{"pageNumber":"724","pageRowStart":"18075","pageSize":"25","recordCount":40783,"records":[{"id":70032471,"text":"70032471 - 2012 - Analogues of doxanthrine reveal differences between the dopamine D1 receptor binding properties of chromanoisoquinolines and hexahydrobenzo[a]phenanthridines","interactions":[],"lastModifiedDate":"2020-12-01T17:46:12.579975","indexId":"70032471","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1592,"text":"European Journal of Medicinal Chemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Analogues of doxanthrine reveal differences between the dopamine D<sub>1</sub> receptor binding properties of chromanoisoquinolines and hexahydrobenzo[a]phenanthridines","title":"Analogues of doxanthrine reveal differences between the dopamine D1 receptor binding properties of chromanoisoquinolines and hexahydrobenzo[a]phenanthridines","docAbstract":"<p><span>Efforts to develop selective&nbsp;agonists&nbsp;for&nbsp;dopamine&nbsp;D</span><sub>1</sub><span>-like receptors led to the discovery of dihydrexidine and doxanthrine, two bioisosteric β-phenyldopamine-type full agonist ligands that display selectivity and potency at D</span><sub>1</sub><span>-like receptors. We report herein an improved methodology for the synthesis of substituted chromanoisoquinolines (doxanthrine derivatives) and the evaluation of several new compounds for their ability to bind to D</span><sub>1</sub><span>- and D</span><sub>2</sub><span>-like receptors. Identical pendant phenyl ring substitutions on the dihydrexidine and doxanthrine templates surprisingly led to different effects on D</span><sub>1</sub><span>-like receptor binding, suggesting important differences between the interactions of these ligands with the D</span><sub>1</sub><span>&nbsp;receptor. We propose, based on the biological results and&nbsp;molecular modeling&nbsp;studies, that slight conformational differences between the&nbsp;tetralin&nbsp;and chroman-based compounds lead to a shift in the location of the pendant ring substituents within the receptor.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejmech.2011.11.039","issn":"02235234","usgsCitation":"Cueva, J., Chemel, B.R., Juncosa, J., Lill, M., Watts, V., and Nichols, D., 2012, Analogues of doxanthrine reveal differences between the dopamine D1 receptor binding properties of chromanoisoquinolines and hexahydrobenzo[a]phenanthridines: European Journal of Medicinal Chemistry, v. 48, p. 97-107, https://doi.org/10.1016/j.ejmech.2011.11.039.","productDescription":"11 p.","startPage":"97","endPage":"107","costCenters":[],"links":[{"id":474649,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3264828","text":"External Repository"},{"id":241753,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214066,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ejmech.2011.11.039"}],"volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059eacce4b0c8380cd48a6a","contributors":{"authors":[{"text":"Cueva, J.P.","contributorId":93781,"corporation":false,"usgs":true,"family":"Cueva","given":"J.P.","email":"","affiliations":[],"preferred":false,"id":436359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chemel, Benjamin R.","contributorId":213894,"corporation":false,"usgs":false,"family":"Chemel","given":"Benjamin","email":"","middleInitial":"R.","affiliations":[{"id":38924,"text":"Northern Rockies Conservation Cooperative","active":true,"usgs":false}],"preferred":false,"id":436355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Juncosa, J.I. Jr.","contributorId":89023,"corporation":false,"usgs":true,"family":"Juncosa","given":"J.I.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":436358,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lill, M.A.","contributorId":84224,"corporation":false,"usgs":true,"family":"Lill","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":436357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Watts, V.J.","contributorId":73473,"corporation":false,"usgs":true,"family":"Watts","given":"V.J.","email":"","affiliations":[],"preferred":false,"id":436356,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nichols, D.E.","contributorId":14268,"corporation":false,"usgs":true,"family":"Nichols","given":"D.E.","affiliations":[],"preferred":false,"id":436354,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70032360,"text":"70032360 - 2012 - Evaluation of MODFLOW-LGR in connection with a synthetic regional-scale model","interactions":[],"lastModifiedDate":"2020-12-02T18:21:27.250191","indexId":"70032360","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of MODFLOW-LGR in connection with a synthetic regional-scale model","docAbstract":"<p><span>This work studies costs and benefits of utilizing local‐grid refinement (LGR) as implemented in MODFLOW‐LGR to simulate groundwater flow in a buried tunnel valley interacting with a regional aquifer. Two alternative LGR methods were used: the shared‐node (SN) method and the ghost‐node (GN) method. To conserve flows the SN method requires correction of sources and sinks in cells at the refined/coarse‐grid interface. We found that the optimal correction method is case dependent and difficult to identify in practice. However, the results showed little difference and suggest that identifying the optimal method was of minor importance in our case. The GN method does not require corrections at the models' interface, and it uses a simpler head interpolation scheme than the SN method. The simpler scheme is faster but less accurate so that more iterations may be necessary. However, the GN method solved our flow problem more efficiently than the SN method. The MODFLOW‐LGR results were compared with the results obtained using a globally coarse (GC) grid. The LGR simulations required one to two orders of magnitude longer run times than the GC model. However, the improvements of the numerical resolution around the buried valley substantially increased the accuracy of simulated heads and flows compared with the GC simulation. Accuracy further increased locally around the valley flanks when improving the geological resolution using the refined grid. Finally, comparing MODFLOW‐LGR simulation with a globally refined (GR) grid showed that the refinement proportion of the model should not exceed 10% to 15% in order to secure method efficiency.</span></p>","language":"English","publisher":"National Ground Water Association","doi":"10.1111/j.1745-6584.2011.00826.x","issn":"0017467X","usgsCitation":"Vilhelmsen, T., Christensen, S., and Mehl, S.W., 2012, Evaluation of MODFLOW-LGR in connection with a synthetic regional-scale model: Ground Water, v. 50, no. 1, p. 118-132, https://doi.org/10.1111/j.1745-6584.2011.00826.x.","productDescription":"15 p.","startPage":"118","endPage":"132","costCenters":[],"links":[{"id":241575,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213905,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2011.00826.x"}],"volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-05-27","publicationStatus":"PW","scienceBaseUri":"505a0c18e4b0c8380cd52a27","contributors":{"authors":[{"text":"Vilhelmsen, T.N.","contributorId":54024,"corporation":false,"usgs":true,"family":"Vilhelmsen","given":"T.N.","email":"","affiliations":[],"preferred":false,"id":435774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christensen, S.","contributorId":30387,"corporation":false,"usgs":true,"family":"Christensen","given":"S.","email":"","affiliations":[],"preferred":false,"id":435773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mehl, Steffen W. swmehl@usgs.gov","contributorId":975,"corporation":false,"usgs":true,"family":"Mehl","given":"Steffen","email":"swmehl@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":435775,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032433,"text":"70032433 - 2012 - Crucial nesting habitat for gunnison sage-grouse: A spatially explicit hierarchical approach","interactions":[],"lastModifiedDate":"2020-12-02T12:53:54.173606","indexId":"70032433","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Crucial nesting habitat for gunnison sage-grouse: A spatially explicit hierarchical approach","docAbstract":"<p>Gunnison sage-grouse (Centrocercus minimus) is a species of special concern and is currently considered a candidate species under Endangered Species Act. Careful management is therefore required to ensure that suitable habitat is maintained, particularly because much of the species' current distribution is faced with exurban development pressures. We assessed hierarchical nest site selection patterns of Gunnison sage-grouse inhabiting the western portion of the Gunnison Basin, Colorado, USA, at multiple spatial scales, using logistic regression-based resource selection functions. Models were selected using Akaike Information Criterion corrected for small sample sizes (AIC c ) and predictive surfaces were generated using model averaged relative probabilities. Landscape-scale factors that had the most influence on nest site selection included the proportion of sagebrush cover &gt;5%, mean productivity, and density of 2 wheel-drive roads. The landscape-scale predictive surface captured 97% of known Gunnison sage-grouse nests within the top 5 of 10 prediction bins, implicating 57% of the basin as crucial nesting habitat. Crucial habitat identified by the landscape model was used to define the extent for patch-scale modeling efforts. Patch-scale variables that had the greatest influence on nest site selection were the proportion of big sagebrush cover &gt;10%, distance to residential development, distance to high volume paved roads, and mean productivity. This model accurately predicted independent nest locations. The unique hierarchical structure of our models more accurately captures the nested nature of habitat selection, and allowed for increased discrimination within larger landscapes of suitable habitat. We extrapolated the landscape-scale model to the entire Gunnison Basin because of conservation concerns for this species. We believe this predictive surface is a valuable tool which can be incorporated into land use and conservation planning as well the assessment of future land-use scenarios.</p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.268","issn":"0022541X","usgsCitation":"Aldridge, C.L., Saher, D., Childers, T., Stahlnecker, K., and Bowen, Z., 2012, Crucial nesting habitat for gunnison sage-grouse: A spatially explicit hierarchical approach: Journal of Wildlife Management, v. 76, no. 2, p. 391-406, https://doi.org/10.1002/jwmg.268.","productDescription":"16 p.","startPage":"391","endPage":"406","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":474769,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.268","text":"Publisher Index Page"},{"id":241680,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Gunnison Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.984375,\n              38.685509760012\n            ],\n            [\n              -108.3251953125,\n              37.96152331396614\n            ],\n            [\n              -106.89697265625,\n              38.20365531807149\n            ],\n            [\n              -106.45751953125,\n              39.36827914916014\n            ],\n            [\n              -106.54541015625,\n              40.38002840251183\n            ],\n            [\n              -107.9736328125,\n              40.49709237269567\n            ],\n            [\n              -108.74267578125,\n              40.06125658140474\n            ],\n            [\n              -109.09423828125,\n              39.99395569397331\n            ],\n            [\n              -108.984375,\n              38.685509760012\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"76","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-10-28","publicationStatus":"PW","scienceBaseUri":"5059fcc9e4b0c8380cd4e42f","contributors":{"authors":[{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":436155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saher, D.J.","contributorId":54933,"corporation":false,"usgs":true,"family":"Saher","given":"D.J.","email":"","affiliations":[],"preferred":false,"id":436156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Childers, T.M.","contributorId":75343,"corporation":false,"usgs":true,"family":"Childers","given":"T.M.","email":"","affiliations":[],"preferred":false,"id":436157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stahlnecker, K.E.","contributorId":8300,"corporation":false,"usgs":true,"family":"Stahlnecker","given":"K.E.","email":"","affiliations":[],"preferred":false,"id":436154,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowen, Z.H.","contributorId":81045,"corporation":false,"usgs":true,"family":"Bowen","given":"Z.H.","email":"","affiliations":[],"preferred":false,"id":436158,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70032429,"text":"70032429 - 2012 - Isotopically modified nanoparticles for enhanced detection in bioaccumulation studies","interactions":[],"lastModifiedDate":"2020-12-02T12:54:27.761732","indexId":"70032429","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Isotopically modified nanoparticles for enhanced detection in bioaccumulation studies","docAbstract":"<p><span>This work presents results on synthesis of isotopically enriched (99%&nbsp;</span><sup>65</sup><span>Cu) copper oxide nanoparticles and its application in ecotoxicological studies.&nbsp;</span><sup>65</sup><span>CuO nanoparticles were synthesized as spheres (7 nm) and rods (7 × 40 nm). Significant differences were observed between the reactivity and dissolution of spherical and rod shaped nanoparticles. The extreme sensitivity of the stable isotope tracing technique developed in this study allowed determining Cu uptake at exposure concentrations equivalent to background Cu concentrations in freshwater systems (0.2–30 μg/L). Without a tracer, detection of newly accumulated Cu was impossible, even at exposure concentrations surpassing some of the most contaminated water systems (&gt;1 mg/L).</span></p>","language":"English","publisher":"American Chemical Society","doi":"10.1021/es2039757","issn":"0013936X","usgsCitation":"Misra, S., Dybowska, A., Berhanu, D., Croteau, M.N., Luoma, S.N., Boccaccini, A., and Valsami-Jones, E., 2012, Isotopically modified nanoparticles for enhanced detection in bioaccumulation studies: Environmental Science & Technology, v. 46, no. 2, p. 1216-1222, https://doi.org/10.1021/es2039757.","productDescription":"7 p.","startPage":"1216","endPage":"1222","costCenters":[],"links":[{"id":241644,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-12-22","publicationStatus":"PW","scienceBaseUri":"505a3fc2e4b0c8380cd647c7","contributors":{"authors":[{"text":"Misra, S.K.","contributorId":47989,"corporation":false,"usgs":true,"family":"Misra","given":"S.K.","email":"","affiliations":[],"preferred":false,"id":436140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dybowska, A.","contributorId":47171,"corporation":false,"usgs":true,"family":"Dybowska","given":"A.","email":"","affiliations":[],"preferred":false,"id":436139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berhanu, D.","contributorId":86177,"corporation":false,"usgs":true,"family":"Berhanu","given":"D.","email":"","affiliations":[],"preferred":false,"id":436142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":436138,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":436143,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boccaccini, A.R.","contributorId":59637,"corporation":false,"usgs":true,"family":"Boccaccini","given":"A.R.","email":"","affiliations":[],"preferred":false,"id":436141,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Valsami-Jones, E.","contributorId":103088,"corporation":false,"usgs":true,"family":"Valsami-Jones","given":"E.","affiliations":[],"preferred":false,"id":436144,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70032372,"text":"70032372 - 2012 - Effects of roads on survival of San Clemente Island foxes","interactions":[],"lastModifiedDate":"2020-12-02T18:07:14.416349","indexId":"70032372","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of roads on survival of San Clemente Island foxes","docAbstract":"<p><span>Roads generate a variety of influences on wildlife populations; however, little is known about the effects of roads on endemic wildlife on islands. Specifically, road‐kills of island foxes (</span><i>Urocyon littoralis</i><span>) on San Clemente Island (SCI), Channel Islands, California, USA are a concern for resource managers. To determine the effects of roads on island foxes, we radiocollared foxes using a 3‐tiered sampling design to represent the entire population in the study area, a sub‐population near roads, and a sub‐population away from roads on SCI. We examined annual survival rates using nest‐survival models, causes of mortalities, and movements for each sample. We found the population had high annual survival (0.90), although survival declined with use of road habitat, particularly for intermediate‐aged foxes. Foxes living near roads suffered lower annual survival (0.76), resulting from high frequencies of road‐kills (7 of 11 mortalities). Foxes living away from roads had the highest annual survival (0.97). Road‐kill was the most prominent cause of mortality detected on SCI, which we estimated as killing 3–8% of the population in the study area annually. Based on movements, we were unable to detect any responses by foxes that minimized their risks from roads. The probabilities of road‐kills increased with use of the road habitat, volume of traffic, and decreasing road sinuosity. We recommend that managers should attempt to reduce road‐kills by deterring or excluding foxes from entering roads, and attempting to modify behaviors of motorists to be vigilant for foxes.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.247","issn":"0022541X","usgsCitation":"Snow, N., Andelt, W.F., Stanley, T.R., Resnik, J., and Munson, L., 2012, Effects of roads on survival of San Clemente Island foxes: Journal of Wildlife Management, v. 76, no. 2, p. 243-252, https://doi.org/10.1002/jwmg.247.","productDescription":"10 p.","startPage":"243","endPage":"252","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":241747,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214060,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.247"}],"country":"United States","state":"California","otherGeospatial":"San Clemente Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.65234374999999,\n              32.699488680852674\n            ],\n            [\n              -118.30078125,\n              32.699488680852674\n            ],\n            [\n              -118.30078125,\n              33.114549382824535\n            ],\n            [\n              -118.65234374999999,\n              33.114549382824535\n            ],\n            [\n              -118.65234374999999,\n              32.699488680852674\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"76","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-09-27","publicationStatus":"PW","scienceBaseUri":"505a07b7e4b0c8380cd517c0","contributors":{"authors":[{"text":"Snow, N.P.","contributorId":99388,"corporation":false,"usgs":true,"family":"Snow","given":"N.P.","email":"","affiliations":[],"preferred":false,"id":435834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andelt, William F.","contributorId":49296,"corporation":false,"usgs":false,"family":"Andelt","given":"William","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":435832,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanley, Thomas R. 0000-0002-8393-0005 stanleyt@usgs.gov","orcid":"https://orcid.org/0000-0002-8393-0005","contributorId":209928,"corporation":false,"usgs":true,"family":"Stanley","given":"Thomas","email":"stanleyt@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":435833,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Resnik, J.R.","contributorId":104295,"corporation":false,"usgs":true,"family":"Resnik","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":435835,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munson, L.","contributorId":40815,"corporation":false,"usgs":true,"family":"Munson","given":"L.","email":"","affiliations":[],"preferred":false,"id":435831,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70032373,"text":"70032373 - 2012 - A plant distribution shift: temperature, drought or past disturbance?","interactions":[],"lastModifiedDate":"2014-09-11T11:29:40","indexId":"70032373","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","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":"A plant distribution shift: temperature, drought or past disturbance?","docAbstract":"Simple models of plant response to warming climates predict vegetation moving to cooler and/or wetter locations: in mountainous regions shifting upslope. However, species-specific responses to climate change are likely to be much more complex. We re-examined a recently reported vegetation shift in the Santa Rosa Mountains, California, to better understand the mechanisms behind the reported shift of a plant distribution upslope. We focused on five elevational zones near the center of the gradient that captured many of the reported shifts and which are dominated by fire-prone chaparral. Using growth rings, we determined that a major assumption of the previous work was wrong: past fire histories differed among elevations. To examine the potential effect that this difference might have on the reported upward shift, we focused on one species, <i>Ceanothus greggii</i>: a shrub that only recruits post-fire from a soil stored seedbank. For five elevations used in the prior study, we calculated time series of past per-capita mortality rates by counting growth rings on live and dead individuals. We tested three alternative hypotheses explaining the past patterns of mortality: 1) mortality increased over time consistent with climate warming, 2) mortality was correlated with drought indices, and 3) mortality peaked 40–50 years post fire at each site, consistent with self-thinning. We found that the sites were different ages since the last fire, and that the reported increase in the mean elevation of <i>C. greggii</i> was due to higher recent mortality at the lower elevations, which were younger sites. The time-series pattern of mortality was best explained by the self-thinning hypothesis and poorly explained by gradual warming or drought. At least for this species, the reported distribution shift appears to be an artifact of disturbance history and is not evidence of a climate warming effect.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0031173","issn":"19326203","usgsCitation":"Schwilk, D.W., and Keeley, J.E., 2012, A plant distribution shift: temperature, drought or past disturbance?: PLoS ONE, v. 7, no. 2, 6 p., https://doi.org/10.1371/journal.pone.0031173.","productDescription":"6 p.","numberOfPages":"6","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":474788,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0031173","text":"Publisher Index Page"},{"id":214061,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0031173"},{"id":241748,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Rosa Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.355844,33.356894 ], [ -116.355844,33.505883 ], [ -116.099726,33.505883 ], [ -116.099726,33.356894 ], [ -116.355844,33.356894 ] ] ] } } ] }","volume":"7","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-02-10","publicationStatus":"PW","scienceBaseUri":"5059e4dce4b0c8380cd469a5","contributors":{"authors":[{"text":"Schwilk, Dylan W.","contributorId":103883,"corporation":false,"usgs":true,"family":"Schwilk","given":"Dylan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":435837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":435836,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70032380,"text":"70032380 - 2012 - The hidden cost of wildfires: Economic valuation of health effects of wildfire smoke exposure in Southern California","interactions":[],"lastModifiedDate":"2020-12-02T17:24:52.445579","indexId":"70032380","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2295,"text":"Journal of Forest Economics","active":true,"publicationSubtype":{"id":10}},"title":"The hidden cost of wildfires: Economic valuation of health effects of wildfire smoke exposure in Southern California","docAbstract":"<p>There is a growing concern that human health impacts from exposure to wildfire smoke are ignored in estimates of monetized damages from wildfires. Current research highlights the need for better data collection and analysis of these impacts. Using unique primary data, this paper quantifies the economic cost of health effects from the largest wildfire in Los Angeles County's modern history. A cost of illness estimate is \\$9.50 per exposed person per day. However, theory and empirical research consistently find that this measure largely underestimates the true economic cost of health effects from exposure to a pollutant in that it ignores the cost of defensive actions taken as well as disutility. For the first time, the defensive behavior method is applied to calculate the willingness to pay for a reduction in one wildfire smoke induced symptom day, which is estimated to be \\$84.42 per exposed person per day.</p>","language":"English","publisher":"now publishers inc.","doi":"10.1016/j.jfe.2011.05.002","issn":"11046899","usgsCitation":"Richardson, L., Champ, P., and Loomis, J., 2012, The hidden cost of wildfires: Economic valuation of health effects of wildfire smoke exposure in Southern California: Journal of Forest Economics, v. 18, no. 1, p. 14-35, https://doi.org/10.1016/j.jfe.2011.05.002.","productDescription":"22 p.","startPage":"14","endPage":"35","costCenters":[],"links":[{"id":241336,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213685,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jfe.2011.05.002"}],"country":"United States","state":"California","otherGeospatial":"Southern California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.9814453125,\n              34.95799531086792\n            ],\n            [\n              -120.89355468749999,\n              34.379712580462204\n            ],\n            [\n              -118.740234375,\n              32.76880048488168\n            ],\n            [\n              -114.697265625,\n              32.84267363195431\n            ],\n            [\n              -113.73046875,\n              34.379712580462204\n            ],\n            [\n              -116.3232421875,\n              36.63316209558658\n            ],\n            [\n              -122.16796875,\n              36.38591277287651\n            ],\n            [\n              -120.9814453125,\n              34.95799531086792\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"18","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bacb7e4b08c986b3236b4","contributors":{"authors":[{"text":"Richardson, L.A.","contributorId":88960,"corporation":false,"usgs":true,"family":"Richardson","given":"L.A.","email":"","affiliations":[],"preferred":false,"id":435880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champ, P.A.","contributorId":55649,"corporation":false,"usgs":true,"family":"Champ","given":"P.A.","affiliations":[],"preferred":false,"id":435878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loomis, J.B.","contributorId":55985,"corporation":false,"usgs":true,"family":"Loomis","given":"J.B.","email":"","affiliations":[],"preferred":false,"id":435879,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032402,"text":"70032402 - 2012 - Spatial interpolation schemes of daily precipitation for hydrologic modeling","interactions":[],"lastModifiedDate":"2020-12-01T22:44:17.77653","indexId":"70032402","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","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":"Spatial interpolation schemes of daily precipitation for hydrologic modeling","docAbstract":"<p><span>Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s00477-011-0509-1","issn":"14363240","usgsCitation":"Hwang, Y., Clark, M., Rajagopalan, B., and Leavesley, G.H., 2012, Spatial interpolation schemes of daily precipitation for hydrologic modeling: Stochastic Environmental Research and Risk Assessment, v. 26, no. 2, p. 295-320, https://doi.org/10.1007/s00477-011-0509-1.","productDescription":"26 p.","startPage":"295","endPage":"320","costCenters":[],"links":[{"id":214027,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00477-011-0509-1"},{"id":241714,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Georgia","otherGeospatial":"Durango, Statenville","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.0010986328125,\n              37.118716304960124\n            ],\n            [\n              -107.78961181640625,\n              37.118716304960124\n            ],\n            [\n              -107.78961181640625,\n              37.32102825630305\n            ],\n            [\n              -108.0010986328125,\n              37.32102825630305\n            ],\n            [\n              -108.0010986328125,\n              37.118716304960124\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.078369140625,\n              30.637912028341123\n            ],\n            [\n              -82.85888671875,\n              30.637912028341123\n            ],\n            [\n              -82.85888671875,\n              32.519026027827515\n            ],\n            [\n              -84.078369140625,\n              32.519026027827515\n            ],\n            [\n              -84.078369140625,\n              30.637912028341123\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"26","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-07-06","publicationStatus":"PW","scienceBaseUri":"505b9483e4b08c986b31ab31","contributors":{"authors":[{"text":"Hwang, Y.","contributorId":62034,"corporation":false,"usgs":true,"family":"Hwang","given":"Y.","email":"","affiliations":[],"preferred":false,"id":435983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, M.R.","contributorId":88135,"corporation":false,"usgs":true,"family":"Clark","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":435985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rajagopalan, B.","contributorId":86947,"corporation":false,"usgs":true,"family":"Rajagopalan","given":"B.","email":"","affiliations":[],"preferred":false,"id":435984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leavesley, George H. george@usgs.gov","contributorId":1202,"corporation":false,"usgs":true,"family":"Leavesley","given":"George","email":"george@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":435986,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70032386,"text":"70032386 - 2012 - Application of a weighted-averaging method for determining paleosalinity: a tool for restoration of south Florida's estuaries","interactions":[],"lastModifiedDate":"2013-04-08T22:28:07","indexId":"70032386","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Application of a weighted-averaging method for determining paleosalinity: a tool for restoration of south Florida's estuaries","docAbstract":"A molluscan analogue dataset is presented in conjunction with a weighted-averaging technique as a tool for estimating past salinity patterns in south Florida’s estuaries and developing targets for restoration based on these reconstructions. The method, here referred to as cumulative weighted percent (CWP), was tested using modern surficial samples collected in Florida Bay from sites located near fixed water monitoring stations that record salinity. The results were calibrated using species weighting factors derived from examining species occurrence patterns. A comparison of the resulting calibrated species-weighted CWP (SW-CWP) to the observed salinity at the water monitoring stations averaged over a 3-year time period indicates, on average, the SW-CWP comes within less than two salinity units of estimating the observed salinity. The SW-CWP reconstructions were conducted on a core from near the mouth of Taylor Slough to illustrate the application of the method.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Estuaries and Coasts","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s12237-011-9441-3","issn":"15592723","usgsCitation":"Wingard, G., and Hudley, J., 2012, Application of a weighted-averaging method for determining paleosalinity: a tool for restoration of south Florida's estuaries: Estuaries and Coasts, v. 35, no. 1, p. 262-280, https://doi.org/10.1007/s12237-011-9441-3.","productDescription":"19 p.","startPage":"262","endPage":"280","costCenters":[{"id":563,"text":"South Florida Information Access","active":false,"usgs":true}],"links":[{"id":213780,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12237-011-9441-3"},{"id":241438,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.63,24.52 ], [ -87.63,31.0 ], [ -80.0,31.0 ], [ -80.0,24.52 ], [ -87.63,24.52 ] ] ] } } ] }","volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-09-13","publicationStatus":"PW","scienceBaseUri":"5059ec8be4b0c8380cd49325","contributors":{"authors":[{"text":"Wingard, G.L.","contributorId":79981,"corporation":false,"usgs":true,"family":"Wingard","given":"G.L.","email":"","affiliations":[],"preferred":false,"id":435911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudley, J.W.","contributorId":18872,"corporation":false,"usgs":true,"family":"Hudley","given":"J.W.","affiliations":[],"preferred":false,"id":435910,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70032235,"text":"70032235 - 2012 - The influence of wave energy and sediment transport on seagrass distribution","interactions":[],"lastModifiedDate":"2017-05-03T13:50:24","indexId":"70032235","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"The influence of wave energy and sediment transport on seagrass distribution","docAbstract":"<p><span>A coupled hydrodynamic and sediment transport model (Delft3D) was used to simulate the water levels, waves, and currents associated with a seagrass (</span><i class=\"a-plus-plus\">Zostera marina</i><span>) landscape along a 4-km stretch of coast in Puget Sound, WA, USA. A hydroacoustic survey of seagrass percent cover and nearshore bathymetry was conducted, and sediment grain size was sampled at 53 locations. Wave energy is a primary factor controlling seagrass distribution at the site, accounting for 73% of the variability in seagrass minimum depth and 86% of the variability in percent cover along the shallow, sandy portions of the coast. A combination of numerical simulations and a conceptual model of the effect of sea-level rise on the cross-shore distribution of seagrass indicates that the area of seagrass habitat may initially increase and that wave dynamics are an important factor to consider in predicting the effect of sea-level rise on seagrass distributions in wave-exposed areas.</span></p>","language":"English","publisher":"Springer-Verlag","doi":"10.1007/s12237-011-9435-1","issn":"15592723","usgsCitation":"Stevens, A.W., and Lacy, J.R., 2012, The influence of wave energy and sediment transport on seagrass distribution: Estuaries and Coasts, v. 35, no. 1, p. 92-108, https://doi.org/10.1007/s12237-011-9435-1.","productDescription":"17 p.","startPage":"92","endPage":"108","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028543","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":242706,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214945,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12237-011-9435-1"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.46665954589844,\n              47.63809698933633\n            ],\n            [\n              -122.46665954589844,\n              47.938426929481054\n            ],\n            [\n              -122.33413696289064,\n              47.938426929481054\n            ],\n            [\n              -122.33413696289064,\n              47.63809698933633\n            ],\n            [\n              -122.46665954589844,\n              47.63809698933633\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-09-02","publicationStatus":"PW","scienceBaseUri":"505ba786e4b08c986b32160b","contributors":{"authors":[{"text":"Stevens, Andrew W. astevens@usgs.gov","contributorId":3199,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew","email":"astevens@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":435166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172 jlacy@usgs.gov","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":3158,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"jlacy@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":435167,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70032390,"text":"70032390 - 2012 - Temporal scaling of groundwater level fluctuations near a stream","interactions":[],"lastModifiedDate":"2020-12-02T13:01:19.21464","indexId":"70032390","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Temporal scaling of groundwater level fluctuations near a stream","docAbstract":"<p>Temporal scaling in stream discharge and hydraulic heads in riparian wells was evaluated to determine the feasibility of using spectral analysis to identify potential surface and groundwater interaction. In floodplains where groundwater levels respond rapidly to precipitation recharge, potential interaction is established if the hydraulic head (h) spectrum of riparian groundwater has a power spectral density similar to stream discharge (Q), exhibiting a characteristic breakpoint between high and low frequencies. At a field site in Walnut Creek watershed in central Iowa, spectral analysis of h in wells located 1 m from the channel edge showed a breakpoint in scaling very similar to the spectrum of Q (∼20 h), whereas h in wells located 20 and 40 m from the channel showed temporal scaling from 1 to 10,000 h without a well‐defined breakpoint. The spectral exponent (β) in the riparian zone decreased systematically from the channel into the floodplain as groundwater levels were increasingly dominated by white noise groundwater recharge. The scaling pattern of hydraulic head was not affected by land cover type, although the number of analyses was limited and site conditions were variable among sites. Spectral analysis would not replace quantitative tracer or modeling studies, but the method may provide a simple means of confirming potential interaction at some sites.</p>","language":"English","publisher":"National Ground Water Association","doi":"10.1111/j.1745-6584.2011.00804.x","issn":"0017467X","usgsCitation":"Schilling, K.E., and Zhang, Y., 2012, Temporal scaling of groundwater level fluctuations near a stream: Ground Water, v. 50, no. 1, p. 59-67, https://doi.org/10.1111/j.1745-6584.2011.00804.x.","productDescription":"9 p.","startPage":"59","endPage":"67","costCenters":[],"links":[{"id":241506,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213844,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2011.00804.x"}],"country":"United States","state":"Iowa","county":"Jasper County","otherGeospatial":"Walnut Creek Watershed","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-93.234,41.8622],[-93.1187,41.8624],[-93.0035,41.8624],[-92.8845,41.8619],[-92.7674,41.8618],[-92.7683,41.776],[-92.768,41.6879],[-92.7683,41.6007],[-92.7567,41.6011],[-92.7564,41.509],[-92.8729,41.5082],[-92.9894,41.5083],[-93.1047,41.5078],[-93.2181,41.5076],[-93.3304,41.5074],[-93.3314,41.6004],[-93.3504,41.6004],[-93.3496,41.688],[-93.3494,41.7757],[-93.3492,41.8624],[-93.234,41.8622]]]},\"properties\":{\"name\":\"Jasper\",\"state\":\"IA\"}}]}","volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-02-25","publicationStatus":"PW","scienceBaseUri":"505ba518e4b08c986b3207e1","contributors":{"authors":[{"text":"Schilling, K. E.","contributorId":61982,"corporation":false,"usgs":true,"family":"Schilling","given":"K.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":435922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Y.-K.","contributorId":44309,"corporation":false,"usgs":true,"family":"Zhang","given":"Y.-K.","email":"","affiliations":[],"preferred":false,"id":435921,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70032391,"text":"70032391 - 2012 - The challenges of implementing pathogen control strategies for fishes used in biomedical research","interactions":[],"lastModifiedDate":"2020-12-22T18:36:23.765716","indexId":"70032391","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1296,"text":"Comparative Biochemistry and Physiology, Part C: Toxicology & Pharmacology","active":true,"publicationSubtype":{"id":10}},"title":"The challenges of implementing pathogen control strategies for fishes used in biomedical research","docAbstract":"<p><span>Over the past several decades, a number of fish species, including the zebrafish, medaka, and platyfish/swordtail, have become important models for human health and disease. Despite the increasing prevalence of these and other fish species in research, methods for health maintenance and the management of diseases in laboratory populations of these animals are underdeveloped. There is a growing realization that this trend must change, especially as the use of these species expands beyond developmental biology and more towards experimental applications where the presence of underlying disease may affect the physiology animals used in experiments and potentially compromise research results. Therefore, there is a critical need to develop, improve, and implement strategies for managing health and disease in aquatic research facilities. The purpose of this review is to report the proceedings of a workshop entitled “Animal Health and Disease Management in Research Animals” that was recently held at the 5th Aquatic Animal Models for Human Disease in September 2010 at Corvallis, Oregon to discuss the challenges involved with moving the field forward on this front.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.cbpc.2011.06.007","issn":"15320456","usgsCitation":"Lawrence, C., Ennis, D., Harper, C., Kent, M., Murray, K., and Sanders, G., 2012, The challenges of implementing pathogen control strategies for fishes used in biomedical research: Comparative Biochemistry and Physiology, Part C: Toxicology & Pharmacology, v. 155, no. 1, p. 160-166, https://doi.org/10.1016/j.cbpc.2011.06.007.","productDescription":"7 p.","startPage":"160","endPage":"166","costCenters":[],"links":[{"id":474626,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3338152","text":"External Repository"},{"id":241507,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213845,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.cbpc.2011.06.007"}],"volume":"155","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505baa14e4b08c986b3226fd","contributors":{"authors":[{"text":"Lawrence, C.","contributorId":52799,"corporation":false,"usgs":true,"family":"Lawrence","given":"C.","affiliations":[],"preferred":false,"id":435926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ennis, D.G.","contributorId":51103,"corporation":false,"usgs":true,"family":"Ennis","given":"D.G.","email":"","affiliations":[],"preferred":false,"id":435925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harper, C.","contributorId":19380,"corporation":false,"usgs":true,"family":"Harper","given":"C.","email":"","affiliations":[],"preferred":false,"id":435923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kent, M.L.","contributorId":108058,"corporation":false,"usgs":true,"family":"Kent","given":"M.L.","email":"","affiliations":[],"preferred":false,"id":435928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, K.","contributorId":69792,"corporation":false,"usgs":true,"family":"Murray","given":"K.","email":"","affiliations":[],"preferred":false,"id":435927,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanders, George","contributorId":243223,"corporation":false,"usgs":true,"family":"Sanders","given":"George","email":"","affiliations":[],"preferred":true,"id":435924,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70032219,"text":"70032219 - 2012 - Geophysical investigations of geology and structure at the Martis Creek Dam, Truckee, California","interactions":[],"lastModifiedDate":"2013-03-06T16:58:12","indexId":"70032219","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2165,"text":"Journal of Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical investigations of geology and structure at the Martis Creek Dam, Truckee, California","docAbstract":"A recent evaluation of Martis Creek Dam highlighted the potential for dam failure due to either seepage or an earthquake on nearby faults. In 1972, the U.S. Army Corps of Engineers constructed this earthen dam, located within the Truckee Basin to the north of Lake Tahoe, CA for water storage and flood control. Past attempts to raise the level of the Martis Creek Reservoir to its design level have been aborted due to seepage at locations downstream, along the west dam abutment, and at the base of the spillway. In response to these concerns, the U.S. Geological Survey has undertaken a comprehensive suite of geophysical investigations aimed at understanding the interplay between geologic structure, seepage patterns, and reservoir and groundwater levels. This paper concerns the geologic structure surrounding Martis Creek Dam and emphasizes the importance of a regional-scale understanding to the interpretation of engineering-scale geophysical data. Our studies reveal a thick package of sedimentary deposits interbedded with Plio-Pleistocene volcanic flows; both the deposits and the flows are covered by glacial outwash. Magnetic field data, seismic tomography models, and seismic reflections are used to determine the distribution and chronology of the volcanic flows. Previous estimates of depth to basement (or the thickness of the interbedded deposits) was 100 m. Magnetotelluric soundings suggest that electrically resistive bedrock may be up to 2500 m deep. Both the Polaris Fault, identified outside of the study area using airborne LiDAR, and the previously unnamed Martis Creek Fault, have been mapped through the dam area using ground and airborne geophysics. Finally, as determined by direct-current resistivity imaging, time-domain electromagnetic sounding, and seismic refraction, the paleotopography of the interface between the sedimentary deposits and the overlying glacial outwash plays a principal role both in controlling groundwater flow and in the distribution of the observed seepage.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Geophysics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jappgeo.2011.11.002","issn":"09269851","usgsCitation":"Bedrosian, P.A., Burton, B., Powers, M., Minsley, B., Phillips, J., and Hunter, L.E., 2012, Geophysical investigations of geology and structure at the Martis Creek Dam, Truckee, California: Journal of Applied Geophysics, v. 77, p. 7-20, https://doi.org/10.1016/j.jappgeo.2011.11.002.","productDescription":"14 p.","startPage":"7","endPage":"20","costCenters":[],"links":[{"id":214727,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jappgeo.2011.11.002"},{"id":242477,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Truckee","otherGeospatial":"Martis Creek Dam","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.4,32.5 ], [ -124.4,42.0 ], [ -114.1,42.0 ], [ -114.1,32.5 ], [ -124.4,32.5 ] ] ] } } ] }","volume":"77","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2832e4b0c8380cd59f0b","contributors":{"authors":[{"text":"Bedrosian, P. A.","contributorId":100109,"corporation":false,"usgs":true,"family":"Bedrosian","given":"P.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":435101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burton, B.L.","contributorId":93983,"corporation":false,"usgs":true,"family":"Burton","given":"B.L.","email":"","affiliations":[],"preferred":false,"id":435100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powers, M.H.","contributorId":40352,"corporation":false,"usgs":true,"family":"Powers","given":"M.H.","email":"","affiliations":[],"preferred":false,"id":435098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minsley, B. J.","contributorId":52107,"corporation":false,"usgs":true,"family":"Minsley","given":"B. J.","affiliations":[],"preferred":false,"id":435099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phillips, J. D. 0000-0002-6459-2821","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":22366,"corporation":false,"usgs":true,"family":"Phillips","given":"J. D.","affiliations":[],"preferred":false,"id":435097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunter, L. E.","contributorId":100207,"corporation":false,"usgs":true,"family":"Hunter","given":"L.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":435102,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70005382,"text":"70005382 - 2012 - Spatial patterns of aquatic habitat richness in the Upper Mississippi River floodplain, USA","interactions":[],"lastModifiedDate":"2021-01-05T15:27:00.693105","indexId":"70005382","displayToPublicDate":"2011-12-01T10:07:00","publicationYear":"2012","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":"Spatial patterns of aquatic habitat richness in the Upper Mississippi River floodplain, USA","docAbstract":"Interactions among hydrology and geomorphology create shifting mosaics of aquatic habitat patches in large river floodplains (e.g., main and side channels, floodplain lakes, and shallow backwater areas) and the connectivity among these habitat patches underpins high levels of biotic diversity and productivity. However, the diversity and connectivity among the habitats of most floodplain rivers have been negatively impacted by hydrologic and structural modifications that support commercial navigation and control flooding. We therefore tested the hypothesis that the rate of increase in patch richness (# of types) with increasing scale reflects anthropogenic modifications to habitat diversity and connectivity in a large floodplain river, the Upper Mississippi River (UMR). To do this, we calculated the number of aquatic habitat patch types within neighborhoods surrounding each of the &#8776;19 million 5-m aquatic pixels of the UMR for multiple neighborhood sizes (1&ndash;100 ha). For all of the 87 river-reach focal areas we examined, changes in habitat richness (<i>R</i>) with increasing neighborhood length (<i>L</i>, # pixels) were characterized by a fractal-like power function <i>R</i> = <i>L</i><sup>z</sup> (<i>R</i><sup>2</sup> > 0.92 (<i>P</i> < 0.05)). The scaling exponent (<i>z</i>) measures the rate of increase in habitat richness with neighborhood size and is related to a fractal dimension. Variation in <i>z</i> reflected fundamental changes to spatial patterns of aquatic habitat richness in this river system. With only a few exceptions, <i>z</i> exceeded the river-wide average of 0.18 in focal areas where side channels, contiguous floodplain lakes, and contiguous shallow-water areas exceeded 5%, 5%, and 10% of the floodplain respectively. In contrast, <i>z</i> was always less than 0.18 for focal areas where impounded water exceeded 40% of floodplain area. Our results suggest that rehabilitation efforts that target areas with <5% of the floodplain in side channels, <5% in floodplain lakes, and/or <10% in shallow-water areas could improve habitat diversity across multiple scales in the UMR.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2011.06.013","usgsCitation":"De Jager, N.R., and Rohweder, J., 2012, Spatial patterns of aquatic habitat richness in the Upper Mississippi River floodplain, USA: Ecological Indicators, v. 13, no. 1, p. 275-283, https://doi.org/10.1016/j.ecolind.2011.06.013.","productDescription":"9 p.","startPage":"275","endPage":"283","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":381878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.59277343749999,\n              45.73685954736049\n            ],\n            [\n              -93.8671875,\n              44.84029065139799\n            ],\n            [\n              -91.845703125,\n              42.71473218539458\n            ],\n            [\n              -91.97753906249999,\n              40.1452892956766\n            ],\n            [\n              -91.0546875,\n              37.71859032558816\n            ],\n            [\n              -90.3955078125,\n              36.4566360115962\n            ],\n            [\n              -88.11035156249999,\n              36.77409249464195\n            ],\n            [\n              -89.2529296875,\n              39.67337039176558\n            ],\n            [\n              -89.6044921875,\n              42.19596877629178\n            ],\n            [\n              -91.23046875,\n              45.30580259943578\n            ],\n            [\n              -92.59277343749999,\n              45.73685954736049\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b949ae4b08c986b31ab9e","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":104616,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":352390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rohweder, Jason J.","contributorId":25629,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason J.","affiliations":[],"preferred":false,"id":352389,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70189252,"text":"70189252 - 2012 - Influences of the El Niño Southern Oscillation and the Pacific Decadal Oscillation on the timing of the North American spring","interactions":[],"lastModifiedDate":"2017-07-07T09:50:56","indexId":"70189252","displayToPublicDate":"2011-11-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Influences of the El Niño Southern Oscillation and the Pacific Decadal Oscillation on the timing of the North American spring","docAbstract":"Detrended, modelled first leaf dates for 856 sites across North America for the period 1900–2008 are used to examine how the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) separately and together might influence the timing of spring. Although spring (mean March through April) ENSO and PDO signals are apparent in first leaf dates, the signals are not statistically significant (at a 95% confidence level (p < 0.05)) for most sites. The most significant ENSO/PDO signal in first leaf dates occurs for El Niño and positive PDO conditions. An analysis of the spatial distributions of first leaf dates for separate and combined ENSO/PDO conditions features a northwest–southeast dipole that is significantly (at p < 0.05) different than the distributions for neutral conditions. The nature of the teleconnection between Pacific SST's and first leaf dates is evident in comparable composites for detrended sea level pressure (SLP) in the spring months. During positive ENSO/PDO, there is an anomalous flow of warm air from the southwestern US into the northwestern US and an anomalous northeasterly flow of cold air from polar regions into the eastern and southeastern US. These flow patterns are reversed during negative ENSO/PDO. Although the magnitudes of first leaf date departures are not necessarily significantly related to ENSO and PDO, the spatial patterns of departures are significantly related to ENSO and PDO. These significant relations and the long-lived persistence of SSTs provide a potential tool for forecasting the tendencies for first leaf dates to be early or late.","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/joc.3400","usgsCitation":"McCabe, G., Ault, T., Cook, B., Betancourt, J.L., and Schwartz, M.D., 2012, Influences of the El Niño Southern Oscillation and the Pacific Decadal Oscillation on the timing of the North American spring: International Journal of Climatology, v. 32, p. 2301-2310, https://doi.org/10.1002/joc.3400.","productDescription":"10 p. ","startPage":"2301","endPage":"2310","ipdsId":"IP-026240","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":474693,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2060/20140001049","text":"External Repository"},{"id":343429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.7060546875,\n              32.175612478499346\n            ],\n            [\n              -73.125,\n              30.90222470517144\n            ],\n            [\n              -61.17187499999999,\n              43.32517767999296\n            ],\n            [\n              -64.16015624999999,\n              44.465151013519645\n            ],\n            [\n              -73.125,\n              46.55886030311719\n            ],\n            [\n              -82.44140625,\n              48.80686346108517\n            ],\n            [\n              -109.16015624999999,\n              52.908902047770255\n            ],\n            [\n              -129.90234375,\n              52.37559917665908\n            ],\n            [\n              -125.1123046875,\n              39.095962936305476\n            ],\n            [\n              -120.76171875,\n              34.63320791137959\n            ],\n            [\n              -78.7060546875,\n              32.175612478499346\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"32","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2011-11-15","publicationStatus":"PW","scienceBaseUri":"595f4c47e4b0d1f9f057e37d","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":167116,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":703741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ault, Toby R.","contributorId":48852,"corporation":false,"usgs":true,"family":"Ault","given":"Toby R.","affiliations":[],"preferred":false,"id":703745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Benjamin I.","contributorId":81237,"corporation":false,"usgs":true,"family":"Cook","given":"Benjamin I.","affiliations":[],"preferred":false,"id":703743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":703742,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwartz, Mark D.","contributorId":175228,"corporation":false,"usgs":false,"family":"Schwartz","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":false,"id":703744,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70227333,"text":"70227333 - 2012 - Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO2 injection experiment","interactions":[],"lastModifiedDate":"2022-01-10T15:36:27.174564","indexId":"70227333","displayToPublicDate":"2011-11-26T09:26:26","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2049,"text":"International Journal of Greenhouse Gas Control","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO<sub>2</sub> injection experiment","title":"Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO2 injection experiment","docAbstract":"<div id=\"aep-abstract-id35\" class=\"abstract author\"><div id=\"aep-abstract-sec-id36\"><p id=\"spar0010\">A field experiment involving the release of carbon dioxide (CO<sub>2</sub>) into a shallow aquifer was conducted near Bozeman, Montana, during the summer of 2008, to investigate the potential groundwater quality impacts in the case of leakage of CO<sub>2</sub><span>&nbsp;</span>from deep geological storage. As an essential part of the Montana State University Zero Emission Research and Technology (MSU-ZERT) field program, food-grade CO<sub>2</sub><span>&nbsp;</span>was injected over a 30 day period into a horizontal perforated pipe a few feet below the water table of a shallow aquifer. The impact of elevated CO<sub>2</sub><span>&nbsp;</span>concentrations on groundwater quality was investigated by analyzing water samples taken before, during, and following CO<sub>2</sub><span>&nbsp;</span>injection, from observation wells located in the vicinity of the injection pipe, and from two distant monitoring wells. Field measurements and laboratory analyses showed rapid and systematic changes in pH, alkalinity, and conductance, as well as increases in the aqueous concentrations of naturally occurring major and trace element species.</p><p id=\"spar0015\">The geochemical data were evaluated using principal component analysis (PCA) to (1) understand potential correlations between aqueous species, and (2) to identify minerals controlling the chemical composition of the groundwater prior to CO<sub>2</sub><span>&nbsp;</span>injection. These evaluations were used to assess possible geochemical processes responsible for the observed increases in the concentrations of dissolved constituents, and to simulate these processes using a multicomponent reaction path model. Reasonable agreement between observed and modeled data suggests that (1) calcite dissolution was the primary pH buffer, yielding increased Ca<sup>+2</sup><span>&nbsp;</span>concentrations in the groundwater, (2) increases in the concentrations of most major and trace metal cations except Fe could be a result of Ca<sup>+2</sup>-driven exchange reactions, (3) the release of anions from adsorption sites due to competitive adsorption of carbonate could explain the observed trends of most anions, and (4) the dissolution of reactive Fe minerals (presumed ferrihydrite and fougerite, from thermodynamic analyses) could explain increases in total Fe concentration.</p></div></div><div id=\"aep-abstract-id33\" class=\"abstract graphical\"><div id=\"aep-abstract-sec-id34\"><h3 class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Highlights</h3><p id=\"spar0005\">► Because the possibility of CO<sub>2</sub><span>&nbsp;</span>leakage cannot be completely ruled out, the potential impact of CO<sub>2</sub><span>&nbsp;</span>intrusion on the quality of fresh water aquifers overlying CO<sub>2</sub><span>&nbsp;</span>storage sites needs to be investigated. ► Geochemical data from a field experiment involving the release of carbon dioxide (CO<sub>2</sub>) into a shallow aquifer were evaluated. ► Geochemical model used to assess possible geochemical processes responsible for the observed increases in the concentrations of dissolved constituents. ► Reasonable agreement between observed and modeled data suggests that increases in the concentrations of most major and trace metal cations except Fe could be a result of Ca<sup>+2</sup>-driven exchange reactions and the release of anions from adsorption sites due to competitive adsorption of carbonate could explain the observed trends of most anions.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijggc.2011.10.003","usgsCitation":"Zheng, L., Apps, J.A., Spycher, N., Birkholzer, J., Kharaka, Y.K., Thordsen, J., Beers, S.R., Herkelrath, W.N., Kakouros, E., and Trautz, R.C., 2012, Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO2 injection experiment: International Journal of Greenhouse Gas Control, v. 7, p. 202-217, https://doi.org/10.1016/j.ijggc.2011.10.003.","productDescription":"16 p.","startPage":"202","endPage":"217","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":474694,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1210906","text":"External Repository"},{"id":394105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","city":"Bozeman","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.20292663574217,\n              45.58809518781759\n            ],\n            [\n              -110.95916748046875,\n              45.58809518781759\n            ],\n            [\n              -110.95916748046875,\n              45.670684230297006\n            ],\n            [\n              -111.20292663574217,\n              45.670684230297006\n            ],\n            [\n              -111.20292663574217,\n              45.58809518781759\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zheng, Liange","contributorId":209333,"corporation":false,"usgs":false,"family":"Zheng","given":"Liange","email":"","affiliations":[],"preferred":false,"id":830491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Apps, J. A.","contributorId":60386,"corporation":false,"usgs":false,"family":"Apps","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":830492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spycher, N.","contributorId":54424,"corporation":false,"usgs":true,"family":"Spycher","given":"N.","email":"","affiliations":[],"preferred":false,"id":830493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birkholzer, J.","contributorId":84590,"corporation":false,"usgs":true,"family":"Birkholzer","given":"J.","affiliations":[],"preferred":false,"id":830494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kharaka, Yousif K. 0000-0001-9861-8260 ykharaka@usgs.gov","orcid":"https://orcid.org/0000-0001-9861-8260","contributorId":1928,"corporation":false,"usgs":true,"family":"Kharaka","given":"Yousif","email":"ykharaka@usgs.gov","middleInitial":"K.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":830495,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thordsen, James J. jthordsn@usgs.gov","contributorId":3329,"corporation":false,"usgs":true,"family":"Thordsen","given":"James J.","email":"jthordsn@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":830496,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beers, Sarah R.","contributorId":209331,"corporation":false,"usgs":false,"family":"Beers","given":"Sarah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":830497,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Herkelrath, William N. 0000-0002-6149-5524 wnherkel@usgs.gov","orcid":"https://orcid.org/0000-0002-6149-5524","contributorId":2612,"corporation":false,"usgs":true,"family":"Herkelrath","given":"William","email":"wnherkel@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":830498,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kakouros, Evangelos 0000-0002-4778-4039 kakouros@usgs.gov","orcid":"https://orcid.org/0000-0002-4778-4039","contributorId":2587,"corporation":false,"usgs":true,"family":"Kakouros","given":"Evangelos","email":"kakouros@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":830499,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Trautz, Robert C.","contributorId":171754,"corporation":false,"usgs":false,"family":"Trautz","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":26941,"text":"Electric Power Research Institute, Palo Alto, CA","active":true,"usgs":false}],"preferred":false,"id":830500,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70155280,"text":"70155280 - 2012 - Recent summer precipitation trends in the Greater Horn of Africa and the emerging role of Indian Ocean sea surface temperature","interactions":[],"lastModifiedDate":"2021-04-27T19:59:48.530087","indexId":"70155280","displayToPublicDate":"2011-10-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1248,"text":"Climate Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"Recent summer precipitation trends in the Greater Horn of Africa and the emerging role of Indian Ocean sea surface temperature","docAbstract":"<div id=\"kb-nav--main\" class=\"col-main has-full-enumeration\"><div class=\"abstract-content formatted\"><p class=\"Para\"><span>We utilize a variety of climate datasets to examine impacts of two mechanisms on precipitation in the Greater Horn of Africa (GHA) during northern-hemisphere summer. First, surface-pressure gradients draw moist air toward the GHA from the tropical Atlantic Ocean and Congo Basin. Variability of the strength of these gradients strongly influences GHA precipitation totals and accounts for important phenomena such as the 1960s–1980s rainfall decline and devastating 1984 drought. Following the 1980s, precipitation variability became increasingly influenced by the southern tropical Indian Ocean (STIO) region. Within this region, increases in sea-surface temperature, evaporation, and precipitation are linked with increased exports of dry mid-tropospheric air from the STIO region toward the GHA. Convergence of dry air above the GHA reduces local convection and precipitation. It also produces a clockwise circulation response near the ground that reduces moisture transports from the Congo Basin. Because precipitation originating in the Congo Basin has a unique isotopic signature, records of moisture transports from the Congo Basin may be preserved in the isotopic composition of annual tree rings in the Ethiopian Highlands. A negative trend in tree-ring oxygen-18 during the past half century suggests a decline in the proportion of precipitation originating from the Congo Basin. This trend may not be part of a natural cycle that will soon rebound because climate models characterize Indian Ocean warming as a principal signature of greenhouse-gas induced climate change. We therefore expect surface warming in the STIO region to continue to negatively impact GHA precipitation during northern-hemisphere summer.</span></p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s00382-011-1222-y","usgsCitation":"Williams, A.P., Funk, C.C., Michaelsen, J., Rauscher, S.A., Robertson, I., Wils, T.H., Koprowski, M., Eshetu, Z., and Loader, N.J., 2012, Recent summer precipitation trends in the Greater Horn of Africa and the emerging role of Indian Ocean sea surface temperature: Climate Dynamics, v. 39, p. 2307-2328, https://doi.org/10.1007/s00382-011-1222-y.","productDescription":"22 p.","startPage":"2307","endPage":"2328","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030669","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474695,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00382-011-1222-y","text":"Publisher Index Page"},{"id":306614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ethiopia, Kenya, Sudan, Uganda","otherGeospatial":"Greater Horn of Africa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              41.484375,\n              -1.625758360412755\n            ],\n            [\n              40.8251953125,\n              0.4394488164139768\n            ],\n            [\n              41.044921875,\n              2.767477951092084\n            ],\n            [\n              41.7919921875,\n              3.9519408561575946\n            ],\n            [\n              44.560546875,\n              5.090944175033399\n            ],\n           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G.","contributorId":257647,"corporation":false,"usgs":false,"family":"Wils","given":"Tommy","email":"","middleInitial":"H. G.","affiliations":[],"preferred":false,"id":814828,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Koprowski, Marcin","contributorId":257648,"corporation":false,"usgs":false,"family":"Koprowski","given":"Marcin","email":"","affiliations":[],"preferred":false,"id":814829,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Eshetu, Zewdu","contributorId":257650,"corporation":false,"usgs":false,"family":"Eshetu","given":"Zewdu","email":"","affiliations":[],"preferred":false,"id":814831,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Loader, Neil J.","contributorId":257649,"corporation":false,"usgs":false,"family":"Loader","given":"Neil","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":814830,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70032532,"text":"70032532 - 2012 - Fitting a structured juvenile-adult model for green tree frogs to population estimates from capture-mark-recapture field data","interactions":[],"lastModifiedDate":"2021-02-04T19:41:57.048472","indexId":"70032532","displayToPublicDate":"2011-10-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1107,"text":"Bulletin of Mathematical Biology","active":true,"publicationSubtype":{"id":10}},"title":"Fitting a structured juvenile-adult model for green tree frogs to population estimates from capture-mark-recapture field data","docAbstract":"<p><span>We derive point and interval estimates for an urban population of green tree frogs (</span><i>Hyla cinerea</i><span>) from capture–mark–recapture field data obtained during the years 2006–2009. We present an infinite-dimensional least-squares approach which compares a mathematical population model to the statistical population estimates obtained from the field data. The model is composed of nonlinear first-order hyperbolic equations describing the dynamics of the amphibian population where individuals are divided into juveniles (tadpoles) and adults (frogs). To solve the least-squares problem, an explicit finite difference approximation is developed. Convergence results for the computed parameters are presented. Parameter estimates for the vital rates of juveniles and adults are obtained, and standard deviations for these estimates are computed. Numerical results for the model sensitivity with respect to these parameters are given. Finally, the above-mentioned parameter estimates are used to illustrate the long-time behavior of the population under investigation.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s11538-011-9682-0","usgsCitation":"Ackleh, A.S., Carter, J., Deng, K., Huang, Q., Pal, N., and Yang, X., 2012, Fitting a structured juvenile-adult model for green tree frogs to population estimates from capture-mark-recapture field data: Bulletin of Mathematical Biology, v. 74, no. 3, p. 641-665, https://doi.org/10.1007/s11538-011-9682-0.","productDescription":"25 p.","startPage":"641","endPage":"665","ipdsId":"IP-032520","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":241621,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-10-13","publicationStatus":"PW","scienceBaseUri":"505a10c6e4b0c8380cd53dd6","contributors":{"authors":[{"text":"Ackleh, Azmy S.","contributorId":119949,"corporation":false,"usgs":true,"family":"Ackleh","given":"Azmy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":436663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, J. 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":81839,"corporation":false,"usgs":true,"family":"Carter","given":"J.","email":"carterj@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":436668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deng, Keng","contributorId":119746,"corporation":false,"usgs":true,"family":"Deng","given":"Keng","email":"","affiliations":[],"preferred":false,"id":436665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huang, Qihua","contributorId":119159,"corporation":false,"usgs":true,"family":"Huang","given":"Qihua","email":"","affiliations":[],"preferred":false,"id":436664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pal, Nabendu","contributorId":119796,"corporation":false,"usgs":true,"family":"Pal","given":"Nabendu","email":"","affiliations":[],"preferred":false,"id":436667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yang, Xing","contributorId":116164,"corporation":false,"usgs":true,"family":"Yang","given":"Xing","email":"","affiliations":[],"preferred":false,"id":436666,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70102820,"text":"70102820 - 2012 - Programs for calibration‐based Monte Carlo simulation of recharge areas","interactions":[],"lastModifiedDate":"2019-07-03T14:25:36","indexId":"70102820","displayToPublicDate":"2011-10-11T13:24:55","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Programs for calibration‐based Monte Carlo simulation of recharge areas","docAbstract":"<p><span>One use of groundwater flow models is to simulate contributing recharge areas to wells or springs. Particle tracking can be used to simulate these recharge areas, but in many cases the modeler is not sure how accurate these recharge areas are because parameters such as hydraulic conductivity and recharge have errors associated with them. The scripts described in this article (GEN_LHS and MCDRIVER_LHS) use the Python scripting language to run a Monte Carlo simulation with Latin hypercube sampling where model parameters such as hydraulic conductivity and recharge are randomly varied for a large number of model simulations, and the probability of a particle being in the contributing area of a well is calculated based on the results of multiple simulations. Monte Carlo simulation provides one useful measure of the variability in modeled particles. The Monte Carlo method described here is unique in that it uses parameter sets derived from the optimal parameters, their standard deviations, and their correlation matrix, all of which are calculated during nonlinear regression model calibration. In addition, this method uses a set of acceptance criteria to eliminate unrealistic parameter sets.</span></p>","language":"English","publisher":"NGWA","doi":"10.1111/j.1745-6584.2011.00868.x","usgsCitation":"Starn, J., and Bagtzoglou, A.C., 2012, Programs for calibration‐based Monte Carlo simulation of recharge areas: Ground Water, v. 50, no. 3, p. 472-476, https://doi.org/10.1111/j.1745-6584.2011.00868.x.","productDescription":"5 p.","startPage":"472","endPage":"476","ipdsId":"IP-029084","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":365284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Starn, J. Jeffrey 0000-0001-5909-0010 jjstarn@usgs.gov","orcid":"https://orcid.org/0000-0001-5909-0010","contributorId":1916,"corporation":false,"usgs":true,"family":"Starn","given":"J. Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":false,"id":518736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagtzoglou, Amvrossios C.","contributorId":211518,"corporation":false,"usgs":false,"family":"Bagtzoglou","given":"Amvrossios","email":"","middleInitial":"C.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":765422,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005482,"text":"70005482 - 2012 - Effects of flow releases on macroinvertebrate assemblages in the Indian and Hudson Rivers in the Adirondack Mountains of Northern New York","interactions":[],"lastModifiedDate":"2021-05-20T22:31:50.948419","indexId":"70005482","displayToPublicDate":"2011-10-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Effects of flow releases on macroinvertebrate assemblages in the Indian and Hudson Rivers in the Adirondack Mountains of Northern New York","docAbstract":"<p><span>The effects of flow releases (daily during spring and four times weekly during summer) from a small impoundment on macroinvertebrate assemblages in the lower Indian River and upper Hudson River of northern New York were assessed during the summers of 2005 and 2006. Community indices, feeding guilds, dominant species and Bray–Curtis similarities at three sites on the Indian River, below a regulated impoundment, were compared with those at four control sites on the Cedar River, below a run-of-the-river impoundment of comparable size. The same indices at four less-likely affected sites on the Hudson River, below the mouth of the Indian River, were compared with those at an upstream control site on the Hudson River. Results show that the function and apparent health of macroinvertebrate communities were generally unaffected by atypical flow regimes and/or altered water quality at study reaches downstream from both dams in the Indian, Cedar and Hudson Rivers. The lentic nature of releases from both impoundments, however, produced significant changes in the structure of assemblages at Indian and Cedar River sites immediately downstream from both dams, moderate effects at two Indian River sites 2.4 and 4.0 km downstream from its dam, little or no effect at three Cedar River sites 7.2–34.2 km downstream from its dam, and no effect at any Hudson River site. Bray–Curtis similarities indicate that assemblages did not differ significantly among sites within similar impact categories. The paucity of scrapers at all Indian River sites, and the predominance of filter-feeding&nbsp;</span><i>Simulium gouldingi</i><span>&nbsp;and&nbsp;</span><i>Pisidium compressum</i><span>&nbsp;immediately below Abanakee dam, show that only minor differences in dominant species and trophic structure of macroinvertebrate communities occurred at affected sites in the Indian River compared to the Cedar River. Thus, flow releases had only a small, localized effect on macroinvertebrate communities in the Indian River.</span></p>","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/rra.1480","usgsCitation":"Baldigo, B., and Smith, A.J., 2012, Effects of flow releases on macroinvertebrate assemblages in the Indian and Hudson Rivers in the Adirondack Mountains of Northern New York: River Research and Applications, v. 28, no. 7, p. 858-871, https://doi.org/10.1002/rra.1480.","productDescription":"14 p.","startPage":"858","endPage":"871","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":474696,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.1480","text":"Publisher Index Page"},{"id":204469,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"projection":"Universal Transverse Mercator","country":"United States","state":"New York","otherGeospatial":"Cedar River, Hudson River,  Indian River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.6,43.583333333333336 ], [ -74.6,43.916666666666664 ], [ -74,43.916666666666664 ], [ -74,43.583333333333336 ], [ -74.6,43.583333333333336 ] ] ] } } ] }","volume":"28","issue":"7","noUsgsAuthors":false,"publicationDate":"2011-01-20","publicationStatus":"PW","scienceBaseUri":"4f4e4a2ce4b07f02db613a24","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":25174,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, A. J.","contributorId":67040,"corporation":false,"usgs":false,"family":"Smith","given":"A.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":352639,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70156356,"text":"70156356 - 2012 - A reevaluation of the Munson-Nygren-Retriever submarine landslide complex, Georges bank lower slope, western north Atlantic","interactions":[],"lastModifiedDate":"2017-11-18T12:08:47","indexId":"70156356","displayToPublicDate":"2011-09-15T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3915,"text":"Advances in Natural and Technological Hazards Research","active":true,"publicationSubtype":{"id":10}},"title":"A reevaluation of the Munson-Nygren-Retriever submarine landslide complex, Georges bank lower slope, western north Atlantic","docAbstract":"<p>The Munson-Nygren-Retriever (MNR) landslide complex is a series of distinct submarine landslides located between Nygren and Powell canyons on the Georges Bank lower slope. These landslides were first imaged in 1978 using widely-spaced seismic reflection profiles and were further investigated using continuous coverage GLORIA sidescan imagery collected over the landslide complex in 1987. Recent acquisition of highresolution multibeam bathymetry across these landslides has provided an unprecedented view of their complex morphology and allows for a more detailed investigation of their evacuation and deposit morphologies and sizes, modes of failure, and relationship to the adjacent sections of the margin, including the identification of an additional landslide within the MNR complex, referred to here as the Pickett slide. The evacuation zone of these landslides covers an area of approximately 1,780 km2 . The headwalls of these landslides are at a depth of approximately 1,800 m, with evacuation extending for approximately 60 km downslope to the top of the continental rise. High-relief debris deposits, in the form of blocks and ridges, are present down the length of the majority of the evacuation zones and within the deposition area at the base of the slope. On the continental rise, the deposits from each of the most recent failures of the MNR complex landslides merge with debris from earlier continental slope failures, canyon and alongslope derived deposits, and prominent upper-rise failures.</p>","language":"English","publisher":"SpringerLink","doi":"10.1007/978-94-007-2162-3_12","usgsCitation":"Chaytor, J., Twichell, D.C., and ten Brink, U., 2012, A reevaluation of the Munson-Nygren-Retriever submarine landslide complex, Georges bank lower slope, western north Atlantic: Advances in Natural and Technological Hazards Research, v. 31, p. 135-146, https://doi.org/10.1007/978-94-007-2162-3_12.","productDescription":"11 p.","startPage":"135","endPage":"146","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":308182,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -65.3466796875,\n              37.54457732085582\n            ],\n            [\n              -65.3466796875,\n              40.3130432088809\n            ],\n            [\n              -59.83154296874999,\n              40.3130432088809\n            ],\n            [\n              -59.83154296874999,\n              37.54457732085582\n            ],\n            [\n              -65.3466796875,\n              37.54457732085582\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"31","noUsgsAuthors":false,"publicationDate":"2011-09-15","publicationStatus":"PW","scienceBaseUri":"55fa92ace4b05d6c4e501a42","contributors":{"authors":[{"text":"Chaytor, Jason D. jchaytor@usgs.gov","contributorId":4961,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason D.","email":"jchaytor@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":568842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Twichell, David C.","contributorId":37730,"corporation":false,"usgs":true,"family":"Twichell","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":568843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":568844,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70004913,"text":"70004913 - 2012 - Development and use of a floristic quality index for coastal Louisiana marshes","interactions":[],"lastModifiedDate":"2019-08-27T11:34:45","indexId":"70004913","displayToPublicDate":"2011-06-10T11:30:03","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Development and use of a floristic quality index for coastal Louisiana marshes","docAbstract":"The Floristic Quality Index (FQI) has been used as a tool for assessing the integrity of plant communities and for assessing restoration projects in many regions of the USA. Here, we develop a modified FQI (FQImod) for coastal Louisiana wetlands and verify it using 12 years of monitoring data from a coastal restoration project. Plant species that occur in coastal Louisiana were assigned a coefficient of conservatism (CC) score by a local group with expertise in Louisiana coastal vegetation. Species percent cover and both native and non-native species were included in the FQImod which was scaled from 0?100. The FQImod scores from the long-term monitoring project demonstrated the utility of this index for assessing wetland condition over time, including its sensitivity to a hurricane. Ultimately, the FQI developed for coastal Louisiana will be used in conjunction with other wetland indices (e.g., hydrology and soils) to assess wetland condition coastwide and these indices will aid managers in coastal restoration and management decisions.","language":"English","publisher":"Springer","doi":"10.1007/s10661-011-2125-4","usgsCitation":"Visser, M.J., Cretini, K., Krauss, K.W., and Steyer, G.D., 2012, Development and use of a floristic quality index for coastal Louisiana marshes: Environmental Monitoring and Assessment, v. 184, no. 4, p. 2389-2403, https://doi.org/10.1007/s10661-011-2125-4.","productDescription":"15 p.","startPage":"2389","endPage":"2403","ipdsId":"IP-020272","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":366962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": 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         29.34387539941801\n            ],\n            [\n              -90.274658203125,\n              29.0273547804184\n            ],\n            [\n              -89.8681640625,\n              29.23847708592805\n            ],\n            [\n              -89.4287109375,\n              28.8927788645183\n            ],\n            [\n              -88.87939453125,\n              29.152161283318915\n            ],\n            [\n              -89.593505859375,\n              29.5830116903775\n            ],\n            [\n              -89.296875,\n              29.754839972510933\n            ],\n            [\n              -89.088134765625,\n              30.002516938570686\n            ],\n            [\n              -89.307861328125,\n              30.135626231134587\n            ],\n            [\n              -89.593505859375,\n              30.164126343161097\n            ],\n            [\n              -89.80224609374999,\n              30.496017831341284\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"184","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Visser, M Jenneke Jenneke","contributorId":119531,"corporation":false,"usgs":true,"family":"Visser","given":"M","suffix":"Jenneke","email":"","middleInitial":"Jenneke","affiliations":[],"preferred":false,"id":513238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cretini, Kari 0000-0003-0419-0748","orcid":"https://orcid.org/0000-0003-0419-0748","contributorId":207226,"corporation":false,"usgs":true,"family":"Cretini","given":"Kari","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":769362,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70118981,"text":"70118981 - 2012 - MODFLOW-style parameters in underdetermined parameter estimation","interactions":[],"lastModifiedDate":"2024-04-24T16:19:51.813673","indexId":"70118981","displayToPublicDate":"2011-02-25T09:11:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"MODFLOW-style parameters in underdetermined parameter estimation","docAbstract":"<p><span>In this article, we discuss the use of MODFLOW-Style&nbsp;</span><i>parameters</i><span>&nbsp;in the numerical codes MODFLOW_2005 and MODFLOW_2005-Adjoint for the definition of variables in the Layer Property Flow package.&nbsp;</span><i>Parameters</i><span>&nbsp;are a useful tool to represent aquifer properties in both codes and are the only option available in the adjoint version. Moreover, for overdetermined parameter estimation problems, the&nbsp;</span><i>parameter</i><span>&nbsp;approach for model input can make data input easier. We found that if each estimable parameter is defined by one&nbsp;</span><i>parameter</i><span>, the codes require a large computational effort and substantial gains in efficiency are achieved by removing logical comparison of character strings that represent the names and types of the&nbsp;</span><i>parameters.</i><span>&nbsp;An alternative formulation already available in the current implementation of the code can also alleviate the efficiency degradation due to character comparisons in the special case of&nbsp;</span><i>distributed parameters</i><span>&nbsp;defined through multiplication matrices. The authors also hope that lessons learned in analyzing the performance of the MODFLOW family codes will be enlightening to developers of other Fortran implementations of numerical codes.</span></p>","language":"English","publisher":"National Groundwater Association","doi":"10.1111/j.1745-6584.2011.00803.x","usgsCitation":"D’Oria, M.D., and Fienen, M., 2012, MODFLOW-style parameters in underdetermined parameter estimation: Groundwater, v. 50, no. 1, p. 149-153, https://doi.org/10.1111/j.1745-6584.2011.00803.x.","productDescription":"5 p.","startPage":"149","endPage":"153","ipdsId":"IP-016755","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":291560,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-02-25","publicationStatus":"PW","scienceBaseUri":"53e09e5be4b0beb42bdca469","contributors":{"authors":[{"text":"D’Oria, Marco D.","contributorId":22258,"corporation":false,"usgs":true,"family":"D’Oria","given":"Marco","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":497550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":497549,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70036375,"text":"70036375 - 2012 - Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal","interactions":[],"lastModifiedDate":"2017-04-06T14:20:32","indexId":"70036375","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal","docAbstract":"<p><span>Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km</span><sup>2</sup><span> in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/bg-9-631-2012","issn":"18106277","usgsCitation":"Dieye, A., Roy, D.P., Hanan, N., Liu, S., Hansen, M., and Toure, A., 2012, Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal: Biogeosciences, v. 9, p. 631-648, https://doi.org/10.5194/bg-9-631-2012.","productDescription":"18 p.","startPage":"631","endPage":"648","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474697,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-9-631-2012","text":"Publisher Index Page"},{"id":246158,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2012-02-03","publicationStatus":"PW","scienceBaseUri":"505b8d24e4b08c986b318292","contributors":{"authors":[{"text":"Dieye, A.M.","contributorId":35988,"corporation":false,"usgs":true,"family":"Dieye","given":"A.M.","email":"","affiliations":[],"preferred":false,"id":455789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, David P.","contributorId":54761,"corporation":false,"usgs":false,"family":"Roy","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false},{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false},{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":455790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanan, N.P.","contributorId":82123,"corporation":false,"usgs":true,"family":"Hanan","given":"N.P.","affiliations":[],"preferred":false,"id":455791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, S.","contributorId":93170,"corporation":false,"usgs":true,"family":"Liu","given":"S.","affiliations":[],"preferred":false,"id":455792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, M.","contributorId":34670,"corporation":false,"usgs":true,"family":"Hansen","given":"M.","affiliations":[],"preferred":false,"id":455788,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Toure, A.","contributorId":98920,"corporation":false,"usgs":true,"family":"Toure","given":"A.","email":"","affiliations":[],"preferred":false,"id":455793,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70237802,"text":"70237802 - 2012 - Numerical simulations examining the possible role of anthropogenic and volcanic emissions during the 1997 Indonesian fires","interactions":[],"lastModifiedDate":"2022-10-25T10:58:15.17341","indexId":"70237802","displayToPublicDate":"2010-12-02T09:01:03","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12793,"text":"Air Quality, Atmosphere & Health","active":true,"publicationSubtype":{"id":10}},"title":"Numerical simulations examining the possible role of anthropogenic and volcanic emissions during the 1997 Indonesian fires","docAbstract":"<p><span>The regional atmospheric chemistry and climate model REMOTE has been used to conduct numerical simulations of the atmosphere during the catastrophic Indonesian fires of 1997. These simulations represent one possible scenario of the event, utilizing the RETRO wildland fire emission database. Emissions from the fires dominate the atmospheric concentrations of O</span><sub>3</sub><span>, CO, NO</span><sub>2</sub><span>, and SO</span><sub>2</sub><span>&nbsp;creating many possible exceedances of the Indonesian air quality standards. The scenario described here suggests that urban anthropogenic emissions contributed to the poor air quality due primarily to the fires. The urban air pollution may have increased the total number of people exposed to exceedances of the O</span><sub>3</sub><span>&nbsp;1-h standard by 17%. Secondary O</span><sub>3</sub><span>&nbsp;from anthropogenic emissions enhanced the conversion of SO</span><sub>2</sub><span>&nbsp;released by the fires to&nbsp;</span><span class=\"mathjax-tex\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msubsup><mrow class=&quot;MJX-TeXAtom-ORD&quot;><mrow class=&quot;MJX-TeXAtom-ORD&quot;><mi mathvariant=&quot;normal&quot;>S</mi><mi mathvariant=&quot;normal&quot;>O</mi></mrow></mrow><mn>4</mn><mrow class=&quot;MJX-TeXAtom-ORD&quot;><mn>2</mn><mo>&amp;#x2212;</mo></mrow></msubsup></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msubsup\"><span id=\"MathJax-Span-4\" class=\"texatom\"><span id=\"MathJax-Span-5\" class=\"mrow\"><span id=\"MathJax-Span-6\" class=\"texatom\"><span id=\"MathJax-Span-7\" class=\"mrow\"><span id=\"MathJax-Span-8\" class=\"mi\">S</span><span id=\"MathJax-Span-9\" class=\"mi\">O</span></span></span></span></span><sup><span id=\"MathJax-Span-10\" class=\"texatom\"><span id=\"MathJax-Span-11\" class=\"mrow\"><span id=\"MathJax-Span-12\" class=\"mn\">2</span><span id=\"MathJax-Span-13\" class=\"mo\">−</span></span></span></sup><sub><span id=\"MathJax-Span-14\" class=\"mn\">4</span></sub></span></span></span></span></span></span><span>, demonstrating that the urban pollution actively altered the atmospheric behavior and lifetime of the fire emissions. Under the conditions present during the fires, volcanic SO</span><sub>2</sub><span>&nbsp;emissions had a negligible influence on surface pollution.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s11869-010-0105-4","usgsCitation":"Pfeffer, M.A., Langmann, B., Heil, A., and Graf, H., 2012, Numerical simulations examining the possible role of anthropogenic and volcanic emissions during the 1997 Indonesian fires: Air Quality, Atmosphere & Health, v. 5, p. 277-292, https://doi.org/10.1007/s11869-010-0105-4.","productDescription":"16 p.","startPage":"277","endPage":"292","ipdsId":"IP-015123","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":474698,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11869-010-0105-4","text":"Publisher Index Page"},{"id":408657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia, Indonesia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              117.5924087688469,\n              -22.044190232100448\n            ],\n            [\n              147.41177478692185,\n              -21.240008281154616\n            ],\n            [\n              143.1536814245564,\n              -10.581228199188786\n            ],\n            [\n              122.95751134770723,\n              3.5612064227482705\n            ],\n            [\n              115.25784717158785,\n              4.500549743223559\n            ],\n            [\n              114.82526028667945,\n              0.8421315654653654\n            ],\n            [\n              112.53337407375636,\n              1.3178108731174376\n            ],\n            [\n              109.22250289407305,\n              1.9046429719454494\n            ],\n            [\n              105.20040890559852,\n              -6.922567902936095\n            ],\n            [\n              117.5924087688469,\n              -22.044190232100448\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"5","noUsgsAuthors":false,"publicationDate":"2010-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Pfeffer, Melissa A.","contributorId":298479,"corporation":false,"usgs":false,"family":"Pfeffer","given":"Melissa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":855683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langmann, Barbel","contributorId":298485,"corporation":false,"usgs":false,"family":"Langmann","given":"Barbel","email":"","affiliations":[],"preferred":false,"id":855712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heil, Angelika","contributorId":213987,"corporation":false,"usgs":false,"family":"Heil","given":"Angelika","email":"","affiliations":[{"id":38956,"text":"Max Planck Institute for Meteorology, Environmental Modeling, Hamburg, Germany","active":true,"usgs":false}],"preferred":false,"id":855713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graf, Hans-F.","contributorId":298486,"corporation":false,"usgs":false,"family":"Graf","given":"Hans-F.","email":"","affiliations":[],"preferred":false,"id":855714,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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