacement vegetation on ecosystem functions and services. We studied the vegetation response to a folivore beetle (Diorhabda genus, Coleoptera) that has been introduced along southwestern US river valleys to control the invasion of non-native shrubs in the genus Tamarix (Tamaricaceae). We collected detailed plant compositional and environmental data during four different surveys over 7 years (2010–2017), including two surveys prior to when substantial beetle-induced dieback occurred in summer 2012, along the lower Virgin River, Nevada. The study river was of special interest because it is one of only a few largely unregulated rivers in the region, and a large flood of 40-year return period occurred between the first and second surveys, allowing us to study the combined effects of fluvial processes, which typically drive riparian plant community assembly, and biocontrol. Vegetation trajectories differed as a function of the dominant geomorphological process. Tamarix cover declined an average of 75% and was replaced by the native shrub Pluchea sericea as the new dominant species in the floodplain, especially where sediment deposition predominated. Following deposition, and especially erosion, opportunistic native herbs, Tamarix seedlings, and noxious weeds colonized the understory layer but did not increase in cover over time. Stands of the native shrub Salix exigua, a desirable replacement species following Tamarix control, only increased slightly and remained subordinate in the floodplain. Overall, our results showed that, by successfully controlling the target non-native plant, a biocontrol agent can substantially modify the replacement plant communities in a riparian system, but that fluvial processes also strongly influence the resulting communities.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-020-02259-9","usgsCitation":"Gonzalez, E., Shafroth, P., Lee, S.R., Ostoja, S., and Brooks, M.L., 2020, Combined effects of biological control of an invasive shrub and fluvial processes on riparian vegetation dynamics: Biological Invasions, v. 22, p. 2339-2356, https://doi.org/10.1007/s10530-020-02259-9.","productDescription":"18 p.","startPage":"2339","endPage":"2356","ipdsId":"IP-117377","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":437028,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97KZJGP","text":"USGS data release","linkHelpText":"Riparian vegetation, topography, sediment quality and river corridor geomorphology in the Lower Virgin River 2010-2017"},{"id":375517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Nevada, Utah","otherGeospatial":"Virgin River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.55419921875,\n 36.328402729422656\n ],\n [\n -113.02734374999999,\n 36.328402729422656\n ],\n [\n -113.02734374999999,\n 37.496652341233364\n ],\n [\n -115.55419921875,\n 37.496652341233364\n ],\n [\n -115.55419921875,\n 36.328402729422656\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","noUsgsAuthors":false,"publicationDate":"2020-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Gonzalez, Eduardo","contributorId":225181,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Eduardo","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":790705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":790706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Steven R. 0000-0002-4581-3684 srlee@usgs.gov","orcid":"https://orcid.org/0000-0002-4581-3684","contributorId":5630,"corporation":false,"usgs":true,"family":"Lee","given":"Steven","email":"srlee@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":790707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ostoja, Steven M.","contributorId":225183,"corporation":false,"usgs":false,"family":"Ostoja","given":"Steven M.","affiliations":[{"id":32922,"text":"USDA California Climate Hub","active":true,"usgs":false}],"preferred":false,"id":790708,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":790709,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70209419,"text":"70209419 - 2020 - The relation of geogenic contaminants to groundwater age, aquifer hydrologic position, water type, and redox conditions in Atlantic and Gulf Coastal Plain aquifers, eastern and south-central USA","interactions":[],"lastModifiedDate":"2020-04-08T14:08:17.456546","indexId":"70209419","displayToPublicDate":"2020-04-08T09:03:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"The relation of geogenic contaminants to groundwater age, aquifer hydrologic position, water type, and redox conditions in Atlantic and Gulf Coastal Plain aquifers, eastern and south-central USA","docAbstract":"Groundwater age distributions developed from carbon-14 (14C), tritium (3H), and helium-4 (4He) concentrations, along with aquifer hydrologic position, water type, and redox conditions, were compared to geogenic contaminants of concern (GCOC) from 252 public-supply wells in six Atlantic and Gulf Coastal Plain unconsolidated-sediment aquifers. Concentrations of one or more GCOCs in 168 (67%) wells exceeded MCLs (maximum contaminant levels), SMCLs (secondary MCLs), or HBSLs (health-based screening levels). Human-health benchmark thresholds (MCLs or HBSLs) were exceeded in 31 (12%) wells, and included 0.8% for fluoride (F), 2.4% for arsenic (As), 4% for lead-210 (210Pb), and 4.8% for polonium-210 (210Po). Values of pH increase with age and were outside the SMCL in 31% of wells (23% < 6.5 and 7.5% > 8.5, SMCL). Among GCOCs with concentrations that increased significantly with groundwater age, the frequency of sentry threshold exceedances (i.e., one-half of MCL, SMCL, or HBSL) included 40% for dissolved solids (DS), 12% for chloride (Cl), 3.6% for F, 4.4% for As, and 9.1% for 210Po. Iron (Fe) concentrations did not correlate with groundwater age but exceeded sentry thresholds in 29% of wells. Groundwater age, water types, redox, pH, and GCOCs varied because of unique hydrogeologic features of the aquifers (recharge locations and geometry). As expected, primarily confined aquifers had young, oxic, low to near-neutral pH water near the outcrop (recharge area), and older, reduced, high pH water deeper and farther along flow paths. However, unique aquifer hydrogeologic conditions, such as multiple-recharge zones produced anomalous patterns of young and old groundwater at varying depths and locations along flow paths. Evidence for this variability is seen in disequilibrium patterns in the progression of the chemical evolution of groundwater with hydrologic position. 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Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":786440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Levitt, Joseph Patrick 0000-0002-2058-9516","orcid":"https://orcid.org/0000-0002-2058-9516","contributorId":223857,"corporation":false,"usgs":true,"family":"Levitt","given":"Joseph","email":"","middleInitial":"Patrick","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Szabo, Zoltan 0000-0002-0760-9607","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":203408,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":786442,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209463,"text":"70209463 - 2020 - Seismic and geodetic progression of the 2018 summit caldera collapse of Kīlauea Volcano","interactions":[],"lastModifiedDate":"2020-04-09T12:39:04.12856","indexId":"70209463","displayToPublicDate":"2020-04-08T07:36:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Seismic and geodetic progression of the 2018 summit caldera collapse of Kīlauea Volcano","docAbstract":"The 2018 eruption of Kīlauea volcano, Hawaiʻi, resulted in a major collapse of the summit caldera along with an effusive eruption in the lower East Rift Zone. The caldera collapse comprised 62 highly similar collapse cycles of strong ground deformation and earthquake swarms that ended with a magnitude 5 collapse event and one partial cycle that did not end with a collapse event. We analyzed geodetic and seismic data to better understand how the caldera collapse progressed over 3 months of activity, focusing on the cyclical activity. We identified 3 main phases of collapse: initial ring-fault activation and small explosions (Phase 1), an eastward shift in activity and freeing of the central piston (Phase 2), and a recoupling of the piston to the reservoir followed by relatively steady behavior until the eruption’s end (Phase 3). Additionally, we observed geodetic evidence of tangential motion from the localization of the main ring fault (Phase 2) and the formation of a major peripheral ring fault on the eastern side of the collapse caldera during Phase 3. Both geodetic and seismic parameters suggest that the collapse may have had an eastward-component of motion after the ring fault system had formed. The cyclical seismic and geodetic parameters show no obvious signs that the collapse was coming to an end, with the only notable change being a significant increase in the ratio of cyclical displacement to co-collapse displacement observed during the last complete cycle on GNSS stations outside the caldera region.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2020.116250","collaboration":"","usgsCitation":"Tepp, G., Hotovec-Ellis, A.J., Shiro, B., Johanson, I.A., Thelen, W., and Haney, M.M., 2020, Seismic and geodetic progression of the 2018 summit caldera collapse of Kīlauea Volcano: Earth and Planetary Science Letters, v. 540, 116250, https://doi.org/10.1016/j.epsl.2020.116250.","productDescription":"116250","ipdsId":"IP-114024","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":457144,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2020.116250","text":"Publisher Index Page"},{"id":373856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.31097412109372,\n 19.391477141932153\n ],\n [\n -155.2313232421875,\n 19.391477141932153\n ],\n [\n -155.2313232421875,\n 19.43454305903574\n ],\n [\n -155.31097412109372,\n 19.43454305903574\n ],\n [\n -155.31097412109372,\n 19.391477141932153\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"540","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tepp, Gabrielle 0000-0001-5388-5138","orcid":"https://orcid.org/0000-0001-5388-5138","contributorId":206305,"corporation":false,"usgs":true,"family":"Tepp","given":"Gabrielle","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":786571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hotovec-Ellis, Alicia J. 0000-0003-1917-0205","orcid":"https://orcid.org/0000-0003-1917-0205","contributorId":211785,"corporation":false,"usgs":true,"family":"Hotovec-Ellis","given":"Alicia","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":786572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shiro, Brian 0000-0001-8756-288X","orcid":"https://orcid.org/0000-0001-8756-288X","contributorId":204040,"corporation":false,"usgs":true,"family":"Shiro","given":"Brian","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":786573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johanson, Ingrid A. 0000-0002-6049-2225","orcid":"https://orcid.org/0000-0002-6049-2225","contributorId":215613,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":786574,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thelen, Weston 0000-0003-2534-5577","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":215530,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":786575,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":786576,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209466,"text":"70209466 - 2020 - Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932","interactions":[],"lastModifiedDate":"2020-07-09T14:47:53.051322","indexId":"70209466","displayToPublicDate":"2020-04-08T07:04:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932","title":"Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932","docAbstract":"With the global-scale loss of biodiversity, current restoration programs have been often required as part of conservation plans for species richness and ecosystem integrity. The restoration of pelagic-oriented cisco (Coregonus artedi) has been an interest of Lake Michigan managers because it may increase the diversity and resilience of the fish assemblages and conserve the integrity of the ecosystems in a changing environment. To inform restoration, we described historical habitat use of cisco by analyzing a unique fishery-independent dataset collected in 1930–1932 by the U.S. Bureau of Fisheries’ first research vessel Fulmar and a commercial catch dataset reported by the State of Michigan in the same period, both based on gear fished on the bottom. Our results confirmed that the two major embayments, Green Bay and Grand Traverse Bay, were important habitats for cisco and suggest that cisco could complete the entire lifecycle within either of the Bays as there was no lack of summer feeding and fall spawning habitats. Seasonally, our results showed that cisco stayed in nearshore waters in spring, migrated to offshore waters in summer, and then migrated back to nearshore waters in fall for spawning. The results also suggest that in summer, most ciscoes were in waters with bottom depths of 20–70 m, but the highest cisco density occurred in waters with a bottom depth around 40 m. We highlight the importance of embayment habitats to cisco restoration and the seasonal migration pattern of cisco identified in this study, which suggests that a restored cisco population can diversify the food web by occupying different habitats from the exotic fishes that now dominate the pelagic waters of Lake Michigan.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0231420","usgsCitation":"Kao, Y., Bunnell, D., Eshenroder, R.L., and Murray, D.N., 2020, Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932: PLoS ONE, v. 15, no. 4, e0231420, 21 p., https://doi.org/10.1371/journal.pone.0231420.","productDescription":"e0231420, 21 p.","ipdsId":"IP-112754","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":457149,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0231420","text":"Publisher Index Page"},{"id":437032,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JMLWER","text":"USGS data release","linkHelpText":"1930-1932 Gill net data from Lake Michigan"},{"id":373854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.1875,\n 41.541477666790286\n ],\n [\n -86.46240234375,\n 41.83682786072714\n ],\n [\n -85.97900390625,\n 42.79540065303723\n ],\n [\n -86.4404296875,\n 43.67581809328341\n ],\n [\n -85.869140625,\n 44.74673324024678\n ],\n [\n -85.4736328125,\n 44.63739123445585\n ],\n [\n -84.52880859375,\n 45.82879925192134\n ],\n [\n -85.18798828125,\n 46.27103747280261\n ],\n [\n -86.0888671875,\n 46.13417004624326\n ],\n [\n -87.38525390624999,\n 45.78284835197676\n ],\n [\n -87.978515625,\n 45.01141864227728\n ],\n [\n -88.1982421875,\n 44.449467536006935\n ],\n [\n -88.06640625,\n 44.402391829093915\n ],\n [\n -87.451171875,\n 44.933696389694674\n ],\n [\n -87.099609375,\n 45.182036837015886\n ],\n [\n -87.4951171875,\n 44.512176171071054\n ],\n [\n -87.7587890625,\n 43.8028187190472\n ],\n [\n -88.00048828124999,\n 42.94033923363181\n ],\n [\n -87.890625,\n 42.407234661551875\n ],\n [\n -87.71484375,\n 41.902277040963696\n ],\n [\n -87.1875,\n 41.541477666790286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Kao, Yu-Chun","contributorId":35626,"corporation":false,"usgs":false,"family":"Kao","given":"Yu-Chun","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":786603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David 0000-0003-3521-7747","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":217344,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":786604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eshenroder, Randy L.","contributorId":177867,"corporation":false,"usgs":false,"family":"Eshenroder","given":"Randy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":786605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murray, Devin N. 0000-0003-1429-6669","orcid":"https://orcid.org/0000-0003-1429-6669","contributorId":223909,"corporation":false,"usgs":false,"family":"Murray","given":"Devin","email":"","middleInitial":"N.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":786606,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70212842,"text":"70212842 - 2020 - The impact is in the details: Evaluating a standardized protocol and scale for determining non-native insect impact","interactions":[],"lastModifiedDate":"2020-08-31T14:31:47.909529","indexId":"70212842","displayToPublicDate":"2020-04-03T09:27:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"The impact is in the details: Evaluating a standardized protocol and scale for determining non-native insect impact","docAbstract":"Assessing the ecological and economic impacts of non-native species is crucial to providing managers and policymakers with the information necessary to respond effectively. Most non-native species have minimal impacts on the environment in which they are introduced, but a small fraction are highly deleterious. The definition of ‘damaging’ or ‘high-impact’ varies based on the factors determined to be valuable by an individual or group, but interpretations of whether non-native species meet particular definitions can be influenced by the interpreter’s bias or level of expertise, or lack of group consensus. Uncertainty or disagreement about an impact classification may delay or otherwise adversely affect policymaking on management strategies. One way to prevent these issues would be to have a detailed, nine-point impact scale that would leave little room for interpretation and then divide the scale into agreed upon categories, such as low, medium, and high impact. Following a previously conducted, exhaustive search regarding non-native, conifer-specialist insects, the authors independently read the same sources and scored the impact of 41 conifer-specialist insects to determine if any variation among assessors existed when using a detailed impact scale. Each of the authors, who were selected to participate in the working group associated with this study because of their diverse backgrounds, also provided their level of expertise and uncertainty for each insect evaluated. We observed 85% congruence in impact rating among assessors, with 27% of the insects having perfect inter-rater agreement. Variance in assessment peaked in insects with a moderate impact level, perhaps due to ambiguous information or prior assessor perceptions of these specific insect species. The authors also participated in a joint fact-finding discussion of two insects with the most divergent impact scores to isolate potential sources of variation in assessor impact scores. We identified four themes that could be experienced by impact assessors: ambiguous information, discounted details, observed versus potential impact, and prior knowledge. To improve consistency in impact decision-making, we encourage groups to establish a detailed scale that would allow all observed and published impacts to fall under a particular score, provide clear, reproducible guidelines and training, and use consensus-building techniques when necessary.
","language":"English","publisher":"PenSoft","doi":"10.3897/neobiota.55.38981","usgsCitation":"Schulz, A.N., Mech, A.M., Allen, C., Ayres, M.P., Gandhi, K., Gurevitch, J., Havill, N.P., Herms, D.A., Hufbauer, R.A., Liebhold, A.M., Raffa, K.F., Raupp, M.J., Thomas, K.A., Tobin, P.C., and Marsico, T.D., 2020, The impact is in the details: Evaluating a standardized protocol and scale for determining non-native insect impact: NeoBiota, v. 55, p. 61-83, https://doi.org/10.3897/neobiota.55.38981.","productDescription":"13 p.","startPage":"61","endPage":"83","ipdsId":"IP-099057","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":457164,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.55.38981","text":"Publisher Index Page"},{"id":378028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","noUsgsAuthors":false,"publicationDate":"2020-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Schulz, Ashley N.","contributorId":219894,"corporation":false,"usgs":false,"family":"Schulz","given":"Ashley","email":"","middleInitial":"N.","affiliations":[{"id":40088,"text":"Department of Biological Sciences, Arkansas State University, Jonesboro, AR","active":true,"usgs":false}],"preferred":false,"id":797634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mech, Angela M.","contributorId":219892,"corporation":false,"usgs":false,"family":"Mech","given":"Angela","email":"","middleInitial":"M.","affiliations":[{"id":40087,"text":"School of Environmental and Forest Sciences, University of Washington, Seattle, WA. Corresponding email: ammech@wcu.edu. Present address: Department of Geosciences and Natural Resources, Western Carolina University, Cullowhee, NC","active":true,"usgs":false}],"preferred":false,"id":797635,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig 0000-0001-8655-8227 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8227","contributorId":219896,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":797636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ayres, Matthew P.","contributorId":219897,"corporation":false,"usgs":false,"family":"Ayres","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":35787,"text":"Department of Biological Sciences, Dartmouth College, Hanover, NH","active":true,"usgs":false}],"preferred":false,"id":797637,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gandhi, Kamal J.K.","contributorId":219898,"corporation":false,"usgs":false,"family":"Gandhi","given":"Kamal J.K.","affiliations":[{"id":40090,"text":"D.B. Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA","active":true,"usgs":false}],"preferred":false,"id":797638,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gurevitch, Jessica","contributorId":219899,"corporation":false,"usgs":false,"family":"Gurevitch","given":"Jessica","email":"","affiliations":[{"id":33447,"text":"Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY","active":true,"usgs":false}],"preferred":false,"id":797639,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Havill, Nathan P.","contributorId":219900,"corporation":false,"usgs":false,"family":"Havill","given":"Nathan","email":"","middleInitial":"P.","affiliations":[{"id":40091,"text":"Northern Research Station, USDA Forest Service, Hamden, CT","active":true,"usgs":false}],"preferred":false,"id":797640,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Herms, Daniel A.","contributorId":219895,"corporation":false,"usgs":false,"family":"Herms","given":"Daniel","email":"","middleInitial":"A.","affiliations":[{"id":40089,"text":"The Davey Tree Expert Company, Kent, OH","active":true,"usgs":false}],"preferred":false,"id":797641,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hufbauer, Ruth A.","contributorId":219901,"corporation":false,"usgs":false,"family":"Hufbauer","given":"Ruth","email":"","middleInitial":"A.","affiliations":[{"id":40092,"text":"Department of Bioagricultural Science and Pest Management, Colorado State University, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":797642,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Liebhold, Andrew M.","contributorId":219902,"corporation":false,"usgs":false,"family":"Liebhold","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":40093,"text":"USDA Forest Service Northern Research Station, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":797643,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Raffa, Kenneth F.","contributorId":219903,"corporation":false,"usgs":false,"family":"Raffa","given":"Kenneth","email":"","middleInitial":"F.","affiliations":[{"id":40094,"text":"Department of Entomology, University of Wisconsin, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":797644,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Raupp, Michael J.","contributorId":239692,"corporation":false,"usgs":false,"family":"Raupp","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":47979,"text":"University of Maryland, Department of Entomology, 4112 Plant Sciences Building, College Park, MD 20742, USA","active":true,"usgs":false}],"preferred":false,"id":797645,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":797646,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Tobin, Patrick C.","contributorId":200172,"corporation":false,"usgs":false,"family":"Tobin","given":"Patrick","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":797647,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Marsico, Travis D.","contributorId":219893,"corporation":false,"usgs":false,"family":"Marsico","given":"Travis","email":"","middleInitial":"D.","affiliations":[{"id":40088,"text":"Department of Biological Sciences, Arkansas State University, Jonesboro, AR","active":true,"usgs":false}],"preferred":false,"id":797648,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70211966,"text":"70211966 - 2020 - Runoff-initiated post-fire debris flow Western Cascades, Oregon","interactions":[],"lastModifiedDate":"2020-08-12T20:57:19.586297","indexId":"70211966","displayToPublicDate":"2020-04-01T15:54:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Runoff-initiated post-fire debris flow Western Cascades, Oregon","docAbstract":"Wildfires dramatically alter the hydraulics and root reinforcement of soil on forested hillslopes, which can promote the generation of debris flows. In the Pacific Northwest, post-fire shallow landsliding has been well documented and studied, but the potential role of runoff-initiated debris flows is not well understood and only one previous to 2018 had been documented in the region. On 20 June 2018, approximately 1 year after the Milli fire burned 24,000 acres, a runoff-initiated debris flow occurred on the flanks of Black Crater in the Oregon Cascade Range. The debris flow was initiated via dispersed rilling on > 30-degree slopes near the crater rim and traveled > 1.5 km downslope. We measured exceptionally low soil infiltration rates at the study site, likely due to high burn severity during the Milli fire. Based on nearby 5-min rain gage data, we quantified rainfall rates for the storm event that triggered the debris flow. Our results show that peak 15-min rainfall rates were 25.4 mmh−1, equaling or exceeding the measured infiltration rates at the study site, which had a geometric mean of ~ 24 mmh−1. Field mapping shows that high burn severity resulted in the initiation of the debris flow and that convergent and steep topography promoted the development of a debris flow at this site. As wildfires increase in frequency and intensity across the western USA, the Pacific Northwest could become more susceptible to runoff-initiated debris flows. Therefore, characterization of the conditions that resulted in this debris flow is crucial for understanding how runoff-initiated debris flows may shape terrain and impact hazards in the Pacific Northwest.
","language":"English","publisher":"Springerlink","doi":"10.1007/s10346-020-01376-9","usgsCitation":"Wall, S., Roering, J., and Rengers, F.K., 2020, Runoff-initiated post-fire debris flow Western Cascades, Oregon: Landslides, v. 17, p. 1649-1661, https://doi.org/10.1007/s10346-020-01376-9.","productDescription":"13 p.","startPage":"1649","endPage":"1661","ipdsId":"IP-114420","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":377441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Western Cascades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.882080078125,\n 43.23719944365308\n ],\n [\n -121.695556640625,\n 43.23719944365308\n ],\n [\n -121.695556640625,\n 45.26715476332791\n ],\n [\n -122.882080078125,\n 45.26715476332791\n ],\n [\n -122.882080078125,\n 43.23719944365308\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2020-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Wall, Sara","contributorId":238092,"corporation":false,"usgs":false,"family":"Wall","given":"Sara","email":"","affiliations":[{"id":33615,"text":"Carleton College","active":true,"usgs":false}],"preferred":false,"id":796002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roering, J.J.","contributorId":238093,"corporation":false,"usgs":false,"family":"Roering","given":"J.J.","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":796003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":796004,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70206592,"text":"sir20195128 - 2020 - Hydrogeology and shallow groundwater quality in the tidal Anacostia River watershed, Washington, D.C.","interactions":[],"lastModifiedDate":"2022-04-25T19:32:37.833436","indexId":"sir20195128","displayToPublicDate":"2020-04-01T10:00:00","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":"2019-5128","displayTitle":"Hydrogeology and Shallow Groundwater Quality in the Tidal Anacostia River Watershed, Washington, D.C.","title":"Hydrogeology and shallow groundwater quality in the tidal Anacostia River watershed, Washington, D.C.","docAbstract":"Groundwater hydrology and geochemistry within the tidal Anacostia River watershed of Washington, D.C. are related to natural and human influences. The U.S. Geological Survey, in cooperation with the District Department of Energy & Environment, began investigating the hydrogeology and groundwater quality of the watershed in 2002. Lithologic coring, groundwater-level and tidal monitoring, and water-quality sampling have been conducted to improve understanding of the groundwater-flow system, geochemistry, water quality, and the likely interaction between groundwater and the tidal Anacostia River. The flow and interaction of shallow groundwater with the tidal Anacostia River and other area streams are affected by diversions, pumping, land reclamation, and other human activities in this highly urbanized watershed.
The tidal Anacostia River watershed is underlain by a wedge of unconsolidated sediments that is part of the Atlantic Coastal Plain Physiographic Province. These sediments form a system of confined and unconfined aquifers. The coarse sediments of the Potomac Group sand-dominated lithofacies form the Patuxent aquifer. The Patuxent aquifer crops out and subcrops in the northwestern part of the study area, but is confined to the southeast by the overlying Potomac Group clay-dominated lithofacies. Overlying the Potomac Group is a series of interbedded sands and clays that form an unconfined surficial aquifer system. Regional correlation in the unconfined surficial aquifer system is complicated by local heterogeneity in aquifer sediments. Local perched and semi-confined conditions occur in some areas.
Recharge of the confined Patuxent aquifer occurs primarily in the outcrop and subcrop area, although some recharge may also occur through overlying confining units. Recharge to the unconfined surficial aquifer system occurs through infiltration of precipitation and possible artificial recharge from structures such as underground water or sewer pipes. In the Patuxent aquifer, hydraulic gradients indicate downward movement in the outcrop area, whereas hydraulic heads beneath the Anacostia River are higher than land surface, indicating an upward hydraulic gradient. In the unconfined surficial aquifer system, groundwater generally flows from upland recharge areas towards discharge areas near the Anacostia River and its tributaries. Groundwater from the confined part of the Patuxent aquifer also may discharge to the Anacostia River in locations where the overlying clay-dominated lithofacies of the Potomac Group is absent as a result of past geologic and (or) alluvial processes.
Geochemistry and groundwater quality are affected by hydrologic conditions as well as anthropogenic influences. Local variability in groundwater quality reflects local variability in hydrogeologic conditions and sources of chemicals. Groundwater ranges from anoxic and iron- or calcium-bicarbonate type, to oxic with elevated nitrate. The occurrence and distribution of pesticides, volatile organic compounds, and other selected chemical compounds in groundwater reflect the multitude of sources common to urban areas, as well as variable hydrogeologic and geochemical conditions that affect their fate and transport in the environment. Overall, concentrations of only a few of the over 200 chemical constituents included in laboratory analyses exceeded regulatory standards or guidance values. These include tetrachloroethene and arsenic, which were each detected one time in different wells. There were also several detections of iron and manganese that exceeded regulatory standards or guidance values that are associated with reducing conditions in aquifer sediments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195128","usgsCitation":"Ator, S.W., Denver, J.M., and Dieter, C.A., 2020, Hydrogeology and shallow groundwater quality in the tidal Anacostia River watershed, Washington, D.C.: U.S. Geological Survey Scientific Investigations Report 2019-5128, 93 p., https://doi.org/10.3133/sir20195128.","productDescription":"Report: viii, 93 p.; 6 Appendixes","numberOfPages":"106","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-039169","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":373579,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix5.pdf","text":"Appendix 5","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- South Capitol Street Geotechnical Report, MACTEC Engineering and Consulting, Inc., 2005 (reproduced with permission)"},{"id":399609,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109888.htm"},{"id":373578,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix4d.txt","text":"Appendix 4d","size":"1.45 MB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Tide Levels at USGS Station 01651750, Anacostia River Aquatic Gardens at Washington, D.C., 2007"},{"id":373577,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix4c.txt","text":"Appendix 4c","size":"1.97 MB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Tide Levels at USGS Station 01651750, Anacostia River Aquatic Gardens at Washington, D.C., 2006"},{"id":373569,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5128/coverthb.jpg"},{"id":373570,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128.pdf","text":"Report","size":"3.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5128"},{"id":373575,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix4a.txt","text":"Appendix 4a","size":"1.20 MB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Tide Levels at USGS Station 01651750, Anacostia River Aquatic Gardens at Washington, D.C., 2004"},{"id":373576,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix4b.txt","text":"Appendix 4b","size":"2.08 MB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Tide Levels at USGS Station 01651750, Anacostia River Aquatic Gardens at Washington, D.C., 2005"},{"id":373574,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5128/sir20195128_appendix3.xlsx","text":"Appendix 3","size":"59.4 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Instantaneous Groundwater-Level Measurements Collected at Selected Sites in the Anacostia River Watershed, 2002–11"}],"country":"United States","state":"Washington, D.C.","otherGeospatial":"Tidal Anacostia River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.1185302734375,\n 38.79048618862274\n ],\n [\n -76.93313598632812,\n 38.79048618862274\n ],\n [\n -76.93313598632812,\n 38.93698019310818\n ],\n [\n -77.1185302734375,\n 38.93698019310818\n ],\n [\n -77.1185302734375,\n 38.79048618862274\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Plague is a bacterial zoonosis of mammalian hosts and flea vectors. The disease is capable of ravaging rodent populations and transforming ecosystems. Because plague mortality is likely to be predicted by flea parasitism, it is critical to understand vector dynamics. It has been hypothesized that paltry precipitation and reduced vegetative production predispose herbivorous rodents to malnourishment and flea parasitism, and flea parasitism varies directly with plague mortality. We evaluated these hypotheses on five colonies of Utah prairie dogs (UPDs; Cynomys parvidens), on the Awapa Plateau, Utah, US, in 2013–16. Ten flea species were identified among 3,257 fleas from UPDs. These 10 flea species parasitize prairie dogs, mice, rats, voles, ground squirrels, chipmunks, and marmots, all known hosts of plague. The abundance of fleas on individual UPDs (1,198 observations) varied inversely with UPD body condition; fleas were most abundant on lightweight, malnourished UPDs. Flea abundance on UPDs was highest in dry years that were preceded by wet years. Increased precipitation and soil moisture in the prior year might generate humid microclimates in UPD burrows (that could facilitate flea survival and reproduction) and paltry precipitation in the current year could predispose UPDs to malnourishment and flea parasitism. Annual re-encounter rates for UPDs (1,072 observations) were reduced in wetter years preceded by drier years; reduced precipitation and vegetative production might kill UPDs, and increased flea densities in drier years could provide conditions for plague transmission (and UPD mortality) when moisture returns. Re-encounter rates were reduced for UPDs carrying at least one flea compared to UPDs with no detected fleas. These results support the hypothesis that reduced precipitation in the current year predisposes UPDs to flea parasitism. Our results also suggest a link between flea parasitism and UPD mortality. Given documented connections between flea parasitism and plague transmission, our results point toward an effect of flea parasitism on plague-related deaths for individual UPDs, a phenomenon rarely investigated in nature.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2019-08-201","usgsCitation":"Eads, D.A., Abbott, R.C., Biggins, D.E., and Rocke, T.E., 2020, Flea parasitism and host survival in a plague-relevant system: Theoretical and conservation implications: Journal of Wildlife Diseases, v. 56, no. 2, p. 378-387, https://doi.org/10.7589/2019-08-201.","productDescription":"10 p.","startPage":"378","endPage":"387","ipdsId":"IP-112909","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":437045,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IG320C","text":"USGS data release","linkHelpText":"Data on Flea Parasitism and Annual Re-encounters of Utah Prairie Dogs at 5 colonies on the Awapa Plateau, Utah, USA, 2013-2016"},{"id":387804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Awapa Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.85317993164062,\n 38.10916794391597\n ],\n [\n -111.69731140136719,\n 38.10916794391597\n ],\n [\n -111.69731140136719,\n 38.24087667992996\n ],\n [\n -111.85317993164062,\n 38.24087667992996\n ],\n [\n -111.85317993164062,\n 38.10916794391597\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":820904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abbott, Rachel C. 0000-0003-4820-9295 rabbott@usgs.gov","orcid":"https://orcid.org/0000-0003-4820-9295","contributorId":1183,"corporation":false,"usgs":true,"family":"Abbott","given":"Rachel","email":"rabbott@usgs.gov","middleInitial":"C.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":820905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":820906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":820907,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209481,"text":"70209481 - 2020 - Multiple mechanisms determine the effect of warming on plant litter decomposition in a dryland","interactions":[],"lastModifiedDate":"2020-08-07T12:59:03.003161","indexId":"70209481","displayToPublicDate":"2020-03-31T06:20:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3416,"text":"Soil Biology and Biochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Multiple mechanisms determine the effect of warming on plant litter decomposition in a dryland","docAbstract":"In drylands, where soil fertility is typically low, plant litter decomposition provides particularly critical carbon and nitrogen inputs into soil. Although climate change is projected to increase the already large global extent of drylands, it is unknown how warmer temperatures will affect core ecosystem processes, such as plant litter decomposition, in these systems. To address this key unknown, we conducted a litterbag study in a long-term dryland warming experiment in southeastern Utah, USA. Unexpectedly, we did not find an overall effect of warming on leaf litter mass loss over time. Instead, our results indicated both positive and negative effects of warming on mass loss which offset one another. In particular, our findings suggested that a warming-induced degradation of biological soil crusts (soil surface community of mosses, lichens, and/or cyanobacteria that live in drylands worldwide) increased soil-litter mixing, thereby accelerating decomposition. Results also suggested that warming-induced decreases in litter moisture slowed decomposition. In addition to assessing mass loss, we found that warming lowered the carbon-to-nitrogen ratio of the decomposing litter. These results showed that warming did not alter the total litter mass-loss rates in this ecosystem, but that decomposition patterns were affected through more nuanced changes to both the biological and physical environment of dryland soils.","language":"English","publisher":"Elsevier","doi":"10.1016/j.soilbio.2020.107799","usgsCitation":"Chuckran, P.F., Reibold, R.H., Throop, H.L., and Reed, S., 2020, Multiple mechanisms determine the effect of warming on plant litter decomposition in a dryland: Soil Biology and Biochemistry, v. 145, 107799, 7 p., https://doi.org/10.1016/j.soilbio.2020.107799.","productDescription":"107799, 7 p.","ipdsId":"IP-108550","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":457229,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1608374","text":"Publisher Index Page"},{"id":373884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","city":"Castle Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.70878601074219,\n 38.4514377951069\n ],\n [\n -109.18556213378906,\n 38.4514377951069\n ],\n [\n -109.18556213378906,\n 38.800654269933005\n ],\n [\n -109.70878601074219,\n 38.800654269933005\n ],\n [\n -109.70878601074219,\n 38.4514377951069\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chuckran, Peter F.","contributorId":223956,"corporation":false,"usgs":false,"family":"Chuckran","given":"Peter","email":"","middleInitial":"F.","affiliations":[{"id":40809,"text":"Center for Ecosystem Science and Society (ECOSS), Northern Arizona University, Box 5620, Flagstaff, AZ 86011, USA","active":true,"usgs":false}],"preferred":false,"id":786709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reibold, Robin H. 0000-0002-3323-487X","orcid":"https://orcid.org/0000-0002-3323-487X","contributorId":207499,"corporation":false,"usgs":true,"family":"Reibold","given":"Robin","email":"","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":786710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Throop, Heather L. 0000-0002-7963-4342","orcid":"https://orcid.org/0000-0002-7963-4342","contributorId":139051,"corporation":false,"usgs":false,"family":"Throop","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":12633,"text":"Biology Department, New Mexico State University, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":786711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":786712,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210069,"text":"70210069 - 2020 - Operational global actual evapotranspiration: Development, evaluation, and dissemination","interactions":[],"lastModifiedDate":"2020-05-13T14:25:13.766951","indexId":"70210069","displayToPublicDate":"2020-03-30T09:21:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Operational global actual evapotranspiration: Development, evaluation, and dissemination","docAbstract":"Satellite-based actual evapotranspiration (ETa) is becoming increasingly reliable and available for various water management and agricultural applications from water budget studies to crop performance monitoring. The Operational Simplified Surface Energy Balance (SSEBop) model is currently used by the US Geological Survey (USGS) Famine Early Warning System Network (FEWS NET) to routinely produce and post multitemporal ETa and ETa anomalies online for drought monitoring and early warning purposes. Implementation of the global SSEBop using the Aqua satellite’s Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and global gridded weather datasets is presented. Evaluation of the SSEBop ETa data using 12 eddy covariance (EC) flux tower sites over six continents indicated reasonable performance in capturing seasonality with a correlation coefficient up to 0.87. However, the modeled ETa seemed to show regional biases whose natures and magnitudes require a comprehensive investigation using complete water budgets and more quality-controlled EC station datasets. While the absolute magnitude of SSEBop ETa would require a one-time bias correction for use in water budget studies to address local or regional conditions, the ETa anomalies can be used without further modifications for drought monitoring. All ETa products are freely available for download from the USGS FEWS NET website.
","language":"English","publisher":"MDPI","doi":"10.3390/s20071915","collaboration":"","usgsCitation":"Senay, G., Kagone, S., and Velpuri, N.M., 2020, Operational global actual evapotranspiration: Development, evaluation, and dissemination, v. 7, no. 20, 1915, 18 p., https://doi.org/10.3390/s20071915.","productDescription":"1915, 18 p.","ipdsId":"IP-116111","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":457241,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s20071915","text":"Publisher Index Page"},{"id":437046,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OUVUUI","text":"USGS data release","linkHelpText":"Operational Global Actual Evapotranspiration using the SSEBop model"},{"id":374752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"20","noUsgsAuthors":false,"publicationDate":"2020-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Senay, Gabriel 0000-0002-8810-8539","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":216910,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":788972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kagone, Stefanie 0000-0002-2979-4655","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":210980,"corporation":false,"usgs":true,"family":"Kagone","given":"Stefanie","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":788973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Velpuri, Naga M. 0000-0002-6370-1926","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":96183,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":788974,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70220206,"text":"70220206 - 2020 - Hillslope groundwater discharges provide localized ecosystem buffers from regional PFAS contamination in a gaining coastal stream","interactions":[],"lastModifiedDate":"2021-04-27T13:19:56.792469","indexId":"70220206","displayToPublicDate":"2020-03-29T08:04:39","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":"Hillslope groundwater discharges provide localized ecosystem buffers from regional PFAS contamination in a gaining coastal stream","docAbstract":"Emerging groundwater contaminants such as per- and polyfluoroalkyl substances (PFAS) may impact surface-water quality and groundwater-dependent ecosystems of gaining streams. Although complex near-surface hydrogeology of stream corridors challenges sampling efforts, recent advances in heat tracing of discharge zones enable efficient and informed data collection. For this study we used a combination of streambed temperature push-probe and thermal infrared methods to guide a discharge-zone-oriented sample collection along approximately 6 km of a coastal trout stream on Cape Cod, MA where groundwater discharge constitutes approximately 95% of total streamflow. Eight surface-water locations and discharging groundwater from 24 streambed and bank seepages were analyzed for dissolved oxygen, specific conductance, stable water isotopes, and a range of PFAS compounds which are contaminants of emerging concern in aquatic environments. The results indicate a complex system of groundwater discharge source flowpaths, where the sum of concentrations of six PFAS compounds (Environmental Protection Agency third Unregulated Contaminant Monitoring Rule UCMR 3) showed a median concentration of 52 331 (SD) ng/L with two higher outliers and three discharges with non-detection of PFAS. Higher UCMR 3 PFAS concentration was related -0.66 (Spearman Rank, p<0.001) to discharging groundwater that showed an evaporative signature (deuterium excess), indicating flow through at least one upgradient kettle lake. Therefore, more regional groundwater flowpaths originating from outside the local river corridor tended to show higher PFAS concentrations as evaluated at their respective discharge zones. Conversely, UCMR 3 PFAS concentrations were typically low at discharges that did not indicate evaporation and were adjacent to steep hillslopes and, therefore, were classified as locally recharged groundwater. Previous research at this stream found that the native brook trout favor discharge points of groundwater recharged on local hillslopes for spawning, likely in response to generally higher levels of dissolved oxygen compared to discharge zones located further away from hillslopes. Our study shows that the trout may thereby be avoiding emerging contaminants such as PFAS in groundwater recharged farther from the stream.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13752","usgsCitation":"Briggs, M.A., Tokranov, A.K., Hull, R.B., LeBlanc, D.R., Haynes, A., and Lane, J., 2020, Hillslope groundwater discharges provide localized ecosystem buffers from regional PFAS contamination in a gaining coastal stream: Hydrological Processes, v. 34, no. 10, p. 2281-2291, https://doi.org/10.1002/hyp.13752.","productDescription":"11 p.","startPage":"2281","endPage":"2291","ipdsId":"IP-117276","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":385320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod, Quashnet River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.24932861328125,\n 42.06356771883277\n ],\n [\n -70.2081298828125,\n 42.02481360781777\n ],\n [\n -70.1806640625,\n 42.01665183556825\n ],\n [\n -70.16693115234375,\n 42.032974332441405\n ],\n [\n -70.18890380859375,\n 42.04317376494972\n ],\n [\n -70.16143798828125,\n 42.06356771883277\n ],\n [\n -70.11199951171875,\n 42.04113400940807\n ],\n [\n -70.07904052734375,\n 41.92475971933975\n ],\n [\n -70.0653076171875,\n 41.89818843043047\n ],\n [\n -70.0543212890625,\n 41.920672548686824\n ],\n [\n -70.02960205078125,\n 41.92271616673922\n ],\n [\n -70.0213623046875,\n 41.887965758804484\n ],\n [\n -70.00762939453125,\n 41.81021999190292\n ],\n [\n -70.07080078125,\n 41.777456667491066\n ],\n [\n -70.125732421875,\n 41.76106872528616\n ],\n [\n -70.16693115234375,\n 41.75492216766298\n ],\n [\n -70.20263671875,\n 41.748775021355044\n ],\n [\n -70.257568359375,\n 41.7180304600481\n ],\n [\n -70.279541015625,\n 41.72828028223453\n ],\n [\n -70.345458984375,\n 41.74262728637672\n ],\n [\n -70.44158935546875,\n 41.75287318430239\n ],\n [\n -70.49102783203125,\n 41.77336007442076\n ],\n [\n -70.55145263671875,\n 41.775408403663285\n ],\n [\n -70.587158203125,\n 41.748775021355044\n ],\n [\n -70.6201171875,\n 41.73647896274239\n ],\n [\n -70.65582275390625,\n 41.68316883525891\n ],\n [\n -70.6475830078125,\n 41.64213096472801\n ],\n [\n -70.653076171875,\n 41.60312076451184\n ],\n [\n -70.64208984375,\n 41.57436130598913\n ],\n [\n -70.78765869140625,\n 41.47771800887871\n ],\n [\n -70.94146728515625,\n 41.42625319507269\n ],\n [\n -70.94970703125,\n 41.409775832009565\n ],\n [\n -70.86181640625,\n 41.41801503608024\n ],\n [\n -70.784912109375,\n 41.4509614012039\n ],\n [\n -70.653076171875,\n 41.51680395810118\n ],\n [\n -70.6201171875,\n 41.541477666790286\n ],\n [\n -70.5487060546875,\n 41.53531012183376\n ],\n [\n -70.48828125,\n 41.54764462357737\n ],\n [\n -70.4443359375,\n 41.588742636696765\n ],\n [\n -70.43060302734375,\n 41.60517452129933\n ],\n [\n -70.39764404296875,\n 41.60722821271717\n ],\n [\n -70.367431640625,\n 41.61749568924243\n ],\n [\n -70.3125,\n 41.6257084937525\n ],\n [\n -70.26580810546875,\n 41.60928183876483\n ],\n [\n -70.24108886718749,\n 41.6257084937525\n ],\n [\n -70.17791748046875,\n 41.65239288426814\n ],\n [\n -70.13946533203124,\n 41.65034063112266\n ],\n [\n -70.06805419921875,\n 41.66470503009207\n ],\n [\n -70.015869140625,\n 41.668808555620586\n ],\n [\n -69.98016357421875,\n 41.65239288426814\n ],\n [\n -70.0103759765625,\n 41.566141964768384\n ],\n [\n -70.0103759765625,\n 41.539421883822854\n ],\n [\n -69.9884033203125,\n 41.54764462357737\n ],\n [\n -69.98016357421875,\n 41.59490508367679\n ],\n [\n -69.92523193359375,\n 41.68316883525891\n ],\n [\n -69.93072509765625,\n 41.81431422987254\n ],\n [\n -69.97467041015625,\n 41.94927724511655\n ],\n [\n -70.048828125,\n 42.039094188385945\n ],\n [\n -70.13397216796875,\n 42.07783959017503\n ],\n [\n -70.21087646484375,\n 42.08803181932636\n ],\n [\n -70.24932861328125,\n 42.06356771883277\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tokranov, Andrea K. 0000-0003-4811-8641","orcid":"https://orcid.org/0000-0003-4811-8641","contributorId":255483,"corporation":false,"usgs":true,"family":"Tokranov","given":"Andrea","email":"","middleInitial":"K.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hull, Robert B. 0000-0002-0216-5250","orcid":"https://orcid.org/0000-0002-0216-5250","contributorId":215569,"corporation":false,"usgs":true,"family":"Hull","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":219907,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"","middleInitial":"R.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haynes, A.","contributorId":257634,"corporation":false,"usgs":false,"family":"Haynes","given":"A.","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":814759,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":814760,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211209,"text":"70211209 - 2020 - Intraspecific and biogeographical variation in foliar fungal communities and pathogen damage of native and invasive Phragmites australis","interactions":[],"lastModifiedDate":"2020-07-17T18:36:21.201033","indexId":"70211209","displayToPublicDate":"2020-03-26T13:31:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Intraspecific and biogeographical variation in foliar fungal communities and pathogen damage of native and invasive Phragmites australis","title":"Intraspecific and biogeographical variation in foliar fungal communities and pathogen damage of native and invasive Phragmites australis","docAbstract":"Recent research has highlighted that the relationship between species interactions and latitude can differ between native and invasive plant taxa, generating biogeographical heterogeneity in community resistance to plant invasions. In the first study with foliar pathogens, we tested whether co‐occurring native and invasive lineages of common reed (Phragmites australis ) exhibit non‐parallel latitudinal gradients in foliar fungal communities, pathogen susceptibility and damage, and whether these biogeographical patterns can influence the success of invasion.
North America.
2015–2017.
Perennial grass P. australis .
We surveyed 35 P. australis field populations, spanning 17° latitude and comprising four phylogeographical lineages, including one endemic to North America and one invasive from Europe. For each population, we quantified the percentage of leaf pathogen damage and cultured fungi from diseased leaves, which we identified using molecular tools. To assess whether latitudinal gradients in pathogen damage had a genetic basis, we inoculated plants from 73 populations with four putative pathogens in a complementary common garden experiment and measured P. australis susceptibility (i.e., diseased leaf area).
We isolated 84 foliar fungal taxa. Phragmites australis lineage influenced fungal community composition but not diversity. Despite the invasive European P. australis lineage being the least susceptible to three of the four pathogens tested in the common garden experiment, pathogen damage in the field was similar between native and invasive lineages, providing no evidence that release from foliar pathogens contributes to the success of invasion. Genetically based latitudinal gradients in pathogen susceptibility observed in the common garden were isolate specific and obscured by local environmental conditions in the field, where pathogen damage was threefold higher for northern compared with southern populations, regardless of lineage.
Our results highlight that host plant lineage and genetically based biogeographical gradients strongly influence foliar fungal communities and pathogen susceptibility, but do not translate to patterns of pathogen damage observed in the field.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.13097","usgsCitation":"Allen, W.J., Devries, A., Bologna, N.J., Bickford, W.A., Kowalski, K., Meyerson, L., and Cronin, J.T., 2020, Intraspecific and biogeographical variation in foliar fungal communities and pathogen damage of native and invasive Phragmites australis: Global Ecology and Biogeography, v. 29, no. 7, p. 1199-1211, https://doi.org/10.1111/geb.13097.","productDescription":"13 p.","startPage":"1199","endPage":"1211","ipdsId":"IP-113518","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":457261,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/geb.13097","text":"External Repository"},{"id":376479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Warwick J.","contributorId":229451,"corporation":false,"usgs":false,"family":"Allen","given":"Warwick","email":"","middleInitial":"J.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":793209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devries, Aaron","contributorId":229452,"corporation":false,"usgs":false,"family":"Devries","given":"Aaron","affiliations":[{"id":37768,"text":"USGS Contractor","active":true,"usgs":false}],"preferred":false,"id":793210,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bologna, Nicholas J.","contributorId":229453,"corporation":false,"usgs":false,"family":"Bologna","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":793211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bickford, Wesley A. 0000-0001-7612-1325 wbickford@usgs.gov","orcid":"https://orcid.org/0000-0001-7612-1325","contributorId":5687,"corporation":false,"usgs":true,"family":"Bickford","given":"Wesley","email":"wbickford@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":793212,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":793213,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meyerson, Laura A.","contributorId":229454,"corporation":false,"usgs":false,"family":"Meyerson","given":"Laura A.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":793214,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cronin, James T.","contributorId":229455,"corporation":false,"usgs":false,"family":"Cronin","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":793215,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70255608,"text":"70255608 - 2020 - Quantifying background nitrate removal mechanisms in an agricultural watershed with contrasting subcatchment baseflow concentrations","interactions":[],"lastModifiedDate":"2024-06-26T13:34:30.48224","indexId":"70255608","displayToPublicDate":"2020-03-25T08:28:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying background nitrate removal mechanisms in an agricultural watershed with contrasting subcatchment baseflow concentrations","docAbstract":"Numerous studies have documented the linkages between agricultural nitrogen loads and surface water degradation. In contrast, potential water quality improvements due to agricultural best management practices are difficult to detect because of the confounding effect of background nitrate removal rates, as well as the groundwater-driven delay between land surface action and stream response. To characterize background controls on nitrate removal in two agricultural catchments, we calibrated groundwater travel time distributions with subsurface environmental tracer data to quantify the lag time between historic agricultural inputs and measured baseflow nitrate. We then estimated spatially distributed loading to the water table from nitrate measurements at monitoring wells, using machine learning techniques to extrapolate the loading to unmonitored portions of the catchment to subsequently estimate catchment removal controls. Multiple models agree that in-stream processes remove as much as 75% of incoming loads for one subcatchment while removing <20% of incoming loads for the other. The use of a spatially variable loading field did not result in meaningfully different optimized parameter estimates or model performance when compared with spatially constant loading derived directly from a county-scale agricultural nitrogen budget. Although previous studies using individual well measurements have shown that subsurface denitrification due to contact with a reducing argillaceous confining unit plays an important role in nitrate removal, the catchment-scale contribution of this process is difficult to quantify given the available data. Nonetheless, the study provides a baseline characterization of nitrate transport timescales and removal mechanisms that will support future efforts to detect water quality benefits from ongoing best management practice implementation.
","language":"English","publisher":"American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America","doi":"10.1002/jeq2.20049","usgsCitation":"Zell, W.O., Culver, T., Sanford, W.E., and Goodall, J.L., 2020, Quantifying background nitrate removal mechanisms in an agricultural watershed with contrasting subcatchment baseflow concentrations: Journal of Environmental Quality, v. 49, no. 2, p. 392-403, https://doi.org/10.1002/jeq2.20049.","productDescription":"12 p.","startPage":"392","endPage":"403","ipdsId":"IP-110824","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":437051,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VWY11M","text":"USGS data release","linkHelpText":"MODFLOW-2005 and MODPATH6 models used to simulate groundwater flow and nitrate transport in two tributaries to the Upper Chester River, Maryland"},{"id":430521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Upper Chester study area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76,\n 39.333\n ],\n [\n -76,\n 39.25\n ],\n [\n -75.916667,\n 39.25\n ],\n [\n -75.916667,\n 39.333\n ],\n [\n -76,\n 39.333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Zell, Wesley O. 0000-0002-8782-6627","orcid":"https://orcid.org/0000-0002-8782-6627","contributorId":339721,"corporation":false,"usgs":true,"family":"Zell","given":"Wesley","email":"","middleInitial":"O.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":904929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Culver, Teresa B","contributorId":339722,"corporation":false,"usgs":false,"family":"Culver","given":"Teresa B","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":904930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":904931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goodall, Jonathan L","contributorId":339724,"corporation":false,"usgs":false,"family":"Goodall","given":"Jonathan","email":"","middleInitial":"L","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":904932,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210347,"text":"70210347 - 2020 - Li and Ca enrichment in the Bristol Dry Lake brine compared to brines from Cadiz and Danby Dry Lakes, Barstow-Bristol Trough, California, USA","interactions":[],"lastModifiedDate":"2020-06-09T20:42:07.632544","indexId":"70210347","displayToPublicDate":"2020-03-21T16:16:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5207,"text":"Minerals","active":true,"publicationSubtype":{"id":10}},"title":"Li and Ca enrichment in the Bristol Dry Lake brine compared to brines from Cadiz and Danby Dry Lakes, Barstow-Bristol Trough, California, USA","docAbstract":"We present the first description of summer stream thermal regimes in Alaska using metrics that represent the magnitude, variability, frequency, duration, and timing of temperature events related to salmon life histories. We used cluster analysis to characterize thermal regimes present in the Matanuska-Susitna (Mat-Su) Basin based on 10 nonredundant temperature metrics and identified the most important drivers of our thermal regimes using random forests. Our results indicated four distinct thermal regimes among the 248 site-years in the Mat-Su Basin. Over 41% of site-years had cold-stable temperatures. An additional 22% of site-years had cold-variable temperatures and the latest timing of maximum stream temperatures. Twenty-eight percent of site-years had warm-variable temperatures that remained above 13°C for approximately two months. The remaining 9% of site-years had the warmest and most variable daily maximum temperatures, exceeding 18°C for almost one month, indicating potential impacts to spawning and rearing salmon. Climate and landscape drivers differentiating thermal regimes included spring and summer air temperatures, spring snowpack, summer precipitation, wetlands, and lakes. Climate change projections for 2050–2069 indicated a future shift toward warm thermal regimes and a reduced portfolio of thermal diversity. These results portend negative impacts to some salmon populations and stress the importance of prioritizing actions that maintain thermal regime diversity.
Many models in population ecology, including spatial capture–recapture (SCR) models, assume that individuals are distributed and detected independently of one another. In reality, this is rarely the case – both antagonistic and gregarious relationships lead to non-independent spatial configurations, with territorial exclusion at one end of the spectrum and group-living at the other. Previous simulation studies suggest that grouping has limited impact on the outcome of SCR analyses. However, group associations entail not only spatial clustering of activity centers but also coordinated space use by group members, potentially impacting both ecological and observation processes underlying SCR analysis. We simulated SCR scenarios with different strengths of aggregation (clustering of individuals into groups with shared activity centers) and cohesion (synchronization of detection patterns of members of a group). We then fit SCR models to the simulated data sets and evaluated the effect of aggregation and cohesion on parameter estimates. Low to moderate aggregation and cohesion did not impact the bias and precision of estimates of density and the scale parameter of the detection function. However, non-independence between individuals led to high levels of overdispersion. Overdispersion strongly decreased the coverage of confidence intervals around parameter estimates, thereby increasing the probability of erroneous predictions. Our results indicate that SCR models are robust to moderate levels of aggregation and cohesion. Nonetheless, spatial dependence between individuals can lead to false inference. We recommend that practitioners 1) test for the presence of overdispersion in SCR data caused by aggregation and cohesion, and, if necessary, 2) correct their variance estimates using the overdispersion factor ĉ . Approaches for doing both are described in this paper. We also urge the development of SCR models that incorporate spatial associations between individuals not only to account for overdispersion but also to obtain quantitative information about social aspects of study populations.
","language":"English","publisher":"BioOne","doi":"10.2981/wlb.00649","usgsCitation":"Bischof, R., Dupont, P., Milleret, C., Chipperfield, J., and Royle, J.A., 2020, Consequences of ignoring group association in spatial capture-recapture analysis: Wildlife Biology, v. 2020, no. 1, wlb.00649, 11 p., https://doi.org/10.2981/wlb.00649.","productDescription":"wlb.00649, 11 p.","ipdsId":"IP-113777","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":457343,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2981/wlb.00649","text":"Publisher Index Page"},{"id":377200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2020","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bischof, Richard","contributorId":237793,"corporation":false,"usgs":false,"family":"Bischof","given":"Richard","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":795324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dupont, Pierre","contributorId":237794,"corporation":false,"usgs":false,"family":"Dupont","given":"Pierre","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":795325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milleret, Cyril","contributorId":237795,"corporation":false,"usgs":false,"family":"Milleret","given":"Cyril","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":795326,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chipperfield, Joseph","contributorId":237796,"corporation":false,"usgs":false,"family":"Chipperfield","given":"Joseph","email":"","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":795327,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795328,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70209158,"text":"70209158 - 2020 - A 'weight of evidence' approach to evaluating structural equation models","interactions":[],"lastModifiedDate":"2020-03-19T19:09:47","indexId":"70209158","displayToPublicDate":"2020-03-13T19:08:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5943,"text":"One Ecosystem","active":true,"publicationSubtype":{"id":10}},"title":"A 'weight of evidence' approach to evaluating structural equation models","docAbstract":"It is possible that model selection has been the most researched and most discussed topic in the history of both statistics and structural equation modeling (SEM). The reason for this is because selecting one model for interpretive use from amongst many possible models is both essential and difficult. The published protocols and advice for model evaluation and selection in SEM studies are complex and difficult to integrate with current approaches used in biology. Opposition to the use of p-values and decision thresholds has been voiced by the statistics community, yet certain phases of model evaluation have been historically tied to reliance on p-values. In this paper, I outline an approach to model evaluation, comparison and selection based on a weight-of-evidence paradigm. The details and proposed sequence of steps are illustrated using a real-world example. At the end of the paper, I briefly discuss the current state of knowledge and a possible direction for future studies.","language":"English","publisher":"Pensoft Publisher","doi":"10.3897/oneeco.5.e50452","usgsCitation":"Grace, J., 2020, A 'weight of evidence' approach to evaluating structural equation models: One Ecosystem, v. 5, e50452, https://doi.org/10.3897/oneeco.5.e50452.","productDescription":"e50452","ipdsId":"IP-115758","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":457375,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/oneeco.5.e50452","text":"Publisher Index Page"},{"id":373395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Grace, James 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":219648,"corporation":false,"usgs":true,"family":"Grace","given":"James","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":785160,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70210526,"text":"70210526 - 2020 - Sub-annual streamflow responses to rainfall and snowmelt inputs in snow-dominated watersheds of the western U.S.","interactions":[],"lastModifiedDate":"2020-06-09T12:42:32.961647","indexId":"70210526","displayToPublicDate":"2020-03-13T07:40:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Sub-annual streamflow responses to rainfall and snowmelt inputs in snow-dominated watersheds of the western U.S.","docAbstract":"Streamflow generation in mountain watersheds is strongly influenced by snow accumulation and melt, and multiple studies have found that snow loss leads to earlier snowmelt timing and declines in annual streamflow. However, hydrologic responses to snow loss are heterogeneous, and not all areas experience streamflow declines. This research examines whether streamflow generation is different for rainfall versus snowmelt inputs. We compiled a sample of 57 small U.S. Geological Survey watersheds in the western United States containing a Natural Resource Conservation Service Snow Telemetry site and having ratios of mean annual peak snow water equivalent to precipitation ratios >0.25. Daily streamflow was separated into quickflow and baseflow using a digital filter, and quickflow was then divided into quickflow response intervals using thresholds in quickflow slope. Each quickflow response interval was categorized by its fraction of input from snowmelt. Most sites exhibited two streamflow generation peaks each year, with one peak in the winter when runoff efficiency is greatest, and the second in the spring during peak snowmelt input. On average, study watersheds were dominated by snowmelt inputs (70%), and snowmelt and mixed inputs usually generated greater streamflow than rainfall because of higher inputs and longer durations. However, rainfall produced high streamflow generation in winter, when watersheds have their highest runoff efficiency (81%) across all input types. We demonstrate that while snowmelt is important for streamflow generation due to high input over long periods, increases in rain and mixed input during wet winter periods can countervail tendencies for reduced streamflow with declining snowpacks.
Water samples were collected at several wastewater treatment plants in southeast Florida, and water and sediment samples were collected along and around one outfall pipe, as well as along several transects extending both north and south of the respective outfall outlet. Two sets of samples were collected to address potential seasonal differences, including 38 in the wet season (June 2018) and 42 in the dry season (March 2019). Samples were screened for the presence/absence of 15 select antibiotic resistance gene targets using the polymerase chain reaction. A contrast between seasons was found, with a higher frequency of detections occurring in the wet season and fewer during the dry season. These data illustrate an anthropogenic influence on offshore microbial genetics and seasonal flux regarding associated health risks to recreational users and the regional ecosystem.