Karst spring measurements assess biogeochemical processes occurring within groundwater contributing areas to springs (springsheds) but can only provide aggregated information. To better understand spatially distributed processes that comprise these aggregated measures, we investigated aquifer denitrification evidence in groundwater wells (n = 16) distributed throughout a springshed in the Upper Floridan aquifer in northern Florida. Aquifer geochemistry, nitrate isotopes, and dissolved gases were compared against similar measurements at the spring outlet to evaluate spatial heterogeneity of denitrification evidence in relation to land surface–aquifer connectivity. Sample locations spanned spatial variation in recharge processes (i.e., diffuse vs. focused recharge) and proximity to sources of denitrification reactants (e.g., wetlands). Although no distinct spatial pattern in denitrification was uncovered, excess dissolved N2 gas measurements were only above detection in the unconfined springshed, with some evidence of a wetland proximity effect. Measured oxidation–reduction potential and dissolved oxygen poorly predicted denitrification, indicating that measured denitrification may be occurring upgradient from sampled wells. Despite dramatic spatial chemical heterogeneity across wells, mean values for recharge nitrate concentrations (0.02 to 5.56 mg N L−1) and excess N2 from aquifer denitrification (below detection to 1.37 mg N L−1) corresponded reasonably with mean spring outlet measurements for initial nitrate (0.78 to 1.36 mg N L−1) and excess N2 (0.15 to 1.04 mg N L−1). Congruence between groundwater and spring measurements indicates that combining sampling at the spring outlet and across the springshed is useful for understanding spatial aquifer denitrification. However, this approach would be improved with a high‐density sampling network with transects of wells along distinct groundwater flow paths.
Interactions between oceanic and atmospheric processes within coral reefs can significantly alter local-scale (< km) water temperatures, and consequently drive variations in heat stress and bleaching severity. The Scott Reef atoll system was one of many reefs affected by the 2015–2016 mass coral bleaching event across tropical Australia, and specifically experienced sea surface temperature anomalies of 2 °C that caused severe mass bleaching (> 60%) over most of this system; however, the bleaching patterns were not uniform. Little is known about the processes governing thermodynamic variability within atolls, particularly those that are dominated by large amplitude tides. Here, we identify three mechanisms at Scott Reef that alleviated heat stress during the marine heatwave in 2016: (1) the cool wake of a tropical cyclone that induced temperature drops of 1.3 °C over a period of 8 days; (2) air–sea heat fluxes that interacted with the reef morphology during neap tides at one of the atolls to reduce water temperatures by up to 2.9 °C; (3) internal tidal processes that forced deeper and cooler water (up to 2.7 °C) into some sections of the shallow reefs. The latter two processes created localized areas of reduced temperatures that led to lower incidences of coral bleaching for parts of the reef. We predict these processes are likely to occur in other similar tide-dominated reef environments worldwide. Identifying locations where physical processes reduce heat stress will likely be critical for coral reefs in the future, by maintaining communities that can help facilitate local recovery of reefs following bleaching events that are expected to increase in frequency and severity in the coming decades.
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The injection of CO2 in deep subsurface sedimentary reservoirs is the most commonly discussed method; however, the potential for CO2 leakage can create long-term stability concerns. This report discusses the feasibility of an alternative form of geologic CO2 storage: CO2 mineralization. In this method, CO2 reacts with rocks and minerals to form solid and stable carbonate rocks. New pilot projects and laboratory-based kinetics experiments have revealed that this method, both in situ and ex situ, may be a viable option for storage. In situ storage targets in-place rocks at the surface or subsurface. Ex situ storage targets industrial byproducts at the surface like mine tailings. Environmental risks include induced seismicity for in situ methods if pressure is not managed properly, as well as potential water and land use effects. However, there are fewer long-term CO2-leakage concerns for mineralization methods compared to saline storage methods and therefore potentially lower long-term monitoring costs. The costs and benefits of CO2 mineralization are compared to those of CO2 storage in saline reservoirs using estimates of pressure-limited dynamic storage capacity. This report highlights the regional potential of areas in the United States for in situ and ex situ storage, as well as their proximity to potential sources of CO2. Especially suitable targets include asbestos or other ultramafic mine tailings, in situ ultramafic rocks on the East and West Coasts, the Columbia River basalts in the Pacific Northwest, the Midcontinent Rift basalts in the midcontinent, and the basaltic Hawaiian Islands.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185079","usgsCitation":"Blondes, M.S., Merrill, M.D., Anderson, S.T., and DeVera, C.A., 2019, Carbon dioxide mineralization feasibility in the United States: U.S. Geological Survey Scientific Investigations Report 2018–5079, 29 p., https://doi.org/10.3133/sir20185079.","productDescription":"viii, 29 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095254","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":437568,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D92L53","text":"USGS data release","linkHelpText":"Geologic formations and mine locations for potential CO2 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States\"}}]}","contact":"Energy Resources Program
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
Email: gd-energyprogram@usgs.gov
Sea stars are ecologically important in rocky intertidal habitats where they can play an apex predator role, completely restructuring communities. The recent sea star die-off throughout the eastern Pacific, known as Sea Star Wasting Disease, has prompted a need to understand spatial and temporal patterns of sea star assemblages and the environmental variables that structure these assemblages. We examined spatial and temporal patterns in sea star assemblages (composition and density) across regions in the northern Gulf of Alaska and assessed the role of seven static environmental variables (distance to freshwater inputs, tidewater glacial presence, exposure to wave action, fetch, beach slope, substrate composition, and tidal range) in influencing sea star assemblage structure before and after sea star declines. Environmental variables correlated with sea star distribution can serve as proxies to environmental stressors, such as desiccation, attachment, and wave action. Intertidal sea star surveys were conducted annually from 2005 to 2018 at five sites in each of four regions that were between 100 and 420 km apart across the northern Gulf of Alaska. In the pre-disease years, assemblages were different among regions, correlated mostly to tidewater glacier presence, fetch, and tidal range. The assemblages after wasting disease were different from those before the event with lower diversity and lower density. In addition to these declines, the disease manifested itself at different times across the northern Gulf of Alaska and did not impact all species uniformly across sites. Post sea star wasting, there was a shift in the environmental variables that correlated with sea star structure, resulting in sea star assemblages being highly correlated with slope, fetch, and tidal range. In essence, sea star wasting disease resulted in a shift in the sea star assemblage that is now correlating with a slightly different combination of environmental variables. Understanding the delicate interplay of environmental variables that influence sea star assemblages could expand knowledge of the habitat preferences and tolerance ranges of important and relatively unstudied species within the northern Gulf of Alaska.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jembe.2019.151209","usgsCitation":"Konar, B., Mitchell, T.J., Iken, K., Dean, T., Esler, D., Lindeberg, M., Pister, B., and Weitzman, B., 2019, Wasting disease and static environmental variables drive sea star assemblages in the northern Gulf of Alaska: Journal of Experimental Marine Biology and Ecology, v. 520, p. 1-10, https://doi.org/10.1016/j.jembe.2019.151209.","productDescription":"151209, 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-107631","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":372418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Northern 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 -154.62158203125,\n 57.28498092462365\n ],\n [\n -145.535888671875,\n 57.28498092462365\n ],\n [\n -145.535888671875,\n 61.554109444927185\n ],\n [\n -154.62158203125,\n 61.554109444927185\n ],\n [\n -154.62158203125,\n 57.28498092462365\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"520","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Konar, Brenda","contributorId":131034,"corporation":false,"usgs":false,"family":"Konar","given":"Brenda","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":782618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Timothy J.","contributorId":222573,"corporation":false,"usgs":false,"family":"Mitchell","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":true,"id":782619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iken, K.","contributorId":178282,"corporation":false,"usgs":false,"family":"Iken","given":"K.","affiliations":[],"preferred":false,"id":782620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dean, Thomas","contributorId":140481,"corporation":false,"usgs":false,"family":"Dean","given":"Thomas","affiliations":[{"id":13512,"text":"Coastal Resources Inc., Carlsbad, CA","active":true,"usgs":false}],"preferred":false,"id":782621,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":782622,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lindeberg, Mandy","contributorId":195895,"corporation":false,"usgs":false,"family":"Lindeberg","given":"Mandy","email":"","affiliations":[],"preferred":false,"id":782623,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pister, Benjamin","contributorId":219669,"corporation":false,"usgs":false,"family":"Pister","given":"Benjamin","email":"","affiliations":[{"id":40046,"text":"Ocean Alaska Science and Learning Center, National Park Service","active":true,"usgs":false}],"preferred":false,"id":782624,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weitzman, Ben P. 0000-0001-7559-3654 bweitzman@usgs.gov","orcid":"https://orcid.org/0000-0001-7559-3654","contributorId":5123,"corporation":false,"usgs":true,"family":"Weitzman","given":"Ben P.","email":"bweitzman@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":782625,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202237,"text":"70202237 - 2019 - Improved automated detection of subpixel-scale inundation – Revised Dynamic Surface Water Extent (DSWE) partial surface water tests","interactions":[],"lastModifiedDate":"2019-02-19T11:45:14","indexId":"70202237","displayToPublicDate":"2019-02-19T11:45:10","publicationYear":"2019","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":"Improved automated detection of subpixel-scale inundation – Revised Dynamic Surface Water Extent (DSWE) partial surface water tests","docAbstract":"In order to produce useful hydrologic and aquatic habitat data from the Landsat system, the U.S. Geological Survey has developed the “Dynamic Surface Water Extent” (DSWE) Landsat Science Product. DSWE will provide long-term, high-temporal resolution data on variations in inundation extent. The model used to generate DSWE is composed of five decision-rule based tests that do not require scene-based training. To allow its general application, required inputs are limited to the Landsat at-surface reflectance product and a digital elevation model. Unlike other Landsat-based water products, DSWE includes pixels that are only partially covered by water to increase inundation dynamics information content. Previously published DSWE model development included one wetland-focused test developed through visual inspection of field-collected Everglades spectra. A comparison of that test’s output against Everglades Depth Estimation Network (EDEN) in situ data confirmed the expectation that omission errors were a prime source of inaccuracy in vegetated environments. Further evaluation exposed a tendency toward commission error in coniferous forests. Improvements to the subpixel level “partial surface water” (PSW) component of DSWE was the focus of this research. Spectral mixture models were created from a variety of laboratory and image-derived endmembers. Based on the mixture modeling, a more “aggressive” PSW rule improved accuracy in herbaceous wetlands and reduced errors of commission elsewhere, while a second “conservative” test provides an alternative when commission errors must be minimized. Replication of the EDEN-based experiments using the revised PSW tests yielded a statistically significant increase in mean overall agreement (4%, p = 0.01, n = 50) and a statistically significant decrease (11%, p = 0.009, n = 50) in mean errors of omission. Because the developed spectral mixture models included image-derived vegetation endmembers and laboratory spectra for soil groups found across the US, simulations suggest where the revised DSWE PSW tests perform as they do in the Everglades and where they may prove problematic. Visual comparison of DSWE outputs with an unusual variety of coincidently collected images for locations spread throughout the US support conclusions drawn from Everglades quantitative analyses and highlight DSWE PSW component strengths and weaknesses.
","language":"English","publisher":"MDPI","doi":"10.3390/rs11040374","usgsCitation":"Jones, J., 2019, Improved automated detection of subpixel-scale inundation – Revised Dynamic Surface Water Extent (DSWE) partial surface water tests: Remote Sensing, v. 11, no. 4, p. 1-26, https://doi.org/10.3390/rs11040374.","productDescription":"Article 374; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-102379","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":467892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11040374","text":"Publisher Index Page"},{"id":361339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":757437,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70208585,"text":"70208585 - 2019 - Micro-geographic population genetic structure within Arctic cod (Boreogadus saida) in Beaufort Sea of Alaska","interactions":[],"lastModifiedDate":"2020-02-19T11:53:13","indexId":"70208585","displayToPublicDate":"2019-02-19T11:44:42","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1936,"text":"ICES Journal of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"Micro-geographic population genetic structure within Arctic cod (Boreogadus saida) in Beaufort Sea of Alaska","docAbstract":"Many marine organisms show significant levels of genetic heterogeneity on local spatial scales despite exhibiting limited genetic structure at large geographic scales which can be produced through a variety of mechanisms. The Arctic cod (Boreogadus saida) is a circumpolar species and is a vital species in Arctic food webs. To examine population genetic structure of Arctic cod at macro- and micro-geographic scales, we characterized variation at mitochondrial DNA (mtDNA) and microsatellite loci among Arctic cod located in the Chukchi and Beaufort seas in Alaska. We found two distinct mtDNA haplotype clusters, although there was no underlying geographic pattern (FST = −0.001). Congruent with this finding, microsatellite loci suggested a panmictic population (FST = 0.001) across northern Alaskan marine waters at a large spatial scale. However, we found slight but significant micro-geographic partitioning of genetic variation in the southern shelf of the Beaufort Sea that appeared to be associated with the western reaches of the Mackenzie River plume. This fine-scale spatial pattern was not associated with kin-associated groups, suggesting larvae cohorts are not remaining together throughout development. We hypothesize that this pattern reflects the intermixing of Pacific and Arctic origin lineages of Arctic cod.
","language":"English","publisher":"Oxford Uni. Press","doi":"10.1093/icesjms/fsz041","usgsCitation":"Wilson, R.E., Sage, G.K., Wedemeyer, K., Sonsthagen, S.A., Menning, D.M., Gravley, M.C., Nelson, R.J., and Talbot, S.L., 2019, Micro-geographic population genetic structure within Arctic cod (Boreogadus saida) in Beaufort Sea of Alaska: ICES Journal of Marine Science, v. 76, no. 6, p. 1713-1721, https://doi.org/10.1093/icesjms/fsz041.","productDescription":"9 p.","startPage":"1713","endPage":"1721","ipdsId":"IP-102019","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":372416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beafort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.728515625,\n 68.95839084822076\n ],\n [\n -141.416015625,\n 69.2249968541159\n ],\n [\n -141.416015625,\n 73.94679115710252\n ],\n [\n -168.8818359375,\n 73.87371654457475\n ],\n [\n -169.716796875,\n 66.9816661111497\n ],\n [\n -165.8056640625,\n 67.08455048507471\n ],\n [\n -166.4208984375,\n 67.82583637985663\n ],\n [\n -166.728515625,\n 68.95839084822076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":782604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":782605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wedemeyer, Kate","contributorId":207047,"corporation":false,"usgs":false,"family":"Wedemeyer","given":"Kate","email":"","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":false,"id":782606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":782607,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Menning, Damian M. 0000-0003-3547-3062 dmenning@usgs.gov","orcid":"https://orcid.org/0000-0003-3547-3062","contributorId":205131,"corporation":false,"usgs":true,"family":"Menning","given":"Damian","email":"dmenning@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":782608,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gravley, Megan C. 0000-0002-4947-0236 mgravley@usgs.gov","orcid":"https://orcid.org/0000-0002-4947-0236","contributorId":202812,"corporation":false,"usgs":true,"family":"Gravley","given":"Megan","email":"mgravley@usgs.gov","middleInitial":"C.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":782609,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nelson, R. John","contributorId":98215,"corporation":false,"usgs":true,"family":"Nelson","given":"R.","email":"","middleInitial":"John","affiliations":[],"preferred":false,"id":782610,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":782611,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202260,"text":"70202260 - 2019 - Estimating uncertainty of North American landbird population sizes","interactions":[],"lastModifiedDate":"2019-02-19T11:38:08","indexId":"70202260","displayToPublicDate":"2019-02-19T11:38:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating uncertainty of North American landbird population sizes","docAbstract":"An important metric for many aspects of species conservation planning and risk assessment is an estimate of total population size. For landbirds breeding in North America, Partners in Flight (PIF) generates global, continental, and regional population size estimates. These estimates are an important component of the PIF species assessment process, but have also been used by others for a range of applications. The PIF population size estimates are primarily calculated using a formula designed to extrapolate bird counts recorded by the North American Breeding Bird Survey (BBS) to regional population estimates. The extrapolation formula includes multiple assumptions and sources of uncertainty, but there were previously no attempts to quantify this uncertainty in the published population size estimates aside from a categorical data quality score. Using a Monte Carlo approach, we propagated the main sources of uncertainty arising from individual components of the model through to the final estimation of landbird population sizes. This approach results in distributions of population size estimates rather than point estimates. We found the width of uncertainty of population size estimates to be generally narrower than the order-of-magnitude distances between the population size score categories PIF uses in the species assessment process, suggesting confidence in the categorical ranking used by PIF. Our approach provides a means to identify species whose uncertainty bounds span more than one categorical rank, which was not previously possible with the data quality scores. Although there is still room for additional improvements to the estimation of avian population sizes and uncertainty, particularly with respect to replacing categorical model components with empirical estimates, our estimates of population size distributions have broader utility to a range of conservation planning and risk assessment activities relying on avian population size estimates.
","language":"English","publisher":"American Ornithological Society","doi":"10.5751/ACE-01331-140104","usgsCitation":"Stanton, J.C., Blancher, P.J., Rosenberg, K.V., Panjabi, A.O., and Thogmartin, W.E., 2019, Estimating uncertainty of North American landbird population sizes: Avian Conservation and Ecology, v. 14, no. 1, Article 4; 16 p., https://doi.org/10.5751/ACE-01331-140104.","productDescription":"Article 4; 16 p.","ipdsId":"IP-090781","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467893,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-01331-140104","text":"Publisher Index Page"},{"id":437569,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90SWVFU","text":"USGS data release","linkHelpText":"Population Size uncertainty estimates"},{"id":361335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":757536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blancher, Peter J.","contributorId":175182,"corporation":false,"usgs":false,"family":"Blancher","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":757537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberg, Kenneth V.","contributorId":171463,"corporation":false,"usgs":false,"family":"Rosenberg","given":"Kenneth","email":"","middleInitial":"V.","affiliations":[{"id":27615,"text":"Cornell Lab of Ornithology, Conservation Science Program","active":true,"usgs":false}],"preferred":false,"id":757538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Panjabi, Arvind O.","contributorId":169967,"corporation":false,"usgs":false,"family":"Panjabi","given":"Arvind","email":"","middleInitial":"O.","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":757539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":757540,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200151,"text":"sir20185125 - 2019 - Potential for increased inundation in flood-prone regions of southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69","interactions":[],"lastModifiedDate":"2019-02-19T14:54:42","indexId":"sir20185125","displayToPublicDate":"2019-02-19T11:28:48","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5125","displayTitle":"Potential for Increased Inundation in Flood-Prone Regions of Southeast Florida in Response to Climate and Sea-Level Changes in Broward County, Florida, 2060–69","title":"Potential for increased inundation in flood-prone regions of southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69","docAbstract":"The U.S. Geological Survey, in cooperation with Broward County Environmental Planning and Resilience Division, has developed county-scale and local-scale groundwater/surface-water models to study the potential for increased inundation and flooding in eastern Broward County that are due to changes in future climate and sea-level rise. These models were constructed by using MODFLOW 2005, with the surface-water system represented by using the Surface-Water Routing process and a new Urban Runoff process. The local-scale model allowed the use of finer grid resolution in a selected area of the county, whereas the county-scale model provided boundary conditions for the local-scale model and insight into the hydrologic behavior of the larger system. The aquifer layering, properties, and boundaries relied heavily on a previous three-dimensional variable-density solute-transport model of the same area developed by the U.S. Geological Survey. The surface-water system within these new models actively simulates a part of the extensive canal network by using level-pool routing and active structure operations within the Surface-Water Routing process. These models were used to simulate a historical base-case period (1990–99) by using measured data and regional climate model rainfall and potential evapotranspiration output. The simulated flow and water-level results generally captured the behavior of the hydrologic system. A future period (2060–69) was simulated by using regional climate model rainfall and potential evapotranspiration output representing a wetter and drier future and low, intermediate, and high sea-level rise projections. The results were used to evaluate the potential effects on the surface-water drainage system, coastal-structure operation, and wet-season groundwater levels.
Future period simulations using the county-scale model indicate that (1) the effects of the changing climate and sea level are much more evident in eastern and coastal areas of Broward County compared to western areas, with increases in groundwater level nearly equivalent to sea-level rise; (2) coastal groundwater-level increases are distributed farther inland in the wetter future scenarios than in the drier future scenarios; (3) water levels at the westernmost groundwater station locations exhibited little change caused by sea-level rise and showed more dependence on changes in precipitation; (4) there was a reduced west-to-east groundwater gradient with increasing sea-level rise; and (5) increased downstream tidal stage at the S–13 structure resulted in increased reliance on the pump to control upstream inland canal stages. Future simulations using the local-scale model indicate similar behavior as seen in the county-scale model: (1) the coastal areas exhibited the largest impacts in groundwater levels in the future scenarios; (2) the westernmost, interior areas exhibited little change during the future scenarios; and (3) there was an increased reliance on the pump at the S–13 coastal structure but to a lesser extent than indicated in the county-scale model because of the reduced temporal scale of the local-scale model.
Possible adaptation and mitigation strategies were simulated to evaluate the county-scale and local-scale models’ ability to simulate hydrologic changes. Alterations to S–13 pump operations within the county-scale model were tested, and results indicate a reduced effect of sea-level rise inland of the control structure, but the affected area is spatially limited. The concept of using pumps to reduce the local groundwater levels in two neighborhood-sized areas was tested by using the local-scale model. The MODFLOW 2005 Drain package was used to remove groundwater by using drainage elevations set to zero, 1 foot, and 2 feet above average wet-season groundwater levels. Area 1 was well connected to coastal boundaries, and a high rate of groundwater removal was required, whereas the rate of groundwater removal required was greatly reduced in Area 2, which is less connected to tidal boundaries. Water for these scenarios was assumed to be pumped to tide with no downstream effects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185125","collaboration":"Prepared in cooperation with the Broward County Environmental Planning and Resilience Division","usgsCitation":"Decker, J.D., Hughes, J.D., and Swain, E.D., 2019, Potential for increased inundation in flood-prone regions of southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69: U.S. Geological Survey Scientific Investigations Report 2018–5125, 106 p., https://doi.org/10.3133/sir20185125.","productDescription":"Report: viii, 106 p.; Data Release","numberOfPages":"118","onlineOnly":"Y","ipdsId":"IP-066244","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":361163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5125/sir20185125.pdf","text":"Report","size":"10.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5125"},{"id":361162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5125/coverthb.jpg"},{"id":361164,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E6INWZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW 2005 data sets for the simulation of potential increased inundation in flood-prone regions of Southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69"}],"country":"United States","state":"Florida","county":"Broward County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.44326782226562,\n 25.95557515483912\n ],\n [\n -80.07522583007812,\n 25.95557515483912\n ],\n [\n -80.07522583007812,\n 26.331576128197028\n ],\n [\n -80.44326782226562,\n 26.331576128197028\n ],\n [\n -80.44326782226562,\n 25.95557515483912\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Volcanoes at subduction zones reside above complex magma plumbing systems, where individual magmatic components may originate and interact at a range of pressures. Because whole-rock compositions of subduction zone magmas are the integrated result of processes operating throughout the entire plumbing system, processes such as mixing, homogenisation and magma assembly during shallow storage can overprint the chemical signatures of deeper crustal processes. Whereas melt inclusions provide an effective way to study the uppermost 10–15 km of the plumbing system, challenges remain in understanding magma intrusion, fractionation and hybridisation processes in the middle to lower crust (15–30 km depth), which commonly involves amphibole crystallisation. Here, we present new insights into the mid-crustal plumbing system at Mount St. Helens, USA, using multiple regression methods to calculate trace element partition coefficients for amphibole phenocrysts, and thus infer the trace element compositions of their equilibrium melts. The results indicate vertically distributed crystal fractionation, dominated by amphibole at higher pressures and in intermediate melts, and by plagioclase at lower pressures. Variations in Nb, Zr and REE concentrations at intermediate SiO2 contents suggest repeated scavenging of partially remelted intrusive material in the mid-crust, and mixing with material from geochemically diverse sources. Amphibole is an effective probe for deep crustal magmatism worldwide, and this approach offers a new tool to explore the structure and chemistry of arc magmas, including those forming plutonic or cumulate materials that offer no other constraints on melt composition.
","language":"English","publisher":"Springer","doi":"10.1007/s00410-018-1543-5","usgsCitation":"Humphreys, M.C., Cooper, G.F., Zhang, J., Loewen, M.W., Kent, A.J., Macpherson, C.G., and Davidson, J.P., 2019, Unravelling the complexity of magma plumbing at Mount St. Helens: A new trace element partitioning scheme for amphibole: Contributions to Mineralogy and Petrology, v. 174, p. 1-15, https://doi.org/10.1007/s00410-018-1543-5.","productDescription":"Article 9; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-094683","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467894,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/output/1308434","text":"External Repository"},{"id":361333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"174","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Humphreys, Madeleine C. S.","contributorId":213322,"corporation":false,"usgs":false,"family":"Humphreys","given":"Madeleine","email":"","middleInitial":"C. S.","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":757454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooper, George F.","contributorId":213323,"corporation":false,"usgs":false,"family":"Cooper","given":"George","email":"","middleInitial":"F.","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":757455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Jing","contributorId":213324,"corporation":false,"usgs":false,"family":"Zhang","given":"Jing","email":"","affiliations":[{"id":38738,"text":"University of Durham and Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":757456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loewen, Matthew W. 0000-0002-5621-285X","orcid":"https://orcid.org/0000-0002-5621-285X","contributorId":213321,"corporation":false,"usgs":true,"family":"Loewen","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":757453,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kent, Adam J. R.","contributorId":213325,"corporation":false,"usgs":false,"family":"Kent","given":"Adam","email":"","middleInitial":"J. R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":757457,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Macpherson, Colin G.","contributorId":213326,"corporation":false,"usgs":false,"family":"Macpherson","given":"Colin","email":"","middleInitial":"G.","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":757458,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davidson, Jon P.","contributorId":213327,"corporation":false,"usgs":false,"family":"Davidson","given":"Jon","email":"","middleInitial":"P.","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":757459,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205978,"text":"70205978 - 2019 - Assemblage structure, vertical distributions and stable‐isotope compositions of anguilliform leptocephali in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2019-10-14T11:28:02","indexId":"70205978","displayToPublicDate":"2019-02-19T11:07:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"title":"Assemblage structure, vertical distributions and stable‐isotope compositions of anguilliform leptocephali in the Gulf of Mexico","docAbstract":"In August 2007, October 2008 and September–October 2010, 241 Tucker trawl and plankton net tows were conducted at the surface to depths of 1377 m at six locations in the northern and eastern Gulf of Mexico (GOM) to document leptocephalus diversity and determine how assemblage structure, larval size, abundance and isotopic signatures differ across the region and with depth. Overall, 2696 leptocephali representing 59 distinct taxa from 10 families were collected. Five families accounted for 96% of the total catch with Congridae and Ophichthidae being the most abundant. The top four most abundant species composed 59% of the total catch and included: Ariosoma balearicum, Paraconger caudilimbatus, Rhynchoconger flavus and Ophichthus gomesii. Four anguilliform species not previously documented in the GOM as adults or leptocephali were collected in this study, including Monopenchelys acuta, Quassiremus ascensionis, Saurenchelys stylura and one leptocephalus only known from its larval stage, Leptocephalus proboscideus. Leptocephalus catches were significantly greater at night than during the day. Catches at night were concentrated in the upper 200 m of the water column and significantly declined with increasing depth. Leptocephali abundances and assemblages were significantly different between sites on the upper continental slope (c. 500 m depth) and sites on the middle to lower continental slope (c. 1500–2300 m). Sites on the lower continental slope had a mixture of deep‐sea demersal, bathypelagic and coastal species, whereas upper‐slope sites contained several numerically dominant species (e.g., A. balearicum, P. caudilimbatus) that probably spawn over the continental shelf and upper slope of the GOM. Standard lengths of the four dominant species differed between sites and years, indicating heterochronic reproduction and potential larval source pools within and outside of the GOM. Stable‐isotope analyses (δ13C and δ15N) conducted on 185 specimens from six families revealed that leptocephali had a wide range of isotopic values at the family and size‐class levels. Species in the families Muraenidae, Congridae and Ophichthidae had similar δ15N values compared with the broad range of δ15N values seen in the deep‐sea families Nemichthyidae, Nettastomatidae and Synaphobranchidae. Stable‐isotope values were variably related to length, with δ15N values being positively size correlated in ophichthids and δ13C values being negatively size correlated in A. balearicum and P. caudilimbatus. Results suggest that leptocephali feed in various water depths and masses, and on different components of POM, which could lead to niche partitioning. Ecological aspects of these important members of the plankton community provide insight into larval connectivity in the GOM as well as the early life history of Anguilliformes.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.13933","usgsCitation":"Quattrini, A., McClain Counts, J., Artabane, S.J., Roa-Varon, A., McIver, T.C., Michael Rhode, and Ross, S., 2019, Assemblage structure, vertical distributions and stable‐isotope compositions of anguilliform leptocephali in the Gulf of Mexico: Journal of Fish Biology, v. 94, no. 4, p. 621-647, https://doi.org/10.1111/jfb.13933.","productDescription":"27 p.","startPage":"621","endPage":"647","ipdsId":"IP-097672","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":368303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.71240234375,\n 25.799891182088334\n ],\n [\n -83.1005859375,\n 25.799891182088334\n ],\n [\n -83.1005859375,\n 30.4297295750316\n ],\n [\n -97.71240234375,\n 30.4297295750316\n ],\n [\n -97.71240234375,\n 25.799891182088334\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"94","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Quattrini, Andrea M. 0000-0002-4247-3055","orcid":"https://orcid.org/0000-0002-4247-3055","contributorId":62339,"corporation":false,"usgs":false,"family":"Quattrini","given":"Andrea M.","affiliations":[],"preferred":false,"id":773146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McClain Counts, Jennifer 0000-0002-3383-5472","orcid":"https://orcid.org/0000-0002-3383-5472","contributorId":215718,"corporation":false,"usgs":true,"family":"McClain Counts","given":"Jennifer","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":773147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Artabane, Stephen J.","contributorId":219772,"corporation":false,"usgs":false,"family":"Artabane","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":773148,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roa-Varon, Adela","contributorId":189930,"corporation":false,"usgs":false,"family":"Roa-Varon","given":"Adela","affiliations":[],"preferred":false,"id":773149,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIver, Tara C.","contributorId":219773,"corporation":false,"usgs":false,"family":"McIver","given":"Tara","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":773150,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Michael Rhode","contributorId":195732,"corporation":false,"usgs":false,"family":"Michael Rhode","affiliations":[],"preferred":false,"id":773151,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ross, Steve W.","contributorId":41134,"corporation":false,"usgs":false,"family":"Ross","given":"Steve W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":773152,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205813,"text":"70205813 - 2019 - The effects of topographic surveying technique and data resolution on the detection and interpretation of geomorphic change","interactions":[],"lastModifiedDate":"2019-10-04T10:30:15","indexId":"70205813","displayToPublicDate":"2019-02-19T10:21:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"The effects of topographic surveying technique and data resolution on the detection and interpretation of geomorphic change","docAbstract":"Change detection of high resolution topographic data is commonly used in river valleys to quantify reach- and site-scale sediment budgets by estimating the erosion/deposition volume, and to interpret the geomorphic processes driving erosion and deposition. Field survey data are typically collected as point clouds that are often converted to gridded raster datasets and the ultimate choice of grid resolution is left to the user. This choice may have important implications for both the quantification and interpretation of geomorphic change. Here we used concurrent topographic data collected by terrestrial laser scanning (TLS) and structure-from-motion (SfM) photogrammetry to quantify the influence of grid resolution and sampling technique on (a) the sediment budget and (b) the presence and role of geomorphic processes (i.e., alluvial, colluvial, aeolian, and fluvial transport) driving topographic change at four sites along the Colorado River in Grand Canyon, Arizona, USA. We found that while both techniques produced similar estimates for site-scale sediment budgets, the magnitude of detected topographic change was dampened at coarser pixel resolutions. An overall decrease in the areal extent of erosion and deposition were observed, respectively, when coarsening pixel size from 5 cm to 1 m among all sites. Coarser resolution data tended to affect interpretation of landscape change along the margins of river valleys. For example, when changing from 5 cm to 1 m pixel resolution, the inferred contribution of aeolian changes to total site-scale geomorphic change increased in area by 7.9%, whereas the inferred contribution of alluvial and colluvial processes decreased in area by 97.9% and 88.2%, respectively. More generally, we found that coarsening pixel sizes disproportionately attributed geomorphic change to one or more of the most common processes operating at a site. We also found that coarsening pixel resolution amplified the net sediment imbalance at the site scale, driving the imbalance at erosional sites further into erosion and vice versa for depositional sites. Our results have implications both for point cloud data collection and for raster dataset processing. We argue that selecting the finest obtainable resolution is not always warranted to accurately quantify and interpret geomorphic change, because remote sensing technique, topographic data resolution, and analysis procedure can be optimized to capture the spatial scale of those processes driving landscape change. However, in landscapes at or near sediment equilibrium (i.e., equal amounts of erosion and deposition), the finest obtainable topographic data resolution is warranted to avoid amplifying sediment imbalance and erroneously inferring that sites are trending toward erosion or deposition.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2019.02.020","usgsCitation":"Kasprak, A., Bransky, N., Sankey, J.B., Caster, J., and Sankey, T.T., 2019, The effects of topographic surveying technique and data resolution on the detection and interpretation of geomorphic change: Geomorphology, v. 333, p. 1-15, https://doi.org/10.1016/j.geomorph.2019.02.020.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-102800","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":467895,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2019.02.020","text":"Publisher Index Page"},{"id":368004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.6865234375,\n 35.70414710206052\n ],\n [\n -111.4178466796875,\n 35.70414710206052\n ],\n [\n -111.4178466796875,\n 36.97842095659727\n ],\n [\n -113.6865234375,\n 36.97842095659727\n ],\n [\n -113.6865234375,\n 35.70414710206052\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"333","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128 akasprak@usgs.gov","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":190848,"corporation":false,"usgs":true,"family":"Kasprak","given":"Alan","email":"akasprak@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":772462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bransky, Nathaniel D.","contributorId":219526,"corporation":false,"usgs":false,"family":"Bransky","given":"Nathaniel D.","affiliations":[],"preferred":false,"id":772463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":772464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":772465,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sankey, Temulen T.","contributorId":214481,"corporation":false,"usgs":false,"family":"Sankey","given":"Temulen","email":"","middleInitial":"T.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":772466,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203010,"text":"70203010 - 2019 - The mighty Susquehanna—extreme floods in Eastern North America during the past two millennia","interactions":[],"lastModifiedDate":"2019-06-18T11:25:00","indexId":"70203010","displayToPublicDate":"2019-02-19T08:52:51","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The mighty Susquehanna—extreme floods in Eastern North America during the past two millennia","docAbstract":"The hazards posed by infrequent major floods to communities along the Susquehanna River and the ecological health of Chesapeake Bay remain largely unconstrained due to the short length of streamgage records. Here we develop a history of high‐flow events on the Susquehanna River during the late Holocene from flood deposits contained in MD99‐2209, a sediment core recovered in 26 m of water from Chesapeake Bay near Annapolis, Maryland, United States. We identify coarse‐grained deposits left by Hurricane Agnes (1972) and the Great Flood of 1936, as well as during three intervals that predate instrumental flood records (~1800–1500, 1300–1100, and 400–0 CE). Comparison to sedimentary proxy data (pollen and ostracode Mg/Ca ratios) from the same core site indicates that prehistoric flooding on the Susquehanna often accompanied cooler‐than‐usual winter/spring temperatures near Chesapeake Bay—typical of negative phases of the North Atlantic Oscillation and conditions thought to foster hurricane landfalls along the East Coast.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GL080890","usgsCitation":"Toomey, M., Cantwell, M., Colman, S., Cronin, T.M., Donnelly, J.P., Giosan, L., Heil, C., Korty, R.L., Marot, M.E., and Willard, D.A., 2019, The mighty Susquehanna—extreme floods in Eastern North America during the past two millennia: Geophysical Research Letters, v. 46, no. 6, p. 3398-3407, https://doi.org/10.1029/2018GL080890.","productDescription":"10 p.","startPage":"3398","endPage":"3407","ipdsId":"IP-104701","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":467896,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gl080890","text":"Publisher Index Page"},{"id":362903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Chesapeake Bay, Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.398681640625,\n 36.78289206199065\n ],\n [\n -75.443115234375,\n 36.78289206199065\n ],\n [\n -75.443115234375,\n 39.816975090490004\n ],\n [\n -77.398681640625,\n 39.816975090490004\n ],\n [\n -77.398681640625,\n 36.78289206199065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science 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Long-term capture–recapture datasets provide valuable ecological insights and baselines for conservation and management, but where such studies rely on noninvasive re-encounters, such as field-readable color bands, there is the potential to accumulate detection errors as the length of the study and number of tags deployed increases. We investigated the prevalence and effects of misreads in a 10-yr dataset of Red Knots (Calidris canutus rufa) marked with field-readable leg flags in Delaware, USA. We quantified the effects of misreads on survival estimation via a simulation study and evaluated whether removal of individuals only reported once in a year (potential misreads) influenced survival estimation from both simulated datasets and our case study data. We found overall apparent error rates of 0.31% (minimum) to 6.6% (maximum). Observer-specific error rates and the variation among observers both decreased with the number of flags an observer recorded. Our simulation study showed that misreads lead to spurious negative trends in survival over time, particularly for long-term studies. Removing all records in which a flag was only recorded once in a sampling occasion reduced bias and eliminated spurious negative trends in survival but also reduced precision in survival estimates. Without data filtering, we found a slight decrease in Red Knot annual survival probability from 2008 to 2018 (β = −0.043 ± 0.03), but removing all single-observation records resulted in no apparent trend (β = −0.0074 ± 0.02). Spurious trends in demographic rates could influence inference about population trajectories and resultant conservation decision-making. Data filtering could eliminate errors, but researchers should carefully consider the tradeoff between precision obtained by larger sample sizes and potential bias due to misreads in their data.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duy017","usgsCitation":"Tucker, A.M., McGowan, C.P., Robinson, R.A., Clark, J.A., Lyons, J.E., Derose-Wilson, A., Du Feu, R., Austin, G.E., Atkinson, P.W., and Clark, N.A., 2019, Effects of individual misidentification on estimates of survival in long-term mark–resight studies: Condor, v. 121, no. 1, duy017, 13 p., https://doi.org/10.1093/condor/duy017.","productDescription":"duy017, 13 p.","ipdsId":"IP-095982","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware","otherGeospatial":"Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.4705810546875,\n 39.71986348549764\n ],\n [\n -75.6243896484375,\n 39.63530729658601\n ],\n [\n -75.574951171875,\n 39.2492708462234\n ],\n [\n -75.322265625,\n 38.79690830348427\n ],\n [\n -75.12451171875,\n 38.453588708941375\n ],\n [\n -74.970703125,\n 38.42347008084991\n ],\n [\n -75.0531005859375,\n 38.80118939192329\n ],\n [\n -75.135498046875,\n 39.13006024213511\n ],\n [\n -75.4925537109375,\n 39.42346418978382\n ],\n [\n -75.5474853515625,\n 39.50827899034114\n ],\n [\n -75.55847167968749,\n 39.63530729658601\n ],\n [\n -75.4705810546875,\n 39.71986348549764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Tucker, A. 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The only large viable source population of tigers in mainland Southeast Asia occurs in Thailand's Western Forest Complex (WEFCOM), an approximately 19,000 km 2 landscape of 17 contiguous protected areas. We used an occupancy modeling framework, which accounts for imperfect detection, to identify the factors that affect tiger distribution at the approximate scale of a female tiger's home range, 64 km 2 , and site use at a scale of 1-km 2 . At the larger scale, we estimated the proportion of sites at WEFCOM that were occupied by tigers; at the finer scale, we identified the key variables that influence site-use and developed a predictive distribution map. At both scales, we examined key anthropogenic and ecological factors that help explain tiger distribution and habitat use, including probabilities of gaur, banteng, and sambar occurrence from a companion study. Occupancy estimated at the 64-km 2 scale was primarily influenced by the combined presence of all three large prey species, and 37% or 5,858 km 2 of the landscape was predicted to be occupied by tigers. In contrast, site use estimated at the scale of 1 km 2 was most strongly influenced by the presence of sambar. By modeling occupancy while accounting for imperfect probability of detection, we established reliable benchmark data on the distribution of tigers in WEFCOM. This study also identified factors that limit tiger distributions; which managers can then target to expand tiger distribution and guide recovery elsewhere in Southeast Asia.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4845","usgsCitation":"Duangchatrasiri, S., Jornburom, P., Jinamoy, S., Pattanvibool, A., Hines, J.E., Arnold, T.W., Fieberg, J., and Smith, J.L., 2019, Impact of prey occupancy and other ecological and anthropogenic factors on Tiger distribution in Thailand’s Western Forest Complex: Ecology and Evolution, v. 9, no. 5, p. 2449-2458, https://doi.org/10.1002/ece3.4845.","productDescription":"10 p.","startPage":"2449","endPage":"2458","ipdsId":"IP-098845","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467897,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4845","text":"Publisher Index 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In this study we evaluated wetland, lake, and river systems across the Prairie Pothole Region to explore where pan-sharpened high-resolution (PSHR) imagery, relative to Landsat imagery, could provide additional data on surface water distribution and movement, missed by Landsat. We used the monthly Global Surface Water (GSW) Landsat product as well as surface water derived from Landsat imagery using a matched filtering algorithm (MF Landsat) to help consider how including partially inundated Landsat pixels as water influenced our findings. The PSHR outputs (and MF Landsat) were able to identify ~60–90% more surface water interactions between waterbodies, relative to the GSW Landsat product. However, regardless of Landsat source, by documenting many smaller (<0.2 ha), inundated wetlands, the PSHR outputs modified our interpretation of wetland size distribution across the Prairie Pothole Region.
The General Lake Model (GLM) is a one-dimensional open-source code designed to simulate the hydrodynamics of lakes, reservoirs, and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice cover dynamics, vertical mixing, and inflow–outflow dynamics. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-12-473-2019","usgsCitation":"Hipsey, M.R., Bruce, L.C., Boon, C., Busch, B., Carey, C.C., Hamilton, D., Hanson, P.C., Read, J.S., de Sousa, E., Weber, M., and Winslow, L., 2019, A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON): Geoscientific Model Development, v. 12, p. 473-523, https://doi.org/10.5194/gmd-12-473-2019.","productDescription":"51 p.","startPage":"473","endPage":"523","ipdsId":"IP-091920","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":467899,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-12-473-2019","text":"Publisher Index 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Australia","active":true,"usgs":false}],"preferred":false,"id":757430,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Weber, Michael","contributorId":213318,"corporation":false,"usgs":false,"family":"Weber","given":"Michael","affiliations":[],"preferred":false,"id":757431,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Winslow, Luke A. 0000-0002-8602-5510","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":211187,"corporation":false,"usgs":false,"family":"Winslow","given":"Luke A.","affiliations":[{"id":12656,"text":"Rensselaer Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":757432,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70202218,"text":"70202218 - 2019 - Water column nutrient processing rates in rivermouths of Green Bay (Lake Michigan)","interactions":[],"lastModifiedDate":"2019-02-15T12:53:23","indexId":"70202218","displayToPublicDate":"2019-02-15T12:53:20","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Water column nutrient processing rates in rivermouths of Green Bay (Lake Michigan)","docAbstract":"Understanding the quantity and form of nutrient loads to large lakes is necessary to understand controls over primary production, phytoplankton community composition and the production of phytotoxins. Nutrient loading estimates to large lakes are primarily made at stream gages that are deliberately placed outside the direct influence of lake processes, but these estimates cannot take into account processes that occur in the biologically active river-to-lake transition zone. These transition zones (rivermouths) sometimes alter nutrient concentrations and ratios substantially, but few studies have directly measured processing rates of nutrients within rivermouths. From April through September 2016, we conducted 23 water column incubation experiments to measure nutrient loss rates in four rivermouths. First order loss rates (K) for inorganic nitrogen (N) and phosphorus (P) indicated greater loss in light than in dark treatments, suggesting primary production increases N and P removal. Variability in K was high across both time and space, and the measured environmental parameters did not appear to be strongly associated with this variation in K for most N and P forms. If the measured Kvalues and water residence times are accurate, then between 0 and 99% of the inorganic P and nitrates entering the rivermouth would be lost (i.e., converted to organic or particulate P). In late summer, Fox River discharge is low and residence times are usually long, which allow for much higher proportional nutrient removal in the water column. Water column processing appears to be capable of transforming large quantities of dissolved N and P to particulate forms and thus altering its transport and presumably its bioavailability.
","language":"English","publisher":"Springer","doi":"10.1007/s10533-018-0517-z","usgsCitation":"Larson, J.H., Evans, M.A., Fitzpatrick, F.A., Frost, P.C., Bailey, S., Kennedy, R.J., James, W.F., Richardson, W.B., and Reneau, P.C., 2019, Water column nutrient processing rates in rivermouths of Green Bay (Lake Michigan): Biogeochemistry, v. 142, no. 1, p. 73-93, https://doi.org/10.1007/s10533-018-0517-z.","productDescription":"21 p.","startPage":"73","endPage":"93","ipdsId":"IP-090442","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437571,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XCDEBE","text":"USGS data release","linkHelpText":"Water column nutrient processing rates in rivermouths of Green Bay, Lake Michigan: Data"},{"id":361289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Green Bay, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.11859130859375,\n 44.45534933372025\n ],\n [\n -87.43743896484375,\n 44.45534933372025\n ],\n [\n -87.43743896484375,\n 45.00365115687186\n ],\n [\n -88.11859130859375,\n 45.00365115687186\n ],\n [\n -88.11859130859375,\n 44.45534933372025\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"142","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 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F.","contributorId":213265,"corporation":false,"usgs":false,"family":"James","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":38729,"text":"University of Wisconsin-Stout","active":true,"usgs":false}],"preferred":false,"id":757305,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Richardson, William B. 0000-0002-7471-4394 wrichardson@usgs.gov","orcid":"https://orcid.org/0000-0002-7471-4394","contributorId":3277,"corporation":false,"usgs":true,"family":"Richardson","given":"William","email":"wrichardson@usgs.gov","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":757306,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reneau, Paul C. 0000-0002-1335-7573 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organic carbon (SOC) in subsoils originating from catchment erosion processes with subsequent floodplain deposition. Our study focussed on the assessment of SOC pools associated with alluvial floodplain soils that are affected by human-induced changes in floodplain deposition and in situ SOC mineralisation due to land use change and drainage. We evaluated depth-dependent SOC contents based on 23 soil cores down to 3 m and 10 drillings down to 7 m in a floodplain area of the lower Cosumnes River. An estimate of 266 Mg C ha−1 or about 59% of the entire SOC stored within the 7 m profiles was found in the upper 2 m. Most profiles (n = 25) contained discrete buried A horizons at depths of approximately 0.8 m. These profiles had up to 130% higher SOC stocks. The mean δ13C of all deep soil profiles clearly indicated that arable land use has already altered the stable isotopic signature in the first meter of the profile. Radiocarbon dating showed that the 14C age in the buried horizon was younger than in overlaying soils indicating a substantial sedimentation phase for the overlaying soils. An additional analysis of total mercury contents in the soil profiles indicated that this sedimentation was associated with upstream hydraulic gold mining after the 1850s. In summary, deep alluvial soils in floodplains store large amounts of SOC not yet accounted for in global carbon models. Historic data give evidence that large amounts of sediment were transported into the floodplains of most rivers of the Central Valley and deposited over organically rich topsoil, which promoted the stabilization of SOC, and needs to be considered to improve our understanding of the human-induced interference with C cycling.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.09.205","usgsCitation":"Steger, K., Fiener, P., Marvin-DiPasquale, M.C., Viers, J.H., and Smart, D.R., 2019, Human-induced and natural carbon storage in floodplains of the Central Valley of California: Science of the Total Environment, v. 651, no. Part 1, p. 851-858, https://doi.org/10.1016/j.scitotenv.2018.09.205.","productDescription":"8 p.","startPage":"851","endPage":"858","ipdsId":"IP-094594","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467900,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://nbn-resolving.org/urn:nbn:de:bvb:384-opus4-765705","text":"Publisher Index Page"},{"id":362276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","volume":"651","issue":"Part 1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Steger, Kristin 0000-0002-7737-0697","orcid":"https://orcid.org/0000-0002-7737-0697","contributorId":214369,"corporation":false,"usgs":false,"family":"Steger","given":"Kristin","email":"","affiliations":[{"id":39022,"text":"University of California, Davis CA","active":true,"usgs":false}],"preferred":false,"id":759732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fiener, Peter","contributorId":214370,"corporation":false,"usgs":false,"family":"Fiener","given":"Peter","email":"","affiliations":[{"id":39023,"text":"Augsburg University, Augsburg, Germany","active":true,"usgs":false}],"preferred":false,"id":759733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":759731,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viers, Joshua H.","contributorId":214371,"corporation":false,"usgs":false,"family":"Viers","given":"Joshua","email":"","middleInitial":"H.","affiliations":[{"id":39024,"text":"Univ. of California, Merced, CA","active":true,"usgs":false}],"preferred":false,"id":759734,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smart, David R.","contributorId":214372,"corporation":false,"usgs":false,"family":"Smart","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":39025,"text":"Univ. of California, Davis CA","active":true,"usgs":false}],"preferred":false,"id":759735,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201100,"text":"ofr20181183 - 2019 - Design and methods of the U.S. Geological Survey Northeast Stream Quality Assessment (NESQA), 2016","interactions":[],"lastModifiedDate":"2019-02-15T14:02:05","indexId":"ofr20181183","displayToPublicDate":"2019-02-15T08:30:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1183","displayTitle":"Design and Methods of the U.S. Geological Survey Northeast Stream Quality Assessment (NESQA), 2016","title":"Design and methods of the U.S. Geological Survey Northeast Stream Quality Assessment (NESQA), 2016","docAbstract":"During 2016, as part of the National Water-Quality Assessment Project (NAWQA), the U.S. Geological Survey conducted the Northeast Stream Quality Assessment (NESQA) to investigate stream quality in the northeastern United States. The goal of the NESQA was to assess the health of wadeable streams in the region by characterizing multiple water-quality factors that are stressors to aquatic life and by evaluating the relation between these stressors and the condition of biological communities. Urbanization, agriculture, and human modifications to streamflow are anthropogenic changes that greatly affect water quality in the region; consequently, the study design primarily selected sites and targeted stressors associated with these activities. The NESQA built on a prior NAWQA study conducted in the region in 2014, the Atlantic Highlands flow-ecology study, which investigated the effects of anthropogenically modified flows on aquatic biological communities in primarily forested watersheds. Land-cover data for the NESQA were used to identify and select sites within the region that had watersheds ranging in levels of urban and agricultural development. A total of 95 sites were selected: 67 on streams in watersheds representing a range of urban land use, 13 on streams in watersheds with some degree of agricultural land use, and 15 on streams in predominantly forested watersheds with little development. Depending on land-cover characteristics, sites were sampled weekly for metal and organic contaminants, nutrients, and sediment for either a 9-week period that began the week of June 6, 2016, or a 4-week period that begin the week of July 11, 2016. Beginning August 1, 2016, and for about 2 weeks, an ecological survey was conducted at every site to assess stream habitat, and algal, benthic invertebrate, and fish communities. Additional samples collected during the ecological surveys were streambed sediment for chemical analysis and toxicity testing, and fish tissue for mercury analysis. This report describes the various study components and methods of the NESQA and describes a precursor effort for the Atlantic Highlands flow-ecology study. Details are presented for measurements of water quality, sediment chemistry, streamflow, and ecological surveys of stream biota and habitat, as well as processes of sample analysis, quality assurance and quality control, and data management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181183","collaboration":"National Water Quality Program","usgsCitation":"Coles, J.F., Riva-Murray, K., Van Metre, P.C., Button, D.T., Bell, A.H., Qi, S.L., Journey, C.A., and Sheibley, R.W., 2019, Design and methods of the U.S. Geological Survey Northeast Stream Quality Assessment (NESQA), 2016: U.S. Geological Survey Open-File Report 2018–1183, 46 p., https://doi.org/10.3133/ofr20181183.","productDescription":"Report: vii, 46 p.; Appendixes 1 and 2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095438","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":361093,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1183/ofr20181183_appendix2.xlsx","text":"Appendix 2, tables 2.1 through 2.10: Excel ","size":"119 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":361094,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1183/ofr20181183_appendixes.zip","text":"Appendixes 1 and 2, all tables in CSV format","size":"5.45 GB","linkFileType":{"id":6,"text":"zip"}},{"id":361095,"rank":6,"type":{"id":18,"text":"Project Site"},"url":"https://webapps.usgs.gov/rsqa/#!/"},{"id":361090,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1183/coverthb.jpg"},{"id":361091,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1183/ofr20181183.pdf","text":"Report","size":"2.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1183"},{"id":361092,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1183/ofr20181183_appendix1.xlsx","text":"Appendix 1, tables 1.1 through 1.4: Excel","size":"777 KB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.9365234375,\n 40.17887331434696\n ],\n [\n -68.291015625,\n 40.17887331434696\n ],\n [\n -68.291015625,\n 47.60616304386874\n ],\n [\n -79.9365234375,\n 47.60616304386874\n ],\n [\n -79.9365234375,\n 40.17887331434696\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Fluvial features such as floodplains and point bars are built by sediment deposition and sculpted by erosion. Long-term measurements (38 yr) of the cross-section topography of active floodplains and point bars along the freely-meandering Powder River in southeastern Montana, USA (mean daily discharge of 12.5 m3 s−1), were used to develop dynamic relations between annual sediment deposition and peak-flood discharge. Five floodplain sections and five point-bar sections were selected from 24 cross sections along a 90-km study reach. At each cross section the sediment deposition volume per unit streamwise distance was computed as the difference between two topographic surveys made in consecutive years.
Snowmelt floods were found to be the dominant annual process. However, other processes such as flash floods, ice breakup floods, and autumnal floods were important episodically. The dynamic relations were linear for both fluvial features. The snowmelt deposition-discharge relations showed, in general, that point bars were about two times more efficient at trapping sediment than floodplains. Each relation had a discharge threshold that must be exceeded before sediment was deposited. Although these discharge thresholds for floodplains and point bars had essentially the same mean value (69 and 71 m3 s−1, respectively), they represented different processes. Thresholds for other rivers will probably differ from those for Powder River because of different channel geometry and sediment characteristics.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2018.11.032","usgsCitation":"Moody, J.A., 2019, Dynamic relations for the deposition of sediment on floodplains and point bars of a freely-meandering river: Geomorphology, v. 327, p. 585-597, https://doi.org/10.1016/j.geomorph.2018.11.032.","productDescription":"13 p.","startPage":"585","endPage":"597","ipdsId":"IP-099112","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":408881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.0,\n 45.0\n ],\n [\n -105.2,\n 45.0\n ],\n [\n -105.2,\n 45.3\n ],\n [\n -106.0,\n 45.3\n ],\n [\n -106.0,\n 45.0\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"327","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":856136,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70217885,"text":"70217885 - 2019 - Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities","interactions":[],"lastModifiedDate":"2021-02-09T13:17:15.996901","indexId":"70217885","displayToPublicDate":"2019-02-15T07:06:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities","docAbstract":"The effectiveness of Integrated Water Resource Management (IWRM) modeling hinges on the quality of practices employed through the process, starting from early problem definition all the way through to using the model in a way that serves its intended purpose. The adoption and implementation of effective modeling practices need to be guided by a practical understanding of the variety of decisions that modelers make, and the information considered in making these choices. There is still limited documented knowledge on the modeling workflow, and the role of contextual factors in determining this workflow and which practices to employ. This paper attempts to contribute to this knowledge gap by providing systematic guidance of the modeling practices through the phases (Planning, Development, Application, and Perpetuation) and steps that comprise the modeling process, positing questions that should be addressed. Practice-focused guidance helps explain the detailed process of conducting IWRM modeling, including the role of contextual factors in shaping practices. We draw on findings from literature and the authors’ collective experience to articulate what and how contextual factors play out in employing those practices. In order to accelerate our learning about how to improve IWRM modeling, the paper concludes with five key areas for future practice-related research: knowledge sharing, overcoming data limitations, informed stakeholder involvement, social equity and uncertainty management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2019.02.013","usgsCitation":"Badham, J., Elsawah, S., Guillaume, J., Hamilton, S.H., Hunt, R., Jakeman, A.J., Pierce, S.A., Babbar-Sebens, M., Fu, B., Gober, P., Hill, M.C., Iwanaga, T., Loucks, D.P., Merritt, W.S., Peckham, S.D., Richmond, A.K., Zare, F., Ames, D.P., and Bammer, G., 2019, Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities: Environmental Modelling & Software, v. 116, 17 p., https://doi.org/10.1016/j.envsoft.2019.02.013.","productDescription":"17 p.","ipdsId":"IP-098737","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":467903,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://ro.ecu.edu.au/ecuworkspost2013/5935","text":"Publisher Index Page"},{"id":383145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"116","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Badham, J.","contributorId":248842,"corporation":false,"usgs":false,"family":"Badham","given":"J.","affiliations":[{"id":36943,"text":"Queens University","active":true,"usgs":false}],"preferred":false,"id":810046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elsawah, Sondoss","contributorId":146686,"corporation":false,"usgs":false,"family":"Elsawah","given":"Sondoss","affiliations":[],"preferred":false,"id":810047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guillaume, Joseph H. 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Although the importance of these factors in the success of reintroductions is well‐accepted, they are typically evaluated independently, which can miss important interactions. For species that persist in metapopulations, movement through and interaction with the landscape is predicted to be a vital component of persistence. Simulation‐based approaches are a promising technique for evaluating the independent and combined effects of these factors on the outcome of various reintroduction and associated management actions. We report results from a simulation study of bull trout (Salvelinus confluentus) reintroduction to three watersheds of the Pend Oreille River system in northeastern Washington State, USA. We used an individual‐based, spatially explicit simulation model to evaluate how reintroduction strategies, life history variation, and riverscape structure (e.g., network topology) interact to influence the demographic and genetic characteristics of reintroduced bull trout populations in three watersheds. Simulation scenarios included a range of initial genetic stocks (informed by empirical bull trout genetic data), variation in migratory tendency and life history, and two landscape connectivity alternatives representing a connected network (isolation‐by‐distance) and a fragmented network (isolation‐by‐barrier, using the known existing barriers). A novel feature of these simulations was the ability to consider the interaction of both demographic and genetic (i.e., demogenetic) factors in riverscapes with implicit asymmetric movement probabilities across the barriers. We found that connectivity (presence or absence of barriers) had the largest effect on demographic and genetic outcomes over 200 yr, with a greater effect than both initial genetic diversity and life history variation. We also identified regions of the study system in which bull trout populations persisted across a wide range of demographic, life history, and environmental connectivity parameters. Finally, we found no evidence that initial neutral genetic diversity influenced genetic diversity and structure after 200 yr; instead, genetic drift due to stray rate and population isolation dominated and erased any initial differences in genetic diversity. Our results highlight the utility of spatially explicit demogenetic approaches in exploring and understanding population dynamics—and their implications for management strategies—in fresh waters.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2589","usgsCitation":"Mims, M.C., Day, C.C., Burkhart, J.J., Fuller, M.R., Hinkle, J., Bearlin, A., Dunham, J.B., DeHaan, P.W., Holden, Z.A., and Landguth, E.L., 2019, Simulating demography, genetics, and spatially explicit processes to inform reintroduction of a threatened char: Ecosphere, v. 10, no. 2, p. 1-24, https://doi.org/10.1002/ecs2.2589.","productDescription":"Article e02589; 24 p.","startPage":"1","endPage":"24","ipdsId":"IP-103940","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":467904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2589","text":"Publisher Index Page"},{"id":361262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Pend Oreille 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Inundation itself is an outcome of multi‐scalar interactions and can vary strongly within and among river reaches. As a result, establishing to what degree and how inundation dynamics vary spatially both within and among river reaches can be challenging. The objective of this study was to understand how river‐valley morphology, basin size, and flow‐event magnitude interact to affect inundation dynamics in river‐valley bottoms. We used 2D hydraulic models to simulate inundation in four river reaches from Maryland's Piedmont physiographic province, and qualitatively and quantitatively summarized within‐ and among‐reach patterns of inundation extent, duration, depth, shear stress, and wetting frequencies. On average, reaches from confined valley settings experienced less extensive flooding, shorter durations and shallower depths, stronger gradients of maximum shear stress, and relatively infrequent wetting compared to reaches from unconfined settings. These patterns were generally consistent across flow‐event magnitudes. Patterns of within‐reach flooding across event magnitudes revealed complex interactions between hydrology and surface topography. We concluded that valley morphology had a greater impact on flooding patterns than basin size: Inundation patterns were more consistent across reaches of similar morphology than similar basin size, but absolute values of inundation characteristics varied between large and small basins. Our results showed that the manifestation of out‐of‐bank flows in valley floors can vary widely depending on geomorphic context, even within a single physiographic province, which suggests that hydrologic and hydraulic conditions experienced on the valley floor may not be well represented by existing hydrologic metrics derived from discharge data alone. We thus support the notion that 2D hydraulic models can be useful hydrometric tools for cross‐scale investigations of floodplain ecosystems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2546","usgsCitation":"Van Appledorn, M., Baker, M.E., and Miller, A.J., 2019, River‐valley morphology, basin size, and flow‐event magnitude interact to produce wide variation in flooding dynamics: Ecosphere, v. 10, no. 1, p. 1-25, https://doi.org/10.1002/ecs2.2546.","productDescription":"Article e02546; 25 p.","startPage":"1","endPage":"25","ipdsId":"IP-096187","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467905,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2546","text":"Publisher Index Page"},{"id":437572,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ITQTNQ","text":"USGS data release","linkHelpText":"Complex interactions among river-valley morphology, basin size, and flow-event magnitude structure the physical template of floodplain ecosystems. Data"},{"id":361256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Chesapeake Bay Watershed","volume":"10","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":757248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Matthew E.","contributorId":149189,"corporation":false,"usgs":false,"family":"Baker","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":17665,"text":"Department of Geography and Environmental Systems, University of Maryland, Baltimore County, Baltimore, Maryland, US","active":true,"usgs":false}],"preferred":false,"id":757249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Andrew J.","contributorId":207595,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":15309,"text":"University of Maryland Baltimore County","active":true,"usgs":false}],"preferred":false,"id":757250,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202210,"text":"70202210 - 2019 - Effects of urban multi-stressors on three stream biotic assemblages","interactions":[],"lastModifiedDate":"2019-02-14T12:28:29","indexId":"70202210","displayToPublicDate":"2019-02-14T12:28:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Effects of urban multi-stressors on three stream biotic assemblages","docAbstract":"During 2014, the U.S. Geological Survey (USGS) National Water-Quality Assessment(NAWQA) project assessed stream quality in 75 streams across an urban disturbance gradient within the Piedmont ecoregion of southeastern United States. Our objectives were to identify primary instream stressors affecting algal, macroinvertebrate and fish assemblages in wadeable streams. Biotic communities were surveyed once at each site, and various instream stressors were measured during a 4-week index period preceding the ecological sampling. The measured stressors included nutrients; contaminants in water, passive samplers, and sediment; instream habitat; and flow variability. All nine boosted regression tree models – three for each of algae, invertebrates, and fish – had cross-validation R2 (CV R2) values of 0.41 or above, and an invertebrate model had the highest CV R2 of 0.65. At least one contaminant metric was important in every model, and minimum daytime dissolved oxygen (DO), nutrients, and flow alteration were important explanatory variables in many of the models. Physical habitat metrics such as sediment substrate were only moderately important. Flow alteration metrics were useful factors in eight of the nine models. Total phosphorus, acetanilide herbicides and flow (time since last peak) were important in all three algal models, whereas insecticide metrics (especially those representing fipronil and imidacloprid) were dominant in the invertebrate models. DO values below approximately 7 mg/L corresponded to a strong decrease in sensitive taxa or an increase in tolerant taxa. DO also showed strong interactions with other variables, particularly contaminants and sediment, where the combined effect of low DO and elevated contaminants increased the impact on the biota more than each variable individually. Contaminants and flow alteration were strongly correlated to urbanization, indicating the importance of urbanization to ecological stream condition in the region.
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