Observations from ground-penetrating radar, sediment cores, elevation surveys and aerial imagery are used to understand the development of the Elwha River delta in north-western Washington, USA, which prograded as a result of two dam removals in late 2011. Swash-bar, foreshore and swale depositional elements are recognized within ground-penetrating radar profiles and sediment cores. A model for the growth and development of small mountainous river wave-dominated deltas is proposed based on observation of both the fluvial and deltaic settings. If enough sediment is available in the fluvial system, mouth-bars form after higher than average river discharge events, creating a large platform seaward of the subaqueous delta plain. Swash-bars form concurrently or within a month of mouth-bar deposition as a result of wave action. Fair-weather waves drive swash-bar migration landward and in the direction of littoral drift. The signature of swash-bar welding to the shoreline is landward-dipping reflections, as a result of overwash processes and slipface migration. However, most swash-bars are eroded by the river mouth, as only 10 of the 37 swash-bars that formed between August 2011 and July 2016 survived within the Elwha River delta. The swash-bars that do survive either amalgamate onto the shoreline or an earlier deposited swash-bar, forming a single larger barrier at the delta front. In asymmetrical deltas, the signature of swash-bar welding is more likely to be preserved on the downdrift side of the delta, where formation is more likely and accommodation behind newer swash-bars preserves older deposits. On small mountainous river deltas, welded swash-bars may be more indicative of a large sediment pulse to the system, rather than large hydrological events.
","language":"English","publisher":"Wiley","doi":"10.1111/sed.12702","usgsCitation":"Zurbuchen, J., Simms, A., Warrick, J.A., Miller, I.M., and Ritchie, A., 2020, A model for the growth and development of wave-dominated deltas fed by small mountainous rivers: Insights from the Elwha River delta, Washington: Sedimentology, v. 67, no. 5, p. 2310-2331, https://doi.org/10.1111/sed.12702.","productDescription":"22 p.","startPage":"2310","endPage":"2331","ipdsId":"IP-091098","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/sed.12702","text":"Publisher Index Page"},{"id":483949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.53500604047304,\n 48.153518237078885\n ],\n [\n -123.57618620014911,\n 48.153518237078885\n ],\n [\n -123.57618620014911,\n 48.12519411609762\n ],\n [\n -123.53500604047304,\n 48.12519411609762\n ],\n [\n -123.53500604047304,\n 48.153518237078885\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"67","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Zurbuchen, Julie","contributorId":352837,"corporation":false,"usgs":false,"family":"Zurbuchen","given":"Julie","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":932190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simms, Alexander R.","contributorId":352838,"corporation":false,"usgs":false,"family":"Simms","given":"Alexander R.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":932191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":932193,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ritchie, Andrew C. 0000-0001-5826-9983","orcid":"https://orcid.org/0000-0001-5826-9983","contributorId":333630,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932194,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208538,"text":"70208538 - 2020 - Patterns of denitrification potential in tidal freshwater forested wetlands","interactions":[],"lastModifiedDate":"2020-02-14T09:52:26","indexId":"70208538","displayToPublicDate":"2020-01-02T09:48:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Patterns of denitrification potential in tidal freshwater forested wetlands","docAbstract":"Limited evidence for spatial patterns of denitrification in tidal freshwater forested wetlands (TFFWs), seemingly due to high spatial variability in the process, is surprising considering the various spatial gradients of its biogeochemical and hydrogeomorphic controls in these ecosystems. Because certain physical environmental gradients may be useful for the prediction of denitrification in TFFWs, we measured denitrification and ecosystem attributes in hummock-hollow microtopography of TFFWs along longitudinal riverine positions (upper, middle, and lower tidal river sites, and nearby upstream nontidal forested floodplains) of the adjoining Pamunkey and Mattaponi Rivers, Virginia. We tested differences by river, site, and plot in denitrification enzyme activity (DEA) and substrate limitations of denitrification potential (DP). The Pamunkey River carries greater river nitrate concentrations, and we found less nitrate limitation of DP and greater soil nitrate in hollows of this river. DEA in tidal hummocks was positively correlated with soil organic matter, nitrogen, and carbon, with the highest rates in lower tidal sites. Hummocks also promoted greater oxygen-controlled substrate limitation of DP, whereby experimental aeration stimulated DP under subsequent inundation more in hummocks than hollows. Additionally, tidal sites had greater DEA than nontidal sites, inferred to be caused by a combination of higher moisture, organic, and nutrient content. Our results indicate that the increasing nitrogen concentrations in these rivers will increase denitrification more on the Mattaponi River by alleviating its greater nitrogen limitation compared to the Pamunkey River, and modification to sedimentation, inundation, or microtopography from sea level rise may alter denitrification gradients in TFFWs and upstream low-elevation nontidal floodplains.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-019-00663-6","usgsCitation":"Korol, A.R., and Noe, G.E., 2020, Patterns of denitrification potential in tidal freshwater forested wetlands, v. 43, no. 2, p. 329-346, https://doi.org/10.1007/s12237-019-00663-6.","productDescription":"18 p.","startPage":"329","endPage":"346","ipdsId":"IP-103254","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":372341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Mattaponi River, Pamunkey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.31903076171875,\n 37.44106442458557\n ],\n [\n -76.76010131835938,\n 37.44106442458557\n ],\n [\n -76.76010131835938,\n 37.86943313301452\n ],\n [\n -77.31903076171875,\n 37.86943313301452\n ],\n [\n -77.31903076171875,\n 37.44106442458557\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Korol, Alicia R.","contributorId":174405,"corporation":false,"usgs":false,"family":"Korol","given":"Alicia","email":"","middleInitial":"R.","affiliations":[{"id":27449,"text":"Department of Environmental Science and Policy, George Mason University, 4400 University Drive, Fairfax, VA, 22030","active":true,"usgs":false}],"preferred":false,"id":782341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":782340,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226609,"text":"70226609 - 2020 - Planktic foraminiferal test size and weight response to the late Pliocene environment","interactions":[],"lastModifiedDate":"2024-09-16T22:40:08.160059","indexId":"70226609","displayToPublicDate":"2020-01-02T07:05:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"title":"Planktic foraminiferal test size and weight response to the late Pliocene environment","docAbstract":"Atmospheric carbon dioxide (pCO2atm) is impacting the ocean and marine organisms directly via changes in carbonate chemistry and indirectly via a range of changes in physical parameters most dominantly temperature. To assess potential impacts of climate change on carbonate production in the open ocean, we measured size and weight of planktic foraminifers during the late Pliocene at pCO2atm concentrations comparable to today and global temperatures 2 to 3 °C warmer. Size of all foraminifers was measured at Atlantic Ocean Deep Sea Drilling Project (DSDP) Site 610, Ocean Drilling Program (ODP) Site 999, and Integrated Ocean Drilling Program (IODP) Site U1313. Test size was smaller during the Pliocene than in modern assemblages under the same environmental conditions. During the cold marine isotope stage (MIS) M2, size increased at Site 999, potentially linked to intensified stratification of the surface ocean in response to the closure of the Central American Seaway. At Site U1313, test size tracks the warming throughout the late Pliocene. Size-normalized weight (SNW) of Globigerina bulloides at Site U1313 decreased during warmer temperature intervals. SNW of Globigerinoides ruber (white) at Site 999 displays high-frequency variability not correlated to temperature. Yet during the glacial period within MIS M2, test weight was higher during higher temperatures. Our results support studies in the modern ocean, which challenge the view that carbonate chemistry is the primary driver for calcification. To better understand processes driving changes in SNW, computer tomography was used to quantify calcite to volume ratios. During interglacial periods, lower calcite volume but higher test volume suggests less suitable conditions for calcification. As this signal is not evident in SNW, subtle changes in calcification might not be observed by the weight-based method.
Pacific capelin Mallotus catervarius are planktivorous, small pelagic fish that serve an intermediate trophic role in marine food webs. Due to the lack of a directed fishery or monitoring of capelin in the Northeast Pacific, there is limited information on their distribution and abundance, and how spatio-temporal fluctuations in capelin density affects their availability as prey. To provide information on life history, spatial patterns, and population dynamics of capelin in the Gulf of Alaska (GOA), we modeled distributions of spawning habitat and larval dispersal, and synthesized spatially-indexed data from multiple, independent sources from 1996 to 2016. Potential capelin spawning areas were broadly distributed across the GOA. Models of larval drift show the GOA’s advective circulation patterns disperse capelin larvae over the continental shelf and upper slope, indicating potential connections between spawning areas and observed offshore distributions that are influenced by the location and timing of spawning. Spatial overlap in composite distributions of larval and age-1+ fish was used to identify core areas where capelin consistently occur and concentrate. Capelin primarily occupy shelf waters near the Kodiak Archipelago, and are patchily distributed across the GOA shelf and inshore waters. Interannual variations in abundance along with spatio-temporal differences in density indicates the availability of capelin to predators and monitoring surveys is highly variable in the GOA. We demonstrate that the limitations of individual data series can be compensated for by integrating multiple data sources to monitor fluctuations in distributions and abundance trends of an ecologically important species across a large marine ecosystem.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps13211","usgsCitation":"David W. McGowan, Goldstein, E., Arimitsu, M.L., Dreary, A., Ormseth, O., DeRobertis, A., Horne, J., Lauren Rogers, Wilson, M., Coyle, K., Holderied, K., Piatt, J.F., Stockhausen, W., and Stephani Zador, 2020, Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: Implications for ecosystem-based fisheries management: Marine Ecology Progress Series, v. 637, p. 117-140, https://doi.org/10.3354/meps13211.","productDescription":"24 p.","startPage":"117","endPage":"140","ipdsId":"IP-109292","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":458260,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/54053","text":"External Repository"},{"id":437180,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96XJDK3","text":"USGS data release","linkHelpText":"Inshore Catch Data for Capelin (Mallotus villosus) in the Gulf of Alaska 1996-2017"},{"id":372202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.017578125,\n 55.52863052257191\n ],\n [\n -134.912109375,\n 55.52863052257191\n ],\n [\n -134.912109375,\n 59.93300042374631\n ],\n [\n -153.017578125,\n 59.93300042374631\n ],\n [\n -153.017578125,\n 55.52863052257191\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"637","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"David W. McGowan","contributorId":222299,"corporation":false,"usgs":false,"family":"David W. McGowan","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":781827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Esther","contributorId":222300,"corporation":false,"usgs":false,"family":"Goldstein","given":"Esther","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":781826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dreary, Alison","contributorId":222301,"corporation":false,"usgs":false,"family":"Dreary","given":"Alison","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ormseth, Olav","contributorId":222302,"corporation":false,"usgs":false,"family":"Ormseth","given":"Olav","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeRobertis, Alex","contributorId":222303,"corporation":false,"usgs":false,"family":"DeRobertis","given":"Alex","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Horne, John","contributorId":222304,"corporation":false,"usgs":false,"family":"Horne","given":"John","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":781832,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lauren Rogers","contributorId":222305,"corporation":false,"usgs":false,"family":"Lauren Rogers","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781833,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wilson, Matt","contributorId":222306,"corporation":false,"usgs":false,"family":"Wilson","given":"Matt","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781834,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Coyle, Kenneth","contributorId":222307,"corporation":false,"usgs":false,"family":"Coyle","given":"Kenneth","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":781835,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Holderied, Kris","contributorId":222308,"corporation":false,"usgs":false,"family":"Holderied","given":"Kris","affiliations":[{"id":40515,"text":"NOAA Kasitsna Bay Lab","active":true,"usgs":false}],"preferred":false,"id":781836,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":781837,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stockhausen, W.T.","contributorId":31952,"corporation":false,"usgs":true,"family":"Stockhausen","given":"W.T.","email":"","affiliations":[],"preferred":false,"id":781987,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stephani Zador","contributorId":222309,"corporation":false,"usgs":false,"family":"Stephani Zador","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781838,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70216693,"text":"70216693 - 2020 - Improving predictions of water supply in the Rio Grande under changing climate conditions","interactions":[],"lastModifiedDate":"2021-02-18T16:04:26.417642","indexId":"70216693","displayToPublicDate":"2020-01-01T10:02:20","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5883,"text":"Cooperator Report","active":true,"publicationSubtype":{"id":1}},"title":"Improving predictions of water supply in the Rio Grande under changing climate conditions","docAbstract":"This product is a case study summarizing the original work authored by David Gutzler, Shaleene Chavarria, and Nels Bjarke. The content will be part of a collection of Case Studies shared via the Collaborative Conservation and Adaptation Strategy Toolbox (CCAST). The research featured in this case study is an analysis of historical observations and climate models developed by the US Bureau of Reclamation. The work aims to identify changes to streamflow predictability, assess future predictability, and inform the development of more reliable water supply outlooks essential for planning purposes in the Upper Rio Grande Basin.","language":"English","publisher":"CCAST","usgsCitation":"Casarez, I.R., 2020, Improving predictions of water supply in the Rio Grande under changing climate conditions: Cooperator Report, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-123347","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":383316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383315,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://usbr.maps.arcgis.com/apps/MapSeries/index.html?appid=e1174c82d65f4124872bb1fe1efa9c3b"}],"country":"United States","state":"Colorado, New Mexico","otherGeospatial":"Upper Rio Grande River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.55639648437499,\n 36.155617833818525\n ],\n [\n -104.96337890625,\n 36.155617833818525\n ],\n [\n -104.96337890625,\n 37.75334401310656\n ],\n [\n -106.55639648437499,\n 37.75334401310656\n ],\n [\n -106.55639648437499,\n 36.155617833818525\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Casarez, Ilana Renae 0000-0001-7690-3802","orcid":"https://orcid.org/0000-0001-7690-3802","contributorId":228961,"corporation":false,"usgs":true,"family":"Casarez","given":"Ilana","email":"","middleInitial":"Renae","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805902,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70270769,"text":"70270769 - 2020 - Understanding the impacts of surface-groundwater conditions on stream fishes under altered baseflow conditions","interactions":[],"lastModifiedDate":"2025-08-27T14:30:09.606834","indexId":"70270769","displayToPublicDate":"2020-01-01T09:18:33","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-136-2020","title":"Understanding the impacts of surface-groundwater conditions on stream fishes under altered baseflow conditions","docAbstract":"Persistence of aquatic fauna depends on the conditions and connectivity of surface water and groundwater. In light of altered baseflows and both current and future predicted increases in stream temperatures, it is important to assess current thermal conditions, examine thermal responses of aquatic fauna, and evaluate water-management practices. Our study objectives were to determine (1) how changes in baseflow levels in the Kiamichi River influence hyporheic exchange, which correspondingly influences temperature at the reach scale; (2) temperature tolerances of stream fishes as a means for predicting how habitat complexity influences stream-fish populations; and (3) assess how dam releases influence the downstream temperature and dissolved oxygen regime during the low-flow period. We quantified hyporheic exchange at four reaches and, as expected, found higher groundwater exchange via transient storage occurred at the upstream sites. The net groundwater flux estimation was negative for the majority of reaches indicating that surface water is lost to groundwater during summer (i.e., losing), baseflow conditions. We determined critical thermal maximum (CTMax) for 17 stream fishes and thermal tolerances ranged 32-38°C. We determined the average thermal tolerance for two habitat fish guilds to calculate changes in thermal stress due to hypothetical reservoir release scenarios. We developed a process-based Water Quality Analysis Simulation Program model to predict downstream temperature conditions over 74-km of river in response to reservoir releases that corresponded to discharges of 0.00 (control), 0.34, 0.59, 0.76, 1.13, and 1.50 m3/s. Based on the dissolved oxygen conditions observed in 2015 and 2017 and biological oxygen demand sampling results, reservoir releases did not directly reduce dissolved oxygen concentrations in the Kiamichi River (though dissolved oxygen concentrations are limited to current water-release strategies by the managing agency). We simulated three scenarios using three water-release temperatures: 27.64°C, 26.00°C and 24.07°C that corresponded to average reservoir temperatures at gate locations on the dam. We compared the predicted temperature time series with CTMax of two fish-habitat guilds to quantify the cumulative time when stream fishes experienced severe thermal stress downstream from Sardis Reservoir. According to our simulations, reservoir releases would be capable of regulating downstream water temperature during the summer baseflow period. The 0.00 m3/s scenario resulted in 130 h of thermal stress for benthic fishes, and 73 h for mid-column fishes. As expected, thermal relief increased with increasing release magnitude and decreasing release water temperature. The 0.34 m3/s release scenario reduced thermal stress (range is simulations from the top and bottom gate) by 11-18% for mid-column fishes and 8-12% for benthic fishes with an effective distance (where the cumulative time above CTMax was reduced by half) of 1-2 km for both guilds. The 0.59 m3/s release scenario reduced thermal stress by 18-25% for mid-column fishes and 12-20% for benthic fishes with effective distances of 4-8 km and 2-7 km, respectively. Three releases representing pre-dam flow magnitudes (0.76, 1.13 and 1.50 m3/s released from top gate) reduced thermal stress up to 46% for mid-column fishes and 41% for benthic fishes with an effective distance of 13-16 km, respectively. Lastly, we quantified temperature-induced stress via whole-body cortisol concentration of six stream fishes in response to prolonged thermal exposure at two temperatures (27°C and 32°C). We found no difference in cortisol levels between temperatures for any of the six species, indicating acclimation to elevated temperatures during the test period. However, Highland Stoneroller Campostoma spadiceum expressed cortisol concentrations greater than typical basal levels at both temperatures, suggesting stress from factors other than temperature (i.e., captivity). Our results suggest different reservoir-release options could improve downstream thermal-fish habitat during the summer baseflow period.
","language":"English","doi":"10.3996/css49046075","usgsCitation":"Brewer, S., Fox, G., Zhou, Y., and Alexander, J., 2020, Understanding the impacts of surface-groundwater conditions on stream fishes under altered baseflow conditions: Cooperator Science Series CSS-136-2020, 113 p., https://doi.org/10.3996/css49046075.","productDescription":"113 p.","ipdsId":"IP-106826","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":494942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Brewer, Shannon K. 0000-0002-1537-3921","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":340552,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":947039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fox, G.","contributorId":273105,"corporation":false,"usgs":false,"family":"Fox","given":"G.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":947040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhou, Y.","contributorId":360419,"corporation":false,"usgs":false,"family":"Zhou","given":"Y.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":947041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, J.","contributorId":305320,"corporation":false,"usgs":false,"family":"Alexander","given":"J.","email":"","affiliations":[],"preferred":false,"id":947042,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227147,"text":"70227147 - 2020 - Barnyardgrass (Echinochloa crusgalli) emergence and growth in a changing climate in great plains wetlands","interactions":[],"lastModifiedDate":"2022-01-03T16:06:54.252963","indexId":"70227147","displayToPublicDate":"2020-01-01T09:10:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Barnyardgrass (Echinochloa crusgalli) emergence and growth in a changing climate in great plains wetlands","title":"Barnyardgrass (Echinochloa crusgalli) emergence and growth in a changing climate in great plains wetlands","docAbstract":"Projected twenty first century increases in temperature and precipitation intensity in the U.S. Great Plains may alter playa wetland hydroperiods. Our objective was to identify favorable germination conditions for a common moist-soil grass, Barnyardgrass (Echinochloa crusgalli L.), by evaluating emergence and growth response to various environmental conditions specific to the Northern (Nebraska) and Southern (Texas) range of playas. We used a temperature-controlled growth chamber experiment to evaluate emergence and growth response of Barnyardgrass to three main effects: (i) weekly temperatures representing historical and future conditions under a moderate emissions scenario, (ii) dry, moist, and saturated soil moisture conditions, and (iii) various seed bank densities. In Nebraska samples, projected future temperatures reduced emergence percentage by up to 20%, but increased emergence percentage by up to 15% for Texas samples. For Nebraska samples, plants were 9.6 cm taller under field capacity moisture compared to saturated moisture. Texas plant height was driven by temperature, where historical conditions produced plants that were 13 cm shorter than future warm conditions. These effects may be exacerbated in natural settings over time and when inter-specific competition exists; thus, temperature, soil moisture, and seed bank densities may be important considerations when planning for playa management in future climate conditions.
","language":"English","publisher":"Springer","doi":"10.1007/s11273-019-09693-0","usgsCitation":"Owen, R.K., Webb, E.B., Haukos, D.A., Fritschi, F.B., and Goyne, K.W., 2020, Barnyardgrass (Echinochloa crusgalli) emergence and growth in a changing climate in great plains wetlands: Wetlands Ecology and Management, v. 28, p. 35-50, https://doi.org/10.1007/s11273-019-09693-0.","productDescription":"16 p.","startPage":"35","endPage":"50","ipdsId":"IP-107339","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":393740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.56614685058594,\n 40.65615965408628\n ],\n [\n -97.15347290039061,\n 40.65615965408628\n ],\n [\n -97.15347290039061,\n 40.980934813391414\n ],\n [\n -97.56614685058594,\n 40.980934813391414\n ],\n [\n -97.56614685058594,\n 40.65615965408628\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.2,\n 33.5\n ],\n [\n -101.75,\n 33.5\n ],\n [\n -101.75,\n 34.7\n ],\n [\n -102.2,\n 34.7\n ],\n [\n -102.2,\n 33.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationDate":"2020-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Owen, R. 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B.","contributorId":270702,"corporation":false,"usgs":false,"family":"Fritschi","given":"F.","email":"","middleInitial":"B.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":829791,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goyne, K. W.","contributorId":244518,"corporation":false,"usgs":false,"family":"Goyne","given":"K.","email":"","middleInitial":"W.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":829792,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208625,"text":"70208625 - 2020 - Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change","interactions":[],"lastModifiedDate":"2020-12-15T20:16:16.059853","indexId":"70208625","displayToPublicDate":"2019-12-31T14:44:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2785,"text":"Monographs of the Western North American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change","docAbstract":"Over 80% of the Mid-Continent Sandhill Crane (Antigone canadensis) Population (MCP), estimated at over 660,000 individuals, stops in the Central Platte River Valley (CPRV) during spring migration from mid-February through mid-April. Research suggests that the MCP may be shifting its distribution spatially and temporally within the CPRV. From 2002 to 2017, we conducted weekly aerial surveys of Sandhill Cranes staging in the CPRV to examine temporal and spatial trends in their abundance and distribution. Then, we used winter temperature and drought severity measures from key wintering and early migratory stopover locations to assess the impacts of weather patterns on annual migration chronology in the CPRV. We also evaluated channel width and land cover characteristics using aerial imagery from 1938, 1998, and 2016 to assess the relationship between habitat change and the spatial distribution of the MCP in the CPRV. We used generalized linear models, cumulative link models, and Akaike’s information criterion corrected for small sample sizes (AICc) to compare temporal and spatial models. Temperatures and drought conditions at wintering and migration locations that are heavily used by Greater Sandhill Cranes (A. c. tabida) best predicted migration chronology of the MCP to the CPRV. The spatial distribution of roosting Sandhill Cranes from 2015 to 2017 was best predicted by the proportion of width reduction in the main channel since 1938 (rather than its width in 2016) and the proportion of land cover as prairie-meadow habitat within 800 m of the Platte River. Our data suggest that Sandhill Cranes advanced their migration by an average of just over 1 day per year from 2002 to 2017, and that they continued to shift eastward, concentrating at eastern reaches of the CPRV. Climate change, land use change, and habitat loss have all likely contributed to Sandhill Cranes coming earlier and staying longer in fewer reaches of the CPRV, increasing their site use intensity. These historically unprecedented densities may present a disease risk to Sandhill Cranes and other waterbirds, including Whooping Cranes (Grus americana). Our models suggest that conservation actions may be maintaining Sandhill Crane densities in areas that would otherwise be declining in use. We suggest that management actions intended to mitigate trends in the distribution of Sandhill Cranes, including wet meadow restoration, may similarly benefit prairie- and braided river–endemic species of concern.
","language":"English","publisher":"BioOne","doi":"10.3398/042.011.0104","usgsCitation":"Caven, A.J., Brinley Buckley, E.M., King, K.C., Wiese, J.D., Baasch, D.M., Wright, G.D., Harner, M.J., Pearse, A.T., Rabbe, M., Varner, D., Krohn, B., Arcilla, N., Schroeder, K.D., and Dinan, K.F., 2020, Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change: Monographs of the Western North American Naturalist, v. 11, p. 33-76, https://doi.org/10.3398/042.011.0104.","productDescription":"44 p.","startPage":"33","endPage":"76","ipdsId":"IP-102357","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458279,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3398/042.011.0104","text":"Publisher Index Page"},{"id":372957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.03237915039062,\n 41.024981358869915\n ],\n [\n -98.06465148925781,\n 41.055537533528636\n ],\n [\n -98.27957153320312,\n 40.954492756949186\n ],\n [\n -98.40934753417967,\n 40.88029480552824\n ],\n [\n -98.81515502929688,\n 40.73112880602221\n ],\n [\n -98.99642944335938,\n 40.69938133866613\n ],\n [\n -99.55535888671874,\n 40.73321007823572\n ],\n [\n -99.60548400878906,\n 40.66293116628907\n ],\n [\n -99.1845703125,\n 40.63740418690266\n ],\n [\n -98.86459350585938,\n 40.64469860601899\n ],\n [\n -98.55491638183594,\n 40.72540497175607\n ],\n [\n -98.28781127929688,\n 40.805493843894155\n 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Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiese, Joshua D","contributorId":222651,"corporation":false,"usgs":false,"family":"Wiese","given":"Joshua","email":"","middleInitial":"D","affiliations":[{"id":40581,"text":"Platte River Whooping Crane Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baasch, David M.","contributorId":147145,"corporation":false,"usgs":false,"family":"Baasch","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":16795,"text":"Headwaters Corp, Kearney, NE","active":true,"usgs":false}],"preferred":false,"id":782802,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wright, Greg D.","contributorId":177585,"corporation":false,"usgs":false,"family":"Wright","given":"Greg","email":"","middleInitial":"D.","affiliations":[{"id":12957,"text":"Chippewa Ottawa Resource Authority","active":true,"usgs":false}],"preferred":false,"id":782803,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harner, Mary J.","contributorId":177584,"corporation":false,"usgs":false,"family":"Harner","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":782804,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":782797,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rabbe, Matt","contributorId":202597,"corporation":false,"usgs":false,"family":"Rabbe","given":"Matt","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":782805,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Varner, Dana","contributorId":222652,"corporation":false,"usgs":false,"family":"Varner","given":"Dana","affiliations":[{"id":40582,"text":"Rainwater Basin Joint Venture","active":true,"usgs":false}],"preferred":false,"id":782806,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Krohn, Brice","contributorId":222653,"corporation":false,"usgs":false,"family":"Krohn","given":"Brice","email":"","affiliations":[{"id":40581,"text":"Platte River Whooping Crane Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782807,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Arcilla, Nicole","contributorId":223085,"corporation":false,"usgs":false,"family":"Arcilla","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":782808,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Schroeder, Kirk D","contributorId":222655,"corporation":false,"usgs":false,"family":"Schroeder","given":"Kirk","email":"","middleInitial":"D","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":782809,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dinan, Kenneth F","contributorId":222656,"corporation":false,"usgs":false,"family":"Dinan","given":"Kenneth","email":"","middleInitial":"F","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":782810,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70209255,"text":"70209255 - 2020 - Event and decadal-scale modeling of barrier island restoration designs for decision support","interactions":[],"lastModifiedDate":"2020-03-26T11:18:40","indexId":"70209255","displayToPublicDate":"2019-12-31T11:18:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3385,"text":"Shore & Beach","printIssn":"0037-4237","active":true,"publicationSubtype":{"id":10}},"title":"Event and decadal-scale modeling of barrier island restoration designs for decision support","docAbstract":"An interdisciplinary project team was convened to develop a modeling framework that simulates the potential impacts of storms and sea level-rise to habitat availability at Breton Island, Louisiana (Breton) for existing conditions and potential future restoration designs. The model framework was iteratively developed through evaluation of model results at multiple checkpoints. A methodology was developed for characterizing regional wave and water levels, and the numerical model XBeach was used to simulate the potential impacts from a wide range of storm events. Simulations quantified the potential for erosion, overwash, and inundation of the pre- and post-restoration beach and dune system and were used as a preliminary screening of restoration designs. The model framework also incorporated a computationally efficient method to evaluate the impacts of storms, long-term shoreline changes, and relative sea level rise over a 15-year time period in order to evaluate the effect of the preferred restoration alternative on habitat distribution. Results directly informed engineering design decisions and expedited later project stages including the construction permitting process.","language":"English","publisher":"American Shore and Beach Preservation Association","usgsCitation":"Long, J.W., Dalyander, P., Poff, M., Spears, B., Borne, B., Thompson, D.M., Mickey, R.C., Dartez, S., and Gandy, G., 2020, Event and decadal-scale modeling of barrier island restoration designs for decision support: Shore & Beach, v. 88, no. 1, p. 49-57.","productDescription":"9 p.","startPage":"49","endPage":"57","ipdsId":"IP-115503","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":373548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373522,"type":{"id":15,"text":"Index Page"},"url":"https://asbpa.org/publications/shore-and-beach/shore-beach-in-2020-vol-88/"}],"volume":"88","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Long, Joseph W. 0000-0003-2912-1992","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":219235,"corporation":false,"usgs":false,"family":"Long","given":"Joseph","email":"","middleInitial":"W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":785594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":221891,"corporation":false,"usgs":false,"family":"Dalyander","given":"P. Soupy","affiliations":[{"id":40456,"text":"St. Petersburg Coastal and Marine Science Center (Former Employee)","active":true,"usgs":false}],"preferred":false,"id":785595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poff, Michael","contributorId":223601,"corporation":false,"usgs":false,"family":"Poff","given":"Michael","email":"","affiliations":[{"id":40745,"text":"Coastal Engineering Consultants, Inc.","active":true,"usgs":false}],"preferred":false,"id":785596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spears, Brian","contributorId":223602,"corporation":false,"usgs":false,"family":"Spears","given":"Brian","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":785597,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Borne, Brett","contributorId":223603,"corporation":false,"usgs":false,"family":"Borne","given":"Brett","email":"","affiliations":[{"id":40745,"text":"Coastal Engineering Consultants, Inc.","active":true,"usgs":false}],"preferred":false,"id":785598,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":785593,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mickey, Rangley C. 0000-0001-5989-1432 rmickey@usgs.gov","orcid":"https://orcid.org/0000-0001-5989-1432","contributorId":141016,"corporation":false,"usgs":true,"family":"Mickey","given":"Rangley","email":"rmickey@usgs.gov","middleInitial":"C.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":785599,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dartez, Steve","contributorId":223604,"corporation":false,"usgs":false,"family":"Dartez","given":"Steve","email":"","affiliations":[{"id":40745,"text":"Coastal Engineering Consultants, Inc.","active":true,"usgs":false}],"preferred":false,"id":785600,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gandy, Gregory","contributorId":223605,"corporation":false,"usgs":false,"family":"Gandy","given":"Gregory","email":"","affiliations":[{"id":13608,"text":"Louisiana Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":785601,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70216997,"text":"70216997 - 2020 - A transect through Vermont's most famous volcano - Mount Ascutney","interactions":[],"lastModifiedDate":"2023-03-23T16:18:22.745397","indexId":"70216997","displayToPublicDate":"2019-12-31T09:57:15","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A transect through Vermont's most famous volcano - Mount Ascutney","docAbstract":"The Cretaceous Ascutney Mountain igneous complex affords a classic exposure of the White Mountain Igneous Suite. Often called Vermont’s most famous volcano, Mount Ascutney (elev. 3,144 feet, 958 m) stands as a prominent monadnock in the Connecticut River Valley. The mountain often serves as an inspirational landmark, as it does when viewed from locations throughout the valley including the Saint-Gaudens National Historic Site (Walsh, 2017). The Ascutney Mountain igneous complex (Ratcliffe and others, 2011) consists of several mafic to felsic nested plutons including gabbro-diorite exposed at Little Ascutney to the west, and the Ascutney Mountain stock composed of syenite, granite, and related volcanic rocks underlying the main summit to the east (Fig. 1) (Schneiderman, 1989, 1991). Foland and Faul (1977) and Foland and others (1985) dated the gabbro-diorite complex at 125.5 to 122.2 Ma by K-Ar on biotite and by whole rock Rb/Sr, and dated the syenite-granite complex at 123.2 to 121.4 Ma by K-Ar on biotite. During the field trip we will visit the host rocks south of the mountain and the main rocks types of the Ascutney Mountain stock exposed near the summit and along the Mount Ascutney toll road. \n \n Mount Ascutney is the classic location where Daly (1903) discussed the evidence for piecemeal stoping as a pluton emplacement mechanism. This theory was later modified to favor cauldron subsidence, or ring-fracture stoping, as an alternative mode of emplacement (Chapman and Chapman, 1940). Our new mapping (Walsh and others, in press), which supersedes an earlier provisional study (Walsh and others, 1996a, b), supports the cauldron subsidence model, and shows that the main Ascutney Mountain stock is a funnel shaped composite pluton in agreement with geophysical data (Daniels, 1990). This field guide will primarily highlight the results of the new geologic mapping.\n\n This field guide is modified from a field trip presented in 2017 (Walsh, 2017). Additional stops have been added to examine the host rocks in the region south of the Ascutney Mountain stock. Two hikes are planned as part of this trip. Other NEIGC field trip guides to Mount Ascutney include Stoiber (1954) and Schneiderman (1988).","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"111th New England Intercollegiate Geological Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"111th New England Intercollegiate Geological Conference","conferenceDate":"October 1-13, 2019","conferenceLocation":"Barre, VT","language":"English","publisher":"New England Intercollegiate Geological Conference","usgsCitation":"Walsh, G.J., Proctor, B., Sicard, K.R., and Valley, P.M., 2020, A transect through Vermont's most famous volcano - Mount Ascutney, in 111th New England Intercollegiate Geological Conference, v. 111, Barre, VT, October 1-13, 2019, p. 1-6.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-109653","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":381650,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":414625,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://neigc.info/guidebooks/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Vermont","otherGeospatial":"Mount Ascutney","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.48590469360352,\n 43.4175176458317\n ],\n [\n -72.40299224853516,\n 43.4175176458317\n ],\n [\n -72.40299224853516,\n 43.466002139041116\n ],\n [\n -72.48590469360352,\n 43.466002139041116\n ],\n [\n -72.48590469360352,\n 43.4175176458317\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"111","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Gregory J. 0000-0003-4264-8836 gwalsh@usgs.gov","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":873,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory","email":"gwalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":807199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Proctor, Brooks P. 0000-0002-4878-8728 bproctor@usgs.gov","orcid":"https://orcid.org/0000-0002-4878-8728","contributorId":178527,"corporation":false,"usgs":true,"family":"Proctor","given":"Brooks P.","email":"bproctor@usgs.gov","affiliations":[],"preferred":true,"id":807200,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sicard, Karri R. 0000-0003-4062-8030","orcid":"https://orcid.org/0000-0003-4062-8030","contributorId":219210,"corporation":false,"usgs":false,"family":"Sicard","given":"Karri","email":"","middleInitial":"R.","affiliations":[],"preferred":true,"id":807201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valley, Peter M. 0000-0002-9957-0403 pvalley@usgs.gov","orcid":"https://orcid.org/0000-0002-9957-0403","contributorId":4809,"corporation":false,"usgs":true,"family":"Valley","given":"Peter","email":"pvalley@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":807202,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208091,"text":"70208091 - 2020 - Establishing high-frequency noise baselines to 100 Hz based on millions of power spectra from IRIS MUSTANG","interactions":[],"lastModifiedDate":"2020-02-06T11:42:11","indexId":"70208091","displayToPublicDate":"2019-12-31T07:16:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Establishing high-frequency noise baselines to 100 Hz based on millions of power spectra from IRIS MUSTANG","docAbstract":"Advances in seismic instrumentation have enabled data to be recorded at increasing sample rates. This has in turn created a need to establish higher-frequency baselines for assessing data quality, as the widely-used New High (NHNM) and Low Noise Models (NLNM) of Peterson (1993) do not extend to frequencies above 10 Hz. To provide a baseline for higher frequencies (10-100 Hz), we examine power spectral density probability density functions (PSDPDFs) for high-sample-rate stations available from the Incorporated Research Institutions for Seismology Data Services (IRIS DS) MUSTANG quality control system. We compute high-frequency high and low noise baselines by matching the appropriate composite PSDPDF percentile points to NHNM and NLNM power levels at overlapping frequencies (1-10 Hz) and then extending to higher frequencies (10-100 Hz) with piecewise linear fits to the matching PSDPDF percentile.\n\nWe find that the Peterson NLNM remains an accurate representation of the lower bound of global ambient Earth noise since it is matched by only 0.1% of Global Seismographic Network (GSN) PSDs. We present high-frequency high and low noise baselines intended primarily for use by temporary networks targeting high-frequency signals (e.g. monitoring of aftershocks or induced seismicity) based on statistics of PSDPDFs from all publicly available high-sample-rate data. \n\nMost publicly-available high-sample-rate data is recorded by temporary deployments, and the experiment design and scientific targets of these deployments strongly influence the observed statistical distribution of high-frequency noise. We anticipate that the noise baselines presented here will be useful in automated quality control of high-sample-rate seismic data. However, we note that establishing a low noise model that accurately represents the lowest possible ambient Earth noise at frequencies up to 100 Hz will require additional continuous high-sample-rate data from high-quality permanent stations in low-noise environments.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120190123","usgsCitation":"Wolin, E., and McNamara, D., 2020, Establishing high-frequency noise baselines to 100 Hz based on millions of power spectra from IRIS MUSTANG: Bulletin of the Seismological Society of America, v. 110, no. 1, p. 270-278, https://doi.org/10.1785/0120190123.","productDescription":"9 p.","startPage":"270","endPage":"278","ipdsId":"IP-107994","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":371634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"110","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Wolin, Emily 0000-0003-1610-1191","orcid":"https://orcid.org/0000-0003-1610-1191","contributorId":221834,"corporation":false,"usgs":true,"family":"Wolin","given":"Emily","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":780442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNamara, Daniel 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":221835,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":780443,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208092,"text":"70208092 - 2020 - Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian","interactions":[],"lastModifiedDate":"2020-01-27T19:59:37","indexId":"70208092","displayToPublicDate":"2019-12-30T19:58:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian","docAbstract":"Determining the spatial scale at which landscape features influence population persistence is an important task for conservation planning. One challenge is that sampling biases confound factors that influence species occurrence and survey effort. Recent developments in Point Process Models (PPMs) enable researchers to disentangle the sampling process from ecological drivers of species' distributions. Land-cover change is a driver of decline for the western spadefoot (Spea hammondii), which has been extirpated from much of its range in California. Assessing this species' status requires information on the current distribution of suitable habitat within its historical range, but little is known about the effect of the landscape surrounding breeding ponds on spadefoot occurrence. Critically, surveys for western spadefoots often occur along roads, potentially biasing data used to fit species distribution models. We created PPMs integrating historical presence/non-detection and presence-only data for western spadefoots and land-cover data at multiple spatial scales to model the distribution of this species while removing the influence of sampling bias. There was spatial sampling bias in presence-only data; records were more likely to be reported near roads and urban centers and PPMs that removed sampling bias outperformed models that ignored sampling bias. The occurrence of western spadefoots was positively related to the proportion of grassland within a 2000 m buffer. The remaining habitat for western spadefoots is largely found in the foothills surrounding California's Central Valley. Our study illustrates how PPMs can improve projections of habitat suitability and our understanding of the drivers of species' distributions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2019.108374","usgsCitation":"Rose, J.P., Halstead, B., and Fisher, R.N., 2020, Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian: Biological Conservation, v. 241, 108374, https://doi.org/10.1016/j.biocon.2019.108374.","productDescription":"108374","ipdsId":"IP-108816","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458282,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2019.108374","text":"Publisher Index Page"},{"id":371628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.14599609375001,\n 40.96330795307353\n ],\n [\n -123.06884765625,\n 41.062786068733026\n ],\n [\n -123.15673828124999,\n 39.13006024213511\n ],\n [\n -120.21240234375001,\n 35.06597313798418\n ],\n [\n -117.83935546874999,\n 34.17999758688084\n ],\n [\n -117.00439453125,\n 34.994003757575776\n ],\n [\n -117.97119140625,\n 36.06686213257888\n ],\n [\n -119.2236328125,\n 37.77071473849609\n ],\n [\n -122.14599609375001,\n 40.96330795307353\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"241","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":780444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780446,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228175,"text":"70228175 - 2020 - Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data","interactions":[],"lastModifiedDate":"2022-02-07T17:50:09.933226","indexId":"70228175","displayToPublicDate":"2019-12-27T11:39:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data","docAbstract":"Aquatic scientists require robust, accurate information about nutrient concentrations and indicators of algal biomass in unsampled lakes in order to understand and predict the effects of global climate and land-use change. Historically, lake and landscape characteristics have been used as predictor variables in regression models to generate nutrient predictions, but often with significant uncertainty. An alternative approach to improve predictions is to leverage the observed relationship between water clarity and nutrients, which is possible because water clarity is more commonly measured than lake nutrients. We used a joint-nutrient model that conditioned predictions of total phosphorus, nitrogen, and chlorophyll a on observed water clarity. Our results demonstrated substantial reductions (8–27%; median = 23%) in prediction error when conditioning on water clarity. These models will provide new opportunities for predicting nutrient concentrations of unsampled lakes across broad spatial scales with reduced uncertainty.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lol2.10134","usgsCitation":"Wagner, T., Noah R., O.L., Bartley, M.L., Hanks, E., Schliep, E.M., Wikle, N.B., King, K.B., McCullough, I., Stachelek, J., Cheruvelil, K.S., Filstrup, C.T., Lapierre, J., Liu, B., Sorrano, P., Tan, P., Wang, Q., Webster, K., and Zhou, J., 2020, Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data: Limnology and Oceanography Letters, v. 5, no. 2, p. 228-235, https://doi.org/10.1002/lol2.10134.","productDescription":"8 p.","startPage":"228","endPage":"235","ipdsId":"IP-109351","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":488957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lol2.10134","text":"Publisher Index Page"},{"id":395550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noah R., oa Lottig Lottig","contributorId":274769,"corporation":false,"usgs":false,"family":"Noah R.","given":"oa","suffix":"Lottig","email":"","middleInitial":"Lottig","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":833308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartley, Meridith L.","contributorId":274772,"corporation":false,"usgs":false,"family":"Bartley","given":"Meridith","email":"","middleInitial":"L.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanks, Ephraim M.","contributorId":274775,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim M.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schliep, Erin M.","contributorId":274778,"corporation":false,"usgs":false,"family":"Schliep","given":"Erin","email":"","middleInitial":"M.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833311,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wikle, Nathan B.","contributorId":274780,"corporation":false,"usgs":false,"family":"Wikle","given":"Nathan","email":"","middleInitial":"B.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833312,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"King, Katelyn B. S.","contributorId":274782,"corporation":false,"usgs":false,"family":"King","given":"Katelyn","email":"","middleInitial":"B. S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833313,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCullough, Ian","contributorId":274784,"corporation":false,"usgs":false,"family":"McCullough","given":"Ian","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833314,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stachelek, Jemma","contributorId":274864,"corporation":false,"usgs":false,"family":"Stachelek","given":"Jemma","email":"","affiliations":[],"preferred":false,"id":833315,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cheruvelil, Kendra S.","contributorId":172029,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":833316,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Filstrup, Christopher T.","contributorId":169032,"corporation":false,"usgs":false,"family":"Filstrup","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":833440,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lapierre, Jean-Francois","contributorId":264522,"corporation":false,"usgs":false,"family":"Lapierre","given":"Jean-Francois","affiliations":[{"id":54487,"text":"University of Montreal","active":true,"usgs":false}],"preferred":false,"id":833441,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Liu, Boyang","contributorId":274865,"corporation":false,"usgs":false,"family":"Liu","given":"Boyang","email":"","affiliations":[],"preferred":false,"id":833442,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sorrano, Patricia","contributorId":204929,"corporation":false,"usgs":false,"family":"Sorrano","given":"Patricia","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833443,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tan, Pang-Ning","contributorId":172193,"corporation":false,"usgs":false,"family":"Tan","given":"Pang-Ning","affiliations":[],"preferred":false,"id":833444,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wang, Q.","contributorId":83761,"corporation":false,"usgs":true,"family":"Wang","given":"Q.","affiliations":[],"preferred":false,"id":833445,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Webster, Katherine","contributorId":274866,"corporation":false,"usgs":false,"family":"Webster","given":"Katherine","affiliations":[],"preferred":false,"id":833446,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zhou, Jiayu","contributorId":204926,"corporation":false,"usgs":false,"family":"Zhou","given":"Jiayu","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833447,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70222540,"text":"70222540 - 2020 - Metal bioavailability models: Current status, lessons learned, considerations for regulatory use, and the path forward","interactions":[],"lastModifiedDate":"2021-08-03T13:47:20.331188","indexId":"70222540","displayToPublicDate":"2019-12-27T08:45:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Metal bioavailability models: Current status, lessons learned, considerations for regulatory use, and the path forward","docAbstract":"Since the early 2000s, biotic ligand models and related constructs have been a dominant paradigm for risk assessment of aqueous metals in the environment. We critically review 1) the evidence for the mechanistic approach underlying metal bioavailability models; 2) considerations for the use and refinement of bioavailability-based toxicity models; 3) considerations for the incorporation of metal bioavailability models into environmental quality standards; and 4) some consensus recommendations for developing or applying metal bioavailability models. We note that models developed to date have been particularly challenged to accurately incorporate pH effects because they are unique with multiple possible mechanisms. As such, we doubt it is ever appropriate to lump algae/plant and animal bioavailability models; however, it is often reasonable to lump bioavailability models for animals, although aquatic insects may be an exception. Other recommendations include that data generated for model development should consider equilibrium conditions in exposure designs, including food items in combined waterborne–dietary matched chronic exposures. Some potentially important toxicity-modifying factors are currently not represented in bioavailability models and have received insufficient attention in toxicity testing. Temperature is probably of foremost importance; phosphate is likely important in plant and algae models. Acclimation may result in predictions that err on the side of protection. Striking a balance between comprehensive, mechanistically sound models and simplified approaches is a challenge. If empirical bioavailability tools such as multiple-linear regression models and look-up tables are employed in criteria, they should always be informed qualitatively and quantitatively by mechanistic models. If bioavailability models are to be used in environmental regulation, ongoing support and availability for use of the models in the public domain are essential.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.4560","usgsCitation":"Mebane, C.A., Chowdhury, M., De Schamphelaere, K.A., Lofts, S., Paquin, P.R., Santore, R.C., and Wood, C.M., 2020, Metal bioavailability models: Current status, lessons learned, considerations for regulatory use, and the path forward: Environmental Toxicology and Chemistry, v. 39, no. 1, p. 60-84, https://doi.org/10.1002/etc.4560.","productDescription":"25 p.","startPage":"60","endPage":"84","ipdsId":"IP-110208","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":458289,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.4560","text":"Publisher Index Page"},{"id":387661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chowdhury, M. Jasim","contributorId":261730,"corporation":false,"usgs":false,"family":"Chowdhury","given":"M. Jasim","affiliations":[{"id":52970,"text":"International Lead Association, Durham, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":820504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Schamphelaere, Karel A.C.","contributorId":261731,"corporation":false,"usgs":false,"family":"De Schamphelaere","given":"Karel","email":"","middleInitial":"A.C.","affiliations":[{"id":52971,"text":"Ghent University, Gent, Belgium","active":true,"usgs":false}],"preferred":false,"id":820505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lofts, Stephen","contributorId":261732,"corporation":false,"usgs":false,"family":"Lofts","given":"Stephen","email":"","affiliations":[{"id":52972,"text":"Centre for Ecology and Hydrology, Bailrigg, Lancaster, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":820506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paquin, Paul R.","contributorId":261733,"corporation":false,"usgs":false,"family":"Paquin","given":"Paul","email":"","middleInitial":"R.","affiliations":[{"id":52973,"text":"HDR, New York, New York, USA","active":true,"usgs":false}],"preferred":false,"id":820507,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Santore, Robert C.","contributorId":202449,"corporation":false,"usgs":false,"family":"Santore","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":36447,"text":"Windward Environmental LLC, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":820508,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, Chris M.","contributorId":261734,"corporation":false,"usgs":false,"family":"Wood","given":"Chris","email":"","middleInitial":"M.","affiliations":[{"id":52974,"text":"University of British Columbia, Vancouver, British Columbia, Canada.","active":true,"usgs":false}],"preferred":false,"id":820509,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208100,"text":"70208100 - 2020 - Thresholds for post-wildfire debris flows: Insights from the Pinal Fire, Arizona, USA","interactions":[],"lastModifiedDate":"2020-06-04T16:48:14.988077","indexId":"70208100","displayToPublicDate":"2019-12-27T07:11:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Thresholds for post-wildfire debris flows: Insights from the Pinal Fire, Arizona, USA","docAbstract":"Wildfire significantly alters the hydrologic properties of a burned area, leading to increases in overland flow, erosion, and the potential for runoff-generated debris flows. The initiation of debris flows in recently burned areas is well-characterized by rainfall intensity-duration (ID) thresholds. However, there is currently a paucity of data quantifying the rainfall intensities required to trigger post-wildfire debris flows, which limits our understanding of how and why rainfall ID thresholds vary in different climatic and geologic settings. In this study, we monitored debris-flow activity following the Pinal Fire in central Arizona, which differs from both a climatic and hydrogeomorphic perspective from other regions in the western U.S. where ID thresholds for post-wildfire debris flows are well-established, namely the Transverse Ranges of southern CA. Since the peak rainfall intensity within a rainstorm may exceed the rainfall intensity required to trigger a debris flow, the development of robust rainfall ID thresholds requires knowledge of the timing of debris flows within rainstorms. Existing post-wildfire debris-flow studies in Arizona only constrain the peak rainfall intensity within debris-flow-producing storms, which may far exceed the intensity that actually triggered the observed debris flow. In this study, we used pressure transducers within 5 burned drainage basins to constrain the timing of debris flows within rainstorms. Rainfall ID thresholds derived here from triggering rainfall intensities are, on average, 22 mm/h lower than ID thresholds derived under the assumption that the triggering intensity is equal to the maximum rainfall intensity recorded during a rainstorm. We then use a hydrologic model to demonstrate that the magnitude of the 15-minute rainfall ID threshold at the Pinal Fire site is associated with the rainfall intensity required to exceed a recently proposed dimensionless discharge threshold for debris-flow initiation. Model results further suggest that previously observed differences in regional ID thresholds between Arizona and the San Gabriel Mountains of southern CA may be attributed, in large part, to differences in the hydraulic properties of burned soils.","language":"English","publisher":"Wiley","doi":"10.1002/esp.4805","usgsCitation":"Raymond, C.A., McGuire, L.A., Youberg, A.M., Staley, D.M., and Kean, J.W., 2020, Thresholds for post-wildfire debris flows: Insights from the Pinal Fire, Arizona, USA: Earth Surface Processes and Landforms, v. 45, no. 6, p. 1349-1360, https://doi.org/10.1002/esp.4805.","productDescription":"12 p.","startPage":"1349","endPage":"1360","ipdsId":"IP-112967","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":371633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.994873046875,\n 33.25936011503665\n ],\n [\n -110.60348510742188,\n 33.25936011503665\n ],\n [\n -110.60348510742188,\n 33.543683878655926\n ],\n [\n -110.994873046875,\n 33.543683878655926\n ],\n [\n -110.994873046875,\n 33.25936011503665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Raymond, Carissa A","contributorId":221837,"corporation":false,"usgs":false,"family":"Raymond","given":"Carissa","email":"","middleInitial":"A","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":780463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Luke A. 0000-0001-8178-7922 lmcguire@usgs.gov","orcid":"https://orcid.org/0000-0001-8178-7922","contributorId":203420,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":780464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Youberg, Ann M. 0000-0002-2005-3674","orcid":"https://orcid.org/0000-0002-2005-3674","contributorId":172609,"corporation":false,"usgs":false,"family":"Youberg","given":"Ann","email":"","middleInitial":"M.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":true,"id":780465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":780466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":780462,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211487,"text":"70211487 - 2020 - Local climate determines vulnerability to camouflage mismatch in snowshoe hares","interactions":[],"lastModifiedDate":"2020-07-29T00:55:17.688689","indexId":"70211487","displayToPublicDate":"2019-12-26T19:45:25","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}},"title":"Local climate determines vulnerability to camouflage mismatch in snowshoe hares","docAbstract":"Phenological mismatches, when life‐events become mistimed with optimal environmental conditions, have become increasingly common under climate change. Population‐level susceptibility to mismatches depends on how phenology and phenotypic plasticity vary across a species’ distributional range. Here, we quantify the environmental drivers of colour moult phenology, phenotypic plasticity, and the extent of phenological mismatch in seasonal camouflage to assess vulnerability to mismatch in a common North American mammal.
North America.
2010–2017.
Snowshoe hare (Lepus americanus ).
We used > 5,500 by‐catch photographs of snowshoe hares from 448 remote camera trap sites at three independent study areas. To quantify moult phenology and phenotypic plasticity, we used multinomial logistic regression models that incorporated geospatial and high‐resolution climate data. We estimated occurrence of camouflage mismatch between hares’ coat colour and the presence and absence of snow over 7 years of monitoring.
Spatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on dark, snowless background occurred primarily during low‐snow years in regions characterized by shallow, short‐lasting snowpack.
Long‐term climate and annual variation in snow and temperature determine coat colour moult phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of camouflage mismatch varies across the species’ range. Our results underscore the population‐specific susceptibility to climate change‐induced stressors and the necessity to understand this variation to prioritize the populations most vulnerable under global environmental change.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.13049","usgsCitation":"Zimova, M., Siren, A., Nowak, J.J., Bryan, A., Ivan, J., Morelli, T.L., Suhrer, S.L., Whittington, J., and Mills, L.S., 2020, Local climate determines vulnerability to camouflage mismatch in snowshoe hares: Global Ecology and Biogeography, v. 29, no. 3, p. 503-515, https://doi.org/10.1111/geb.13049.","productDescription":"13 p.","startPage":"503","endPage":"515","ipdsId":"IP-112695","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":467307,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/geb.13049","text":"External Repository"},{"id":376822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.16796875,\n 39.774769485295465\n ],\n [\n -63.10546874999999,\n 43.70759350405294\n ],\n [\n -50.9765625,\n 48.10743118848039\n ],\n [\n -61.87499999999999,\n 57.42129439209407\n ],\n [\n -74.53125,\n 59.355596110016315\n ],\n [\n -78.22265625,\n 59.085738569819505\n ],\n [\n -75.5859375,\n 56.17002298293205\n ],\n [\n -79.1015625,\n 54.36775852406841\n ],\n [\n -79.27734374999999,\n 51.069016659603896\n ],\n [\n -82.6171875,\n 55.27911529201561\n ],\n [\n -91.58203125,\n 57.42129439209407\n ],\n [\n -94.74609375,\n 59.5343180010956\n ],\n [\n -131.484375,\n 67.941650035336\n ],\n [\n -154.51171875,\n 69.96043926902489\n ],\n [\n -166.46484375,\n 68.52823492039876\n ],\n [\n -162.24609375,\n 66.58321725728175\n ],\n [\n -163.125,\n 66.16051056018838\n ],\n [\n -164.35546875,\n 66.65297740055279\n ],\n [\n -167.51953124999997,\n 65.58572002329473\n ],\n [\n -165.76171875,\n 64.47279382008166\n ],\n [\n -160.3125,\n 64.77412531292873\n ],\n [\n -162.0703125,\n 63.6267446447533\n ],\n [\n -164.35546875,\n 62.83508901142283\n ],\n [\n -166.2890625,\n 61.438767493682825\n ],\n [\n -164.00390625,\n 59.80063426102869\n ],\n [\n -161.3671875,\n 58.63121664342478\n ],\n [\n -156.796875,\n 58.35563036280964\n ],\n [\n -169.45312499999997,\n 52.696361078274485\n ],\n [\n -153.80859375,\n 56.75272287205736\n ],\n [\n -149.23828125,\n 59.80063426102869\n ],\n [\n -145.1953125,\n 59.977005492196\n ],\n [\n -139.74609375,\n 58.26328705248601\n ],\n [\n -135.35156249999997,\n 55.87531083569679\n ],\n [\n -132.890625,\n 52.908902047770255\n ],\n [\n -124.1015625,\n 47.635783590864854\n ],\n [\n -124.98046874999999,\n 41.376808565702355\n ],\n [\n -121.11328124999999,\n 46.07323062540835\n ],\n [\n -111.796875,\n 36.73888412439431\n ],\n [\n -107.57812499999999,\n 46.92025531537451\n ],\n [\n -103.18359375,\n 47.517200697839414\n ],\n [\n -89.296875,\n 44.33956524809713\n ],\n [\n -83.14453125,\n 43.068887774169625\n ],\n [\n -79.98046875,\n 42.032974332441405\n ],\n [\n -77.16796875,\n 39.774769485295465\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Zimova, Marketa","contributorId":171704,"corporation":false,"usgs":false,"family":"Zimova","given":"Marketa","affiliations":[],"preferred":false,"id":794285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siren, Alexej P. K.","contributorId":236810,"corporation":false,"usgs":false,"family":"Siren","given":"Alexej P. K.","affiliations":[],"preferred":false,"id":794286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowak, Joshua J.","contributorId":236829,"corporation":false,"usgs":false,"family":"Nowak","given":"Joshua","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":794287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bryan, Alexander 0000-0003-2040-7636 abryan@usgs.gov","orcid":"https://orcid.org/0000-0003-2040-7636","contributorId":168822,"corporation":false,"usgs":true,"family":"Bryan","given":"Alexander","email":"abryan@usgs.gov","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":794290,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ivan, Jacob S.","contributorId":200243,"corporation":false,"usgs":false,"family":"Ivan","given":"Jacob S.","affiliations":[],"preferred":false,"id":794284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":794289,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Suhrer, Skyler L.","contributorId":236830,"corporation":false,"usgs":false,"family":"Suhrer","given":"Skyler","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":794367,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Whittington, Jesse","contributorId":179372,"corporation":false,"usgs":false,"family":"Whittington","given":"Jesse","email":"","affiliations":[],"preferred":false,"id":794368,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mills, L. Scott","contributorId":236757,"corporation":false,"usgs":false,"family":"Mills","given":"L.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":794288,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70208469,"text":"70208469 - 2020 - Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use","interactions":[],"lastModifiedDate":"2020-02-11T10:05:32","indexId":"70208469","displayToPublicDate":"2019-12-26T10:04:22","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use","title":"Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use","docAbstract":"Escherichia coli levels in recreational waters are often used to predict when fecal-associated pathogen levels are a human health risk. The reach of the Chattahoochee River that flows through the Chattahoochee River National Recreation Area (CRNRA), located in the Atlanta-metropolitan area, is a popular recreation area that frequently exceeds the U.S. Environmental Protection Agency beach action value (BAV) for E. coli. A BacteriALERT program has been implemented to provide real-time E. coli estimates in the reach and notify the public of potentially harmful levels of fecal-associated pathogens as indicated by surrogate models based on real-time turbidity measurements from continuous water quality monitoring stations. However, E. coli does not provide information about the sources of fecal contamination and its accuracy as a human health indicator is questionable when sources of contamination are non-human. The objectives of our study were to investigate, within the Park and surrounding watersheds, seasonal and precipitation-related patterns in microbial source tracking marker concentrations of possible sources (human, dog, and ruminant), assess correlations between source contamination levels and culturable E. coli levels, determine which sources best explained model-based E. coli estimates above the BAV and detection of esp2 (a marker for the esp gene associated with pathogenic strains of Enterococcus faecium and Enterococcus faecalis), and investigate associations between source contamination levels and land use features. Three BacteriALERT sites on the Chattahoochee River were sampled six times per season in the winter and summer from December 2015 through September 2017, and 11 additional stream sites (synoptic sites) from the CRNRA watershed were sampled once per season. Samples were screened with microbial source tracking (MST) quantitative PCR (qPCR) markers for humans (HF183 Taqman), dogs (DogBact), and ruminants (Rum2Bac), the esp2 qPCR marker, and culturable E. coli. At the BacteriALERT sites, HF183 Taqman concentrations were higher under wet conditions DogBact concentrations were greater in the winter and under wet conditions, and Rum2Bac concentrations were comparatively low throughout the study with no difference across seasons or precipitation conditions. Concentrations of HF183 Taqman, DogBact, and Rum2Bac were positively correlated with culturable E. coli concentrations; however, DogBact had the largest R2 value among the three markers, and the forward stepwise regression indicated it was the best predictor of culturable E. coli concentrations at the BacteriALERT sites. Recursive partitioning indicated that BAV exceedances of model-based E. coli estimates were best explained by DogBact concentrations ≥3 gene copies per mL (CN/mL). Detections of esp2 at BacteriALERT sites were best explained by DogBact concentrations ≥11 CN/mL, while detections of esp2 at synoptic sites were best explained by HF183 Taqman ≥29 CN/mL. At the synoptic sites, HF183 Taqman levels were associated with wastewater treatment plant density. However, this relationship was driven primarily by a single site, suggesting possible conveyance issues in that catchment. esp2 detections at synoptic sites were positively associated with development within a 2-km radius and negatively associated with development within the catchment, suggesting multiple sources of esp2 in the watershed. DogBact and Rum2Bac were not associated with the land use features included in our analyses. Implications for Park management include: 1) fecal contamination levels were highest during wet conditions and in the off season when fewer visitors are expected to be participating in water-based recreation, 2) dogs are likely contributors to fecal contamination in the CRNRA and may be sources of pathogenic bacteria indicating further investigation of the origins of this contamination may be warranted as would be research to understand the human health risks from exposure to dog fecal contamination, and 3) high levels of the human marker at one site in the CRNRA watershed suggests more extensive monitoring in that catchment may locate the origin of human fecal contamination detected during this study.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2019.115435","usgsCitation":"McKee, A.M., Molina, M., Cyterski, M., and Couch, A., 2020, Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use: Water Research, v. 171, 115435, 12 p., https://doi.org/10.1016/j.watres.2019.115435.","productDescription":"115435, 12 p.","ipdsId":"IP-105660","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":458294,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2019.115435","text":"Publisher Index Page"},{"id":437182,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P957P46S","text":"USGS data release","linkHelpText":"Microbial Source Tracking Marker Concentrations in the Chattahoochee River National Recreation Area Watershed in 2015-2017, Georgia, USA"},{"id":372227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Chattahoochee River National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.51370239257812,\n 33.90347621404078\n ],\n [\n -83.91769409179688,\n 33.90347621404078\n ],\n [\n -83.91769409179688,\n 34.250405862125\n ],\n [\n -84.51370239257812,\n 34.250405862125\n ],\n [\n -84.51370239257812,\n 33.90347621404078\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"171","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKee, Anna M. 0000-0003-2790-5320 amckee@usgs.gov","orcid":"https://orcid.org/0000-0003-2790-5320","contributorId":166725,"corporation":false,"usgs":true,"family":"McKee","given":"Anna","email":"amckee@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Molina, Marirosa","contributorId":220538,"corporation":false,"usgs":false,"family":"Molina","given":"Marirosa","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":782033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cyterski, Mike","contributorId":222389,"corporation":false,"usgs":false,"family":"Cyterski","given":"Mike","email":"","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":782034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Couch, Ann","contributorId":222390,"corporation":false,"usgs":false,"family":"Couch","given":"Ann","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":782035,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227717,"text":"70227717 - 2020 - Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA","interactions":[],"lastModifiedDate":"2022-01-27T16:55:07.591983","indexId":"70227717","displayToPublicDate":"2019-12-25T10:48:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7470,"text":"Ecology & Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA","title":"Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA","docAbstract":"Leveraging existing presence records and geospatial datasets, species distribution modeling has been widely applied to informing species conservation and restoration efforts. Maxent is one of the most popular modeling algorithms, yet recent research has demonstrated Maxent models are vulnerable to prediction errors related to spatial sampling bias and model complexity. Despite elevated rates of biodiversity imperilment in stream ecosystems, the application of Maxent models to stream networks has lagged, as has the availability of tools to address potential sources of error and calculate model evaluation metrics when modeling in nonraster environments (such as stream networks). Herein, we use Maxent and customized R code to estimate the potential distribution of paddlefish (Polyodon spathula) at a stream-segment level within the Arkansas River basin, USA, while accounting for potential spatial sampling bias and model complexity. Filtering the presence data appeared to adequately remove an eastward, large-river sampling bias that was evident within the unfiltered presence dataset. In particular, our novel riverscape filter provided a repeatable means of obtaining a relatively even coverage of presence data among watersheds and streams of varying sizes. The greatest differences in estimated distributions were observed among models constructed with default versus AICC-selected parameterization. Although all models had similarly high performance and evaluation metrics, the AICC-selected models were more inclusive of westward-situated and smaller, headwater streams. Overall, our results solidified the importance of accounting for model complexity and spatial sampling bias in SDMs constructed within stream networks and provided a roadmap for future paddlefish restoration efforts in the study area.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5913","usgsCitation":"Taylor, A., Hafen, T., Holley, C.T., Gonzalez, A., and Long, J.M., 2020, Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA: Ecology & Evolution, v. 10, no. 2, p. 705-717, https://doi.org/10.1002/ece3.5913.","productDescription":"13 p.","startPage":"705","endPage":"717","ipdsId":"IP-108639","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5913","text":"Publisher Index Page"},{"id":394979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Colorado, Kansas, Missouri, Nebraska, New Mexico, Texas","otherGeospatial":"Arkansas River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.314453125,\n 34.08906131584994\n ],\n [\n -91.845703125,\n 34.08906131584994\n ],\n [\n -91.845703125,\n 39.30029918615029\n ],\n [\n -107.314453125,\n 39.30029918615029\n ],\n [\n -107.314453125,\n 34.08906131584994\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-12-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, A. T.","contributorId":264887,"corporation":false,"usgs":false,"family":"Taylor","given":"A. T.","affiliations":[{"id":54572,"text":"University of Central Oklahoma","active":true,"usgs":false}],"preferred":false,"id":831896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hafen, T.","contributorId":272271,"corporation":false,"usgs":false,"family":"Hafen","given":"T.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":831897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holley, Colt Taylor 0000-0003-4172-4331","orcid":"https://orcid.org/0000-0003-4172-4331","contributorId":272272,"corporation":false,"usgs":true,"family":"Holley","given":"Colt","email":"","middleInitial":"Taylor","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":831898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonzalez, A.","contributorId":272273,"corporation":false,"usgs":false,"family":"Gonzalez","given":"A.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":831899,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":831900,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70209448,"text":"70209448 - 2020 - Environmental tracer evidence for connection between shallow and bedrock aquifers and high intrinsic susceptibility to contamination of the conterminous U.S. glacial aquifer","interactions":[],"lastModifiedDate":"2020-05-04T18:29:03.706787","indexId":"70209448","displayToPublicDate":"2019-12-23T07:20:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Environmental tracer evidence for connection between shallow and bedrock aquifers and high intrinsic susceptibility to contamination of the conterminous U.S. glacial aquifer","docAbstract":"Covering a large portion of the northern conterminous United States (1.87 x 106 km2), the glacial aquifer serves as the primary water supply for 39 million public and domestic water users. Mean groundwater age, groundwater age distribution, and susceptibility to land surface contamination, using a new metric (Susceptibility Index; SI) based on the full age distribution and less prone to bias than estimated mean age, is reported for 168 public and domestic wells across the aquifer. Comparison of groundwater age metrics between well networks of varying spatial scale suggest an extensive sample network of equally spaced, long screened interval wells can be used to characterize aquifer wide groundwater age. Estimated mean age ranges from 1 to 50,000 years and, according to the composite age distribution, approximately 63 percent of all sampled water recharged after 1950 (i.e., modern) and 18 percent of the sampled water was recharged greater than 10,000 years ago. The later finding strongly suggests a connection between the glacial aquifer and underlying bedrock aquifers. Statistical analysis of glacial aquifer hydrogeology and age metrics show groundwater ages are young (less than few 100 years) and more susceptible to land surface contamination (larger SI) in unconfined and shallow portions of the aquifer. Old groundwater (greater than 1000 years) is more often associated with thicker sequences of fine grain sediments and/or shallow bedrock. Calculated SI is shown to be more strongly related to the number of land surface contaminants detected than mean age or fraction modern. Statistical analysis of SI and hydrogeology indicates SI is largely dictated by well depth and confinement. This study demonstrates how sample network design can be used to characterize groundwater age of large aquifers with a limited number of samples and how interpretation of environmental tracers can be used to improve conceptual models of groundwater aquifers and identify groundwater susceptible to contamination.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.124505","collaboration":"","usgsCitation":"Solder, J.E., Jurgens, B., Stackelberg, P.E., and Shope, C., 2020, Environmental tracer evidence for connection between shallow and bedrock aquifers and high intrinsic susceptibility to contamination of the conterminous U.S. glacial aquifer: Journal of Hydrology, v. 583, 124505, 12 p., https://doi.org/10.1016/j.jhydrol.2019.124505.","productDescription":"124505, 12 p.","ipdsId":"IP-090099","costCenters":[{"id":610,"text":"Utah Water Science 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0000-0002-1818-355X","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":204864,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":786518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shope, Christopher L. 0000-0003-4209-049X","orcid":"https://orcid.org/0000-0003-4209-049X","contributorId":223873,"corporation":false,"usgs":false,"family":"Shope","given":"Christopher L.","affiliations":[{"id":40783,"text":"State of Utah Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":786519,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207547,"text":"70207547 - 2020 - An experimental evaluation of the feasibility of inferring concentrations of a visible tracer dye from remotely sensed data in turbid rivers","interactions":[],"lastModifiedDate":"2019-12-24T12:08:16","indexId":"70207547","displayToPublicDate":"2019-12-22T11:55:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"An experimental evaluation of the feasibility of inferring concentrations of a visible tracer dye from remotely sensed data in turbid rivers","docAbstract":"The movement of contaminants and biota within river channels is influenced by the flow field via various processes of dispersion. Understanding and modeling of these processes thus can facilitate applications ranging from the prediction of travel times for spills of toxic materials to the simulation of larval drift for endangered species of fish. A common means of examining dispersion in rivers involves conducting tracer experiments with a visible tracer dye. Whereas conventional in situ instruments can only measure variations in dye concentration over time at specific, fixed locations, remote sensing could provide more detailed, spatially distributed information for characterizing dispersion patterns and validating two-dimensional numerical models. Although previous studies have demonstrated the potential to infer dye concentrations from remotely sensed data in clear-flowing streams, whether this approach can be applied to more turbid rivers remains an open question. To evaluate the feasibility of mapping spatial patterns of dispersion in streams with greater turbidity, we conducted an experiment that involved manipulating dye concentration and turbidity while acquiring field spectra and hyperspectral and RGB (red, green, blue) images from a small Unoccupied Aircraft System (sUAS). Applying an Optimal Band Ratio Analysis (OBRA) algorithm to these data sets indicated strong relationships between reflectance (i.e., water color) and Rhodamine WT dye concentration across four different turbidity levels from 40-60 NTU. Moreover, we obtained high correlations between spectrally based quantities (i.e., band ratios) and dye concentration for the original, essentially continuous field spectra; field spectra resampled to the bands of a five-band imaging system and an RGB camera; and both hyperspectral and RGB images acquired from a sUAS during the experiment. The results of this study thus confirmed the potential to map dispersion patterns of tracer dye via remote sensing and suggested that this approach can be extended to more turbid rivers than those examined previously.","language":"English","publisher":"MDPI","doi":"10.3390/rs12010057","usgsCitation":"Legleiter, C.J., Manley, P., Erwin, S.O., and Bulliner, E.A., 2020, An experimental evaluation of the feasibility of inferring concentrations of a visible tracer dye from remotely sensed data in turbid rivers: Remote Sensing, v. 12, no. 1, 57, 21 p., https://doi.org/10.3390/rs12010057.","productDescription":"57, 21 p.","ipdsId":"IP-112896","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":458311,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12010057","text":"Publisher Index Page"},{"id":437185,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91ZRGKQ","text":"USGS data release","linkHelpText":"Field spectra, UAS-based hyperspectral and RGB images, and in situ measurements of turbidity and Rhodamine WT dye concentration from an experiment conducted at the USGS Columbia Environmental Research Center, Columbia, MO, on April 2, 2019"},{"id":370672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","city":"Columbia","otherGeospatial":"Columbia Environmental Research Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.28494167327881,\n 38.905995699991145\n ],\n [\n -92.27007150650024,\n 38.905995699991145\n ],\n [\n -92.27007150650024,\n 38.91711561447239\n ],\n [\n -92.28494167327881,\n 38.91711561447239\n ],\n [\n -92.28494167327881,\n 38.905995699991145\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":778425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manley, Paul 0000-0001-6062-1149","orcid":"https://orcid.org/0000-0001-6062-1149","contributorId":221490,"corporation":false,"usgs":false,"family":"Manley","given":"Paul","email":"","affiliations":[{"id":37501,"text":"Missouri University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":778426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erwin, Susannah O. 0000-0002-2799-0118 serwin@usgs.gov","orcid":"https://orcid.org/0000-0002-2799-0118","contributorId":5183,"corporation":false,"usgs":true,"family":"Erwin","given":"Susannah","email":"serwin@usgs.gov","middleInitial":"O.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":778427,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bulliner, Edward A. 0000-0002-2774-9295 ebulliner@usgs.gov","orcid":"https://orcid.org/0000-0002-2774-9295","contributorId":4983,"corporation":false,"usgs":true,"family":"Bulliner","given":"Edward","email":"ebulliner@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":778428,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215153,"text":"70215153 - 2020 - A hydrologic landscapes perspective on groundwater connectivity of depressional wetlands","interactions":[],"lastModifiedDate":"2020-10-08T14:52:59.912851","indexId":"70215153","displayToPublicDate":"2019-12-21T09:46:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A hydrologic landscapes perspective on groundwater connectivity of depressional wetlands","docAbstract":"Structural evidence presented here documents that deformation was ongoing within the lower Colorado River corridor (southwestern USA) during and after the latest Miocene Epoch, postdating large-magnitude extension and metamorphic core complex formation. Geometric and kinematic data collected on faults in key geologic units constrain the timing of deformation in relation to the age of the Bouse Formation, a unit that records the first arrival and integration of the Colorado River. North-south–striking extensional, NW-SE–striking oblique dextral, NE-SW–striking oblique sinistral, and east-west–striking contractional faults and related structures are observed to deform pre– (>6 Ma), syn– (6–4.8 Ma), and post–Bouse Formation (<4.8 Ma) strata. Fault displacements are typically at the centimeter to meter scale, and locally exhibit 10-m-scale displacements. Bouse Formation basalt carbonate locally exhibits outcrop-scale (tens of meters) syndepositional dips of 30°–90°, draped over and encrusted upon paleotopography, and has a basin-wide vertical distribution of as much as 500 m. We argue that part of this vertical distribution of Bouse Formation deposits represents syn- and post-Bouse deformation that enhanced north-south–trending depocenters due to combined tectonic and isostatic subsidence in a regional fault kinematic framework of east-west diffuse extension within an overall strain field of dextral transtension. Here we (1) characterize post-detachment tectonism within the corridor, (2) show that diffuse tectonism is cumulatively significant and likely modified original elevations of Bouse Formation outcrops, and (3) demonstrate that this tectonism may have played a role in the integration history of the lower Colorado River. We suggest a model whereby intracontinental transtension took place in a several hundred kilometers-wide area inboard of the San Andreas fault within a diffuse Pacific–North America plate margin since the latest Miocene.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02104.1","usgsCitation":"Thacker, J., Karlstrom, K., Crossey, L., Crow, R.S., Cassidy, C., Beard, L.S., Singleton, J., Strickland, E., Seymour, N., and Wyatt, M., 2020, Post-12 Ma deformation of the lower Colorado River corridor, southwestern USA: Implications for diffuse transtension and the Bouse Formation: Geosphere, v. 16, no. 1, p. 111-135, https://doi.org/10.1130/GES02104.1.","productDescription":"25 p.","startPage":"111","endPage":"135","ipdsId":"IP-104568","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":458319,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02104.1","text":"Publisher Index Page"},{"id":371093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Lower Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.6201171875,\n 32.7872745269555\n ],\n [\n -113.51074218749999,\n 32.7872745269555\n ],\n [\n -113.51074218749999,\n 35.94243575255426\n ],\n [\n -115.6201171875,\n 35.94243575255426\n ],\n [\n -115.6201171875,\n 32.7872745269555\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Thacker, Jacob 0000-0001-7174-6115 jthacker@usgs.gov","orcid":"https://orcid.org/0000-0001-7174-6115","contributorId":187771,"corporation":false,"usgs":false,"family":"Thacker","given":"Jacob","email":"jthacker@usgs.gov","affiliations":[],"preferred":false,"id":779160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karlstrom, Karl","contributorId":218165,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Karl","affiliations":[{"id":16658,"text":"UNM","active":true,"usgs":false}],"preferred":false,"id":775174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crossey, Laura","contributorId":220554,"corporation":false,"usgs":false,"family":"Crossey","given":"Laura","affiliations":[{"id":16658,"text":"UNM","active":true,"usgs":false}],"preferred":false,"id":775175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crow, Ryan S. 0000-0002-2403-6361 rcrow@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-6361","contributorId":5792,"corporation":false,"usgs":true,"family":"Crow","given":"Ryan","email":"rcrow@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":775172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cassidy, Colleen 0000-0003-2963-9185","orcid":"https://orcid.org/0000-0003-2963-9185","contributorId":207193,"corporation":false,"usgs":true,"family":"Cassidy","given":"Colleen","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":775176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beard, L. Sue 0000-0001-9552-1893 sbeard@usgs.gov","orcid":"https://orcid.org/0000-0001-9552-1893","contributorId":152,"corporation":false,"usgs":true,"family":"Beard","given":"L.","email":"sbeard@usgs.gov","middleInitial":"Sue","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":775177,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Singleton, John","contributorId":220555,"corporation":false,"usgs":false,"family":"Singleton","given":"John","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":775178,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Strickland, Evan","contributorId":220556,"corporation":false,"usgs":false,"family":"Strickland","given":"Evan","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":775179,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Seymour, Nikki","contributorId":220557,"corporation":false,"usgs":false,"family":"Seymour","given":"Nikki","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":775180,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wyatt, Michael","contributorId":220558,"corporation":false,"usgs":false,"family":"Wyatt","given":"Michael","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":775181,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70207543,"text":"70207543 - 2020 - Invertebrate communities of Prairie-Pothole wetlands in the age of the aquatic Homogenocene","interactions":[],"lastModifiedDate":"2020-10-12T16:29:50.24873","indexId":"70207543","displayToPublicDate":"2019-12-20T11:44:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Invertebrate communities of Prairie-Pothole wetlands in the age of the aquatic Homogenocene","docAbstract":"Simplification of communities is a common consequence of anthropogenic modification. However, the prevalence and mechanisms of biotic homogenization among wetland systems require further examination. Biota of wetlands in the North American Prairie Pothole Region are adapted to high spatial and temporal variability in ponded-water duration and salinity. Recent climate change, however, has resulted in decreased hydrologic variability. Land-use changes have exacerbated this loss of variability. We used aquatic-macroinvertebrate data from 16 prairie-pothole wetlands sampled between 1992 and 2015 to explore homogenization of wetland communities. Macroinvertebrate communities of small wetlands that continued to cycle between wet and dry phases experienced greater turnover and supported unique taxa compared to larger wetlands that shifted towards less dynamic permanently ponded, lake-like regimes. Temporal turnover in beta-diversity was lowest in these permanently ponded wetlands. Additionally, wetlands that shifted to permanently ponded regimes also experienced a shift from palustrine to lacustrine communities. While increased pond permanence can increase species and overall beta-diversity in local areas previously lacking lake communities, homogenization of wetland communities at a larger, landscape scale can result in an overall loss of biodiversity as the diverse communities of many wetland systems become increasingly similar to those of lakes.
","language":"English","publisher":"Springer International Publishing","doi":"10.1007/s10750-019-04154-4","usgsCitation":"McLean, K., Mushet, D.M., Sweetman, J.N., Anteau, M.J., and Wiltermuth, M.T., 2020, Invertebrate communities of Prairie-Pothole wetlands in the age of the aquatic Homogenocene: Hydrobiologia, v. 847, p. 3773-3793, https://doi.org/10.1007/s10750-019-04154-4.","productDescription":"21 p.","startPage":"3773","endPage":"3793","ipdsId":"IP-111199","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":370671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","county":"Stutsman County","otherGeospatial":"Cottonwood Lake Study Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.77999114990234,\n 47.820762392755846\n ],\n [\n -100.63407897949219,\n 47.820762392755846\n ],\n [\n -100.63407897949219,\n 47.939116930322\n ],\n [\n -100.77999114990234,\n 47.939116930322\n ],\n [\n -100.77999114990234,\n 47.820762392755846\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"847","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"McLean, Kyle 0000-0003-3803-0136 kmclean@usgs.gov","orcid":"https://orcid.org/0000-0003-3803-0136","contributorId":168533,"corporation":false,"usgs":true,"family":"McLean","given":"Kyle","email":"kmclean@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":778407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":778408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweetman, Jon N. 0000-0002-9849-7355","orcid":"https://orcid.org/0000-0002-9849-7355","contributorId":221489,"corporation":false,"usgs":false,"family":"Sweetman","given":"Jon","email":"","middleInitial":"N.","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":778409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":778410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":778411,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}