Tropical regions are experiencing high rates of forest cover loss coupled with changes in the volume and timing of rainfall. These shifts can compromise streamflow and water provision, highlighting the need to identify how forest cover influences streamflow generation under variable rainfall conditions. Although rainfall is the key driver of streamflow regimes, the role of forests is less clear, particularly in tropical regions where forest loss is an ongoing risk. Forest cover loss alters evapotranspiration, rainfall infiltration and storage, and may increase stream ecosystem vulnerability to rainfall extremes. Puerto Rico, an island with spatially heterogenous forest cover and a marked geographic rainfall gradient, is projected to experience more frequent droughts and flash flooding. Using 15-minute streamflow data collected between 2005 and 2016 from 20 USGS stream gages and 3-hourly Multi-Source Weighted-Ensemble Precipitation rainfall estimates, we utilized flow-duration curves and linear mixed regression models to examine the role of forest cover in regulating the timing and volume of streamflow. The mixed model approach helps to account for differences in watershed characteristics. We determined the effects of rainfall and forest cover on low and peak flows in Puerto Rican streams, then evaluated changes in these relationships under dry and wet antecedent rainfall conditions. Watersheds with high forest cover had consistently greater low and peak streamflow than deforested ones under all rainfall conditions, although the effect was more marked during wet antecedent conditions, suggesting that peak flow is largely the result of saturation excess overland flow. During dry antecedent rainfall conditions, highly forested watersheds had higher streamflow than deforested ones, suggesting greater hillslope storage and release may also be at play. Our results demonstrate that forest cover generated a net increase in hillslope infiltration and storage and may lessen drought impacts on streamflow in Puerto Rico. Resilience to prolonged drought may be limited by finite water storage potential in this steep, mountainous setting, highlighting maintenance of forest cover as an important water management strategy to increase infiltration.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14551","usgsCitation":"Hall, J.S., Scholl, M.A., Gorokhovich, Y., and Uriarte, M., 2022, Forest cover lessens the impact of drought on streamflow in Puerto Rico: Hydrological Processes, v. 36, no. 5, e14551, 16 p., https://doi.org/10.1002/hyp.14551.","productDescription":"e14551, 16 p.","ipdsId":"IP-122081","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":399811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto 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Rico\",\"nation\":\"USA \"}}]}","volume":"36","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hall, Jazlynn S. 0000-0002-8782-0065","orcid":"https://orcid.org/0000-0002-8782-0065","contributorId":290688,"corporation":false,"usgs":false,"family":"Hall","given":"Jazlynn","email":"","middleInitial":"S.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":841585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":841586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorokhovich, Yuri","contributorId":290689,"corporation":false,"usgs":false,"family":"Gorokhovich","given":"Yuri","email":"","affiliations":[{"id":39562,"text":"City University of New York","active":true,"usgs":false}],"preferred":false,"id":841587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Uriarte, Maria","contributorId":287019,"corporation":false,"usgs":false,"family":"Uriarte","given":"Maria","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":841588,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230147,"text":"70230147 - 2022 - Complex life-cycles in trophically transmitted helminths: Do the benefits of increased growth and transmission outweigh generalism and complexity costs?","interactions":[],"lastModifiedDate":"2022-03-30T12:09:56.574531","indexId":"70230147","displayToPublicDate":"2022-03-15T07:08:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10528,"text":"Current Research in Parasitology & Vector-borne Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Complex life-cycles in trophically transmitted helminths: Do the benefits of increased growth and transmission outweigh generalism and complexity costs?","docAbstract":"Why do so many parasitic worms have complex life-cycles? A complex life-cycle has at least two hypothesized costs: (i) worms with longer life-cycles, i.e. more successive hosts, must be generalists at the species level, which might reduce lifetime survival or growth, and (ii) each required host transition adds to the risk that a worm will fail to complete its life-cycle. Comparing hundreds of trophically transmitted acanthocephalan, cestode, and nematode species with different life-cycles suggests these costs are weaker than expected. Helminths with longer cycles exhibit higher species-level generalism without impaired lifetime growth. Further, risk in complex life-cycles is mitigated by increasing establishment rates in each successive host. Two benefits of longer cycles are transmission and production. Longer cycles normally include smaller (and thus more abundant) first hosts that are likely to consume parasite propagules, as well as bigger (and longer-lived) definitive hosts, in which adult worms grow to larger and presumably more fecund reproductive sizes. Additional factors, like host immunity or dispersal, may also play a role, but are harder to address. Given the ubiquity of complex life-cycles, the benefits of incorporating or retaining hosts in a cycle must often exceed the costs.
The risk of a newly discovered non-native fish species in Florida (USA): Cichlasoma dimerus ([Heckel, 1840]; Family: Cichlidae) is assessed. Its tolerance to cold temperatures was experimentally evaluated and information on its biology and ecology was synthesized. In the cold-temperature tolerance experiment, temperature was lowered from 24 °C by increments of 1 °C per hour, mimicking a typical cold weather front. Fish lost equilibrium at a mean temperature of 7.8 °C and died at 4.7 °C. Those values are lower than most other non-native fishes from the state that have been experimentally evaluated, and it appears C. dimerus is the most cold-tolerant cichlid established in Florida. The combination of cold-temperature tolerance and other biological/ecological factors (e.g., adult size, reproduction and parental care, diet, habitat, and other behaviors) along with the geographic range and habitat diversity of specimens vouchered in museums, indicate C. dimerus may be able to invade many freshwater ecosystems in the state, including environmentally sensitive freshwater springs.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2022.13.2.10","usgsCitation":"Brown, M., Robins, R.H., and Schofield, P., 2022, Risk assessment of chanchita Cichlasoma dimerus (Heckel, 1840), a newly identified non-native cichlid fish in Florida: Management of Biological Invasions, v. 13, no. 2, p. 435-448, https://doi.org/10.3391/mbi.2022.13.2.10.","productDescription":"14 p.; Data Release","startPage":"435","endPage":"448","ipdsId":"IP-133716","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":448503,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2022.13.2.10","text":"Publisher Index Page"},{"id":401743,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417841,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P949CEKG"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.5947265625,\n 25.005972656239187\n ],\n [\n -79.4970703125,\n 25.005972656239187\n ],\n [\n -79.4970703125,\n 31.015278981711266\n ],\n [\n -84.5947265625,\n 31.015278981711266\n ],\n [\n -84.5947265625,\n 25.005972656239187\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Mary 0000-0002-5580-137X","orcid":"https://orcid.org/0000-0002-5580-137X","contributorId":205227,"corporation":false,"usgs":true,"family":"Brown","given":"Mary","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":844160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robins, Robert H.","contributorId":292263,"corporation":false,"usgs":false,"family":"Robins","given":"Robert","email":"","middleInitial":"H.","affiliations":[{"id":40459,"text":"Florida Museum, University of Florida","active":true,"usgs":false}],"preferred":false,"id":844161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schofield, Pam 0000-0002-8752-2797","orcid":"https://orcid.org/0000-0002-8752-2797","contributorId":216025,"corporation":false,"usgs":true,"family":"Schofield","given":"Pam","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":844162,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70255076,"text":"70255076 - 2022 - Carnivores in color: Pelt color patterns among carnivores in Idaho","interactions":[],"lastModifiedDate":"2024-06-13T11:15:44.724402","indexId":"70255076","displayToPublicDate":"2022-03-15T06:12:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Carnivores in color: Pelt color patterns among carnivores in Idaho","docAbstract":"Pelt color serves many functions from signaling to crypsis to thermoregulation and its purpose has been a lively source of debate in biology for over a century. Determining the effects of both habitat and human influences on pelt color patterns can be difficult. We made novel use of a multispecies occupancy model by defining “pelt color” as “species.” We then used this model to test predictions and estimate pelt color patterns concurrently for three carnivore species in Idaho, United States. We predicted pelt patterns of all three carnivores would be affected by environmental variables as well as human disturbance. Areas of Idaho where baiting was allowed and preferential harvest possible did not explain pelt patterns in black bears and neither did forest cover. Road density was positively associated with detection probability but negatively associated with occupancy of both black and brown pelt bears, however. Gray pelt wolves were found more often in areas with higher road densities than black wolves. As predicted, black, but not gray, wolves were positively associated with forest cover. Both red and black pelt foxes were positively associated with increasing elevation and road density. Black pelt foxes were negatively associated with forest cover, mirroring the habitat use described for native black pelt foxes. We demonstrate how using noninvasively collected data and extending multispecies occupancy models can allow biologists to study the distribution of different pelt colors in wild populations.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyab166","usgsCitation":"Ausband, D.E., and Krohner, J.M., 2022, Carnivores in color: Pelt color patterns among carnivores in Idaho: Journal of Mammalogy, v. 103, no. 3, p. 598-607, https://doi.org/10.1093/jmammal/gyab166.","productDescription":"10 p.","startPage":"598","endPage":"607","ipdsId":"IP-130703","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":448504,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyab166","text":"Publisher Index Page"},{"id":430060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"103","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krohner, Jessica M.","contributorId":338521,"corporation":false,"usgs":false,"family":"Krohner","given":"Jessica","email":"","middleInitial":"M.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":903327,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70229658,"text":"sir20225013 - 2022 - Evaluation of salinity and nutrient conditions in the Heart River Basin, North Dakota, 1970–2020","interactions":[],"lastModifiedDate":"2022-05-03T15:07:28.164535","indexId":"sir20225013","displayToPublicDate":"2022-03-14T11:12:51","publicationYear":"2022","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":"2022-5013","displayTitle":"Evaluation of Salinity and Nutrient Conditions in the Heart River Basin, North Dakota, 1970–2020","title":"Evaluation of salinity and nutrient conditions in the Heart River Basin, North Dakota, 1970–2020","docAbstract":"The Heart River Basin is predominantly an agricultural basin in western North Dakota and is approximately 3,350 square miles. The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service and the Grant County Soil Conservation District, completed a study to assess spatial and temporal patterns of water quality in the Heart River Basin. The purpose of this report is to describe the methods and results of a study to evaluate salinity and nutrients in the Heart River Basin in western North Dakota. Water-quality and streamflow data used in the study were compiled from 1970 to 2020 using the National Water Quality Monitoring Council Water Quality Portal and National Water Information System.
Changes in streamflow characteristics were investigated at three sites from 1970 to 2020, and changes in water quality were investigated at four sites from 1974 to 2019. Streamflow analysis indicated decreasing streamflow from 1970 until the late 1990s followed by increasing streamflow through 2020, with the largest increase in the 7-day minimum streamflow or base flow. For the historical water-quality trend period (1974–2019), total dissolved solids, sulfate, sodium, chloride, and sodium adsorption ratio concentrations have increased since the mid-1970s through 2019. Potassium concentrations during the historical period remained mostly constant with some small fluctuations. Calcium and magnesium concentrations increased since the mid-1970s at all sites, except for a decrease at one site between 1974 and 1999. During the recent trend period (1999–2019), increasing concentrations in total dissolved solids, sulfate, sodium, chloride, calcium, magnesium, and sodium adsorption ratios were observed across the Heart River Basin. The magnitude of the increases was smaller at tributary sites compared to main-stem sites. During the recent period, potassium was mostly constant, although small (−0.9 milligram per liter or less) decreases on tributaries and minor (1.3 milligrams per liter) increases on the main-stem sites were detected. Unlike dissolved ion concentrations, significant increases in nutrient concentrations were not detected from 1999 to 2019, but nitrate plus nitrite concentrations most likely decreased upstream from Lake Tschida.
Inverse modeling for period 1 (1974–99) in model zone 1 (Heart River reach from site 5 to site 6) had eight reasonable models that indicated the clay mineral-water interactions and dissolution of evaporites control the geochemistry. Results of the inverse modeling for period 2 (1999–2019) in model zone 1 also had eight reasonable models that indicated that the dissolution of evaporites was the major geochemical control. Results of the geochemical modeling for period 1 (1974–99) in model zone 2 (Heart River and Sweetbriar Creek reach from sites 20 and 21 to site 22) produced seven reasonable models, and the geochemical control of the system was the dissolution of sulfate evaporite minerals. Geochemical modeling results for period 2 (1999–2019) in model zone 2 produced 11 reasonable models and was also controlled by the dissolution of sulfate evaporite minerals. Differences between the two model zones indicated that geology controls some of the water-quality changes in the Heart River Basin.
Loads were estimated for total dissolved solids, sulfate, sodium, and chloride and total phosphorus. Annual loads estimated for the Heart River from 2013 through 2020 at the Heart River site upstream from Lake Tschida (site 5) and near Mandan (site 22) were generally greatest in 2014 and least in 2016 for total dissolved solids, sulfate, sodium, and chloride. Most of the annual loads of total dissolved solids, sulfate, sodium, and chloride are delivered in March through July in the Heart River at these sites and are likely from snowmelt and spring and summer rains. The mean annual yields of total dissolved solids and sodium from 2013 to 2020 generally were largest in Big Muddy Creek (site 18), whereas yields of sulfate and chloride were largest at Sweetbriar Creek (site 21) compared to the other selected sites in the Heart River Basin. Larger yields of total dissolved solids, sulfate, sodium, and chloride at sites located on Big Muddy Creek and Sweet Briar Creek in the lower Heart River Basin were likely a result of differences in geology and soils upstream from the selected sites.
A mass balance of total dissolved solids, sulfate, sodium, and chloride was estimated for the lower Heart River Basin, specifically the reach below Lake Tschida to Mandan (site 7 to site 22). Intervening flow was the largest contributor to the dissolved ion loads in the lower Heart River Basin and is an important part of understanding the transport of dissolved ions in the basin. The intervening load can include groundwater discharge, irrigation return flow, local runoff, and input from smaller ephemeral tributaries. Tributaries in the lower Heart River Basin contributed portions of the total dissolved solids, sulfate, sodium, and chloride loads at the Heart River near Mandan (site 22) that generally were proportional to the streamflow contributions.
Annual loads for total phosphorus between 2013 and 2020 at the Heart River site upstream from Lake Tschida (site 5) and near Mandan (site 22) generally were largest in 2019 and smallest in 2016. Most of the total phosphorus loads for main-stem sites 5 and 22 were transported in March, April, and June, likely from snowmelt and early summer rains. The mean annual yields of total phosphorus for 2013–20 were largest on the main-stem site upstream from Lake Tschida (site 5) and Sweetbriar Creek (site 21), whereas the smallest yields were in Big Muddy Creek (site 18). Much of the phosphorus that enters Lake Tschida from the upper basin does not get transported downstream to the lower basin, and much of the phosphorus in the lower basin was attributed to intervening flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225013","collaboration":"Prepared in cooperation with the Department of Agriculture Natural Resources Conservation Service and Grant County Soil Conservation District","usgsCitation":"Tatge, W.S., Nustad, R.A., and Galloway, J.M., 2022, Evaluation of salinity and nutrient conditions in the Heart River Basin, North Dakota, 1970–2020: U.S. Geological Survey Scientific Investigations Report 2022–5013, 76 p., https://doi.org/10.3133/sir20225013.","productDescription":"Report: ix, 76; Data Release; Dataset","numberOfPages":"90","onlineOnly":"Y","ipdsId":"IP-131163","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":398527,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225013/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":397040,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5013/images"},{"id":397039,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5013/sir20225013.XML"},{"id":397038,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5013/sir20225013.pdf","text":"Report","size":"21.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5013"},{"id":397037,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5013/coverthb.jpg"},{"id":397042,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":397041,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P987APZ8","text":"USGS data release","linkHelpText":"Data and scripts used in water-quality trend and load analysis in the Heart River Basin, North Dakota, 1970–2020"}],"country":"United States","state":"North Dakota","otherGeospatial":"Heart River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.2769775390625,\n 46.27863122156088\n ],\n [\n -100.8160400390625,\n 46.27863122156088\n ],\n [\n -100.8160400390625,\n 47.25\n ],\n [\n -103.2769775390625,\n 47.25\n ],\n [\n -103.2769775390625,\n 46.27863122156088\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
You can learn a lot about rivers, lakes, estuaries, and oceans by looking down at them from the sky. Scientists use a technique called remote sensing to measure the amount of light or heat energy reflected and emitted from the Earth. Sensors can be on satellites or mounted on airplanes, helicopters, or drones. Scientists use this information to map the quality of water in the San Francisco Bay-Delta estuary. Remote sensing helps scientists see where and when there might be problems for human health or for the plants and animals living in the estuary.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frym.2022.619716","usgsCitation":"Mejia, F.H., Torgersen, C.E., and Fichot, C.G., 2022, Keeping an eye on water quality from the sky: Frontiers for Young Minds, HTML Document, https://doi.org/10.3389/frym.2022.619716.","productDescription":"HTML Document","ipdsId":"IP-123673","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448507,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frym.2022.619716","text":"Publisher Index Page"},{"id":398217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay-Delta estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.55249023437501,\n 37.32430451813815\n ],\n [\n -121.57470703125,\n 37.32430451813815\n ],\n [\n -121.57470703125,\n 38.244651696093634\n ],\n [\n -122.55249023437501,\n 38.244651696093634\n ],\n [\n -122.55249023437501,\n 37.32430451813815\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Mejia, Francine H. 0000-0003-4447-231X","orcid":"https://orcid.org/0000-0003-4447-231X","contributorId":214345,"corporation":false,"usgs":true,"family":"Mejia","given":"Francine","email":"","middleInitial":"H.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":839741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":839742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fichot, Cedric G","contributorId":289767,"corporation":false,"usgs":false,"family":"Fichot","given":"Cedric","email":"","middleInitial":"G","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":839743,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230174,"text":"70230174 - 2022 - Are little brown bats (Myotis lucifugus) impacted by dietary exposure to microcystin?","interactions":[],"lastModifiedDate":"2022-04-01T21:56:27.062893","indexId":"70230174","displayToPublicDate":"2022-03-14T09:18:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Are little brown bats (Myotis lucifugus ) impacted by dietary exposure to microcystin?","title":"Are little brown bats (Myotis lucifugus) impacted by dietary exposure to microcystin?","docAbstract":"The cyanobacterium, Microcystis aeruginosa, can produce the hepatotoxin microcystin. When toxic M. aeruginosa overwinters in the sediments of lakes, it may be ingested by aquatic insects and bioaccumulate in nymphs of Hexagenia mayflies. When volant Hexagenia emerge from lakes to reproduce, they provide an abundant, albeit temporary, food source for many terrestrial organisms including bats. Little brown bats, Myotis lucifugus, feed opportunistically on aquatic insects including Hexagenia. To determine if microcystin moves from aquatic to terrestrial ecosystems via trophic transfer, we combined a dietary analysis with the quantification of microcystin in bat livers and feces. In June 2014, coincident with the local Hexagenia emergence, bat feces were collected from underneath a maternity roost near Little Traverse Lake (Leelanau County, Michigan, USA). Insects in the diet were identified via molecular analyses of fecal pellets from the roost and from individual bats. Livers and feces were collected from 19 female M. lucifugus, and the concentrations of microcystin in these liver tissues and feces were measured using an enzyme-linked immunosorbent assay (ELISA) and liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We show that the majority of the bats’ diets consisted of aquatic insects and that microcystin was detected in high concentrations (up to 129.9 μg/kg dw) in the bat feces by ELISA. Histopathological examination of three bat livers with the highest concentrations of microcystin showed no evidence of phycotoxicosis, indicating that M. lucifugus may not be immediately affected by the ingestion of microcystin. Future work could examine whether bats suffer delayed physiological effects from ingestion of microcystin.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.hal.2022.102221","usgsCitation":"Jones, D.N., Boyer, G.L., Lankton, J.S., Woller-Skar, M., and Russell, A.L., 2022, Are little brown bats (Myotis lucifugus) impacted by dietary exposure to microcystin?: Harmful Algae, v. 114, 102221, 9 p., https://doi.org/10.1016/j.hal.2022.102221.","productDescription":"102221, 9 p.","ipdsId":"IP-134089","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":435926,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E2VU1Y","text":"USGS data release","linkHelpText":"Histopathology of little brown bats (Myotis lucifugus) collected from a maternity roost in Leelanau County, Michigan, USA, in June 2014"},{"id":397974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","county":"Leelanau","otherGeospatial":"Little Traverse Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.86759567260742,\n 44.91449249713902\n ],\n [\n -85.81506729125977,\n 44.91449249713902\n ],\n [\n -85.81506729125977,\n 44.930901285577555\n ],\n [\n -85.86759567260742,\n 44.930901285577555\n ],\n [\n -85.86759567260742,\n 44.91449249713902\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"114","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Devon N.","contributorId":289583,"corporation":false,"usgs":false,"family":"Jones","given":"Devon","email":"","middleInitial":"N.","affiliations":[{"id":62195,"text":"Department of Biology, Grand Valley State University, Allendale, Michigan, USA","active":true,"usgs":false}],"preferred":false,"id":839367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyer, Gregory L. 0000-0003-4490-5461","orcid":"https://orcid.org/0000-0003-4490-5461","contributorId":289584,"corporation":false,"usgs":false,"family":"Boyer","given":"Gregory","email":"","middleInitial":"L.","affiliations":[{"id":62197,"text":"Department of Chemistry, State University of New York, Syracuse, College of Environmental Science and Forestry, Syracuse, New York, USA","active":true,"usgs":false}],"preferred":false,"id":839368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":839369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woller-Skar, Megan","contributorId":289585,"corporation":false,"usgs":false,"family":"Woller-Skar","given":"Megan","email":"","affiliations":[{"id":62195,"text":"Department of Biology, Grand Valley State University, Allendale, Michigan, USA","active":true,"usgs":false}],"preferred":false,"id":839370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russell, Amy L.","contributorId":143710,"corporation":false,"usgs":false,"family":"Russell","given":"Amy","email":"","middleInitial":"L.","affiliations":[{"id":15305,"text":"Grand Valley State University","active":true,"usgs":false}],"preferred":false,"id":839371,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229702,"text":"70229702 - 2022 - Land management explains major trends in forest structure and composition over the last millennium in California’s Klamath Mountains","interactions":[],"lastModifiedDate":"2022-03-15T13:57:50.207002","indexId":"70229702","displayToPublicDate":"2022-03-14T08:48:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Land management explains major trends in forest structure and composition over the last millennium in California’s Klamath Mountains","docAbstract":"For millennia, forest ecosystems in California have been shaped by fire from both natural processes and Indigenous land management, but the notion of climatic variation as a primary controller of the pre-colonial landscape remains pervasive. Understanding the relative influence of climate and Indigenous burning on the fire regime is key because contemporary forest policy and management are informed by historical baselines. This need is particularly acute in California, where 20th-century fire suppression, coupled with a warming climate, has caused forest densification and increasingly large wildfires that threaten forest ecosystem integrity and management of the forests as part of climate mitigation efforts. We examine climatic versus anthropogenic influence on forest conditions over 3 millennia in the western Klamath Mountains—the ancestral territories of the Karuk and Yurok Tribes—by combining paleoenvironmental data with Western and Indigenous knowledge. A fire regime consisting of tribal burning practices and lightning were associated with long-term stability of forest biomass. Before Euro-American colonization, the long-term median forest biomass was between 104 and 128 Mg/ha, compared to values over 250 Mg/ha today. Indigenous depopulation after AD 1800, coupled with 20th-century fire suppression, likely allowed biomass to increase, culminating in the current landscape: a closed Douglas fir–dominant forest unlike any seen in the preceding 3,000 y. These findings are consistent with precontact forest conditions being influenced by Indigenous land management and suggest large-scale interventions could be needed to return to historic forest biomass levels.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2116264119","usgsCitation":"Knight, C.A., Anderson, L., Bunting, M.J., Champagne, M.R., Clayburn, R.M., Crawford, J.N., Klimaszewski-Patterson, A., Knapp, E.E., Lake, F.K., Mensing, S.A., Wahl, D., Wanket, J., Watts-Tobin, A., Potts, M.D., and Battles, J.J., 2022, Land management explains major trends in forest structure and composition over the last millennium in California’s Klamath Mountains: Proceedings of the National Academy of Sciences, v. 119, no. 12, e2116264119, 11 p., https://doi.org/10.1073/pnas.2116264119.","productDescription":"e2116264119, 11 p.","ipdsId":"IP-129584","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":448509,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2116264119","text":"Publisher Index Page"},{"id":397104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Klamath Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.88046264648438,\n 41.17555303422341\n ],\n [\n -123.585205078125,\n 41.17555303422341\n ],\n [\n -123.585205078125,\n 41.572306568724365\n ],\n [\n -123.88046264648438,\n 41.572306568724365\n ],\n [\n -123.88046264648438,\n 41.17555303422341\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"119","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Knight, Clarke Alexandra 0000-0003-0002-6959","orcid":"https://orcid.org/0000-0003-0002-6959","contributorId":288487,"corporation":false,"usgs":true,"family":"Knight","given":"Clarke","email":"","middleInitial":"Alexandra","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":838001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Lysanna 0000-0001-5650-9744 landerson@usgs.gov","orcid":"https://orcid.org/0000-0001-5650-9744","contributorId":5339,"corporation":false,"usgs":true,"family":"Anderson","given":"Lysanna","email":"landerson@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":838002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunting, M. Jane 0000-0002-3152-5745","orcid":"https://orcid.org/0000-0002-3152-5745","contributorId":248213,"corporation":false,"usgs":false,"family":"Bunting","given":"M.","email":"","middleInitial":"Jane","affiliations":[{"id":49826,"text":"Department of Geography, Geology and Environment, University of Hull, Cottingham Road, Hull, HU6 7RX UK","active":true,"usgs":false}],"preferred":false,"id":838003,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Champagne, Marie Rhondelle 0000-0001-8236-3910","orcid":"https://orcid.org/0000-0001-8236-3910","contributorId":248214,"corporation":false,"usgs":true,"family":"Champagne","given":"Marie","email":"","middleInitial":"Rhondelle","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":838004,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clayburn, Rosie M.","contributorId":288488,"corporation":false,"usgs":false,"family":"Clayburn","given":"Rosie","email":"","middleInitial":"M.","affiliations":[{"id":61774,"text":"Yurok Tribe’s Cultural Resources Manager","active":true,"usgs":false}],"preferred":false,"id":838005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crawford, Jeffrey N.","contributorId":288489,"corporation":false,"usgs":false,"family":"Crawford","given":"Jeffrey","email":"","middleInitial":"N.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":838006,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Klimaszewski-Patterson, Anna 0000-0001-7765-8802","orcid":"https://orcid.org/0000-0001-7765-8802","contributorId":288490,"corporation":false,"usgs":false,"family":"Klimaszewski-Patterson","given":"Anna","email":"","affiliations":[{"id":39151,"text":"California State University Sacramento","active":true,"usgs":false}],"preferred":false,"id":838007,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Knapp, Eric E. 0000-0002-6991-8157","orcid":"https://orcid.org/0000-0002-6991-8157","contributorId":288491,"corporation":false,"usgs":false,"family":"Knapp","given":"Eric","email":"","middleInitial":"E.","affiliations":[{"id":61775,"text":"US Forest Service Pacific Southwest Research Station","active":true,"usgs":false}],"preferred":false,"id":838008,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lake, Frank K.","contributorId":288492,"corporation":false,"usgs":false,"family":"Lake","given":"Frank","email":"","middleInitial":"K.","affiliations":[{"id":61775,"text":"US Forest Service Pacific Southwest Research Station","active":true,"usgs":false}],"preferred":false,"id":838009,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mensing, Scott A. 0000-0003-4302-112X","orcid":"https://orcid.org/0000-0003-4302-112X","contributorId":288493,"corporation":false,"usgs":false,"family":"Mensing","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":838010,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wahl, David 0000-0002-0451-3554","orcid":"https://orcid.org/0000-0002-0451-3554","contributorId":206113,"corporation":false,"usgs":true,"family":"Wahl","given":"David","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":838011,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wanket, James","contributorId":248216,"corporation":false,"usgs":false,"family":"Wanket","given":"James","email":"","affiliations":[{"id":49829,"text":"Department of Geography, California State University, Sacramento, Sacramento, California 95819 USA","active":true,"usgs":false}],"preferred":false,"id":838012,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Watts-Tobin, Alex","contributorId":288494,"corporation":false,"usgs":false,"family":"Watts-Tobin","given":"Alex","email":"","affiliations":[{"id":61776,"text":"Karuk Tribe’s Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":838013,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Potts, Matthew D. 0000-0001-7442-3944","orcid":"https://orcid.org/0000-0001-7442-3944","contributorId":248215,"corporation":false,"usgs":false,"family":"Potts","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":49825,"text":"Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, California 94720 USA","active":true,"usgs":false}],"preferred":false,"id":838014,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Battles, John J.","contributorId":102006,"corporation":false,"usgs":false,"family":"Battles","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":838015,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70229660,"text":"70229660 - 2022 - Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights","interactions":[],"lastModifiedDate":"2022-03-14T13:57:19.916542","indexId":"70229660","displayToPublicDate":"2022-03-14T08:44:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights","docAbstract":"Rapid expansion of wind energy development across the world has highlighted the need to better understand turbine-caused avian mortality. The risk to golden eagles (Aquila chrysaetos) is of particular concern due to their small population size and conservation status. Golden eagles subsidize their flight in part by soaring in orographic updrafts, which can place them in conflict with wind turbines utilizing the same low-altitude wind resource. Understanding the behavior of soaring raptors in varying atmospheric conditions can therefore be relevant to predicting and mitigating their risk of collision. We present a predictive movement model that simulates individual paths of golden eagles during directional flight (such as migration) that is subsidized by orographic updraft. We modeled eagles in a 50 km by 50 km study area in Wyoming containing three wind power plants with documented golden eagle collisions with turbines. The movement model is applicable to any region where ground elevation is known at turbine scale (
Sequence stratigraphy provides a unifying framework for integrating diverse observations to interpret sedimentary basin evolution; however, key time assumptions about stratigraphic elements spanning hundreds of kilometers are rarely quantified. We integrate new detrital zircon U-Pb (DZ) dates from 28 samples with seismic mapping to establish a chronostratigraphic framework across 800 km and ~20 m.y. for the middle-Cretaceous Torok-Nanushuk clinothem of Arctic Alaska (USA). Shelf-margin DZ dates indicate continent-scale sediment routing with Russian Chukotka provenance and provide reliable maximum depositional ages derived from arc volcanism. Shelf-margin advance rates display a clear relationship to toplap trajectories and provide empirical support for long-held inferences linking sediment supply to margin architecture. Two distinct shelf-margin growth regimes are evident: (1) a ca. 115–107 Ma phase of rapid ~50 km/m.y. shelf advance rates with mainly progradational trajectories; and (2) a ca. 107–98 Ma phase of moderate ~13 km/m.y. shelf advance rates with progradational-retrogradational-aggradational trajectories. We established a subsequent shelf–to–deep water correlation by independently dating ca. 98–95 Ma low shelf accommodation and basin-floor deposition as far as 240 km east that indicate lowstand shedding and a change to localized routing with Brooks Range provenance. Finally, we dated a ca. 95 Ma basin-wide transgression at deep-water to shelfal settings across 350 km that exhibits apparent synchroneity consistent with an event-significant surface. In one of the world’s largest foreland-basin clinothems, our work constrains the timing and duration of key depositional elements to test large-scale sequence stratigraphic assumptions, enables reliable correlation and quantification of sediment dynamics across 800 km, and captures the chronology of a giant regressive-transgressive cycle.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G49118.1","usgsCitation":"Lease, R.O., Houseknecht, D.W., and Kylander-Clark, A.R., 2022, Quantifying large-scale continental shelf margin growth and dynamics across mid-Cretaceous Arctic Alaska with detrital zircon U-Pb dating: Geology, v. 50, no. 5, p. 620-625, https://doi.org/10.1130/G49118.1.","productDescription":"6 p.","startPage":"620","endPage":"625","ipdsId":"IP-135413","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":448513,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g49118.1","text":"Publisher Index Page"},{"id":435927,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F8BHTN","text":"USGS data release","linkHelpText":"U-Pb Isotopic Data and Ages of Detrital Zircon and Volcanic Zircon Grains from the Torok and Nanushuk Formations, Arctic Alaska, 2021"},{"id":397055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -140.99853515625,\n 69.65708627301174\n ],\n [\n -139.81201171874997,\n 73.23937702441908\n ],\n [\n -162.59765625,\n 73.02900629225599\n ],\n [\n -169.8046875,\n 69.17037257214531\n ],\n [\n -163.828125,\n 67.05887024878373\n ],\n [\n -160.6640625,\n 67.30597574414466\n ],\n [\n -157.58789062499997,\n 67.04173496919447\n ],\n [\n -154.95117187499997,\n 66.93866882358137\n ],\n [\n -151.7431640625,\n 67.12729044909526\n ],\n [\n -147.3046875,\n 67.53377157140451\n ],\n [\n -145.1513671875,\n 68.46379955520322\n ],\n [\n -141.0205078125,\n 68.86351700272681\n ],\n [\n -140.99853515625,\n 69.65708627301174\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-03-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":837863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":837864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kylander-Clark, Andrew R. C.","contributorId":212897,"corporation":false,"usgs":false,"family":"Kylander-Clark","given":"Andrew","email":"","middleInitial":"R. C.","affiliations":[],"preferred":false,"id":837865,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70248934,"text":"70248934 - 2022 - A physical interpretation of asymmetric growth and decay of the geomagnetic dipole moment","interactions":[],"lastModifiedDate":"2023-09-27T12:25:01.645868","indexId":"70248934","displayToPublicDate":"2022-03-14T07:24:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"A physical interpretation of asymmetric growth and decay of the geomagnetic dipole moment","docAbstract":"Observations of relative paleointensity reveal several forms of asymmetry in the time dependence of the virtual axial dipole moment (VADM). Slow decline of the VADM into a reversal is often followed by a more rapid rise back to a quasi-steady state. Asymmetry is also observed in trends of VADM during times of stable polarity. Trends of increasing VADM over time intervals of a few 10s of kyr are more intense and less frequent than decreasing trends. We examine the origin of this behavior using stochastic models. The usual (Langevin) model can account for asymmetries during reversals, but it cannot reproduce the observed asymmetry in trends during stable polarity. Better agreement is achieved with a different class of stochastic models in which the dipole is generated by a series of impulsive events in time. The timing of each event occurs randomly as a Poisson process and the amplitude is also randomly distributed. Predicted trends replicate the observed asymmetry when the generation events are large and the recurrence time is long (typically longer than 3 kyr). Large and infrequent generation events argue against dipole generation by small-scale turbulent flow. Instead, the observations favor a mechanism that relies on expulsion of poloidal magnetic field from the core.
Despite tectonic conditions and atmospheric CO2 levels (pCO2) similar to those of present-day, geological reconstructions from the mid-Pliocene (3.3-3.0 Ma) document high lake levels in the Sahel and mesic conditions in subtropical Eurasia, suggesting drastic reorganizations of subtropical terrestrial hydroclimate during this interval. Here, using a compilation of proxy data and multi-model paleoclimate simulations, we show that the mid-Pliocene hydroclimate state is not driven by direct CO2 radiative forcing but by a loss of northern high-latitude ice sheets and continental greening. These ice sheet and vegetation changes are long-term Earth system feedbacks to elevated pCO2. Further, the moist conditions in the Sahel and subtropical Eurasia during the mid-Pliocene are a product of enhanced tropospheric humidity and a stationary wave response to the surface warming pattern, which varies strongly with land cover changes. These findings highlight the potential for amplified terrestrial hydroclimate responses over long timescales to a sustained CO2 forcing.
Castration is commonly used to control the behavior of companion animals and livestock, yet there have been few longitudinal studies of its effects. Despite the ubiquity of this surgery in ridden horses, the effects of castration (termed gelding in horses) have rarely been examined in a reproductive population. We tested effects of gelding on maintenance and social behaviors of individuals pre- and post-gelding, and in comparison to intact control adult males (2 to >16 years old) in both harem and bachelor status, we then tested how gelding affected association with mares (i.e., maintenance of a harem group) compared to intact controls, and any effects on bachelor social associations. We further explored any effects on foaling rate to assess potential impacts on population growth rate. We conducted this study over four years (2017–2020) at two Herd Management Areas (HMAs) in western Utah, USA: Conger and Frisco. We conducted demographic observations year round at both HMAs to record survival and foaling rate. We additionally recorded behavioral observations at Conger HMA. In December 2017, 27 adult males from Conger (42% of adult males in the population) were gelded and returned to the range with their social groups. Due to pre-treatment observations we were able to compare stallions of known status pre- and post-treatment (harem or bachelor), as well as gelded and intact males. We had no morbidity or mortality related to the gelding surgery and all males maintained good body condition throughout the study. There was no effect of gelding on maintenance behaviors (feeding, moving, and standing). There was no effect of gelding on frequency of agonistic behavior, and a non-significant tendency for less reproductive behavior in geldings; geldings showed more affiliative and less marking behavior. Age class and/or social status were better predictors of behavior than gelding. Over time fewer geldings maintained a harem, and their harem size declined during the study. Horses that were bachelors when gelded tended to remain as bachelors, whereas intact bachelors of the same cohort mostly attained a harem. Foaling rate at Conger was reduced in the year following treatment, but then returned to pre-treatment levels. From a welfare perspective gelding is safe to use in feral horses and has minimal effects on horse behavior and social interactions in a reproductive herd. Effectiveness for population growth control would likely require a larger proportion of males in the population to be castrated for longer-term effects on foaling rate.
Intense geoelectric fields during geomagnetic storms drive geomagnetically induced currents in power grids and other infrastructure, yet there are limited direct measurements of these storm-time geoelectric fields. Moreover, most previous studies examining storm-time geoelectric fields focused on single events or small geographic regions, making it difficult to determine the typical source(s) of intense geoelectric fields. We perform the first comparative analysis of (a) the sources of intense geoelectric fields over multiple geomagnetic storms, (b) using 1-s cadence geoelectric field measurements made at (c) magnetotelluric survey sites distributed widely across the United States. Temporally localized intense perturbations in measured geoelectric fields with prominences (a measure of the relative amplitude of geoelectric field enhancement above the surrounding signal) of at least 500 mV/km were detected during geomagnetic storms with Dst minima (Dstmin) of less than −100 nT from 2006 to 2019. Most of the intense geoelectric fields were observed in resistive regions with magnetic latitudes greater than 55° even though we have 167 sites located at lower latitudes during geomagnetic storms of −200 nT ≤ Dstmin < −100 nT. Our study indicates intense short-lived (<1 min) and geoelectric field perturbations with periods on the order of 1–2 min are common. Most of these perturbations cannot be resolved with 1-min data because they correspond to higher frequency or impulsive phenomena that vary on timescales shorter than that sampling interval. The sources of geomagnetic perturbations inducing these intense geoelectric fields include interplanetary shocks, interplanetary magnetic field turnings, substorms, and ultralow frequency waves.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021SW002967","usgsCitation":"Shi, X., Hartinger, M.D., Baker, J.B., Murphy, B.S., Bedrosian, P.A., Kelbert, A., and Rigler, E., 2022, Characteristics and sources of intense geoelectric fields in the United States: Comparative analysis of multiple geomagnetic storms: Space Weather, v. 20, no. 4, e2021SW002967, 18 p., https://doi.org/10.1029/2021SW002967.","productDescription":"e2021SW002967, 18 p.","ipdsId":"IP-137255","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":448523,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021sw002967","text":"Publisher Index Page"},{"id":406954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.158203125,\n 32.47269502206151\n ],\n [\n -114.169921875,\n 32.76880048488168\n ],\n [\n -114.169921875,\n 34.52466147177172\n ],\n [\n -119.35546875000001,\n 38.75408327579141\n ],\n [\n -119.794921875,\n 39.30029918615029\n ],\n [\n -101.953125,\n 39.027718840211605\n ],\n [\n -98.26171875,\n 38.8225909761771\n ],\n [\n -97.646484375,\n 37.37015718405753\n ],\n [\n -94.130859375,\n 36.73888412439431\n ],\n [\n -90,\n 36.94989178681327\n ],\n [\n -88.857421875,\n 35.817813158696616\n ],\n [\n -87.451171875,\n 33.063924198120645\n ],\n [\n -84.90234375,\n 29.916852233070173\n ],\n [\n -81.03515625,\n 30.44867367928756\n ],\n [\n -76.37695312499999,\n 35.17380831799959\n ],\n [\n -73.037109375,\n 40.713955826286046\n ],\n [\n -70.3125,\n 41.64007838467894\n ],\n [\n -70.48828125,\n 43.004647127794435\n ],\n [\n -66.884765625,\n 44.84029065139799\n ],\n [\n -67.587890625,\n 46.92025531537451\n ],\n [\n -68.37890625,\n 47.45780853075031\n ],\n [\n -69.9609375,\n 47.45780853075031\n ],\n [\n -70.751953125,\n 45.521743896993634\n ],\n [\n -75.05859375,\n 44.77793589631623\n ],\n [\n -77.080078125,\n 43.32517767999296\n ],\n [\n -79.013671875,\n 43.197167282501276\n ],\n [\n -81.298828125,\n 41.83682786072714\n ],\n [\n -82.96875,\n 41.376808565702355\n ],\n [\n -82.79296874999999,\n 42.68243539838623\n ],\n [\n -82.79296874999999,\n 44.84029065139799\n ],\n [\n -84.638671875,\n 46.73986059969267\n ],\n [\n -90,\n 48.10743118848039\n ],\n [\n -92.021484375,\n 48.16608541901253\n ],\n [\n -95.537109375,\n 48.748945343432936\n ],\n [\n -95.712890625,\n 49.095452162534826\n ],\n [\n -101.6015625,\n 48.980216985374994\n ],\n [\n -109.77539062499999,\n 49.38237278700955\n ],\n [\n -110.0390625,\n 58.12431960569374\n ],\n [\n -119.970703125,\n 59.84481485969105\n ],\n [\n -120.234375,\n 53.64463782485651\n ],\n [\n -121.28906250000001,\n 50.17689812200107\n ],\n [\n -123.22265625000001,\n 49.095452162534826\n ],\n [\n -123.22265625000001,\n 48.10743118848039\n ],\n [\n -125.068359375,\n 48.40003249610685\n ],\n [\n -124.18945312500001,\n 46.437856895024204\n ],\n [\n -124.541015625,\n 43.26120612479979\n ],\n [\n -124.8046875,\n 40.84706035607122\n ],\n [\n -123.662109375,\n 37.71859032558816\n ],\n [\n -120.673828125,\n 34.52466147177172\n ],\n [\n -117.158203125,\n 32.47269502206151\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-04-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Shi, Xueling 0000-0001-8425-8241","orcid":"https://orcid.org/0000-0001-8425-8241","contributorId":296644,"corporation":false,"usgs":false,"family":"Shi","given":"Xueling","email":"","affiliations":[{"id":64114,"text":"Virginia Tech; NCAR High Altitude Observatory","active":true,"usgs":false}],"preferred":false,"id":852080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartinger, Michael D 0000-0002-2643-2202","orcid":"https://orcid.org/0000-0002-2643-2202","contributorId":296645,"corporation":false,"usgs":false,"family":"Hartinger","given":"Michael","email":"","middleInitial":"D","affiliations":[{"id":48422,"text":"Space Science Institute","active":true,"usgs":false}],"preferred":false,"id":852081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, Joseph B. H. 0000-0001-6255-3039","orcid":"https://orcid.org/0000-0001-6255-3039","contributorId":296646,"corporation":false,"usgs":false,"family":"Baker","given":"Joseph","email":"","middleInitial":"B. H.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":852082,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Benjamin Scott 0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":242928,"corporation":false,"usgs":true,"family":"Murphy","given":"Benjamin","email":"","middleInitial":"Scott","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":852083,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":852084,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":852085,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rigler, Erin (Josh) 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":156385,"corporation":false,"usgs":true,"family":"Rigler","given":"Erin (Josh)","email":"erigler@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":852086,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237849,"text":"70237849 - 2022 - Mechanisms for retention of low molecular weight organic carbon varies with soil depth at a coastal prairie ecosystem","interactions":[],"lastModifiedDate":"2022-10-26T12:23:06.994149","indexId":"70237849","displayToPublicDate":"2022-03-12T07:20:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3416,"text":"Soil Biology and Biochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms for retention of low molecular weight organic carbon varies with soil depth at a coastal prairie ecosystem","docAbstract":"Though primary sources of carbon (C) to soil are plant inputs (e.g., rhizodeposits), the role of microorganisms as mediators of soil organic carbon (SOC) retention is increasingly recognized. Yet, insufficient knowledge of sub-soil processes complicates attempts to describe microbial-driven C cycling at depth as most studies of microbial-mineral-C interactions focus on surface horizons. We leveraged a well-studied paleo-marine terrace (90 ka) located near Santa Cruz, CA, to characterize the short-term (days to weeks) and intermediate-term (months to years) fate of two low molecular weight organic carbon. compounds at three depths in the soil profile (∼25 cm, A horizon; ∼75 cm A/B transition; and ∼125 cm, B horizon). We employed isotopically-labeled glucose (GLU) and oxalic acid (OXA) to represent two common classes of rhizodeposits: carbohydrates and organic acids. Using a combination of laboratory (9 d) and field (490 d) incubations, we traced the fate of GLU-C and OXA-C through dissolved-, metal-associated-, and microbially-respired CO2 and bulk SOC pools. Our results suggest new SOC retention (i.e., defined as 13C label identified in solid or aqueous fractions) over intermediate time frames (490 d) is correlated with patterns in short-term (9 d) cycling dynamics, which in turn is related to the theoretical efficiency by which microorganisms process each substrate. For all horizons (A, A/B, and B) GLU-C was converted to CO2 more quickly than OXA-C with modeled decomposition rates ∼2–4 times faster for GLU depending on microbial density (higher in A than B horizon). The faster decomposition rates of GLU-C increased fractional recovery (0.399 ± 0.026 to 0.504 ± 0.030 for GLU-C) compared to OXA-C (0.035 ± 0.003 to 0.127 ± 0.010) among all horizons in our field experiment (490 d). Though the overall proportion of GLU-C recovered in solid fractions did not vary significantly with horizon, based on 13C recovered in aqueous fractions the apparent mechanism for retention did. After the 9-d laboratory incubation, fractional recovery for GLU-C among C pools associated with microbial biomass was almost 20× higher than OXA-C (0.192 versus 0.010, respectively across all horizons). More than a year later, 43–46% of GLU-C retained in the field incubation was extractable with a neutral salt (representing a pool of soil C residing within or available to microbial biomass) among A and A/B horizons, while only 6% of retained GLU-C was similarly extractable in the B horizon. Thus, it appears among depths with higher microbial density (A, A/B horizons), anabolic recycling is the most likely process contributing to the persistence of glucose C, whereas abiotic sinks contributed more to intermediate-term stability for GLU-C in the B horizon. By contrast, most OXA-C was lost, presumably as CO2, over the short-term from the A and A/B horizons (fractional recovery: 0.136 ± 0.011 and 0.091 ± 0.002, respectively). However, though substantially lower than GLU-C recovered at the conclusion of our field experiment, the fraction of oxalic acid C retained in the B horizon over both short- (0.72 ± 0.037) and intermediate-time (0.127 ± 0.010) frames was several-fold higher than for overlying horizons. The specific process(es) (e.g., more efficient microbial utilization, metal-organic complexation, direct adsorption to the mineral matrix, etc.) contributing to higher retention for OXA-C at depth are discussed but remain unresolved.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.soilbio.2022.108601","usgsCitation":"McFarland, J., Lawrence, C., Creamer, C., Schulz, M., Conaway, C., Peek, S., Waldrop, M., Sevilgen, S.N., and Haw, M., 2022, Mechanisms for retention of low molecular weight organic carbon varies with soil depth at a coastal prairie ecosystem: Soil Biology and Biochemistry, v. 168, 108601, 14 p., https://doi.org/10.1016/j.soilbio.2022.108601.","productDescription":"108601, 14 p.","ipdsId":"IP-133200","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":448524,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.soilbio.2022.108601","text":"Publisher Index Page"},{"id":435929,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98AD5H5","text":"USGS data release","linkHelpText":"Short vs intermediate-term fate of glucose and oxalic acid in surface and subsurface soils of a coastal grassland near Santa Cruz California"},{"id":408746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"168","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McFarland, Jack 0000-0001-9672-8597","orcid":"https://orcid.org/0000-0001-9672-8597","contributorId":214819,"corporation":false,"usgs":true,"family":"McFarland","given":"Jack","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":855854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Corey 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":219251,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":855855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Creamer, Courtney 0000-0001-8270-9387","orcid":"https://orcid.org/0000-0001-8270-9387","contributorId":201952,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":855856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":3720,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie S.","email":"mschulz@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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2022 - Detecting algal toxins and organic contaminants of concern in the environment","interactions":[],"lastModifiedDate":"2022-03-14T10:46:43.542315","indexId":"fs20223009","displayToPublicDate":"2022-03-11T14:11:31","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3009","displayTitle":"Detecting Algal Toxins and Organic Contaminants of Concern in the Environment","title":"Detecting algal toxins and organic contaminants of concern in the environment","docAbstract":"The U.S. Geological Survey (USGS) Kansas Water Science Center Organic Geochemistry Research Laboratory (OGRL) was established in 1987. The OGRL is a multidisciplinary program that contributes knowledge about the distribution, fate, transport, and effects of new and understudied organic compounds that may affect human health and (or) ecosystems. The OGRL consists of two units: Algal and Other Environmental Toxins Unit and Environmental Organic Chemistry Unit. The OGRL does independent and collaborative research, develops robust analytical methods, and provides fee-for-service analytical laboratory analyses.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223009","usgsCitation":"Dietze, J.E., Lane, R.F., Loftin, K.A., Tush, D.L., and Wilson, M.C., 2022, Detecting algal toxins and organic contaminants of concern in the environment: U.S. Geological Survey Fact Sheet 2022–3009, 2 p., https://doi.org/10.3133/fs20223009.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-120628","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":397001,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3009/fs20223009.XML"},{"id":397000,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3009/fs20223009.pdf","text":"Report","size":"9.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3009"},{"id":396999,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3009/coverthb.jpg"},{"id":397002,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3009/images"}],"contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
This systematic assessment of occurrence for 85 volatile organic compounds (VOCs) in raw (untreated) groundwater used for public supply across the United States (U.S.), which includes 43 compounds not previously monitored by national studies, relates VOC occurrence to explanatory factors and assesses VOC detections in a human-health context. Samples were collected in 2013 through 2019 from 1537 public-supply wells in aquifers representing 78% of the volume pumped for public drinking-water supply. Laboratory detection limits for VOCs generally were less than 0.1 μg/L. Detections were reported for 36% of the sampled principal-aquifer area (38% of sampled wells) and were most common in wells in shallow, unconfined aquifers in urban areas that produce high proportions of modern-age and oxic groundwater. The disinfection by-product trichloromethane (chloroform) was the most commonly detected VOC associated primarily with anthropogenic sources (24% of the sampled area, 25% of sampled wells), followed by the gasoline oxygenate methyl tert-butyl ether (8.4% of area, 11% of wells). Carbon disulfide (12% of area, 14% of wells) was examined separately because of likely substantial contributions from natural sources. Newly monitored VOCs were each detected in <1% of the sampled area. Although detections of 1,4-dioxane in this first national study of its occurrence in raw groundwater were rare, measured concentrations exceeded the most stringent (non-enforceable) human-health benchmark in 0.5% of the sampled area (9 wells). Two wells had exceedances of enforceable benchmarks for tetrachloroethylene and trichloroethylene, and 50 wells total (representing 2.0% of the sampled area, 3.3% of sampled wells) had combined VOC concentrations exceeding 10% of benchmarks of any type. Compared with previous national findings, this study reports lower rates of VOC detection, but confirms widespread anthropogenic influence on groundwater used for public supply, with relatively few concentrations of individual VOCs or mixtures that approach or exceed human-health benchmarks.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.154313","usgsCitation":"Bexfield, L.M., Belitz, K., Fram, M.S., and Lindsey, B.D., 2022, Volatile organic compounds in groundwater used for public supply across the United States: Occurrence, explanatory factors, and human-health context: Science of the Total Environment, v. 827, 154313, 12 p., https://doi.org/10.1016/j.scitotenv.2022.154313.","productDescription":"154313, 12 p.","ipdsId":"IP-132315","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467192,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2022.154313","text":"Publisher Index Page"},{"id":435930,"rank":0,"type":{"id":30,"text":"Data 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]\n}","volume":"827","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":837959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":837961,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229986,"text":"70229986 - 2022 - The use of continuous sediment-transport measurements to improve sand-load estimates in a large sand-bedded river: The Lower Chippewa River, WI","interactions":[],"lastModifiedDate":"2022-07-07T16:43:25.271928","indexId":"70229986","displayToPublicDate":"2022-03-11T08:49:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"The use of continuous sediment-transport measurements to improve sand-load estimates in a large sand-bedded river: The Lower Chippewa River, WI","docAbstract":"Accurately determining sediment loads is necessary for managing river environments but is difficult because multiple processes can lead to large discharge-independent changes in sediment transport. Thus, estimations of sediment load using discharge–sediment rating curves fit to sparse or historical sediment-transport measurements can be inaccurate, necessitating alternative approaches to reduce uncertainty. Continuous sediment-transport measurements reduce uncertainty because they can be used to detect discharge-independent changes in transport and are therefore unaffected by hysteresis. We used largely continuous approaches to measure sand transport in the lower Chippewa River, a large sand-supplying tributary to the Mississippi River. We used side-looking acoustic-Doppler profilers to continuously measure suspended-sand concentration, and bedform-tracking techniques to episodically measure bedload transport. Bedload transport was then continuously estimated using a discharge-dependent ratio of bedload to suspended-sand transport. This approach allowed determination of sand loads that were not estimated based only on water discharge. Our continuous suspended-sand measurements show that hysteresis between discharge and suspended-sand concentration occurs during most floods. Quasi-continuous bed-elevation measurements using a scour monitor show that lags between discharge and dune geometric adjustment is also common, causing hysteresis between discharge and bedload transport during floods. Furthermore, comparisons of our measurements with historical sediment-transport measurements indicate large discharge-independent declines in both suspended-sand and bedload transport since the 1980s. These findings indicate that sand transport is a non-stationary function of water discharge over timescales ranging from within individual floods to decades. Consequently, although our continuous-measurement approach yields only a ~20–30% improvement over rating-curve estimates of sand load over multi-year periods, our approach yields up to a factor-of-five improvement in sand-load estimates over the shorter, i.e., within a flood, timescales over which the largest discharge-independent changes in sand transport occur.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.5360","usgsCitation":"Dean, D.J., Topping, D.J., Buscombe, D., Groten, J.T., Ziegeweid, J.R., Fitzpatrick, F., Lund, J., and Coenen, E.N., 2022, The use of continuous sediment-transport measurements to improve sand-load estimates in a large sand-bedded river: The Lower Chippewa River, WI: Earth Surface Processes and Landforms, v. 47, no. 8, p. 2006-2023, https://doi.org/10.1002/esp.5360.","productDescription":"18 p.","startPage":"2006","endPage":"2023","ipdsId":"IP-132461","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":448528,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.5360","text":"Publisher Index Page"},{"id":397392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lower Chippewa River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.4169921875,\n 44.33956524809713\n ],\n [\n -91.263427734375,\n 44.33956524809713\n ],\n [\n -91.263427734375,\n 45.120052841530544\n ],\n [\n -92.4169921875,\n 45.120052841530544\n ],\n [\n -92.4169921875,\n 44.33956524809713\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dean, David J. 0000-0003-0203-088X djdean@usgs.gov","orcid":"https://orcid.org/0000-0003-0203-088X","contributorId":131047,"corporation":false,"usgs":true,"family":"Dean","given":"David","email":"djdean@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":838577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topping, David J. 0000-0002-2104-4577","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":215068,"corporation":false,"usgs":true,"family":"Topping","given":"David","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":838578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buscombe, D. D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":289131,"corporation":false,"usgs":true,"family":"Buscombe","given":"D. D.","affiliations":[{"id":62054,"text":"Marda Science, LLC, contracted to U.S. Geological Survey Pacific Coastal and Marine Science Center, Santa Cruz, CA","active":true,"usgs":false}],"preferred":false,"id":838579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Groten, Joel T. 0000-0002-0441-8442 jgroten@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-8442","contributorId":173464,"corporation":false,"usgs":true,"family":"Groten","given":"Joel","email":"jgroten@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":838580,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ziegeweid, Jeffrey R. 0000-0001-7797-3044 jrziege@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-3044","contributorId":4166,"corporation":false,"usgs":true,"family":"Ziegeweid","given":"Jeffrey","email":"jrziege@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":838581,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":838582,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lund, J. William 0000-0002-8830-4468","orcid":"https://orcid.org/0000-0002-8830-4468","contributorId":289132,"corporation":false,"usgs":true,"family":"Lund","given":"J. William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":838583,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coenen, Erin Nicole 0000-0003-2470-3854","orcid":"https://orcid.org/0000-0003-2470-3854","contributorId":289133,"corporation":false,"usgs":true,"family":"Coenen","given":"Erin","email":"","middleInitial":"Nicole","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":838584,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70226205,"text":"ofr20211106 - 2022 - Preliminary geologic map of the Cherry Hill quadrangle, Dinwiddie, Sussex, and Greensville Counties, Virginia","interactions":[],"lastModifiedDate":"2026-03-25T17:45:56.254572","indexId":"ofr20211106","displayToPublicDate":"2022-03-10T15:15:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1106","displayTitle":"Preliminary Geologic Map of the Cherry Hill Quadrangle, Dinwiddie, Sussex, and Greensville Counties, Virginia","title":"Preliminary geologic map of the Cherry Hill quadrangle, Dinwiddie, Sussex, and Greensville Counties, Virginia","docAbstract":"The Cherry Hill 7.5-minute quadrangle straddles the Coastal Plain and Piedmont Provinces along the Tidewater Fall Line. Rocks of the eastern Piedmont Roanoke Rapids terrane crop out in the western part of the quadrangle and consist of greenschist- to amphibolite-facies Neoproterozoic felsic to intermediate metavolcanic rocks, some of which contain flattened quartz phenocrysts and are locally isoclinally folded; greenstone that locally preserves primary layering; and intrusive metadiorite and metagabbro, much of which has been altered to amphibolite. Most of these rocks are strongly foliated and jointed. Greenschist-facies metasiltstone that preserves primary bedding also occurs locally in the Roanoke Rapids terrane. Neoproterozoic mica schist, middle Paleozoic foliated metagranite, and late Paleozoic massive and porphyritic granite crop out in the eastern part of the quadrangle and are part of the Dinwiddie terrane and the late Paleozoic De Witt pluton. Upper greenschist- to lower amphibolite-facies mica schist consists of stringers and boudins of vein quartz and contains porphyroclasts of staurolite that preserve an earlier foliation as inclusion trails. Porphyroblasts of garnet, staurolite, and kyanite also occur locally. Foliation in granites of the De Witt pluton may be magmatic. Separating the Dinwiddie terrane from the Roanoke Rapids terrane are greenschist-facies, highly strained granitic mylonite and bodies of less deformed granite within the Nottoway River fault zone, which is a strand of the eastern Piedmont fault system. Paleozoic pegmatite dikes and quartz veins cross-cut rocks of the Dinwiddie terrane, and quartz veins and Jurassic diabase dikes cross-cut rocks of the Roanoke Rapids terrane.
Sand and gravel deposits of the Atlantic Coastal Plain overlie Piedmont rocks. Two units assigned to the upper part of the Neogene Chesapeake Group occur at elevations up to 295 feet (90 meters) above sea level atop the Richmond plain in the central part of the quadrangle. Two units of the Quaternary Bacons Castle Formation occupy the Essex plain and Norge uplands at elevations up to 180 feet (55 meters) above sea level in the eastern part of the quadrangle. In the western part of the quadrangle, multiple levels of terrace deposits are the fluvial equivalent of estuarine to marine units of the Atlantic Coastal Plain to the east. Holocene alluvium occurs along creeks and the Nottoway River. Quaternary colluvial deposits occur locally. Numerous Carolina bays pock the landscape of the Richmond and Essex plains, and three abandoned channelways represent former locations of Sappony Creek, one of the major drainages of the quadrangle.
Brittle faults juxtapose Piedmont basement rocks against Neogene sediments of the upper part of the Chesapeake Group. These Cenozoic faults were first uncovered in mine excavations in the late 1990s; new mapping indicates that many of these faults are reactivated silicified cataclasite zones that occur throughout the Piedmont basement rocks. Silicified cataclasites and associated quartz veins are typically mineralized with iron and iron sulfide minerals. The quadrangle was the focus of extensive mining for heavy minerals, including ilmenite and zircon, in upland Atlantic Coastal Plain deposits beginning in the mid-1990s. Other mineral resources, including precious metals, clay for structural brick, crushed stone, and building stone for millstones, have also been prospected or quarried in the quadrangle.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211106","usgsCitation":"Carter, M.W., Karst, A.T., Berquist, C.R., Jr., Schindler, J.S., Weems, R.E., Weinmann, B.R., and Crider, E.A., Jr., 2022, Preliminary geologic map of the Cherry Hill quadrangle, Dinwiddie, Sussex, and Greensville Counties, Virginia: U.S. Geological Survey Open-File Report 2021–1106, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20211106.","productDescription":"1 Sheet: 40.00 x 54.01 inches; Data Release","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118811","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":391751,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1106/coverthb.jpg"},{"id":394115,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P910X7BJ","text":"USGS data release","linkHelpText":"Database for the Preliminary Geologic Map of the Cherry Hill Quadrangle, Dinwiddie, Sussex, and Greensville Counties, Virginia"},{"id":391752,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1106/ofr20211106.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1106"},{"id":501531,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112547.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Virginia","county":"Dinwiddie County, Sussex County, Greensville County","otherGeospatial":"Cherry Hill quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.625,\n 36.875\n ],\n [\n -77.50,\n 36.875\n ],\n [\n -77.50,\n 37.00\n ],\n [\n -77.625,\n 37.00\n ],\n [\n -77.625,\n 36.875\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey worked in cooperation with the New York State Department of Environmental Conservation to assess the potential sources of fecal contamination entering Port Jefferson Harbor, Setauket Harbor, and Conscience Bay, an embayment complex on the northern shore of Suffolk County, Long Island, New York. Water samples are routinely collected by the New York State Department of Environmental Conservation in the harbor and analyzed for fecal coliform bacteria, an indicator of fecal contamination, to determine the need for closure of shellfish beds for harvest and consumption. Fecal coliform and other bacteria are an indicator of the potential presence of pathogenic (disease-causing) bacteria. However, indicator bacteria alone cannot determine the biological or geographical sources of contamination; therefore, microbial source tracking was implemented to determine various biological sources of contamination. In addition, information such as the location, weather and season, and surrounding land use where a sample was collected help determine the geographical source and conveyance of land-based water to the embayment.
Our analysis revealed that the most substantial source of fecal contamination to the Port Jefferson Harbor complex was discharge from sites draining ponds and wetlands, particularly during the summer months. Fecal coliform bacteria at sites where ponds and wetlands drain are increased by stormwater runoff, which is another substantial source of fecal contamination. Human markers, likely originating from the outfall of the Port Jefferson sewage treatment plant, were found at least once in every sample collected within Port Jefferson Harbor; however, fecal coliform concentrations were low, indicating that the sewage treatment plant is not a likely source of fecal contamination to the embayment. Canine markers detected in Conscience Bay were associated with high fecal coliform, particularly in wet summer samples. Waterfowl markers were most often detected in source water for Port Jefferson Harbor, but in Conscience Bay, waterfowl was frequently detected within the bay itself. Resuspension of bed sediment may contribute to fecal contamination in the harbor, but more targeted analyses are needed to support this finding. There was little evidence of groundwater-contributing fecal bacteria by direct discharge from the subsurface. A classification scheme was developed to convey the degree of fecal contamination to stakeholders and resource managers. Based on this classification scheme, the Culvert North of State Route 25A, Culvert North of Shore Road, Old Mill Creek Culvert, and Mill Pond Culvert to Conscience Bay sites were identified as locations that contribute substantial fecal contamination to the Port Jefferson Harbor complex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215141","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., 2022, Using microbial source tracking to identify contamination sources in Port Jefferson Harbor, Setauket Harbor, and Conscience Bay on Long Island, New York: U.S. Geological Survey Scientific Investigations Report 2021–5141, 25 p., https://doi.org/10.3133/sir20215141.","productDescription":"Report: vi, 25 p.; Database","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127839","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":396934,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20215033","text":"Scientific Investigations Report 2021–5033","linkHelpText":"- Overview and Methodology for a Study To Identify Fecal Contamination Sources Using Microbial Source Tracking in Seven Embayments on Long Island, New York"},{"id":396998,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215141/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":396933,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5141/images/"},{"id":396932,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5141/sir20215141.XML"},{"id":396931,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the nation"},{"id":396930,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5141/sir20215141.pdf","text":"Report","size":"1.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5141"},{"id":396929,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5141/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Port Jefferson Harbor, Setauket Harbor, Conscience Bay, Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.18061828613281,\n 40.90936126702326\n ],\n [\n -72.95127868652344,\n 40.90936126702326\n ],\n [\n -72.95127868652344,\n 40.994410999439516\n ],\n [\n -73.18061828613281,\n 40.994410999439516\n ],\n [\n -73.18061828613281,\n 40.90936126702326\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
The Rice Creek Watershed District (RCWD) cooperated with the U.S. Geological Survey to establish a 10-year suspended sediment and bedload monitoring and streamflow modeling study to evaluate the effects of two restored meander sections on middle Rice Creek in Arden Hills, Minnesota. The RCWD goals of this stream restoration were to reduce water quality impairments, improve aquatic habitat, and reduce associated costs of dredging a sedimentation pond. During the study there were several factors that introduced uncertainty in the sampling results; however, the sampling results indicated there was an increase in the post-stream restoration sediment data because of higher streamflows during the post-stream than the pre-stream restoration monitoring period. The negative relation between suspended fines and streamflow was explained by a reduction in the supply of fines with increasing streamflows. The positive relation among suspended sand, bedload, and streamflow was because of those constituents having a functional relation with the hydraulic properties of flow and a consistent supply of sand. Two-dimensional flow modeling simulations indicated the downstream restored section had less shear stress, more pools, and could access the floodplain at a lower streamflow than the original channel. Overall, the uncertainty of the sampling results indicates the complexity of sediment transport in a river and suggests a need for multisite, multifaceted, multiyear data, and tools to simulate those data to effectively evaluate river restorations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225004","collaboration":"Prepared in cooperation with Rice Creek Watershed District","usgsCitation":"Groten, J.T., Livdahl, C.T., DeLong, S.B., Lund, J.W., Nelson, J.M., Coenen, E.N., Ziegeweid, J.R., and Kocian, M.J., 2022, Sediment monitoring and streamflow modeling before and after a stream restoration in Rice Creek, Minnesota, 2010–2019: U.S. Geological Survey Scientific Investigations Report 2022–5004, 40 p., https://doi.org/10.3133/sir20225004.","productDescription":"Report: viii, 40 p.; Data release; Dataset","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-126710","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":396980,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SJIY32","text":"USGS data release","linkHelpText":"Suspended sediment and bedload data, simple linear regression models, loads, elevation data, and FaSTMECH models for Rice Creek, Minnesota, 2010-2019"},{"id":396978,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5004/images"},{"id":396977,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5004/sir20225004.XML"},{"id":396979,"rank":5,"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":396975,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5004/coverthb.jpg"},{"id":396976,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5004/sir20225004.pdf","text":"Report","size":"19.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5004"}],"country":"United States","state":"Minnesota","otherGeospatial":"Rice Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.21710586547852,\n 45.08236949749694\n ],\n [\n -93.18449020385742,\n 45.08236949749694\n ],\n [\n -93.18449020385742,\n 45.09957848291159\n ],\n [\n -93.21710586547852,\n 45.09957848291159\n ],\n [\n -93.21710586547852,\n 45.08236949749694\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Migratory waterbirds (i.e., shorebirds, wading birds, and waterfowl) rely on a diffuse continental network of wetland habitats to support annual life cycle needs. Emerging threats of climate and land-use change raise new concerns over the sustainability of these habitat networks as water scarcity triggers cascading ecological effects impacting wetland habitat availability. Here we use important waterbird regions in Oregon and California, United States, as a model system to examine patterns of landscape change impacting wetland habitat networks in western North America. Wetland hydrology and flooded agricultural habitats were monitored monthly from 1988 to 2020 using satellite imagery to quantify the timing and duration of inundation—a key delimiter of habitat niche values associated with waterbird use. Trends were binned by management practice and wetland hydroperiods (semi-permanent, seasonal, and temporary) to identify differences in their climate and land-use change sensitivity. Wetland results were assessed using 33 waterbird species to detect non-linear effects of network change across a diversity of life cycle and habitat needs. Pervasive loss of semi-permanent wetlands was an indicator of systemic functional decline. Shortened hydroperiods caused by excessive drying transitioned semi-permanent wetlands to seasonal and temporary hydrologies—a process that in part counterbalanced concurrent seasonal and temporary wetland losses. Expansion of seasonal and temporary wetlands associated with closed-basin lakes offset wetland declines on other public and private lands, including wildlife refuges. Diving ducks, black terns, and grebes exhibited the most significant risk of habitat decline due to semi-permanent wetland loss that overlapped important migration, breeding, molting, and wintering periods. Shorebirds and dabbling ducks were beneficiaries of stable agricultural practices and top-down processes of functional wetland declines that operated collectively to maintain habitat needs. Outcomes from this work provide a novel perspective of wetland ecosystem change affecting waterbirds and their migration networks. Understanding the complexity of these relationships will become increasingly important as water scarcity continues to restructure the timing and availability of wetland resources.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2022.844278","usgsCitation":"Donnelly, J., Moore, J.N., Casazza, M.L., and Coons, S.P., 2022, Functional wetland loss drives emerging risks to waterbird migration networks: Frontiers in Ecology and Evolution, v. 10, 844278, 18 p., https://doi.org/10.3389/fevo.2022.844278.","productDescription":"844278, 18 p.","ipdsId":"IP-137357","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448530,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2022.844278","text":"Publisher Index Page"},{"id":397863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.71826171875,\n 35.35321610123823\n ],\n [\n -118.71826171875,\n 36.06686213257888\n ],\n [\n -119.35546875000001,\n 36.87962060502676\n ],\n [\n -120.62988281249999,\n 38.151837403006766\n ],\n [\n -121.31103515625,\n 39.36827914916014\n ],\n [\n -121.86035156249999,\n 40.59727063442024\n ],\n [\n -122.36572265625,\n 40.730608477796636\n ],\n [\n -122.87109375,\n 40.38002840251183\n ],\n [\n -122.56347656249999,\n 39.33429742980725\n ],\n [\n -121.9921875,\n 38.54816542304656\n ],\n [\n -121.06933593749999,\n 37.579412513438385\n ],\n [\n -120.498046875,\n 36.61552763134925\n ],\n [\n -119.2236328125,\n 35.28150065789119\n ],\n [\n -118.71826171875,\n 35.35321610123823\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.47607421874999,\n 40.730608477796636\n ],\n [\n -119.46533203125,\n 40.697299008636755\n ],\n [\n -119.46533203125,\n 41.64007838467894\n ],\n [\n -118.740234375,\n 42.32606244456202\n ],\n [\n -117.99316406249999,\n 43.004647127794435\n ],\n [\n -118.89404296875,\n 44.15068115978094\n ],\n [\n -119.90478515625,\n 44.465151013519616\n ],\n [\n -121.1572265625,\n 44.071800467511565\n ],\n [\n -121.66259765625001,\n 43.27720532212024\n ],\n [\n -121.13525390625,\n 42.24478535602799\n ],\n [\n -121.2451171875,\n 41.672911819602085\n ],\n [\n -121.06933593749999,\n 41.244772343082076\n ],\n [\n -120.56396484375,\n 41.16211393939692\n ],\n [\n -120.47607421874999,\n 40.730608477796636\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Donnelly, J Patrick","contributorId":289526,"corporation":false,"usgs":false,"family":"Donnelly","given":"J Patrick","affiliations":[{"id":62169,"text":"Intermountain West Joint Venture - U.S. Fish and Wildlife Service, Migratory Bird Program, Missoula, MT, United States","active":true,"usgs":false}],"preferred":false,"id":839227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Johnnie N","contributorId":289527,"corporation":false,"usgs":false,"family":"Moore","given":"Johnnie","email":"","middleInitial":"N","affiliations":[{"id":62170,"text":"Group for Quantitative Study of Snow and Ice, Department of Geosciences, University of Montana, Missoula, MT, United States","active":true,"usgs":false}],"preferred":false,"id":839228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coons, Shea P","contributorId":289528,"corporation":false,"usgs":false,"family":"Coons","given":"Shea","email":"","middleInitial":"P","affiliations":[{"id":62172,"text":"Avian Science Center - University of Montana, Missoula, MT, United States","active":true,"usgs":false}],"preferred":false,"id":839230,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230303,"text":"70230303 - 2022 - Seasonal and multi-year changes in CO2 degassing at Mammoth Mountain explained by solid-earth-driven fault valving","interactions":[],"lastModifiedDate":"2022-04-07T15:24:46.15982","indexId":"70230303","displayToPublicDate":"2022-03-09T17:10:16","publicationYear":"2022","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}},"displayTitle":"Seasonal and multi-year changes in CO2 degassing at Mammoth Mountain explained by solid-earth-driven fault valving","title":"Seasonal and multi-year changes in CO2 degassing at Mammoth Mountain explained by solid-earth-driven fault valving","docAbstract":"Changes in CO2 emissions from volcanoes may evidence volcanic unrest. We use a multiyear time series of CO2 flux collected at the Horseshoe Lake Tree Kill area on Mammoth Mountain, CA, to understand processes that cause variations in flux from this system. Seasonal variations are systematically lowest during the winter months and reach maximum values during the summer season. A persistent ∼20% reduction in CO2 flux occurred during the Spring of 2017, coincident with the emergence of the area from drought and earthquake swarms in Long Valley Caldera. We used continuous GNSS measurements to calculate seasonal strains and stresses across the Mammoth Mountain area, and resolved resultant stresses onto the Mammoth Mountain Fault, which appears to facilitate gas transport to the surface. The normal stress changes are consistent with seasonal and multiyear changes in CO2 flux, suggesting that fault valving by solid earth processes can alter surface gas fluxes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL096595","usgsCitation":"Hilley, G.E., Lewicki, J.L., and Baden, C., 2022, Seasonal and multi-year changes in CO2 degassing at Mammoth Mountain explained by solid-earth-driven fault valving: Geophysical Research Letters, v. 49, no. 6, e2021GL096595, 10 p., https://doi.org/10.1029/2021GL096595.","productDescription":"e2021GL096595, 10 p.","ipdsId":"IP-133409","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":398287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Horseshoe Lake Tree Kill , Mammoth Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.05540466308592,\n 37.58458197392559\n ],\n [\n -118.98399353027344,\n 37.58458197392559\n ],\n [\n -118.98399353027344,\n 37.64060676109015\n ],\n [\n -119.05540466308592,\n 37.64060676109015\n ],\n [\n -119.05540466308592,\n 37.58458197392559\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Hilley, George E.","contributorId":197258,"corporation":false,"usgs":false,"family":"Hilley","given":"George","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":839923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":839924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baden, Curtis W","contributorId":222424,"corporation":false,"usgs":false,"family":"Baden","given":"Curtis W","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":839925,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229524,"text":"70229524 - 2022 - Fire (plus) flood (equals) beach: Coastal response to an exceptional river sediment discharge event","interactions":[],"lastModifiedDate":"2022-03-10T21:53:37.028589","indexId":"70229524","displayToPublicDate":"2022-03-09T15:48:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Fire (plus) flood (equals) beach: Coastal response to an exceptional river sediment discharge event","docAbstract":"Wildfire and post-fire rainfall have resounding effects on hillslope processes and sediment yields of mountainous landscapes. Yet, it remains unclear how fire–flood sequences influence downstream coastal littoral systems. It is timely to examine terrestrial–coastal connections because climate change is increasing the frequency, size, and intensity of wildfires, altering precipitation rates, and accelerating sea-level rise; and these factors can be understood as contrasting accretionary and erosive agents for coastal systems. Here we provide new satellite-derived shoreline measurements of Big Sur, California and show how river sediment discharge significantly influenced shoreline positions during the past several decades. A 2016 wildfire followed by record precipitation increased sediment discharge in the Big Sur River and resulted in almost half of the total river sediment load of the past 50 years (~ 2.2 of ~ 4.8 Mt). Roughly 30% of this river sediment was inferred to be littoral-grade sand and was incorporated into the littoral cell, causing the widest beaches in the 37-year satellite record and spreading downcoast over timescales of years. Hence, the impact of fire–flood events on coastal sediment budgets may be substantial, and these impacts may increase with time considering projected intensification of wildfires and extreme rain events under global warming.
","language":"English","publisher":"Nature Pulications","doi":"10.1038/s41598-022-07209-0","usgsCitation":"Warrick, J.A., Vos, K., East, A.E., and Vitousek, S., 2022, Fire (plus) flood (equals) beach: Coastal response to an exceptional river sediment discharge event: Scientific Reports, v. 12, https://doi.org/10.1038/s41598-022-07209-0.","productDescription":"3848, 15 p.","startPage":"3848","ipdsId":"IP-133190","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448535,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-022-07209-0","text":"Publisher Index Page"},{"id":397006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Big Sur watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.87099456787108,\n 36.24898019141822\n ],\n [\n -121.77984237670898,\n 36.24898019141822\n ],\n [\n -121.77984237670898,\n 36.29257573938972\n ],\n [\n -121.87099456787108,\n 36.29257573938972\n ],\n [\n -121.87099456787108,\n 36.24898019141822\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vos, Kilian 0000-0002-9518-1582","orcid":"https://orcid.org/0000-0002-9518-1582","contributorId":229435,"corporation":false,"usgs":false,"family":"Vos","given":"Kilian","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":837746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837748,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229510,"text":"sir20225003 - 2022 - Response of Green Lake, Wisconsin, to changes in phosphorus loading, with special emphasis on near-surface total phosphorus concentrations and metalimnetic dissolved oxygen minima","interactions":[],"lastModifiedDate":"2022-03-10T11:51:53.307516","indexId":"sir20225003","displayToPublicDate":"2022-03-09T13:55:00","publicationYear":"2022","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":"2022-5003","displayTitle":"Response of Green Lake, Wisconsin, to Changes in Phosphorus Loading, With Special Emphasis on Near-Surface Total Phosphorus Concentrations and Metalimnetic Dissolved Oxygen Minima","title":"Response of Green Lake, Wisconsin, to changes in phosphorus loading, with special emphasis on near-surface total phosphorus concentrations and metalimnetic dissolved oxygen minima","docAbstract":"Green Lake is the deepest natural inland lake in Wisconsin, with a maximum depth of about 72 meters. In the early 1900s, the lake was believed to have very good water quality (low nutrient concentrations and good water clarity) with low dissolved oxygen (DO) concentrations occurring in only the deepest part of the lake. Because of increased phosphorus (P) inputs from anthropogenic activities in its watershed, total phosphorus (TP) concentrations in the lake have increased; these changes have led to increased algal production and low DO concentrations not only in the deepest areas but also in the middle of the water column (metalimnion). The U.S. Geological Survey has routinely monitored the lake since 2004 and its tributaries since 1988. Results from this monitoring led the Wisconsin Department of Natural Resources (WDNR) to list the lake as impaired because of low DO concentrations in the metalimnion, and they identified elevated TP concentrations as the cause of impairment.
As part of this study by the U.S. Geological Survey, in cooperation with the Green Lake Sanitary District, the lake and its tributaries were comprehensively sampled in 2017–18 to augment ongoing monitoring that would further describe the low DO concentrations in the lake (especially in the metalimnion). Empirical and process-driven water-quality models were then used to determine the causes of the low DO concentrations and the magnitudes of P-load reductions needed to improve the water quality of the lake enough to meet multiple water-quality goals, including the WDNR’s criteria for TP and DO.
Data from previous studies showed that DO concentrations in the metalimnion decreased slightly as summer progressed in the early 1900s but, since the late 1970s, have typically dropped below 5 milligrams per liter (mg/L), which is the WDNR criterion for impairment. During 2014–18 (the baseline period for this study), the near-surface geometric mean TP concentration during June–September in the east side of the lake was 0.020 mg/L and in the west side was 0.016 mg/L (both were above the 0.015-mg/L WDNR criterion for the lake), and the metalimnetic DO minimum concentrations (MOMs) measured in August ranged from 1.0 to 4.7 mg/L. The degradation in water quality was assumed to have been caused by excessive P inputs to the lake; therefore, the TP inputs to the lake were estimated. The mean annual external P load during 2014–18 was estimated to be 8,980 kilograms per year (kg/yr), of which monitored and unmonitored tributary inputs contributed 84 percent, atmospheric inputs contributed 8 percent, waterfowl contributed 7 percent, and septic systems contributed 1 percent. During fall turnover, internal sediment recycling contributed an additional 7,040 kilograms that increased TP concentrations in shallow areas of the lake by about 0.020 mg/L. The elevated TP concentrations then persisted until the following spring. On an annual basis, however, there was a net deposition of P to the bottom sediments.
Empirical models were used to describe how the near-surface water quality of Green Lake would be expected to respond to changes in external P loading. Predictions from the models showed a relatively linear response between P loading and TP and chlorophyll-a (Chl-a) concentrations in the lake, with the changes in TP and Chl-a concentrations being less on a percentage basis (50–60 percent for TP and 30–70 percent for Chl-a) than the changes in P loading. Mean summer water clarity, quantified by Secchi disk depths, had a greater response to decreases in P loading than to increases in P loading. Based on these relations, external P loading to the lake would need to be decreased from 8,980 kg/yr to about 5,460 kg/yr for the geometric mean June–September TP concentration in the east side of the lake, with higher TP concentrations than in the west side, to reach the WDNR criterion of 0.015 mg/L. This reduction of 3,520 kg/yr is equivalent to a 46-percent reduction in the potentially controllable external P sources (all external sources except for precipitation, atmospheric deposition, and waterfowl) from those measured during water years 2014–18. The total external P loading would need to decrease to 7,680 kg/yr (a 17-percent reduction in potentially controllable external P sources) for near-surface June–September TP concentrations in the west side of the lake to reach 0.015 mg/L. Total external P loading would need to decrease to 3,870–5,320 kg/yr for the lake to be classified as oligotrophic, with a near-surface June–September TP concentration of 0.012 mg/L.
Results from the hydrodynamic water-quality model GLM–AED (General Lake Model coupled to the Aquatic Ecodynamics modeling library) indicated that MOMs are driven by external P loading and internal sediment recycling that lead to high TP concentrations during spring and early summer, which in turn lead to high phytoplankton production, high metabolism and respiration, and ultimately DO consumption in the upper, warmer areas of the metalimnion. GLM–AED results indicated that settling of organic material during summer might be slowed by the colder, denser, and more viscous water in the metalimnion and thus increase DO consumption. Based on empirical evidence from a comparison of MOMs with various meteorological, hydrologic, water quality, and in-lake physical factors, MOMs were lower during summers, when metalimnetic water temperatures were warmer, near-surface Chl-a and TP concentrations were higher, and Secchi depths were lower. GLM–AED results indicated that the external P load would need to be reduced to about 4,060 kg/yr, a 57-percent reduction from that measured in 2014–18, to eliminate the occurrence of MOMs less than 5 mg/L during more than 75 percent of the years (the target provided by the WDNR).
Large reductions in external P loading are expected to have an immediate effect on the near-surface TP concentrations and metalimnetic DO concentrations in Green Lake; however, it may take several years for the full effects of the external-load reduction to be observed because internal sediment recycling is an important source of P for the following spring.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225003","collaboration":"Prepared in cooperation with the Green Lake Sanitary District","usgsCitation":"Robertson, D.M., Siebers, B.J., Ladwig, R., Hamilton, D.P., Reneau, P.C., McDonald, C.P., Prellwitz, S., and Lathrop, R.C., 2022, Response of Green Lake, Wisconsin, to changes in phosphorus loading, with special emphasis on near-surface total phosphorus concentrations and metalimnetic dissolved oxygen minima: U.S. Geological Survey Scientific Investigations Report 2022–5003, 77 p., https://doi.org/10.3133/sir20225003.","productDescription":"Report: xi, 77 p.; Data release","numberOfPages":"77","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123380","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":396908,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5003/coverthb.jpg"},{"id":396909,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5003/sir20225003.pdf","text":"Report","size":"8.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5003"},{"id":396911,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5003/sir20225003.XML"},{"id":396910,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H85BK0","text":"USGS data release","linkHelpText":"Eutrophication models to simulate changes in the water quality of Green Lake, Wisconsin in response to changes in phosphorus loading, with supporting water-quality data for the lake, its tributaries, and atmospheric deposition"},{"id":396912,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5003/images/"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Green Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.09225463867188,\n 43.756712928570245\n ],\n [\n -88.86428833007814,\n 43.756712928570245\n ],\n [\n -88.86428833007814,\n 43.85384062624276\n ],\n [\n -89.09225463867188,\n 43.85384062624276\n ],\n [\n -89.09225463867188,\n 43.756712928570245\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726