{"pageNumber":"479","pageRowStart":"11950","pageSize":"25","recordCount":165415,"records":[{"id":70222466,"text":"70222466 - 2021 - Field evaluation of an improved solid TFM formulation for use in treating small tributary streams","interactions":[],"lastModifiedDate":"2021-07-30T14:22:37.638537","indexId":"70222466","displayToPublicDate":"2021-05-31T09:21:11","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"Field Evaluation of an Improved Solid TFM Formulation for Use in Treating Small Tributary Streams","title":"Field evaluation of an improved solid TFM formulation for use in treating small tributary streams","docAbstract":"A solid lampricide formulation containing 23% 3-trifluoromethyl-4-nitrophenol (TFM) as the active ingredient was developed in the mid-1980s for use in small tributaries of dendritic streams during routine treatments to kill larval sea lamprey. This TFM bar formulation was designed to use a matrix of commercially prepared surfactants that would dissolve and slowly release their TFM payload over an 8–10-hour period. Although this formulation has proven useful, several matrix surfactants have been discontinued, resulting in the need to reformulate the TFM bar multiple times. Maintaining acceptable performance of the TFM bars while reformulating has been challenging. As a result, an experimental surfactant-free tableted TFM formulation was developed as a potential TFM bar replacement. Release of TFM from the tablet formulation was evaluated in four independent experimental applications made over varied substrates in three small tributaries of the Ford River (Delta County, Michigan). For each tributary, TFM release from tablets was modeled using exponential decay curves and the time required to release 25, 50, 75 and 90% of the TFM tablets was calculated. Differences in water-quality properties were detected using one-way analysis of variance tests, and post-hoc Tukey Honest Significant Difference tests were used to determine which water-quality properties differed among the trials. The influences of water temperature and water velocity on the release of TFM from the tablets has been previously reported; however, in this study substrate type also appeared to be an indicator of TFM release. In this study the performance of the TFM tablets appeared acceptable; however, it may be beneficial to conduct additional investigations to determine storage stability and handling durability as well as to identify potential challenges with mass production.","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Luoma, J.A., Robertson, N., Schueller, J., Schloesser, N., Johnson, T., Severson, T.J., Meulemans, M.J., and Muelemans, E., 2021, Field evaluation of an improved solid TFM formulation for use in treating small tributary streams, 21 p.","productDescription":"21 p.","ipdsId":"IP-127807","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":387600,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387559,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/pubs/pdfs/research/reports/2020_LUO_760150.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Luoma, James A. 0000-0003-3556-0190 jluoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3556-0190","contributorId":4449,"corporation":false,"usgs":true,"family":"Luoma","given":"James","email":"jluoma@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Nicholas","contributorId":237024,"corporation":false,"usgs":false,"family":"Robertson","given":"Nicholas","email":"","affiliations":[{"id":18886,"text":"Northland College","active":true,"usgs":false}],"preferred":false,"id":820121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schueller, Justin R. 0000-0002-7102-3889","orcid":"https://orcid.org/0000-0002-7102-3889","contributorId":213527,"corporation":false,"usgs":true,"family":"Schueller","given":"Justin","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schloesser, Nicholas 0000-0002-3815-5302","orcid":"https://orcid.org/0000-0002-3815-5302","contributorId":237025,"corporation":false,"usgs":true,"family":"Schloesser","given":"Nicholas","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Todd 0000-0003-2152-8528","orcid":"https://orcid.org/0000-0003-2152-8528","contributorId":261519,"corporation":false,"usgs":true,"family":"Johnson","given":"Todd","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Severson, Todd J. 0000-0001-5282-3779 tseverson@usgs.gov","orcid":"https://orcid.org/0000-0001-5282-3779","contributorId":4749,"corporation":false,"usgs":true,"family":"Severson","given":"Todd","email":"tseverson@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meulemans, Matthew 0000-0003-4584-8737","orcid":"https://orcid.org/0000-0003-4584-8737","contributorId":261521,"corporation":false,"usgs":true,"family":"Meulemans","given":"Matthew","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820126,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Muelemans, Erica","contributorId":261523,"corporation":false,"usgs":false,"family":"Muelemans","given":"Erica","email":"","affiliations":[{"id":52865,"text":"Northland College, Ashland, WI","active":true,"usgs":false}],"preferred":false,"id":820127,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223180,"text":"70223180 - 2021 - Alaska landbird montoring survey: Alaska regional protocol framework for monitoring landbirds using point counts","interactions":[],"lastModifiedDate":"2021-08-17T14:13:12.185743","indexId":"70223180","displayToPublicDate":"2021-05-31T09:03:14","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5856,"text":"Regional Protocol Framework","active":true,"publicationSubtype":{"id":1}},"title":"Alaska landbird montoring survey: Alaska regional protocol framework for monitoring landbirds using point counts","docAbstract":"

Alaska provides habitat for 143 species of landbirds that occur regularly in the state, about half of which breed predominantly north of the border between the contiguous United States and Canada. The road-based North American Breeding Bird Survey (BBS) provides some data on population trends in Alaska, but most northern populations are inadequately monitored by this program because of a paucity of roads. To remedy this deficiency, Boreal Partners in Flight developed the Alaska Landbird Monitoring Survey (ALMS) to monitor breeding populations of landbirds in off-road areas of Alaska in tandem with data collected from the roadside BBS. The primary objective of ALMS is to monitor long-term population trends of landbirds and other species that can be monitored by diurnal point counts during the breeding season, including many shorebirds and aquatic birds. A secondary objective is to estimate landbird densities by habitat, which can be used to model avian distribution and abundance across Alaska. ALMS is a collaborative program whereby agencies and other entities conduct standardized surveys of breeding birds and their habitats on the lands they manage and then contribute the data to the U.S. Geological Survey Alaska Science Center for storage and analysis.

The short-term implementation goal of ALMS is to monitor birds systematically within each of 100 randomly selected survey blocks, thereby matching the number of BBS surveys conducted in each of Alaska's five Bird Conservation Regions (BCRs). Each block has a mini-grid of 15−25 points that are surveyed biennially, with half of the blocks surveyed in alternating years. Survey blocks are stratified by accessibility and cost-effectiveness. Refuges may opt to limit sites to those accessible by foot, vehicle, boat, or fixed-wing aircraft, as these can be surveyed more inexpensively and reliably over time. Observers survey each point within a survey block for birds using a 10-min point count once per summer on a biennial basis. They collect corresponding habitat data during the first visit and at subsequent 10-year intervals or whenever a disturbance (e.g., fire, wind) has caused a significant change. USGS analyzes ALMS data jointly with BBS data to test for differences between off-road and roadside areas and to increase power to detect statewide trends. Additional blocks can be surveyed in areas that are more difficult and expensive to access as resources become available in the future. Long-term monitoring enables detection of change in bird populations in relation to fire, disease and insect damage, resource development, climate-related change, and other landscape-level disturbances across Alaska. Results from ALMS can also help prioritize conservation and research towards species before they become endangered and require expensive recovery programs.

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N.","contributorId":173930,"corporation":false,"usgs":false,"family":"Cady","given":"Melissa","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":821283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Granfors, Diane A.","contributorId":174567,"corporation":false,"usgs":false,"family":"Granfors","given":"Diane","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":821284,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70224592,"text":"70224592 - 2021 - Using tree-rings to unravel avalanche frequency and associated climate drivers in the northern Rocky Mountains","interactions":[],"lastModifiedDate":"2021-09-29T14:02:49.719415","indexId":"70224592","displayToPublicDate":"2021-05-31T08:59:53","publicationYear":"2021","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":9362,"text":"Earth Science Matters 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No abstract available.

","largerWorkTitle":"Earth Science Matters","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Peitzsch, E.H., 2021, Using tree-rings to unravel avalanche frequency and associated climate drivers in the northern Rocky Mountains: Earth Science Matters Newsletter, v. 12, no. Spring, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-129404","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":389954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":389938,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/center-news/using-tree-rings-unravel-avalanche-frequency-and-associated-climate-drivers-northern?qt-news_science_products=3#qt-news_science_products"}],"country":"United States","state":"Montana","otherGeospatial":"northern Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.86181640625001,\n 46.927758623434435\n ],\n [\n -111.99462890625,\n 46.927758623434435\n ],\n [\n -111.99462890625,\n 48.980216985374994\n ],\n [\n -115.86181640625001,\n 48.980216985374994\n ],\n [\n -115.86181640625001,\n 46.927758623434435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"Spring","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peitzsch, Erich H. 0000-0001-7624-0455","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":202576,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":824230,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70221725,"text":"70221725 - 2021 - Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide","interactions":[],"lastModifiedDate":"2021-12-10T16:36:17.553183","indexId":"70221725","displayToPublicDate":"2021-05-31T07:50:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide","docAbstract":"

Despite its successes, the U.S. Endangered Species Act (ESA) has proven challenging to implement due to funding limitations, workload backlog, and other problems. As threats to species survival intensify and as more species come under threat, the need for the ESA and similar conservation laws and policies in other countries to function efficiently has grown. Attempts by the U.S. Fish and Wildlife Service (USFWS) to streamline ESA decisions include multispecies recovery plans and habitat conservation plans. We address species status assessment (SSA), a USFWS process to inform ESA decisions from listing to recovery, within the context of multispecies and ecosystem planning. Although existing SSAs have a single-species focus, ecosystem-based research can efficiently inform multiple SSAs within a region and provide a foundation for transition to multispecies SSAs in the future. We considered at-risk grassland species and ecosystems within the southeastern United States, where a disproportionate number of rare and endemic species are associated with grasslands. To initiate our ecosystem-based approach, we used a combined literature-based and structured World Café workshop format to identify science needs for SSAs. Discussions concentrated on 5 categories of threats to grassland species and ecosystems, consistent with recommendations to make shared threats a focus of planning under the ESA: (1) habitat loss, fragmentation, and disruption of functional connectivity; (2) climate change; (3) altered disturbance regimes; (4) invasive species; and (5) localized impacts. For each threat, workshop participants identified science and information needs, including database availability, research priorities, and modeling and mapping needs. Grouping species by habitat and shared threats can make the SSA process and other planning processes for conservation of at-risk species worldwide more efficient and useful. We found a combination of literature review and structured discussion effective for identifying the scientific information and analysis needed to support the development of multiple SSAs.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.13777","usgsCitation":"Noss, R., Cartwright, J.M., Estes, D., Witsell, T., Elliott, G., Adams, D.S., Albrecht, M.A., Boyles, R., Comer, P., Doffitt, C., Hill, J.G., Hunter, W.C., Knapp, W.M., Marshall, M., Singhurst, J.R., Tracey, C., Walck, J.L., and Weakley, A., 2021, Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide: Conservation Biology, v. 35, no. 6, p. 1715-1724, https://doi.org/10.1111/cobi.13777.","productDescription":"10 p.","startPage":"1715","endPage":"1724","ipdsId":"IP-122143","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":452069,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/cobi.13777","text":"External 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Center","active":true,"usgs":true}],"preferred":true,"id":818520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Estes, Dwayne","contributorId":260711,"corporation":false,"usgs":false,"family":"Estes","given":"Dwayne","affiliations":[{"id":52648,"text":"Southeastern Grasslands Initiative","active":true,"usgs":false}],"preferred":false,"id":818521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witsell, Theo","contributorId":258187,"corporation":false,"usgs":false,"family":"Witsell","given":"Theo","email":"","affiliations":[],"preferred":false,"id":818522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elliott, Gregg","contributorId":260712,"corporation":false,"usgs":false,"family":"Elliott","given":"Gregg","email":"","affiliations":[{"id":52648,"text":"Southeastern Grasslands Initiative","active":true,"usgs":false}],"preferred":false,"id":818523,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Daniel S. 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R.","contributorId":258196,"corporation":false,"usgs":false,"family":"Singhurst","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":818533,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tracey, Christopher","contributorId":260714,"corporation":false,"usgs":false,"family":"Tracey","given":"Christopher","affiliations":[{"id":52650,"text":"Pennsylvania Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":818534,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Walck, Jeffrey L. 0000-0002-8518-9900","orcid":"https://orcid.org/0000-0002-8518-9900","contributorId":258197,"corporation":false,"usgs":false,"family":"Walck","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":818535,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Weakley, Alan 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We report a new calibration model for manganese using the laser-induced breakdown spectroscopy instrument that is part of the ChemCam instrument suite onboard the NASA Curiosity rover. The model has been trained using an expanded set of 523 manganese-bearing rock, mineral, metal ore, and synthetic standards. The optimal calibration model uses the Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO) multivariate techniques, with a novel “double blending” technique. We determined the detection limit for manganese is 82 ppm using a method blank procedure and is possibly as low as 27 ppm based on visual inspection of the spectra. Based on a representative test set consisting of measurements on 93 standards, the double blended multivariate model shows a Root Mean Squared Error of Prediction (RMSEP) accuracy of 1.39 wt% MnO for the full blended model. Employing a local RMSEP estimate where the model performance is evaluated based on nearby test samples, the accuracy is 0.03 wt% at the quantification limit (0.05 wt% MnO), 0.4 wt% accuracy at 1.0 wt% MnO, and 4.4 wt% accuracy at 100 wt% MnO. Precision is estimated using the standard deviation of the test set measurements, and is ±0.01 wt% MnO at the quantification limit, ±0.09 wt% MnO at 1.0 wt% MnO, and ± 2.1 wt% MnO at 100 wt% MnO (all 1 standard deviation). This new calibration is important for understanding the variation of manganese in the bedrock with the Curiosity rover on Mars, which provides insight into past redox conditions on Mars.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.sab.2021.106223","usgsCitation":"Gasda, P.J., Anderson, R.B., Cousin, A., Forni, O., Clegg, S.M., Ollila, A., Lanza, N.L., Lamm, S., Wiens, R.C., Maurice, S., Gasnault, O., Beal, R., Reyes-Newell, A., and Delapp, D., 2021, Quantification of manganese for ChemCam Mars and laboratory spectra using a multivariate model: Spectrochimica Acta B, v. 181, 106223, https://doi.org/10.1016/j.sab.2021.106223.","productDescription":"106223","ipdsId":"IP-127445","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":452071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hal.science/hal-03449982","text":"Publisher Index Page"},{"id":410785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"181","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gasda, Patrick J.","contributorId":196313,"corporation":false,"usgs":false,"family":"Gasda","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":859645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Ryan B. 0000-0003-4465-2871 rbanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-4465-2871","contributorId":170054,"corporation":false,"usgs":true,"family":"Anderson","given":"Ryan","email":"rbanderson@usgs.gov","middleInitial":"B.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":859646,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cousin, A.","contributorId":290035,"corporation":false,"usgs":false,"family":"Cousin","given":"A.","affiliations":[{"id":62314,"text":"Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":859647,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forni, O.","contributorId":290037,"corporation":false,"usgs":false,"family":"Forni","given":"O.","affiliations":[{"id":62314,"text":"Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":859648,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clegg, S. M.","contributorId":300207,"corporation":false,"usgs":false,"family":"Clegg","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":27196,"text":"LANL","active":true,"usgs":false}],"preferred":false,"id":859649,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ollila, A.","contributorId":290050,"corporation":false,"usgs":false,"family":"Ollila","given":"A.","affiliations":[{"id":62306,"text":"Space and Planetary Exploration Team, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":859650,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lanza, Nina L.","contributorId":140299,"corporation":false,"usgs":false,"family":"Lanza","given":"Nina","email":"","middleInitial":"L.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":859651,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lamm, S","contributorId":300208,"corporation":false,"usgs":false,"family":"Lamm","given":"S","email":"","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":859652,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wiens, Roger C.","contributorId":140330,"corporation":false,"usgs":false,"family":"Wiens","given":"Roger","email":"","middleInitial":"C.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":859653,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Maurice, Sylvestre","contributorId":82626,"corporation":false,"usgs":false,"family":"Maurice","given":"Sylvestre","email":"","affiliations":[],"preferred":false,"id":859654,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gasnault, Olivier","contributorId":181501,"corporation":false,"usgs":false,"family":"Gasnault","given":"Olivier","email":"","affiliations":[],"preferred":false,"id":859655,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Beal, R.","contributorId":290059,"corporation":false,"usgs":false,"family":"Beal","given":"R.","email":"","affiliations":[{"id":62306,"text":"Space and Planetary Exploration Team, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":859656,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Reyes-Newell, A.","contributorId":290113,"corporation":false,"usgs":false,"family":"Reyes-Newell","given":"A.","affiliations":[{"id":62306,"text":"Space and Planetary Exploration Team, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":859657,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Delapp, D.","contributorId":290074,"corporation":false,"usgs":false,"family":"Delapp","given":"D.","affiliations":[{"id":62306,"text":"Space and Planetary Exploration Team, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":859658,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70226461,"text":"70226461 - 2021 - Reptile and amphibian diversity and abundance in an urban landscape: Impacts of fragmentation and the conservation value of small patches","interactions":[],"lastModifiedDate":"2021-11-18T12:42:28.253092","indexId":"70226461","displayToPublicDate":"2021-05-31T06:40:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9341,"text":"Ichthyology & Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Reptile and amphibian diversity and abundance in an urban landscape: Impacts of fragmentation and the conservation value of small patches","docAbstract":"

Urbanization is a major contributor to habitat loss and fragmentation and is considered a global threat to biodiversity. We studied reptile and amphibian species diversity and abundance in a highly fragmented landscape adjacent to the second largest metropolitan area in the United States. Habitat patches in our study area were made up of remnant native vegetation surrounded by roads, housing, and other urban development. Species richness and diversity were positively associated with patch size, but patch age was not significantly associated with community characteristics. Four relatively common species were not detected in the small patches, indicating the possibility they had been extirpated by the time monitoring began, and six rarer species were not detected or detected only once in these patches. Although the patch size effect on species diversity was strong, we found that several of the small habitat patches had similar diversity to large patches, indicating potential value of these small habitat patches in protecting species as “microreserves.” In addition, one lizard species was found to be significantly more abundant in the smaller patches. To determine if abundance changed over time, we compared capture rates for four common lizards at the same sites ten years later. For three of the four species, abundance decreased over that period, specifically in the small patches. Although our long-term monitoring has confirmed that the full suite of herpetofauna is currently preserved in the study area overall, declines even in the common species over time hint at the potential severity of the threat of urbanization to rare species.

","language":"English","publisher":"The American Society of Ichthyologists and Herpetologists","doi":"10.1643/h2019261","usgsCitation":"Delaney, K., Busteed, G., Fisher, R., and Riley, S.P., 2021, Reptile and amphibian diversity and abundance in an urban landscape: Impacts of fragmentation and the conservation value of small patches: Ichthyology & Herpetology, v. 109, no. 2, p. 424-435, https://doi.org/10.1643/h2019261.","productDescription":"12 p.","startPage":"424","endPage":"435","ipdsId":"IP-119087","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":391853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.970947265625,\n 33.65120829920497\n ],\n [\n -117.44384765625,\n 33.65120829920497\n ],\n [\n -117.44384765625,\n 34.279914398549934\n ],\n [\n -118.970947265625,\n 34.279914398549934\n ],\n [\n -118.970947265625,\n 33.65120829920497\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"109","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Delaney, Kathleen Semple","contributorId":269389,"corporation":false,"usgs":false,"family":"Delaney","given":"Kathleen Semple","affiliations":[{"id":55965,"text":"NPS - Santa Monica Mountains National Recreation Area","active":true,"usgs":false}],"preferred":false,"id":826994,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Busteed, Gary","contributorId":269390,"corporation":false,"usgs":false,"family":"Busteed","given":"Gary","email":"","affiliations":[{"id":55965,"text":"NPS - Santa Monica Mountains National Recreation Area","active":true,"usgs":false}],"preferred":false,"id":826995,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":826996,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Riley, Seth P.D.","contributorId":145429,"corporation":false,"usgs":false,"family":"Riley","given":"Seth","middleInitial":"P.D.","affiliations":[{"id":7237,"text":"NPS, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":826997,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221053,"text":"70221053 - 2021 - Perfluoroalkyl substances in plasma of smallmouth bass from the Chesapeake Bay Watershed","interactions":[],"lastModifiedDate":"2021-07-02T13:32:14.906126","indexId":"70221053","displayToPublicDate":"2021-05-30T06:57:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2041,"text":"International Journal of Environmental Research and Public Health","active":true,"publicationSubtype":{"id":10}},"title":"Perfluoroalkyl substances in plasma of smallmouth bass from the Chesapeake Bay Watershed","docAbstract":"

Smallmouth bass Micropterus dolomieu is an economically important sportfish and within the Chesapeake Bay watershed has experienced a high prevalence of external lesions, infectious disease, mortality events, reproductive endocrine disruption and population declines. To date, no clear or consistent associations with contaminants measured in fish tissue or surface water have been found. Therefore, plasma samples from two sites in the Potomac River and two in the Susquehanna River drainage basins, differing in land-use characteristics, were utilized to determine if perfluoroalkyl substances were present. Four compounds, perfluorooctane sulphonic acid (PFOS), perfluoroundecanoic acid (PFUnA), perfluorodecanoic acid (PFDA) and perfluorododecanoic acid (PFDoA), were detected in every fish. Two additional compounds, perfluorooctane sulphonamide (PFOSA) and perfluorononanoic acid (PFNA), were less commonly detected at lower concentrations, depending on the site. Concentrations of PFOS (up to 574 ng/mL) were the highest detected and varied significantly among sites. No seasonal differences (spring versus fall) in plasma concentrations were observed. Concentrations of PFOS were not significantly different between the sexes. However, PFUnA and PFDoA concentrations were higher in males than females. Both agricultural and developed land-use appeared to be associated with exposure. Further research is needed to determine if these compounds could be affecting the health of smallmouth bass and identify sources.

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],\n [\n -76.190185546875,\n 36.66841891894786\n ],\n [\n -76.0693359375,\n 36.65079252503471\n ],\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.948486328125,\n 36.76529191711624\n ],\n [\n -75.904541015625,\n 37.01132594307015\n ],\n [\n -75.926513671875,\n 37.17782559332976\n ],\n [\n -75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"18","noUsgsAuthors":false,"publicationDate":"2021-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":816653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":816654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":816655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Cheyenne R. 0000-0002-7226-1774","orcid":"https://orcid.org/0000-0002-7226-1774","contributorId":219236,"corporation":false,"usgs":true,"family":"Smith","given":"Cheyenne","email":"","middleInitial":"R.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":true,"id":816656,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220904,"text":"70220904 - 2021 - Surface flow velocities from space: Particle image velocimetry of satellite video of a large, sediment-laden river","interactions":[],"lastModifiedDate":"2021-05-28T18:41:13.32766","indexId":"70220904","displayToPublicDate":"2021-05-28T13:36:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7170,"text":"Frontiers in Water","active":true,"publicationSubtype":{"id":10}},"title":"Surface flow velocities from space: Particle image velocimetry of satellite video of a large, sediment-laden river","docAbstract":"

Conventional, field-based streamflow monitoring in remote, inaccessible locations such as Alaska poses logistical challenges. Safety concerns, financial considerations, and a desire to expand water-observing networks make remote sensing an appealing alternative means of collecting hydrologic data. In an ongoing effort to develop non-contact methods for measuring river discharge, we evaluated the potential to estimate surface flow velocities from satellite video of a large, sediment-laden river in Alaska via particle image velocimetry (PIV). In this setting, naturally occurring sediment boil vortices produced distinct water surface features that could be tracked from frame to frame as they were advected by the flow, obviating the need to introduce artificial tracer particles. In this study, we refined an end-to-end workflow that involved stabilization and geo-referencing, image preprocessing, PIV analysis with an ensemble correlation algorithm, and post-processing of PIV output to filter outliers and scale and geo-reference velocity vectors. Applying these procedures to image sequences extracted from satellite video allowed us to produce high resolution surface velocity fields; field measurements of depth-averaged flow velocity were used to assess accuracy. Our results confirmed the importance of preprocessing images to enhance contrast and indicated that lower frame rates (e.g., 0.25 Hz) lead to more reliable velocity estimates because longer capture intervals allow more time for water surface features to translate several pixels between frames, given the relatively coarse spatial resolution of the satellite data. Although agreement between PIV-derived velocity estimates and field measurements was weak (R2 = 0.39) on a point-by-point basis, correspondence improved when the PIV output was aggregated to the cross-sectional scale. For example, the correspondence between cross-sectional maximum velocities inferred via remote sensing and measured in the field was much stronger (R2 = 0.76), suggesting that satellite video could play a role in measuring river discharge. Examining correlation matrices produced as an intermediate output of the PIV algorithm yielded insight on the interactions between image frame rate and sensor spatial resolution, which must be considered in tandem. Although further research and technological development are needed, measuring surface flow velocities from satellite video could become a viable tool for streamflow monitoring in certain fluvial environments.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/frwa.2021.652213","usgsCitation":"Legleiter, C.J., and Kinzel, P.J., 2021, Surface flow velocities from space: Particle image velocimetry of satellite video of a large, sediment-laden river: Frontiers in Water, v. 3, 652213, 20 p., https://doi.org/10.3389/frwa.2021.652213.","productDescription":"652213, 20 p.","ipdsId":"IP-125455","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":452077,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frwa.2021.652213","text":"Publisher Index Page"},{"id":436332,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZY5LK1","text":"USGS data release","linkHelpText":"Satellite video and field measurements of flow velocity acquired from the Tanana River in Alaska and used for particle image velocimetry (PIV)"},{"id":386020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Nenana","otherGeospatial":"Tanana River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.21218872070312,\n 64.53486288126804\n ],\n [\n -148.92929077148438,\n 64.53486288126804\n ],\n [\n -148.92929077148438,\n 64.61387025268262\n ],\n [\n -149.21218872070312,\n 64.61387025268262\n ],\n [\n -149.21218872070312,\n 64.53486288126804\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2021-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":816651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":816652,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70220871,"text":"sir20205057 - 2021 - Flood-inundation maps for the Blue River near Red Bridge Road, Kansas City, Missouri, 2019","interactions":[],"lastModifiedDate":"2021-05-28T19:21:03.271116","indexId":"sir20205057","displayToPublicDate":"2021-05-28T11:11:37","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5057","displayTitle":"Flood-Inundation Maps for the Blue River near Red Bridge Road, Kansas City, Missouri, 2019","title":"Flood-inundation maps for the Blue River near Red Bridge Road, Kansas City, Missouri, 2019","docAbstract":"

Digital flood-inundation maps for a 4.6-mile reach of the Blue River near Red Bridge Road in Kansas City, Missouri, were created by the U.S. Geological Survey (USGS), in cooperation with the City of Kansas City, Missouri. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 06893195, Blue River at Red Bridge Road, Kansas City, Mo. Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or the Johnson County, Kansas, StormWatch Automated Local Elevation in Real Time Flood Warning System at https://www.stormwatch.com.

Flood profiles were computed for the Blue River reach by means of a one-dimensional model for simulating water-surface profiles with steady-state flow computations. The model was calibrated by using the current stage-streamflow relations at the upstream USGS streamgage 06893150, Blue River at Blue Ridge Boulevard Extension, Kansas City, Mo., and the downstream streamgage 06893500, Blue River at Kansas City, Mo.

The hydraulic model was then used to compute 37 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 11 ft, or near bankfull, to 47 ft at the reference streamgage 06893195. The upper stage for the map library exceeds the stage corresponding to the estimated 0.2-percent annual exceedance probability flood (500-year recurrence interval flood) in the model reach. The simulated water-surface profiles were then combined with a geographic information system digital elevation model with a maximum 10-centimeter vertical root mean square error and 4.0-ft horizontal resolution to delineate the area flooded at each water level.

The availability of these maps, along with real-time internet information regarding current stage from the USGS streamgage, will help guide emergency management personnel and residents in flood mitigation, preparedness and planning, flood-response activities such as evacuations and road closures, and any postflood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205057","collaboration":"Prepared in cooperation with the City of Kansas City, Missouri","usgsCitation":"Heimann, D.C., Voss, J.D., and Rydlund, P.H., Jr., 2021, Flood-inundation maps for the Blue River near Red Bridge Road, Kansas City, Missouri, 2019: U.S. Geological Survey Scientific Investigations Report 2020–5057, 14 p., https://doi.org/10.3133/sir20205057.","productDescription":"Report: vi, 14 p.; Data Release; Dataset","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-117597","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385983,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90MH291","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets for the flood-inundation study of the Blue River near Red Bridge Road, Kansas City, Missouri, 2019"},{"id":385984,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":385981,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5057/coverthb.jpg"},{"id":385982,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5057/sir20205057.pdf","text":"Report","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5057"}],"country":"United States","state":"Kansas, Missouri","otherGeospatial":"Blue River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.83333,\n 38.8333\n ],\n [\n -94.45,\n 38.8333\n ],\n [\n -94.45,\n 39.1666\n ],\n [\n -94.833333,\n 39.1666\n ],\n [\n -94.833333,\n 38.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-05-28","noUsgsAuthors":false,"publicationDate":"2021-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voss, Jonathon D. 0000-0001-8219-7887","orcid":"https://orcid.org/0000-0001-8219-7887","contributorId":224636,"corporation":false,"usgs":true,"family":"Voss","given":"Jonathon","email":"","middleInitial":"D.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rydlund, Paul H. Jr. 0000-0001-9461-9944 prydlund@usgs.gov","orcid":"https://orcid.org/0000-0001-9461-9944","contributorId":3840,"corporation":false,"usgs":true,"family":"Rydlund","given":"Paul","suffix":"Jr.","email":"prydlund@usgs.gov","middleInitial":"H.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":816512,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70220894,"text":"sir20215044 - 2021 - Characterization of historical and stochastically generated climate and streamflow conditions in the Souris River Basin, United States and Canada","interactions":[],"lastModifiedDate":"2021-05-28T19:05:24.819834","indexId":"sir20215044","displayToPublicDate":"2021-05-28T10:53:21","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5044","displayTitle":"Characterization of Historical and Stochastically Generated Climate and Streamflow Conditions in the Souris River Basin, United States and Canada","title":"Characterization of historical and stochastically generated climate and streamflow conditions in the Souris River Basin, United States and Canada","docAbstract":"

The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba in Canada and the State of North Dakota in the United States. Greater than average snowpack during the winter of 2010–11, along with record-setting rains in May and June 2011, resulted in historically unprecedented flooding in the Souris River Basin. The severity of the 2011 flood led the United States and Canada to request a review of the operating plan for any improvements of reservoir operations and flood control measures in the basin, and the Souris River Basin Task Force was formed. The International Souris River Study Board was then formed in 2017 to carry out the recommendations of the Souris River Basin Task Force laid out in a plan of study. To support the International Souris River Study Board, the U.S. Geological Survey (USGS), in cooperation with the North Dakota State Water Commission and the International Joint Commission, used the previously developed unregulated and regulated streamflow models and data for stochastic streamflow in the Souris River Basin to characterize climate and streamflow and support selection of streamflow traces based on their characterization. Components of the original stochastic hydrology models and their outputs were used in this phase of the study to (1) characterize historical and stochastic climate and streamflow for the Souris River Basin, (2) disaggregate monthly stochastic streamflow spatially and temporally to meet the needs of the U.S. Army Corps of Engineers, Hydrologic Engineering Center, Reservoir System Simulation model for the Souris River Basin, and (3) discuss selection of disaggregated streamflow traces (simulations) using the characteristics of climate and streamflow. A trace is a time series of a stochastic variable such as streamflow, potential evapotranspiration, or precipitation.

To characterize climate conditions, precipitation, potential evapotranspiration (PET), and moisture deficit for the Souris River Basin and individual points at Rafferty, Grant Devine, and Lake Darling Reservoirs were determined annually and seasonally. The annual basin (November 1–October 31) precipitation for the 50-percent nonexceedance probability is 452 millimeters (mm). Spring (March–May) is the wettest season, followed by summer (June–August), fall (September–November), and winter (December–February). Annual moisture deficit was largest at Lake Darling Reservoir, followed by Rafferty Reservoir, and then Grant Devine Reservoir.

Annual maximum monthly mean streamflow was determined for the Souris River below Rafferty Reservoir, Saskatchewan (Canadian streamgage 05NB036); Long Creek near Noonan (above Boundary Reservoir), North Dakota (USGS streamgage 05113600); Moose Mountain Creek near Oxbow, Saskatchewan (Canadian streamgage 05ND004); the Souris River near Sherwood, N. Dak. (USGS streamgage 05114000); the Des Lacs River at Foxholm, N. Dak. (USGS streamgage 05116500); and the Souris River above Minot, N. Dak. (USGS streamgage 05117500). When the seasonal maximum monthly mean streamflows are evaluated in contrast to annual maximum monthly mean streamflows separated by their seasonal occurrence, summer months of annual maximum monthly mean streamflows have a higher 50-percent exceedance probability of streamflow compared to annual maximum monthly mean streamflows that occur in spring, seasonal maximum monthly mean streamflows that occur in spring, and seasonal maximum monthly mean streamflows that occur in summer. When annual maximum monthly mean streamflows in summer are compared to annual maximum monthly mean streamflows in spring, they are consistently higher in streamflow but occur in less than 4.2 percent of years. Evaluation of whether the annual maximum monthly mean streamflows that occur in summer can be described as a separate population from annual maximum monthly mean streamflows that occur in spring was outside the scope of this study, and the summer and spring annual maximum monthly mean streamflows were not tested for statistical differences in mean or variance. Further investigation of seasonal weather patterns that induce flooding could lead to a better understanding of the seasonal differences in flooding.

Long-term hydrologic drought was characterized by evaluating multiyear mean streamflow. Shorter averaging periods have greater streamflow variability than longer periods and hence have a wider range of values. As the averaging period is extended to a longer period, the variability of mean streamflow decreases, and the more extreme streamflow volumes seen in shorter averaging periods cannot be sustained. Stochastic streamflow time series were disaggregated spatially and temporally for use in a HEC–ResSim model. The combination of monthly and daily stochastic streamflow data was used to select traces with qualities that could be used to test alternatives focused on water supply, summer flooding, and apportionment.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215044","collaboration":"Prepared in cooperation with the North Dakota State Water Commission and the International Joint Commission","usgsCitation":"Gregory, A., and Galloway, J.M., 2021, Characterization of historical and stochastically generated climate and streamflow conditions in the Souris River Basin, United States and Canada: U.S. Geological Survey Scientific Investigations Report 2021–5044, 36 p., https://doi.org/10.3133/sir20215044.","productDescription":"Report: viii, 36 p.; Data Release; Dataset","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-120682","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":386014,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":386011,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5044/coverthb.jpg"},{"id":386012,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5044/sir20215044.pdf","text":"Report","size":"5.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021—5044"},{"id":386013,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93AOWFL","text":"USGS data release","linkHelpText":"Historical and stochastically generated climate and streamflow data for the Souris River Basin, United States and Canada"}],"country":"Canada, United States","state":"Manitoba, North Dakota, Saskatchewan","otherGeospatial":"Souris River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.55859375,\n 46.6795944656402\n ],\n [\n -98.0859375,\n 50.12057809796008\n ],\n [\n -101.25,\n 51.67255514839674\n ],\n [\n -107.138671875,\n 53.48804553605622\n ],\n [\n -108.6328125,\n 50.958426723359935\n ],\n [\n -102.568359375,\n 48.22467264956519\n ],\n [\n -99.66796875,\n 46.98025235521883\n ],\n [\n -97.55859375,\n 46.6795944656402\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702

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","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-05-28","noUsgsAuthors":false,"publicationDate":"2021-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Gregory, Angela 0000-0002-9905-1240","orcid":"https://orcid.org/0000-0002-9905-1240","contributorId":45018,"corporation":false,"usgs":true,"family":"Gregory","given":"Angela","email":"","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816617,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226787,"text":"70226787 - 2021 - Dry formation of recent Martian slope features","interactions":[],"lastModifiedDate":"2021-12-13T13:27:42.656542","indexId":"70226787","displayToPublicDate":"2021-05-28T07:26:38","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"10","title":"Dry formation of recent Martian slope features","docAbstract":"

Martian surface conditions are cold and dry, unfavorable for liquid water, yet steep slopes display young and currently active features suggestive of wet processes. These include recurring slope lineae and slope streaks, gully landforms, and small lobate features. Wet origins for these features would imply surprising amounts of liquid water at the surface. However, detailed observations of the morphology and activity of these features have demonstrated that dry processes, some of them unique to the Martian environment, can account for all of them. This reconciles the contradiction between physics and geomorphology and provides a self-consistent model of a Martian surface that is very active today despite having negligible volumes of liquid water.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mars Geological Enigmas From the Late Noachian Epoch to the Present Day","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-820245-6.00010-0","usgsCitation":"Dundas, C., 2021, Dry formation of recent Martian slope features, chap. 10 of Mars Geological Enigmas From the Late Noachian Epoch to the Present Day, p. 263-288, https://doi.org/10.1016/B978-0-12-820245-6.00010-0.","productDescription":"26 p.","startPage":"263","endPage":"288","ipdsId":"IP-117640","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":392786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dundas, Colin M. 0000-0003-2343-7224","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":237028,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":828257,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70226594,"text":"70226594 - 2021 - Floral resource selection by wild bees and honey bees in the Midwest United States: Implications for designing pollinator habitat","interactions":[],"lastModifiedDate":"2021-12-01T13:21:30.054747","indexId":"70226594","displayToPublicDate":"2021-05-28T07:19:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Floral resource selection by wild bees and honey bees in the Midwest United States: Implications for designing pollinator habitat","docAbstract":"

Many seed mix recommendations for creating pollinator habitat are in part based on anecdotal evidence or field observations of bees visiting forbs (i.e. use). However, there is limited information on what forbs are preferred by bees, particularly in working landscapes where bee forage may be limited. We examined floral resource selection by wild bees and honey bees on grasslands in the Midwest using a 5-year dataset containing over 8,000 plant-bee interactions. We observed wild bees visiting 83 forb species, but only 14 species were significantly selected (i.e. bees visited a plant more than expected based on availability). Approximately 70% of all wild bee visitations were on native flowers, whereas only 20% of all honey bee visitations were on natives. Honey bees visited 70 forb species, but only four forbs were significantly selected. The selection ratio for each forb species was not correlated with proportion of use by wild bees or honey bees, suggesting that bee visitation data alone do not elucidate patterns of forb selection or avoidance. We then compared our resource selection results to forbs recommended by U.S. Department of Agriculture (USDA) for regional pollinator habitat plantings. Many forbs that were selected by bees in our study were also recommended by USDA; however, some USDA-recommended forbs were selected against by bees. A greater understanding of which floral resources are selected by bees can assist land managers in assessing conservation seed mixes and ultimately provide diverse, season-long pollinator forage in working landscapes.

","language":"English","publisher":"Wiley","doi":"10.1111/rec.13456","usgsCitation":"Simanonok, S.C., Otto, C., and Buhl, D.A., 2021, Floral resource selection by wild bees and honey bees in the Midwest United States: Implications for designing pollinator habitat: Restoration Ecology, v. 29, no. 8, e13456, 11 p., https://doi.org/10.1111/rec.13456.","productDescription":"e13456, 11 p.","ipdsId":"IP-121320","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":392299,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, North Dakota, South 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\"}}]}","volume":"29","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-07-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Simanonok, Stacy C. 0000-0002-0287-3871","orcid":"https://orcid.org/0000-0002-0287-3871","contributorId":229607,"corporation":false,"usgs":true,"family":"Simanonok","given":"Stacy","email":"","middleInitial":"C.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":827430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":827431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buhl, Deborah A. 0000-0002-8563-5990 dbuhl@usgs.gov","orcid":"https://orcid.org/0000-0002-8563-5990","contributorId":146226,"corporation":false,"usgs":true,"family":"Buhl","given":"Deborah","email":"dbuhl@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":827432,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221162,"text":"70221162 - 2021 - Amplified impact of climate change on fine-sediment delivery to a subsiding coast, Humboldt Bay, California","interactions":[],"lastModifiedDate":"2021-11-01T15:19:55.310982","indexId":"70221162","displayToPublicDate":"2021-05-28T07:19:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Amplified impact of climate change on fine-sediment delivery to a subsiding coast, Humboldt Bay, California","docAbstract":"

In Humboldt Bay, tectonic subsidence exacerbates sea-level rise (SLR). To build surface elevations and to keep pace with SLR, the sediment demand created by subsidence and SLR must be balanced by an adequate sediment supply. This study used an ensemble of plausible future scenarios to predict potential climate change impacts on suspended-sediment discharge (Qss) from fluvial sources. Streamflow was simulated using a deterministic water-balance model, and Qss was computed using statistical sediment-transport models. Changes relative to a baseline period (1981–2010) were used to assess climate impacts. For local basins that discharge directly to the bay, the ensemble means projected increases in Qss of 27% for the mid-century (2040–2069) and 58% for the end-of-century (2070–2099). For the Eel River, a regional sediment source that discharges sediment-laden plumes to the coastal margin, the ensemble means projected increases in Qss of 53% for the mid-century and 99% for the end-of-century. Climate projections of increased precipitation and streamflow produced amplified increases in the regional sediment supply that may partially or wholly mitigate sediment demand caused by the combined effects of subsidence and SLR. This finding has important implications for coastal resiliency. Coastal regions with an increasing sediment supply may be more resilient to SLR. In a broader context, an increasing sediment supply from fluvial sources has global relevance for communities threatened by SLR that are increasingly building resiliency to SLR using sediment-based solutions that include regional sediment management, beneficial reuse strategies, and marsh restoration.

","language":"English","publisher":"Springer","doi":"10.1007/s12237-021-00938-x","usgsCitation":"Curtis, J., Flint, L.E., Stern, M.A., Lewis, J., and Klein, R.D., 2021, Amplified impact of climate change on fine-sediment delivery to a subsiding coast, Humboldt Bay, California: Estuaries and Coasts, v. 44, p. 2173-2193, https://doi.org/10.1007/s12237-021-00938-x.","productDescription":"21 p.","startPage":"2173","endPage":"2193","ipdsId":"IP-102755","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":452090,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-021-00938-x","text":"Publisher Index Page"},{"id":436333,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97UBENK","text":"USGS data release","linkHelpText":"Daily Basin Characterization Model (BCM) archive for Humboldt Bay/Eel River"},{"id":386195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Humboldt County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.49707031249999,\n 39.53793974517623\n ],\n [\n -123.96972656249999,\n 39.53793974517623\n ],\n [\n -123.96972656249999,\n 41.41801503608022\n ],\n [\n -124.49707031249999,\n 41.41801503608022\n ],\n [\n -124.49707031249999,\n 39.53793974517623\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2021-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Curtis, Jennifer 0000-0001-7766-994X","orcid":"https://orcid.org/0000-0001-7766-994X","contributorId":212727,"corporation":false,"usgs":true,"family":"Curtis","given":"Jennifer","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816912,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816913,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816914,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, Jack","contributorId":189105,"corporation":false,"usgs":false,"family":"Lewis","given":"Jack","email":"","affiliations":[],"preferred":false,"id":816915,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klein, Randy D.","contributorId":259269,"corporation":false,"usgs":false,"family":"Klein","given":"Randy","email":"","middleInitial":"D.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":816916,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229016,"text":"70229016 - 2021 - Declining diversity of wild-caught species puts dietary nutrient supplies at risk","interactions":[],"lastModifiedDate":"2022-02-25T13:11:00.258941","indexId":"70229016","displayToPublicDate":"2021-05-28T07:06:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Declining diversity of wild-caught species puts dietary nutrient supplies at risk","docAbstract":"
Although biodiversity loss adversely influences a variety of ecosystem functions, how declining wild food diversity affects nutrient supplies for people is poorly understood. Here, we analyze the impact of declining biodiversity on nutrients supplied by fish using detailed information from the Peruvian Amazon, where inland fisheries provide a critical source of nutrition for many of the region’s 800,000 people. We found that the impacts of biodiversity loss on nutrient supplies depended on compensation, trophic dynamics, and functional diversity. When small sedentary species compensated for declines in large migratory species, fatty acid supplies increased, while zinc and iron supplies decreased. In contrast, the probability of failing to maintain supplies or nutrient supply risk increased when species were nutritionally unique. Our results show that trait-based regulations and public health polices need to consider biodiversity’s vital role in sustaining nutritional benefits for over 2 billion people dependent on wild foods across the globe.
","language":"English","publisher":"Science","doi":"10.1126/sciadv.abf9967","usgsCitation":"Heilpern, S.A., DeFries, R., Fiorella, K.J., Flecker, A., Sethi, S., Uriarte, M., and Naeem, S., 2021, Declining diversity of wild-caught species puts dietary nutrient supplies at risk: Science Advances, v. 7, no. 22, eabf9967, 8 p., https://doi.org/10.1126/sciadv.abf9967.","productDescription":"eabf9967, 8 p.","ipdsId":"IP-120442","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":452094,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1126/sciadv.abf9967","text":"External Repository"},{"id":396474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"22","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Heilpern, Sebastian A.","contributorId":280260,"corporation":false,"usgs":false,"family":"Heilpern","given":"Sebastian","email":"","middleInitial":"A.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":836131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeFries, Ruth","contributorId":280261,"corporation":false,"usgs":false,"family":"DeFries","given":"Ruth","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":836132,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fiorella, Kathryn J.","contributorId":268093,"corporation":false,"usgs":false,"family":"Fiorella","given":"Kathryn","email":"","middleInitial":"J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":836158,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flecker, Alexander","contributorId":280262,"corporation":false,"usgs":false,"family":"Flecker","given":"Alexander","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":836133,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":836159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Uriarte, María","contributorId":280263,"corporation":false,"usgs":false,"family":"Uriarte","given":"María","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":836134,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Naeem, Shahid","contributorId":280264,"corporation":false,"usgs":false,"family":"Naeem","given":"Shahid","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":836135,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70221343,"text":"70221343 - 2021 - Use of the smeltCam as an efficient fish sampling alternative within the San Francisco Estuary","interactions":[],"lastModifiedDate":"2021-06-11T12:05:22.631939","indexId":"70221343","displayToPublicDate":"2021-05-28T07:04:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Use of the smeltCam as an efficient fish sampling alternative within the San Francisco Estuary","docAbstract":"

Resource managers often rely on long-term monitoring surveys to detect trends in biological data. However, no survey gear is 100% efficient, and many sources of bias can be responsible for detecting or not detecting biological trends. The SmeltCam is an imaging apparatus developed as a potential sampling alternative to long-term trawling gear surveys within the San Francisco Estuary, California, to reduce handling stress on sensitive species like the Delta Smelt (Hypomesus transpacificus). Although believed to be a reliable alternative to closed cod-end trawling surveys, no formal test of sampling efficiency has been implemented using the SmeltCam. We used a paired deployment of the SmeltCam and a conventional closed cod-end trawl within the Napa River and San Pablo Bay, a Bayesian binomial N-mixture model, and data simulations to determine the sampling efficiency of both deployed gear types to capture a Delta Smelt surrogate (Northern Anchovy, Engraulis mordax) and to test potential bias in our modeling framework. We found that retention efficiency—a component of detection efficiency that estimates the probability a fish is retained by the gear, conditional on gear contact—was slightly higher using the SmeltCam (mean = 0.58) than the conventional trawl (mean = 0.47, Probability SmeltCam retention efficiency > trawl retention efficiency = 94%). We also found turbidity did not affect the SmeltCam’s retention efficiency, although total fish density during an individual tow improved the trawl’s retention efficiency. Simulations also showed the binomial model was accurate when model assumptions were met. Collectively, our results suggest the SmeltCam to be a reliable alternative to sampling with conventional trawling gear, but future tests are needed to confirm whether the SmeltCam is as reliable when applied to taxa other than Northern Anchovy over a greater range of conditions.

","language":"English","publisher":"University of California","doi":"10.15447/sfews.2021v19iss2art6","usgsCitation":"Huntsman, B., Feyrer, F.V., and Young, M.J., 2021, Use of the smeltCam as an efficient fish sampling alternative within the San Francisco Estuary: San Francisco Estuary and Watershed Science, v. 19, no. 2, 16 p., https://doi.org/10.15447/sfews.2021v19iss2art6.","productDescription":"16 p.","ipdsId":"IP-123894","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":452096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2021v19iss2art6","text":"Publisher Index Page"},{"id":386410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.57421875,\n 36.84446074079564\n ],\n [\n -121.86035156249999,\n 36.84446074079564\n ],\n [\n -121.86035156249999,\n 39.40224434029275\n ],\n [\n -123.57421875,\n 39.40224434029275\n ],\n [\n -123.57421875,\n 36.84446074079564\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Huntsman, Brock 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":223101,"corporation":false,"usgs":true,"family":"Huntsman","given":"Brock","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":178379,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817386,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70239051,"text":"70239051 - 2021 - Predicting light regime controls on primary productivity across CONUS river networks","interactions":[],"lastModifiedDate":"2022-12-22T13:03:46.202793","indexId":"70239051","displayToPublicDate":"2021-05-28T06:54:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Predicting light regime controls on primary productivity across CONUS river networks","docAbstract":"

Solar radiation is a fundamental driver of ecosystem productivity, but widespread estimates of light available for primary producers in rivers are lacking. We developed a model to predict light available for river primary producers and used it to estimate river primary production across the contiguous United States (CONUS). Successively accounting for riparian and water column processes improved predictions of primary production as a function of light. We calculated the ratio of river width to riparian tree height and used this metric to predict whether riparian zones or water column processes most limit productivity for over 2 million reaches. Water column processes limited productivity for 50% of the nation's river length and 80% of its surface area, with variations across ecoregions related to riparian forest cover. Our findings facilitate large-scale predictions of stream and river ecosystem productivity, as well as understanding the processes controlling productivity across networks.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL092149","usgsCitation":"Savoy, P., and Harvey, J., 2021, Predicting light regime controls on primary productivity across CONUS river networks: Geophysical Research Letters, v. 48, no. 10, e2020GL092149, 10 p., https://doi.org/10.1029/2020GL092149.","productDescription":"e2020GL092149, 10 p.","ipdsId":"IP-123965","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":452099,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020gl092149","text":"Publisher Index Page"},{"id":436334,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LREC3P","text":"USGS data release","linkHelpText":"Light model and GPP estimates for 173 U.S. rivers"},{"id":410924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Division","active":true,"usgs":true}],"preferred":true,"id":859854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":859855,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221054,"text":"70221054 - 2021 - Ten years of volcanic activity at Mt Etna: High-resolution mapping and accurate quantification of the morphological changes by Pleiades and Lidar data","interactions":[],"lastModifiedDate":"2021-06-01T14:22:02.175408","indexId":"70221054","displayToPublicDate":"2021-05-28T06:52:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8912,"text":"International Journal of Applied Earth Observations and Geoinformation","active":true,"publicationSubtype":{"id":10}},"title":"Ten years of volcanic activity at Mt Etna: High-resolution mapping and accurate quantification of the morphological changes by Pleiades and Lidar data","docAbstract":"

The topography of Mt. Etna, Italy, is subjected to continuous modifications depending on intensity and magnitude of eruptions that frequently occur at the volcano summit and flanks. In order to make high-resolution maps of morphological changes and accurately calculate the overall volume of the erupted products (e.g., lava flows, tephra fall out, scoriae cones) in ten years, we have compared the altimetry models of Mt. Etna derived from 2005 Airborne Laser Scanning data and 2015 Pleiades stereo satellite imagery. Both models cover a common area of 400 km2 with spatial resolution of 2 m and comparable vertical accuracy (RMSE < 0.8 m). The results show that the area most affected by the erupted products is the mid-upper portion of the volcano with an altitude ranging from 1300 m to more than 3300 m a.s.l., value reached at the summit of the North East crater. In particular, this portion changes dramatically in the eastern sector due to the birth and growth of the New South-East Crater, the invasion of dozens of lava flows in the Valle del Bove, and the formation of the 2014 scoriae cones and lava field at the base of the North-East Crater. The total volume of products erupted in the investigated period results in 284.3±15.8 x 106 m3 with a yearly average volume of 28.4 x 106 m3/y comparable with the previous decades. In addition, the products emitted by the 2014 sub-terminal eruption are mapped and quantified including, for the first time, the volume of the 2014 scoriae cones generated on the eastern flank of North-East Crater This study demonstrates how a rigorous comparison between digital elevation models derived from different remote sensing techniques produce high accurate mapping and quantifications of morphological changes applicable for worldwide active volcanoes. This allows to quantify volumes and areas of erupted products reducing the error estimations, a crucial point to provide precise data often used as key parameters for many volcanic hazard studies.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jag.2021.102369","usgsCitation":"Bisson, M., Spinetti, C., Andronico, D., Palaseanu-Lovejoy, M., Buongiorno, M.F., Alexandrov, O., and Cecere, T., 2021, Ten years of volcanic activity at Mt Etna: High-resolution mapping and accurate quantification of the morphological changes by Pleiades and Lidar data: International Journal of Applied Earth Observations and Geoinformation, v. 102, 102369, 11 p., https://doi.org/10.1016/j.jag.2021.102369.","productDescription":"102369, 11 p.","ipdsId":"IP-121404","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":452102,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jag.2021.102369","text":"Publisher Index Page"},{"id":386026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","otherGeospatial":"Mt. Etna, Sicily","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 14.849395751953125,\n 37.62402129571883\n ],\n [\n 15.137786865234377,\n 37.62402129571883\n ],\n [\n 15.137786865234377,\n 37.85859141570558\n ],\n [\n 14.849395751953125,\n 37.85859141570558\n ],\n [\n 14.849395751953125,\n 37.62402129571883\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bisson, Marina 0000-0002-7104-9210","orcid":"https://orcid.org/0000-0002-7104-9210","contributorId":221724,"corporation":false,"usgs":false,"family":"Bisson","given":"Marina","email":"","affiliations":[{"id":40408,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, via Della Faggiola, Pisa, 56126, Italy","active":true,"usgs":false}],"preferred":false,"id":816657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spinetti, Claudia 0000-0002-1861-5666","orcid":"https://orcid.org/0000-0002-1861-5666","contributorId":221725,"corporation":false,"usgs":false,"family":"Spinetti","given":"Claudia","email":"","affiliations":[{"id":40409,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Sezione ONT, via di Vigna Murata, Roma, 00143, Italy","active":true,"usgs":false}],"preferred":false,"id":816658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andronico, Daniele 0000-0002-8333-1547","orcid":"https://orcid.org/0000-0002-8333-1547","contributorId":259163,"corporation":false,"usgs":false,"family":"Andronico","given":"Daniele","email":"","affiliations":[{"id":52323,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo","active":true,"usgs":false}],"preferred":false,"id":816659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":816660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buongiorno, Maria Fabrizia 0000-0002-6095-6974","orcid":"https://orcid.org/0000-0002-6095-6974","contributorId":221726,"corporation":false,"usgs":false,"family":"Buongiorno","given":"Maria","email":"","middleInitial":"Fabrizia","affiliations":[{"id":40409,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Sezione ONT, via di Vigna Murata, Roma, 00143, Italy","active":true,"usgs":false}],"preferred":false,"id":816661,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alexandrov, Oleg","contributorId":167662,"corporation":false,"usgs":false,"family":"Alexandrov","given":"Oleg","email":"","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":816662,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cecere, Thomas 0000-0001-5254-8404 tcecere@usgs.gov","orcid":"https://orcid.org/0000-0001-5254-8404","contributorId":221727,"corporation":false,"usgs":true,"family":"Cecere","given":"Thomas","email":"tcecere@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":816663,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70222118,"text":"70222118 - 2021 - The contribution of land cover change to the decline of honey yields in the Northern Great Plains","interactions":[],"lastModifiedDate":"2021-07-21T11:49:16.089532","indexId":"70222118","displayToPublicDate":"2021-05-28T06:51:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The contribution of land cover change to the decline of honey yields in the Northern Great Plains","docAbstract":"

Decreased availability of forage, as well as increased pesticide exposure, are important factors in the decline of honey bee health. Here, we isolate land cover transitions and their effect on honey production at 160 commercial apiaries in the Northern Great Plains. We found that land cover changes from 2008 to 2012 caused an annual decline in honey yields of 0.9% in the study area. Transitions from grassland to soybean (but not corn) were particularly detrimental to honey yields, potentially due to bee contact with pesticides within and around agricultural fields. When our results are applied to known apiary locations across all of North Dakota (U.S.A.), we estimate a 2.5% (1.6 million USD) decline in 2012 honey yields due to land cover changes occurring between 2008 and 2012. Even when controlling for changes in land cover, we found that on average colonies in the study area experienced a 14% annual decline in honey yields. We discuss possible explanations for these non-land-cover-related honey yield declines, including changing economic conditions (e.g. pollination services), changes in land management (e.g. pesticides), and increases in pests or diseases.

","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/abfde8","usgsCitation":"Smith, D., Davis, A.Y., Hitaj, C., Hellerstein, D., Preslicka, A., Kirkpatrick, E., Mushet, D., and Lonsdorf, E., 2021, The contribution of land cover change to the decline of honey yields in the Northern Great Plains: Environmental Research Letters, v. 16, 064050, 12 p., https://doi.org/10.1088/1748-9326/abfde8.","productDescription":"064050, 12 p.","ipdsId":"IP-105742","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":452104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/abfde8","text":"Publisher Index Page"},{"id":387285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.755859375,\n 43.004647127794435\n ],\n [\n -96.50390625,\n 43.004647127794435\n ],\n [\n -96.50390625,\n 44.465151013519616\n ],\n [\n -99.755859375,\n 44.465151013519616\n ],\n [\n -99.755859375,\n 43.004647127794435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2021-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, David","contributorId":261251,"corporation":false,"usgs":false,"family":"Smith","given":"David","affiliations":[{"id":52784,"text":"U.S. Department of Agriculture, Economic Research Service","active":true,"usgs":false}],"preferred":false,"id":819594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Amelie Y. 0000-0001-7373-7618","orcid":"https://orcid.org/0000-0001-7373-7618","contributorId":261252,"corporation":false,"usgs":false,"family":"Davis","given":"Amelie","email":"","middleInitial":"Y.","affiliations":[{"id":17754,"text":"Miami University, Department of Geography & Institute for the Environment and Sustainability","active":true,"usgs":false}],"preferred":false,"id":819595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hitaj, Claudia 0000-0002-6408-9265","orcid":"https://orcid.org/0000-0002-6408-9265","contributorId":261253,"corporation":false,"usgs":false,"family":"Hitaj","given":"Claudia","email":"","affiliations":[{"id":52784,"text":"U.S. Department of Agriculture, Economic Research Service","active":true,"usgs":false}],"preferred":false,"id":819596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hellerstein, Dan","contributorId":261254,"corporation":false,"usgs":false,"family":"Hellerstein","given":"Dan","affiliations":[{"id":52784,"text":"U.S. Department of Agriculture, Economic Research Service","active":true,"usgs":false}],"preferred":false,"id":819597,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Preslicka, Amanda","contributorId":261255,"corporation":false,"usgs":false,"family":"Preslicka","given":"Amanda","email":"","affiliations":[{"id":17754,"text":"Miami University, Department of Geography & Institute for the Environment and Sustainability","active":true,"usgs":false}],"preferred":false,"id":819598,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kirkpatrick, Emma","contributorId":261256,"corporation":false,"usgs":false,"family":"Kirkpatrick","given":"Emma","email":"","affiliations":[{"id":17754,"text":"Miami University, Department of Geography & Institute for the Environment and Sustainability","active":true,"usgs":false}],"preferred":false,"id":819599,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mushet, David M. 0000-0002-5910-2744","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":248468,"corporation":false,"usgs":true,"family":"Mushet","given":"David M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819600,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lonsdorf, Eric","contributorId":261257,"corporation":false,"usgs":false,"family":"Lonsdorf","given":"Eric","email":"","affiliations":[{"id":52785,"text":"University of Minnesota, Institute on the Environment","active":true,"usgs":false}],"preferred":false,"id":819601,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70220717,"text":"sir20215033 - 2021 - Overview and methodology for a study to identify fecal contamination sources using microbial source tracking in seven embayments on Long Island, New York","interactions":[],"lastModifiedDate":"2022-09-01T10:06:27.850627","indexId":"sir20215033","displayToPublicDate":"2021-05-27T18:19:54","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5033","displayTitle":"Overview and Methodology for a Study To Identify Fecal Contamination Sources Using Microbial Source Tracking in Seven Embayments on Long Island, New York","title":"Overview and methodology for a study to identify fecal contamination sources using microbial source tracking in seven embayments on Long Island, New York","docAbstract":"

Between June 2018 and July 2019, the U.S. Geological Survey collaborated with the New York State Department of Environmental Conservation to analyze water quality in seven embayments on Long Island, New York, for a study to examine fecal contamination using microbial source tracking. This report documents the approach, methodology, and quality-assurance data used in the study. All samples and field data were collected in accordance with U.S. Geological Survey National Field Manual procedures. Samples were analyzed for host-specific deoxyribonucleic acid (DNA) markers, fecal coliform bacteria, inorganic and total organic nitrogen, and stable isotopes of nitrate and ammonium.

Samples for quality control were collected for microbiological analyses at a rate of 1 per 20 environmental samples. A total of 14 blank and 15 replicate samples were collected for DNA markers, 52 sequential field replicates were analyzed by the Public Environmental Health Laboratory of the Suffolk County Department of Health Services and the New York State Department of Conservation Marine Laboratory for fecal coliform, and 7 blank and 7 replicate samples were collected to be analyzed for nutrients. Results from quality-control samples collected throughout the course of the study confirmed that sampling procedures were adequate and did not disqualify any data from analysis.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215033","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Tagliaferri, T.N., Fisher, S.C., Kephart, C.M., Cheung, N., Reed, A.P., and Welk, R.J., 2021, Overview and methodology for a study to identify fecal contamination sources using microbial source tracking in seven embayments on Long Island, New York: U.S. Geological Survey Scientific Investigations Report 2021–5033, 8 p., https://doi.org/10.3133/sir20215033.","productDescription":"iv, 8 p.","numberOfPages":"8","onlineOnly":"Y","ipdsId":"IP-128174","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":406050,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20215042","text":"Scientific Investigations Report 2021–5042","linkHelpText":"- Using Microbial Source Tracking To Identify Fecal Contamination Sources in an Embayment in Hempstead Harbor on Long Island, New York"},{"id":406049,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20215141","text":"Scientific Investigations Report 2021–5141","linkHelpText":"- Using Microbial Source Tracking To Identify Contamination Sources in Port Jefferson Harbor, Setauket Harbor, and Conscience Bay on Long Island, New York"},{"id":406048,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20225007","text":"Scientific Investigations Report 2022–5007","linkHelpText":"- Using Microbial Source Tracking To Identify Fecal Contamination Sources in Patchogue and Bellport Bays on Long Island, New York"},{"id":406047,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20225028","text":"Scientific Investigations Report 2022–5028","linkHelpText":"- Using Microbial Source Tracking To Identify Fecal Contamination Sources in Sag Harbor on Long Island, New York"},{"id":406046,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20225038","text":"Scientific Investigations Report 2022–5038","linkHelpText":"- Using Microbial Source Tracking To Identify Fecal Contamination Sources in Lake Montauk on Long Island, New York"},{"id":406045,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20225057","text":"Scientific Investigations Report 2022–5057","linkHelpText":"- Using Microbial Source Tracking To Identify Fecal Contamination Sources in Great South Bay on Long Island, New York"},{"id":406044,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20225082","text":"Scientific Investigations Report 2022–5082","linkHelpText":"- Using Microbial Source Tracking To Identify Fecal Contamination Sources in South Oyster Bay on Long Island, New York"},{"id":385932,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5033/sir20215033.pdf","text":"Report","size":"1.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5033"},{"id":385931,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5033/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.0313720703125,\n 40.58684239087908\n ],\n [\n -73.883056640625,\n 40.534676780615406\n ],\n [\n -72.85858154296875,\n 40.66605624777337\n ],\n [\n -72.13623046875,\n 40.93426521177941\n ],\n [\n -71.8011474609375,\n 41.06899846310619\n ],\n [\n -72.2625732421875,\n 41.18692242290296\n ],\n [\n -72.6910400390625,\n 41.017210578228436\n ],\n [\n -73.10577392578125,\n 40.992337919312305\n ],\n [\n -73.47381591796875,\n 40.96952973563832\n ],\n [\n -73.7237548828125,\n 40.896905775860006\n ],\n [\n -73.795166015625,\n 40.82212357516945\n ],\n [\n -73.94073486328125,\n 40.749337730454826\n ],\n [\n -74.0313720703125,\n 40.65980593837852\n ],\n [\n -74.0423583984375,\n 40.60978237983301\n ],\n [\n -74.0313720703125,\n 40.58684239087908\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2021-05-27","noUsgsAuthors":false,"publicationDate":"2021-05-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Tagliaferri, Tristen N. 0000-0001-7408-7899 ttagliaferri@usgs.gov","orcid":"https://orcid.org/0000-0001-7408-7899","contributorId":5138,"corporation":false,"usgs":true,"family":"Tagliaferri","given":"Tristen","email":"ttagliaferri@usgs.gov","middleInitial":"N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Shawn C. 0000-0001-6324-1061 scfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-6324-1061","contributorId":4843,"corporation":false,"usgs":true,"family":"Fisher","given":"Shawn","email":"scfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kephart, Christopher M. 0000-0002-3369-5596 ckephart@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-5596","contributorId":1932,"corporation":false,"usgs":true,"family":"Kephart","given":"Christopher","email":"ckephart@usgs.gov","middleInitial":"M.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheung, Natalie 0000-0003-2987-0440 ncheung@usgs.gov","orcid":"https://orcid.org/0000-0003-2987-0440","contributorId":258429,"corporation":false,"usgs":true,"family":"Cheung","given":"Natalie","email":"ncheung@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Ariel P. 0000-0002-0792-5204","orcid":"https://orcid.org/0000-0002-0792-5204","contributorId":219992,"corporation":false,"usgs":true,"family":"Reed","given":"Ariel","email":"","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Welk, Robert J. 0000-0003-0852-5584 rwelk@usgs.gov","orcid":"https://orcid.org/0000-0003-0852-5584","contributorId":194109,"corporation":false,"usgs":true,"family":"Welk","given":"Robert","email":"rwelk@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816440,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229737,"text":"70229737 - 2021 - Improving short-term recruitment forecasts for coho salmon using a spatiotemporal integrated population model","interactions":[],"lastModifiedDate":"2022-03-16T16:11:47.02032","indexId":"70229737","displayToPublicDate":"2021-05-27T11:06:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Improving short-term recruitment forecasts for coho salmon using a spatiotemporal integrated population model","docAbstract":"

Fishery managers often rely on forecasts of future population abundance to set allowable harvest quotas or exploitation rates. While there has been substantial research devoted to identifying environmental factors that can predict recruitment for individual populations, such correlations often degrade over time, thereby limiting their utility for management. Conversely, examining multiple populations at once to detect shared, spatially structured patterns can offer insights into their recruitment dynamics that are advantageous for forecasting. Here, we develop a population dynamics model for natural origin coho salmon (Oncorhynchus kisutch) stocks in Washington State that leverages spatial and temporal autocorrelation in marine survival to improve one-year-ahead forecasts of adult returns. Executed in a Bayesian hierarchical integrated modelling framework, our spatiotemporal approach incorporates multiple data types and shares information among stocks to estimate key biological parameters that are informative for forecasting. Retrospective evaluation of one-year-ahead forecast skill indicated that the spatiotemporal integrated population model (ST-IPM) outperformed existing forecasts of Washington State coho salmon returns by 25–38 % on average. Moreover, the ST-IPM estimates parameters that were previously non-identifiable for many stocks, and propagates uncertainty from multiple contributing data sources into model forecasts. Our results add to a growing body of work demonstrating the utility of spatiotemporal and integrated approaches for modelling population dynamics, and the framework developed here has broad applications to the assessment and management of coho salmon in Washington State and elsewhere throughout their range.

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duration","interactions":[],"lastModifiedDate":"2022-02-17T15:27:17.969322","indexId":"70228726","displayToPublicDate":"2021-05-27T09:18:07","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale variation in wave attenuation of oyster reef living shorelines and the influence of inundation duration","docAbstract":"

One of the paramount goals of oyster reef living shorelines is to achieve sustained and adaptive coastal protection, which requires meeting ecological (i.e., develop a self-sustaining oyster population) and engineering (i.e., provide coastal defense) targets. In a large-scale comparison along the Atlantic and Gulf coasts of the United States, the efficacy of various designs of oyster reef living shorelines at providing wave attenuation was evaluated accounting for the ecological limitations of oysters with regard to inundation duration. A critical threshold for intertidal oyster reef establishment is 50% inundation duration. Living shorelines that spent less than one-half of the time (<50%) inundated were not considered suitable habitat for oysters, however, were effective at wave attenuation (68% reduction in wave height). Reefs that experienced >50% inundation were considered suitable habitat for oysters, but wave attenuation was similar to controls (no reef; ~5% reduction in wave height). Many of the oyster reef living shoreline approaches therefore failed to optimize the ecological and engineering goals. In both inundation regimes, wave transmission decreased with an increasing freeboard (difference between reef crest elevation and water level), supporting its importance in the wave attenuation capacity of oyster reef living shorelines. However, given that the reef crest elevation (and thus freeboard) should be determined by the inundation duration requirements of oysters, research needs to be refocused on understanding the implications of other reef parameters (e.g., width) for optimizing wave attenuation. A broader understanding of the reef characteristics and seascape contexts that result in effective coastal defense by oyster reefs is needed to inform appropriate design and implementation of oyster-based living shorelines globally.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2382","usgsCitation":"Morris, R.L., La Peyre, M., Webb, B.M., Marshall, D.A., Bilkovic, D., Cebrian, J., McClenachan, G., Kibler, K.M., Walters, L.J., Bushek, D., Sparks, E.L., Temple, N.A., Moody, J., Angstadt, K., Goff, J., Boswell, M.K., Sacks, P.E., and Swearer, S.E., 2021, Large-scale variation in wave attenuation of oyster reef living shorelines and the influence of inundation duration: Ecological Applications, v. 31, no. 6, e02382, 15 p., https://doi.org/10.1002/eap.2382.","productDescription":"e02382, 15 p.","ipdsId":"IP-113781","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":481103,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.wm.edu/vimsarticles/2082","text":"External Repository"},{"id":396101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Louisiana, New Jersey, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.35205078124999,\n 30.278044377800153\n ],\n [\n -88.0224609375,\n 30.278044377800153\n ],\n [\n -88.0224609375,\n 30.751277776257812\n ],\n [\n -88.35205078124999,\n 30.751277776257812\n ],\n [\n -88.35205078124999,\n 30.278044377800153\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.736328125,\n 29.707139348134145\n ],\n [\n -89.31884765624999,\n 29.707139348134145\n ],\n [\n -89.31884765624999,\n 30.20211367909724\n ],\n [\n -89.736328125,\n 30.20211367909724\n ],\n [\n -89.736328125,\n 29.707139348134145\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.14501953125,\n 28.671310915880834\n ],\n [\n -80.5078125,\n 28.671310915880834\n ],\n [\n -80.5078125,\n 29.209713225868185\n ],\n [\n -81.14501953125,\n 29.209713225868185\n ],\n [\n -81.14501953125,\n 28.671310915880834\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.43212890625,\n 39.07890809706475\n ],\n [\n -74.970703125,\n 39.07890809706475\n ],\n [\n -74.970703125,\n 39.50404070558415\n ],\n [\n -75.43212890625,\n 39.50404070558415\n ],\n [\n -75.43212890625,\n 39.07890809706475\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.61865234374999,\n 37.09023980307208\n ],\n [\n -76.0693359375,\n 37.09023980307208\n ],\n [\n -76.0693359375,\n 37.77071473849609\n ],\n [\n -76.61865234374999,\n 37.77071473849609\n ],\n [\n -76.61865234374999,\n 37.09023980307208\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Morris, R. 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M.","contributorId":243400,"corporation":false,"usgs":false,"family":"Webb","given":"B.","email":"","middleInitial":"M.","affiliations":[{"id":48710,"text":"University of South Alabama","active":true,"usgs":false}],"preferred":false,"id":835205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marshall, D. A.","contributorId":276081,"corporation":false,"usgs":false,"family":"Marshall","given":"D.","email":"","middleInitial":"A.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":835206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bilkovic, D. M.","contributorId":243391,"corporation":false,"usgs":false,"family":"Bilkovic","given":"D. 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M.","contributorId":243396,"corporation":false,"usgs":false,"family":"Kibler","given":"K.","email":"","middleInitial":"M.","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":835210,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walters, L. J.","contributorId":243403,"corporation":false,"usgs":false,"family":"Walters","given":"L.","email":"","middleInitial":"J.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":835211,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bushek, D.","contributorId":243393,"corporation":false,"usgs":false,"family":"Bushek","given":"D.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":835212,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sparks, E. 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A.","affiliations":[],"preferred":false,"id":835215,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Angstadt, K.","contributorId":279613,"corporation":false,"usgs":false,"family":"Angstadt","given":"K.","email":"","affiliations":[{"id":57314,"text":"William & Mary","active":true,"usgs":false}],"preferred":false,"id":835216,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Goff, J.","contributorId":279614,"corporation":false,"usgs":false,"family":"Goff","given":"J.","affiliations":[{"id":48711,"text":"Dauphin Island Sea Lab","active":true,"usgs":false}],"preferred":false,"id":835217,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Boswell, M. 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E.","contributorId":243401,"corporation":false,"usgs":false,"family":"Swearer","given":"S.","email":"","middleInitial":"E.","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":835220,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70220879,"text":"70220879 - 2021 - Appendix C: Central sands lakes study technical report: Modeling documentation","interactions":[],"lastModifiedDate":"2021-05-27T14:04:05.646141","indexId":"70220879","displayToPublicDate":"2021-05-27T08:51:14","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":8761,"text":"Wisconsin DNR Technical Report","active":true,"publicationSubtype":{"id":2}},"title":"Appendix C: Central sands lakes study technical report: Modeling documentation","docAbstract":"

This report provides the necessary documentation of the numerical models developed for the Central Sands Lake study in central Wisconsin and will be included as a technical appendix in the report to the Wisconsin State Legislature by the Wisconsin Department of Natural Resources (WDNR) in response to 2017 Wisconsin Act 10. This legislation directed WDNR to determine whether existing and potential groundwater withdrawals are causing or are likely to cause significant reduction of mean seasonal water levels at Pleasant Lake, Long Lake, and Plainfield Lake (s. 281.34(7m)(2)(b), Wis. Stats.) in Waushara County, Wisconsin. To evaluate the potential hydrologic connection between groundwater withdrawals and the nearby study lakes, hydrologic models were created that focused on the lakes of interest and yet were large enough to cover a broad enough region to extend to the major hydrologic boundaries of the natural flow system. The areas near the lakes require finer-scale grid discretization (or spacing) to better represent the lakes and streams in the model, but also need to cover a large enough area to include the groundwater withdrawal locations that have the potential to cause reduction in water levels in the lakes. To accomplish these goals, three groundwater models were created: a regional model extending to major hydrologic boundaries; and two inset models, inheriting boundaries from the regional model but focused near the lakes. Each of the inset models, in turn, included a detailed area close to the lakes surrounded by an area at the same spatial scale as the regional model (Figure 1).

To support WDNR in evaluating the connection between groundwater withdrawals and lake levels, a representative time period was required over which to compare land use with and without irrigated agriculture and for WDNR to evaluate potential lake stage and flux changes related to irrigated agriculture. WDNR chose the climate period of 1981-2018 to be representative of a typical period and provided two land use scenarios—one with no irrigated agriculture and one with assumed crop rotations similar to current conditions—to simulate with groundwater models to, then, compare lake responses with. As a result, simulations over this climate record are not intended to recreate the history of 1981-2018 because land use changed over that time. These runs are, instead, intended to provide a basis on which to compare land use with and without irrigation-related groundwater withdrawals based on the current arrangement of land use and a varied climatic record. Groundwater withdrawals focused on irrigated-agriculture-related water use because greater than 95% of groundwater withdrawal in the two inset models around the study lakes is for irrigated agriculture water use.

The period of 2012-2018 was used for parameter estimation (synonymously referred to as “history matching”) for the groundwater models. This time period was chosen because it includes the most complete water use records to simulate groundwater withdrawals. History matching was performed using groundwater elevations, lake stages, and streamflow observations over the 2012-2018 time period and processed observations derived from those raw data.

Climatic data were incorporated into the model using a soil-water balance approach. A soil water balance model was constructed at the scale of the regional groundwater model to both calculate recharge based on land use and climate, and in the long-term climate-period runs, to estimate water use required by irrigated agriculture to apply as well boundary conditions in the groundwater model in the absence of reported water use values over that period.

","language":"English","publisher":"Wisconsin Department of Natural Resources","usgsCitation":"Fienen, M., Haserodt, M.J., Leaf, A.T., and Westenbroek, S., 2021, Appendix C: Central sands lakes study technical report: Modeling documentation: Wisconsin DNR Technical Report, ix, 137 p.","productDescription":"ix, 137 p.","ipdsId":"IP-127829","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":386002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385990,"type":{"id":15,"text":"Index Page"},"url":"https://dnr.wisconsin.gov/topic/Wells/HighCap/CSLStudy.html"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Central Sands region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.78851318359375,\n 43.58834891179792\n ],\n [\n -89.29962158203125,\n 43.57641143300888\n ],\n [\n -89.219970703125,\n 43.75919263886012\n ],\n [\n -89.54132080078125,\n 44.471031231561845\n ],\n [\n -89.7967529296875,\n 44.41808794374846\n ],\n [\n -89.85443115234375,\n 44.33367180085156\n ],\n [\n -89.98901367187499,\n 44.11125397357155\n ],\n [\n -90.01373291015625,\n 44.03232064275081\n ],\n [\n -89.96978759765625,\n 43.878097874251736\n ],\n [\n -89.8187255859375,\n 43.71156424665851\n ],\n [\n -89.78851318359375,\n 43.58834891179792\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haserodt, Megan J. 0000-0002-8304-090X mhaserodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8304-090X","contributorId":174791,"corporation":false,"usgs":true,"family":"Haserodt","given":"Megan","email":"mhaserodt@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Westenbroek, Stephen, M. 0000-0002-6284-8643","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":206429,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen, M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816550,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230038,"text":"70230038 - 2021 - Assessing the uncertainties in climatic estimates based on vegetation assemblages: Examples from modern vegetation assemblages in the American Southwest","interactions":[],"lastModifiedDate":"2022-03-29T18:57:47.258287","indexId":"70230038","displayToPublicDate":"2021-05-27T08:35:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the uncertainties in climatic estimates based on vegetation assemblages: Examples from modern vegetation assemblages in the American Southwest","docAbstract":"

Assemblages of fossil plant remains have been widely used to reconstruct past climatic conditions, usually through the application of methods that involve either finding vegetation analogues on the modern landscape (and using the modern associated climatic values as the basis for an estimate) or using the modern climatic ranges of individual taxa in an assemblage to determine the range of a given climate variable that would allow these plant taxa to live together. Although these approaches are relatively straightforward, it is difficult to assess the uncertainties associated with each approach, particularly in regard to their application to plant macrofossil assemblages. To explore the uncertainty that may arise from inaccuracy and imprecision in climate reconstructions and from ecological considerations we used variants of both approaches to estimate climate from two data sets of modern vegetation assemblages from the southwestern United States: (1) 1752 gridded “virtual plant assemblages” based on plant range maps that provide uniform spatial coverage of the presence or absence of major woody plant taxa across the study area; and (2) 43 modern packrat (Neotoma spp.) midden presence-absence assemblages that are similar to fossil midden assemblages. By comparing observed and estimated climate values, we evaluated the quality of the climate estimates, identified sources of uncertainty, and characterized the nature and magnitude of the effects of these uncertainties on the climate estimates.

Uncertainties in estimating climate from vegetation assemblages arise because any given plant taxon (or assemblage) must have the resiliency to survive a range of climatic variability, and because of the strong intercorrelations among climatic variables in the modern climate data. Additional sources of uncertainty in climate estimates from plant assemblages include: (1) the modern climate and plant distribution data that are selected as the basis for estimation; (2) the particular quantitative approach that is used to estimate climate; (3) the sufficiency of the number of taxa in the analysis for providing an unbiased representation of the vegetation community as it existed for each time period in the analysis; and, (4) the location of the assemblage on the climatic and environmental gradients in the calibration data set for each climate variable under consideration.

We conclude that vegetation assemblages can provide valid and reproducible estimates of climatic variables and that the primary trends and mapped patterns in the observed climate data can be reconstructed from such estimates. However, many factors may affect the quality of an estimate from a given plant assemblage, including aspects of data selection, data adequacy, methodologies, and the location of the assemblage site relative to gradients in the base climate data. It is particularly difficult to accurately estimate extreme values in the observed climate data, because estimated values from either end of an observed climate gradient necessarily “move toward the middle” of the gradient. In addition, the interval chosen to represent modern climate (here we used 1961 to 1990) may have a large impact on the size of the estimated difference between modern and past climate at a given site.

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for productive lab meetings","docAbstract":"

The aim of this article is to delineate 10 simple rules on how to achieve productive lab meetings. We use the term “meeting” interchangeably to represent both the single meeting event and the overarching concept of the recurring meeting. In this article we speak from our experience, as a lab group at the University of Massachusetts that meets regularly (Fig 1). Although the rules are mostly tailored toward academic or research institution settings, insights can be gained for other contexts. We believe these rules are applicable across a diverse set of labs and lab structures. For example, while many members of our current lab have remained constant for many years, the lab composition has changed as various undergraduate students, graduate students, postdoctoral fellow, visiting professors, and other faculty have joined and/or moved on. Throughout these experiences, lab rules, presented in modified form here, proved flexible and adaptable enough to be useful in helping guide productive lab meetings. Note that this article is written for principal investigator/s (PI), students, postdocs, and other lab members; it takes the whole lab group to succeed. The key to planning productive lab meetings boils down to discussing and determining as a team the answers to why, who, what, where, when, and how: Why are lab meetings important for the functioning of the lab? Who will participate? What will be the focus of lab meetings? When and where should the lab meetings occur? How should each meeting be structured and carried out so that the goals and objectives of the lab and its participants are met?

","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pcbi.1008953","usgsCitation":"Golden, N., Devarajan, K., Balantic, C., Drake, J., Hallworth, M.T., and Morelli, T.L., 2021, Ten simple rules for productive lab meetings: PLOS Computational Biology, v. 17, no. 5, e1008953, 13 p., https://doi.org/10.1371/journal.pcbi.1008953.","productDescription":"e1008953, 13 p.","ipdsId":"IP-125473","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":452113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pcbi.1008953","text":"Publisher Index Page"},{"id":410702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-27","publicationStatus":"PW","contributors":{"editors":[{"text":"Schwartz, Russell","contributorId":300129,"corporation":false,"usgs":false,"family":"Schwartz","given":"Russell","email":"","affiliations":[{"id":12943,"text":"Carnegie Mellon University","active":true,"usgs":false}],"preferred":false,"id":859459,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Golden, Nigel","contributorId":300012,"corporation":false,"usgs":false,"family":"Golden","given":"Nigel","email":"","affiliations":[{"id":65000,"text":"University of Massachusetts, Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":859268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devarajan, Kadambari","contributorId":236828,"corporation":false,"usgs":false,"family":"Devarajan","given":"Kadambari","email":"","affiliations":[],"preferred":false,"id":859269,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balantic, Cathleen","contributorId":275317,"corporation":false,"usgs":false,"family":"Balantic","given":"Cathleen","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":859270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drake, Joseph","contributorId":300015,"corporation":false,"usgs":false,"family":"Drake","given":"Joseph","email":"","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":859271,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hallworth, Michael T.","contributorId":213805,"corporation":false,"usgs":false,"family":"Hallworth","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":38879,"text":"National Zoological Park, Migratory Bird Center","active":true,"usgs":false}],"preferred":false,"id":859272,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":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":859273,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70221154,"text":"70221154 - 2021 - Transient disease dynamics across ecological scales","interactions":[],"lastModifiedDate":"2022-01-06T17:10:13.809411","indexId":"70221154","displayToPublicDate":"2021-05-27T08:12:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3592,"text":"Theoretical Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Transient disease dynamics across ecological scales","docAbstract":"

Analyses of transient dynamics are critical to understanding infectious disease transmission and persistence. Identifying and predicting transients across scales, from within-host to community-level patterns, plays an important role in combating ongoing epidemics and mitigating the risk of future outbreaks. Moreover, greater emphases on non-asymptotic processes will enable timely evaluations of wildlife and human diseases and lead to improved surveillance efforts, preventive responses, and intervention strategies. Here, we explore the contributions of transient analyses in recent models spanning the fields of epidemiology, movement ecology, and parasitology. In addition to their roles in predicting epidemic patterns and endemic outbreaks, we explore transients in the contexts of pathogen transmission, resistance, and avoidance at various scales of the ecological hierarchy. Examples illustrate how (i) transient movement dynamics at the individual host level can modify opportunities for transmission events over time; (ii) within-host energetic processes often lead to transient dynamics in immunity, pathogen load, and transmission potential; (iii) transient connectivity between discrete populations in response to environmental factors and outbreak dynamics can affect disease spread across spatial networks; and (iv) increasing species richness in a community can provide transient protection to individuals against infection. Ultimately, we suggest that transient analyses offer deeper insights and raise new, interdisciplinary questions for disease research, consequently broadening the applications of dynamical models for outbreak preparedness and management.

","language":"English","publisher":"Springer","doi":"10.1007/s12080-021-00514-w","usgsCitation":"Tao, Y., Hite, J.L., Lafferty, K.D., Earn, D.J., and Bharti, N., 2021, Transient disease dynamics across ecological scales: Theoretical Ecology, v. 14, p. 625-640, https://doi.org/10.1007/s12080-021-00514-w.","productDescription":"16 p.","startPage":"625","endPage":"640","ipdsId":"IP-129495","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":452115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12080-021-00514-w","text":"Publisher Index Page"},{"id":386173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2021-05-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Tao, Yun","contributorId":259235,"corporation":false,"usgs":false,"family":"Tao","given":"Yun","email":"","affiliations":[{"id":52331,"text":"Intelligence Community Postdoctoral Research Fellowship Program, Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA, 93106, USA","active":true,"usgs":false}],"preferred":false,"id":816871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hite, Jessica L","contributorId":259236,"corporation":false,"usgs":false,"family":"Hite","given":"Jessica","email":"","middleInitial":"L","affiliations":[{"id":52333,"text":"School of Veterinary Medicine, Department of Pathobiological Sciences, University of Wisconsin, Madison, WI, 53706, USA","active":true,"usgs":false}],"preferred":false,"id":816872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Earn, David J D","contributorId":259237,"corporation":false,"usgs":false,"family":"Earn","given":"David","email":"","middleInitial":"J D","affiliations":[{"id":52334,"text":"Department of Mathematics and Statistics, McMaster University, Hamilton, ON, L8S 4K1, Canada","active":true,"usgs":false}],"preferred":false,"id":816874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bharti, Nita","contributorId":259238,"corporation":false,"usgs":false,"family":"Bharti","given":"Nita","email":"","affiliations":[{"id":52336,"text":"Department of Biology Center for Infectious Disease Dynamics, Penn State University, University Park, PA, 16802, USA","active":true,"usgs":false}],"preferred":false,"id":816875,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}