Negative relationships between dissolved organic carbon (DOC) concentration and fish productivity have been reported from correlative studies across lakes, but to date there have not been experimental tests of these relationships. We increased the DOC concentration in a lake by 3.4 mg L-1, using a before-after control-impact (BACI) design, to quantify the effects on the productivity and population structure of Largemouth Bass (Micropterus salmoides). Greater DOC reduced the volume of the epilimnion, the preferred habitat of Largemouth Bass, resulting in increased bass density. The likelihood that adult bass had empty diets decreased despite this increase in bass density; diet composition also changed. There was no apparent change in bass growth or condition. Overall, there was no net change in Largemouth Bass productivity. However, changes in YOY and juvenile recruitment and feeding success suggest the possibility that future effects could occur. Our results are the first to examine the effects of an increase in DOC on fish productivity through a five-year temporal lens, which demonstrates that the relationship between DOC and fish productivity is multi-dimensional and complex.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2017-0283","usgsCitation":"Koizumi, S., Craig, N., Zwart, J., Kelly, P.T., Ziegler, J.P., Weidel, B., Jones, S.E., and Solomon, C.T., 2018, Experimental whole-lake dissolved organic carbon increase alters fish diet and density but not growth or productivity: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 11, p. 1859-1867, https://doi.org/10.1139/cjfas-2017-0283.","productDescription":"9 p.","startPage":"1859","endPage":"1867","ipdsId":"IP-090537","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":501085,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/89189","text":"External Repository"},{"id":352686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"11","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6fae4b0da30c1bfc008","contributors":{"authors":[{"text":"Koizumi, Shuntaro","contributorId":203399,"corporation":false,"usgs":false,"family":"Koizumi","given":"Shuntaro","email":"","affiliations":[{"id":36610,"text":"McGill","active":true,"usgs":false}],"preferred":false,"id":731391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Craig, Nicola","contributorId":150803,"corporation":false,"usgs":false,"family":"Craig","given":"Nicola","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":731392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":731393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelly, Patrick T.","contributorId":193577,"corporation":false,"usgs":false,"family":"Kelly","given":"Patrick","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":731394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ziegler, Jacob P.","contributorId":196715,"corporation":false,"usgs":false,"family":"Ziegler","given":"Jacob","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":731395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":731390,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Stuart E.","contributorId":203400,"corporation":false,"usgs":false,"family":"Jones","given":"Stuart","email":"","middleInitial":"E.","affiliations":[{"id":36611,"text":"Notre Dame","active":true,"usgs":false}],"preferred":false,"id":731396,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":731397,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196147,"text":"sim3393 - 2018 - Delineation of the hydrogeologic framework of the Big Sioux aquifer near Sioux Falls, South Dakota, using airborne electromagnetic data","interactions":[],"lastModifiedDate":"2018-09-25T08:02:09","indexId":"sim3393","displayToPublicDate":"2018-03-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3393","title":"Delineation of the hydrogeologic framework of the Big Sioux aquifer near Sioux Falls, South Dakota, using airborne electromagnetic data","docAbstract":"The U.S. Geological Survey, in cooperation with the City of Sioux Falls, South Dakota, began developing a groundwater-flow model of the Big Sioux aquifer in 2014 that will enable the City to make more informed water management decisions, such as delineation of areas of the greatest specific yield, which is crucial for locating municipal wells. Innovative tools are being evaluated as part of this study that can improve the delineation of the hydrogeologic framework of the aquifer for use in development of a groundwater-flow model, and the approach could have transfer value for similar hydrogeologic settings. The first step in developing a groundwater-flow model is determining the hydrogeologic framework (vertical and horizontal extents of the aquifer), which typically is determined by interpreting geologic information from drillers’ logs and surficial geology maps. However, well and borehole data only provide hydrogeologic information for a single location; conversely, nearly continuous geophysical data are collected along flight lines using airborne electromagnetic (AEM) surveys. These electromagnetic data are collected every 3 meters along a flight line (on average) and subsequently can be related to hydrogeologic properties. AEM data, coupled with and constrained by well and borehole data, can substantially improve the accuracy of aquifer hydrogeologic framework delineations and result in better groundwater-flow models.
AEM data were acquired using the Resolve frequency-domain AEM system to map the Big Sioux aquifer in the region of the city of Sioux Falls. The survey acquired more than 870 line-kilometers of AEM data over a total area of about 145 square kilometers, primarily over the flood plain of the Big Sioux River between the cities of Dell Rapids and Sioux Falls. The U.S. Geological Survey inverted the survey data to generate resistivity-depth sections that were used in two-dimensional maps and in three-dimensional volumetric visualizations of the Earth resistivity distribution. Contact lines were drawn using a geographic information system to delineate interpreted geologic stratigraphy. The contact lines were converted to points and then interpolated into a raster surface. The methods used to develop elevation and depth maps of the hydrogeologic framework of the Big Sioux aquifer are described herein.
The final AEM interpreted aquifer thickness ranged from 0 to 31 meters with an average thickness of 12.8 meters. The estimated total volume of the aquifer was 1,060,000,000 cubic meters based on the assumption that the top of the aquifer is the land-surface elevation. A simple calculation of the volume (length times width times height) of a previous delineation of the aquifer estimated the aquifer volume at 378,000,000 cubic meters; thus, the estimation based on AEM data is more than twice the previous estimate. The depth to top of Sioux Quartzite, which ranged in depth from 0 to 90 meters, also was delineated from the AEM data.
Director, Dakota Water Science Center, South Dakota Office
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
Unique responses to climate change can occur across intraspecific levels, resulting in individualistic adaptation or movement patterns among populations within a given species. Thus, the need to model potential responses among genetically distinct populations within a species is increasingly recognized. However, predictive models of future distributions are regularly fit at the species level, often because intraspecific variation is unknown or is identified only within limited sample locations. In this study, we considered the role of intraspecific variation to shape the geographic distribution of ponderosa pine (Pinus ponderosa), an ecologically and economically important tree species in North America. Morphological and genetic variation across the distribution of ponderosa pine suggest the need to model intraspecific populations: the two varieties (var. ponderosa and var. scopulorum) and several haplotype groups within each variety have been shown to occupy unique climatic niches, suggesting populations have distinct evolutionary lineages adapted to different environmental conditions. We utilized a recently-available, geographically-widespread dataset of intraspecific variation (haplotypes) for ponderosa pine and a recently-devised lineage distance modeling approach to derive additional, likely intraspecific occurrence locations. We confirmed the relative uniqueness of each haplotype-climate relationship using a niche-overlap analysis, and developed ecological niche models (ENMs) to project the distribution for two varieties and eight haplotypes under future climate forecasts. Future projections of haplotype niche distributions generally revealed greater potential range loss than predicted for the varieties. This difference may reflect intraspecific responses of distinct evolutionary lineages. However, directional trends are generally consistent across intraspecific levels, and include a loss of distributional area and an upward shift in elevation. Our results demonstrate the utility in modeling intraspecific response to changing climate and they inform management and conservation strategies, by identifying haplotypes and geographic areas that may be most at risk, or most secure, under projected climate change.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/sysbio/syy017","usgsCitation":"Maguire, K.C., Shinneman, D.J., Potter, K.M., and Hipkins, V.D., 2018, Intraspecific niche models for ponderosa pine (Pinus ponderosa) suggest potential variability in population-level response to climate change: Systematic Biology, v. 67, no. 6, p. 965-978, https://doi.org/10.1093/sysbio/syy017.","productDescription":"14 p.","startPage":"965","endPage":"978","ipdsId":"IP-088076","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468902,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/sysbio/syy017","text":"Publisher Index Page"},{"id":352679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"67","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5afee6f9e4b0da30c1bfc000","contributors":{"authors":[{"text":"Maguire, Kaitlin C. 0000-0001-8193-2384","orcid":"https://orcid.org/0000-0001-8193-2384","contributorId":203419,"corporation":false,"usgs":true,"family":"Maguire","given":"Kaitlin","email":"","middleInitial":"C.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":731442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":731443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Potter, Kevin M.","contributorId":167660,"corporation":false,"usgs":false,"family":"Potter","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":24794,"text":"Department of Forestry and Environmental Resources, North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":731444,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hipkins, Valerie D.","contributorId":167661,"corporation":false,"usgs":false,"family":"Hipkins","given":"Valerie","email":"","middleInitial":"D.","affiliations":[{"id":24795,"text":"National Forest Genetics Laboratory, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":731445,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196112,"text":"70196112 - 2018 - Tributyltin: Advancing the science on assessing endocrine disruption with an unconventional endocrine-disrupting compound","interactions":[],"lastModifiedDate":"2018-09-04T09:16:33","indexId":"70196112","displayToPublicDate":"2018-03-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Tributyltin: Advancing the science on assessing endocrine disruption with an unconventional endocrine-disrupting compound","docAbstract":"Tributyltin (TBT) has been recognized as an endocrine disrupting chemical (EDC) for several decades. However, only in the last decade, was its primary endocrine mechanism of action (MeOA) elucidated—interactions with the nuclear retinoid-X receptor (RXR), peroxisome proliferator-activated receptor γ (PPARγ), and their heterodimers. This molecular initiating event (MIE) alters a range of reproductive, developmental, and metabolic pathways at the organism level. It is noteworthy that a variety of MeOAs have been proposed over the years for the observed endocrine-type effects of TBT; however, convincing data for the MIE was provided only recently and now several researchers have confirmed and refined the information on this MeOA. One of the most important lessons learned from years of research on TBT concerns apparent species sensitivity. Several aspects such as the rates of uptake and elimination, chemical potency, and metabolic capacity are all important for identifying the most sensitive species for a given chemical, including EDCs. For TBT, much of this was discovered by trial and error, hence important relationships and important sensitive taxa were not identified until several decades after its introduction to the environment. As recognized for many years, TBT-induced responses are known to occur at very low concentrations for molluscs, a fact that has more recently also been observed in fish species. This review explores the MeOA and effects of TBT in different species (aquatic molluscs and other invertebrates, fish, amphibians, birds, and mammals) according to the OECD Conceptual Framework for Endocrine Disruptor Testing and Assessment (CFEDTA). The information gathered on biological effects that are relevant for populations of aquatic animals was used to construct Species Sensitivity Distributions (SSDs) based on No Observed Effect Concentrations (NOECs) and Lowest Observed Effect Concentrations (LOECs). Fish appear at the lower end of these distributions, showing that they are as sensitive as molluscs, and for some species, even more sensitive. Concentrations in the range of 1 ng/L for water exposure (10 ng/g for whole-body burden) have been shown to elicit endocrine-type responses, whereas mortality occurs at water concentrations ten times higher. Current screening and assessment methodologies as compiled in the OECD CFEDTA are able to identify TBT as a potent endocrine disruptor with a high environmental risk for the original use pattern. If those approaches had been available when TBT was introduced to the market, it is likely that its use would have been regulated sooner, thus avoiding the detrimental effects on marine gastropod populations and communities as documented over several decades.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reviews of environmental contamination and toxicology Volume 245","language":"English","publisher":"Springer","doi":"10.1007/398_2017_8","usgsCitation":"Lagadic, L., Katsiadaki, I., Biever, R.C., Guiney, P., Karouna-Renier, N., Schwarz, T., and Meador, J., 2018, Tributyltin: Advancing the science on assessing endocrine disruption with an unconventional endocrine-disrupting compound, chap. of Reviews of environmental contamination and toxicology Volume 245, v. 245, p. 65-127, https://doi.org/10.1007/398_2017_8.","productDescription":"63 p.","startPage":"65","endPage":"127","ipdsId":"IP-075961","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":352685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"245","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-09","publicationStatus":"PW","scienceBaseUri":"5afee6fae4b0da30c1bfc006","contributors":{"authors":[{"text":"Lagadic, Laurent","contributorId":200679,"corporation":false,"usgs":false,"family":"Lagadic","given":"Laurent","email":"","affiliations":[],"preferred":false,"id":731400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katsiadaki, Ioanna","contributorId":200653,"corporation":false,"usgs":false,"family":"Katsiadaki","given":"Ioanna","email":"","affiliations":[],"preferred":false,"id":731401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biever, Ronald C.","contributorId":200660,"corporation":false,"usgs":false,"family":"Biever","given":"Ronald","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":731402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guiney, Patrick","contributorId":193148,"corporation":false,"usgs":false,"family":"Guiney","given":"Patrick","affiliations":[],"preferred":false,"id":731403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":200983,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":731399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwarz, Tamar","contributorId":200733,"corporation":false,"usgs":false,"family":"Schwarz","given":"Tamar","email":"","affiliations":[],"preferred":false,"id":731404,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meador, James P.","contributorId":174075,"corporation":false,"usgs":false,"family":"Meador","given":"James P.","affiliations":[],"preferred":false,"id":731405,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196115,"text":"70196115 - 2018 - Annual variation in polychlorinated biphenyl (PCB) exposure in tree swallow (Tachycineta bicolor) eggs and nestlings at Great Lakes Restoration Initiative (GLRI) study sites","interactions":[],"lastModifiedDate":"2022-04-04T20:43:36.748088","indexId":"70196115","displayToPublicDate":"2018-03-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Annual variation in polychlorinated biphenyl (PCB) exposure in tree swallow (Tachycineta bicolor) eggs and nestlings at Great Lakes Restoration Initiative (GLRI) study sites","title":"Annual variation in polychlorinated biphenyl (PCB) exposure in tree swallow (Tachycineta bicolor) eggs and nestlings at Great Lakes Restoration Initiative (GLRI) study sites","docAbstract":"Tree swallow (Tachycineta bicolor) eggs and nestlings were collected from 16 sites across the Great Lakes to quantify normal annual variation in total polychlorinated biphenyl (PCB) exposure and to validate the sample size choice in earlier work. A sample size of five eggs or five nestlings per site was adequate to quantify exposure to PCBs in tree swallows given the current exposure levels and variation. There was no difference in PCB exposure in two randomly selected sets of five eggs collected in the same year, but analyzed in different years. Additionally, there was only modest annual variation in exposure, with between 69% (nestlings) and 73% (eggs) of sites having no differences between years. There was a tendency, both statistically and qualitatively, for there to be less exposure in the second year compared to the first year.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-018-6617-3","usgsCitation":"Custer, C.M., Custer, T.W., Dummer, P.M., Goldberg, D., and Franson, J.C., 2018, Annual variation in polychlorinated biphenyl (PCB) exposure in tree swallow (Tachycineta bicolor) eggs and nestlings at Great Lakes Restoration Initiative (GLRI) study sites: Environmental Monitoring and Assessment, v. 190, p. 1-7, https://doi.org/10.1007/s10661-018-6617-3.","productDescription":"Article 227; 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-090193","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":352684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.21923828124999,\n 41.244772343082076\n ],\n [\n -78.7060546875,\n 41.244772343082076\n ],\n [\n -78.7060546875,\n 46.86019101567027\n ],\n [\n -92.21923828124999,\n 46.86019101567027\n ],\n [\n -92.21923828124999,\n 41.244772343082076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"190","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-17","publicationStatus":"PW","scienceBaseUri":"5afee6fae4b0da30c1bfc004","contributors":{"authors":[{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":731421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Custer, Thomas W. 0000-0003-3170-6519 tcuster@usgs.gov","orcid":"https://orcid.org/0000-0003-3170-6519","contributorId":2835,"corporation":false,"usgs":true,"family":"Custer","given":"Thomas","email":"tcuster@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":731422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dummer, Paul M. 0000-0002-2055-9480 pdummer@usgs.gov","orcid":"https://orcid.org/0000-0002-2055-9480","contributorId":3015,"corporation":false,"usgs":true,"family":"Dummer","given":"Paul","email":"pdummer@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":731423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldberg, Diana R. 0000-0001-8540-8512","orcid":"https://orcid.org/0000-0001-8540-8512","contributorId":82252,"corporation":false,"usgs":true,"family":"Goldberg","given":"Diana R.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":731424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Franson, J. Christian 0000-0002-0251-4238 jfranson@usgs.gov","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":177499,"corporation":false,"usgs":true,"family":"Franson","given":"J.","email":"jfranson@usgs.gov","middleInitial":"Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":731425,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196125,"text":"70196125 - 2018 - Developing Foram-AMBI for biomonitoring in the Mediterranean: Species assignments to ecological categories","interactions":[],"lastModifiedDate":"2018-03-21T09:34:04","indexId":"70196125","displayToPublicDate":"2018-03-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2673,"text":"Marine Micropaleontology","active":true,"publicationSubtype":{"id":10}},"title":"Developing Foram-AMBI for biomonitoring in the Mediterranean: Species assignments to ecological categories","docAbstract":"Most environmental bio-monitoring methods using the species composition of marine faunas define the Ecological Quality Status of soft bottom ecosystems based on the relative proportions of species assigned to a limited number of ecological categories. In this study we analyse the distribution patterns of benthic foraminifera in the Mediterranean as a function of organic carbon gradients on the basis of 15 publications and assign the individual species to five ecological categories. Our categories (of sensitive, indifferent and 3rd, 2nd and 1st order opportunists) are very similar to the ecological categories commonly used for macrofauna, but show some minor differences. In the 15 analysed publications, we considered the numerical data of 493 taxa, of which 199 could be assigned. In all 79 taxa were classified as sensitive, 60 as indifferent, 46 as 3rd order, 12 as 2nd order and 2 as 1st order opportunists. The remaining 294 taxa are all accessory, and will only marginally contribute to biotic indices based on relative species proportions. In this paper we wanted also to explain the methodology we used for these species assignments, paying particular attention to all complications and problems encountered. We think that the species list proposed here will constitute a highly useful tool for foraminiferal bio-monitoring of soft bottoms in the Mediterranean Sea, which can be used in different ecological indices (Foram-AMBI and similar methods). With additional information becoming available in the next few years, it will be possible to expand the list, and, if necessary, to apply some minor corrections. As a next step, we intend to test this species list using several biotic indices, in a number of independent data sets, as soon as these will become available.
Assessment of the “Bird or Animal Deformities or Reproductive Problems” Beneficial Use Impairment (BUI) can be accomplished by (1) comparing tissue concentrations to established background and Lowest Observable Effect Level (LOEL) for reproductive effects, or (2) directly measuring reproductive success at Areas of Concern (AOCs) and statistically comparing those rates to minimally impacted reference locations (non-AOCs). Results from recent tree swallow (Tachycineta bicolor) publications were used to evaluate this BUI based on both approaches. For both endpoints, a 95-percent confidence interval (CI) was used to test for significant differences. Additional information on BUIs, AOCs, and the program in general can be found in the Great Lakes Water Quality Agreement (2012).
For the first metric, there are good background and reproductive effect threshold LOELs for tree swallow egg concentrations for polychlorinated biphenyls (PCBs), dioxins and furans (PCDD/Fs), and mercury, as well as, for some other organic and inorganic contaminants. For the second assessment, comparisons were made between AOC and non-AOC sites for reproductive success, which was measured as the daily probability of egg failure and the percentage of eggs laid that hatched. Multistate modeling was used to assess whether there was an association between the daily probability of egg failure and a suite of contaminants, including PCBs, but also whether there was an association with ecological variables, such as female age and date within season. Both of these ecological variables are known to affect hatching success in birds. The objective of this report is to synthesize the previously published information to assist in the assessment of the “Bird or Animal Deformities or Reproductive Problems” BUI at 16 sites within the 5 Wisconsin AOCs (table 1). The logic behind this interpretation is applicable to other AOCs as well.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181032","usgsCitation":"Custer, C.M., Custer, T.W., and Dummer, P.M., 2018, Synthesis of tree swallow (Tachycineta bicolor) data for Beneficial Use Impairment (BUI) assessment at Wisconsin Areas of Concern: U.S. Geological Survey Open-File Report 2018–1032, 8 p., https://doi.org/10.3133/ofr20181032.","productDescription":"iv, 8 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092682","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":352653,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1032/ofr20181032.pdf","text":"Report","size":"111 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1032"},{"id":352652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1032/coverthb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconsin","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Cross, WI 54603
The daily and annual loads of nitrate plus nitrite and total nitrogen for the Connecticut River at Middle Haddam, Connecticut, were determined for water years 2009 to 2014. The analysis was done with a combination of methods, which included a predefined rating curve method for nitrate plus nitrite and total nitrogen for water years 2009 to 2011 and a custom rating curve method that included sensor measurements of nitrate plus nitrite nitrogen concentration and turbidity along with mean daily flow to determine total nitrogen loads for water years 2011 to 2014. Instantaneous concentrations of total nitrogen were estimated through the use of a regression model based on sensor measurements at 15-minute intervals of nitrate plus nitrite nitrogen and turbidity for water years 2011 to 2014.
Annual total nitrogen loads at the Connecticut River at Middle Haddam ranged from 12,900 to 19,200 metric tons, of which about 42 to 49 percent was in the form of nitrate plus nitrite. The mean 95-percent prediction intervals on daily total nitrogen load estimates were smaller from the custom model, which used sensor data, than those calculated by the predefined model.
Annual total nitrogen load estimates at the Connecticut River at Middle Haddam were compared with the upstream load estimates at the Connecticut River at Thompsonville, Conn. Annual gains in total nitrogen loads between the two stations ranged from 3,430 to 6,660 metric tons. These increases between the two stations were attributed to the effects of increased urbanization and to combined annual discharges of 1,540 to 2,090 metric tons of nitrogen from 24 wastewater treatment facilities in the drainage area between the two stations. The contribution of total nitrogen from wastewater discharge between the two stations had declined substantially before the beginning of this study and accounted for from 31 to 52 percent of the gain in nitrogen load between the Thompsonville and Middle Haddam sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185006","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Mullaney, J.R., Martin, J.W., and Morrison, J., 2018, Nitrogen concentrations and loads for the Connecticut River at Middle Haddam, Connecticut, computed with the use of autosampling and continuous measurements of water quality for water years 2009 to 2014: U.S. Geological Survey Scientific Investigations Report 2018–5006, 22 p., https://doi.org/10.3133/sir20185006.","productDescription":"Report: vii, 22 p.; Data release","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091217","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":352399,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5006/sir20185006.pdf","text":"Report","size":"4.79 MB ","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5006"},{"id":352631,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VQ31WT","text":"USGS data release","description":"USGS data release","linkHelpText":"Nitrogen Concentrations and Loads for the Connecticut River at Middle Haddam, Connecticut, Computed With the Use of Autosampling and Continuous Measurements of Water Quality for Water Years 2009 to 2014"},{"id":352409,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5006/coverthb.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Connecticut River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.94097900390625,\n 41.34691753986531\n ],\n [\n -72.18154907226562,\n 41.34691753986531\n ],\n [\n -72.18154907226562,\n 42.04011410708205\n ],\n [\n -72.94097900390625,\n 42.04011410708205\n ],\n [\n -72.94097900390625,\n 41.34691753986531\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
101 Pitkin Street
East Hartford, CT 06108
The number of stranding response facilities for marine mammals in the United States has increased over the past two decades, resulting in thousands of rehabilitated marine mammals released back into the wild (Geraci and Lounsbury 2005; Moore et al. 2007; Johnson and Mayer 2015; Simeone et al. 2015). All rehabilitated marine mammals released in the United States must be tagged or marked (50 CFR 216.27) and post-release monitoring is recommended, if not required, for some taxonomic groups. This depends on their release category as determined by a veterinarian in concordance with guidelines established by the National Marine Fisheries Service (NMFS) and the US Fish and Wildlife Service (USFWS; Whaley and Borkowski 2009). Monitoring the fate of released, rehabilitated marine mammals is not only necessary for the validation and refinement of veterinary procedures and treatments, but allows for the recovery of individuals that are unable to adapt to the wild (Whaley and Borkowski 2009). For cases in which rehabilitation is used to enhance small or endangered populations, monitoring the ability of individuals to forage, survive, and ultimately reproduce following release is essential for assessing the conservation value of a given program’s efforts. Post-release monitoring has also been useful in some cases for elucidating poorly understood ranges and habitat use of wild populations (Moore et al. 2007).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"CRC handbook of marine mammal medicine, 3rd edition","language":"English","publisher":"CRC Press : Taylor & Francis Group","usgsCitation":"Lander, M.E., Westgate, A.J., Balmer, B.C., Reid, J.P., Murray, M.J., and Laidre, K.L., 2018, Tagging and tracking, chap. of CRC handbook of marine mammal medicine, 3rd edition, p. 767-798.","productDescription":"32 p.","startPage":"767","endPage":"798","ipdsId":"IP-080536","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":356956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":356309,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/books/9781498796880"}],"edition":"3rd","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2eae4b0702d0e84300a","contributors":{"authors":[{"text":"Lander, Michelle E.","contributorId":206850,"corporation":false,"usgs":false,"family":"Lander","given":"Michelle","email":"","middleInitial":"E.","affiliations":[{"id":37416,"text":"Marine Mammal Laboratory, Alaska Fisheries Science Center, NOAA, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":741940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westgate, Andrew J.","contributorId":206851,"corporation":false,"usgs":false,"family":"Westgate","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":37417,"text":"Dept. of Biology and Marine Biology, University of North Carolina Wilmington, Wilmington, NC","active":true,"usgs":false}],"preferred":false,"id":741941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balmer, Brian C.","contributorId":206853,"corporation":false,"usgs":false,"family":"Balmer","given":"Brian","email":"","middleInitial":"C.","affiliations":[{"id":27926,"text":"NOAA, National Centers for Coastal Ocean Science","active":true,"usgs":false}],"preferred":false,"id":741943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reid, James P. 0000-0002-8497-1132 jreid@usgs.gov","orcid":"https://orcid.org/0000-0002-8497-1132","contributorId":3460,"corporation":false,"usgs":true,"family":"Reid","given":"James","email":"jreid@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":741939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, Michael J.","contributorId":206852,"corporation":false,"usgs":false,"family":"Murray","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":37418,"text":"Monterey Bay Aquarium, Monterey, CA","active":true,"usgs":false}],"preferred":false,"id":741942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Laidre, Kristen L.","contributorId":206854,"corporation":false,"usgs":false,"family":"Laidre","given":"Kristen","email":"","middleInitial":"L.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":741944,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196107,"text":"70196107 - 2018 - Population estimates of the Endangered Hawaiʻi ʻĀkepa (Loxops coccineus) in different habitats on windward Mauna Loa","interactions":[],"lastModifiedDate":"2018-03-20T08:59:44","indexId":"70196107","displayToPublicDate":"2018-03-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Population estimates of the Endangered Hawaiʻi ʻĀkepa (Loxops coccineus) in different habitats on windward Mauna Loa","title":"Population estimates of the Endangered Hawaiʻi ʻĀkepa (Loxops coccineus) in different habitats on windward Mauna Loa","docAbstract":"Endangered Hawai‘i ʻĀkepas (Loxops coccineus) are endemic to Hawai‘i island, where they occur in five spatially distinct populations. Data concerning the status and population trends of these unique Hawaiian honeycreepers are crucial for assessing the effectiveness of recovery and management actions. In 2016, we used point‐transect distance sampling to estimate the abundance of Hawai‘i ʻĀkepas in portions of Hawai‘i Volcanoes National Park (HAVO) and the Kaʻū Forest Reserve (KFR) on Mauna Loa volcano. We then compiled the survey data from four other populations to provide a global population estimate. In our HAVO and KFR study area, we mapped habitat classes to determine the population densities in each habitat. Densities were highest (1.03 birds/ha) in open‐canopy montane ʻōhiʻa (Metrosideros polymorpha) woodland. In contrast, densities of the largest ʻĀkepa population on Mauna Kea volcano were highest in closed‐canopy ʻōhiʻa and koa (Acacia koa) forest where the species is dependent on nest cavities in tall (> 15 m), large (> 50‐cm diameter at breast height) trees. We surveyed potential nesting habitat in HAVO and KFR and found only one cavity in the short‐stature montane ʻōhiʻa woodland and five cavities in the tall‐stature forest. Differences in densities between the Mauna Kea and Mauna Loa populations suggest that Hawai‘i ʻĀkepas may exhibit different foraging and nesting behaviors in the two habitats. The estimated overall population density in the HAVO and KFR study area was 0.52 birds/ha, which equates to 3663 (95% CI 1725–6961) birds in their 11,377‐ha population range. We calculated a global population of 16,428 (95% CI 10,065–25,198) birds, which is similar to an estimate of 13,892 (95% CI 10,315–17,469) birds made in 1986. Our results suggest that populations are stable to increasing in the two largest populations, but the three other populations are smaller (range = 77–1443 birds) and trends for those populations are unknown.
","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12243","usgsCitation":"Judge, S.W., Camp, R.J., Hart, P.J., and Kichman, S.T., 2018, Population estimates of the Endangered Hawaiʻi ʻĀkepa (Loxops coccineus) in different habitats on windward Mauna Loa: Journal of Field Ornithology, v. 89, no. 1, p. 11-21, https://doi.org/10.1111/jofo.12243.","productDescription":"11 p.","startPage":"11","endPage":"21","ipdsId":"IP-094596","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":437983,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7S181SV","text":"USGS data release","linkHelpText":"HAVO Montane Ohia Diameter and Cavity Data 2017"},{"id":352647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Mauna Loa","volume":"89","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5afee6fbe4b0da30c1bfc00e","contributors":{"authors":[{"text":"Judge, Seth W.","contributorId":8718,"corporation":false,"usgs":true,"family":"Judge","given":"Seth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":731375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":116175,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":false,"id":731376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Patrick J.","contributorId":147728,"corporation":false,"usgs":false,"family":"Hart","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":731377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kichman, Scott T.","contributorId":203396,"corporation":false,"usgs":false,"family":"Kichman","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":36609,"text":"NPS, Pacific Island Inventory and Monitoring Program","active":true,"usgs":false}],"preferred":false,"id":731378,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196104,"text":"70196104 - 2018 - Spatial and temporal variation in sources of atmospheric nitrogen deposition in the Rocky Mountains using nitrogen isotopes","interactions":[],"lastModifiedDate":"2018-03-20T09:03:28","indexId":"70196104","displayToPublicDate":"2018-03-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":924,"text":"Atmospheric Environment","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variation in sources of atmospheric nitrogen deposition in the Rocky Mountains using nitrogen isotopes","docAbstract":"Variation in source areas and source types of atmospheric nitrogen (N) deposition to high-elevation ecosystems in the Rocky Mountains were evaluated using spatially and temporally distributed N isotope data from atmospheric deposition networks for 1995-2016. This unique dataset links N in wet deposition and snowpack to mobile and stationary emissions sources, and enhances understanding of the impacts of anthropogenic activities and environmental policies that mitigate effects of accelerated N cycling across the Rocky Mountain region. δ15N−NO3− at 50 U.S. Geological Survey Rocky Mountain Snowpack (Snowpack) sites ranged from −3.3‰ to +6.5‰, with a mean value of +1.4‰. At 15 National Atmospheric Deposition Program (NADP)/National Trends Network wet deposition (NADP Wetfall) sites, summer δ15N−NO3− is significantly lower ranging from −7.6‰ to −1.3‰ while winter δ15N−NO3− ranges from −2.6‰ to +5.5‰, with a mean value of +0.7‰ during the cool season. The strong seasonal difference in NADP Wetfall δ15N−NO3− is due in part to variation in the proportion of N originating from source regions at different times of the year due to seasonal changes in weather patterns. Snowpack NO3− and δ15N−NO3− are significantly related to NADP Wetfall (fall and winter) suggesting that bulk snowpack samples provide a reliable estimate at high elevations. Spatial trends show higher NO3−concentrations and δ15N−NO3− in the Southern Rocky Mountains located near larger anthropogenic N emission sources compared to the Northern Rocky Mountains. NADP Wetfall δ15N−NH4+ ranged from −10‰ to 0‰, with no observed spatial pattern. However, the lowest δ15N−NH4+(−9‰), and the highest NH4+ concentration (35 μeq/L) were observed at a Utah site dominated by local agricultural activities, whereas the higher δ15N−NH4+observed in Colorado and Wyoming are likely due to mixed sources, including fossil fuel combustion and agricultural sources. These findings show spatial and seasonal variation in N isotope data that reflect differences in sources of anthropogenic N deposition to high-elevation ecosystems and have important implications for environmental policy across the Rocky Mountain region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2017.12.023","usgsCitation":"Nanus, L., Campbell, D.H., Lehmann, C.M., and Mast, M.A., 2018, Spatial and temporal variation in sources of atmospheric nitrogen deposition in the Rocky Mountains using nitrogen isotopes: Atmospheric Environment, v. 176, p. 110-119, https://doi.org/10.1016/j.atmosenv.2017.12.023.","productDescription":"10 p.","startPage":"110","endPage":"119","ipdsId":"IP-088572","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":468904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atmosenv.2017.12.023","text":"Publisher Index Page"},{"id":352648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Rocky Mountains","volume":"176","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6fbe4b0da30c1bfc010","contributors":{"authors":[{"text":"Nanus, Leora","contributorId":27930,"corporation":false,"usgs":true,"family":"Nanus","given":"Leora","email":"","affiliations":[],"preferred":false,"id":731365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Donald H. dhcampbe@usgs.gov","contributorId":1670,"corporation":false,"usgs":true,"family":"Campbell","given":"Donald","email":"dhcampbe@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":731366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lehmann, Christopher M.B.","contributorId":84859,"corporation":false,"usgs":true,"family":"Lehmann","given":"Christopher","email":"","middleInitial":"M.B.","affiliations":[],"preferred":false,"id":731367,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731364,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196095,"text":"70196095 - 2018 - Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes","interactions":[],"lastModifiedDate":"2018-03-20T09:08:21","indexId":"70196095","displayToPublicDate":"2018-03-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"title":"Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes","docAbstract":"Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines.
","language":"English","publisher":"MDPI","doi":"10.3390/s18030880","usgsCitation":"Gallant, A.L., Sadinski, W.J., Brown, J.F., Senay, G., and Roth, M.F., 2018, Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes: Sensors, v. 18, no. 3, p. 1-38, https://doi.org/10.3390/s18030880.","productDescription":"Article 880; 38 p.","startPage":"1","endPage":"38","ipdsId":"IP-094477","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468903,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s18030880","text":"Publisher Index Page"},{"id":437982,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QF8S3H","text":"USGS data release","linkHelpText":"Data files supporting the paper titled "Complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate lessons from temperate wetland-upland landscapes""},{"id":352650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-16","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc012","contributors":{"authors":[{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":731314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sadinski, Walter J. wsadinski@usgs.gov","contributorId":3287,"corporation":false,"usgs":true,"family":"Sadinski","given":"Walter","email":"wsadinski@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":731315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":3241,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":731316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":152206,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","email":"senay@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":731317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roth, Mark F. 0000-0001-5095-1865 mroth@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-1865","contributorId":3286,"corporation":false,"usgs":true,"family":"Roth","given":"Mark","email":"mroth@usgs.gov","middleInitial":"F.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":731318,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191483,"text":"sir20175088 - 2018 - Hydrologic assessment of the Edwin B. Forsythe National Wildlife Refuge","interactions":[],"lastModifiedDate":"2018-03-19T16:50:38","indexId":"sir20175088","displayToPublicDate":"2018-03-19T12:15:00","publicationYear":"2018","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":"2017-5088","title":"Hydrologic assessment of the Edwin B. Forsythe National Wildlife Refuge","docAbstract":"The Edwin B. Forsythe National Wildlife Refuge (hereafter Forsythe refuge or the refuge) is situated along the central New Jersey coast and provides a mixture of freshwater and saltwater habitats for numerous bird, wildlife, and plant species. Little data and information were previously available regarding the freshwater dynamics that support the refuge’s ecosystems. In cooperation with the U.S. Fish and Wildlife Service, the U.S. Geological Survey conducted an assessment of the hydrologic resources and processes in the refuge and surrounding areas to provide baseline information for evaluating restoration projects and future changes in the hydrologic system associated with climate change and other anthropogenic stressors.
During spring 2015, water levels were measured at groundwater and surface-water sites in and near the Forsythe refuge. These water-level measurements, along with surface-water elevations obtained from digital elevation models, were used to construct water-table-elevation and depth-to-water maps of the refuge and surrounding areas. Water-table elevations in the refuge ranged from sea level to approximately 65 feet above sea level; in most of the refuge, the water-table elevation was within 3 feet of sea level. The water-table-elevation map indicates that the direction of shallow groundwater flow at the regional scale is generally from west to east (much of it from the northwest to the southeast), and groundwater moves downgradient from the uplands toward major groundwater discharge areas consisting of coastal streams and wetlands. The depth to water is estimated to be less than 2 feet for approximately 86 percent of the refuge, which coincides closely with the percentage of wetland area in the refuge. Depth to water in excess of 20 feet below land surface is limited to higher elevation areas of the refuge.
Streamflow data collected at continuous-record streamgages and partial-record stations within the Mullica-Toms Basin were summarized. Hydrograph separation of streamflow data for eight streamgages (2004–13) reveals that base flow accounts for 68–94 percent of streamflow in basins upstream from the refuge. The high base-flow inputs underscore the importance of groundwater as a source of freshwater that supports both the streams that flow into the refuge and the hydroecology of the contributing basins. Mean annual flow typically ranged from 1.7 to 2.1 cubic feet per second per square mile at the streamgages (2004–13) and between 1.2 and 2.3 cubic feet per second per square mile at the partial-record stations (1965–2015) but was notably greater or lower than these ranges at several stations.
Mean annual water budgets were estimated for multiple regions of the refuge for 2004–13 using data compiled from nearby meteorological stations and groundwater flows derived from previously calibrated groundwater-flow models. Precipitation, groundwater recharge, and evapotranspiration were estimated from available data; direct runoff was calculated as the residual component of the water balance. Groundwater recharge rates were greatest in the upland-dominated areas of the refuge with estimates of 14.4 to 18.9 inches per year, which are equivalent to 30 to 40 percent of precipitation. Groundwater recharge rates were nearly zero in the central coastal areas because these areas are major groundwater discharge zones, the water table is near land surface, the subsurface is close to saturation and cannot accept much recharge, and much of the area is underlain by thick marsh deposits likely with low permeability. Estimates of evapotranspiration varied from about 26 inches per year in the upland-dominated areas to more than 35 inches per year in the coastal wetlands, equivalent to 55–79 percent of mean annual precipitation, indicating that it is a major component of the hydrodynamics of the Forsythe refuge.
On the basis of output from previously calibrated groundwater-flow models, nearly all of the groundwater exiting the surficial aquifer system in the central coastal areas of the refuge is discharged to wetlands, which highlights the importance of groundwater discharge in supporting the ecosystems of the Forsythe refuge. In the central coastal areas, horizontal flow contributes more than 90 percent of the groundwater flow to the surficial system, indicating that the upbasin areas are a substantial source of water that ultimately discharges to streams and wetlands in the refuge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175088","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Wieben, C.M., and Chepiga, M.M., 2018, Hydrologic assessment of the Edwin B. Forsythe National Wildlife Refuge, New Jersey: U.S. Geological Survey Scientific Investigations Report 2017–5088, 38 p., https://doi.org/10.3133/sir20175088.\n","productDescription":"Report: viii, 38 p.; 2 Plates: 24.0 x 36.0 inches; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079840","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":352411,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5088/sir20175088.pdf","text":"Report","size":"25.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5088"},{"id":352410,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5088/coverthb.jpg"},{"id":352412,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78G8JMN","text":"USGS data release","description":"USGS data release","linkHelpText":"Water-table elevation contours and depth-to-water grid for the Edwin B. Forsythe National Wildlife Refuge, New Jersey, and vicinity, spring 2015"},{"id":352535,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5088/sir20175088_plate02.pdf","text":"Plate 2","size":"4.15 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Water-Table Elevation in and near the Southern Part of the Edwin B. Forsythe National Wildlife Refuge, New Jersey, Spring 2015"},{"id":352426,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20175135","text":"Scientific Investigations Report 2017–5135","linkHelpText":"- Hydrogeology of, Simulation of Groundwater Flow in, and Potential Effects of Sea-Level Rise on the Kirkwood-Cohansey Aquifer System in the Vicinity of Edwin B. Forsythe National Wildlife Refuge, New Jersey"},{"id":352534,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5088/sir20175088_plate01.pdf","text":"Plate 1 ","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Water-Table Elevation in and near the Northern Part of the Edwin B. Forsythe National Wildlife Refuge, New Jersey, Spring 2015"}],"country":"United States","state":"New Jersey","otherGeospatial":"Edwin B. Forsythe 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 -74,\n 39.4167\n ],\n [\n -74,\n 40.07807142745009\n ],\n [\n -74.5,\n 40.07807142745009\n ],\n [\n -74.5,\n 39.4167\n ],\n [\n -74,\n 39.4167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The Edwin B. Forsythe National Wildlife Refuge encompasses more than 47,000 acres of New Jersey coastal habitats, including salt marshes, freshwater wetlands, tidal wetlands, barrier beaches, woodlands, and swamps. The refuge is along the Atlantic Flyway and provides breeding habitat for fish, migratory birds, and other wildlife species. The refuge area may be threatened by global climate change, including sea-level rise (SLR).
The Kirkwood-Cohansey aquifer system underlies the Edwin B. Forsythe National Wildlife Refuge. Groundwater is an important source of freshwater flow into the refuge, but information about the interaction of surface water and groundwater in the refuge area and the potential effects of SLR on the underlying aquifer system is limited. The U.S. Geological Survey (USGS), in cooperation with the U.S. Fish and Wildlife Service (USFWS), conducted a hydrologic assessment of the refuge in New Jersey and developed a groundwater flow model to improve understanding of the geohydrology of the refuge area and to serve as a tool to evaluate changes in groundwater-level altitudes that may result from a rise in sea level.
Groundwater flow simulations completed for this study include a calibrated baseline simulation that represents 2005–15 hydraulic conditions and three SLR scenarios―20, 40, and 60 centimeters (cm) (0.656, 1.312, and 1.968 feet, respectively). Results of the three SLR simulations indicate that the water table in the unconfined Kirkwood-Cohansey aquifer system in the refuge area will rise, resulting in increased discharge of fresh groundwater to freshwater wetlands and streams. As sea level rises, simulated groundwater discharge to the salt marsh, bay, and ocean is projected to decrease. Flow from the salt marsh, bay, and ocean to the overlying surface water is projected to increase as sea level rises.
The simulated movement of the freshwater-seawater interface as sea level rises depends on the hydraulic-head gradient. In the center of the Forsythe model area, topographic relief is 23 feet (ft) and the hydraulic-head gradient is 0.0033. In the center of the Forsythe model area, the simulated interface moved inland about 600 ft and downward about 15 ft from the baseline simulation to scenario 3 as a result of a SLR of 60 cm. In the southern part of the Forsythe model area, the topography is flatter (relief of 8 ft) and the hydraulic-head gradient is smaller (0.001). In the southern part of the Forsythe model study area, the simulated interface in this area is projected to move inland about 200 ft from the baseline simulation to scenario 3 and does not move downward.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175135","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Fiore, A.R., Voronin, L.M., and Wieben, C.M., 2018, Hydrogeology of, simulation of groundwater flow in, and potential effects of sea-level rise on the Kirkwood-Cohansey aquifer system in the vicinity of Edwin B. Forsythe National Wildlife Refuge, New Jersey: U.S. Geological Survey Scientific Investigations Report 2017-5135, 59 p., https://doi.org/10.3133/sir20175135.","productDescription":"Report: vii, 59 p.; Data releases","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074587","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":352424,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76W98JB","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 model used to evaluate the potential effects of sea-level rise on the Kirkwood-Cohansey aquifer system in the vicinity of Edwin B. Forsythe National Wildlife Refuge, New Jersey"},{"id":352423,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JH3KBD","text":"USGS data release","description":"USGS data release","linkHelpText":"Raw ground-penetrating radar data, Edwin B. Forsythe National Wildlife Refuge, New Jersey, 2014–15"},{"id":352422,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5135/sir20175135.pdf","text":"Report","size":"16.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5135"},{"id":352421,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5135/coverthb.jpg"},{"id":352425,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20175088","text":"Scientific Investigations Report 2017–5088","linkHelpText":"- Hydrologic Assessment of the Edwin B. Forsythe National Wildlife Refuge, New Jersey"}],"country":"United States","state":"New Jersey","otherGeospatial":"Edwin B. Forsythe 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 -74.67,\n 39.33\n ],\n [\n -73.67,\n 39.33\n ],\n [\n -73.67,\n 40.09067983779908\n ],\n [\n -74.67,\n 40.09067983779908\n ],\n [\n -74.67,\n 39.33\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Late-winter lake ice regimes are controlled by water depth relative to maximum ice thickness (MIT). When MIT exceeds maximum water depth, lakes freeze to the bottom with bedfast ice (BI) and when MIT is less than maximum water depth lakes have floating ice (FI). Both airborne radar and space-borne synthetic aperture radar (SAR) imagery (Ku-, X-, C-, and L-band) have been used previously to determine whether lakes have a BI or FI regime in a given year, across a number of years, or across large regions. In this study, we use a combination of ERS-1/2, RADARSAT-2, Envisat, and Sentinel-1 SAR imagery for seven lake-rich regions in Arctic Alaska to analyze lake ice regime extents and dynamics over a 25-year period (1992–2016). Our interactive threshold classification method determines a unique statistic-based intensity threshold for each SAR scene, allowing for the comparison of classification results from C-band SAR data acquired with different polarizations and incidence angles. Additionally, our novel method accommodates declining signal strength in aging extended-mission satellite SAR instruments. Comparison of SAR ice regime classifications with extensive field measurements from six years yielded a 93% accuracy. Significant declines in BI regimes were only observed in the Fish Creek area with 3% of lakes exhibiting transitional ice regimes—lakes that switch from BI to FI during this 25-year period. This analysis suggests that the potential conversion from BI to FI regimes is primarily a function of lake depth distributions in addition to regional differences in climate variability. Remote sensing of lake ice regimes with C-band SAR is a useful tool to monitor the associated thermal impacts on permafrost, since lake ice regimes can be used as a proxy for of sub-lake permafrost thaw, considered by the Global Climate Observing System as an Essential Climate Variable (ECV). Continued winter warming and variable snow conditions in the Arctic are expected and our long-term analysis provides a valuable baseline for predicting where potential future lake ice regimes shifts will be most pronounced.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2018.02.022","usgsCitation":"Engram, M., Arp, C.D., Jones, B.M., Ajadi, O.A., and Meyer, F.J., 2018, Analyzing floating and bedfast lake ice regimes across Arctic Alaska using 25 years of space-borne SAR imagery: Remote Sensing of Environment, v. 209, p. 660-676, https://doi.org/10.1016/j.rse.2018.02.022.","productDescription":"17 p.","startPage":"660","endPage":"676","ipdsId":"IP-090354","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":468905,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2018.02.022","text":"Publisher Index Page"},{"id":408647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -159.5263144061035,\n 71.43267111072981\n ],\n [\n -159.5263144061035,\n 68.42639425141334\n ],\n [\n -146.22562492863324,\n 68.42639425141334\n ],\n [\n -146.22562492863324,\n 71.43267111072981\n ],\n [\n -159.5263144061035,\n 71.43267111072981\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -163.58954484767287,\n 66.64438234906729\n ],\n [\n -166.61500668033133,\n 66.64438234906729\n ],\n [\n -166.61500668033133,\n 65.88496852258822\n ],\n [\n -163.58954484767287,\n 65.88496852258822\n ],\n [\n -163.58954484767287,\n 66.64438234906729\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"209","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Engram, Melanie","contributorId":191062,"corporation":false,"usgs":false,"family":"Engram","given":"Melanie","email":"","affiliations":[],"preferred":false,"id":855648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":855649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":855650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ajadi, Olaniyi A","contributorId":298461,"corporation":false,"usgs":false,"family":"Ajadi","given":"Olaniyi","email":"","middleInitial":"A","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":855651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyer, Franz J","contributorId":298463,"corporation":false,"usgs":false,"family":"Meyer","given":"Franz","email":"","middleInitial":"J","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":855652,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70219033,"text":"70219033 - 2018 - Development of Raman spectroscopy as a thermal maturity proxy in unconventional resource assessment","interactions":[],"lastModifiedDate":"2021-03-19T12:45:16.582845","indexId":"70219033","displayToPublicDate":"2018-03-19T07:43:56","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Development of Raman spectroscopy as a thermal maturity proxy in unconventional resource assessment","docAbstract":"The objective of this study was to correlate shale hydrous pyrolysis with thermal maturity measurements based on solid bitumen reflectance (BRo) at the U.S. Geological Survey (USGS) and Raman microscopy (RM) at WellDog. In semi-blind Phase I, BRo values of the initial set of 8 samples were withheld prior to RM analysis. As reported previously, a strong correlation was observed between BRo and Raman parameters. For Phase-II, BRo values for the second set of 8 samples were shared before RM. Observations from Phase-II are reported here as well as the ability of RM to correctly order the semi-blind Phase I samples.\n\nImmature shale samples from the Bakken (Phase-I) and Duvernay (Phase-II) formations were subjected to hydrous pyrolysis for 72 hours at temperatures from 280°C to 360°C. Rock residues from both series were mounted and polished (ASTM D2797) for analysis of BRo (ASTM D7708) and confocal laser-scanning Raman microscopy. For RM, multiple hyperspectral maps were collected from each sample, resulting in tens of thousands of spectra per sample. Map areas were ~5,000 μm2, with a spectrum collected from every square micrometer. The organic carbon G- (Graphitic-) and D- (Disordered) bands in each Raman spectrum were fit algorithmically to a multi-peak model, yielding a number of diagnostic parameters that correlate with changes occurring in samples as a result of thermal maturation and pyrolysis.\n\nParameters extracted from analysis of Raman spectra were plotted against the previously determined BRo values to determine which Raman parameters best correlate with thermal maturity. Plotting two of the sample-averaged anonymized spectral parameters versus BRo in the Bakken series indicated an exponential trend with strong correlations (R2>0.8) as reported at URTeC in 2017 (MS-2671253). Similar strong relationships occurred in the Duvernay samples with respect to increasing maturity when using Partial Least-Squares analysis.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Unconventional Resources Technology Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"URTeC","doi":"10.15530/urtec-2018-2903536","usgsCitation":"Myers, G.A., Kehoe, K., and Hackley, P.C., 2018, Development of Raman spectroscopy as a thermal maturity proxy in unconventional resource assessment, in Proceedings of the Unconventional Resources Technology Conference, 12 p., https://doi.org/10.15530/urtec-2018-2903536.","productDescription":"12 p.","ipdsId":"IP-098028","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":384503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Myers, Grant A.","contributorId":255533,"corporation":false,"usgs":false,"family":"Myers","given":"Grant","email":"","middleInitial":"A.","affiliations":[{"id":51579,"text":"WellDog Gas Sensing Technology Corp.","active":true,"usgs":false}],"preferred":false,"id":812507,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kehoe, Kelsey","contributorId":255534,"corporation":false,"usgs":false,"family":"Kehoe","given":"Kelsey","email":"","affiliations":[{"id":51579,"text":"WellDog Gas Sensing Technology Corp.","active":true,"usgs":false}],"preferred":false,"id":812508,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812509,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196092,"text":"70196092 - 2018 - Spatial organization of the gastrointestinal microbiota in urban Canada geese","interactions":[],"lastModifiedDate":"2018-03-19T10:28:54","indexId":"70196092","displayToPublicDate":"2018-03-19T00:00:00","publicationYear":"2018","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":"Spatial organization of the gastrointestinal microbiota in urban Canada geese","docAbstract":"Recent reviews identified the reliance on fecal or cloacal samples as a significant limitation hindering our understanding of the avian gastrointestinal (gut) microbiota and its function. We investigated the microbiota of the esophagus, duodenum, cecum, and colon of a wild urban population of Canada goose (Branta canadensis). From a population sample of 30 individuals, we sequenced the V4 region of the 16S SSU rRNA on an Illumina MiSeq and obtained 8,628,751 sequences with a median of 76,529 per sample. These sequences were assigned to 420 bacterial OTUs and a single archaeon. Firmicutes, Proteobacteria, and Bacteroidetes accounted for 90% of all sequences. Microbiotas from the four gut regions differed significantly in their richness, composition, and variability among individuals. Microbial communities of the esophagus were the most distinctive whereas those of the colon were the least distinctive, reflecting the physical downstream mixing of regional microbiotas. The downstream mixing of regional microbiotas was also responsible for the majority of observed co-occurrence patterns among microbial families. Our results indicate that fecal and cloacal samples inadequately represent the complex patterns of richness, composition, and variability of the gut microbiota and obscure patterns of co-occurrence of microbial lineages.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-21892-y","usgsCitation":"Drovetski, S., O’Mahoney, M., Ransome, E.J., Matterson, K., Lim, H.C., Chesser, T., and Graves, G.R., 2018, Spatial organization of the gastrointestinal microbiota in urban Canada geese: Scientific Reports, v. 8, p. 1-10, https://doi.org/10.1038/s41598-018-21892-y.","productDescription":"Article number 3713; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-093486","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468906,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-21892-y","text":"Publisher Index Page"},{"id":352628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-27","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc01a","contributors":{"authors":[{"text":"Drovetski, Sergei V.","contributorId":203364,"corporation":false,"usgs":false,"family":"Drovetski","given":"Sergei V.","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":731299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Mahoney, Michael","contributorId":203365,"corporation":false,"usgs":false,"family":"O’Mahoney","given":"Michael","email":"","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":731300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ransome, Emma J.","contributorId":203366,"corporation":false,"usgs":false,"family":"Ransome","given":"Emma","email":"","middleInitial":"J.","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":731301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matterson, Kenan O.","contributorId":203367,"corporation":false,"usgs":false,"family":"Matterson","given":"Kenan O.","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":731302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lim, Haw Chuan","contributorId":203368,"corporation":false,"usgs":false,"family":"Lim","given":"Haw","email":"","middleInitial":"Chuan","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":731303,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chesser, Terry 0000-0003-4389-7092 tchesser@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-7092","contributorId":177781,"corporation":false,"usgs":true,"family":"Chesser","given":"Terry","email":"tchesser@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":731298,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Graves, Gary R.","contributorId":203369,"corporation":false,"usgs":false,"family":"Graves","given":"Gary","email":"","middleInitial":"R.","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":731304,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196080,"text":"ofr20181041 - 2018 - Pilot testing and protocol development of giant applesnail suppression at Mandalay National Wildlife Refuge, Louisiana—July–October 2017","interactions":[],"lastModifiedDate":"2018-03-21T11:43:23","indexId":"ofr20181041","displayToPublicDate":"2018-03-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1041","title":"Pilot testing and protocol development of giant applesnail suppression at Mandalay National Wildlife Refuge, Louisiana—July–October 2017","docAbstract":"This report provides an overview of the pilot study and description of the techniques developed for a future mitigation study of Pomacea maculata (giant applesnail) at the U.S. Fish and Wildlife Service Mandalay National Wildlife Refuge, Louisiana (MNWR). Egg mass suppression is a potential strategy for the mitigation of the invasive giant applesnail. In previous studies at Langan Municipal Park in Mobile, Alabama (LMP), and National Park Service Jean Lafitte National Park-Barataria Unit, Louisiana (JLNP), we determined that spraying food-grade oil (coconut oil or Pam™ spray) on egg masses significantly reduced egg hatching. At JLNP we also developed methods to estimate snail population size. The purpose of this pilot study was to adapt techniques developed for previous studies to the circumstances of MNWR in preparation for a larger experiment whereby we will test the effectiveness of egg mass suppression as an applesnail mitigation tool. We selected four canals that will be used as treatment and control sites for the experiment (two each). We established that an efficient way to destroy egg masses is to knock them down with a high-velocity stream of water pumped directly from the canal. The traps used at JLNP had to be modified to accommodate the greater range of water-level fluctuation at MNWR. One of the three marking methods used at JLNP was selected for use at MNWR.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181041","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Barataria-Terrebonne National Estuary Program","usgsCitation":"Carter, Jacoby, and Merino, Sergio, 2018, Pilot testing and protocol development of giant applesnail suppression at Mandalay National Wildlife Refuge, Louisiana—July–October 2017: U.S. Geological Survey Open-File Report 2018-1041, 17 p., https://doi.org/10.3133/ofr20181041.","productDescription":"vi, 17 p.","numberOfPages":"17","onlineOnly":"Y","ipdsId":"IP-093234","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":352641,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1041/ofr20181041.pdf","text":"Report","size":"903 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1041"},{"id":352640,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1041/coverthb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mandalay 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 -90.84182739257812,\n 29.486378867043253\n ],\n [\n -90.76766967773438,\n 29.486378867043253\n ],\n [\n -90.76766967773438,\n 29.559422089438876\n ],\n [\n -90.84182739257812,\n 29.559422089438876\n ],\n [\n -90.84182739257812,\n 29.486378867043253\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
700 Cajundome Blvd.
Lafayette, LA 70506
The giant gartersnake (Thamnophis gigas) is a state and federally threatened species precinctive to California. The range of the giant gartersnake has contracted in the last century because its wetland habitat has been drained for agriculture and development. As a result of this habitat alteration, giant gartersnakes now largely persist in and near rice agriculture in the Sacramento Valley, because the system of canals that conveys water for rice growing approximates historical wetland habitat. Many aspects of the demography of giant gartersnakes are unknown, including how individuals grow throughout their life, how size influences reproduction, and how survival varies over time and among populations. We studied giant gartersnakes throughout the Sacramento Valley of California from 1995 to 2016 using capture-mark-recapture to study the growth, reproduction, and survival of this threatened species. We then use these data to construct an Integral Projection Model, and analyze this demographic model to understand which vital rates contribute most to the growth rate of giant gartersnake populations. We find that giant gartersnakes exhibit indeterminate growth; growth slows as individuals’ age. Fecundity, probability of reproduction, and survival all increase with size, although survival may decline for the largest female giant gartersnakes. The population growth rate of giant gartersnakes is most influenced by the survival and growth of large adult females, and the size at which 1 year old recruits enter the population. Our results indicate that management actions benefitting these influential demographic parameters will have the greatest positive effect on giant gartersnake population growth rates, and therefore population persistence. This study informs the conservation and management of giant gartersnakes and their habitat, and illustrates the effectiveness of hierarchical Bayesian models for the study of rare and elusive species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171164","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Rose, J.P., Ersan, J.S.M., Wylie, G.D., Casazza, M.L., and Halstead, B.J., 2018, Construction and analysis of a giant gartersnake (Thamnophis gigas) population projection model: U.S. Geological Survey Open-File Report 2017–1164, 98 p., https://doi.org/10.3133/ofr20171164.","productDescription":"viii, 98 p.","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-090465","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":352644,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1164/ofr20171164.pdf","text":"Report","size":"8.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1164"},{"id":352643,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1164/coverthb.jpg"}],"contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The magmatic degassing history of newly erupted volcanic glass is recorded in its remaining volatile content. However, this history is subsequently overprinted by post-depositional (secondary) hydration, the rates and origins of which are not yet adequately constrained. Here, we present the results of a natural experiment using products of the 1980 eruptions of Mount St. Helens. We measured water concentration, δDglass, and δ18OBSG (δ18O of the bulk silicate glass) of samples collected during the dry summer months of 1980 and compared them with material resampled in 2015 from the same deposits. Samples collected from the subsurface near gas escape pipes show elevated water concentrations (near 2.0 wt%), and these are associated with lower δDglass (− 110 to − 130‰) and δ18OBSG (6.0 to 6.6‰) values than the 1980 glass (− 70 to − 100‰ and 6.8 to 6.9‰, respectively). Samples collected in 2015 from the surface to 10-cm subsurface of the 1980 summer deposits have a small increase in average water contents of 0.1–0.2 wt% but similar δ18OBSG (6.8–6.9‰) values compared to the 1980 glass values. These samples, however, show 15‰ higher δDglass values; exchange with meteoric water is expected to yield lower δDglass values. We attribute higher δDglass values in the upper portion of the 1980 deposits collected in 2015 to rehydration by higher δD waters that were degassed for several months to a year from the hot underlying deposits, which hydrated the overlying deposits with relatively high δD gases. Our data also contribute to magmatic degassing of crystal-rich volcanoes. Using the 1980 samples, our reconstructed δD-H2O trends for the dacitic Mount St. Helens deposits with rhyolitic groundmass yield a trend that overlaps with the degassing trend for crystal-poor rhyolitic eruptions studied previously elsewhere, suggesting similar behavior of volatiles upon exsolution from magma. Furthermore, our data support previous studies proposing that exsolved volatiles were trapped within a rapidly rising magma and started degassing only at shallow depths during the 1980 eruptions.
Field characterization of a trichloroethene (TCE) source area in fractured mudstones produced a detailed understanding of the geology, contaminant distribution in fractures and the rock matrix, and hydraulic and transport properties. Groundwater flow and chemical transport modeling that synthesized the field characterization information proved critical for designing bioremediation of the source area. The planned bioremediation involved injecting emulsified vegetable oil and bacteria to enhance the naturally occurring biodegradation of TCE. The flow and transport modeling showed that injection will spread amendments widely over a zone of lower‐permeability fractures, with long residence times expected because of small velocities after injection and sorption of emulsified vegetable oil onto solids. Amendments transported out of this zone will be diluted by groundwater flux from other areas, limiting bioremediation effectiveness downgradient. At nearby pumping wells, further dilution is expected to make bioremediation effects undetectable in the pumped water. The results emphasize that in fracture‐dominated flow regimes, the extent of injected amendments cannot be conceptualized using simple homogeneous models of groundwater flow commonly adopted to design injections in unconsolidated porous media (e.g., radial diverging or dipole flow regimes). Instead, it is important to synthesize site characterization information using a groundwater flow model that includes discrete features representing high‐ and low‐permeability fractures. This type of model accounts for the highly heterogeneous hydraulic conductivity and groundwater fluxes in fractured‐rock aquifers, and facilitates designing injection strategies that target specific volumes of the aquifer and maximize the distribution of amendments over these volumes.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12585","usgsCitation":"Tiedeman, C.R., Shapiro, A.M., Hsieh, P.A., Imbrigiotta, T.E., Goode, D.J., Lacombe, P., DeFlaun, M.F., Drew, S.R., Johnson, C.D., Williams, J., and Curtis, G.P., 2018, Bioremediation in fractured rock: 1. Modeling to inform design, monitoring, and expectations: Groundwater, v. 56, no. 2, p. 300-316, https://doi.org/10.1111/gwat.12585.","productDescription":"17 p.","startPage":"300","endPage":"316","ipdsId":"IP-088879","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":352623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-05","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc01e","contributors":{"authors":[{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":731272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":731273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hsieh, Paul A. 0000-0003-4873-4874 pahsieh@usgs.gov","orcid":"https://orcid.org/0000-0003-4873-4874","contributorId":1634,"corporation":false,"usgs":true,"family":"Hsieh","given":"Paul","email":"pahsieh@usgs.gov","middleInitial":"A.","affiliations":[{"id":39113,"text":"WMA - Office of Quality Assurance","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":731274,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Imbrigiotta, Thomas E. 0000-0003-1716-4768 timbrig@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-4768","contributorId":152114,"corporation":false,"usgs":true,"family":"Imbrigiotta","given":"Thomas","email":"timbrig@usgs.gov","middleInitial":"E.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goode, Daniel J. 0000-0002-8527-2456 djgoode@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":193394,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel","email":"djgoode@usgs.gov","middleInitial":"J.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":731276,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lacombe, Pierre 0000-0002-9596-7622 placombe@usgs.gov","orcid":"https://orcid.org/0000-0002-9596-7622","contributorId":152113,"corporation":false,"usgs":true,"family":"Lacombe","given":"Pierre","email":"placombe@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731277,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeFlaun, Mary F.","contributorId":203177,"corporation":false,"usgs":false,"family":"DeFlaun","given":"Mary","email":"","middleInitial":"F.","affiliations":[{"id":36571,"text":"Geosyntec Consultants","active":true,"usgs":false}],"preferred":false,"id":731278,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Drew, Scott R.","contributorId":203178,"corporation":false,"usgs":false,"family":"Drew","given":"Scott","email":"","middleInitial":"R.","affiliations":[{"id":36571,"text":"Geosyntec Consultants","active":true,"usgs":false}],"preferred":false,"id":731279,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnson, Carole D. 0000-0001-6941-1578 cjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":1891,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole","email":"cjohnson@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":731280,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Williams, John 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731281,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Curtis, Gary P. 0000-0003-3975-8882 gpcurtis@usgs.gov","orcid":"https://orcid.org/0000-0003-3975-8882","contributorId":2346,"corporation":false,"usgs":true,"family":"Curtis","given":"Gary","email":"gpcurtis@usgs.gov","middleInitial":"P.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":731282,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70196087,"text":"70196087 - 2018 - Fate of antimony and arsenic in contaminated waters at the abandoned Su Suergiu mine (Sardinia, Italy)","interactions":[],"lastModifiedDate":"2018-03-17T17:44:10","indexId":"70196087","displayToPublicDate":"2018-03-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2745,"text":"Mine Water and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Fate of antimony and arsenic in contaminated waters at the abandoned Su Suergiu mine (Sardinia, Italy)","docAbstract":"We investigated the fate of Sb and As downstream of the abandoned Su Suergiu mine (Sardinia, Italy) and surrounding areas. The mined area is a priority in the Sardinian remediation plan for contaminated sites due to the high concentrations of Sb and As in the mining-related wastes, which may impact the Flumendosa River that supplies water for agriculture and domestic uses. Hydrogeochemical surveys conducted from 2005 to 2015 produced time-series data and downstream profiles of water chemistry at 46 sites. Water was sampled at: springs and streams unaffected by mining; adits and streams in the mine area; drainage from the slag heaps; stream water downstream of the slag drainages; and the Flumendosa River downstream from the confluence of the contaminated waters. At specific sites, water sampling was repeated under different flow conditions, resulting in a total of 99 samples. The water samples were neutral to slightly alkaline. Elevated Sb (up to 30 mg L−1) and As (up to 16 mg L−1) concentrations were observed in water flowing from the slag materials from where the Sb ore was processed. These slag materials were the main Sb and As source at Su Suergiu. A strong base, Na-carbonate, from the foundry wastes, had a major influence on mobilizing Sb and As. Downstream contamination can be explained by considering that: (1) the predominant aqueous species, Sb(OH)6 − and HAsO4 −2, are not favored in sorption processes at the observed pH conditions; (2) precipitation of Sb- and As-bearing solid phases was not observed, which is consistent with modeling results indicating undersaturation; and (3) the main decrease in dissolved Sb and As concentrations was by dilution. Dissolved As concentrations in the Flumendosa River did not generally exceed the EU limit of 10 µg L−1, whereas dissolved Sb in the river downstream of the contamination source always exceeded the EU limit of 5 µg L−1. Recent actions aimed at retaining runoff from the slag heaps are apparently not sufficiently mitigating contamination in the Flumendosa River.
","language":"English","publisher":"Springer","doi":"10.1007/s10230-017-0479-8","usgsCitation":"Cidu, R., Dore, E., Biddau, R., and Nordstrom, D.K., 2018, Fate of antimony and arsenic in contaminated waters at the abandoned Su Suergiu mine (Sardinia, Italy): Mine Water and the Environment, v. 37, no. 1, p. 151-165, https://doi.org/10.1007/s10230-017-0479-8.","productDescription":"15 p.","startPage":"151","endPage":"165","ipdsId":"IP-071489","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":352624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","state":"Sardinia","otherGeospatial":"Su Suergiu mine","volume":"37","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-31","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc020","contributors":{"authors":[{"text":"Cidu, Rosa","contributorId":194017,"corporation":false,"usgs":false,"family":"Cidu","given":"Rosa","affiliations":[{"id":36605,"text":"University of Cagliari, Cagliari, Sardinia","active":true,"usgs":false}],"preferred":false,"id":731269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dore, Elisabetta","contributorId":203363,"corporation":false,"usgs":false,"family":"Dore","given":"Elisabetta","email":"","affiliations":[{"id":36605,"text":"University of Cagliari, Cagliari, Sardinia","active":true,"usgs":false}],"preferred":false,"id":731271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biddau, Riccardo","contributorId":203362,"corporation":false,"usgs":false,"family":"Biddau","given":"Riccardo","email":"","affiliations":[{"id":36605,"text":"University of Cagliari, Cagliari, Sardinia","active":true,"usgs":false}],"preferred":false,"id":731270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":731268,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196083,"text":"70196083 - 2018 - Calibration of a field-scale Soil and Water Assessment Tool (SWAT) model with field placement of best management practices in Alger Creek, Michigan","interactions":[],"lastModifiedDate":"2018-03-26T13:40:10","indexId":"70196083","displayToPublicDate":"2018-03-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Calibration of a field-scale Soil and Water Assessment Tool (SWAT) model with field placement of best management practices in Alger Creek, Michigan","docAbstract":"Subwatersheds within the Great Lakes “Priority Watersheds” were targeted by the Great Lakes Restoration Initiative (GLRI) to determine the effectiveness of the various best management practices (BMPs) from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) Database. A Soil and Water Assessment Tool (SWAT) model is created for Alger Creek, a 50 km2 tributary watershed to the Saginaw River in Michigan. Monthly calibration yielded very good Nash–Sutcliffe efficiency (NSE) ratings for flow, sediment, total phosphorus (TP), dissolved reactive phosphorus (DRP), and total nitrogen (TN) (0.90, 0.79, 0.87, 0.88, and 0.77, respectively), and satisfactory NSE rating for nitrate (0.51). Two-year validation results in at least satisfactory NSE ratings for flow, sediment, TP, DRP, and TN (0.83, 0.54, 0.73, 0.53, and 0.60, respectively), and unsatisfactory NSE rating for nitrate (0.28). The model estimates the effect of BMPs at the field and watershed scales. At the field-scale, the most effective single practice at reducing sediment, TP, and DRP is no-tillage followed by cover crops (CC); CC are the most effective single practice at reducing nitrate. The most effective BMP combinations include filter strips, which can have a sizable effect on reducing sediment and phosphorus loads. At the watershed scale, model results indicate current NCP BMPs result in minimal sediment and nutrient reductions (<10%).
","language":"English","publisher":"MDPI","doi":"10.3390/su10030851","usgsCitation":"Merriman, K.R., Russell, A.M., Rachol, C.M., Daggupati, P., Srinivasan, R., Hayhurst, B.A., and Stuntebeck, T.D., 2018, Calibration of a field-scale Soil and Water Assessment Tool (SWAT) model with field placement of best management practices in Alger Creek, Michigan: Sustainability, v. 10, no. 3, p. 1-23, https://doi.org/10.3390/su10030851.","productDescription":"Article 851; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-092133","costCenters":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":468908,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/su10030851","text":"Publisher Index Page"},{"id":352617,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Alger Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.9167,\n 42.8333\n ],\n [\n -83.75,\n 42.8333\n ],\n [\n -83.75,\n 42.95\n ],\n [\n -83.9167,\n 42.95\n ],\n [\n -83.9167,\n 42.8333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-16","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc022","contributors":{"authors":[{"text":"Merriman, Katherine R. 0000-0002-1303-2410","orcid":"https://orcid.org/0000-0002-1303-2410","contributorId":203352,"corporation":false,"usgs":true,"family":"Merriman","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Amy M. 0000-0003-0582-0094 arussell@usgs.gov","orcid":"https://orcid.org/0000-0003-0582-0094","contributorId":200011,"corporation":false,"usgs":true,"family":"Russell","given":"Amy","email":"arussell@usgs.gov","middleInitial":"M.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rachol, Cynthia M. 0000-0001-9984-3435","orcid":"https://orcid.org/0000-0001-9984-3435","contributorId":203353,"corporation":false,"usgs":true,"family":"Rachol","given":"Cynthia","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daggupati, Prasad 0000-0002-7044-3435","orcid":"https://orcid.org/0000-0002-7044-3435","contributorId":189193,"corporation":false,"usgs":false,"family":"Daggupati","given":"Prasad","email":"","affiliations":[],"preferred":false,"id":731247,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Srinivasan, Raghavan","contributorId":189191,"corporation":false,"usgs":false,"family":"Srinivasan","given":"Raghavan","affiliations":[],"preferred":false,"id":731248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayhurst, Brett A. 0000-0002-1717-2015 bhayhurs@usgs.gov","orcid":"https://orcid.org/0000-0002-1717-2015","contributorId":3398,"corporation":false,"usgs":true,"family":"Hayhurst","given":"Brett","email":"bhayhurs@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731245,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stuntebeck, Todd D. 0000-0002-8405-7295 tdstunte@usgs.gov","orcid":"https://orcid.org/0000-0002-8405-7295","contributorId":902,"corporation":false,"usgs":true,"family":"Stuntebeck","given":"Todd","email":"tdstunte@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731249,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196077,"text":"70196077 - 2018 - Prey fish returned to Forster’s tern colonies suggest spatial and temporal differences in fish composition and availability","interactions":[],"lastModifiedDate":"2018-03-16T15:20:12","indexId":"70196077","displayToPublicDate":"2018-03-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Prey fish returned to Forster’s tern colonies suggest spatial and temporal differences in fish composition and availability","docAbstract":"Predators sample the available prey community when foraging; thus, changes in the environment may be reflected by changes in predator diet and foraging preferences. We examined Forster’s tern (Sterna forsteri) prey species over an 11-year period by sampling approximately 10,000 prey fish returned to 17 breeding colonies in south San Francisco Bay, California. We compared the species composition among repeatedly-sampled colonies (≥ 4 years), using both relative species abundance and the composition of total dry mass by species. Overall, the relative abundances of prey species at seven repeatedly-sampled tern colonies were more different than would be expected by chance, with the most notable differences in relative abundance observed between geographically distant colonies. In general, Mississippi silverside (Menidia audens) and topsmelt silverside (Atherinops affinis) comprised 42% of individuals and 40% of dry fish mass over the study period. Three-spined stickleback (Gasterosteus aculeatus) comprised the next largest proportion of prey species by individuals (19%) but not by dry mass (6%). Five additional species each contributed ≥ 4% of total individuals collected over the study period: yellowfin goby (Acanthogobius flavimanus; 10%), longjaw mudsucker (Gillichthys mirabilis; 8%), Pacific herring (Clupea pallasii; 6%), northern anchovy (Engraulis mordax; 4%), and staghorn sculpin (Leptocottus armatus; 4%). At some colonies, the relative abundance and biomass of specific prey species changed over time. In general, the abundance and dry mass of silversides increased, whereas the abundance and dry mass of three-spined stickleback and longjaw mudsucker decreased. As central place foragers, Forster’s terns are limited in the distance they forage; thus, changes in the prey species returned to Forster’s tern colonies suggest that the relative availability of some fish species in the environment has changed, possibly in response to alteration of the available habitat.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0193430","usgsCitation":"Peterson, S.H., Ackerman, J., Eagles-Smith, C.A., Herzog, M.P., and Hartman, C.A., 2018, Prey fish returned to Forster’s tern colonies suggest spatial and temporal differences in fish composition and availability: PLoS ONE, v. 13, no. 3, p. 1-23, https://doi.org/10.1371/journal.pone.0193430.","productDescription":"e0193430; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-090278","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468907,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0193430","text":"Publisher Index Page"},{"id":437985,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PG1QXT","text":"USGS data release","linkHelpText":"Prey fish returned to Forsters tern colonies in South San Francisco Bay during 2005-2015"},{"id":352619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.2,\n 37.4\n ],\n [\n -121.9,\n 37.4\n ],\n [\n -121.9,\n 37.6\n ],\n [\n -122.2,\n 37.6\n ],\n [\n -122.2,\n 37.4\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc024","contributors":{"authors":[{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":731223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":731222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":731225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131109,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":731226,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}