Karst hydrogeologic systems represent challenging and unique conditions to scientists attempting to study groundwater flow and contaminant transport. Karst terrains are characterized by distinct and beautiful landscapes, caverns, and springs, and many of the exceptional karst areas are designated as national or state parks. The range and complexity of landforms and groundwater flow systems associated with karst terrains are enormous, perhaps more than any other type of aquifer.
The U.S. Geological Survey (USGS) Karst Interest Group (KIG), formed in 2000, is a loosely knit, grassroots organization of USGS and non-USGS scientists and researchers devoted to fostering better communication among scientists working on, or interested in, karst aquifers. The primary mission of the KIG is to encourage and support interdisciplinary collaboration and technology transfer among scientists working in karst areas. To accomplish its mission, the KIG has organized a series of workshops. To date (2021), eight KIG workshops, including the workshop documented in this report, have been held. This workshop is the first virtual workshop. The abstracts and extended abstracts provide a snapshot in time of past and current karst-related studies. The field trip guide is included in the proceedings volume even though the field trip will not occur in person.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205019","usgsCitation":"Kuniansky, E.L., and Spangler, L.E., eds., 2021, U.S. Geological Survey Karst Interest Group Proceedings, October 19–20, 2021: U.S. Geological Survey Scientific Investigations Report 2020–5019, 147 p., https://doi.org/10.3133/sir20205019.","productDescription":"iv, 147 p.","numberOfPages":"147","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114317","costCenters":[{"id":448,"text":"National Water Availability and Use Program","active":false,"usgs":true}],"links":[{"id":390521,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5019/coverthb.jpg"},{"id":390522,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5019/sir20205019.pdf","text":"Report","size":"9.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5019"}],"contact":"Water Mission Area
U.S. Geological Survey
1770 Corporate Drive
Suite 500
Norcross, GA 30093
https://www.usgs.gov/mission-areas/water-resources/science/karst-aquifers
Placer and dredging operations in the Yankee Fork Basin, Idaho, have left more than 5 miles of the lower Yankee Fork of the Salmon River (Yankee Fork) in a highly altered fluvial condition, resulting in poor habitat quantity and quality for native fish species. Since 2011, the Bureau of Reclamation and other stakeholders have implemented a series of restoration efforts to improve the connectivity of the river with its floodplain and to improve aquatic and terrestrial habitat in the Yankee Fork. In conjunction with these rehabilitation efforts, the U.S. Geological Survey monitored streamflow and suspended-sediment and bedload transport during water years 2012–19 at four sites in the affected lower reach of the Yankee Fork. The objectives of the monitoring were to (1) identify source areas of sediment, (2) quantify sediment transport in the lower Yankee Fork, and (3) provide a benchmark to evaluate the effects of rehabilitation efforts in the basin.
During the 8 years of sampling, the annual flow-weighted suspended-sediment concentrations (SSCs) were largest at the most downstream Clayton site, ranging from a low of 11 milligrams per liter (mg/L) in 2015 to 145 mg/L in 2017. The Clayton site also had the largest flow-weighted concentrations of suspended sand and suspended fines. At relatively low streamflow, the fine-grained fraction of the suspended sediment was the dominant component of the SSC at all sites, with an increase in the sand-size fraction as streamflow increased during snowmelt runoff. Each of the three main-stem Yankee Fork sites indicated a large amount of hysteresis in SSCs during snowmelt runoff, with concentrations on the rising limb of the hydrograph larger than concentrations on the falling limb at similar streamflow. Hysteresis was particularly evident in the fine-grained fraction of suspended sediment, indicating that sediment transport in the lower Yankee Fork is more limited by the supply of fine-grained sediment as compared to coarser-grained sediment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215111","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Clark, G.M., and Ducar, S.D., 2021, Sediment transport in the Yankee Fork of the Salmon River near Stanley, Idaho, water years 2012–19: U.S. Geological Survey Scientific Investigations Report 2021–5111, 36 p., https://doi.org/10.3133/sir20215111.","productDescription":"Report: vi, 36 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-126315","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":397358,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5111/sir20215111.XML"},{"id":397357,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5111/images"},{"id":390610,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T1F6SW","text":"USGS data release","description":"USGS data release","linkHelpText":"Synthetic streamflow regressions and daily mean streamflow estimates at three sites on the Yankee Fork Salmon River near Clayton, ID, Water Years 2012-2019"},{"id":403445,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215111/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5111"},{"id":390609,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5111/sir20215111.pdf","text":"Report","size":"4.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5111"},{"id":390608,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5111/coverthb.jpg"}],"country":"United States","state":"Idaho","city":"Stanley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.0213623046875,\n 44.05601169578525\n ],\n [\n -113.84033203125,\n 44.05601169578525\n ],\n [\n -113.84033203125,\n 44.89479576469787\n ],\n [\n -115.0213623046875,\n 44.89479576469787\n ],\n [\n -115.0213623046875,\n 44.05601169578525\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
Satellite-derived bathymetry (SDB) based upon an empirical band ratio method is a cost-effective means for mapping nearshore bathymetry in coastal areas vulnerable to natural hazards. This is particularly important for the low-lying coastal community of Unalakleet, Alaska, that has been negatively affected not only by flooding, storm surge, and historically strong storms but also by high erosion rates stemming from the Unalakleet River and Norton Sound. The purpose of this study was to assess the viability of different satellite imagery, including Landsat 8 (L8) Operational Land Imager, Sentinel–2B, WorldView–3, and L8 Provisional Aquatic Reflectance science product, for deriving SDB for Unalakleet, Alaska. Correlations were performed between satellite imagery band ratios and topobathymetric (topobathy) light detection and ranging (lidar) and in situ single-beam sound navigation and ranging (sonar). The satellite imagery correlations with topobathy lidar did not yield as high of a linear relation with water depths as the satellite imagery correlations with the single-beam sonar. An extinction depth, where light no longer attenuates through the water column, was not identified because of the shallow depths within the topobathy lidar and single-beam sonar datasets. Although some single-beam soundings measured at 7 meters deep, the correlations with the SDB band ratios did not yield a strong linear relation. Satellite imagery band ratio correlations with Electronic Navigational Chart soundings did not yield a strong linear relation because of older source data. Less than optimal linear regressions were most likely due to the geography of Unalakleet, Alaska, a low-lying coastal community subject to high erosion rates from surrounding waters. This study is one of the first attempts to compare different satellite imagery band ratio correlations with topobathy lidar and in situ sonar to assess the viability for nearshore SDB for coastal Unalakleet, Alaska.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215097","usgsCitation":"Poppenga, S.K., and Danielson, J.J., 2021, A comparison of Landsat 8 Operational Land Imager and Provisional Aquatic Reflectance science product, Sentinel–2B, and WorldView–3 imagery for empirical satellite-derived bathymetry, Unalakleet, Alaska: U.S. Geological Survey Scientific Investigations Report 2021–5097, 15 p., https://doi.org/10.3133/sir20215097.","productDescription":"Report: vii, 15 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-132009","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":390537,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5097/coverthb.jpg"},{"id":390538,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5097/sir20215097.pdf","text":"Report","size":"1.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5097"},{"id":390539,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9238F8K","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Nearshore bathymetry data from the Unalakleet River mouth, Alaska, 2019"}],"country":"United States","state":"Alaska","city":"Unalakleet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -164.4873046875,\n 63.16675579239305\n ],\n [\n -159.6038818359375,\n 63.16675579239305\n ],\n [\n -159.6038818359375,\n 64.58146958015028\n ],\n [\n -164.4873046875,\n 64.58146958015028\n ],\n [\n -164.4873046875,\n 63.16675579239305\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
In early September 2019, a morbidity and mortality event affecting California tiger salamanders (Ambystoma californiense) and Santa Cruz long-toed salamanders (Ambystoma macrodactylum croceum) in late stages of metamorphosis was reported at a National Wildlife Refuge in Santa Cruz County, California, U.S.A. During the postmortem disease investigation, severe integumentary metacercarial (Class: Trematoda) infection, associated with widespread skin lesions, was observed. Planorbid snails collected from the ponds of the refuge within seven days of the mortality event were infected with Ribeiroia ondatrae, a digenetic trematode that can cause malformation and death in some amphibians. We suggest sustained seasonal high-water levels due to active habitat management along with several years of increased rainfall led to increased bird visitation, increased over-wintering of snails, and prolonged salamander metamorphosis, resulting in a confluence of conditions and cascading of host-parasite dynamics to create a hyper-parasitized state.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijppaw.2021.10.008","usgsCitation":"Keller, S., Roderick, C., Caris, C., Grear, D.A., and Cole, R.A., 2021, Acute mortality in California tiger salamander (Ambystoma californiense) and Santa Cruz long-toed salamander (Ambystoma macrodactylum croceum) caused by Ribeiroia ondatrae (Class: Trematoda): International Journal for Parasitology: Parasites and Wildlife, v. 16, p. 255-261, https://doi.org/10.1016/j.ijppaw.2021.10.008.","productDescription":"7 p.","startPage":"255","endPage":"261","ipdsId":"IP-130453","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":450418,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijppaw.2021.10.008","text":"Publisher Index Page"},{"id":436151,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CD92ZZ","text":"USGS data release","linkHelpText":"Carcass weights, 28S rRNA alignment file and parasite sample vouchers collected from California tiger salamanders (Ambystoma californiense) CTS and Santa Cruz long-toed salamander (Ambystoma macrodactylum croceum) SCLT from Prospect or Ellicott Pond, on Ellicott Slough National Wildlife Refuge, California U.S.A. recorded September 11, 2019"},{"id":391267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Santa Cruz County","otherGeospatial":"Ellicott Slough National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.80971145629881,\n 36.9106467256463\n ],\n [\n -121.80035591125488,\n 36.9106467256463\n ],\n [\n -121.80035591125488,\n 36.92423384099305\n ],\n [\n -121.80971145629881,\n 36.92423384099305\n ],\n [\n -121.80971145629881,\n 36.9106467256463\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keller, Saskia","contributorId":255627,"corporation":false,"usgs":false,"family":"Keller","given":"Saskia","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":826146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roderick, Constance 0000-0001-8330-8024","orcid":"https://orcid.org/0000-0001-8330-8024","contributorId":215346,"corporation":false,"usgs":true,"family":"Roderick","given":"Constance","email":"","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":826147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caris, Christopher","contributorId":268197,"corporation":false,"usgs":false,"family":"Caris","given":"Christopher","email":"","affiliations":[{"id":55590,"text":"U.S. Fish and Wildlife Service, San Francisco Bay National Wildlife Refuge Complex, Fremont, CA, USA","active":true,"usgs":false}],"preferred":false,"id":826148,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":826149,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole, Rebecca A. 0000-0003-2923-1622 rcole@usgs.gov","orcid":"https://orcid.org/0000-0003-2923-1622","contributorId":2873,"corporation":false,"usgs":true,"family":"Cole","given":"Rebecca","email":"rcole@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":826150,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225673,"text":"70225673 - 2021 - Machine learning predictions of nitrate in groundwater used for drinking supply in the conterminous United States","interactions":[],"lastModifiedDate":"2021-11-02T11:54:43.920548","indexId":"70225673","displayToPublicDate":"2021-10-18T06:51:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning predictions of nitrate in groundwater used for drinking supply in the conterminous United States","docAbstract":"Groundwater is an important source of drinking water supplies in the conterminous United State (CONUS), and presence of high nitrate concentrations may limit usability of groundwater in some areas because of the potential negative health effects. Prediction of locations of high nitrate groundwater is needed to focus mitigation and relief efforts. A three-dimensional extreme gradient boosting (XGB) machine learning model was developed to predict the distribution of nitrate. Nitrate was predicted at a 1 km resolution for two drinking water zones, each of variable depth, one for domestic supply and one for public supply. The model used measured nitrate concentrations from 12,082 wells and included predictor variables representing well characteristics, hydrologic conditions, soil type, geology, land use, climate, and nitrogen inputs. Predictor variables derived from empirical or numerical process-based models were also included to integrate information on controlling processes and conditions. The model provided accurate estimates at national and regional scales: the training (R2 of 0.83) and hold-out (R2 of 0.49) data fits compared favorably to previous studies. Predicted nitrate concentrations were less than 1 mg/L across most of the CONUS. Nationally, well depth, soil and climate characteristics, and the absence of developed land use were among the most influential explanatory factors. Only 1% of the area in either water supply zone had predicted nitrate concentrations greater than 10 mg/L; however, about 1.4 M people depend on groundwater for their drinking supplies in those areas. Predicted high concentrations of nitrate were most prevalent in the central CONUS. In areas of predicted high nitrate concentration, applied manure, farm fertilizer, and agricultural land use were influential predictor variables. This work represents the first application of XGB to a three-dimensional national-scale groundwater quality model and provides a significant milestone in the efforts to document nitrate in groundwater across the CONUS.
Winter carbon loss in northern ecosystems is estimated to be greater than the average growing season carbon uptake and is primarily driven by microbial decomposers. Viruses modulate microbial carbon cycling via induced mortality and metabolic controls, but it is unknown whether viruses are active under winter conditions (anoxic and sub-freezing temperatures).
We used stable isotope probing (SIP) targeted metagenomics to reveal the genomic potential of active soil microbial populations under simulated winter conditions, with an emphasis on viruses and virus-host dynamics. Arctic peat soils from the Bonanza Creek Long-Term Ecological Research site in Alaska were incubated under sub-freezing anoxic conditions with H218O or natural abundance water for 184 and 370 days. We sequenced 23 SIP-metagenomes and measured carbon dioxide (CO2) efflux throughout the experiment. We identified 46 bacterial populations (spanning 9 phyla) and 243 viral populations that actively took up 18O in soil and respired CO2 throughout the incubation. Active bacterial populations represented only a small portion of the detected microbial community and were capable of fermentation and organic matter degradation. In contrast, active viral populations represented a large portion of the detected viral community and one third were linked to active bacterial populations. We identified 86 auxiliary metabolic genes and other environmentally relevant genes. The majority of these genes were carried by active viral populations and had diverse functions such as carbon utilization and scavenging that could provide their host with a fitness advantage for utilizing much-needed carbon sources or acquiring essential nutrients.
Overall, there was a stark difference in the identity and function of the active bacterial and viral community compared to the unlabeled community that would have been overlooked with a non-targeted standard metagenomic analysis. Our results illustrate that substantial active virus-host interactions occur in sub-freezing anoxic conditions and highlight viruses as a major community-structuring agent that likely modulates carbon loss in peat soils during winter, which may be pivotal for understanding the future fate of arctic soils' vast carbon stocks.
","language":"English","publisher":"Springer","doi":"10.1186/s40168-021-01154-2","usgsCitation":"Trubl, G., Kimbrel, J.A., Liquet-Gonzalez, J., Nuccio, E.E., Weber, P.K., Pett-Ridge, J., Jansson, J.K., Waldrop, M., and Blazewicz, S., 2021, Active virus-host interactions at sub-freezing temperatures in Arctic peat soil: Microbiome, v. 9, 208, 15 p., https://doi.org/10.1186/s40168-021-01154-2.","productDescription":"208, 15 p.","ipdsId":"IP-128011","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467223,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40168-021-01154-2","text":"Publisher Index Page"},{"id":462901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2021-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Trubl, Gareth","contributorId":345156,"corporation":false,"usgs":false,"family":"Trubl","given":"Gareth","email":"","affiliations":[{"id":82502,"text":"Lawrence Livermore National Labs","active":true,"usgs":false}],"preferred":false,"id":915862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kimbrel, Jeffrey A","contributorId":345157,"corporation":false,"usgs":false,"family":"Kimbrel","given":"Jeffrey","email":"","middleInitial":"A","affiliations":[{"id":82502,"text":"Lawrence Livermore National Labs","active":true,"usgs":false}],"preferred":false,"id":915863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liquet-Gonzalez, Jose","contributorId":345158,"corporation":false,"usgs":false,"family":"Liquet-Gonzalez","given":"Jose","email":"","affiliations":[{"id":82502,"text":"Lawrence Livermore National Labs","active":true,"usgs":false}],"preferred":false,"id":915864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nuccio, Erin E.","contributorId":345159,"corporation":false,"usgs":false,"family":"Nuccio","given":"Erin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":915865,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weber, Peter K.","contributorId":345160,"corporation":false,"usgs":false,"family":"Weber","given":"Peter","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":915866,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pett-Ridge, Jennifer","contributorId":254974,"corporation":false,"usgs":false,"family":"Pett-Ridge","given":"Jennifer","affiliations":[{"id":51376,"text":"Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore CA 94551","active":true,"usgs":false}],"preferred":false,"id":915867,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jansson, Janet K.","contributorId":345161,"corporation":false,"usgs":false,"family":"Jansson","given":"Janet","email":"","middleInitial":"K.","affiliations":[{"id":82503,"text":"Pacific Northwest National Labs","active":true,"usgs":false}],"preferred":false,"id":915868,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216758,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[],"preferred":true,"id":915869,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Blazewicz, Steve 0000-0001-7517-1750","orcid":"https://orcid.org/0000-0001-7517-1750","contributorId":272100,"corporation":false,"usgs":false,"family":"Blazewicz","given":"Steve","email":"","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":915870,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70226823,"text":"70226823 - 2021 - Effects of hydrologic variability and remedial actions on first flush and metal loading from streams draining the Silverton caldera, 1992–2014","interactions":[],"lastModifiedDate":"2021-12-14T12:52:04.069102","indexId":"70226823","displayToPublicDate":"2021-10-18T06:45:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Effects of hydrologic variability and remedial actions on first flush and metal loading from streams draining the Silverton caldera, 1992–2014","docAbstract":"This study examined water quality in the upper Animas River watershed, a mined watershed that gained notoriety following the 2015 Gold King mine release of acid mine drainage to downstream communities. Water-quality data were used to evaluate trends in metal concentrations and loads over a two-decade period. Selected sites included three sites on tributary streams and one main-stem site on the Animas River downstream from the tributary confluences. During the study period, metal concentrations and loads varied seasonally and annually because of hydrologic variability and remedial actions designed to ameliorate the effects of acid mine drainage. Water-quality data were divided into two periods based on the timing of remedial activities in the watershed. The first period includes active water treatment, surface reclamation and installation of bulkheads in adits; the second period includes the decade following these activities. Water-quality data were used to estimate annual and monthly zinc loads using the Adjusted Maximum Likelihood Method (using LOADEST software) and U.S. Geological Survey streamflow data. This study presents one of the first applications of LOADEST focused on metal loads. Monthly flow-weighted concentrations were analysed using a Mann-Kendall trend test to determine the direction, magnitude, and significance of temporal trends in zinc loading in any given month and using t-test comparisons between the two periods. Zinc loads estimated for the Animas River below the tributaries indicate decreased zinc loading during the rising limb of the hydrograph in the second period, perhaps reflecting a reduction of snowmelt-derived zinc load following surface reclamation activities. In contrast, base-flow zinc loading increased at the main-stem site, perhaps because of the cessation of water treatment in tributary streams. Flow weighting of monthly load estimates yielded increased statistical significance and enabled more nuanced differentiation between the effects of hydrologic variability and remedial activities on zinc loading.
For several decades, white plagues (WPDs: WPD-I, II and III) and more recently, stony coral tissue loss disease (SCTLD) have significantly impacted Caribbean corals. These diseases are often difficult to separate in the field as they produce similar gross signs. Here we aimed to compare what we know about WPD and SCTLD in terms of: (1) pathology, (2) etiology, and (3) epizootiology. We reviewed over 114 peer-reviewed publications from 1973 to 2021. Overall, WPD and SCTLD resemble each other macroscopically, mainly due to the rapid tissue loss they produce in their hosts, however, SCTLD has a more concise case definition. Multiple-coalescent lesions are often observed in colonies with SCTLD and rarely in WPD. A unique diagnostic sign of SCTLD is the presence of bleached circular areas when SCTLD lesions are first appearing in the colony. The paucity of histopathologic archives for WPDs for multiple species across geographies makes it impossible to tell if WPD is the same as SCTLD. Both diseases alter the coral microbiome. WPD is controversially regarded as a bacterial infection and more recently a viral infection, whereas for SCTLD the etiology has not been identified, but the putative pathogen, likely to be a virus, has not been confirmed yet. Most striking differences between WPD and SCTLD have been related to duration and phases of epizootic events and mortality rates. While both diseases may become highly prevalent on reefs, SCTLD seems to be more persistent even throughout years. Both transmit directly (contact) and horizontally (waterborne), but organism-mediated transmission is only proven for WPD-II. Given the differences and similarities between these diseases, more detailed information is needed for a better comparison. Specifically, it is important to focus on: (1) tagging colonies to look at disease progression and tissue mortality rates, (2) tracking the fate of the epizootic event by looking at initial coral species affected, the features of lesions and how they spread over colonies and to a wider range of hosts, (3) persistence across years, and (4) repetitive sampling to look at changes in the microbiome as the disease progresses. Our review shows that WPDs and SCTLD are the major causes of coral tissue loss recorded in the Caribbean.
We quantified permafrost peat plateau and post-thaw carbon (C) stocks across a chronosequence in Interior Alaska to evaluate the amount of C lost with thaw. Macrofossil reconstructions revealed three stratigraphic layers of peat: (1) a base layer of fen/marsh peat, (2) peat from a forested peat plateau (with permafrost) and, (3) collapse-scar bog peat (at sites where permafrost thaw has occurred). Radiocarbon dating revealed that peat initiated within the last 2,500 years and that permafrost aggraded during the Little Ice Age (ca. 250 – 575 years ago) and degraded within the last several decades. The timing of permafrost thaw within each feature was not related to thaw bog size. Their rate of expansion may be more influenced by local factors, such as ground ice content and subsurface water inputs. We found C losses due to thaw over the past century were up to 46% of the C available, but the absolute amount of C lost (kg m-2) was over 50% lower than losses previously described in other Alaskan peatland chronosequences. We hypothesize that this difference stems from the process by which permafrost aggraded, with sites that formed permafrost epigenetically (significantly later than most peat accumulation) experiencing less absolute C loss with thaw than sites that formed syngenetically (simultaneously with peat accumulation). Epigenetic peat from our site had lower C:N ratios as compared to Alaskan sites that have syngenetic peat. This difference could help predict the magnitude of C loss with thaw across a range or permafrost types and histories.
In forested wetlands, accumulation of organic matter in soil is partly governed by carbon fluxes where photosynthesis, respiration, lateral advection of waterborne carbon, fire-derived carbon emissions, and methanogenesis are balanced by changes in stored carbon. Stored carbon can eventually accumulate as soil over time if net primary productivity exceeds biomass decomposition. For this study, potential soil accumulation was estimated based on four years of continuous daily carbon cycling data and a one-dimensional mass-balance model of landscape-atmospheric exchange for cypress and pine forested wetlands in the Greater Everglades of south Florida. The mass-balance model was driven by eddy-covariance estimates of vertical net ecosystem exchange of carbon dioxide and methane. Key findings include confirmation of a basic premise of the historic Everglades restoration project; specifically, more water either from rainfall or water management encourages soil carbon accumulation and thus conservation of soils that support biologic activity and ecosystem services. For example, an anomalous wet season for south Florida that flooded the forested wetlands through the traditional dry season was followed by the most productive year for photosynthetic carbon uptake and potential soil accumulation. On the other hand, methane emissions were enhanced by the anomalous wet season and extended flooding – which confirmed a complex tradeoff to consider if wetlands are managed for both soil conservation and reduction of greenhouse gas emissions. Potential soil accumulation rates were about 1.7, 2.8, and 18 millimeters per year at the Dwarf Cypress, Cypress Swamp, and Pine Upland ecosystems, assuming soil C density values of 0.07, 0.09, and 0.02 grams of carbon per cubic centimeter, respectively. For these values of soil C density, the accumulation rates are considered a “best-case” upper limit because the lateral export of carbon in the canals and creeks that drain the study area were assumed negligible.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wetland carbon and environmental management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/9781119639305.ch20","usgsCitation":"Shoemaker, W.B., Anderson, F.E., Sirianni, M., and Daniels, A., 2021, Carbon fluxes and potential soil accumulation within Greater Everglades cypress and pine forested wetlands, chap. 20 of Wetland carbon and environmental management, p. 371-384, https://doi.org/10.1002/9781119639305.ch20.","productDescription":"14 p.","startPage":"371","endPage":"384","ipdsId":"IP-111043","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":436158,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GFKJCY","text":"USGS data release","linkHelpText":"Potential Accumulation of Soil Organic Matter from Carbon Cycling within Greater Everglades Cypress and Pine Forested Wetlands data"},{"id":394397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.1,\n 25.5\n ],\n [\n -80.5,\n 25.5\n ],\n [\n -80.5,\n 26\n ],\n [\n -81.1,\n 26\n ],\n [\n -81.1,\n 25.5\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-10-15","publicationStatus":"PW","contributors":{"editors":[{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":823426,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":823425,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":830889,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Shoemaker, W. Barclay 0000-0002-7680-377X bshoemak@usgs.gov","orcid":"https://orcid.org/0000-0002-7680-377X","contributorId":215239,"corporation":false,"usgs":true,"family":"Shoemaker","given":"W.","email":"bshoemak@usgs.gov","middleInitial":"Barclay","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823423,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Frank E. 0000-0002-1418-4678 fanders@usgs.gov","orcid":"https://orcid.org/0000-0002-1418-4678","contributorId":2605,"corporation":false,"usgs":true,"family":"Anderson","given":"Frank","email":"fanders@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830887,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daniels, Andre 0000-0003-4172-2344 andre_daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-4172-2344","contributorId":4031,"corporation":false,"usgs":true,"family":"Daniels","given":"Andre","email":"andre_daniels@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":830888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sirianni, Matt 0000-0002-6296-0002","orcid":"https://orcid.org/0000-0002-6296-0002","contributorId":265804,"corporation":false,"usgs":false,"family":"Sirianni","given":"Matt","email":"","affiliations":[{"id":17770,"text":"FAU","active":true,"usgs":false}],"preferred":false,"id":823424,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220231,"text":"70220231 - 2021 - Modeling the impacts of hydrology and management on carbon balance at the Great Dismal Swamp, Virginia and North Carolina, USA","interactions":[],"lastModifiedDate":"2022-03-07T17:39:52.92648","indexId":"70220231","displayToPublicDate":"2021-10-15T11:34:26","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"21","title":"Modeling the impacts of hydrology and management on carbon balance at the Great Dismal Swamp, Virginia and North Carolina, USA","docAbstract":"The impact of drainage on the stability of peatland carbon sinks is well known; however, much less is understood regarding the way active management of the water-table affects carbon balance. In this study, we determined the carbon balance in the Great Dismal Swamp, a large, forested peatland in the southeastern USA, which has been drained for over two hundred years and is now being restored through hydrologic management. We modeled future net ecosystem carbon balance over 100 years (2012 to 2112) using in situ field observations paired with simulations of water-table depth. The three scenarios used in the model were baseline conditions, flooded/wet conditions, and drained/dry conditions, which represent a range of potential management actions and climate conditions at the Great Dismal Swamp. In the Baseline scenario, results show a carbon sink of 0.7 Tg, or an average annual rate of 0.23 Mg C/ha/yr. The Flooded/Wet scenario produced a net ecosystem carbon balance of 4.6 Tg C or an average annual rate of 1.06 Mg C/ha/yr. For the Drained/Dry scenario, under which no management was conducted, and typically dry conditions were assumed, the Great Dismal Swamp becomes a net carbon source at –2.07 Tg C or an average annual rate of –0.38 Mg C/ha/yr.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wetland carbon and environmental management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/9781119639305.ch21","usgsCitation":"Sleeter, R., 2021, Modeling the impacts of hydrology and management on carbon balance at the Great Dismal Swamp, Virginia and North Carolina, USA, chap. 21 of Wetland carbon and environmental management, p. 385-402, https://doi.org/10.1002/9781119639305.ch21.","productDescription":"18 p.","startPage":"385","endPage":"402","ipdsId":"IP-119032","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":436160,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P970W305","text":"USGS data release","linkHelpText":"Model parameters and output of net ecosystem carbon balance for the Great Dismal Swamp, Virginia and North Carolina, USA"},{"id":396799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia","otherGeospatial":"Great Dismal Swamp","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.57058715820312,\n 36.42017738514984\n ],\n [\n -76.35223388671875,\n 36.42017738514984\n ],\n [\n -76.35223388671875,\n 36.79389010047562\n ],\n [\n -76.57058715820312,\n 36.79389010047562\n ],\n [\n -76.57058715820312,\n 36.42017738514984\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-10-15","publicationStatus":"PW","contributors":{"editors":[{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":837369,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":837370,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":837371,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Sleeter, Rachel 0000-0003-3477-0436 rsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-0436","contributorId":666,"corporation":false,"usgs":true,"family":"Sleeter","given":"Rachel","email":"rsleeter@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":814868,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70224318,"text":"70224318 - 2021 - Summary of wetland carbon and environmental management: Path forward","interactions":[],"lastModifiedDate":"2022-01-14T17:47:03.948432","indexId":"70224318","displayToPublicDate":"2021-10-15T11:13:35","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"25","title":"Summary of wetland carbon and environmental management: Path forward","docAbstract":"Wetlands around the world are under pressure from both anthropogenic sources such as land-use change and accelerating climate change (Erwin, 2009; Moomaw et al., 2018). Storage of carbon resources is a key ecosystem service of wetlands and offer natural solutions to climate change mitigation; policies and management actions could determine the fate of these resources and their contributions to climate mitigation and society needs. Inland and tidal wetlands store and sequester more carbon in soil and biomass than any other ecosystems on a per unit area basis, but also are responsible for the majority of ecosystem methane emissions (NASEM, 2019; Knox et al., 2019). Most of wetland carbon is stored deep in soils, thus providing long-term preservation of the resource (Nahlik and Fennessy, 2016). In addition to productive carbon sequestration in situ, wetlands also play a major role in lateral fluxes of carbon and other greenhouse gases along the continuum of different landscape features, including lakes, rivers, and coastal waters (Aufdenkampe et al., 2011; Ciais et al., 2008; Troxler et al., 2013). The ability of wetlands to regulate key processes of the carbon cycle is related to characteristics of the ecosystem, particularly hydrologic functions (Zhou et al., 2018). Disturbances to wetland hydrology, from land use change to natural disturbances such as wildfire, could lead to major disruptions to the wetland carbon cycle (Moomaw et al., 2018).\n\nThis book is organized to first introduce fundamentals of wetland biogeochemistry (Neubauer and Megonigal, 2020) and carbon stock distribution and management in broad geographic and temporal domains, then provide a more in-depth treatment of case studies of different wetland types across the world (Fig. 1). A range of wetland management actions are described in the context of carbon sequestration and greenhouse gas emissions, including hydrology, sediment, avoided loss, restoration, wildfire, and co-habitation of multiple uses. Different wetland types or land uses considered in this book include freshwater herbaceous wetlands, peatlands of temperate as well as tropical climate, coastal tidal marshes and mangroves, drained croplands, and rice paddies.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wetland carbon and environmental management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/9781119639305.ch25","usgsCitation":"Zhu, Z., Krauss, K., Stagg, C., Ward, E., and Woltz, V., 2021, Summary of wetland carbon and environmental management: Path forward, chap. 25 of Wetland carbon and environmental management, p. 437-446, https://doi.org/10.1002/9781119639305.ch25.","productDescription":"14 p.","startPage":"437","endPage":"446","ipdsId":"IP-120337","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":394395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-10-15","publicationStatus":"PW","contributors":{"editors":[{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":830893,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":830894,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":830895,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":823736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":223022,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":823737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":222386,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":823738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":217389,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":823739,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woltz, Victoria 0000-0001-7843-6486","orcid":"https://orcid.org/0000-0001-7843-6486","contributorId":223011,"corporation":false,"usgs":true,"family":"Woltz","given":"Victoria","email":"","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":823740,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248819,"text":"70248819 - 2021 - Ecosystem service co-benefits provided through wetland carbon management","interactions":[],"lastModifiedDate":"2023-09-22T14:59:46.733808","indexId":"70248819","displayToPublicDate":"2021-10-15T09:59:09","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"22","title":"Ecosystem service co-benefits provided through wetland carbon management","docAbstract":"What is the role of wetland carbon management in providing ecosystem services? Ecosystem services are the benefits that nature provides to people, and they are often categorized as: provisioning (e.g., food and water), regulating (e.g., climate mitigation and flood protection), cultural (e.g., cultural and recreational), and supporting (e.g., nutrient cycling) services ( www.millenniumassessment.org/ ). Ecosystem services are a function of the quantity and quality of the ecosystem. External factors such as land development, pollution, fragmentation, resource overuse, and climate change can negatively influence an ecosystem's capacity to provide ecosystem services; conversely, management actions to conserve and restore systems can increase ecosystem services (Pindilli, 2019). Wetland carbon management is a set of preservation, conservation, or restoration actions used to preserve ecosystem function that protects or enhances stored carbon or biologic carbon sequestration, with the intent to regulate climate (see Moomaw et al., 2018). By managing for wetland carbon resources, there is often a co-benefit of the preservation or enhancement of other ecosystem services; it may also increase ecosystem disservices (such as mosquito production). This chapter provides an overview of the types of ecosystem service co-benefits provided by wetland carbon management, with specific examples from the literature.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wetland carbon and environmental management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/9781119639305.ch22","usgsCitation":"Pindilli, E., 2021, Ecosystem service co-benefits provided through wetland carbon management, chap. 22 of Wetland carbon and environmental management, p. 401-409, https://doi.org/10.1002/9781119639305.ch22.","productDescription":"9 p.","startPage":"401","endPage":"409","ipdsId":"IP-122236","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":421079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-10-15","publicationStatus":"PW","contributors":{"editors":[{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":883899,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":883900,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":883901,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Pindilli, Emily 0000-0002-5101-1266 epindilli@usgs.gov","orcid":"https://orcid.org/0000-0002-5101-1266","contributorId":140262,"corporation":false,"usgs":true,"family":"Pindilli","given":"Emily","email":"epindilli@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":883776,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70224983,"text":"fs20213004 - 2021 - A 40-year story of river sediment at Mount St. Helens","interactions":[],"lastModifiedDate":"2021-10-14T11:41:35.110065","indexId":"fs20213004","displayToPublicDate":"2021-10-13T14:58:02","publicationYear":"2021","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":"2021-3004","displayTitle":"A 40-Year Story of River Sediment at Mount St. Helens","title":"A 40-year story of river sediment at Mount St. Helens","docAbstract":"The 1980 eruption of Mount St. Helens in Washington State unleashed one of the largest debris avalanches (landslide) in recorded history. The debris avalanche deposited 3.3 billion cubic yards of material into the upper North Fork Toutle River watershed and obstructed the Columbia River shipping channel downstream. From the eruption on May 18, 1980, to September 30, 2018, the Toutle River transported a total of about 405 million tons of sediment into the lower Cowlitz River—enough to bury downtown Portland, Oregon, to a depth of 300 feet. Excluding the massive sediment load from the eruption itself, from October 1, 1980, to September 30, 2018, the Toutle River transported more than 248 million tons of sediment, or an average of 6.5 million tons per year.
Increased flood risk to downstream communities is managed by a sediment retention structure, grade building structures, berms, levees, and dredging. Near-real-time monitoring of streamflow and sediment yield is important for effective management of these dynamic mitigation efforts. Since the sediment retention structure began trapping sediment in November 1987, the Toutle River has transported on average 2.8 million tons of sediment per year into the lower Cowlitz River. This is still 10 times greater than pre-eruption levels, with higher sediment transport potentially approaching 50 to 100 times greater during storms. Despite the eruption lasting only a few hours, the socioeconomic effects and mitigation measures for the region continue into the 21st century.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213004","usgsCitation":"Uhrich, M.A., Spicer, K.R., Mosbrucker, A.R., Saunders, D.R., and Christianson, T.S., 2021, A 40-year story of river sediment at Mount St. Helens: U.S. Geological Survey Fact Sheet 2021–3004, 6 p., https://doi.org/10.3133/fs20213004.","productDescription":"Report: 6 p.; Additional Resources","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-114867","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":390437,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3004/covrthb.jpg"},{"id":390438,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3004/fs20213004.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":390439,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3004/fs20213004_resources.pdf","text":"Additional resources","size":"300 KB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.3876953125,\n 46.132266708957125\n ],\n [\n -121.87957763671876,\n 46.132266708957125\n ],\n [\n -121.87957763671876,\n 46.36588370484979\n ],\n [\n -122.3876953125,\n 46.36588370484979\n ],\n [\n -122.3876953125,\n 46.132266708957125\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
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U.S. Geological Survey
1300 SE Cardinal Court
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Rano Raraku, the crater lake constrained by basaltic tuff that served as the primary quarry used to construct the moai statues on Rapa Nui (Easter Island), has experienced fluctuations in lake level over the past centuries. As one of the only freshwater sources on the island, understanding the present and past geochemical characteristics of the lake water is critical to understand if the lake could have been a viable freshwater source for Rapa Nui. At the time of sampling in September 2017, the maximum lake depth was ~1 m. The lake level has substantially declined in the subsequent years, with the lake drying almost completely in January 2018. The lake is currently characterized by highly anoxic conditions, with a predominance of ammonium ions on nitrates, a high concentration of organic carbon in the water-sediment interface and reducing conditions of the lake, as evidenced by Mn/Fe and Cr/V ratios. Our estimates of past salinity inferred from the chloride mass balance indicates that it was unlikely that Rano Raraku provided a viable freshwater source for early Rapa Nui people. The installation of an outlet pipe around 1950 that was active until the late 1970s, as well as grazing of horses on the lake margins appear to have significantly impacted the geochemical conditions of Rano Raraku sediments and lake water in recent decades. Such impacts are distinct from natural environmental changes and highlight the need to consider the sensitivity of the lake geochemistry to human activities.
Per- and polyfluoroalkyl substances (PFAS) have been identified in two lakes near Joint Base McGuire-Dix-Lakehurst (JBMDL) in New Jersey—Little Pine Lake in Pemberton Township and Pine Lake in Manchester Township. The streams that enter these lakes begin in or near JBMDL where sources of PFAS contamination are located. The U.S. Geological Survey, in cooperation with the U.S. Air Force Civil Engineer Center, performed a study of the hydrogeology and the gaining or losing conditions associated with these lakes.
Hydrogeologic characteristics in the vicinity of both lakes were assessed using qualitative vertical hydraulic profiling of the subsurface. Groundwater was pumped from test intervals at various depths below land surface, then groundwater levels were measured until they recovered to static conditions. Low permeability aquifer intervals were identified within the aquifer underlying both lakes, consistent with silty and (or) clayey subunits of the Kirkwood-Cohansey aquifer system indicated on geophysical and lithologic logs.
Gaining or losing conditions between groundwater and lake surface water were assessed with continuous monitoring of water levels and temperature in the lakes and in three piezometers per lake screened at different depths in the underlying aquifer from August 2020 through May 2021. At Little Pine Lake, surface water levels were consistently lower than groundwater levels, which is indicative of a gaining condition with groundwater flowing into the lake. Gaining conditions also support the lack of diurnal temperature fluctuations observed in groundwater, but poor response of surface-water temperature prevents complete analysis. The potential for losing conditions at other locations around Little Pine Lake necessitates further assessment in regard to possible PFAS contamination of groundwater in the underlying aquifer. Temperature results were inconclusive at Pine Lake, but surface water levels were consistently higher than groundwater levels throughout the monitoring period, which indicates a losing condition with lake water flowing into the underlying aquifer. Because of the downward vertical hydraulic gradient identified at Pine Lake, there is a strong possibility that PFAS in the lake water has also contaminated groundwater in its vicinity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215107","collaboration":"Prepared in cooperation with the U.S. Air Force","usgsCitation":"Fiore, A.R., Witzigman, C.M., and Reiser, R.G., 2021, Hydrogeology and gain/loss assessment of two lakes contaminated with per- and polyfluoroalkyl substances, vicinity of Joint Base McGuire-Dix-Lakehurst, New Jersey, 2020–21: U.S. Geological Survey Scientific Investigations Report 2021–5107, 24 p., https://doi.org/10.3133/sir20215107.","productDescription":"Report: viii, 24 p.; Database: 2","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-129804","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":390423,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215107/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":390422,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5107/sir20215107.XML"},{"id":390421,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5107/images/"},{"id":390416,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7X63KT0","text":"USGS GeoLog locator database"},{"id":390415,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://www13.state.nj.us/DataMiner","text":"DEP DataMiner database"},{"id":390414,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5107/sir20215107.pdf","text":"Report","size":"3.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5107"},{"id":390413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5107/coverthb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Joint Base McGuire-Dix-Lakehurst","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.68505859374999,\n 39.93711893299023\n ],\n [\n -74.2023468017578,\n 39.93711893299023\n ],\n [\n -74.2023468017578,\n 40.111688665595956\n ],\n [\n -74.68505859374999,\n 40.111688665595956\n ],\n [\n -74.68505859374999,\n 39.93711893299023\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
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Nitrate concentrations in high-elevation lakes of the Colorado Front Range remain elevated despite declining trends in atmospherically deposited nitrate since 2000. The current source of this elevated nitrate in surface waters remains elusive, given shifts in additional nitrogen sources via glacial inputs and atmospheric ammonium deposition. We present the complete isotopic composition of nitrate (δ15N, δ18O, and Δ17O) from a suite of nitrate-bearing source waters collected during the summers of 2017–2018 from two alpine ecosystems to constrain the provenance of elevated nitrate in surface waters during the summer open-water season. The results indicate a consistent contribution of uncycled atmospheric nitrate throughout the summer (13–23%) to alpine lakes, despite seasonal changes in source water inputs. The balance of nitrate (as high as 87% in late summer) is likely from nitrate production within the catchment via nitrification of reduced nitrogen sources (e.g., thawed soil organic matter and ammonium deposition) and released with rock glacier meltwater. The role of microbially produced nitrate has become increasingly important over time based on historical surface water samples from the mid-90s to present, a trend coincident with increasing ammonium deposition to alpine systems.
","language":"English","publisher":"American Chemical Society Publications","doi":"10.1021/acs.est.1c02515","usgsCitation":"Clark, S.C., Barnes, R.T., Oleksy, I.A., Baron, J., and Hastings, M.G., 2021, Persistent nitrate in alpine waters with changing atmospheric deposition and warming trends: Environmental Science and Technology, v. 55, no. 21, p. 14946-14956, https://doi.org/10.1021/acs.est.1c02515.","productDescription":"11 p.","startPage":"14946","endPage":"14956","ipdsId":"IP-119356","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":395671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Front Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.7049560546875,\n 40\n ],\n [\n -105.3204345703125,\n 40\n ],\n [\n -105.3204345703125,\n 40.50126945841645\n ],\n [\n -105.7049560546875,\n 40.50126945841645\n ],\n [\n -105.7049560546875,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"21","noUsgsAuthors":false,"publicationDate":"2021-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Clark, Sydney C.","contributorId":275307,"corporation":false,"usgs":false,"family":"Clark","given":"Sydney","email":"","middleInitial":"C.","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":833972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnes, Rebecca T.","contributorId":173578,"corporation":false,"usgs":false,"family":"Barnes","given":"Rebecca","email":"","middleInitial":"T.","affiliations":[{"id":27249,"text":"NSF EAR Postdoctoral Fellow","active":true,"usgs":false}],"preferred":false,"id":833973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oleksy, Isabella A.","contributorId":222908,"corporation":false,"usgs":false,"family":"Oleksy","given":"Isabella","email":"","middleInitial":"A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":833974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baron, Jill S. 0000-0002-5902-6251","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":215101,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":833975,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hastings, Meredith G.","contributorId":194136,"corporation":false,"usgs":false,"family":"Hastings","given":"Meredith","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":833976,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270573,"text":"70270573 - 2021 - USGS CEOS analysis ready data for land achievements and future plans","interactions":[],"lastModifiedDate":"2025-08-20T14:55:12.018563","indexId":"70270573","displayToPublicDate":"2021-10-12T08:40:17","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"USGS CEOS analysis ready data for land achievements and future plans","docAbstract":"The efforts of the Committee on Earth Observation Satellites (CEOS) to bring CEOS Analysis Ready Data for Land (CARD4L) products to countries and international organizations quickly and easily continues to receive important support from the U.S. Geological Survey (USGS). As part of its engagement with CARD4L, the USGS worked to address specific Threshold and Target Product Family Specification (PFS) requirements for its Landsat Collection 2 Level-2 science products and in July 2020, received formal CEOS endorsement for 100 percent CARD4L-compliance at the Threshold level for Collection 2 surface reflectance and surface temperature. This endorsement ensures these products meet a level of interoperability with data from other Earth-observing platforms, such as Europe's Sentinel-2 satellites, as the European Space Agency also works toward CARD4L-compliant products. In addition to the Collection 2 Level-2 land surface data products, the USGS recognizes Landsat's potential to make a valuable contribution to aquatic science and environmental monitoring capabilities for aquatic ecosystems, especially in coastal and inland waters. Working with subject matter experts, the USGS has been coordinating an international agency effort to establish a new CARD4L PFS for aquatic reflectance to be considered for CEOS endorsement in 2021.
","conferenceTitle":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","conferenceDate":"July 11-16, 2021","conferenceLocation":"Brussels, Blegium","language":"English","publisher":"IEEE","doi":"10.1109/IGARSS47720.2021.9554440","usgsCitation":"Barnes, C., Siqueira, A., and Labahn, S., 2021, USGS CEOS analysis ready data for land achievements and future plans, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Blegium, July 11-16, 2021, p. 1785-1788, https://doi.org/10.1109/IGARSS47720.2021.9554440.","productDescription":"4 p.","startPage":"1785","endPage":"1788","ipdsId":"IP-129380","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":494346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barnes, Christopher","contributorId":359950,"corporation":false,"usgs":false,"family":"Barnes","given":"Christopher","affiliations":[{"id":68993,"text":"KBR Inc., Contractor to the USGS","active":true,"usgs":false}],"preferred":false,"id":946557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siqueira, Andreia","contributorId":359951,"corporation":false,"usgs":false,"family":"Siqueira","given":"Andreia","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":946558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Labahn, Steven T. 0000-0002-9258-2890 labahn@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2890","contributorId":3994,"corporation":false,"usgs":true,"family":"Labahn","given":"Steven T.","email":"labahn@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":946559,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70225752,"text":"70225752 - 2021 - A comprehensive statewide spatiotemporal stream assessment of per- and polyfluoroalkyl substances (PFAS) in an agricultural region of the United States","interactions":[],"lastModifiedDate":"2021-11-10T13:37:00.433918","indexId":"70225752","displayToPublicDate":"2021-10-12T07:34:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5022,"text":"Environmental Science & Technology Letters","onlineIssn":"2328-8930","active":true,"publicationSubtype":{"id":10}},"title":"A comprehensive statewide spatiotemporal stream assessment of per- and polyfluoroalkyl substances (PFAS) in an agricultural region of the United States","docAbstract":"Public concern regarding per- and polyfluoroalkyl substances (PFAS) has grown substantially in recent years. In addition, research has documented multiple potential agriculture-related release pathways for PFAS (e.g., biosolids and livestock manure). Nevertheless, little research on the environmental prevalence of PFAS has been conducted in agricultural regions of the United States. To fill this gap, we conducted the first statewide spatiotemporal assessment of PFAS in Iowa streams across a region of intense agricultural activity. At least one PFAS was detected at 19 of the 60 stream sites sampled (32%) with 10 different PFAS detected statewide. The number of PFAS detected in the stream samples ranged from one to nine. While PFAS were detected in agricultural streams, sites with the most PFAS detected and in the highest concentration were small, effluent-affected streams where wastewater treatment plant discharge is driving stream PFAS concentrations. No individual PFAS had an exposure:activity ratio (EAR) of >1.0 (exposure concentration shown to trigger observed adverse biological activity). Five stream locations, however, had at least one EAR of >0.001, a precautionary effect screening threshold. Additional targeted temporal sampling would be beneficial to specifically capture potential agricultural source applications and corresponding runoff conditions to fully characterize the prevalence of PFAS in such agricultural systems.
Estuaries represent critical aquatic habitat that connects surface water distributed between Earth’s landmasses and oceans. They are dynamic transitional ecosystems, which provide important habitat for fishes and other aquatic organisms. Effective conservation of species inhabiting estuaries requires knowledge of the habitat features that drive their abundance and distribution. We sought to elucidate how stationary (i.e., wetlands, shoals, and channels) and dynamic (i.e., salinity, temperature, turbidity, and chlorophyll concentration) habitat features interact to drive distributions of individual fish species. The Pacific coast of the conterminous United States has over 400 estuaries of various types. The largest (historical surface area) is San Francisco Estuary, California. We conducted extensive field observations of fishes in the central San Francisco Estuary among stationary habitat types (i.e., wetland, shoal, and channel) over a 19-month period encompassing substantial variability in dynamic water quality conditions. Most of the species observed, especially native species of special management interest, were associated with tidal wetland habitat. Few species exhibited associations with water quality conditions driven by seasonal (temperature) or a combination of broad- and fine-scale ecosystem processes (salinity and turbidity). Our study provides (1) an empirical demonstration of how researchers can deal with the complex and dynamic expressions of habitat in estuarine systems to address urgent natural resource problems and (2) a clear demonstration of the urgent need for habitat restoration and its likely outcome in systems such as San Francisco Estuary. Restoration of suitable tidal wetland habitat on the West Coast of the United States is likely to be an effective conservation tool to support estuarine fishes given that over 90% of historical tidal wetland habitat in San Francisco Estuary and 85% of vegetated wetland habitat along the Pacific coast of the United States has been lost due to human modification.
We show that for some foragers the form that a functional response takes depends on the temporal and spatial scales considered. In representing the consumption rate of an organism, it may be necessary to use a hierarchy of functional responses. Consider, for example, a wading bird foraging in wetland landscape characterized by a spatial distribution of potential foraging sites, such as ponds. At the smallest time scale of minutes or hours, during which a wading bird is foraging within a single site, the functional response will reflect the local density of prey, as well as features of the site that affect the feeding rate, such as water depth. At this short time scale, which is determined by the giving up time of the wading bird in a particular site, prey density may be relatively constant. The food intake from a particular pond is then the product of the time spent before giving-up time and moving to another site and the rate of prey consumption at that site. A prey-centered functional response is most appropriate for describing the prey consumption rate. We propose that over the longer time scale of a day, during which a wading bird may visit several foraging sites, the type of functional response can be considered to be patch centered. That is, it is influenced by the spatial configuration of sites with available prey and the wading bird’s strategy of choosing among different sites and decisions on how long to stay in any given sites. Over the time scale of a day, if the prey densities stay relatively constant, the patch-centered functional response for a constant environment is adequate. However, on the longer time scale of a breeding season, in which changing water levels result in temporal changes in the availability of prey in sites, a third hierarchical level may be relevant. At that scale, the way in which the landscape pattern changes through time, and how the wading bird responds, influences the functional response. This hierarchical concept applies to a colony of breeding wading birds foraging in wetlands such as the Everglades.
Adult “silver-phase” American Eels Anguilla rostrata were a focus of commercial fisheries in the 1970s and 1980s, but stocks have been depleted due to many anthropogenic factors. One significant source of mortality occurs during the downstream migration of eels when passing through turbines at hydroelectric facilities. We sought to construct a model to predict eel migration timing to inform optimization of mitigation actions that might reduce mortality. We utilized commercial catch collected from 16 tributaries in the Penobscot River watershed, Maine (2–10 years), and the Delaware River, New York (31 years). A Bayesian hierarchical approach was used to model the relationship between the timing of silver eel capture and environmental conditions that are known to be related to their movements (i.e., river discharge, water temperature, and lunar cycle). Among river systems, daily catch was associated with higher-than-average flows, temperatures of 7–22°C, and new lunar phase cycles. A cross-validation approach to evaluate the ability of the models to make predictions for new data demonstrated a greater ability (higher R2 values) to predict weekly eel catch (0.01–0.92) compared to daily eel catch (0.00–0.42). In addition, we examined the model’s ability to forecast migration events by applying posterior simulations to make predictions of eel catch by ordinal date. Predicted daily eel catch generally followed the trend of observed daily catch and was stronger for the Delaware River (R2 = 0.67) than for Souadabscook Stream, Maine (R2 = 0.07). Sharp pulses in observed catch were not reflected by the predicted catch. Additionally, variability observed among rivers suggests that site-specific modeling may be advantageous (and necessary) to capture local conditions, thereby improving predictive power. More broadly, our work highlights a novel use of fishery-dependent data in a Bayesian modeling framework to predict intervals of risk for migrating fish.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/mcf2.10182","usgsCitation":"Weaver, D., Sigourney, D., Delucia, M., and Zydlewski, J.D., 2021, Characterizing downstream migration timing of American Eels using commercial catch data in the Penobscot and Delaware rivers: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 13, no. 5, p. 534-547, https://doi.org/10.1002/mcf2.10182.","productDescription":"14 p.","startPage":"534","endPage":"547","ipdsId":"IP-119530","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481100,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10182","text":"Publisher Index Page"},{"id":480929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine, New York","otherGeospatial":"Delaware River, Penobscot 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Conservancy","active":true,"usgs":false}],"preferred":false,"id":924526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":924523,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227461,"text":"70227461 - 2021 - A new analysis of caldera unrest through the integration of geophysical data and FEM modeling: The Long Valley caldera case study","interactions":[],"lastModifiedDate":"2022-01-18T13:17:45.229897","indexId":"70227461","displayToPublicDate":"2021-10-11T07:14:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"A new analysis of caldera unrest through the integration of geophysical data and FEM modeling: The Long Valley caldera case study","docAbstract":"We develop a spatio-temporal geostatistical interpolation framework to estimate hypoxia extent (dissolved oxygen [DO] concentrations below 2 mg/L) with data from a network of DO loggers. The framework uses empirical orthogonal functions and Bayesian kriging to identify the spatially varying temporal pattern and estimate the distribution of hypoxia, including estimation uncertainty. A prototype web application is also developed in R. The framework is applied to analyze spatio-temporal dynamics of DO in the central basin of Lake Erie in North America using data sampled from a logger network placed on the lake bottom during the summers of 2014, 2015, and 2016. Cross-validation results demonstrate that the framework is capable of capturing the dynamic nature of bottom hypoxia over offshore areas, but nearshore areas have poor interpolation performance due to the impacts of complex physical processes such as seiche events. The findings showed that in the central basin, hypoxia started to emerge in early August of 2014, while in 2015 and 2016 hypoxia began in July. The peak hypoxia extent occurred in late September 2014, mid-August 2015, and early September 2016. The prediction error of the overall spatial extent of hypoxia was as large as 25% of the interpolation area based on current logger deployment. Based on the cross-validation and interpolation error, we suggest placing more loggers in nearshore areas to reduce prediction error near the margins of the hypoxic zone.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR027676","usgsCitation":"Xu, W., Collingsworth, P.D., Kraus, R., and Minsker, B., 2021, Spatio-temporal analysis of hypoxia in the Central Basin of Lake Erie of North America: Water Resources Research, e2020WR027676, 21 p., https://doi.org/10.1029/2020WR027676.","productDescription":"e2020WR027676, 21 p.","ipdsId":"IP-118196","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488149,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr027676","text":"Publisher Index Page"},{"id":485521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"central Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.42336336234484,\n 42.064125981872365\n ],\n [\n -80.63612291121615,\n 42.61061044439231\n ],\n [\n -81.33119453643565,\n 42.65041782076645\n ],\n [\n -82.23999909377955,\n 42.12924860730712\n ],\n [\n -82.58547021684097,\n 41.98346357854376\n ],\n [\n -82.60591624431427,\n 41.37891831441843\n ],\n [\n -82.04907153916253,\n 41.448543421544855\n ],\n [\n -81.71420631389763,\n 41.45777327935954\n ],\n [\n -81.26435037076813,\n 41.717583757728164\n ],\n [\n -80.42336336234484,\n 42.064125981872365\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Wenzhao","contributorId":200526,"corporation":false,"usgs":false,"family":"Xu","given":"Wenzhao","email":"","affiliations":[],"preferred":false,"id":935976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collingsworth, Paris D.","contributorId":145526,"corporation":false,"usgs":false,"family":"Collingsworth","given":"Paris","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":935977,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":935978,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minsker, Barbara","contributorId":200528,"corporation":false,"usgs":false,"family":"Minsker","given":"Barbara","email":"","affiliations":[],"preferred":false,"id":935979,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}