{"pageNumber":"201","pageRowStart":"5000","pageSize":"25","recordCount":68807,"records":[{"id":70240861,"text":"70240861 - 2021 - Middle Holocene hydrologic changes catalyzed by river avulsion in Big Soda Lake, Nevada, USA","interactions":[],"lastModifiedDate":"2023-02-27T20:12:21.152859","indexId":"70240861","displayToPublicDate":"2021-04-01T13:56:48","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Middle Holocene hydrologic changes catalyzed by river avulsion in Big Soda Lake, Nevada, USA","docAbstract":"

Big Soda Lake is a 63 m deep, 1.6 km2 maar lake in the Great Basin of Nevada, USA. Water level in the lake is controlled by groundwater inputs from the surrounding aquifer and the only surface water input is rainfall, which is negligible. A core taken in 2010 records an 8.75 m depositional history of the lake. A radiocarbon date on fossil pollen from 8.4 m below the sediment water interface (BSWI) of 14,740 (+1120/−825) cal yr BP suggests that the core may cover the latest Pleistocene and Holocene depositional history of the lake. Stable isotope values of oxygen and carbon (δ18O and δ13C) on authigenic calcite, diatom assemblages, and sedimentary structures all show consistent hydrological change from initially saline water at the bottom of the core to fresh/brackish water at about 6 m BWSI, back to saline water at 4.3 m. At 4.3 m depth, the bedding and color of the core change abruptly, and the stable- isotope and diatom assemblages indicate a consistently hypersaline lake until near the top of the core, when fresh water entered the lake due to irrigation and canal building in the twentieth century. The stable isotopes of the calcite abruptly change from inversely varying isotopic compositions below 4.3 m depth to covarying above. This break between relatively fresh and saline conditions in the lake occurs during the middle Holocene, although the exact timing of the transition is unknown due to variability in the 14C age determinations. The cause for such an abrupt change is difficult to explain through climate shifts, as evidence suggests climate in the Great Basin was different from what the Big Soda Lake record indicates in the Early Holocene. It is hypothesized that the Walker River flowed to the Carson River basin before 5600 cal yr BP, with water either flowing directly into the lake or raising the groundwater table sufficiently to freshen Big Soda Lake. The initial increase in salinity likely was caused by decreased flow of the Walker River due to Middle Holocene aridity. The lake level lowered slowly, and more saline conditions prevailed until 4.3 m depth when water from the Walker River stopped flowing into the Carson River basin. Above 4.3 m depth, diatom and isotopic evidence indicates that the lake became consistently saline. The isotopic and diatom assemblage transitions observed in Big Soda Lake sediment are not consistent with climate reconstructions and demonstrate that hydrologic shifts in a basin can be an important driver of change regardless of climatic conditions. However, climate shifts may also play a role in the hydrologic changes by supplying more or less water to river courses that may induce river avulsion.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Limnogeology: Progress, challenges and opportunities: A tribute to Elizabeth Gierlowski-Kordesch","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-66576-0_10","usgsCitation":"Rosen, M., Reidy, L.M., Starratt, S.W., and Zimmerman, S., 2021, Middle Holocene hydrologic changes catalyzed by river avulsion in Big Soda Lake, Nevada, USA, chap. of Limnogeology: Progress, challenges and opportunities: A tribute to Elizabeth Gierlowski-Kordesch, p. 295-328, https://doi.org/10.1007/978-3-030-66576-0_10.","productDescription":"34 p.","startPage":"295","endPage":"328","ipdsId":"IP-109894","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":436422,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9INH1ID","text":"USGS data release","linkHelpText":"Mineralogic, grain-size, biologic, and stable isotopic analyses of core TOPGUN-SODA10 2A-K from Big Soda Lake, Nevada, USA"},{"id":413426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Big Soda Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.87892835971928,\n 39.51788809213036\n ],\n [\n -118.8770297198971,\n 39.51835411876252\n ],\n [\n -118.87495847645494,\n 39.520218194026086\n ],\n [\n -118.87098859319025,\n 39.521849218843585\n ],\n [\n -118.86969406603852,\n 39.52288107190569\n ],\n [\n -118.86891734974776,\n 39.52690848070142\n ],\n [\n -118.86960776422836,\n 39.529504537764296\n ],\n [\n -118.87465642011955,\n 39.532200340442046\n ],\n [\n -118.87780643618821,\n 39.532200340442046\n ],\n [\n -118.87996398144054,\n 39.53123518854974\n ],\n [\n -118.88039549049098,\n 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B.","affiliations":[],"preferred":false,"id":865098,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Park Boush, Lisa 0000-0002-8169-4600","orcid":"https://orcid.org/0000-0002-8169-4600","contributorId":302674,"corporation":false,"usgs":false,"family":"Park Boush","given":"Lisa","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":865099,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Pla-Pueyo, Sila 0000-0003-4884-4096","orcid":"https://orcid.org/0000-0003-4884-4096","contributorId":302677,"corporation":false,"usgs":false,"family":"Pla-Pueyo","given":"Sila","email":"","affiliations":[{"id":33422,"text":"University of Granada","active":true,"usgs":false}],"preferred":false,"id":865100,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Rosen, Michael R. 0000-0003-3991-0522","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":224435,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reidy, Liam M.","contributorId":302678,"corporation":false,"usgs":false,"family":"Reidy","given":"Liam","email":"","middleInitial":"M.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":865075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":302679,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":865076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmerman, Susan 0000-0002-1320-1878","orcid":"https://orcid.org/0000-0002-1320-1878","contributorId":243580,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Susan","email":"","affiliations":[{"id":48737,"text":"CAMS, LLNL","active":true,"usgs":false}],"preferred":false,"id":865077,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240860,"text":"70240860 - 2021 - Introduction to limnogeology: Progress, challenges, and opportunities: A tribute to Elizabeth Gierlowski-Kordesch","interactions":[],"lastModifiedDate":"2023-02-27T20:13:00.872134","indexId":"70240860","displayToPublicDate":"2021-04-01T13:51:25","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Introduction to limnogeology: Progress, challenges, and opportunities: A tribute to Elizabeth Gierlowski-Kordesch","docAbstract":"

Elizabeth Gierlowski-Kordesch (1956–2016) was a leader and innovator in the specialty field of limnogeology since its beginnings in the late 1980s. Her excitement for field work and examining sediments was contagious, and she was always testing new research ideas. Beth would have been thrilled with the diversity of papers presented in the volume and the wide array of techniques used to determine the history, geochemistry, paleontology, and paleoclimate preserved in the sediments in basins that are located on every continent except Australia and Antarctica. She would also have been delighted that half the chapters were first authored by highly cited women scientists. Beth spent her career teaching, mentoring, conducting research with students and colleagues, and planning limnogeology conferences, books, and field trips. Her contributions span deep-time lakes from North and South America, Africa, Asia, and Europe, starting with her work on the Lower Jurassic East Berlin Formation where she conducted her Ph.D. research. Her work with Kerry Kelts at the University of Minnesota produced two books summarizing global lake research. These volumes are still used by many researchers, particularly as a starting point in their limnogeological studies. Her collaboration with Springer Nature® resulted in the series entitled Syntheses in Limnogeology, a publication that likely would not exist without her enthusiasm and perseverance. The papers in this second volume in the series describe a variety of Jurassic to modern lakes that range from fresh to hypersaline, shallow to deep, vary in size from <1 km2 to 100s of km2, and are found in a number of tectonic settings. Various proxies, including microfossils and trace fossils and analyses of lacustrine sedimentology, stratigraphy, and stable isotopes are used to evaluate the sediment cores and stratigraphic sections to evaluate human and climate influences on the environment, the effects of tectonic, seismic, and volcanic activity, and variations in hydrology. The contributions in this volume reflect the diverse research that Beth conducted herself and we hope is a fitting honor to one of the founding scientists of Limnogeology.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Limnogeology: Progress, challenges and opportunities: A tribute to Elizabeth Gierlowski-Kordesch","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-66576-0_1","usgsCitation":"Rosen, M., Park Boush, L., Finkelstein, D., and Pla-Pueyo, S., 2021, Introduction to limnogeology: Progress, challenges, and opportunities: A tribute to Elizabeth Gierlowski-Kordesch, chap. of Limnogeology: Progress, challenges and opportunities: A tribute to Elizabeth Gierlowski-Kordesch, p. 3-16, https://doi.org/10.1007/978-3-030-66576-0_1.","productDescription":"14 p.","startPage":"3","endPage":"16","ipdsId":"IP-122491","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":413425,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosen, Michael R. 0000-0003-3991-0522","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":224435,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865070,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Park Boush, Lisa 0000-0002-8169-4600","orcid":"https://orcid.org/0000-0002-8169-4600","contributorId":302674,"corporation":false,"usgs":false,"family":"Park Boush","given":"Lisa","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":865071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finkelstein, David 0000-0002-9787-1675","orcid":"https://orcid.org/0000-0002-9787-1675","contributorId":302675,"corporation":false,"usgs":false,"family":"Finkelstein","given":"David","email":"","affiliations":[{"id":65529,"text":"Hobart and William Smith Colleges","active":true,"usgs":false}],"preferred":false,"id":865072,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pla-Pueyo, Sila 0000-0003-4884-4096","orcid":"https://orcid.org/0000-0003-4884-4096","contributorId":302677,"corporation":false,"usgs":false,"family":"Pla-Pueyo","given":"Sila","email":"","affiliations":[{"id":33422,"text":"University of Granada","active":true,"usgs":false}],"preferred":false,"id":865073,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237363,"text":"70237363 - 2021 - Graph-based reinforcement learning for active learning in real time: An application in modeling river networks","interactions":[],"lastModifiedDate":"2022-10-11T16:57:48.969639","indexId":"70237363","displayToPublicDate":"2021-04-01T11:44:45","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Graph-based reinforcement learning for active learning in real time: An application in modeling river networks","docAbstract":"Effective training of advanced ML models requires large amounts of labeled data, which is often scarce in scientific problems given the substantial human labor and material cost to collect labeled data. This poses a challenge on determining when and where we should deploy measuring instruments (e.g., in-situ sensors) to collect labeled data efficiently. This problem differs from traditional pool-based active learning settings in that the labeling decisions have to be made immediately after we observe the input data that come in a time series. In this paper, we develop a real-time active learning method that uses the spatial and temporal contextual information to select representative query samples in a reinforcement learning framework. To reduce the need for large training data, we further propose to transfer the policy learned from simulation data which is generated by existing physics-based models. We demonstrate the effectiveness of the proposed method by predicting streamflow and water temperature in the Delaware River Basin given a limited budget for collecting labeled data. We further study the spatial and temporal distribution of selected samples to verify the ability of this method in selecting informative samples over space and time.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 2021 SIAM International Conference on Data Mining","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"2021 SIAM International Conference on Data Mining","conferenceDate":"April 29-May 1, 2021","conferenceLocation":"Online","language":"English","publisher":"SIAM","doi":"10.1137/1.9781611976700.70","usgsCitation":"Jia, X., Lin, B., Zwart, J.A., Sadler, J.M., Appling, A.P., Oliver, S.K., and Read, J., 2021, Graph-based reinforcement learning for active learning in real time: An application in modeling river networks, in Proceedings of the 2021 SIAM International Conference on Data Mining, Online, April 29-May 1, 2021, p. 621-629, https://doi.org/10.1137/1.9781611976700.70.","productDescription":"9 p.","startPage":"621","endPage":"629","ipdsId":"IP-123542","costCenters":[{"id":37316,"text":"WMA - 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Rio Grande Valley","active":true,"usgs":false}],"preferred":false,"id":854268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854269,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854270,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":854271,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854272,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854273,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228564,"text":"70228564 - 2021 - Investigating the morphological and genetic divergence of arctic char (Salvelinus alpinus) populations in lakes of arctic Alaska","interactions":[],"lastModifiedDate":"2022-02-14T15:58:57.838707","indexId":"70228564","displayToPublicDate":"2021-04-01T09:48:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Investigating the morphological and genetic divergence of arctic char (Salvelinus alpinus) populations in lakes of arctic Alaska","title":"Investigating the morphological and genetic divergence of arctic char (Salvelinus alpinus) populations in lakes of arctic Alaska","docAbstract":"

Polymorphism facilitates coexistence of divergent morphs (e.g., phenotypes) of the same species by minimizing intraspecific competition, especially when resources are limiting. Arctic char (Salvelinus sp.) are a Holarctic fish often forming morphologically, and sometimes genetically, divergent morphs. In this study, we assessed the morphological and genetic diversity and divergence of 263 individuals from seven populations of arctic char with varying length-frequency distributions across two distinct groups of lakes in northern Alaska. Despite close geographic proximity, each lake group occurs on landscapes with different glacial ages and surface water connectivity, and thus was likely colonized by fishes at different times. Across lakes, a continuum of physical (e.g., lake area, maximum depth) and biological characteristics (e.g., primary productivity, fish density) exists, likely contributing to characteristics of present-day char populations. Although some lakes exhibit bimodal size distributions, using model-based clustering of morphometric traits corrected for allometry, we did not detect morphological differences within and across char populations. Genomic analyses using 15,934 SNPs obtained from genotyping by sequencing demonstrated differences among lake groups related to historical biogeography, but within lake groups and within individual lakes, genetic differentiation was not related to total body length. We used PERMANOVA to identify environmental and biological factors related to observed char size structure. Significant predictors included water transparency (i.e., a primary productivity proxy), char density (fish·ha-1), and lake group. Larger char occurred in lakes with greater primary production and lower char densities, suggesting less intraspecific competition and resource limitation. Thus, char populations in more productive and connected lakes may prove more stable to environmental changes, relative to food-limited and closed lakes, if lake productivity increases concomitantly. Our findings provide some of the first descriptions of genomic characteristics of char populations in arctic Alaska, and offer important consideration for the persistence of these populations for subsistence and conservation.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7211","usgsCitation":"Klobucar, S., Rick, J., Mandeville, E., Wagner, C.E., and Budy, P., 2021, Investigating the morphological and genetic divergence of arctic char (Salvelinus alpinus) populations in lakes of arctic Alaska: Ecology and Evolution, v. 11, no. 7, p. 3040-3057, https://doi.org/10.1002/ece3.7211.","productDescription":"18 p.","startPage":"3040","endPage":"3057","ipdsId":"IP-117493","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":452836,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7211","text":"Publisher Index Page"},{"id":395888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Brooks Mountain Range, Toolik Field Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.74365234374997,\n 68.49604022839505\n ],\n [\n -148.95538330078125,\n 68.49604022839505\n ],\n [\n -148.95538330078125,\n 68.70448628851169\n ],\n [\n -149.74365234374997,\n 68.70448628851169\n ],\n [\n -149.74365234374997,\n 68.49604022839505\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Klobucar, Stephen L.","contributorId":172291,"corporation":false,"usgs":false,"family":"Klobucar","given":"Stephen L.","affiliations":[],"preferred":false,"id":834610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rick, Jessica A.","contributorId":276155,"corporation":false,"usgs":false,"family":"Rick","given":"Jessica A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":834611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mandeville, Elizabeth G.","contributorId":270691,"corporation":false,"usgs":false,"family":"Mandeville","given":"Elizabeth G.","affiliations":[{"id":56198,"text":"uwyo","active":true,"usgs":false}],"preferred":false,"id":834612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagner, Catherine E.","contributorId":270693,"corporation":false,"usgs":false,"family":"Wagner","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":56198,"text":"uwyo","active":true,"usgs":false}],"preferred":false,"id":834613,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834609,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218468,"text":"70218468 - 2021 - Climate change indicators: Streamflow","interactions":[],"lastModifiedDate":"2024-03-21T14:34:17.88426","indexId":"70218468","displayToPublicDate":"2021-04-01T09:28:47","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Climate change indicators: Streamflow","docAbstract":"

No abstract available.

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0000-0002-0934-0568","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":220211,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McHale, Michael 0000-0003-3780-1816 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effects","docAbstract":"

Rodents characteristically benefit from increased precipitation, especially in typically dry habitats; “good years” of high precipitation improve their forage and water balance. However, Yersinia pestis (plague), a flea-borne pathogen of mammals that was introduced to western North America, has the greatest negative impact on at least some species of rodents during years of above-average precipitation. In the absence of plague mitigation, negative effects of plague in wet years might overwhelm the otherwise beneficial effects of increased moisture. In Montana and Utah, USA, where plague now occurs enzootically, we investigated the influence of precipitation on finite rates of annual population change (2000–2005) for 3 species of prairie dogs (Cynomys spp.) in replicated plots treated with deltamethrin dust and in non-treated plots for paired comparisons. There was a significant interaction between precipitation and treatment. When we reduced plague vector fleas, prairie dog visual counts tended to increase with increasing precipitation. Simultaneously, there was a negative relationship between counts and precipitation on paired plots where plague was not managed, suggesting that plague transformed and reversed the otherwise beneficial effect of increased precipitation. Are the good years gone for prairie dogs? Even if the good years are not gone, they are perhaps relatively scarce compared to historic times prior to the invasion of plague. This scenario might apply to other ecosystems and may pose broad conservation challenges in western North America.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijppaw.2021.02.006","usgsCitation":"Biggins, D.E., Eads, D.A., and Godbey, J.L., 2021, Plague transforms positive effects of precipitation on prairie dogs to negative effects: International Journal of Parasitology: Parasites and Wildlife, v. 14, p. 329-334, https://doi.org/10.1016/j.ijppaw.2021.02.006.","productDescription":"6 p.","startPage":"329","endPage":"334","ipdsId":"IP-123771","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":452840,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijppaw.2021.02.006","text":"Publisher Index Page"},{"id":436423,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VPEKGV","text":"USGS data release","linkHelpText":"Data on finite population change for 3 species of prairie dogs in Montana and Utah, USA, 2000-2005"},{"id":396341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Utah","county":"Philips County","otherGeospatial":"Awapa Recovery Area, Coyote Basin, Paunsaugunt Recovery Area, West Desert Recovery Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.55429077148438,\n 39.97396296240704\n ],\n [\n -109.05303955078125,\n 39.97396296240704\n ],\n [\n -109.05303955078125,\n 40.30571266770939\n ],\n [\n -109.55429077148438,\n 40.30571266770939\n ],\n [\n -109.55429077148438,\n 39.97396296240704\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.0435791015625,\n 37.01571219880126\n ],\n [\n -110.7916259765625,\n 37.01571219880126\n ],\n [\n -110.7916259765625,\n 38.843986129756615\n ],\n [\n -114.0435791015625,\n 38.843986129756615\n ],\n [\n -114.0435791015625,\n 37.01571219880126\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.841552734375,\n 47.83159592699297\n ],\n [\n -107.31170654296875,\n 47.83159592699297\n ],\n [\n -107.31170654296875,\n 49.001843917978526\n ],\n [\n -108.841552734375,\n 49.001843917978526\n ],\n [\n -108.841552734375,\n 47.83159592699297\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":835701,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Godbey, Jerry L. godbeyj@usgs.gov","contributorId":5121,"corporation":false,"usgs":true,"family":"Godbey","given":"Jerry","email":"godbeyj@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":835702,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229806,"text":"70229806 - 2021 - Reply to comment by R. Parkinson on “Increasing rates of carbon burial in southwest Florida coastal wetlands” by J. Breithaupt et al.","interactions":[],"lastModifiedDate":"2022-03-17T13:46:30.497055","indexId":"70229806","displayToPublicDate":"2021-04-01T08:41:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Reply to comment by R. Parkinson on “Increasing rates of carbon burial in southwest Florida coastal wetlands” by J. Breithaupt et al.","docAbstract":"Breithaupt et al. (2020) investigated why rates of organic carbon (OC) burial in coastal wetlands appear to increase over the past ∼120 years. After comparing dating methods and applying biogeochemical analyses, we concluded that neither dating method nor carbon degradation contribute to the observed trend. Rather, we concluded that OC burial has increased in the past century. Parkinson's (2021) Comment disagrees with our conclusion, contending that: 1) use of a density correction to account for soil auto‐compaction is a flawed methodology that artificially shortens a core's length, 2) there is limited evidence for an acceleration in the regional sea‐level rise (SLR) rate, and 3) vertical accretion rates in previous papers by Breithaupt et al. (2014, 2017) are lower than the regional mean rate of SLR and are not to be believed as these wetlands should have converted to open water by now. We reject these contentions because: 1) no density correction was applied to the cores in this study, 2) local tide gauge records and analyses in the literature support an increase in SLR rates coinciding with the timeframe of our OC burial records, and 3) Parkinson's comparison of the 100‐yr mean rate of SLR neglects temporal variability and uncertainties in the long‐term sea‐level record, as well as biophysical feedbacks between wetland surface elevation and SLR. Here, we provide detailed responses to Parkinson's contentions and establish the importance of differentiating operational definitions of OC burial and accretion to clarify why an auto‐compaction correction is not applicable for OC burial measurements.","language":"English","publisher":"John Wiley & Sons, Inc.","doi":"10.1029/2021JG006245","usgsCitation":"Breithaupt, J.L., Smoak, J.M., Bianchi, T.S., Vaughn, D., Sanders, C.J., Radabaugh, K.R., Osland, M., Feher, L., Lynch, J., Cahoon, D., Anderson, G., Whelan, K.R., Rosenheim, B.E., Moyer, R.P., and Chambers, L.G., 2021, Reply to comment by R. Parkinson on “Increasing rates of carbon burial in southwest Florida coastal wetlands” by J. Breithaupt et al.: Biogeosciences, v. 126, no. 4, e2021JG006245, 7 p., https://doi.org/10.1029/2021JG006245.","productDescription":"e2021JG006245, 7 p.","ipdsId":"IP-125803","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":397223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.68310546875,\n 28.7965462417692\n ],\n [\n -82.96875,\n 27.907058371121995\n ],\n [\n -82.6171875,\n 27.205785724383325\n ],\n [\n -82.353515625,\n 26.8730809659384\n ],\n [\n -82.320556640625,\n 26.480407161007275\n ],\n [\n -81.9140625,\n 26.05678288577881\n ],\n [\n -81.4306640625,\n 25.780107118422244\n ],\n [\n -81.243896484375,\n 25.105497373014686\n 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T.","contributorId":219654,"corporation":false,"usgs":false,"family":"Whelan","given":"Kevin","email":"","middleInitial":"R. T.","affiliations":[{"id":35400,"text":"U.S National Park Service","active":true,"usgs":false}],"preferred":false,"id":838415,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rosenheim, Brad E.","contributorId":150227,"corporation":false,"usgs":false,"family":"Rosenheim","given":"Brad","email":"","middleInitial":"E.","affiliations":[{"id":12607,"text":"Univ of South florida, School of Geosciences, Tampa FL","active":true,"usgs":false}],"preferred":false,"id":838416,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Moyer, Ryan P.","contributorId":198993,"corporation":false,"usgs":false,"family":"Moyer","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":13560,"text":"Florida Fish and Wildlife Conservation Commission, Eustis, FL","active":true,"usgs":false}],"preferred":false,"id":838417,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Chambers, Lisa G.","contributorId":288913,"corporation":false,"usgs":false,"family":"Chambers","given":"Lisa","email":"","middleInitial":"G.","affiliations":[{"id":61906,"text":"University of Central Florida, Orlando, FL, 32816 USA","active":true,"usgs":false}],"preferred":false,"id":838418,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70229495,"text":"70229495 - 2021 - The formation, transport, and breakup of submerged oil-particle aggregates in Great Lakes riverine environments","interactions":[],"lastModifiedDate":"2022-03-09T14:30:11.986408","indexId":"70229495","displayToPublicDate":"2021-04-01T08:21:30","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":10269,"text":"Research Brief","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"EPA/600/S-21/061","title":"The formation, transport, and breakup of submerged oil-particle aggregates in Great Lakes riverine environments","docAbstract":"The formation, transport, and resuspension of oil-particle aggregates (OPA) in freshwater environments are of much interest to oil spill responders and scientists, especially as transportation of light and heavy crude oils has substantially increased across river corridors and coasts in the Great Lakes Basin. The persistent sheening from accumulated OPA along 60 km of the Kalamazoo River in Michigan’s lower peninsula resulted in a lengthy and expensive cleanup for the 2010 Enbridge Line 6B pipeline rupture. The interaction of oil with river mineral sediment and organic matter and its long-term fate depend on the physical properties of the oil and particles as well as the environmental setting of river, its climate, morphology, currents and mixing opportunities. This research brief describes the expanded work conducted for the cleanup for the 2010 Enbridge Line 6B pipeline rupture and includes laboratory experiments of aggregate characteristics with Cold Lake Blend and a range of sediment particle sizes, addition of an OPA formation algorithm to an existing sediment contaminant transport model, and development of a simplified, particle-tracking based rapid response model of OPA formation, transport, and deposition. A description of formulas developed for mixing energy in rivers in terms of river properties is also included.","language":"English","publisher":"Environmental Protection Agency","usgsCitation":"Berens, J., Boufadel, M., Fitzpatrick, F., Garcia, M., Hassan, J.S., Hayter, E., Jones, L., Mravik, S., and Waterman, D., 2021, The formation, transport, and breakup of submerged oil-particle aggregates in Great Lakes riverine environments (Revised March 7, 2022): Research Brief EPA/600/S-21/061, 26 p.","productDescription":"26 p.","ipdsId":"IP-130968","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":396902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396889,"type":{"id":15,"text":"Index Page"},"url":"https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=CESER&dirEntryId=354255"}],"country":"United States","state":"Michigan","otherGeospatial":"Kalamazoo River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.21795654296875,\n 42.23461834757937\n ],\n [\n -85.50384521484375,\n 42.23461834757937\n ],\n [\n -85.50384521484375,\n 42.6844544397102\n ],\n [\n -86.21795654296875,\n 42.6844544397102\n ],\n [\n -86.21795654296875,\n 42.23461834757937\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Revised March 7, 2022","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Berens, John","contributorId":288282,"corporation":false,"usgs":false,"family":"Berens","given":"John","email":"","affiliations":[{"id":61720,"text":"University of IL","active":true,"usgs":false}],"preferred":false,"id":837606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boufadel, Michel C.","contributorId":176576,"corporation":false,"usgs":false,"family":"Boufadel","given":"Michel C.","affiliations":[],"preferred":false,"id":837607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia, Marcelo H.","contributorId":74236,"corporation":false,"usgs":false,"family":"Garcia","given":"Marcelo H.","affiliations":[{"id":33106,"text":"University of Illinois at Urbana Champaign","active":true,"usgs":false}],"preferred":false,"id":837609,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hassan, Jacob S.","contributorId":143668,"corporation":false,"usgs":false,"family":"Hassan","given":"Jacob","email":"","middleInitial":"S.","affiliations":[{"id":15293,"text":"USEPA Region V","active":true,"usgs":false}],"preferred":false,"id":837610,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayter, Earl","contributorId":143665,"corporation":false,"usgs":false,"family":"Hayter","given":"Earl","affiliations":[{"id":15290,"text":"USACE, Coastal and Hydraulic Laboratory","active":true,"usgs":false}],"preferred":false,"id":837611,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Lori","contributorId":288283,"corporation":false,"usgs":false,"family":"Jones","given":"Lori","email":"","affiliations":[{"id":61723,"text":"formerly with the University of IL","active":true,"usgs":false}],"preferred":false,"id":837612,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mravik, Susan","contributorId":288284,"corporation":false,"usgs":false,"family":"Mravik","given":"Susan","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":837613,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Waterman, David","contributorId":143664,"corporation":false,"usgs":false,"family":"Waterman","given":"David","email":"","affiliations":[{"id":15289,"text":"University of Illinois, Ven Te Chow Hydrosystems Laboratory","active":true,"usgs":false}],"preferred":false,"id":837614,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70219585,"text":"70219585 - 2021 - Predicting the spatiotemporal exposure of aquatic species to intrusions of fire retardant in streams with limited data","interactions":[],"lastModifiedDate":"2021-04-15T12:51:24.287992","indexId":"70219585","displayToPublicDate":"2021-04-01T07:50:06","publicationYear":"2021","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":"Predicting the spatiotemporal exposure of aquatic species to intrusions of fire retardant in streams with limited data","docAbstract":"

Because fire retardant can enter streams and harm aquatic species including endangered fish, agencies such as the U.S. Forest Service (USFS) must estimate the downstream extent of toxic effects every time fire retardant enters streams (denoted as an “intrusion”). A challenge in estimating the length of stream affected by the intrusion and the exposure time of species in the affected reach is the lack of data typically available on the stream's geometry and flow characteristics. Previously, the USFS estimated the affected reach length assuming instantaneous mixing of the retardant over the reach; however, this approach neglects key river mixing processes. An approach is described that accounts for advection and dispersion of the retardant as well as the downstream growth of the stream. Applied to 13 intrusions documented by the USFS, the new approach shows affected reach lengths range between 8.0 and 362 km; all 13 cases exceeded previous estimates from an instantaneous mixing model. The time that a stationary individual in the affected reach is exposed to concentrations above a pre-defined toxicity threshold (10% of 96-hour LC50, for example) ranges from 0.17 to 2.73 h, with all but one case having a maximum exposure time less than 1.5 h. Results from 1152 hypothetical intrusions provided by the USFS confirm that exposure times rarely exceed 5 h. This result suggests that 96-hour tests to determine toxicity (LC50) to various species should be reconsidered. Although the approach described can be improved in several ways, it provides a first estimate of the effects of fire retardant intrusions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.146879","usgsCitation":"Rehmann, C.R., Jackson, P.R., and Puglis, H.J., 2021, Predicting the spatiotemporal exposure of aquatic species to intrusions of fire retardant in streams with limited data: Science of the Total Environment, v. 782, 146879, 10 p., https://doi.org/10.1016/j.scitotenv.2021.146879.","productDescription":"146879, 10 p.","ipdsId":"IP-124822","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":452854,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2021.146879","text":"Publisher Index Page"},{"id":385121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"782","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rehmann, Chris R.","contributorId":257439,"corporation":false,"usgs":false,"family":"Rehmann","given":"Chris","email":"","middleInitial":"R.","affiliations":[{"id":26913,"text":"Iowa State University, Ames, Iowa","active":true,"usgs":false}],"preferred":false,"id":814249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":814251,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217172,"text":"70217172 - 2021 - A climate risk management screening and assessment review for Madagascar’s Country Development Cooperation Strategy","interactions":[],"lastModifiedDate":"2021-10-11T18:45:28.138122","indexId":"70217172","displayToPublicDate":"2021-03-31T13:41:12","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7569,"text":"Project Summary","active":true,"publicationSubtype":{"id":1}},"title":"A climate risk management screening and assessment review for Madagascar’s Country Development Cooperation Strategy","docAbstract":"

Madagascar, a country rich in natural capital and biodiversity but with high levels of poverty, food insecurity, and population growth, faces a number of development challenges, including obtaining sustained financial support from external sources and building internal capacity to address the poor environmental, health, and socio-economic conditions. Climate change poses an increasing threat to achieving development goals and is usually considered in development plans and project designs. However, there have been numerous challenges in the effective implementation of those plans, particularly in the sustained engagement of the communities to undertake adaptive actions but also due to insufficient scientific information to inform management decisions. To support the United States Agency for International Development (USAID) in the incorporation of Climate Risk Management into their Country Development Cooperation Strategy, we synthesized the best available information on current and future climate change impacts. Climate risks in Madagascar include increasing temperatures, reduced and more variable precipitation, more frequent droughts, more intense cyclones, and rising sea levels. We synthesized the observed and projected impacts of these climatic changes on water resources, agriculture, coastal and terrestrial ecosystems and ecosystem services, fisheries, and human health. Through interviews with stakeholders in Madagascar, we also discerned ongoing and potential climate adaptation and mitigation activities and information gaps (production, access, exploitation, processing, dissemination of information). The information gathered can be used by USAID, NGOs, and other organizations on how to better incorporate climate risks into development strategies and projects in Madagascar.

","language":"English","publisher":"U.S. Agency for International Development","usgsCitation":"Cushing, J.A., Weiskopf, S.R., Morelli, T.L., and Myers, B., 2021, A climate risk management screening and assessment review for Madagascar’s Country Development Cooperation Strategy: Project Summary, 59 p.","productDescription":"59 p.","ipdsId":"IP-121747","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":390403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390402,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/5050cb0ee4b0be20bb30eac0/60146056d34e162231feedc3"}],"country":"Madagascar","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[49.54352,-12.46983],[49.80898,-12.89528],[50.05651,-13.55576],[50.21743,-14.75879],[50.47654,-15.22651],[50.37711,-15.70607],[50.20027,-16.00026],[49.86061,-15.41425],[49.67261,-15.7102],[49.86334,-16.45104],[49.77456,-16.87504],[49.49861,-17.10604],[49.43562,-17.95306],[49.04179,-19.11878],[48.54854,-20.49689],[47.93075,-22.3915],[47.54772,-23.78196],[47.09576,-24.94163],[46.28248,-25.17846],[45.40951,-25.60143],[44.83357,-25.3461],[44.03972,-24.98835],[43.76377,-24.46068],[43.69778,-23.57412],[43.34565,-22.7769],[43.25419,-22.05741],[43.4333,-21.33648],[43.89368,-21.16331],[43.89637,-20.83046],[44.37433,-20.07237],[44.4644,-19.43545],[44.23242,-18.96199],[44.04298,-18.33139],[43.96308,-17.40994],[44.31247,-16.8505],[44.44652,-16.21622],[44.94494,-16.17937],[45.50273,-15.97437],[45.87299,-15.79345],[46.31224,-15.78002],[46.88218,-15.21018],[47.70513,-14.5943],[48.00521,-14.09123],[47.86905,-13.66387],[48.29383,-13.78407],[48.84506,-13.08917],[48.86351,-12.48787],[49.19465,-12.04056],[49.54352,-12.46983]]]},\"properties\":{\"name\":\"Madagascar\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cushing, Janet Alice 0000-0001-6494-8747","orcid":"https://orcid.org/0000-0001-6494-8747","contributorId":247514,"corporation":false,"usgs":true,"family":"Cushing","given":"Janet","email":"","middleInitial":"Alice","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":807823,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weiskopf, Sarah R. 0000-0002-5933-8191","orcid":"https://orcid.org/0000-0002-5933-8191","contributorId":207699,"corporation":false,"usgs":true,"family":"Weiskopf","given":"Sarah","email":"","middleInitial":"R.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":807824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":807825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Myers, Bonnie 0000-0002-3170-2633","orcid":"https://orcid.org/0000-0002-3170-2633","contributorId":219702,"corporation":false,"usgs":true,"family":"Myers","given":"Bonnie","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":807826,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223112,"text":"70223112 - 2021 - Identifying sources of contaminants in urban stormwater and evaluation of their removal efficacy across a continuum of urban best management practices","interactions":[],"lastModifiedDate":"2021-08-11T17:12:48.868725","indexId":"70223112","displayToPublicDate":"2021-03-31T12:01:30","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":9141,"text":"Final Report","active":true,"publicationSubtype":{"id":2}},"title":"Identifying sources of contaminants in urban stormwater and evaluation of their removal efficacy across a continuum of urban best management practices","docAbstract":"

Precipitation events in urban areas often result in stormwater runoff containing a diverse array of chemical contaminants. Although many traditional contaminants, such as nutrients, heavy metals, and polycyclic aromatic hydrocarbons have been studied extensively, only recently has evidence emerged showing that trace organic compounds (TrOCs), including pharmaceuticals, personal care products and pesticides are frequently found in stormwater runoff. As there is little existing information about the sources of TrOCs in urban stormwater or their removal efficacy across a range of stormwater treatment options, we conducted a study to address these knowledge gaps and to characterize the potential contribution of TrOCs to groundwater resources from stormwater infiltration practices, based on several synoptic measurements. The current study allowed us to enhance an existing effort to assess TrOC presence and toxicity in stormwater runoff and treatment pond outflow by addressing questions related to TrOC sources to stormwater and TrOC transport to groundwaters.

Analysis of eDNA confirms multiple sources of TrOCs to stormwater including human sewage, dog waste, and feces from waterfowl. It is likely that the presence of some TrOCs detected in stormwater are the result of direct, untreated sewage inputs to stormwater from either human (i.e., leaking sewer infrastructure) or pet waste (washed from sidewalks into storm drains). The seasonal detection of avian eDNA is noteworthy as it highlights seasonality and patterns of migration patterns as contributing factors to stormwater contamination. In contrast to human and pet waste, which likely enters stormwater ponds via the stormwater conveyance system, avian feces may enter ponds either through stormwater runoff or through direct inputs by waterfowl stopping-over temporarily at stormwater ponds. Stormwater ponds had little effect in reducing TrOCs as determined by comparative inflow and outflow analysis. Our results also indicate that overall few TrOCs were present in receiving groundwater adjacent to underground infiltration basins, compared to inflow. However, some contaminants were present at relatively high concentrations compared to stormwater flowing into the basins. This is particularly true for pesticides and their degradants. Fewer TrOCs were detected in interstitial water collected near stormwater ponds compared to inflow and outflow. The presence and concentrations of TrOCs in outflow from ponds was generally similar to or higher than what was observed in inflow.

The data collected as part of this study can be used to guide future research or monitoring in an effort to better understand TrOC fate and transport in the environment via stormwater BMPs. Specifically, more work is needed to track parcels of water as they flow through BMPs to better quantify transport and degradation of TrOCs, monitor flow into and out of ponds for mass balance calculations, and conduct tracer tests to better quantify the amount of water that monitoring wells are intercepting from underground infiltration basins.

These results have been shared in multiple presentations and in meetings with high school teachers to develop age-appropriate curriculum to highlight the role of individuals in reducing and preventing stormwater contamination. The ongoing pandemic hindered some of these efforts (cancelled conferences; suspended MN Water Roundtable meetings; pre-occupation with teachers moving materials online), however, as dissemination activities become more common in the near future, we will continue to educate stakeholders and educators about the root causes and effects of urban stormwater contamination.

","language":"English","publisher":"University of Minnesota","usgsCitation":"Schoenfuss, H.L., Kiesling, R.L., Elliott, S.M., and Kohno, S., 2021, Identifying sources of contaminants in urban stormwater and evaluation of their removal efficacy across a continuum of urban best management practices: Final Report, 46 p.","productDescription":"46 p.","ipdsId":"IP-127948","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":387866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387830,"type":{"id":15,"text":"Index Page"},"url":"https://www.wrc.umn.edu/sites/wrc.umn.edu/files/identifying_sources_of_contaminants_scsu_usgs_final_report_march_2021.pdf"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.44970703125,\n 44.95265089681472\n ],\n [\n -93.01162719726562,\n 44.95265089681472\n ],\n [\n -93.01162719726562,\n 45.22364447346731\n ],\n [\n -93.44970703125,\n 45.22364447346731\n ],\n [\n -93.44970703125,\n 44.95265089681472\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":821064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821065,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kohno, Satomi","contributorId":264174,"corporation":false,"usgs":false,"family":"Kohno","given":"Satomi","email":"","affiliations":[],"preferred":false,"id":821066,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228178,"text":"70228178 - 2021 - Long-term salinity change and growth of the harmful alga, Prymnesium parvum","interactions":[],"lastModifiedDate":"2022-02-07T16:35:40.557042","indexId":"70228178","displayToPublicDate":"2021-03-31T10:15:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2422,"text":"Journal of Phycology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Long-term salinity change and growth of the harmful alga, Prymnesium parvum","title":"Long-term salinity change and growth of the harmful alga, Prymnesium parvum","docAbstract":"

Prymnesium parvum is a euryhaline, toxin-producing microalga. Although its abundance in inland waters and growth potential in the laboratory is reduced at high salinity (>20), the ability of inland strains to adjust their growth after long-term residence in high salinity is uncertain. An inland strain of P. parvum maintained at salinity of 5 in modified artificial seawater medium (ASM-5) was subjected to the following treatments over five sequential batch culture rounds: ASM-5 (control); modified ASM at salinity of 30, raised with NaCl; modified ASM at salinity incrementally increased to 30 with NaCl; and Instant Ocean® at salinity of 30 (IO-30). Exponential growth rate (r) was reduced when salinity was increased from 5 to 30 in ASM but returned to control values during the second round. When salinity was incrementally increased, a reduction in r still occurred when salinity reached 25-30. Maximum density was reduced at salinity of 30 in ASM upon abrupt transfer or incremental increase, and compensation did not occur. Growth performance in IO-30 was comparable to control values. In conclusion, (i) long-term compensation for acute inhibitory effects of high salinity occurred for r but not maximum density, (ii) incremental increases in salinity did not prevent growth inhibition, suggesting the existence of a salinity threshold of 25–30 for onset of salinity stress, and (iii) the presence of a seawater-like salt mixture prevented growth inhibition by high salinity. These findings provide new insights on P. parvum's long-term ability to adjust its growth in environments of different salinity and ionic composition.

","language":"English","publisher":"Phycological Society of America","doi":"10.1111/jpy.13172","usgsCitation":"Richardson, E.T., and Patino, R., 2021, Long-term salinity change and growth of the harmful alga, Prymnesium parvum: Journal of Phycology, v. 57, no. 4, p. 1335-1344, https://doi.org/10.1111/jpy.13172.","productDescription":"10 p.","startPage":"1335","endPage":"1344","ipdsId":"IP-109389","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Richardson, Emily T.","contributorId":274795,"corporation":false,"usgs":false,"family":"Richardson","given":"Emily","email":"","middleInitial":"T.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":833318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patino, Reynaldo 0000-0002-4831-8400 r.patino@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-8400","contributorId":2311,"corporation":false,"usgs":true,"family":"Patino","given":"Reynaldo","email":"r.patino@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833317,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70220261,"text":"70220261 - 2021 - Habitat suitability index model improvement recommendations","interactions":[],"lastModifiedDate":"2021-04-29T13:20:08.027314","indexId":"70220261","displayToPublicDate":"2021-03-31T08:19:03","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Habitat suitability index model improvement recommendations","docAbstract":"As part of the model improvement effort for the 2023 Coastal Master Plan, the Habitat Suitability Index (HSI) models used during previous master plans were reevaluated to assess how the model relationships could be improved, and to determine what species should be included in the master plan analyses. This process considered the technical reviews, comments, and suggested improvements provided by model developers, advisory groups, and other experts during previous master plans. Reviews were then conducted to determine the availability of data and information that could be used to make model improvements. As a result of this effort, a recommended list of relevant species to model is provided, and HSI model improvements are recommended that are categorized by whether the suitability index (SI) relationship to be improved is statistical-based or literature-based. \n\nThe species recommended to be included in the 2023 Coastal Master Plan analyses are: eastern oyster, brown shrimp, white shrimp, blue crab, crayfish, gulf menhaden, spotted seatrout, largemouth bass, American alligator, gadwall, mottled duck, brown pelican, seaside sparrow, and bald eagle. These species were selected because they represent a range of taxonomies, life histories, trophic levels, and habitats, and most are commercially- or recreationally-important in coastal Louisiana. Most of these species were also included in the 2017 Coastal Master Plan analyses, and the models used during that effort should be further improved. Seaside sparrow and bald eagle are new for the master plan, and new models should be developed for the analyses. \n\nThe 2017 fish, shrimp, and blue crab HSI models included a water quality SI that was based on statistical analyses of species catch and environmental data collected by the Louisiana Department of Wildlife and Fisheries. As suggested during the 2017 Coastal Master Plan, the modeling approach used to develop the water quality SI was revisited and alternate modeling approaches were explored. Using literature and an evaluation of the general steps of model development, three components for HSI model improvement were identified, including 1) selecting alternative modeling approach(es); 2) detecting and resolving statistical issues; and 3) improving model fit and evaluation. Multiple options for each component were explored, which resulted in a proposed multi-step phased approach for model improvement. This proposed approach entails improving the generalized linear models used for the 2017 water quality SIs and then, if desired, comparing them to alternative model approaches (e.g., generalized additive models) to explore model performance and select the best approach to use for the 2023 Coastal Master Plan HSI models. \n\nAll of the existing master plan HSI models include literature-based SIs, which use information from published studies of species-habitat associations to derive suitability relationships. Similar to previous master plans, these literature-based SIs should be updated and improved for the 2023 Coastal Master Plan using recent literature and new ecological knowledge. Preliminary reviews were conducted and recent information was found that could be used to improve the eastern oyster, crayfish, and potentially brown pelican HSI models; but no appropriate recent literature was located for improvement of the American alligator, gadwall, and mottled duck HSI models. However, it is recommended that the literature reviews and information searches be continued. In addition to the statistical-based water quality SI, the 2017 fish, shrimp, and blue crab HSI models also included a structural habitat SI that was based on literature showing high densities of these species in fragmented marsh. The relationship used for this SI, however, did not account for the effects of other estuarine habitats, such as submerged aquatic vegetation and oyster reefs, which are also important to these species. Therefore, a meta-analysis approach is proposed that would estimate the relative importance of these habitats for each species, and the results of this analysis could be used to calculate a new structural habitat SI for the 2023 Coastal Master Plan.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2023 Coastal Master Plan","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Coastal Protection and Restoration Authority","usgsCitation":"Sable, S.E., Lindquist, D.C., D’Acunto, L., Hijuelos, A., LaPeyre, M.K., O'Connell, A., and Robinson, E.M., 2021, Habitat suitability index model improvement recommendations, 49 p.","productDescription":"49 p.","ipdsId":"IP-109817","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":385388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385374,"type":{"id":15,"text":"Index Page"},"url":"https://coastal.la.gov/our-plan/2023-coastal-master-plan/technical-resources/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sable, Shaye E.","contributorId":257728,"corporation":false,"usgs":false,"family":"Sable","given":"Shaye","email":"","middleInitial":"E.","affiliations":[{"id":52096,"text":"Dynamic Solutions, LLC","active":true,"usgs":false}],"preferred":false,"id":814922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindquist, David C.","contributorId":257729,"corporation":false,"usgs":false,"family":"Lindquist","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":40763,"text":"Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":814923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":814924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hijuelos, Ann 0000-0003-0922-6754","orcid":"https://orcid.org/0000-0003-0922-6754","contributorId":201525,"corporation":false,"usgs":true,"family":"Hijuelos","given":"Ann","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":814925,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":814926,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O'Connell, Ann M.","contributorId":257730,"corporation":false,"usgs":false,"family":"O'Connell","given":"Ann M.","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":814927,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robinson, Elizabeth M.","contributorId":257731,"corporation":false,"usgs":false,"family":"Robinson","given":"Elizabeth","email":"","middleInitial":"M.","affiliations":[{"id":40763,"text":"Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":814928,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70220262,"text":"70220262 - 2021 - Habitat suitability index model improvements","interactions":[],"lastModifiedDate":"2021-04-29T13:18:04.649339","indexId":"70220262","displayToPublicDate":"2021-03-31T08:17:18","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Habitat suitability index model improvements","docAbstract":"Habitat suitability index (HSI) models were developed for the 2023 Coastal Master Plan to evaluate the potential effects of coastal restoration and protection projects on habitat for key coastal fish, shellfish, and wildlife species. These species included: eastern oyster, brown shrimp, white shrimp, blue crab, crayfish, gulf menhaden, spotted seatrout, largemouth bass, American alligator, gadwall, mottled duck, brown pelican, seaside sparrow, and bald eagle. Most of these species were included in the 2017 Coastal Master Plan analyses, and the HSI models from that effort were refined and improved following the recommendations described in the technical memorandum: 2023 Coastal Master Plan Habitat Suitability Index Model Improvement Recommendations (Sable et al., 2019). In addition to model improvements, HSI models were created for seaside sparrow and bald eagle, both of which are new species for the master plan analyses. \n\nFor the HSI models that are primarily literature-based, literature reviews were conducted for recent studies that could be used to improve the suitability index (SI) relationships that compose the models. As a result of this review, modifications were made to the salinity-related SIs of the oyster model including: expanding the time period used for salinity effects to spawning; adjusting the range of suitable annual average salinity to be more representative of Louisiana populations; and making oyster’s minimum salinity tolerance temperature dependent. In addition, a new SI was incorporated in the oyster HSI model that accounts for the effects of sediment deposition on oysters. The crayfish HSI model was improved by adjusting the time periods used for the SIs that describe the hydrology required for the crayfish life cycle, and the soil characteristics SI that was part of the 2017 crayfish model was removed because soil conditions do not appear to be limiting for crayfish burrow construction in coastal Louisiana. The other literature-based HSI models from the 2017 Coastal Master Plan, i.e., American alligator, gadwall, mottled duck, and brown pelican, were unchanged, with the exception of a small adjustment made to the suitability of forested wetlands for gadwall. Lastly, a literature-based HSI model was created for seaside sparrow that consists of SIs related to vegetated habitat type, marsh vegetation coverage, and marsh elevation. \n\nStatistical-based HSI models were developed for brown shrimp (both small and large juvenile stages), white shrimp (small and large juvenile stages), blue crab (juvenile stage), gulf menhaden (juvenile and adult stages), spotted seatrout (juvenile and adult stages), largemouth bass, and bald eagle. The bald eagle HSI model was developed from a bald eagle nest probability of occurrence model that related nest occurrence from survey data with land cover type. The resulting model showed that combinations of forested wetlands, flotant marsh, and open water habitats were most suitable for nesting bald eagles. The 2023 fish, shrimp, and blue crab HSI models were developed using new approaches for the formulation of the water quality and structural habitat SIs that compose the models. For the 2017 models, the water quality SI was derived using only generalized linear mixed models (GLMMs) to estimate the relationship between salinity, water temperature, and species’ catch. For the 2023 models, however, multiple GLMMs and generalized additive models (GAMMs) were created for each species or life stage. These alternative models were compared and a single model that performed well statistically and was ecologically reasonable was selected for the species’ water quality SI. The structural habitat SI was developed using a meta-analysis of published literature to estimate the relative importance of various estuarine habitats to the fish and shellfish species. The results of this analysis were then used to modify the 2017 structural habitat SI relationship to account for the added habitat value of submerged aquatic vegetation and oyster reefs, which are also important habitats for juvenile fish and shellfish. Similar to the 2017 fish, shrimp, and blue crab models, the water quality and structural habitat SIs were then combined to create the 2023 HSI models. \n\nThe 2023 Coastal Master Plan HSI models were integrated with the Integrated Compartment Model (and are referred to as ICM-HSIs) and tested using environmental output from the 2017 Coastal Master Plan Future Without Action scenario. The tests showed that, in general, the models produced reasonable representations of species’ habitat distribution. Furthermore, the improvements made to the oyster, crayfish, fish, shrimp, and blue crab HSI models generally yielded more realistic results compared to the 2017 HSI models.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2023 Coastal Master Plan","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Coastal Protection and Restoration Authority","usgsCitation":"Lindquist, D.C., Sable, S.E., D’Acunto, L., Hijuelos, A., Johnson, E.I., Langlois, S.R., Michel, N.L., Nakashima, L., O’Connell, A.M., Percy, K.L., and Robinson, E.M., 2021, Habitat suitability index model improvements, 189 p.","productDescription":"189 p.","ipdsId":"IP-124495","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":385387,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385375,"type":{"id":15,"text":"Index Page"},"url":"https://coastal.la.gov/our-plan/2023-coastal-master-plan/technical-resources/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lindquist, David C.","contributorId":257729,"corporation":false,"usgs":false,"family":"Lindquist","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":40763,"text":"Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":814929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sable, Shaye E.","contributorId":257728,"corporation":false,"usgs":false,"family":"Sable","given":"Shaye","email":"","middleInitial":"E.","affiliations":[{"id":52096,"text":"Dynamic Solutions, LLC","active":true,"usgs":false}],"preferred":false,"id":814930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":814931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hijuelos, Ann 0000-0003-0922-6754","orcid":"https://orcid.org/0000-0003-0922-6754","contributorId":216667,"corporation":false,"usgs":true,"family":"Hijuelos","given":"Ann","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":814932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Erik I.","contributorId":257732,"corporation":false,"usgs":false,"family":"Johnson","given":"Erik","email":"","middleInitial":"I.","affiliations":[{"id":52099,"text":"Audubon Louisiana","active":true,"usgs":false}],"preferred":false,"id":814933,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Langlois, Summer R.M","contributorId":257733,"corporation":false,"usgs":false,"family":"Langlois","given":"Summer","email":"","middleInitial":"R.M","affiliations":[{"id":40763,"text":"Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":814934,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Michel, Nicole L.","contributorId":257734,"corporation":false,"usgs":false,"family":"Michel","given":"Nicole","email":"","middleInitial":"L.","affiliations":[{"id":52101,"text":"Audubon Louisiana, National Audubon Society","active":true,"usgs":false}],"preferred":false,"id":814935,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nakashima, Lindsay","contributorId":257735,"corporation":false,"usgs":false,"family":"Nakashima","given":"Lindsay","affiliations":[{"id":52099,"text":"Audubon Louisiana","active":true,"usgs":false}],"preferred":false,"id":814936,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"O’Connell, Ann M.","contributorId":257736,"corporation":false,"usgs":false,"family":"O’Connell","given":"Ann","email":"","middleInitial":"M.","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":814937,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Percy, Katie L.","contributorId":191722,"corporation":false,"usgs":false,"family":"Percy","given":"Katie","email":"","middleInitial":"L.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":814938,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Robinson, Elizabeth M.","contributorId":257731,"corporation":false,"usgs":false,"family":"Robinson","given":"Elizabeth","email":"","middleInitial":"M.","affiliations":[{"id":40763,"text":"Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":814939,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70224551,"text":"70224551 - 2021 - Riparian area changes in greenness and water use on the Lower Colorado River in the USA from 2000-2020","interactions":[],"lastModifiedDate":"2025-12-11T22:15:33.73473","indexId":"70224551","displayToPublicDate":"2021-03-31T07:26:26","publicationYear":"2021","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":"Riparian area changes in greenness and water use on the Lower Colorado River in the USA from 2000-2020","docAbstract":"
Declines in riparian ecosystem greenness and water use have been observed in the delta of the Lower Colorado River (LCR) since 2000. The purpose of our case study was to measure these metrics on the U.S. side of the border between Hoover and Morelos Dams to see if declining greenness was unique to the portion of the river in Mexico. In this case study, five riparian reaches of the LCR from Hoover to Morelos Dam since 2000 were studied to evaluate trends in riparian ecosystem health. We measure these riparian woodlands using remotely sensed measurements of the two-band Enhanced Vegetation Index (EVI2; a proxy for greenness); daily evapotranspiration (ET; mmd−1) using EVI2 (ET(EVI2)); and an annualized ET based on EVI2, the Phenology Assessment Metric (PAM ET), an annualized ET using Landsat time-series. A key finding is that riparian health and its water use has been in decline since 2000 on the U.S. portion of the LCR, depicting a loss of green vegetation over the last two decades. EVI2 results show a decline of −13.83%, while average daily ET(EVI2) between the first and last decade had a decrease of over 1 mmd−1 (−27.30%) and the respective average PAM ET losses were 170.91 mmyr−1 (−17.95%). The difference between the first and last five-year periods, 2000–2005 and 2016–2020, showed the largest decrease in daily ET(EVI) of 1.24 mmd−1 (−32.61%). These declines come from a loss in healthy, green, riparian plant-cover, not a change in plant water use efficiency nor efficient use of managed water resources. Our results suggest further deterioration of biodiversity, wildlife habitat and other key ecosystem services on the U.S. portion of the LCR.
","language":"English","publisher":"MDPI","doi":"10.3390/rs13071332","usgsCitation":"Nagler, P.L., Barreto-Muñoz, A., Borujeni, S.C., Nouri, H., Jarchow, C., and Didan, K., 2021, Riparian area changes in greenness and water use on the Lower Colorado River in the USA from 2000-2020: Remote Sensing, v. 13, no. 7, 1332, 48 p.; Data Release, https://doi.org/10.3390/rs13071332.","productDescription":"1332, 48 p.; Data Release","ipdsId":"IP-125535","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":452865,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13071332","text":"Publisher Index Page"},{"id":436426,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MIPBRP","text":"USGS data release","linkHelpText":"Colorado River Project: A compilation of vegetation indices, phenology assessment metrics, estimates of evapotranspiration and change maps for five reaches between Hoover and Morelos Dams on the Lower Colorado River, for nearly the last two decades"},{"id":389803,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California","otherGeospatial":"Lower Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.9169921875,\n 32.509761735919426\n ],\n [\n -113.90625,\n 32.509761735919426\n ],\n [\n -113.90625,\n 35.38904996691167\n ],\n [\n -114.9169921875,\n 35.38904996691167\n ],\n [\n -114.9169921875,\n 32.509761735919426\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barreto-Muñoz, Armando","contributorId":239891,"corporation":false,"usgs":false,"family":"Barreto-Muñoz","given":"Armando","affiliations":[{"id":48028,"text":"University of Arizona, Biosystems Engineering, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":824041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borujeni, Sattar Chavoshi","contributorId":240671,"corporation":false,"usgs":false,"family":"Borujeni","given":"Sattar","email":"","middleInitial":"Chavoshi","affiliations":[],"preferred":false,"id":824042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nouri, Hamideh","contributorId":178847,"corporation":false,"usgs":false,"family":"Nouri","given":"Hamideh","affiliations":[],"preferred":false,"id":824043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":211737,"corporation":false,"usgs":false,"family":"Jarchow","given":"Christopher J.","affiliations":[{"id":38314,"text":"USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":824044,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Didan, Kamel","contributorId":130999,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":824045,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219191,"text":"70219191 - 2021 - Considerations of variability and power for long-term monitoring of stream fish assemblages","interactions":[],"lastModifiedDate":"2021-03-30T12:28:36.815319","indexId":"70219191","displayToPublicDate":"2021-03-30T07:27:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Considerations of variability and power for long-term monitoring of stream fish assemblages","docAbstract":"Little attention has been given to optimizing statistical power for monitoring stream fish assemblages. We explored the relationship between temporal variability and statistical power using 34 metrics from fish community data collected annually at six sites over 10 years via electrofishing. Metric variability differed by the life stage and group of species considered, use of abundance or mass data, and data standardization technique. Lower variability was associated with community data, abundance data, and time-based standardizations, while greater variability was associated with young-of-the-year data, mass data, and area-based standardizations. Simulation-based power analysis indicated metric choice, and to a lesser degree, monitoring design (annual, biennial, endpoints, or haphazard sampling) influenced power to detect change. Across a fixed number of surveys (N = 60), endpoints sampling performed best. The N needed to detect change was heavily dependent upon metric choice for all monitoring designs, with the most biologically specific metrics requiring greater N. Large savings in effort and resource expenditure can be obtained utilizing biologically relevant metrics that are robust to temporal noise within an appropriate sampling design.","language":"English","publisher":"Canadian Journal of Fisheries and Aquatic Sciences","doi":"10.1139/cjfas-2020-0013","usgsCitation":"George, S.D., Daniel Stich, and Baldigo, B.P., 2021, Considerations of variability and power for long-term monitoring of stream fish assemblages: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 3, p. 301-311, https://doi.org/10.1139/cjfas-2020-0013.","productDescription":"11 p.","startPage":"301","endPage":"311","ipdsId":"IP-106954","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":452881,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2020-0013","text":"Publisher Index Page"},{"id":384753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daniel Stich","contributorId":256732,"corporation":false,"usgs":false,"family":"Daniel Stich","affiliations":[{"id":51843,"text":"SUNY College at Oneonta","active":true,"usgs":false}],"preferred":false,"id":813155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813156,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70222116,"text":"70222116 - 2021 - Preliminary assessment of carbon and nitrogen sequestration potential of wildfire-derived sediments stored by erosion control structures in forest ecosystems, southwest USA","interactions":[],"lastModifiedDate":"2021-07-20T12:30:15.167553","indexId":"70222116","displayToPublicDate":"2021-03-30T07:27:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":686,"text":"Air, Soil and Water Research","active":true,"publicationSubtype":{"id":10}},"title":"Preliminary assessment of carbon and nitrogen sequestration potential of wildfire-derived sediments stored by erosion control structures in forest ecosystems, southwest USA","docAbstract":"

The role of pyrogenic carbon (PyC) in the global carbon cycle is still incompletely characterized. Much work has been done to characterize PyC on landforms and in soils where it originates or in “terminal” reservoirs such as marine sediments. Less is known about intermediate reservoirs such as streams and rivers, and few studies have characterized hillslope and in-stream erosion control structures (ECS) designed to capture soils and sediments destabilized by wildfire. In this preliminary study, organic carbon (OC), total nitrogen (N), and stable isotope parameters, δ13C and δ15N, were compared to assess opportunities for carbon and nitrogen sequestration in postwildfire sediments (fluvents) deposited upgradient of ECS in ephemeral- and intermittent-stream channels. The variability of OC, N, δ13C, and δ15N were analyzed in conjunction with fire history, age of captured sediments, topographic position, and land cover. Comparison of samples in 2 watersheds indicates higher OC and N in ECS with more recently captured sediments located downstream of areas with higher burn severity. This is likely a consequence of (1) higher burn severity causing greater runoff, erosion, and transport of OC (organic matter) to ECS and (2) greater cumulative loss of OC and N in older sediments stored behind older ECS. In addition, C/N, δ13C, and δ15N results suggest that organic matter in sediments stored at older ECS are enriched in microbially processed biomass relative to those at newer ECS. We conservatively estimated the potential mean annual capture of OC by ECS, using values from the watershed with lower levels of OC, to be 3 to 4 metric tons, with a total potential storage of 293 to 368 metric tons in a watershed of 7.7 km2 and total area of 2000 ECS estimated at 2.6 ha (203-255 metric tons/ha). We extrapolated the OC results to the regional level (southwest USA) to estimate the potential for carbon sequestration using these practices. We estimated a potential of 0.01 Pg, which is significant in terms of ecosystem services and regional efforts to promote carbon storage.

","language":"English","publisher":"Sage Publishing","doi":"10.1177/11786221211001768","usgsCitation":"Callegary, J.B., Norman, L., Eastoe, C.J., Sankey, J., and Youberg, A., 2021, Preliminary assessment of carbon and nitrogen sequestration potential of wildfire-derived sediments stored by erosion control structures in forest ecosystems, southwest USA: Air, Soil and Water Research, v. 14, 18 p., https://doi.org/10.1177/11786221211001768.","productDescription":"18 p.","ipdsId":"IP-088935","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":452884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/11786221211001768","text":"Publisher Index 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\"}}]}","volume":"14","noUsgsAuthors":false,"publicationDate":"2021-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Callegary, James B. 0000-0003-3604-0517 jcallega@usgs.gov","orcid":"https://orcid.org/0000-0003-3604-0517","contributorId":2171,"corporation":false,"usgs":true,"family":"Callegary","given":"James","email":"jcallega@usgs.gov","middleInitial":"B.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":819586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eastoe, Christopher J.","contributorId":173510,"corporation":false,"usgs":false,"family":"Eastoe","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":819587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":819588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Youberg, Ann 0000-0002-2005-3674","orcid":"https://orcid.org/0000-0002-2005-3674","contributorId":172400,"corporation":false,"usgs":false,"family":"Youberg","given":"Ann","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":819589,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220274,"text":"70220274 - 2021 - Assessing the effectiveness of nourishment in decadal barrier island morphological resilience","interactions":[],"lastModifiedDate":"2021-04-30T12:24:22.609289","indexId":"70220274","displayToPublicDate":"2021-03-30T07:17:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the effectiveness of nourishment in decadal barrier island morphological resilience","docAbstract":"
Nourishment has shown to be an effective method for short-term storm protection along barrier islands and sandy beaches by reducing flooding, wave attack and erosion. However, the ability of nourishment to mitigate the effects of storms and sea level rise (SLR) and improve coastal resilience over decadal time scales is not well understood. This study uses integrated models of storm-driven hydrodynamics, morphodynamics and post-storm dune recovery to assess the effectiveness of beach and dune nourishment on barrier island morphological resilience over a 30-year period, accounting for storms and a moderate amount of SLR. Results show that at the end of the 30 years, nourishment contributes to maintaining island volumes by increasing barrier height and width compared with a no-action scenario (i.e., no nourishment, only natural recovery). During storms where the collision regime was dominant, higher volumes of sand were lost from the wider beach in the nourishment scenario than in the no-action scenario. During stronger storms, nourishment reduced dune overtopping compared with the no-action scenario, allowing the island to maintain height and width. Additionally, nourishment was particularly effective in reducing breaching during back-to-back storms occurring in the same year.
","language":"English","publisher":"MDPI","doi":"10.3390/w13070944","usgsCitation":"Passeri, D., Bilskie, M.V., Hagen, S.C., Mickey, R.C., Dalyander, P., and Gonzalez, V., 2021, Assessing the effectiveness of nourishment in decadal barrier island morphological resilience: Water, v. 13, no. 7, 944, 14 p., https://doi.org/10.3390/w13070944.","productDescription":"944, 14 p.","ipdsId":"IP-126358","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":452887,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13070944","text":"Publisher Index Page"},{"id":436428,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BH4JFR","text":"USGS data release","linkHelpText":"Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs"},{"id":385408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.23532104492186,\n 30.20448740114747\n ],\n [\n -88.00735473632812,\n 30.20448740114747\n ],\n [\n -88.00735473632812,\n 30.28990324883237\n ],\n [\n -88.23532104492186,\n 30.28990324883237\n ],\n [\n -88.23532104492186,\n 30.20448740114747\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":814966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bilskie, Matthew V.","contributorId":166891,"corporation":false,"usgs":false,"family":"Bilskie","given":"Matthew","email":"","middleInitial":"V.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":814967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagen, Scott C.","contributorId":166890,"corporation":false,"usgs":false,"family":"Hagen","given":"Scott","email":"","middleInitial":"C.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":814968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mickey, Rangley C. 0000-0001-5989-1432 rmickey@usgs.gov","orcid":"https://orcid.org/0000-0001-5989-1432","contributorId":141016,"corporation":false,"usgs":true,"family":"Mickey","given":"Rangley","email":"rmickey@usgs.gov","middleInitial":"C.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":814969,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dalyander, P Soupy","contributorId":257752,"corporation":false,"usgs":false,"family":"Dalyander","given":"P Soupy","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":814970,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gonzalez, Victor","contributorId":173702,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Victor","affiliations":[],"preferred":false,"id":814971,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238741,"text":"70238741 - 2021 - Warming induces divergent stomatal dynamics in co-occurring boreal trees","interactions":[],"lastModifiedDate":"2022-12-07T12:59:44.04493","indexId":"70238741","displayToPublicDate":"2021-03-30T06:57:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Warming induces divergent stomatal dynamics in co-occurring boreal trees","docAbstract":"

Climate warming will alter photosynthesis and respiration not only via direct temperature effects on leaf biochemistry but also by increasing atmospheric dryness, thereby reducing stomatal conductance and suppressing photosynthesis. Our knowledge on how climate warming affects these processes is mainly derived from seedlings grown under highly controlled conditions. However, little is known regarding temperature responses of trees growing under field settings. We exposed mature tamarack and black spruce trees growing in a peatland ecosystem to whole-ecosystem warming of up to +9°C above ambient air temperatures in an ongoing long-term experiment (SPRUCE: Spruce and Peatland Responses Under Changing Environments). Here, we report the responses of leaf gas exchange after the first two years of warming. We show that the two species exhibit divergent stomatal responses to warming and vapor pressure deficit. Warming of up to 9°C increased leaf N in both spruce and tamarack. However, higher leaf N in the warmer plots translate into higher photosynthesis in tamarack but not in spruce, with photosynthesis being more constrained by stomatal limitations in spruce than in tamarack under warm conditions. Surprisingly, dark respiration did not acclimate to warming in spruce, and thermal acclimation of respiration was only seen in tamarack once changes in leaf N were considered. Our results highlight how warming can lead to differing stomatal responses to warming in co-occurring species, with consequent effects on both vegetation carbon and water dynamics.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15620","usgsCitation":"Dusenge, M.E., Ward, E., Warren, J.M., Stinziano, J., Wullschleger, S.D., Hanson, P.J., and Way, D.A., 2021, Warming induces divergent stomatal dynamics in co-occurring boreal trees: Global Change Biology, v. 27, no. 13, p. 3079-3094, https://doi.org/10.1111/gcb.15620.","productDescription":"16 p.","startPage":"3079","endPage":"3094","ipdsId":"IP-112805","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":452890,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.15620","text":"External Repository"},{"id":410155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"13","noUsgsAuthors":false,"publicationDate":"2021-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Dusenge, Mirindi E.","contributorId":299727,"corporation":false,"usgs":false,"family":"Dusenge","given":"Mirindi","email":"","middleInitial":"E.","affiliations":[{"id":13224,"text":"The University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":858459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":217389,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":858460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warren, Jeffrey M.","contributorId":266135,"corporation":false,"usgs":false,"family":"Warren","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[{"id":54925,"text":"Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA","active":true,"usgs":false}],"preferred":false,"id":858461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stinziano, Joseph R.","contributorId":299728,"corporation":false,"usgs":false,"family":"Stinziano","given":"Joseph R.","affiliations":[{"id":13224,"text":"The University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":858462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wullschleger, Stan D.","contributorId":167343,"corporation":false,"usgs":false,"family":"Wullschleger","given":"Stan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":858463,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hanson, Paul J.","contributorId":299729,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"J.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":858464,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Way, Danielle A.","contributorId":199465,"corporation":false,"usgs":false,"family":"Way","given":"Danielle","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":858465,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219172,"text":"ds1136 - 2021 - Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January 2017 through December 2019","interactions":[],"lastModifiedDate":"2021-03-30T11:57:07.918866","indexId":"ds1136","displayToPublicDate":"2021-03-29T17:42:50","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1136","displayTitle":"Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project, January 2017 through December 2019","title":"Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January 2017 through December 2019","docAbstract":"

Groundwater-quality environmental data were collected from 983 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water Quality Program and are included in this report. The data were collected from six types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes; vertical flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths; and modeling support studies, which are used to provide data to support groundwater modeling. Groundwater samples were analyzed for many water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, microbiological indicators, and some constituents of special interest (arsenic speciation, hexavalent chromium [chromium (VI)], and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release. Data for microbiological indicators for samples collected in 2016 are included in the companion data release.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1136","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Kingsbury, J.A., Bexfield, L.M., Arnold, T., Musgrove, M., Erickson, M.L., Degnan, J.R., Tesoriero, A.J., Lindsey, B.D., and Belitz, K., 2021, Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January 2017 through December 2019: U.S. Geological Survey Data Series 1136, 97 p., https://doi.org/10.3133/ds1136.","productDescription":"Report: x, 97 p.; 2 Appendixes; Data Release; Dataset","numberOfPages":"112","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118835","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science 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Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park Drive
Nashville, TN 37211

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-03-29","noUsgsAuthors":false,"publicationDate":"2021-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Kingsbury, James A. 0000-0003-4985-275X jakingsb@usgs.gov","orcid":"https://orcid.org/0000-0003-4985-275X","contributorId":883,"corporation":false,"usgs":true,"family":"Kingsbury","given":"James","email":"jakingsb@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnold, Terri 0000-0003-1406-6054 tlarnold@usgs.gov","orcid":"https://orcid.org/0000-0003-1406-6054","contributorId":1598,"corporation":false,"usgs":false,"family":"Arnold","given":"Terri","email":"tlarnold@usgs.gov","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":813124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":197013,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":37277,"text":"WMA - 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While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4. At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15661","usgsCitation":"Knox, S., Bansal, S., McNicol, G., Schafer, K., Sturtevant, C., Ueyama, M., Valach, A., Baldocchi, D., Delwiche, K.B., Desai, A.R., Euskirchen, E.S., Liu, J., Lohila, A., Malhotra, A., Melling, L., Riley, W., Runkle, B.R., Turner, J., Vargas, R., Zhu, Q., Alto, T., Fluet-Chouinard, E., Goeckede, M., Melton, J., Sonnentag, O., Vesala, T., Ward, E., Zhang, Z., Feron, S., Ouyang, Z., Tang, A., Alekseychik, P., Aurela, M., Bohrer, G., Campbell, D.I., Chen, J., Chu, H., Dalmagro, H., Goodrich, J.P., Gottschalk, P., Hirano, T., Iwata, H., Jurasinski, G., Kang, M., Koebsch, F., Mammarella, I., Nilsson, M.B., Ono, K., Peichl, M., Peltola, O., Ryu, Y., Sachs, T., Sakabe, A., Sparks, J., Tuittila, E., Vourlitis, G., Wong, G.X., Windham-Myers, L., Poulter, B., and Jackson, R.B., 2021, Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales: Global 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statistical approaches have greatly expanded the breadth of knowledge regarding aquatic ecosystem metabolism - the measurement and interpretation of gross primary productivity (GPP) and ecosystem respiration (ER). Aquatic scientists are poised to take advantage of widely available datasets and freely-available modeling tools to apply functional information gained through ecosystem metabolism to better environmental management. Historically, several logistical and conceptual factors have limited the widespread application of metabolism in management settings. Benefitting from new instrumental and modeling tools, it is now relatively straightforward to extend routine monitoring of dissolved oxygen (DO) to dynamic measures of aquatic ecosystem function (GPP & ER) and key physical processes such as gas exchange with the atmosphere (G). We review the current approaches for using DO data in environmental management with a focus on the United States, but briefly describe management frameworks in Europe and Canada. We highlight new applications of diel DO data and metabolism in regulatory settings and explore how they can be applied to managing and monitoring ecosystems. We then review existing data types and provide a short guide for implementing field measurements and modeling of ecosystem metabolic processes using currently available tools. Finally, we discuss research needed to overcome current conceptual limitations of applying metabolism in management settings. Despite challenges associated with modeling metabolism in rivers and lakes, rapid developments in this field have moved us closer to utilizing real-time estimates of GPP, ER and G to improve the assessment and management of environmental change.","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1521","usgsCitation":"Jankowski, K.J., Mejia, F.H., Blaszczak, J., and Holtgrieve, G.W., 2021, Aquatic ecosystem metabolism as a tool in environmental management: WIREs Water, v. 8, no. 4, e1521, 27 p., https://doi.org/10.1002/wat2.1521.","productDescription":"e1521, 27 p.","ipdsId":"IP-122380","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":387577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820304,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mejia, Francine H. 0000-0003-4447-231X","orcid":"https://orcid.org/0000-0003-4447-231X","contributorId":214345,"corporation":false,"usgs":true,"family":"Mejia","given":"Francine","email":"","middleInitial":"H.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":820305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blaszczak, Joanna 0000-0001-5122-0829","orcid":"https://orcid.org/0000-0001-5122-0829","contributorId":225159,"corporation":false,"usgs":false,"family":"Blaszczak","given":"Joanna","email":"","affiliations":[{"id":41055,"text":"Natural Resources and Environmental Science, University of Nevada, Reno, NV 89557, USA","active":true,"usgs":false}],"preferred":false,"id":820306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holtgrieve, Gordon W. 0000-0002-4451-3567","orcid":"https://orcid.org/0000-0002-4451-3567","contributorId":213257,"corporation":false,"usgs":false,"family":"Holtgrieve","given":"Gordon","email":"","middleInitial":"W.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":820307,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222492,"text":"70222492 - 2021 - Extreme precipitation across adjacent burned and unburned watersheds reveals impacts of low severity wildfire on debris-flow processes","interactions":[],"lastModifiedDate":"2021-07-30T14:27:52.067847","indexId":"70222492","displayToPublicDate":"2021-03-28T07:54:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6483,"text":"Journal of Geophysical Research-Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Extreme precipitation across adjacent burned and unburned watersheds reveals impacts of low severity wildfire on debris-flow processes","docAbstract":"

In steep landscapes, wildfire-induced changes to soil and vegetation can lead to extreme and hazardous geomorphic responses, including debris flows. The wildfire-induced mechanisms that lead to heightened geomorphic responses, however, depend on many site-specific factors including regional climate, vegetation, soil texture, and soil burn severity. As climate and land use change drive changes in fire regime, there is an increasing need to understand how fire alters geomorphic responses, particularly in areas where fire has been historically infrequent. Here, we examine differences in the initiation, magnitude, and particle-size distribution of debris flows that initiated within the area burned by the 2019 Woodbury Fire in central Arizona, USA, and those that initiated in a nearby unburned area. Despite similar rainfall intensities, unburned watersheds were less likely to produce debris flows. Debris flows in unburned areas initiated from both runoff and shallow landslides, while debris flows only initiated from runoff-related processes in the burned area. The grain-size distribution making up the matrix of debris-flow deposits within the burned area generally had a lower ratio of sand to silt relative to debris flows that initiated in the unburned area, though there were no systematic differences in the coarse fraction of debris-flow sediment between burned and unburned areas. Results help expand our ability to predict postwildfire debris-flow activity in a wider range of settings, specifically the Sonoran Desert ecoregion, and provide general insight into the impact of wildfire on geomorphic processes in steep terrain.

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The subarctic Pacific Ocean and Bering Sea comprise the second-largest high nitrate, low chlorophyll region in the world, where primary production is limited by the availability of iron (Fe). To estimate the potential impact of different terrestrial aerosol Fe sources on marine ecosystems, we performed a suite of laboratory assessments following established protocols, including: (1) leaching with Milli-Q water, (2) sequential extractions, (3) complete acid digestions, (4) X-ray diffraction, and (5) grain size analysis. Measurements were performed on 20 fine-grained (<5 μm) glacier-derived sediments from Alaska and the Yukon, two fresh, never-wetted volcanic ashes (Redoubt 2009 and Pavlof 2016), and six weathered ashes (Redoubt and Augustine) which span the past ~8,700 years. We compared results to published data on Asian desert-derived sediments, finding that the glacier-derived sediments have five times higher easily reducible Fe (median 2.3 ± 0.6 wt.%) than desert-derived samples (0.49 ± 0.1 wt.%) and fourteen times higher easily reducible Fe than fresh ash (0.16 ± 0.1 wt.%). In addition, fractional Fe solubility was higher in glacial sediment (median cumulative 0.31 ± 0.11% FeS) than volcanic ash (0.04 ± 0.02% FeS). Glacial sediments contained higher concentrations of other bioactive metals including Co, Ni, Cu, Zn, Mo, Cd, and Pb. Results suggest that glacier-derived dust may provide the subarctic Pacific with more bioavailable iron per unit mass than either volcanic ash or Asian desert-derived dust.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GB006821","usgsCitation":"Koffman, B., Yoder, M.F., Methven, T., Hanschka, L., Sears, H.B., Saylor, P.L., and Wallace, K.L., 2021, Glacial dust surpasses both volcanic ash and desert dust in its iron fertilization potential: Global Biogeochemical Cycles, v. 35, no. 4, e2020GB006821, 29 p., https://doi.org/10.1029/2020GB006821.","productDescription":"e2020GB006821, 29 p.","ipdsId":"IP-123039","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463334,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -141.37301895851397,\n 64.07015039411576\n ],\n [\n -162.65841833672906,\n 64.07015039411576\n ],\n [\n -162.65841833672906,\n 54.60514707536916\n ],\n [\n -152.20807617114912,\n 57.01723754847467\n ],\n [\n -141.75773400556918,\n 59.429328021580176\n ],\n [\n -141.37301895851397,\n 64.07015039411576\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"35","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Koffman, Bess G.","contributorId":345626,"corporation":false,"usgs":false,"family":"Koffman","given":"Bess G.","affiliations":[{"id":82662,"text":"1Department of Geology, Colby College, Waterville, ME 04901","active":true,"usgs":false}],"preferred":false,"id":917136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yoder, Meg F.","contributorId":345627,"corporation":false,"usgs":false,"family":"Yoder","given":"Meg","email":"","middleInitial":"F.","affiliations":[{"id":82663,"text":"Department of Geology, Colby College, Waterville, ME 04901","active":true,"usgs":false}],"preferred":false,"id":917137,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Methven, Taylor","contributorId":345628,"corporation":false,"usgs":false,"family":"Methven","given":"Taylor","email":"","affiliations":[{"id":82663,"text":"Department of Geology, Colby College, Waterville, ME 04901","active":true,"usgs":false}],"preferred":false,"id":917138,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanschka, Lena","contributorId":345629,"corporation":false,"usgs":false,"family":"Hanschka","given":"Lena","email":"","affiliations":[{"id":82663,"text":"Department of Geology, Colby College, Waterville, ME 04901","active":true,"usgs":false}],"preferred":false,"id":917139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sears, Helen B.","contributorId":345630,"corporation":false,"usgs":false,"family":"Sears","given":"Helen","email":"","middleInitial":"B.","affiliations":[{"id":82663,"text":"Department of Geology, Colby College, Waterville, ME 04901","active":true,"usgs":false}],"preferred":false,"id":917140,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Saylor, Patrick L.","contributorId":345631,"corporation":false,"usgs":false,"family":"Saylor","given":"Patrick","email":"","middleInitial":"L.","affiliations":[{"id":82664,"text":"Cold Regions Research and Engineering Laboratory, Hanover, NH 03755, and Earth Science Department, Dartmouth College, Hanover, NH 03755","active":true,"usgs":false}],"preferred":false,"id":917141,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917142,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219151,"text":"ofr20211004 - 2021 - Field methods, quality-assurance, and data management plan for water-quality activities and water-level measurements, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2021-03-26T22:38:36.027139","indexId":"ofr20211004","displayToPublicDate":"2021-03-26T09:07:01","publicationYear":"2021","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":"2021-1004","displayTitle":"Field Methods, Quality-Assurance, and Data Management Plan for Water-Quality Activities and Water-Level Measurements, Idaho National Laboratory, Idaho","title":"Field methods, quality-assurance, and data management plan for water-quality activities and water-level measurements, Idaho National Laboratory, Idaho","docAbstract":"

Introduction

Water-quality activities and water-level measurements conducted by the U.S. Geological Survey (USGS) Idaho National Laboratory (INL) Project Office coincide with the USGS mission of appraising the quantity and quality of the Nation’s water resources. The activities are conducted in cooperation with the U.S. Department of Energy’s (DOE) Idaho Operations Office. Results of water-quality and hydraulic head investigations are presented in various USGS publications or in refereed scientific journals, and the data are stored in the National Water Information System (NWIS) database. The results of the studies are used by researchers, regulatory and managerial agencies, and civic groups.

In its broadest sense, “quality assurance” refers to doing the job right the first time. It includes the functions of planning for products, review and acceptance of the products, and an audit designed to evaluate the system that produces the products. Quality control and quality assurance differ in that quality control ensures that things are done correctly given the “state-of-the-art” technology, and quality assurance ensures that quality control is maintained within specified limits.

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\"}}]}","contact":"

Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520

","tableOfContents":"","publishedDate":"2021-03-26","noUsgsAuthors":false,"publicationDate":"2021-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maimer, Neil V. 0000-0003-3047-3282 nmaimer@usgs.gov","orcid":"https://orcid.org/0000-0003-3047-3282","contributorId":5659,"corporation":false,"usgs":true,"family":"Maimer","given":"Neil","email":"nmaimer@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wehnke, Amy J. 0000-0003-1237-052X ajwehnke@usgs.gov","orcid":"https://orcid.org/0000-0003-1237-052X","contributorId":5660,"corporation":false,"usgs":true,"family":"Wehnke","given":"Amy","email":"ajwehnke@usgs.gov","middleInitial":"J.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812979,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Helmuth, Samuel L. 0000-0002-2880-7290","orcid":"https://orcid.org/0000-0002-2880-7290","contributorId":256657,"corporation":false,"usgs":false,"family":"Helmuth","given":"Samuel L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":812980,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}