Switchgrass (Panicum virgatum) has been evaluated as one potential source for cellulosic biofuel feedstocks. Planting switchgrass in marginal croplands and waterway buffers can reduce soil erosion, improve water quality, and improve regional ecosystem services (i.e. it serves as a potential carbon sink). In previous studies, we mapped high risk marginal croplands and highly erodible cropland buffers that are potentially suitable for switchgrass development, which would improve ecosystem services and minimally impact food production. In this study, we advance our previous study results and integrate future crop expansion information to develop a switchgrass biofuel potential ensemble map for current and future croplands in eastern Nebraska. The switchgrass biomass productivity and carbon benefits (i.e. NEP: net ecosystem production) for the identified biofuel potential ensemble areas were quantified. The future scenario‐based (‘A1B’) land use and land cover map for 2050, the US Geological Survey crop type and Compound Topographic Index (CTI) maps, and long‐term (1981–2010) averaged annual precipitation data were used to identify future crop expansion regions that are suitable for switchgrass development. Results show that 2528 km2 of future crop expansion regions (~3.6% of the study area) are potentially suitable for switchgrass development. The total estimated biofuel potential ensemble area (including cropland buffers, marginal croplands, and future crop expansion regions) is 4232 km2 (~6% of the study area), potentially producing 3.52 million metric tons of switchgrass biomass per year. Converting biofuel ensemble regions to switchgrass leads to potential carbon sinks (the total NEP for biofuel potential areas is 0.45 million metric tons C) and is environmentally sustainable. Results from this study improve our understanding of environmental conditions and ecosystem services of current and future cropland systems in eastern Nebraska and provide useful information to land managers to make land use decisions regarding switchgrass development.
","language":"English","publisher":"Wiley","doi":"10.1111/gcbb.12468","usgsCitation":"Gu, Y., and Wylie, B., 2018, Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA: GCB Bioenergy, v. 10, no. 2, p. 76-83, https://doi.org/10.1111/gcbb.12468.","productDescription":"8 p.","startPage":"76","endPage":"83","ipdsId":"IP-087756","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469053,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcbb.12468","text":"Publisher Index Page"},{"id":353641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.1845703125,\n 40.01078714046552\n ],\n [\n -95.30639648437499,\n 40.01078714046552\n ],\n [\n -95.30639648437499,\n 42.99661231842139\n ],\n [\n -99.1845703125,\n 42.99661231842139\n ],\n [\n -99.1845703125,\n 40.01078714046552\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-12","publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1d7","contributors":{"authors":[{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":139586,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":733834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":197161,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce K.","email":"wylie@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":733835,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194981,"text":"70194981 - 2018 - Environmental DNA (eDNA): A tool for quantifying the abundant but elusive round goby (Neogobius melanostomus)","interactions":[],"lastModifiedDate":"2018-02-01T12:47:52","indexId":"70194981","displayToPublicDate":"2018-02-01T00:00:00","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}},"displayTitle":"Environmental DNA (eDNA): A tool for quantifying the abundant but elusive round goby (Neogobius melanostomus)","title":"Environmental DNA (eDNA): A tool for quantifying the abundant but elusive round goby (Neogobius melanostomus)","docAbstract":"Environmental DNA (eDNA) is revolutionizing biodiversity monitoring, occupancy estimates, and real-time detections of invasive species. In the Great Lakes, the round goby (Neogobius melanostomus), an invasive benthic fish from the Black Sea, has spread to encompass all five lakes and many tributaries, outcompeting or consuming native species; however, estimates of round goby abundance are confounded by behavior and habitat preference, which impact reliable methods for estimating their population. By integrating eDNA into round goby monitoring, improved estimates of biomass may be obtainable. We conducted mesocosm experiments to estimate rates of goby DNA shedding and decay. Further, we compared eDNA with several methods of traditional field sampling to compare its use as an alternative/complementary monitoring method. Environmental DNA decay was comparable to other fish species, and first-order decay was lower at 12°C (k = 0.043) than at 19°C (k = 0.058). Round goby eDNA was routinely detected in known invaded sites of Lake Michigan and its tributaries (range log10 4.8–6.2 CN/L), but not upstream of an artificial fish barrier. Traditional techniques (mark-recapture, seining, trapping) in Lakes Michigan and Huron resulted in fewer, more variable detections than eDNA, but trapping and eDNA were correlated (Pearson R = 0.87). Additional field testing will help correlate round goby abundance with eDNA, providing insight on its role as a prey fish and its impact on food webs.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0191720","usgsCitation":"Nevers, M., Byappanahalli, M., Morris, C.C., Shively, D., Przybyla-Kelly, K., Spoljaric, A., Dickey, J., and Roseman, E.F., 2018, Environmental DNA (eDNA): A tool for quantifying the abundant but elusive round goby (Neogobius melanostomus): PLoS ONE, v. 13, no. 1, p. 1-22, https://doi.org/10.1371/journal.pone.0191720.","productDescription":"e0191720; 22 p.","startPage":"1","endPage":"22","ipdsId":"IP-091049","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469070,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0191720","text":"Publisher Index Page"},{"id":350891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350889,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GH9H6F","text":"USGS data release","linkHelpText":"Round goby eDNA survey, evaluation, and laboratory data in Lakes Michigan and Huron 2016-2017"}],"country":"United States","otherGeospatial":"Lake Huron, Lake Michigan ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.48098754882812,\n 44.864629668602866\n ],\n [\n -83.19808959960936,\n 44.864629668602866\n ],\n [\n -83.19808959960936,\n 45.091944150432724\n ],\n [\n -83.48098754882812,\n 45.091944150432724\n ],\n [\n -83.48098754882812,\n 44.864629668602866\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.18878746032715,\n 41.60241477051867\n ],\n [\n -87.14561462402344,\n 41.60241477051867\n ],\n [\n -87.14561462402344,\n 41.64642834245559\n ],\n [\n -87.18878746032715,\n 41.64642834245559\n ],\n [\n -87.18878746032715,\n 41.60241477051867\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-22","publicationStatus":"PW","scienceBaseUri":"5a743581e4b0a9a2e9e25c8a","contributors":{"authors":[{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":726326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science 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kprzybyla-kelly@usgs.gov","orcid":"https://orcid.org/0000-0001-9168-3545","contributorId":201534,"corporation":false,"usgs":true,"family":"Przybyla-Kelly","given":"Katarzyna","email":"kprzybyla-kelly@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":726330,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spoljaric, Ashley M.","contributorId":201535,"corporation":false,"usgs":false,"family":"Spoljaric","given":"Ashley M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":726331,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dickey, Joshua","contributorId":201536,"corporation":false,"usgs":false,"family":"Dickey","given":"Joshua","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":726332,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roseman, Edward F. 0000-0002-5315-9838 eroseman@usgs.gov","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":168428,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward","email":"eroseman@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":726333,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70194991,"text":"70194991 - 2018 - Resource competition model predicts zonation and increasing nutrient use efficiency along a wetland salinity gradient","interactions":[],"lastModifiedDate":"2018-03-05T15:32:47","indexId":"70194991","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Resource competition model predicts zonation and increasing nutrient use efficiency along a wetland salinity gradient","docAbstract":"A trade-off between competitive ability and stress tolerance has been hypothesized and empirically supported to explain the zonation of species across stress gradients for a number of systems. Since stress often reduces plant productivity, one might expect a pattern of decreasing productivity across the zones of the stress gradient. However, this pattern is often not observed in coastal wetlands that show patterns of zonation along a salinity gradient. To address the potentially complex relationship between stress, zonation, and productivity in coastal wetlands, we developed a model of plant biomass as a function of resource competition and salinity stress. Analysis of the model confirms the conventional wisdom that a trade-off between competitive ability and stress tolerance is a necessary condition for zonation. It also suggests that a negative relationship between salinity and production can be overcome if (1) the supply of the limiting resource increases with greater salinity stress or (2) nutrient use efficiency increases with increasing salinity. We fit the equilibrium solution of the dynamic model to data from Louisiana coastal wetlands to test its ability to explain patterns of production across the landscape gradient and derive predictions that could be tested with independent data. We found support for a number of the model predictions, including patterns of decreasing competitive ability and increasing nutrient use efficiency across a gradient from freshwater to saline wetlands. In addition to providing a quantitative framework to support the mechanistic hypotheses of zonation, these results suggest that this simple model is a useful platform to further build upon, simulate and test mechanistic hypotheses of more complex patterns and phenomena in coastal wetlands.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2131","usgsCitation":"Schoolmaster, D., and Stagg, C.L., 2018, Resource competition model predicts zonation and increasing nutrient use efficiency along a wetland salinity gradient: Ecology, v. 99, no. 3, p. 670-680, https://doi.org/10.1002/ecy.2131.","productDescription":"11 p.","startPage":"670","endPage":"680","ipdsId":"IP-089350","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":350913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.09765625,\n 28.459033019728043\n ],\n [\n -88.330078125,\n 28.459033019728043\n ],\n [\n -88.330078125,\n 31.11879439598953\n ],\n [\n -95.09765625,\n 31.11879439598953\n ],\n [\n -95.09765625,\n 28.459033019728043\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"99","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-30","publicationStatus":"PW","scienceBaseUri":"5a74357fe4b0a9a2e9e25c78","contributors":{"authors":[{"text":"Schoolmaster, Donald 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":156350,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","email":"schoolmasterd@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":726426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":726427,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195783,"text":"70195783 - 2018 - Dynamic interactions between coastal storms and salt marshes: A review","interactions":[],"lastModifiedDate":"2018-03-02T11:28:31","indexId":"70195783","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic interactions between coastal storms and salt marshes: A review","docAbstract":"This manuscript reviews the progresses made in the understanding of the dynamic interactions between coastal storms and salt marshes, including the dissipation of extreme water levels and wind waves across marsh surfaces, the geomorphic impact of storms on salt marshes, the preservation of hurricanes signals and deposits into the sedimentary records, and the importance of storms for the long term survival of salt marshes to sea level rise. A review of weaknesses, and strengths of coastal defences incorporating the use of salt marshes including natural, and hybrid infrastructures in comparison to standard built solutions is then presented.
Salt marshes are effective in dissipating wave energy, and storm surges, especially when the marsh is highly elevated, and continuous. This buffering action reduces for storms lasting more than one day. Storm surge attenuation rates range from 1.7 to 25 cm/km depending on marsh and storms characteristics. In terms of vegetation properties, the more flexible stems tend to flatten during powerful storms, and to dissipate less energy but they are also more resilient to structural damage, and their flattening helps to protect the marsh surface from erosion, while stiff plants tend to break, and could increase the turbulence level and the scour. From a morphological point of view, salt marshes are generally able to withstand violent storms without collapsing, and violent storms are responsible for only a small portion of the long term marsh erosion.
Our considerations highlight the necessity to focus on the indirect long term impact that large storms exerts on the whole marsh complex rather than on sole after-storm periods. The morphological consequences of storms, even if not dramatic, might in fact influence the response of the system to normal weather conditions during following inter-storm periods. For instance, storms can cause tidal flats deepening which in turn promotes wave energy propagation, and exerts a long term detrimental effect for marsh boundaries even during calm weather. On the other hand, when a violent storm causes substantial erosion but sediments are redistributed across nearby areas, the long term impact might not be as severe as if sediments were permanently lost from the system, and the salt marsh could easily recover to the initial state.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2017.11.001","usgsCitation":"Leonardi, N., Carnacina, I., Donatelli, C., Ganju, N.K., Plater, A.J., Schuerch, M., and Temmerman, S., 2018, Dynamic interactions between coastal storms and salt marshes: A review: Geomorphology, v. 301, p. 92-107, https://doi.org/10.1016/j.geomorph.2017.11.001.","productDescription":"16 p.","startPage":"92","endPage":"107","ipdsId":"IP-090257","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469062,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"text":"Publisher Index Page"},{"id":352179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"301","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee742e4b0da30c1bfc1f7","contributors":{"authors":[{"text":"Leonardi, Nicoletta","contributorId":202868,"corporation":false,"usgs":false,"family":"Leonardi","given":"Nicoletta","email":"","affiliations":[{"id":36541,"text":"University of Liverpool, Department of Geography and Planning, 74 Bedford St S.","active":true,"usgs":false}],"preferred":false,"id":729951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carnacina, Iacopo","contributorId":202869,"corporation":false,"usgs":false,"family":"Carnacina","given":"Iacopo","email":"","affiliations":[{"id":36542,"text":"Liverpool John Moores University, Department of Civil Engineering, Peter Jost","active":true,"usgs":false}],"preferred":false,"id":729952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donatelli, Carmine","contributorId":202870,"corporation":false,"usgs":false,"family":"Donatelli","given":"Carmine","affiliations":[{"id":36541,"text":"University of Liverpool, Department of Geography and Planning, 74 Bedford St S.","active":true,"usgs":false}],"preferred":false,"id":729953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":174763,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil","email":"nganju@usgs.gov","middleInitial":"K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":729950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plater, Andrew James","contributorId":202871,"corporation":false,"usgs":false,"family":"Plater","given":"Andrew","email":"","middleInitial":"James","affiliations":[{"id":36541,"text":"University of Liverpool, Department of Geography and Planning, 74 Bedford St S.","active":true,"usgs":false}],"preferred":false,"id":729954,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schuerch, Mark","contributorId":202872,"corporation":false,"usgs":false,"family":"Schuerch","given":"Mark","email":"","affiliations":[{"id":36543,"text":"Cambridge Coastal Research Unit (CCRU) Department of Geography, University of","active":true,"usgs":false}],"preferred":false,"id":729955,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Temmerman, Stijn","contributorId":189204,"corporation":false,"usgs":false,"family":"Temmerman","given":"Stijn","email":"","affiliations":[],"preferred":false,"id":729956,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196893,"text":"70196893 - 2018 - Vertical self-sorting behavior in juvenile Chinook salmon (Oncorhynchus tshawytscha): evidence for family differences and variation in growth and morphology","interactions":[],"lastModifiedDate":"2018-05-17T15:37:23","indexId":"70196893","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Vertical self-sorting behavior in juvenile Chinook salmon (Oncorhynchus tshawytscha): evidence for family differences and variation in growth and morphology","docAbstract":"Life history variation is fundamental to the evolution of Pacific salmon and their persistence under variable conditions. We discovered that Chinook salmon sort themselves into surface- and bottom-oriented groups in tanks within days after exogenous feeding. We hypothesised that this behaviour is correlated with subsequent differences in body morphology and growth (as measured by final length and mass) observed later in life. We found consistent morphological differences between surface and bottom phenotypes. Furthermore, we found that surface and bottom orientation within each group is maintained for at least one year after the phenotypes were separated. These surface and bottom phenotypes are expressed across genetic stocks, brood years, and laboratories and we show that the proportion of surface- and bottom-oriented offspring also differed among families. Importantly, feed delivery location did not affect morphology or growth, and the surface fish were longer than bottom fish at the end of the rearing experiment. The body shape of the former correlates with wild individuals that rear in mainstem habitats and migrate in the fall as subyearlings and the latter resemble those that remain in the upper tributaries and migrate as yearling spring migrants. Our findings suggest that early self-sorting behaviour may have a genetic basis and be correlated with other phenotypic traits that are important indicators for juvenile migration timing.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-017-0702-2","usgsCitation":"Unrein, J.R., Billman, E., Cogliati, K.M., Chitwood, R.S., Noakes, D.L., and Schreck, C.B., 2018, Vertical self-sorting behavior in juvenile Chinook salmon (Oncorhynchus tshawytscha): evidence for family differences and variation in growth and morphology: Environmental Biology of Fishes, v. 101, no. 2, p. 341-353, https://doi.org/10.1007/s10641-017-0702-2.","productDescription":"13 p.","startPage":"341","endPage":"353","ipdsId":"IP-066132","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"101","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-02","publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1c9","contributors":{"authors":[{"text":"Unrein, Julia R.","contributorId":172777,"corporation":false,"usgs":false,"family":"Unrein","given":"Julia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":735726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Billman, E.J.","contributorId":172038,"corporation":false,"usgs":false,"family":"Billman","given":"E.J.","email":"","affiliations":[],"preferred":false,"id":735727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cogliati, Karen M.","contributorId":200086,"corporation":false,"usgs":false,"family":"Cogliati","given":"Karen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chitwood, Rob S.","contributorId":172779,"corporation":false,"usgs":false,"family":"Chitwood","given":"Rob","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":735729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noakes, David L. G.","contributorId":195116,"corporation":false,"usgs":false,"family":"Noakes","given":"David","email":"","middleInitial":"L. G.","affiliations":[],"preferred":false,"id":735730,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":734925,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196285,"text":"70196285 - 2018 - Image simulation and assessment of the colour and spatial capabilities of the Colour and Stereo Surface Imaging System (CaSSIS) on the ExoMars Trace Gas Orbiter","interactions":[],"lastModifiedDate":"2018-03-30T11:11:48","indexId":"70196285","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3454,"text":"Space Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Image simulation and assessment of the colour and spatial capabilities of the Colour and Stereo Surface Imaging System (CaSSIS) on the ExoMars Trace Gas Orbiter","docAbstract":"This study aims to assess the spatial and visible/near-infrared (VNIR) colour/spectral capabilities of the 4-band Colour and Stereo Surface Imaging System (CaSSIS) aboard the ExoMars 2016 Trace Grace Orbiter (TGO). The instrument response functions for the CaSSIS imager was used to resample spectral libraries, modelled spectra and to construct spectrally (i.e., in I/F space) and spatially consistent simulated CaSSIS image cubes of various key sites of interest and for ongoing scientific investigations on Mars. Coordinated datasets from Mars Reconnaissance Orbiter (MRO) are ideal, and specifically used for simulating CaSSIS. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provides colour information, while the Context Imager (CTX), and in a few cases the High-Resolution Imaging Science Experiment (HiRISE), provides the complementary spatial information at the resampled CaSSIS unbinned/unsummed pixel resolution (4.6 m/pixel from a 400-km altitude). The methodology used herein employs a Gram-Schmidt spectral sharpening algorithm to combine the ∼18–36 m/pixel CRISM-derived CaSSIS colours with I/F images primarily derived from oversampled CTX images. One hundred and eighty-one simulated CaSSIS 4-colour image cubes (at 18–36 m/pixel) were generated (including one of Phobos) based on CRISM data. From these, thirty-three “fully”-simulated image cubes of thirty unique locations on Mars (i.e., with 4 colour bands at 4.6 m/pixel) were made. All simulated image cubes were used to test both the colour capabilities of CaSSIS by producing standard colour RGB images, colour band ratio composites (CBRCs) and spectral parameters. Simulated CaSSIS CBRCs demonstrated that CaSSIS will be able to readily isolate signatures related to ferrous (Fe2+) iron- and ferric (Fe3+) iron-bearing deposits on the surface of Mars, ices and atmospheric phenomena. Despite the lower spatial resolution of CaSSIS when compared to HiRISE, the results of this work demonstrate that CaSSIS will not only compliment HiRISE-scale studies of various geological and seasonal phenomena, it will also enhance them by providing additional colour and geologic context through its wider and longer full-colour coverage (
Environmental contamination is problematic for tropical islands due to their typically dense human populations and competing land and water uses. The Caribbean island of Puerto Rico (USA) has a long history of anthropogenic chemical use, and its human population density is among the highest globally, providing a model environment to study contaminant impacts on tropical island stream ecosystems. Polycyclic Aromatic Hydrocarbons, historic-use chlorinated pesticides, current-use pesticides, Polychlorinated Biphenyls (PCBs), and metals (mercury, cadmium, copper, lead, nickel, zinc, and selenium) were quantified in the habitat and biota of Puerto Rico streams and assessed in relation to land-use patterns and toxicological thresholds. Water, sediment, and native fish and shrimp species were sampled in 13 rivers spanning broad watershed land-use characteristics during 2009–2010. Contrary to expectations, freshwater stream ecosystems in Puerto Rico were not severely polluted, likely due to frequent flushing flows and reduced deposition associated with recurring flood events. Notable exceptions of contamination were nickel in sediment within three agricultural watersheds (range 123–336 ppm dry weight) and organic contaminants (PCBs, organochlorine pesticides) and mercury in urban landscapes. At an urban site, PCBs in several fish species (Mountain Mullet Agonostomus monticola [range 0.019–0.030 ppm wet weight] and American Eel Anguilla rostrata [0.019–0.031 ppm wet weight]) may pose human health hazards, with concentrations exceeding the U.S. Environmental Protection Agency (EPA) consumption limit for 1 meal/month. American Eel at the urban site also contained dieldrin (range < detection-0.024 ppm wet weight) that exceeded the EPA maximum allowable consumption limit. The Bigmouth Sleeper Gobiomorous dormitor, an important piscivorus sport fish, accumulated low levels of organic contaminants in edible muscle tissue (due to its low lipid content) and may be most suitable for human consumption island-wide; only mercury at one site (an urban location) exceeded EPA's consumption limit of 3 meals/month for this species. These results comprise the first comprehensive island-wide contaminant assessment of Puerto Rico streams and biota and provide natural resource and public health agencies here and in similar tropical islands elsewhere with information needed to guide ecosystem and fisheries conservation and management and human health risk assessment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envres.2017.11.053","usgsCitation":"Buttermore, E.N., Cope, W., Kwak, T.J., Cooney, P.B., Shea, D., and Lazaro, P.R., 2018, Contaminants in tropical island streams and their biota: Environmental Research, v. 161, p. 615-623, https://doi.org/10.1016/j.envres.2017.11.053.","productDescription":"9 p.","startPage":"615","endPage":"623","ipdsId":"IP-092384","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354728,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"161","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e5d4e4b060350a15d220","contributors":{"authors":[{"text":"Buttermore, Elissa N.","contributorId":84871,"corporation":false,"usgs":true,"family":"Buttermore","given":"Elissa","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":737243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":737244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":737242,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooney, Patrick B.","contributorId":141249,"corporation":false,"usgs":false,"family":"Cooney","given":"Patrick","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":737245,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shea, Damian","contributorId":145456,"corporation":false,"usgs":false,"family":"Shea","given":"Damian","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":737246,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lazaro, Peter R.","contributorId":205423,"corporation":false,"usgs":false,"family":"Lazaro","given":"Peter","email":"","middleInitial":"R.","affiliations":[{"id":37103,"text":"Department of Biological Sciences, North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":737247,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197788,"text":"70197788 - 2018 - Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States","interactions":[],"lastModifiedDate":"2018-06-20T10:54:13","indexId":"70197788","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3568,"text":"The Leading Edge","active":true,"publicationSubtype":{"id":10}},"title":"Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States","docAbstract":"Probabilistic seismic hazard analysis (PSHA) characterizes ground-motion hazard from earthquakes. Typically, the time horizon of a PSHA forecast is long, but in response to induced seismicity related to hydrocarbon development, the USGS developed one-year PSHA models. In this paper, we present a display of the variability in USGS hazard curves due to epistemic uncertainty in its informed submodel using a simple bootstrapping approach. We find that variability is highest in low-seismicity areas. On the other hand, areas of high seismic hazard, such as the New Madrid seismic zone or Oklahoma, exhibit relatively lower variability simply because of more available data and a better understanding of the seismicity. Comparing areas of high hazard, New Madrid, which has a history of large naturally occurring earthquakes, has lower forecast variability than Oklahoma, where the hazard is driven mainly by suspected induced earthquakes since 2009. Overall, the mean hazard obtained from bootstrapping is close to the published model, and variability increased in the 2017 one-year model relative to the 2016 model. Comparing the relative variations caused by individual logic-tree branches, we find that the highest hazard variation (as measured by the 95% confidence interval of bootstrapping samples) in the final model is associated with different ground-motion models and maximum magnitudes used in the logic tree, while the variability due to the smoothing distance is minimal. It should be pointed out that this study is not looking at the uncertainty in the hazard in general, but only as it is represented in the USGS one-year models.
","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/tle37020141a1.1","usgsCitation":"Mousavi, S.M., Beroza, G.C., and Hoover, S.M., 2018, Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States: The Leading Edge, v. 37, no. 2, p. 141a1-141a9, https://doi.org/10.1190/tle37020141a1.1.","productDescription":"9 p.","startPage":"141a1","endPage":"141a9","ipdsId":"IP-093220","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":355202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115,\n 25\n ],\n [\n -65,\n 25\n ],\n [\n -65,\n 50\n ],\n [\n -115,\n 50\n ],\n [\n -115,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e5d3e4b060350a15d21c","contributors":{"authors":[{"text":"Mousavi, S. Mostafa","contributorId":205790,"corporation":false,"usgs":false,"family":"Mousavi","given":"S.","email":"","middleInitial":"Mostafa","affiliations":[{"id":37167,"text":"Department of Geophysics, Stanford University, Stanford, CA","active":true,"usgs":false}],"preferred":false,"id":738494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":738495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoover, Susan M. 0000-0002-8682-6668 shoover@usgs.gov","orcid":"https://orcid.org/0000-0002-8682-6668","contributorId":5715,"corporation":false,"usgs":true,"family":"Hoover","given":"Susan","email":"shoover@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738496,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221602,"text":"70221602 - 2018 - Spatial and temporal variability in growth of giant gartersnakes: Plasticity, precipitation, and prey","interactions":[],"lastModifiedDate":"2021-06-25T11:47:22.00398","indexId":"70221602","displayToPublicDate":"2018-01-25T06:40:24","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variability in growth of giant gartersnakes: Plasticity, precipitation, and prey","docAbstract":"The growth rate of reptiles is plastic and often varies among individuals, populations, and years in response to environmental conditions. For an imperiled species, the growth rate of individual animals is an important component of demographic models, and changes in individual growth rates might precede changes in abundance. We analyzed a long-term dataset on the growth of Giant Gartersnakes (Thamnophis gigas) to characterize spatial and temporal variability and evaluate potential environmental predictors of growth. We collected data on the growth in snout–vent length (SVL) of Giant Gartersnakes over 22 yr (1995–2016) from eight sites distributed throughout the Sacramento Valley of California, USA. The von Bertalanffy growth curves indicated male Giant Gartersnakes grew faster toward shorter, asymptotic SVL than did females. Nearly equal variability in growth was attributable to differences among years and among sites. From 2003–2016 we collected data on precipitation, temperature, and the abundance of fish and anuran prey at each site and used these variables as predictors in growth models of Giant Gartersnakes. Snake growth was positively related to the amount of precipitation that fell during the prior water year and the abundance of anurans at a site. Fish and frog abundance interacted to affect snake growth: at low abundances of one prey type, the other positively affected growth, but the slope of this relationship decreased as alternative prey abundance increased. Our results highlight the plasticity of growth in this threatened snake species, point to potential environmental drivers of growth, and provide valuable data for demographic modeling efforts.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","doi":"10.1670/17-055","usgsCitation":"Rose, J.P., Halstead, B., Wylie, G.D., and Casazza, M.L., 2018, Spatial and temporal variability in growth of giant gartersnakes: Plasticity, precipitation, and prey: Journal of Herpetology, v. 52, no. 1, p. 40-49, https://doi.org/10.1670/17-055.","productDescription":"10 p.","startPage":"40","endPage":"49","ipdsId":"IP-086235","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":386725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.78320312499999,\n 38.27268853598095\n ],\n [\n -120.38818359374997,\n 38.27268853598095\n ],\n [\n -120.38818359374997,\n 40.863679665481676\n ],\n [\n -122.78320312499999,\n 40.863679665481676\n ],\n [\n -122.78320312499999,\n 38.27268853598095\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":818253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":818254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Glenn D. 0000-0002-7061-6658 glenn_wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-6658","contributorId":3052,"corporation":false,"usgs":true,"family":"Wylie","given":"Glenn","email":"glenn_wylie@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":818255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":818256,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195936,"text":"70195936 - 2018 - Estimating population extinction thresholds with categorical classification trees for Louisiana black bears","interactions":[],"lastModifiedDate":"2018-03-08T09:51:49","indexId":"70195936","displayToPublicDate":"2018-01-23T00:00:00","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":"Estimating population extinction thresholds with categorical classification trees for Louisiana black bears","docAbstract":"Monitoring vulnerable species is critical for their conservation. Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus) was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR) data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years () was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when
, suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. We conclude that population projections and conditional classification trees can be valuable tools for identifying extinction thresholds used in monitoring programs.
Armenia is a landlocked country located in the mountainous Caucasus region between Asia and Europe. It shares borders with the countries of Georgia on the north, Azerbaijan on the east, Iran on the south, and Turkey and Azerbaijan on the west. The Ararat Basin is a transboundary basin in Armenia and Turkey. The Ararat Basin (or Ararat Valley) is an intermountain depression that contains the Aras River and its tributaries, which also form the border between Armenia and Turkey and divide the basin into northern and southern regions. The Ararat Basin also contains Armenia’s largest agricultural and fish farming zone that is supplied by high-quality water from wells completed in the artesian aquifers that underlie the basin. Groundwater constitutes about 40 percent of all water use, and groundwater provides 96 percent of the water used for drinking purposes in Armenia. Since 2000, groundwater withdrawals and consumption in the Ararat Basin of Armenia have increased because of the growth of aquaculture and other uses. Increased groundwater withdrawals caused decreased springflow, reduced well discharges, falling water levels, and a reduction of the number of flowing artesian wells in the southern part of Ararat Basin in Armenia.
In 2016, the U.S. Geological Survey and the U.S. Agency for International Development (USAID) began a cooperative study in Armenia to share science and field techniques to increase the country’s capabilities for groundwater study and modeling. The purpose of this report is to describe the hydrogeologic framework and groundwater conditions of the Ararat Basin in Armenia based on data collected in 2016 and previous hydrogeologic studies. The study area includes the Ararat Basin in Armenia. This report was completed through a partnership with USAID/Armenia in the implementation of its Science, Technology, Innovation, and Partnerships effort through the Advanced Science and Partnerships for Integrated Resource Development program and associated partners, including the Government of Armenia, Armenia’s Hydrogeological Monitoring Center, and the USAID Global Development Lab and its GeoCenter.
The hydrogeologic framework of the Ararat Basin includes several basin-fill stratigraphic units consisting of interbedded dense clays, gravels, sands, volcanic basalts, and andesite deposits. Previously published cross sections and well lithologic logs were used to map nine general hydrogeologic units. Hydrogeologic units were mapped based on lithology and water-bearing potential. Water-level data measured in the water-bearing hydrogeologic units 2, 4, 6, and 8 in 2016 were used to create potentiometric surface maps. In hydrogeologic unit 2, the estimated direction of groundwater flow is from the west to north in the western part of the basin (away from the Aras River) and from north to south (toward the Aras River) in the eastern part of the basin. In hydrogeologic unit 4, the direction of groundwater flow is generally from west to east and north to south (toward the Aras River) except in the western part of the basin where groundwater flow is toward the north or northwest. Hydrogeologic unit 6 has the same general pattern of groundwater flow as unit 4. Hydrogeologic unit 8 is the deepest of the water-bearing units and is confined in the basin. Groundwater flow generally is from the south to north (away from the Aras River) in the western part of the basin and from west to east and north to south (toward the Aras River) elsewhere in the basin.
In addition to water levels, personnel from Armenia’s Hydrogeological Monitoring Center also measured specific conductance at 540 wells and temperature at 2,470 wells in the Ararat Basin using U.S. Geological Survey protocols in 2016. The minimum specific conductance was 377 microsiemens per centimeter (μS/cm), the maximum value was 4,000 μS/cm, and the mean was 998 μS/cm. The maximum water temperature was 24.2 degrees Celsius. An analysis between water temperature and well depth indicated no relation; however, spatially, most wells with cooler water temperatures were within the 2016 pressure boundary or in the western part of the basin. Wells with generally warmer water temperatures were in the eastern part of the basin.
Samples were collected from four groundwater sites and one surface-water site by the U.S. Geological Survey in 2016. The stable-isotope values were similar for all five sites, indicating similar recharge sources for the sampled wells. The Hrazdan River sample was consistent with the groundwater samples, indicating the river could serve as a source of recharge to the Ararat artesian aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175163","usgsCitation":"Valder, J.F., Carter, J.M., Medler, C.J., Thompson, R.F., and Anderson, M.T., 2018, Hydrogeologic framework and groundwater conditions of the Ararat Basin in Armenia: U.S. Geological Survey Scientific Investigations Report 2017–5163, 40 p., https://doi.org/10.3133/sir20175163.","productDescription":"Report: viii, 40 p.; Tables","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-088554","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":350454,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5163/sir20175163_table6.xls","text":"Table 6. Historical water-level and well yield data from various dates ranging from 1981 to 2013 in the Ararat Basin, Armenia","size":"96 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5163 Table 6"},{"id":350430,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5163/coverthb.jpg"},{"id":350452,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5163/sir20175163_table5.xlsx","text":"Table 5. Historical water-level data from 2007 in the Ararat Basin, Armenia, provided to the U.S. Geological Survey by Armenian partners","size":"200 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5163 Table 5"},{"id":350451,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5163/sir20175163_table4.xls","text":"Table 4. Hydrologic data provided to the U.S. Geological Survey from the 2016 well inventory conducted in the Ararat Basin, Armenia, by Armenian partners","size":"808 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5163 Table 4"},{"id":350434,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5163/sir20175163_table1.xlsx","text":"Table 1 Lithologic descriptions, land-surface elevations, geologic layer thicknesses, and hydrogeologic units of the Ararat Basin, Armenia","size":"792 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5163 Table 1"},{"id":350432,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5163/sir20175163.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5163"}],"country":"Armenia","otherGeospatial":"Ararat Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 43.75,\n 39.75\n ],\n [\n 44.8,\n 39.75\n ],\n [\n 44.8,\n 40.25\n ],\n [\n 43.75,\n 40.25\n ],\n [\n 43.75,\n 39.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center, South Dakota Office
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
Riverscapes are complex, landscape-scale mosaics of connected river and stream habitats embedded in diverse ecological and socioeconomic settings. Social–ecological interactions among stakeholders often complicate natural-resource conservation and management of riverscapes. The management challenges posed by the conservation and restoration of wild salmonid populations in the Columbia River Basin (CRB) of western North America are one such example. Because of their ecological, cultural, and socioeconomic importance, salmonids present a complex management landscape due to interacting environmental factors (eg climate change, invasive species) as well as socioeconomic and political factors (eg dams, hatcheries, land-use change, transboundary agreements). Many of the problems in the CRB can be linked to social–ecological interactions occurring within integrated ecological, human–social, and regional–climatic spheres. Future management and conservation of salmonid populations therefore depends on how well the issues are understood and whether they can be resolved through effective communication and collaboration among ecologists, social scientists, stakeholders, and policy makers.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.1752","usgsCitation":"Hand, B., Flint, C.G., Frissell, C.A., Muhlfeld, C.C., Devlin, S.P., Kennedy, B., Crabtree, R.L., McKee, W.A., Luikart, G., and Stanford, J.A., 2018, A social–ecological perspective for riverscape management in the Columbia River Basin: Frontiers in Ecology and the Environment, v. 16, no. S1, p. S23-S33, https://doi.org/10.1002/fee.1752.","productDescription":"11 p.","startPage":"S23","endPage":"S33","ipdsId":"IP-082252","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":469093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.1752","text":"Publisher Index Page"},{"id":352016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Columbia River Basin","volume":"16","issue":"S1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-16","publicationStatus":"PW","scienceBaseUri":"5afee751e4b0da30c1bfc228","contributors":{"authors":[{"text":"Hand, Brian K.","contributorId":139248,"corporation":false,"usgs":false,"family":"Hand","given":"Brian K.","affiliations":[{"id":12707,"text":"Flathead Lake Biological Station, Fish and Wildlife Genomics Group, University of Montana, Polson, MT 59860","active":true,"usgs":false}],"preferred":false,"id":729464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Courtney G.","contributorId":202755,"corporation":false,"usgs":false,"family":"Flint","given":"Courtney","email":"","middleInitial":"G.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":729465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frissell, Chris A.","contributorId":202756,"corporation":false,"usgs":false,"family":"Frissell","given":"Chris","email":"","middleInitial":"A.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":729466,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":729463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Devlin, Shawn P.","contributorId":202757,"corporation":false,"usgs":false,"family":"Devlin","given":"Shawn","email":"","middleInitial":"P.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":729467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kennedy, Brian P.","contributorId":202785,"corporation":false,"usgs":false,"family":"Kennedy","given":"Brian P.","affiliations":[],"preferred":false,"id":729468,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Crabtree, Robert L.","contributorId":202758,"corporation":false,"usgs":false,"family":"Crabtree","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":35162,"text":"Yellowstone Ecological Research Center","active":true,"usgs":false}],"preferred":false,"id":729469,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McKee, W. Arthur","contributorId":202786,"corporation":false,"usgs":false,"family":"McKee","given":"W.","email":"","middleInitial":"Arthur","affiliations":[],"preferred":false,"id":729470,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":729471,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stanford, Jack A.","contributorId":150193,"corporation":false,"usgs":false,"family":"Stanford","given":"Jack","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":729472,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70198431,"text":"70198431 - 2018 - Size, age, renewal, and discharge of groundwater carbon","interactions":[],"lastModifiedDate":"2018-08-06T14:30:57","indexId":"70198431","displayToPublicDate":"2018-01-15T14:30:47","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"Size, age, renewal, and discharge of groundwater carbon","docAbstract":"Groundwater carbon (C) supply to lakes and streams is important to understanding the role of inland waters in global and regional cycles and in the functioning of aquatic ecosystems. We provide new estimates of the size and discharge of the groundwater C pool using data from a broad survey of groundwater C, information on the depth distribution of groundwater, and data on groundwater age. About 0.25 × 106 km3 of the 8 × 106km3 of groundwater resource is within 100 m of the surface and 4.2 × 106 km3 is above 2000 m. Ages show an average groundwater turnover time of 10 yr at 25 m, 350 yr at 100 m, increasing to about 100 000 yr at 600 m. Global groundwater discharge is 16 000 km3 yr−1; >16% of precipitation passes through groundwater. Groundwater dissolved organic C (DOC) can be high in shallow groundwater but stabilizes at ~2–4 mg L−1 at 100 m. Average groundwater dissolved inorganic C (DIC) is ~30–43 mg L−1. Groundwater C content to 2000 m is ~145 Pg, about the same as all marine sediments and about one-sixth that of the surface ocean. Groundwater C discharge to continental waters is 0.68 Pg yr−1, or 3.4 times that estimated from river base-flow and submarine groundwater discharge. This discharge is 68 times previous estimates, implying a total C flux from land of 3.6 Pg yr−1; 80% of discharge occurs from above 40 m and 99% from the upper 100 m.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/20442041.2017.1412918","usgsCitation":"Downing, J.A., and Striegl, R.G., 2018, Size, age, renewal, and discharge of groundwater carbon: Inland Waters, v. 8, no. 1, p. 122-127, https://doi.org/10.1080/20442041.2017.1412918.","productDescription":"6 p.","startPage":"122","endPage":"127","ipdsId":"IP-076067","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":469095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/20442041.2017.1412918","text":"Publisher Index Page"},{"id":356201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-15","publicationStatus":"PW","scienceBaseUri":"5b6fc4bae4b0f5d57878eac2","contributors":{"authors":[{"text":"Downing, John A.","contributorId":169033,"corporation":false,"usgs":false,"family":"Downing","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":741405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":741404,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198089,"text":"70198089 - 2018 - Infrared heater system for warming tropical forest understory plants and soils","interactions":[],"lastModifiedDate":"2018-07-13T10:22:15","indexId":"70198089","displayToPublicDate":"2018-01-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Infrared heater system for warming tropical forest understory plants and soils","docAbstract":"The response of tropical forests to global warming is one of the largest uncertainties\nin predicting the future carbon balance of Earth. To determine the likely effects of elevated\ntemperatures on tropical forest understory plants and soils, as well as other\necosystems, an infrared (IR) heater system was developed to provide in situ warming\nfor the Tropical Responses to Altered Climate Experiment (TRACE) in the Luquillo\nExperimental Forest in Puerto Rico. Three replicate heated 4-m-\ndiameter\nplots were\nwarmed to maintain a 4°C increase in understory vegetation compared to three unheated\ncontrol plots, as sensed by IR thermometers. The equipment was larger than\nany used previously and was subjected to challenges different from those of many\ntemperate ecosystem warming systems, including frequent power surges and outages,\nhigh humidity, heavy rains, hurricanes, saturated clayey soils, and steep slopes. The\nsystem was able to maintain the target 4.0°C increase in hourly average vegetation\ntemperatures to within ± 0.1°C. The vegetation was heterogeneous and on a 21°\nslope, which decreased uniformity of the warming treatment on the plots; yet, the\ngreen leaves were fairly uniformly warmed, and there was little difference among\n0–10 cm depth soil temperatures at the plot centers, edges, and midway between. Soil\ntemperatures at the 40–50 cm depth increased about 3°C compared to the controls\nafter a month of warming. As expected, the soil in the heated plots dried faster than\nthat of the control plots, but the average soil moisture remained adequate for the\nplants. The TRACE heating system produced an adequately uniform warming precisely\ncontrolled down to at least 50-cm\nsoil depth, thereby creating a treatment that allows\nfor assessing mechanistic responses of tropical plants and soil to warming, with applicability\nto other ecosystems. No physical obstacles to scaling the approach to taller\nvegetation (i.e., trees) and larger plots were observed.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3780","usgsCitation":"Kimball, B.A., Alonso-Rodriguez, A.M., Cavaleri, M.A., Reed, S.C., Gonzalez, G., and Wood, T.E., 2018, Infrared heater system for warming tropical forest understory plants and soils: Ecology and Evolution, v. 8, no. 4, p. 1932-1944, https://doi.org/10.1002/ece3.3780.","productDescription":"13 p.","startPage":"1932","endPage":"1944","ipdsId":"IP-092002","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3780","text":"Publisher Index Page"},{"id":355668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -65.7478094101,18.3093884924 ], [ -65.7478094101,18.3233015696 ], [ -65.7264590263,18.3233015696 ], [ -65.7264590263,18.3093884924 ], [ -65.7478094101,18.3093884924 ] ] ] } } ] }","volume":"8","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-15","publicationStatus":"PW","scienceBaseUri":"5b6fc4bbe4b0f5d57878eac4","contributors":{"authors":[{"text":"Kimball, Bruce A.","contributorId":206280,"corporation":false,"usgs":false,"family":"Kimball","given":"Bruce","email":"","middleInitial":"A.","affiliations":[{"id":37299,"text":"The Greenleaf Group","active":true,"usgs":false}],"preferred":false,"id":739963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alonso-Rodriguez, Aura M.","contributorId":206281,"corporation":false,"usgs":false,"family":"Alonso-Rodriguez","given":"Aura","email":"","middleInitial":"M.","affiliations":[{"id":37300,"text":"International Institute of Tropical Forestry, USDA Forest Service, Sabana Field Research Station, Luquillo, Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":739964,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cavaleri, Molly A.","contributorId":206282,"corporation":false,"usgs":false,"family":"Cavaleri","given":"Molly","email":"","middleInitial":"A.","affiliations":[{"id":34284,"text":"School of Forest Resources and Environmental Science, Michigan Technological University","active":true,"usgs":false}],"preferred":false,"id":739965,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":739962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gonzalez, Grizelle","contributorId":191117,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Grizelle","email":"","affiliations":[],"preferred":false,"id":739966,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wood, Tana E.","contributorId":202372,"corporation":false,"usgs":false,"family":"Wood","given":"Tana","email":"","middleInitial":"E.","affiliations":[{"id":36399,"text":"International Institute of Tropical Forestry, USDA Forest Service, Rio Piedras, PR","active":true,"usgs":false}],"preferred":false,"id":739967,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70194662,"text":"70194662 - 2018 - Effects of watershed and in-stream liming on macroinvertebrate communities in acidified tributaries to an Adirondack lake","interactions":[],"lastModifiedDate":"2018-01-05T12:47:53","indexId":"70194662","displayToPublicDate":"2018-01-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Effects of watershed and in-stream liming on macroinvertebrate communities in acidified tributaries to an Adirondack lake","docAbstract":"Liming techniques are being explored as a means to accelerate the recovery of aquatic biota from decades of acid deposition in many regions. The preservation or restoration of native sportfish populations has typically been the impetus for liming programs, and as such, less attention has been given to its effects on other biological assemblages such as macroinvertebrates. Furthermore, the differing effects of various lime application strategies such as in-stream and watershed applications are not well understood. In 2012, a program was initiated using in-stream and aerial (whole-watershed) liming to improve water quality and Brook Trout (Salvelinus fontinalis) recruitment in three acidified tributaries of a high-elevation Adirondack lake in New York State. Concurrently, macroinvertebrates were sampled annually between 2013 and 2016 at 3 treated sites and 3 untreated reference sites to assess the effects of each liming technique on this community. Despite improvements in water chemistry in all three limed streams, our results generally suggest that neither liming technique succeeded in improving the condition of macroinvertebrate communities. The watershed application caused an immediate and unsustained decrease in the density of macroinvertebrates and increase in the proportion of sensitive taxa. These changes were driven primarily by a one-year 71 percent reduction of the acid-tolerant Leuctra stoneflies and likely represent an initial chemistry shock from the lime application rather than a recovery response. The in-stream applications appeared to reduce the density of macroinvertebrates, particularly in one stream where undissolved lime covered the natural substrate. The close proximity of our study sites to the in-stream application points (50 and 1230 m) may partly explain these negative effects. Our results are consistent with prior studies of in-stream liming which indicate that this technique often fails to restore macroinvertebrate communities to a pre-acidification condition, especially at distances <1.5 km downstream of the lime application point. The inability of either liming technique to improve the condition of macroinvertebrate communities may be partly explained by the persistence of acidic episodes in all three streams. This suggests that in order to be effective, liming programs should attempt to eliminate even temporary episodes of unsuitable water chemistry rather than just meeting minimal criteria the majority of the time. Because watershed liming produced a more stable water chemistry regime than in-stream liming, this technique may have greater future potential to eliminate toxic episodes and accelerate the recovery of acid-impacted macroinvertebrate communities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2017.11.048","usgsCitation":"George, S.D., Baldigo, B.P., Lawrence, G.B., and Fuller, R.L., 2018, Effects of watershed and in-stream liming on macroinvertebrate communities in acidified tributaries to an Adirondack lake: Ecological Indicators, v. 85, no. February 2018, p. 1058-1067, https://doi.org/10.1016/j.ecolind.2017.11.048.","productDescription":"10 p.","startPage":"1058","endPage":"1067","ipdsId":"IP-080307","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":350330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Honnedaga Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.88006591796874,\n 43.50174856516506\n ],\n [\n -74.76848602294922,\n 43.50174856516506\n ],\n [\n -74.76848602294922,\n 43.55203173091177\n ],\n [\n -74.88006591796874,\n 43.55203173091177\n ],\n [\n -74.88006591796874,\n 43.50174856516506\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"February 2018","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fad1e4b06e28e9c22727","contributors":{"authors":[{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":724815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":724816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":724818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuller, Randall L.","contributorId":196969,"corporation":false,"usgs":false,"family":"Fuller","given":"Randall","email":"","middleInitial":"L.","affiliations":[{"id":35994,"text":"Colgate University, Hamilton, NY","active":true,"usgs":false}],"preferred":false,"id":724817,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198330,"text":"70198330 - 2018 - Nutrient dynamics in partially drained arctic thaw lakes","interactions":[],"lastModifiedDate":"2018-08-19T20:02:18","indexId":"70198330","displayToPublicDate":"2018-01-02T15:04:46","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Nutrient dynamics in partially drained arctic thaw lakes","docAbstract":"Thaw lakes are ubiquitous on arctic coastal plains (ACPs). While many thaw lakes have steep banks, stable water levels, and static surface areas, others only partially fill their basins and vary in area over the summer. These partially drained lakes (PDLs) are hydrologically connected to the wetlands immediately surrounding them. Heat and nutrient availability limit aquatic productivity on ACPs, and we hypothesized that shallow shorelines and greater hydrologic connectivity with the landscape should result in greater nutrient concentrations and biogeochemical cycling in PDLs. We tested this by monitoring water chemistry in lakes with varying levels of seasonal drainage in sandy and silty peaty lowland sites on the ACP of Alaska. One highly drained lake (N1) was significantly warmer than minimally drained lakes (minDLs) related to earlier ice off, reaching temperatures as high as 16 °C in June when minDLs still contained ice. Ammonia, total dissolved phosphorus, and dissolved organic carbon and nitrogen concentrations were higher in lakes with greater drainage, and concentrations in N1 rivaled those in the small, biologically productive ponds. Many PDLs displayed a midsummer decrease in nutrients consistent with assimilation by the aquatic ecosystem, and a late‐summer increase most likely related to runoff from drained lake margins following precipitation. N1 exported kilograms of ammonium and total dissolved phosphorus to the stream network over the summer. Given increased warming and drying in the arctic, the proportion of PDLs may be changing, which in turn may affect nutrient and organic matter availability in arctic lakes and export to downstream environments.
","language":"English","publisher":"Wiley","doi":"10.1002/2017JG004187","usgsCitation":"Koch, J.C., Fondell, T.F., Schmutz, J.A., and Laske, S.M., 2018, Nutrient dynamics in partially drained arctic thaw lakes: Journal of Geophysical Research: Biogeosciences, v. 123, no. 2, p. 440-452, https://doi.org/10.1002/2017JG004187.","productDescription":"13 p.","startPage":"440","endPage":"452","ipdsId":"IP-085121","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":469103,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jg004187","text":"Publisher Index Page"},{"id":438061,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BC3XHJ","text":"USGS data release","linkHelpText":"Arctic Coastal Plain Seasonal Lake Drainage, Water Temperature, and Solute and Nutrient Concentrations, 2011 - 2014"},{"id":356006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-02-17","publicationStatus":"PW","scienceBaseUri":"5b6fc4cbe4b0f5d57878eacc","contributors":{"authors":[{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":741071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fondell, Tom F. tfondell@usgs.gov","contributorId":3563,"corporation":false,"usgs":true,"family":"Fondell","given":"Tom","email":"tfondell@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":741072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":741073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":741074,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249334,"text":"70249334 - 2018 - Mapping forest change using stacked generalization: An ensemble approach","interactions":[],"lastModifiedDate":"2023-10-04T22:07:19.998682","indexId":"70249334","displayToPublicDate":"2018-01-01T16:49:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Mapping forest change using stacked generalization: An ensemble approach","docAbstract":"The ever-increasing volume and accessibility of remote sensing data has spawned many alternative approaches for mapping important environmental features and processes. For example, there are several viable but highly varied strategies for using time series of Landsat imagery to detect changes in forest cover. Performance among algorithms varies across complex natural systems, and it is reasonable to ask if aggregating the strengths of an ensemble of classifiers might result in increased overall accuracy. Relatively simple rules have been used in the past to aggregate classifications among remotely sensed maps (e.g. using majority predictions), and in other fields, empirical models have been used to create situationally specific algorithm weights. The latter process, called “stacked generalization” (or “stacking”), typically uses a parametric model for the fusion of algorithm outputs. We tested the performance of several leading forest disturbance detection algorithms against ensembles of the outputs of those same algorithms based upon stacking using both parametric and Random Forests-based fusion rules. Stacking using a Random Forests model cut omission and commission error rates in half in many cases in relation to individual change detection algorithms, and cut error rates by one quarter compared to more conventional parametric stacking. Stacking also offers two auxiliary benefits: alignment of outputs to the precise definitions built into a particular set of empirical calibration data; and, outputs which may be adjusted such that map class totals match independent estimates of change in each year. In general, ensemble predictions improve when new inputs are added that are both informative and uncorrelated with existing ensemble components. As increased use of cloud-based computing makes ensemble mapping methods more accessible, the most useful new algorithms may be those that specialize in providing spectral, temporal, or thematic information not already available through members of existing ensembles.
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Joseph","contributorId":330534,"corporation":false,"usgs":false,"family":"Hughes","given":"M.","email":"","middleInitial":"Joseph","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":885219,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kennedy, Robert E.","contributorId":196025,"corporation":false,"usgs":false,"family":"Kennedy","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":885220,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885221,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moisen, Gretchen G.","contributorId":15781,"corporation":false,"usgs":false,"family":"Moisen","given":"Gretchen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":885222,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Schroeder, Todd A. taschroeder@fs.fed.us","contributorId":190802,"corporation":false,"usgs":false,"family":"Schroeder","given":"Todd","email":"taschroeder@fs.fed.us","middleInitial":"A.","affiliations":[],"preferred":false,"id":885223,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stehman, Stephen V. 0000-0001-5234-2027","orcid":"https://orcid.org/0000-0001-5234-2027","contributorId":216812,"corporation":false,"usgs":false,"family":"Stehman","given":"Stephen","email":"","middleInitial":"V.","affiliations":[{"id":39524,"text":"College of Environmental Science and Forestry, State University of New York, Syracuse, NY 13210, USA","active":true,"usgs":false}],"preferred":false,"id":885224,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":885225,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Woodcock, Curtis E.","contributorId":294423,"corporation":false,"usgs":false,"family":"Woodcock","given":"Curtis","email":"","middleInitial":"E.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":885226,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Yang, Limin 0000-0002-2843-6944","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":313589,"corporation":false,"usgs":false,"family":"Yang","given":"Limin","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":885227,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zhu, Zhe","contributorId":260473,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhe","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":885228,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70199946,"text":"70199946 - 2018 - Advancements in hydrochemistry mapping: methods and application to groundwater arsenic and iron concentrations in Varanasi, Uttar Pradesh, India","interactions":[],"lastModifiedDate":"2018-10-05T14:30:40","indexId":"70199946","displayToPublicDate":"2018-01-01T14:30:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3478,"text":"Stochastic Environmental Research and Risk Assessment","active":true,"publicationSubtype":{"id":10}},"title":"Advancements in hydrochemistry mapping: methods and application to groundwater arsenic and iron concentrations in Varanasi, Uttar Pradesh, India","docAbstract":"The area east of Varanasi is one of numerous places along the watershed of the Ganges River with groundwater concentrations of arsenic surpassing the maximum value of 10 parts per billion (ppb) recommended by the World Health Organization in drinking water. Here we apply geostatistics and compositional data analysis for the mapping of arsenic and iron to help in understanding the conditions leading to the occurrence of elevated level of arsenic in groundwater. The methodology allows for displaying concentrations of arsenic and iron as maps consistent with the limited information from 95 water wells across an area of approximately 210 km2; visualization of the uncertainty associated with the sampling; and summary of the findings in the form of probability maps. For thousands of years, Varanasi has been on the erosional side in a meander of the river that is free of arsenic values above 10 ppb. Maps reveal two anomalies of high arsenic concentrations on the depositional side of the valley, which has started seeing urban development. The methodology using geostatistics combined with compositional data analysis is completely general, so this study could be used as a prototype for hydrochemistry mapping in other areas.
","language":"English","publisher":"Springer","doi":"10.1007/s00477-017-1390-3","usgsCitation":"Olea, R., Raju, N.J., Egozcue, J.J., Pawlowsky-Glahn, V., and Singh, S., 2018, Advancements in hydrochemistry mapping: methods and application to groundwater arsenic and iron concentrations in Varanasi, Uttar Pradesh, India: Stochastic Environmental Research and Risk Assessment, v. 32, no. 1, p. 241-259, https://doi.org/10.1007/s00477-017-1390-3.","productDescription":"19 p.","startPage":"241","endPage":"259","ipdsId":"IP-102331","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469109,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10256/14599","text":"External Repository"},{"id":358185,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","state":"Uttar Pradesh","city":"Varanasi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 82.94094085693358,\n 25.22171429348812\n ],\n [\n 83.16032409667969,\n 25.22171429348812\n ],\n [\n 83.16032409667969,\n 25.353644304321104\n ],\n [\n 82.94094085693358,\n 25.353644304321104\n ],\n [\n 82.94094085693358,\n 25.22171429348812\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-13","publicationStatus":"PW","scienceBaseUri":"5bc0304de4b0fc368eb539ee","contributors":{"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":47873,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":747416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Raju, N. Janardhana","contributorId":208504,"corporation":false,"usgs":false,"family":"Raju","given":"N.","email":"","middleInitial":"Janardhana","affiliations":[],"preferred":false,"id":747476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Egozcue, Juan J.","contributorId":208010,"corporation":false,"usgs":false,"family":"Egozcue","given":"Juan","email":"","middleInitial":"J.","affiliations":[{"id":37677,"text":"Dept. Civil and Environmental Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain","active":true,"usgs":false}],"preferred":false,"id":747477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pawlowsky-Glahn, Vera","contributorId":208011,"corporation":false,"usgs":false,"family":"Pawlowsky-Glahn","given":"Vera","email":"","affiliations":[{"id":37678,"text":"Dept. Informatics, Applied Matematics and Statistics, Universitat de Girona, Spain","active":true,"usgs":false}],"preferred":false,"id":747478,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singh, Shubhra","contributorId":208505,"corporation":false,"usgs":false,"family":"Singh","given":"Shubhra","email":"","affiliations":[],"preferred":false,"id":747479,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228293,"text":"70228293 - 2018 - Dietary bioprocessed soybean meal does not affect the growth of exercised juvenile rainbow trout (Oncorhynchus mykiss)","interactions":[],"lastModifiedDate":"2022-02-08T17:00:03.049296","indexId":"70228293","displayToPublicDate":"2018-01-01T10:59:27","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10102,"text":"Journal of Animal Research and Nutrition","onlineIssn":"2572-5459","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Dietary bioprocessed soybean meal does not affect the growth of exercised juvenile rainbow trout (Oncorhynchus mykiss)","title":"Dietary bioprocessed soybean meal does not affect the growth of exercised juvenile rainbow trout (Oncorhynchus mykiss)","docAbstract":"Context: This 88-day experiment evaluated the rearing performance of juvenile rainbow trout (Oncorhynchus mykiss) fed one of three isonitrogenous and isocaloric diets and reared at velocities of either 2.3 or 18.7 cm s-1.
Objective: Evaluate the effects of diet and exercise during rainbow trout rearing.
Design: Fishmeal was the primary protein source for one diet, with bioprocessed soybean meal (BSM) replacing either 60 or 85% of the fishmeal in the other two diets.
Setting: This study was performed at Cleghorn Springs State Fish Hatchery in Rapid City, South Dakota, USA.
Results: At the end of the experiment there were no significant differences among the dietary treatments in gain, percent gain, specific growth rate (SGR), or percent mortality. However, fish fed the fishmeal-based diet ate significantly more, experienced a significantly higher feed conversion ratio (FCR), and had a significantly higher hepatosomatic index than the fish fed the 85% BSM diet. Intestinal histology was not affected by the inclusion of BSM. Fish reared at 2.3 cm/s-1 had significantly lower FCRs, gain, percent gain, and SGR than the fish reared at 18.7 cm/ s-1. There was a significant interaction in food consumed between diet and velocity, but no other significant interactions between the dietary and exercise treatments were observed.
Conclusion: Based on these results, BSM can replace at least 85% of the fishmeal in juvenile rainbow trout, even if the fish are exercised.
","language":"English","publisher":"iMedPub","doi":"10.21767/2572-5459.100050","usgsCitation":"Voorhees, J.M., Barnes, M., Chipps, S.R., and Browne, M., 2018, Dietary bioprocessed soybean meal does not affect the growth of exercised juvenile rainbow trout (Oncorhynchus mykiss): Journal of Animal Research and Nutrition, v. 3, no. 2, p. 1-13, https://doi.org/10.21767/2572-5459.100050.","productDescription":"6, 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-097690","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469112,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.21767/2572-5459.100050","text":"Publisher Index Page"},{"id":395630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","city":"Rapid City","otherGeospatial":"Cleghorn Springs State Fish Hatchery","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.304443359375,\n 44.05554907062273\n ],\n [\n -103.28588247299194,\n 44.05554907062273\n ],\n [\n -103.28588247299194,\n 44.06245723037078\n ],\n [\n -103.304443359375,\n 44.06245723037078\n ],\n [\n -103.304443359375,\n 44.05554907062273\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Voorhees, Jill M.","contributorId":275085,"corporation":false,"usgs":false,"family":"Voorhees","given":"Jill","email":"","middleInitial":"M.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":833624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnes, Michael","contributorId":275086,"corporation":false,"usgs":false,"family":"Barnes","given":"Michael","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":833625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833623,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Browne, Michael","contributorId":178752,"corporation":false,"usgs":false,"family":"Browne","given":"Michael","email":"","affiliations":[],"preferred":false,"id":833626,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198749,"text":"70198749 - 2018 - Quantifying uncertainty and tradeoffs in resilience assessments","interactions":[],"lastModifiedDate":"2018-08-24T12:20:22","indexId":"70198749","displayToPublicDate":"2018-01-01T09:32:03","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying uncertainty and tradeoffs in resilience assessments","docAbstract":"Several frameworks have been developed to assess the resilience of social-ecological systems, but most require substantial data inputs, time, and technical expertise. Stakeholders and practitioners often lack the resources for such intensive efforts. Furthermore, most end with problem framing and fail to explicitly address trade-offs and uncertainty. To remedy this gap, we developed a rapid survey assessment that compares the relative resilience of social-ecological systems with respect to a number of resilience properties. This approach generates large amounts of information relative to stakeholder inputs. We targeted four stakeholder categories: government (policy, regulation, management), end users (farmers, ranchers, landowners, industry), agency/public science (research, university, extension), and NGOs (environmental, citizen, social justice) in four North American watersheds, to assess social-ecological resilience through surveys. Conceptually, social-ecological systems are comprised of components ranging from strictly human to strictly ecological, but that relate directly or indirectly to one another. They have soft boundaries and several important dimensions or axes that together describe the nature of social-ecological interactions, e.g., variability, diversity, modularity, slow variables, feedbacks, capital, innovation, redundancy, and ecosystem services. There is no absolute measure of resilience, so our design takes advantage of cross-watershed comparisons and therefore focuses on relative resilience. Our approach quantifies and compares the relative resilience across watershed systems and potential trade-offs among different aspects of the social-ecological system, e.g., between social, economic, and ecological contributions. This approach permits explicit assessment of several types of uncertainty (e.g., self-assigned uncertainty for stakeholders; uncertainty across respondents, watersheds, and subsystems), and subjectivity in perceptions of resilience among key actors and decision makers and provides an efficient way to develop the mental models that inform our stakeholders and stakeholder categories.
","language":"English","publisher":"Ecology and Society","doi":"10.5751/ES-09920-230103","usgsCitation":"Allen, C.R., Birge, H.E., Angeler, D.G., Arnold, C.A., Chaffin, B.C., DeCaro, D.A., Garmestani, A.S., and Gunderson, L., 2018, Quantifying uncertainty and tradeoffs in resilience assessments: Ecology and Society, v. 1, no. 3, Article 3; 23 p., https://doi.org/10.5751/ES-09920-230103.","productDescription":"Article 3; 23 p.","ipdsId":"IP-089079","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-09920-230103","text":"Publisher Index Page"},{"id":356614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a317e4b0702d0e84302a","contributors":{"authors":[{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":742844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birge, Hannah E.","contributorId":166737,"corporation":false,"usgs":false,"family":"Birge","given":"Hannah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":743039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angeler, David G.","contributorId":205240,"corporation":false,"usgs":false,"family":"Angeler","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":37065,"text":"Swedish University of Agricultural Sciences, Uppsala, Sweden","active":true,"usgs":false}],"preferred":false,"id":743040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arnold, Craig Anthony","contributorId":189230,"corporation":false,"usgs":false,"family":"Arnold","given":"Craig","email":"","middleInitial":"Anthony","affiliations":[],"preferred":false,"id":743041,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chaffin, Brian C.","contributorId":189131,"corporation":false,"usgs":false,"family":"Chaffin","given":"Brian","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":743042,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeCaro, Daniel A.","contributorId":198374,"corporation":false,"usgs":false,"family":"DeCaro","given":"Daniel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":743043,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garmestani, Ahjond S.","contributorId":77285,"corporation":false,"usgs":true,"family":"Garmestani","given":"Ahjond","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":743044,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gunderson, Lance","contributorId":30797,"corporation":false,"usgs":true,"family":"Gunderson","given":"Lance","affiliations":[],"preferred":false,"id":743045,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70195089,"text":"70195089 - 2018 - Using colony monitoring devices to evaluate the impacts of land use and nutritional value of forage on honey bee health","interactions":[],"lastModifiedDate":"2018-02-08T12:55:34","indexId":"70195089","displayToPublicDate":"2018-01-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5622,"text":"Agriculture","active":true,"publicationSubtype":{"id":10}},"title":"Using colony monitoring devices to evaluate the impacts of land use and nutritional value of forage on honey bee health","docAbstract":"Colony monitoring devices used to track and assess the health status of honey bees are becoming more widely available and used by both beekeepers and researchers. These devices monitor parameters relevant to colony health at frequent intervals, often approximating real time. The fine-scale record of hive condition can be further related to static or dynamic features of the landscape, such as weather, climate, colony density, land use, pesticide use, vegetation class, and forage quality. In this study, we fit commercial honey bee colonies in two apiaries with pollen traps and digital scales to monitor floral resource use, pollen quality, and honey production. One apiary was situated in low-intensity agriculture; the other in high-intensity agriculture. Pollen traps were open for 72 h every two weeks while scales recorded weight every 15 min throughout the growing season. From collected pollen, we determined forage quantity per day, species identity using DNA sequencing, pesticide residues, amino acid content, and total protein content. From scales, we determined the accumulated hive weight change over the growing season, relating to honey production and final colony weight going into winter. Hive scales may also be used to identify the occurrence of environmental pollen and nectar dearth, and track phenological changes in plant communities. We provide comparisons of device-derived data between two apiaries over the growing season and discuss the potential for employing apiary monitoring devices to infer colony health in the context of divergent agricultural land use conditions.
","language":"English","publisher":"MDPI","doi":"10.3390/agriculture8010002","usgsCitation":"Smart, M., Otto, C., Cornman, R.S., and Iwanowicz, D.D., 2018, Using colony monitoring devices to evaluate the impacts of land use and nutritional value of forage on honey bee health: Agriculture, v. 81, no. 1, p. 1-14, https://doi.org/10.3390/agriculture8010002.","productDescription":"Article 2; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-091990","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469116,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/agriculture8010002","text":"Publisher Index Page"},{"id":438062,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72V2F4S","text":"USGS data release","linkHelpText":"Using colony monitoring devices to evaluate the impacts of land use and forage quality on honey bee health datasets"},{"id":351351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-25","publicationStatus":"PW","scienceBaseUri":"5a7d6ffee4b00f54eb2441b4","contributors":{"authors":[{"text":"Smart, Matthew 0000-0003-0711-3035 msmart@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-3035","contributorId":174424,"corporation":false,"usgs":true,"family":"Smart","given":"Matthew","email":"msmart@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":726882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":726883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":726885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":726884,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195970,"text":"70195970 - 2018 - Biogenic coal-to-methane conversion efficiency decreases after repeated organic amendment","interactions":[],"lastModifiedDate":"2018-03-19T11:03:07","indexId":"70195970","displayToPublicDate":"2018-01-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1506,"text":"Energy & Fuels","active":true,"publicationSubtype":{"id":10}},"title":"Biogenic coal-to-methane conversion efficiency decreases after repeated organic amendment","docAbstract":"Addition of organic amendments to coal-containing systems can increase the rate and extent of biogenic methane production for 60–80 days before production slows or stops. Understanding the effect of repeated amendment additions on the rate and extent of enhanced coal-dependent methane production is important if biological coal-to-methane conversion is to be enhanced on a commercial scale. Microalgal biomass was added at a concentration of 0.1 g/L to microcosms with and without coal on days 0, 76, and 117. Rates of methane production were enhanced after the initial amendment but coal-containing treatments produced successively decreasing amounts of methane with each amendment. During the first amendment period, 113% of carbon added as amendment was recovered as methane, whereas in the second and third amendment periods, 39% and 32% of carbon added as amendment was recovered as methane, respectively. Additionally, algae-amended coal treatments produced ∼38% more methane than unamended coal treatments and ∼180% more methane than amended coal-free treatments after one amendment. However, a second amendment addition resulted in only an ∼25% increase in methane production for coal versus noncoal treatments and a third amendment addition resulted in similar methane production in both coal and noncoal treatments. Successive amendment additions appeared to result in a shift from coal-to-methane conversion to amendment-to-methane conversion. The reported results indicate that a better understanding is needed of the potential impacts and efficiencies of repeated stimulation for enhanced coal-to-methane conversion.
","language":"English","publisher":"ACS","doi":"10.1021/acs.energyfuels.7b03426","usgsCitation":"Davis, K.J., Barnhart, E.P., Fields, M.W., and Gerlach, R., 2018, Biogenic coal-to-methane conversion efficiency decreases after repeated organic amendment: Energy & Fuels, v. 32, no. 3, p. 2916-2925, https://doi.org/10.1021/acs.energyfuels.7b03426.","productDescription":"10 p.","startPage":"2916","endPage":"2925","ipdsId":"IP-093109","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":469130,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.montana.edu/xmlui/handle/1/14992","text":"External Repository"},{"id":352382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-30","publicationStatus":"PW","scienceBaseUri":"5afee753e4b0da30c1bfc255","contributors":{"authors":[{"text":"Davis, Katherine J.","contributorId":203246,"corporation":false,"usgs":false,"family":"Davis","given":"Katherine","email":"","middleInitial":"J.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":730741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393 epbarnhart@usgs.gov","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":5385,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","email":"epbarnhart@usgs.gov","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fields, Matthew W.","contributorId":172391,"corporation":false,"usgs":false,"family":"Fields","given":"Matthew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":730742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerlach, Robin","contributorId":203247,"corporation":false,"usgs":false,"family":"Gerlach","given":"Robin","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":730743,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196279,"text":"70196279 - 2018 - Environmental and ecological conditions at Arctic breeding sites have limited effects on true survival rates of adult shorebirds","interactions":[],"lastModifiedDate":"2018-03-30T10:26:12","indexId":"70196279","displayToPublicDate":"2018-01-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Environmental and ecological conditions at Arctic breeding sites have limited effects on true survival rates of adult shorebirds","docAbstract":"Many Arctic shorebird populations are declining, and quantifying adult survival and the effects of anthropogenic factors is a crucial step toward a better understanding of population dynamics. We used a recently developed, spatially explicit Cormack–Jolly–Seber model in a Bayesian framework to obtain broad-scale estimates of true annual survival rates for 6 species of shorebirds at 9 breeding sites across the North American Arctic in 2010–2014. We tested for effects of environmental and ecological variables, study site, nest fate, and sex on annual survival rates of each species in the spatially explicit framework, which allowed us to distinguish between effects of variables on site fidelity versus true survival. Our spatially explicit analysis produced estimates of true survival rates that were substantially higher than previously published estimates of apparent survival for most species, ranging from S = 0.72 to 0.98 across 5 species. However, survival was lower for the arcticolasubspecies of Dunlin (Calidris alpina arcticola; S = 0.54), our only study taxon that migrates through the East Asian–Australasian Flyway. Like other species that use that flyway, arcticola Dunlin could be experiencing unsustainably low survival rates as a result of loss of migratory stopover habitat. Survival rates of our study species were not affected by timing of snowmelt or summer temperature, and only 2 species showed minor variation among study sites. Furthermore, although previous reproductive success, predator abundance, and the availability of alternative prey each affected survival of one species, no factors broadly affected survival across species. Overall, our findings of few effects of environmental or ecological variables suggest that annual survival rates of adult shorebirds are generally robust to conditions at Arctic breeding sites. Instead, conditions at migratory stopovers or overwintering sites might be driving adult survival rates and should be the focus of future studies.
","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-17-107.1","usgsCitation":"Weiser, E., Lanctot, R.B., Brown, S.C., Gates, H., Bentzen, R., Bety, J., Boldenow, M.L., English, W.B., Franks, S., Koloski, L., Kwon, E., Lamarre, J., Lank, D.B., Liebezeit, J.R., McKinnon, L., Nol, E., Rausch, J., Saalfeld, S., Senner, N.R., Ward, D.H., Wood, P., and Sandercock, B.K., 2018, Environmental and ecological conditions at Arctic breeding sites have limited effects on true survival rates of adult shorebirds: The Auk, v. 135, no. 1, p. 29-43, https://doi.org/10.1642/AUK-17-107.1.","productDescription":"15 p.","startPage":"29","endPage":"43","ipdsId":"IP-087067","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469120,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1642/auk-17-107.1","text":"Publisher Index Page"},{"id":352988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee753e4b0da30c1bfc24f","contributors":{"authors":[{"text":"Weiser, Emily L.","contributorId":171678,"corporation":false,"usgs":false,"family":"Weiser","given":"Emily L.","affiliations":[],"preferred":false,"id":732054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lanctot, Richard B.","contributorId":31894,"corporation":false,"usgs":true,"family":"Lanctot","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":7029,"text":"Queen's University, Kingston, Ontario, Canada","active":true,"usgs":false},{"id":17786,"text":"Carleton University","active":true,"usgs":false},{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false},{"id":135,"text":"Biological Resources Division","active":false,"usgs":true}],"preferred":false,"id":732055,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Stephen C.","contributorId":38457,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":732056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gates, H. River","contributorId":84256,"corporation":false,"usgs":true,"family":"Gates","given":"H. River","affiliations":[],"preferred":false,"id":732057,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bentzen, Rebecca L.","contributorId":62070,"corporation":false,"usgs":true,"family":"Bentzen","given":"Rebecca L.","affiliations":[],"preferred":false,"id":732058,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bety, Joel","contributorId":203661,"corporation":false,"usgs":false,"family":"Bety","given":"Joel","email":"","affiliations":[{"id":36676,"text":"Université du Québec à Rimouski","active":true,"usgs":false}],"preferred":false,"id":732059,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boldenow, Megan L.","contributorId":203662,"corporation":false,"usgs":false,"family":"Boldenow","given":"Megan","email":"","middleInitial":"L.","affiliations":[{"id":36677,"text":"Department of Biology and Wildlife, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":732060,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"English, Willow B.","contributorId":169341,"corporation":false,"usgs":false,"family":"English","given":"Willow","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":732061,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Franks, Samantha E.","contributorId":92979,"corporation":false,"usgs":true,"family":"Franks","given":"Samantha E.","affiliations":[],"preferred":false,"id":732062,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Koloski, Laura","contributorId":203665,"corporation":false,"usgs":false,"family":"Koloski","given":"Laura","email":"","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":732063,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kwon, Eunbi","contributorId":169349,"corporation":false,"usgs":false,"family":"Kwon","given":"Eunbi","email":"","affiliations":[],"preferred":false,"id":732064,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lamarre, Jean-François","contributorId":169350,"corporation":false,"usgs":false,"family":"Lamarre","given":"Jean-François","affiliations":[],"preferred":false,"id":732065,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lank, David B.","contributorId":42533,"corporation":false,"usgs":false,"family":"Lank","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":29801,"text":"Department of Biological Sciences, Simon Fraser University, Burnaby, BC","active":true,"usgs":false}],"preferred":false,"id":732066,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Liebezeit, Joseph R.","contributorId":127693,"corporation":false,"usgs":false,"family":"Liebezeit","given":"Joseph","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":732067,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"McKinnon, Laura","contributorId":169353,"corporation":false,"usgs":false,"family":"McKinnon","given":"Laura","email":"","affiliations":[],"preferred":false,"id":732068,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Nol, Erica","contributorId":38459,"corporation":false,"usgs":true,"family":"Nol","given":"Erica","affiliations":[],"preferred":false,"id":732069,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Rausch, Jennie","contributorId":103938,"corporation":false,"usgs":true,"family":"Rausch","given":"Jennie","affiliations":[],"preferred":false,"id":732070,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Saalfeld, Sarah T.","contributorId":41721,"corporation":false,"usgs":true,"family":"Saalfeld","given":"Sarah T.","affiliations":[],"preferred":false,"id":732071,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Senner, Nathan R.","contributorId":140465,"corporation":false,"usgs":false,"family":"Senner","given":"Nathan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":732072,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":732053,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Wood, Paul F.","contributorId":203707,"corporation":false,"usgs":false,"family":"Wood","given":"Paul F.","affiliations":[],"preferred":false,"id":732135,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Sandercock, Brett K.","contributorId":95816,"corporation":false,"usgs":true,"family":"Sandercock","given":"Brett","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":732136,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70195094,"text":"70195094 - 2018 - Acute and chronic toxicity of aluminum to a unionid mussel (Lampsilis siliquoidea) and an amphipod (Hyalella azteca) in water‐only exposures","interactions":[],"lastModifiedDate":"2018-03-29T16:53:52","indexId":"70195094","displayToPublicDate":"2018-01-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Acute and chronic toxicity of aluminum to a unionid mussel (Lampsilis siliquoidea) and an amphipod (Hyalella azteca) in water‐only exposures","title":"Acute and chronic toxicity of aluminum to a unionid mussel (Lampsilis siliquoidea) and an amphipod (Hyalella azteca) in water‐only exposures","docAbstract":"The US Environmental Protection Agency (USEPA) is reviewing the protectiveness of the national ambient water quality criteria (WQC) for aluminum (Al) and compiling a toxicity data set to update the WQC. Freshwater mussels are one of the most imperiled groups of animals in the world, but little is known about their sensitivity to Al. The objective of the present study was to evaluate acute 96‐h and chronic 28‐d toxicity of Al to a unionid mussel (Lampsilis siliquoidea) and a commonly tested amphipod (Hyalella azteca) at a pH of 6 and water hardness of 100 mg/L as CaCO3. The acute 50% effect concentration (EC50) for survival of both species was >6200 μg total Al/L. The EC50 was greater than all acute values in the USEPA acute Al data set for freshwater species at a pH range of 5.0 to <6.5 and hardness normalized to 100 mg/L, indicating that the mussel and amphipod were insensitive to Al in acute exposures. The chronic 20% effect concentration (EC20) based on dry weight was 163 μg total Al/L for the mussel and 409 μg total Al/L for the amphipod. Addition of the EC20s to the USEPA chronic Al data set for pH 5.0 to <6.5 would rank the mussel (L. siliquoidea) as the fourth most sensitive species and the amphipod (H. azteca) as the fifth most sensitive species, indicating the 2 species were sensitive to Al in chronic exposures. The USEPA‐proposed acute and chronic WQC for Al would adequately protect the mussel and amphipod tested; however, inclusion of the chronic data from the present study and recalculation of the chronic criterion would likely lower the proposed chronic criterion.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.3850","usgsCitation":"Wang, N., Ivey, C.D., Brunson, E., Cleveland, D.M., Ingersoll, C.G., Stubblefield, W., and Cardwell, A.S., 2018, Acute and chronic toxicity of aluminum to a unionid mussel (Lampsilis siliquoidea) and an amphipod (Hyalella azteca) in water‐only exposures: Environmental Toxicology and Chemistry, v. 37, no. 1, p. 61-69, https://doi.org/10.1002/etc.3850.","productDescription":"9 p.","startPage":"61","endPage":"69","ipdsId":"IP-082948","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":352978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-05","publicationStatus":"PW","scienceBaseUri":"5afee754e4b0da30c1bfc265","contributors":{"authors":[{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":726904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":726905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brunson, Eric L. 0000-0001-6624-0902 elbrunson@usgs.gov","orcid":"https://orcid.org/0000-0001-6624-0902","contributorId":3282,"corporation":false,"usgs":true,"family":"Brunson","given":"Eric L.","email":"elbrunson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":726906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":726907,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":726910,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stubblefield, William A.","contributorId":201762,"corporation":false,"usgs":false,"family":"Stubblefield","given":"William A.","affiliations":[{"id":25665,"text":"Oregon State University, Corvallis, Oregon","active":true,"usgs":false}],"preferred":false,"id":726908,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cardwell, Allison S.","contributorId":201763,"corporation":false,"usgs":false,"family":"Cardwell","given":"Allison","email":"","middleInitial":"S.","affiliations":[{"id":25665,"text":"Oregon State University, Corvallis, Oregon","active":true,"usgs":false}],"preferred":false,"id":726909,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196359,"text":"70196359 - 2018 - The nitrogen window for arctic herbivores: plant phenology and protein gain of migratory caribou (Rangifer tarandus)","interactions":[],"lastModifiedDate":"2018-04-03T14:12:29","indexId":"70196359","displayToPublicDate":"2018-01-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The nitrogen window for arctic herbivores: plant phenology and protein gain of migratory caribou (Rangifer tarandus)","title":"The nitrogen window for arctic herbivores: plant phenology and protein gain of migratory caribou (Rangifer tarandus)","docAbstract":"Terrestrial plants are often limited by nitrogen (N) in arctic systems, but constraints of N supply on herbivores are typically considered secondary to those of energy. We tested the hypothesis that forage N is more limiting than energy for arctic caribou by collecting key forages (three species of graminoids, three species of woody browse, and one genus of forb) over three summers in the migratory range of the Central Arctic Herd in Alaska from the Brooks Range to the Coastal Plain on the Arctic Ocean. We combined in vitro digestion and detergent extraction to measure fiber, digestible energy, and usable fractions of N in forages (n = 771). Digestible energy content fell below the minimum threshold value of 9 kJ/g for one single forage group: graminoids, and only beyond 64–75 d from parturition (6 June), whereas all forages fell below the minimum threshold value for digestible N (1% of dry matter) before female caribou would have weaned their calves at 100 d from parturition. The window for digestible N was shortest for browse, which fell below 1% at 30–41 d from parturition, whereas digestible N contents of graminoids were adequate until 46–57 d from parturition. The low quality of browse as a source of N was also apparent from concentrations of available N (i.e., the N not bound to fiber) that were <1% at 72–80 d from parturition. The Coastal Plain may be favored by female caribou because available and digestible concentrations of N are not only greater than those on the Brooks Range, the window of usable N on the Coastal Plain extends the period of protein gain for females and their calves by 17 d. Conversely, inland areas with greater biomass and densities of digestible N than the Coastal Plain may be more favorable for large male caribou that begin gaining protein from spring to breed in autumn. Our study provides evidence that phenological windows for protein gain in caribou are both spatially and temporally dynamic and likely to affect the distribution and growth of the population.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2073","usgsCitation":"Barboza, P.S., Van Someren, L.L., Gustine, D.D., and Bret-Harte, M., 2018, The nitrogen window for arctic herbivores: plant phenology and protein gain of migratory caribou (Rangifer tarandus): Ecosphere, v. 9, no. 1, e02073, https://doi.org/10.1002/ecs2.2073.","productDescription":"e02073","ipdsId":"IP-088849","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469126,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2073","text":"Publisher Index Page"},{"id":353114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-05","publicationStatus":"PW","scienceBaseUri":"5afee753e4b0da30c1bfc24b","contributors":{"authors":[{"text":"Barboza, Perry S.","contributorId":36454,"corporation":false,"usgs":false,"family":"Barboza","given":"Perry","email":"","middleInitial":"S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":732570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Someren, Lindsay L.","contributorId":203877,"corporation":false,"usgs":false,"family":"Van Someren","given":"Lindsay","email":"","middleInitial":"L.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":732571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gustine, David D. dgustine@usgs.gov","contributorId":3776,"corporation":false,"usgs":true,"family":"Gustine","given":"David","email":"dgustine@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":732572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bret-Harte, M. Syndonia","contributorId":201219,"corporation":false,"usgs":false,"family":"Bret-Harte","given":"M. Syndonia","affiliations":[],"preferred":false,"id":732573,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}