{"pageNumber":"649","pageRowStart":"16200","pageSize":"25","recordCount":46883,"records":[{"id":70156874,"text":"70156874 - 2012 - Variance components estimation for continuous and discrete data, with emphasis on cross-classified sampling designs","interactions":[],"lastModifiedDate":"2015-08-31T16:53:52","indexId":"70156874","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Variance components estimation for continuous and discrete data, with emphasis on cross-classified sampling designs","docAbstract":"

Variance components may play multiple roles (cf. Cox and Solomon 2003). First, magnitudes and relative magnitudes of the variances of random factors may have important scientific and management value in their own right. For example, variation in levels of invasive vegetation among and within lakes may suggest causal agents that operate at both spatial scales – a finding that may be important for scientific and management reasons. Second, variance components may also be of interest when they affect precision of means and covariate coefficients. For example, variation in the effect of water depth on the probability of aquatic plant presence in a study of multiple lakes may vary by lake. This variation will affect the precision of the average depth-presence association. Third, variance component estimates may be used when designing studies, including monitoring programs. For example, to estimate the numbers of years and of samples per year required to meet long-term monitoring goals, investigators need estimates of within and among-year variances. Other chapters in this volume (Chapters 7, 8, and 10) as well as extensive external literature outline a framework for applying estimates of variance components to the design of monitoring efforts. For example, a series of papers with an ecological monitoring theme examined the relative importance of multiple sources of variation, including variation in means among sites, years, and site-years, for the purposes of temporal trend detection and estimation (Larsen et al. 2004, and references therein).

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Design and analysis of long-term ecological monitoring studies","language":"English","publisher":"Cambridge University Press","publisherLocation":"Cambridge; New York","doi":"10.1017/CBO9781139022422.013","usgsCitation":"Gray, B.R., 2012, Variance components estimation for continuous and discrete data, with emphasis on cross-classified sampling designs, chap. of Design and analysis of long-term ecological monitoring studies, p. 200-227, https://doi.org/10.1017/CBO9781139022422.013.","productDescription":"28 p.","startPage":"200","endPage":"227","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":307764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"560bb71ae4b058f706e53f84","contributors":{"editors":[{"text":"Gitzen, Robert A.","contributorId":75498,"corporation":false,"usgs":true,"family":"Gitzen","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":570915,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Millspaugh, Joshua J.","contributorId":11141,"corporation":false,"usgs":false,"family":"Millspaugh","given":"Joshua J.","affiliations":[],"preferred":false,"id":570916,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Cooper, Andrew B.","contributorId":112048,"corporation":false,"usgs":true,"family":"Cooper","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":570917,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Licht, Daniel S.","contributorId":113213,"corporation":false,"usgs":true,"family":"Licht","given":"Daniel S.","affiliations":[],"preferred":false,"id":570918,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":570914,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046353,"text":"70046353 - 2012 - Upper Klamath Basin Landsat Image for August 19, 2006: Path 44 Row 31","interactions":[],"lastModifiedDate":"2013-06-10T11:48:43","indexId":"70046353","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Upper Klamath Basin Landsat Image for August 19, 2006: Path 44 Row 31","docAbstract":"This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046353","usgsCitation":"Snyder, D.T., 2012, Upper Klamath Basin Landsat Image for August 19, 2006: Path 44 Row 31, Dataset, https://doi.org/10.3133/70046353.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273510,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/erosl1t_08202004_p45r30_l5_kl_NAD83.xml"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.382600,41.991760 ], [ -123.382600,43.492919 ], [ -120.601579,43.492919 ], [ -120.601579,41.991760 ], [ -123.382600,41.991760 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6f56ee4b0097a7158e613","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":479540,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159358,"text":"70159358 - 2012 - Maximizing the utility of monitoring to the adaptive management of natural resources","interactions":[],"lastModifiedDate":"2021-10-21T15:36:09.17483","indexId":"70159358","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Maximizing the utility of monitoring to the adaptive management of natural resources","docAbstract":"

Data collection is an important step in any investigation about the structure or processes related to a natural system. In a purely scientific investigation (experiments, quasi-experiments, observational studies), data collection is part of the scientific method, preceded by the identification of hypotheses and the design of any manipulations of the system to test those hypotheses. Data collection and the manipulations that precede it are ideally designed to maximize the information that is derived from the study. That is, such investigations should be designed for maximum power to evaluate the relative validity of the hypotheses posed. When data collection is intended to inform the management of ecological systems, we call it monitoring. Note that our definition of monitoring encompasses a broader range of data-collection efforts than some alternative definitions – e.g. Chapter 3. The purpose of monitoring as we use the term can vary, from surveillance or “thumb on the pulse” monitoring (see Nichols and Williams 2006), intended to detect changes in a system due to any non-specified source (e.g. the North American Breeding Bird Survey), to very specific and targeted monitoring of the results of specific management actions (e.g. banding and aerial survey efforts related to North American waterfowl harvest management). Although a role of surveillance monitoring is to detect unanticipated changes in a system, the same result is possible from a collection of targeted monitoring programs distributed across the same spatial range (Box 4.1). In the face of limited budgets and many specific management questions, tying monitoring as closely as possible to management needs is warranted (Nichols and Williams 2006). Adaptive resource management (ARM; Walters 1986, Williams 1997, Kendall 2001, Moore and Conroy 2006, McCarthy and Possingham 2007, Conroy et al. 2008a) provides a context and specific purpose for monitoring: to evaluate decisions with respect to achievement of specific management objectives; and to evaluate the relative validity of predictive system models. This latter purpose is analogous to the role of data collection within the scientific method, in a research context.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Design and analysis of long-term ecological monitoring studies","language":"English","publisher":"Cambridge University Press","publisherLocation":"Cambridge; New York","doi":"10.1017/CBO9781139022422.007","usgsCitation":"Kendall, W.L., and Moore, C., 2012, Maximizing the utility of monitoring to the adaptive management of natural resources, chap. of Design and analysis of long-term ecological monitoring studies, p. 74-98, https://doi.org/10.1017/CBO9781139022422.007.","productDescription":"24 p.","startPage":"74","endPage":"98","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028880","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":310570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562a08d8e4b011227bf1fd8a","contributors":{"editors":[{"text":"Gitzen, Robert A.","contributorId":75498,"corporation":false,"usgs":true,"family":"Gitzen","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":578197,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cooper, Andrew B.","contributorId":112048,"corporation":false,"usgs":true,"family":"Cooper","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":578198,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Millspaugh, Joshua J.","contributorId":11141,"corporation":false,"usgs":false,"family":"Millspaugh","given":"Joshua J.","affiliations":[],"preferred":false,"id":578199,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Licht, Daniel S.","contributorId":113213,"corporation":false,"usgs":true,"family":"Licht","given":"Daniel S.","affiliations":[],"preferred":false,"id":578200,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Kendall, William L. wkendall@usgs.gov","contributorId":406,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"wkendall@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":578195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Clinton T.","contributorId":9767,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton T.","affiliations":[],"preferred":false,"id":578196,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155848,"text":"70155848 - 2012 - Groundwater and surface-water exchange and resultingnNitrate dynamics in the Bogue Phalia Basin in northwestern Mississippi","interactions":[],"lastModifiedDate":"2022-11-15T16:09:38.395666","indexId":"70155848","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater and surface-water exchange and resultingnNitrate dynamics in the Bogue Phalia Basin in northwestern Mississippi","docAbstract":"

During April 2007 through September 2008, the USGS collected hydrogeologic and water-quality data from a site on the Bogue Phalia to evaluate the role of groundwater and surface-water interaction on the transport of nitrate to the shallow sand and gravel aquifer underlying the Mississippi Alluvial Plain in northwestern Mississippi. A two-dimensional groundwater/surface-water exchange model was developed using temperature and head data and VS2DH, a variably saturated flow and energy transport model. Results from this model showed that groundwater/surface-water exchange at the site occurred regularly and recharge was laterally extensive into the alluvial aquifer. Nitrate was consistently reported in surface-water samples (n = 52, median concentration = 39.8 μmol/L) although never detected in samples collected from in-stream piezometers or shallow monitoring wells adjacent to the stream (n = 46). These two facts, consistent detections of nitrate in surface water and no detections of nitrate in groundwater, coupled with model results that indicate large amounts of surface water moving through an anoxic streambed, support the case for denitrification and nitrate loss through the streambed.

","language":"English","publisher":"Alliance of Crop, Soil, and Environmental Science Societies","doi":"10.2134/jeq2011.0087","usgsCitation":"Barlow, J.R., and Coupe, R.H., 2012, Groundwater and surface-water exchange and resultingnNitrate dynamics in the Bogue Phalia Basin in northwestern Mississippi: Journal of Environmental Quality, v. 41, no. 1, p. 155-169, https://doi.org/10.2134/jeq2011.0087.","productDescription":"15 p.","startPage":"155","endPage":"169","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-024197","costCenters":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"links":[{"id":381802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Bogue Phalia Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.20421710355372,\n 34.156863209912004\n ],\n [\n -90.75054266585917,\n 34.156863209912004\n ],\n [\n -90.8764117905081,\n 34.12139801584064\n ],\n [\n -91.1361842392514,\n 33.60994504300518\n ],\n [\n -91.05316417831278,\n 33.117872488161694\n ],\n [\n -90.22296356892653,\n 33.129086822630626\n ],\n [\n -90.20689517003508,\n 34.156863209912004\n ],\n [\n -90.20421710355372,\n 34.156863209912004\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2012-01-01","publicationStatus":"PW","scienceBaseUri":"55cc6e29e4b08400b1fe0fd2","contributors":{"authors":[{"text":"Barlow, Jeannie R. B. 0000-0002-0799-4656 jbarlow@usgs.gov","orcid":"https://orcid.org/0000-0002-0799-4656","contributorId":3701,"corporation":false,"usgs":true,"family":"Barlow","given":"Jeannie","email":"jbarlow@usgs.gov","middleInitial":"R. B.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":566594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coupe, Richard H. 0000-0001-8679-1015 rhcoupe@usgs.gov","orcid":"https://orcid.org/0000-0001-8679-1015","contributorId":551,"corporation":false,"usgs":true,"family":"Coupe","given":"Richard","email":"rhcoupe@usgs.gov","middleInitial":"H.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"preferred":true,"id":566595,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70032540,"text":"70032540 - 2012 - A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data","interactions":[],"lastModifiedDate":"2020-11-30T21:58:43.196979","indexId":"70032540","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data","docAbstract":"

Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004–2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance model for (i) quantitative assessment of the impact of basin developmental activities on lake levels and for (ii) forecasting lake level changes and their impact on fisheries. From this study, we suggest that globally available satellite altimetry data provide a unique opportunity for calibration and validation of hydrologic models in ungauged basins.

","language":"English","publisher":"European Geosciences Union","publisherLocation":"Munich, Germany","doi":"10.5194/hess-16-1-2012","issn":"10275606","usgsCitation":"Velpuri, N., Senay, G., and Asante, K., 2012, A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data: Hydrology and Earth System Sciences, v. 16, no. 1, p. 1-18, https://doi.org/10.5194/hess-16-1-2012.","productDescription":"18 p.","startPage":"1","endPage":"18","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474744,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-16-1-2012","text":"Publisher Index Page"},{"id":241758,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214070,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/hess-16-1-2012"}],"country":"Kenya","otherGeospatial":"Lake Turkana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 35.79345703125,\n 2.4162756547063857\n ],\n [\n 36.8701171875,\n 2.4162756547063857\n ],\n [\n 36.8701171875,\n 4.718777551249855\n ],\n [\n 35.79345703125,\n 4.718777551249855\n ],\n [\n 35.79345703125,\n 2.4162756547063857\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-03","publicationStatus":"PW","scienceBaseUri":"5059e48be4b0c8380cd466ee","contributors":{"authors":[{"text":"Velpuri, N.M. 0000-0002-6370-1926","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":66495,"corporation":false,"usgs":true,"family":"Velpuri","given":"N.M.","affiliations":[],"preferred":false,"id":436730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":152206,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","email":"senay@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":436729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asante, K.O. 0000-0001-5408-1852","orcid":"https://orcid.org/0000-0001-5408-1852","contributorId":17051,"corporation":false,"usgs":true,"family":"Asante","given":"K.O.","affiliations":[],"preferred":false,"id":436728,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70032500,"text":"70032500 - 2012 - Why farmers adopt best management practice in the United States: A meta-analysis of the adoption literature","interactions":[],"lastModifiedDate":"2013-01-10T14:03:22","indexId":"70032500","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Why farmers adopt best management practice in the United States: A meta-analysis of the adoption literature","docAbstract":"This meta-analysis of both published and unpublished studies assesses factors believed to influence adoption of agricultural Best Management Practices in the United States. Using an established statistical technique to summarize the adoption literature in the United States, we identified the following variables as having the largest impact on adoption: access to and quality of information, financial capacity, and being connected to agency or local networks of farmers or watershed groups. This study shows that various approaches to data collection affect the results and comparability of adoption studies. In particular, environmental awareness and farmer attitudes have been inconsistently used and measured across the literature. This meta-analysis concludes with suggestions regarding the future direction of adoption studies, along with guidelines for how data should be presented to enhance the adoption of conservation practices and guide research.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jenvman.2011.10.006","issn":"03014797","usgsCitation":"Baumgart-Getz, A., Stalker Prokopy, L., and Floress, K., 2012, Why farmers adopt best management practice in the United States: A meta-analysis of the adoption literature: Journal of Environmental Management, v. 96, no. 1, p. 17-25, https://doi.org/10.1016/j.jenvman.2011.10.006.","productDescription":"9 p.","startPage":"17","endPage":"25","numberOfPages":"9","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":214033,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jenvman.2011.10.006"},{"id":241720,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"96","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bd0a2e4b08c986b32ef8e","contributors":{"authors":[{"text":"Baumgart-Getz, Adam","contributorId":44365,"corporation":false,"usgs":true,"family":"Baumgart-Getz","given":"Adam","email":"","affiliations":[],"preferred":false,"id":436493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stalker Prokopy, Linda","contributorId":73419,"corporation":false,"usgs":true,"family":"Stalker Prokopy","given":"Linda","email":"","affiliations":[],"preferred":false,"id":436494,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Floress, Kristin","contributorId":106326,"corporation":false,"usgs":true,"family":"Floress","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":436495,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70032301,"text":"70032301 - 2012 - Trophic cascades linking wolves (Canis lupus), coyotes (Canis latrans), and small mammals","interactions":[],"lastModifiedDate":"2012-03-12T17:21:29","indexId":"70032301","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Trophic cascades linking wolves (Canis lupus), coyotes (Canis latrans), and small mammals","docAbstract":"When large carnivores are extirpated from ecosystems that evolved with apex predators, these systems can change at the herbivore and plant trophic levels. Such changes across trophic levels are called cascading effects and they are very important to conservation. Studies on the effects of reintroduced wolves in Yellowstone National Park have examined the interaction pathway of wolves (Canis lupus L., 1758) to ungulates to plants. This study examines the interaction effects of wolves to coyotes to rodents (reversing mesopredator release in the absence of wolves). Coyotes (Canis latrans Say, 1823) generally avoided areas near a wolf den. However, when in the proximity of a den, they used woody habitats (pine or sage) compared with herbaceous habitats (grass or forb or sedge)- when they were away from the wolf den. Our data suggested a significant increase in rodent numbers, particularly voles (genus Microtus Schrank, 1798), during the 3-year study on plots that were within 3 km of the wolf den, but we did not detect a significant change in rodent numbers over time for more distant plots. Predation by coyotes may have depressed numbers of small mammals in areas away from the wolf den. These factors indicate a top-down effect by wolves on coyotes and subsequently on the rodents of the area. Restoration of wolves could be a powerful tool for regulating predation at lower trophic levels.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Zoology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1139/Z11-115","issn":"00084301","usgsCitation":"Miller, B., Harlow, H., Harlow, T., Biggins, D., and Ripple, W.J., 2012, Trophic cascades linking wolves (Canis lupus), coyotes (Canis latrans), and small mammals: Canadian Journal of Zoology, v. 90, no. 1, p. 70-78, https://doi.org/10.1139/Z11-115.","startPage":"70","endPage":"78","numberOfPages":"9","costCenters":[],"links":[{"id":215040,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1139/Z11-115"},{"id":242809,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bb882e4b08c986b3278ca","contributors":{"authors":[{"text":"Miller, B.J.","contributorId":17173,"corporation":false,"usgs":true,"family":"Miller","given":"B.J.","email":"","affiliations":[],"preferred":false,"id":435505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harlow, H.J.","contributorId":20178,"corporation":false,"usgs":true,"family":"Harlow","given":"H.J.","email":"","affiliations":[],"preferred":false,"id":435506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harlow, T.S.","contributorId":15849,"corporation":false,"usgs":true,"family":"Harlow","given":"T.S.","email":"","affiliations":[],"preferred":false,"id":435504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Biggins, D.","contributorId":53343,"corporation":false,"usgs":true,"family":"Biggins","given":"D.","affiliations":[],"preferred":false,"id":435508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ripple, W. J.","contributorId":36333,"corporation":false,"usgs":true,"family":"Ripple","given":"W.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":435507,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70032294,"text":"70032294 - 2012 - The effect of diagenesis and fluid migration on rare earth element distribution in pore fluids of the northern Cascadia accretionary margin","interactions":[],"lastModifiedDate":"2013-04-25T13:32:35","indexId":"70032294","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"The effect of diagenesis and fluid migration on rare earth element distribution in pore fluids of the northern Cascadia accretionary margin","docAbstract":"Analytical challenges in obtaining high quality measurements of rare earth elements (REEs) from small pore fluid volumes have limited the application of REEs as deep fluid geochemical tracers. Using a recently developed analytical technique, we analyzed REEs from pore fluids collected from Sites U1325 and U1329, drilled on the northern Cascadia margin during the Integrated Ocean Drilling Program (IODP) Expedition 311, to investigate the REE behavior during diagenesis and their utility as tracers of deep fluid migration. These sites were selected because they represent contrasting settings on an accretionary margin: a ponded basin at the toe of the margin, and the landward Tofino Basin near the shelf's edge. REE concentrations of pore fluid in the methanogenic zone at Sites U1325 and U1329 correlate positively with concentrations of dissolved organic carbon (DOC) and alkalinity. Fractionations across the REE series are driven by preferential complexation of the heavy REEs. Simultaneous enrichment of diagenetic indicators (DOC and alkalinity) and of REEs (in particular the heavy elements Ho to Lu), suggests that the heavy REEs are released during particulate organic carbon (POC) degradation and are subsequently chelated by DOC. REE concentrations are greater at Site U1325, a site where shorter residence times of POC in sulfate-bearing redox zones may enhance REE burial efficiency within sulfidic and methanogenic sediment zones where REE release ensues. Cross-plots of La concentrations versus Cl, Li and Sr delineate a distinct field for the deep fluids (z > 75 mbsf) at Site U1329, and indicate the presence of a fluid not observed at the other sites drilled on the Cascadia margin. Changes in REE patterns, the presence of a positive Eu anomaly, and other available geochemical data for this site suggest a complex hydrology and possible interaction with the igneous Crescent Terrane, located east of the drilled transect.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Chemical Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2011.10.010","issn":"00092541","usgsCitation":"Kim, J., Torres, M.E., Haley, B.A., Kastner, M., Pohlman, J., Riedel, M., and Lee, Y., 2012, The effect of diagenesis and fluid migration on rare earth element distribution in pore fluids of the northern Cascadia accretionary margin: Chemical Geology, v. 291, p. 152-165, https://doi.org/10.1016/j.chemgeo.2011.10.010.","productDescription":"14 p.","startPage":"152","endPage":"165","numberOfPages":"14","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":214915,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.chemgeo.2011.10.010"},{"id":242675,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada;United States","city":"Vancouver","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01611111111111111,0.0011111111111111111 ], [ -0.01611111111111111,0.001388888888888889 ], [ -0.01611111111111111,0.001388888888888889 ], [ -0.01611111111111111,0.0011111111111111111 ], [ -0.01611111111111111,0.0011111111111111111 ] ] ] } } ] }","volume":"291","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bab1fe4b08c986b322c30","contributors":{"authors":[{"text":"Kim, Ji-Hoon","contributorId":105547,"corporation":false,"usgs":true,"family":"Kim","given":"Ji-Hoon","email":"","affiliations":[],"preferred":false,"id":435487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torres, Marta E.","contributorId":33546,"corporation":false,"usgs":true,"family":"Torres","given":"Marta","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":435483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haley, Brian A.","contributorId":43996,"corporation":false,"usgs":true,"family":"Haley","given":"Brian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":435484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kastner, Miriam","contributorId":24187,"corporation":false,"usgs":true,"family":"Kastner","given":"Miriam","email":"","affiliations":[],"preferred":false,"id":435482,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pohlman, John W.","contributorId":95288,"corporation":false,"usgs":true,"family":"Pohlman","given":"John W.","affiliations":[],"preferred":false,"id":435486,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Riedel, Michael","contributorId":7518,"corporation":false,"usgs":true,"family":"Riedel","given":"Michael","email":"","affiliations":[],"preferred":false,"id":435481,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lee, Young-Joo","contributorId":82548,"corporation":false,"usgs":true,"family":"Lee","given":"Young-Joo","email":"","affiliations":[],"preferred":false,"id":435485,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70032316,"text":"70032316 - 2012 - Intelligent estimation of spatially distributed soil physical properties","interactions":[],"lastModifiedDate":"2020-12-02T21:51:46.727938","indexId":"70032316","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"Intelligent estimation of spatially distributed soil physical properties","docAbstract":"

Spatial analysis of soil samples is often times not possible when measurements are limited in number or clustered. To obviate potential problems, we propose a new approach based on the self-organizing map (SOM) technique. This approach exploits underlying nonlinear relation of the steady-state geomorphic concave–convex nature of hillslopes (from hilltop to bottom of the valley) to spatially limited soil textural data. The topographic features are extracted from Shuttle Radar Topographic Mission elevation data; whereas soil textural (clay, silt, and sand) and hydraulic data were collected in 29 spatially random locations (50 to 75 cm depth). In contrast to traditional principal component analysis, the SOM identifies relations among relief features, such as, slope, horizontal curvature and vertical curvature. Stochastic cross-validation indicates that the SOM is unbiased and provides a way to measure the magnitude of prediction uncertainty for all variables. The SOM cross-component plots of the soil texture reveals higher clay proportions at concave areas with convergent hydrological flux and lower proportions for convex areas with divergent flux. The sand ratio has an opposite pattern with higher values near the ridge and lower values near the valley. Silt has a trend similar to sand, although less pronounced. The relation between soil texture and concave–convex hillslope features reveals that subsurface weathering and transport is an important process that changed from loss-to-gain at the rectilinear hillslope point. These results illustrate that the SOM can be used to capture and predict nonlinear hillslope relations among relief, soil texture, and hydraulic conductivity data.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2011.11.002","issn":"00167061","usgsCitation":"Iwashita, F., Friedel, M.J., Ribeiro, G., and Fraser, S.J., 2012, Intelligent estimation of spatially distributed soil physical properties: Geoderma, v. 170, p. 1-10, https://doi.org/10.1016/j.geoderma.2011.11.002.","productDescription":"10 p.","startPage":"1","endPage":"10","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":242483,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214733,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geoderma.2011.11.002"}],"volume":"170","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3c98e4b0c8380cd62e87","contributors":{"authors":[{"text":"Iwashita, F.","contributorId":96912,"corporation":false,"usgs":true,"family":"Iwashita","given":"F.","affiliations":[],"preferred":false,"id":435582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friedel, Michael J. 0000-0002-5060-3999 mfriedel@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":595,"corporation":false,"usgs":true,"family":"Friedel","given":"Michael","email":"mfriedel@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":435581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ribeiro, G.F.","contributorId":60032,"corporation":false,"usgs":true,"family":"Ribeiro","given":"G.F.","email":"","affiliations":[],"preferred":false,"id":435579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fraser, Stephen J.","contributorId":87769,"corporation":false,"usgs":true,"family":"Fraser","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":435580,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032318,"text":"70032318 - 2012 - Experimental determination of soil heat storage for the simulation of heat transport in a coastal wetland","interactions":[],"lastModifiedDate":"2020-12-03T13:01:40.584017","indexId":"70032318","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Experimental determination of soil heat storage for the simulation of heat transport in a coastal wetland","docAbstract":"

Two physical experiments were developed to better define the thermal interaction of wetland water and the underlying soil layer. This information is important to numerical models of flow and heat transport that have been developed to support biological studies in the South Florida coastal wetland areas. The experimental apparatus consists of two 1.32 m diameter by 0.99 m tall, trailer-mounted, well-insulated tanks filled with soil and water. A peat–sand–soil mixture was used to represent the wetland soil, and artificial plants were used as a surrogate for emergent wetland vegetation based on size and density observed in the field. The tanks are instrumented with thermocouples to measure vertical and horizontal temperature variations and were placed in an outdoor environment subject to solar radiation, wind, and other factors affecting the heat transfer. Instruments also measure solar radiation, relative humidity, and wind speed.

Tests indicate that heat transfer through the sides and bottoms of the tanks is negligible, so the experiments represent vertical heat transfer effects only. The temperature fluctuations measured in the vertical profile through the soil and water are used to calibrate a one-dimensional heat-transport model. The model was used to calculate the thermal conductivity of the soil. Additionally, the model was used to calculate the total heat stored in the soil. This information was then used in a lumped parameter model to calculate an effective depth of soil which provides the appropriate heat storage to be combined with the heat storage in the water column. An effective depth, in the model, of 5.1 cm of wetland soil represents the heat storage needed to match the data taken in the tank containing 55.9 cm of peat/sand/soil mix. The artificial low-density laboratory sawgrass reduced the solar energy absorbed by the 35.6 cm of water and 55.9 cm of soil at midday by less than 5%. The maximum heat transfer into the underlying peat–sand–soil mix lags behind maximum solar radiation by approximately 2 h. A slightly longer temperature lag was observed between the maximum solar radiation and maximum water temperature both with and without soil.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2011.12.036","issn":"00221694","usgsCitation":"Swain, M., Swain, M., Lohmann, M., and Swain, E., 2012, Experimental determination of soil heat storage for the simulation of heat transport in a coastal wetland: Journal of Hydrology, v. 422-423, p. 53-62, https://doi.org/10.1016/j.jhydrol.2011.12.036.","productDescription":"10 p.","startPage":"53","endPage":"62","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":242515,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"422-423","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0dc5e4b0c8380cd531b0","contributors":{"authors":[{"text":"Swain, Michael","contributorId":79716,"corporation":false,"usgs":true,"family":"Swain","given":"Michael","email":"","affiliations":[],"preferred":false,"id":435586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swain, Matthew","contributorId":68126,"corporation":false,"usgs":true,"family":"Swain","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":435585,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lohmann, Melinda 0000-0003-1472-159X mlohmann@usgs.gov","orcid":"https://orcid.org/0000-0003-1472-159X","contributorId":2971,"corporation":false,"usgs":true,"family":"Lohmann","given":"Melinda","email":"mlohmann@usgs.gov","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":435583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swain, Eric 0000-0001-7168-708X","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":23347,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","affiliations":[],"preferred":false,"id":435584,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032574,"text":"70032574 - 2012 - Regional scale impacts of Tamarix leaf beetles (Diorhabda carinulata) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods","interactions":[],"lastModifiedDate":"2017-11-25T14:17:42","indexId":"70032574","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Regional scale impacts of Tamarix leaf beetles (Diorhabda carinulata) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods","docAbstract":"Tamarix leaf beetles (Diorhabda carinulata) have been widely released on western U.S. rivers to control introduced shrubs in the genus Tamarix. Part of the motivation to control Tamarix is to salvage water for human use. Information is needed on the impact of beetles on Tamarix seasonal leaf production and subsequent water use overwide areas andmultiple cycles of annual defoliation.Herewe combine ground data with high resolution phenocam imagery and moderate resolution (Landsat) and coarser resolution (MODIS) satellite imagery to test the effects of beetles on Tamarix evapotranspiration (ET) and leaf phenology at sites on six western rivers. Satellite imagery covered the period 2000 to 2010 which encompassed years before and after beetle release at each study site. Phenocam images showed that beetles reduced green leaf cover of individual canopies by about 30% during a 6-8 week period in summer, but plants produced new leaves after beetles became dormant in August, and over three years no net reduction in peak summer leaf production was noted. ETwas estimated by vegetation index methods, and both Landsat and MODIS analyses showed that beetles reduced ET markedly in the first year of defoliation, but ET recovered in subsequent years. Over all six sites, ET decreased by 14% to 15% by Landsat and MODIS estimates, respectively. However, resultswere variable among sites, ranging fromno apparent effect on ET to substantial reduction in ET. Baseline ET rates before defoliation were low, 394 mmyr-1 by Landsat and 314 mm yr-1 by MODIS estimates (20-25% of potential ET), further constraining the amount of water that could be salvaged. Beetle-Tamarix interactions are in their early stage of development on this continent and it is too soon to predict the eventual extent towhich Tamarix populationswill be reduced. The utility of remote sensing methods for monitoring defoliation was constrained by the small area covered by each phenocamimage, the low temporal resolution of Landsat, and the lowspatial resolution ofMODIS imagery. Even combined image sets did not adequately reveal the details of the defoliation process, and remote sensing data should be combined with ground observations to develop operational monitoring protocols.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2011.11.011","issn":"00344257","usgsCitation":"Nagler, P.L., Brown, T., Hultine, K.R., van Riper, C., Bean, D., Dennison, P.E., Murray, R.S., and Glenn, E.P., 2012, Regional scale impacts of Tamarix leaf beetles (Diorhabda carinulata) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods: Remote Sensing of Environment, v. 118, p. 227-240, https://doi.org/10.1016/j.rse.2011.11.011.","productDescription":"14 p.","startPage":"227","endPage":"240","numberOfPages":"14","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":241759,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214071,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2011.11.011"}],"country":"United States","state":"Colorado;Nevada;Utah;Wyoming","otherGeospatial":"Big Horn River;Humbolt River;Lower Delores River;Middle-upper Delores River;Upper Colorado River;Walker River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.0800,37.0000 ], [ -120.0800,45.0000 ], [ -106.3000,45.0000 ], [ -106.3000,37.0000 ], [ -120.0800,37.0000 ] ] ] } } ] }","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50788eb2e4b0cfc2d59f5b0d","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":436882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Tim","contributorId":17841,"corporation":false,"usgs":true,"family":"Brown","given":"Tim","affiliations":[],"preferred":false,"id":436884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hultine, Kevin R. 0000-0001-9747-6037","orcid":"https://orcid.org/0000-0001-9747-6037","contributorId":23772,"corporation":false,"usgs":true,"family":"Hultine","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":436886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":436888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bean, Daniel W.","contributorId":11016,"corporation":false,"usgs":false,"family":"Bean","given":"Daniel W.","affiliations":[{"id":16124,"text":"Colorado Department of Agriculture, Biological Pest Control","active":true,"usgs":false}],"preferred":false,"id":436883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dennison, Philip E.","contributorId":105132,"corporation":false,"usgs":true,"family":"Dennison","given":"Philip","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":436889,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murray, R. Scott","contributorId":64468,"corporation":false,"usgs":true,"family":"Murray","given":"R.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":436887,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":436885,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70032573,"text":"70032573 - 2012 - Ecoregional analysis of nearshore sea-surface temperature in the North Pacific","interactions":[],"lastModifiedDate":"2016-05-03T16:03:45","indexId":"70032573","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":"Ecoregional analysis of nearshore sea-surface temperature in the North Pacific","docAbstract":"
\n

The quantification and description of sea surface temperature (SST) is critically important because it can influence the distribution, migration, and invasion of marine species; furthermore, SSTs are expected to be affected by climate change. To better understand present temperature regimes, we assembled a 29-year nearshore time series of mean monthly SSTs along the North Pacific coastline using remotely-sensed satellite data collected with the Advanced Very High Resolution Radiometer (AVHRR) instrument. We then used the dataset to describe nearshore (<20 km offshore) SST patterns of 16 North Pacific ecoregions delineated by the Marine Ecoregions of the World (MEOW) hierarchical schema. Annual mean temperature varied from 3.8°C along the Kamchatka ecoregion to 24.8°C in the Cortezian ecoregion. There are smaller annual ranges and less variability in SST in the Northeast Pacific relative to the Northwest Pacific. Within the 16 ecoregions, 31–94% of the variance in SST is explained by the annual cycle, with the annual cycle explaining the least variation in the Northern California ecoregion and the most variation in the Yellow Sea ecoregion. Clustering on mean monthly SSTs of each ecoregion showed a clear break between the ecoregions within the Warm and Cold Temperate provinces of the MEOW schema, though several of the ecoregions contained within the provinces did not show a significant difference in mean seasonal temperature patterns. Comparison of these temperature patterns shared some similarities and differences with previous biogeographic classifications and the Large Marine Ecosystems (LMEs). Finally, we provide a web link to the processed data for use by other researchers.

\n

 

\n
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0030105","issn":"19326203","usgsCitation":"Payne, M., Brown, C., Reusser, D., and Lee, H., 2012, Ecoregional analysis of nearshore sea-surface temperature in the North Pacific: PLoS ONE, v. 7, no. 1, e30105, 12 p., https://doi.org/10.1371/journal.pone.0030105.","productDescription":"e30105, 12 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":474745,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0030105","text":"Publisher Index Page"},{"id":241726,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-11","publicationStatus":"PW","scienceBaseUri":"505a0594e4b0c8380cd50e61","contributors":{"authors":[{"text":"Payne, M.C.","contributorId":93271,"corporation":false,"usgs":true,"family":"Payne","given":"M.C.","email":"","affiliations":[],"preferred":false,"id":436881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, C.A.","contributorId":71776,"corporation":false,"usgs":true,"family":"Brown","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":436880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reusser, D.A.","contributorId":61251,"corporation":false,"usgs":true,"family":"Reusser","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":436879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, H. II","contributorId":9077,"corporation":false,"usgs":true,"family":"Lee","given":"H.","suffix":"II","affiliations":[],"preferred":false,"id":436878,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032565,"text":"70032565 - 2012 - Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains","interactions":[],"lastModifiedDate":"2018-02-23T13:12:35","indexId":"70032565","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains","docAbstract":"Flux tower networks (e. g., AmeriFlux, Agriflux) provide continuous observations of ecosystem exchanges of carbon (e. g., net ecosystem exchange), water vapor (e. g., evapotranspiration), and energy between terrestrial ecosystems and the atmosphere. The long-term time series of flux tower data are essential for studying and understanding terrestrial carbon cycles, ecosystem services, and climate changes. Currently, there are 13 flux towers located within the Great Plains (GP). The towers are sparsely distributed and do not adequately represent the varieties of vegetation cover types, climate conditions, and geophysical and biophysical conditions in the GP. This study assessed how well the available flux towers represent the environmental conditions or \"ecological envelopes\" across the GP and identified optimal locations for future flux towers in the GP. Regression-based remote sensing and weather-driven net ecosystem production (NEP) models derived from different extrapolation ranges (10 and 50%) were used to identify areas where ecological conditions were poorly represented by the flux tower sites and years previously used for mapping grassland fluxes. The optimal lands suitable for future flux towers within the GP were mapped. Results from this study provide information to optimize the usefulness of future flux towers in the GP and serve as a proxy for the uncertainty of the NEP map.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landscape Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1007/s10980-011-9699-7","issn":"09212973","usgsCitation":"Gu, Y., Howard, D., Wylie, B.K., and Zhang, L., 2012, Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains: Landscape Ecology, v. 27, no. 3, p. 319-326, https://doi.org/10.1007/s10980-011-9699-7.","startPage":"319","endPage":"326","numberOfPages":"8","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":241589,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213917,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10980-011-9699-7"}],"volume":"27","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-12-28","publicationStatus":"PW","scienceBaseUri":"505a5053e4b0c8380cd6b5f1","contributors":{"authors":[{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":139586,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":436837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howard, Daniel M. 0000-0002-7563-7538 dhoward@usgs.gov","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":139585,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel M.","email":"dhoward@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":436836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":436838,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhang, Li","contributorId":98139,"corporation":false,"usgs":true,"family":"Zhang","given":"Li","affiliations":[],"preferred":false,"id":436839,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032630,"text":"70032630 - 2012 - Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests","interactions":[],"lastModifiedDate":"2013-06-20T10:22:30","indexId":"70032630","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests","docAbstract":"The timing of spring leaf development, trajectories of summer leaf area, and the timing of autumn senescence have profound impacts to the water, carbon, and energy balance of ecosystems, and are likely influenced by global climate change. Limited field-based and remote-sensing observations have suggested complex spatial patterns related to geographic features that influence climate. However, much of this variability occurs at spatial scales that inhibit a detailed understanding of even the dominant drivers. Recognizing these limitations, we used nonlinear inverse modeling of medium-resolution remote sensing data, organized by day of year, to explore the influence of climate-related landscape factors on the timing of spring and autumn leaf-area trajectories in mid-Atlantic, USA forests. We also examined the extent to which declining summer greenness (greendown) degrades the precision and accuracy of observations of autumn offset of greenness. Of the dominant drivers of landscape phenology, elevation was the strongest, explaining up to 70% of the spatial variation in the onset of greenness. Urban land cover was second in importance, influencing spring onset and autumn offset to a distance of 32 km from large cities. Distance to tidal water also influenced phenological timing, but only within ~5 km of shorelines. Additionally, we observed that (i) growing season length unexpectedly increases with increasing elevation at elevations below 275 m; (ii) along gradients in urban land cover, timing of autumn offset has a stronger effect on growing season length than does timing of spring onset; and (iii) summer greendown introduces bias and uncertainty into observations of the autumn offset of greenness. These results demonstrate the power of medium grain analyses of landscape-scale phenology for understanding environmental controls on growing season length, and predicting how these might be affected by climate change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Global Change Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1365-2486.2011.02521.x","issn":"13541013","usgsCitation":"Elmore, A., Guinn, S., Minsley, B., and Richardson, A., 2012, Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests: Global Change Biology, v. 18, no. 2, p. 656-674, https://doi.org/10.1111/j.1365-2486.2011.02521.x.","productDescription":"19 p.","startPage":"656","endPage":"674","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":241560,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213892,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2486.2011.02521.x"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-09-19","publicationStatus":"PW","scienceBaseUri":"505a4408e4b0c8380cd667c5","contributors":{"authors":[{"text":"Elmore, A.J.","contributorId":103095,"corporation":false,"usgs":true,"family":"Elmore","given":"A.J.","email":"","affiliations":[],"preferred":false,"id":437138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guinn, S.M.","contributorId":35552,"corporation":false,"usgs":true,"family":"Guinn","given":"S.M.","email":"","affiliations":[],"preferred":false,"id":437136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minsley, B. J.","contributorId":52107,"corporation":false,"usgs":true,"family":"Minsley","given":"B. J.","affiliations":[],"preferred":false,"id":437137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richardson, A.D.","contributorId":10629,"corporation":false,"usgs":true,"family":"Richardson","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":437135,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032661,"text":"70032661 - 2012 - Climatic forcing of Quaternary deep-sea benthic communities in the North Pacific Ocean","interactions":[],"lastModifiedDate":"2013-04-21T16:54:18","indexId":"70032661","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3001,"text":"Paleobiology","active":true,"publicationSubtype":{"id":10}},"title":"Climatic forcing of Quaternary deep-sea benthic communities in the North Pacific Ocean","docAbstract":"There is growing evidence that changes in deep-sea benthic ecosystems are modulated by climate changes, but most evidence to date comes from the North Atlantic Ocean. Here we analyze new ostracod and published foraminiferal records for the last 250,000 years on Shatsky Rise in the North Pacific Ocean. Using linear models, we evaluate statistically the ability of environmental drivers (temperature, productivity, and seasonality of productivity) to predict changes in faunal diversity, abundance, and composition. These microfossil data show glacial-interglacial shifts in overall abundances and species diversities that are low during glacial intervals and high during interglacials. These patterns replicate those previously documented in the North Atlantic Ocean, suggesting that the climatic forcing of the deep-sea ecosystem is widespread, and possibly global in nature. However, these results also reveal differences with prior studies that probably reflect the isolated nature of Shatsky Rise as a remote oceanic plateau. Ostracod assemblages on Shatsky Rise are highly endemic but of low diversity, consistent with the limited dispersal potential of these animals. Benthic foraminifera, by contrast, have much greater dispersal ability and their assemblages at Shatsky Rise show diversities typical for deep-sea faunas in other regions. Statistical analyses also reveal ostracod-foraminferal differences in relationships between environmental drivers and biotic change. Rarefied diversity is best explained as a hump-shaped function of surface productivity in ostracods, but as having a weak and positive relationship with temperature in foraminifera. Abundance shows a positive relationship with both productivity and seasonality of productivity in foraminifera, and a hump-shaped relationship with productivity in ostracods. Finally, species composition in ostracods is influenced by both temperature and productivity, but only a temperature effect is evident in foraminifera. Though complex in detail, the global-scale link between deep-sea ecosystems and Quaternary climate changes underscores the importance of the interaction between the physical and biological components of paleoceanographical research for better understanding the history of the biosphere.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Paleobiology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Paleontological Society","publisherLocation":"http://www.paleosoc.org/","doi":"10.1666/10068.1","issn":"00948373","usgsCitation":"Yasuhara, M., Hunt, G., Cronin, T.M., Hokanishi, N., Kawahata, H., Tsujimoto, A., and Ishitake, M., 2012, Climatic forcing of Quaternary deep-sea benthic communities in the North Pacific Ocean: Paleobiology, v. 38, no. 1, p. 162-179, https://doi.org/10.1666/10068.1.","productDescription":"18 p.","startPage":"162","endPage":"179","costCenters":[],"links":[{"id":213894,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1666/10068.1"},{"id":241562,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Pacific Ocean","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 128.7,-85.6 ], [ 128.7,58.2 ], [ -66.5,58.2 ], [ -66.5,-85.6 ], [ 128.7,-85.6 ] ] ] } } ] }","volume":"38","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f666e4b0c8380cd4c737","contributors":{"authors":[{"text":"Yasuhara, Moriaki","contributorId":37935,"corporation":false,"usgs":true,"family":"Yasuhara","given":"Moriaki","affiliations":[],"preferred":false,"id":437332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, G.","contributorId":97699,"corporation":false,"usgs":true,"family":"Hunt","given":"G.","email":"","affiliations":[],"preferred":false,"id":437337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cronin, T. M. 0000-0002-2643-0979","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":42613,"corporation":false,"usgs":true,"family":"Cronin","given":"T.","email":"","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":false,"id":437333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hokanishi, N.","contributorId":34331,"corporation":false,"usgs":true,"family":"Hokanishi","given":"N.","email":"","affiliations":[],"preferred":false,"id":437331,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kawahata, H.","contributorId":90549,"corporation":false,"usgs":true,"family":"Kawahata","given":"H.","email":"","affiliations":[],"preferred":false,"id":437336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tsujimoto, Akira","contributorId":58448,"corporation":false,"usgs":true,"family":"Tsujimoto","given":"Akira","email":"","affiliations":[],"preferred":false,"id":437335,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ishitake, M.","contributorId":47988,"corporation":false,"usgs":true,"family":"Ishitake","given":"M.","email":"","affiliations":[],"preferred":false,"id":437334,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70032468,"text":"70032468 - 2012 - Oxygen and sulfur isotope systematics of sulfate produced during abiotic and bacterial oxidation of sphalerite and elemental sulfur","interactions":[],"lastModifiedDate":"2020-12-02T12:51:10.868614","indexId":"70032468","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Oxygen and sulfur isotope systematics of sulfate produced during abiotic and bacterial oxidation of sphalerite and elemental sulfur","docAbstract":"

Studies of metal sulfide oxidation in acid mine drainage (AMD) systems have primarily focused on pyrite oxidation, although acid soluble sulfides (e.g., ZnS) are predominantly responsible for the release of toxic metals. We conducted a series of biological and abiotic laboratory oxidation experiments with pure and Fe-bearing sphalerite (ZnS & Zn0.88Fe0.12S), respectively, in order to better understand the effects of sulfide mineralogy and associated biogeochemical controls of oxidation on the resultant δ34S and δ18O values of the sulfate produced. The minerals were incubated in the presence and absence of Acidithiobacillus ferrooxidans at an initial solution pH of 3 and with water of varying δ18O values to determine the relative contributions of H2O-derived and O2-derived oxygen in the newly formed sulfate. . Experiments were conducted under aerobic and anaerobic conditions using O2 and Fe(III)aq as the oxidants, respectively. Aerobic incubations with A. ferrooxidans, and So as the sole energy source were also conducted. The &#x3B4;34SSO4\">δ34SSO4 values from both the biological and abiotic oxidation of ZnS and ZnSFe by Fe(III)aq produced sulfur isotope fractionations (&#x3B5;34SSO4-ZnS\">ε34SSO4-ZnS) of up to −2.6‰, suggesting the accumulation of sulfur intermediates during incomplete oxidation of the sulfide. No significant sulfur isotope fractionation was observed from any of the aerobic experiments. Negative sulfur isotope enrichment factors (&#x3B5;34SSO4-ZnS\">ε34SSO4-ZnS) in AMD systems could reflect anaerobic, rather than aerobic pathways of oxidation. During the biological and abiotic oxidation of ZnS and ZnSFe by Fe(III)aq all of the sulfate oxygen was derived from water, with measured &#x3B5;18OSO4-H2O\">ε18OSO4-H2O values of 8.2 ± 0.2‰ and 7.5 ± 0.1‰, respectively. Also, during the aerobic oxidation of ZnSFe and So by A. ferrooxidans, all of the sulfate oxygen was derived from water with similar measured &#x3B5;18OSO4-H2O\">ε18OSO4-H2O values of 8.1 ± 0.1‰ and 8.3 ± 0.3‰, respectively. During biological oxidation of ZnS by O2, an estimated 8% of sulfate–oxygen was derived from O2, which is enriched in 18O relative to water, thus resulting in a larger apparent &#x3B5;18OSO4-H2O\">ε18OSO4-H2O value of 9.5‰. Based on the data presented we hypothesize that the similar &#x3B5;18OSO4-H2O\">ε18OSO4-H2O values of ∼8‰ from all of the aerobic and anaerobic experiments result from a common rate-limiting step that involves oxygen isotopic exchange between a sulfite (SO3-\">SO3-) intermediate and H2O. Our results indicate that the &#x3B4;18OSO4\">δ18OSO4 values cannot be used to distinguish biological and abiotic, nor aerobic versus anaerobic, pathways of sphalerite oxidation. However, the &#x3B5;18OSO4-H2O\">ε18OSO4-H2O values of ∼8‰ measured here are distinctly higher than &#x3B5;18OSO4-H2O\">ε18OSO4-H2O values of ∼4‰ previously reported for pyrite oxidation indicating the influence of sulfide mineralogy on measured &#x3B4;18OSO4\">δ18OSO4 values.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2011.10.022","issn":"00167037","usgsCitation":"Balci, N., Mayer, B., Shanks, W.C., and Mandernack, K., 2012, Oxygen and sulfur isotope systematics of sulfate produced during abiotic and bacterial oxidation of sphalerite and elemental sulfur: Geochimica et Cosmochimica Acta, v. 77, p. 335-351, https://doi.org/10.1016/j.gca.2011.10.022.","productDescription":"17 p.","startPage":"335","endPage":"351","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":241682,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213998,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.gca.2011.10.022"}],"volume":"77","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a7286e4b0c8380cd76b53","contributors":{"authors":[{"text":"Balci, N.","contributorId":15005,"corporation":false,"usgs":true,"family":"Balci","given":"N.","email":"","affiliations":[],"preferred":false,"id":436334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mayer, B.","contributorId":84538,"corporation":false,"usgs":true,"family":"Mayer","given":"B.","email":"","affiliations":[],"preferred":false,"id":436337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanks, W. C. Pat III 0000-0001-5336-3954","orcid":"https://orcid.org/0000-0001-5336-3954","contributorId":240915,"corporation":false,"usgs":true,"family":"Shanks","given":"W.","suffix":"III","email":"","middleInitial":"C. Pat","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":436335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mandernack, K.W.","contributorId":68913,"corporation":false,"usgs":true,"family":"Mandernack","given":"K.W.","email":"","affiliations":[],"preferred":false,"id":436336,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032554,"text":"70032554 - 2012 - Ecological controls on the shell geochemistry of pink and white Globigerinoides ruber in the northern Gulf of Mexico: implications for paleoceanographic reconstruction","interactions":[],"lastModifiedDate":"2014-01-14T10:15:16","indexId":"70032554","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2673,"text":"Marine Micropaleontology","active":true,"publicationSubtype":{"id":10}},"title":"Ecological controls on the shell geochemistry of pink and white Globigerinoides ruber in the northern Gulf of Mexico: implications for paleoceanographic reconstruction","docAbstract":"We evaluate the relationship between foraminiferal test size and shell geochemistry (δ13C, δ18O, and Mg/Ca) for two of the most commonly used planktonic foraminifers for paleoceanographic reconstruction in the subtropical Atlantic Ocean: the pink and white varieties of Globigerinoides ruber. Geochemical analyses were performed on foraminifera from modern core-top samples of high-accumulation rate basins in the northern Gulf of Mexico. Mg/Ca analysis indicates a positive relationship with test size, increasing by 1.1 mmol/mol (~ 2.5 °C) from the smallest (150–212 μm) to largest (> 500 μm) size fractions of G. ruber (pink), but with no significant relationship in G. ruber (white). In comparison, oxygen isotope data indicate a negative relationship with test size, decreasing by 0.6‰ across the size range of both pink and white G. ruber. The observed increase in Mg/Ca and decrease in δ18O are consistent with an increase in calcification temperature of 0.7 °C per 100 μm increase in test size, suggesting differences in the seasonal and/or depth distribution among size fractions. Overall, these results stress the necessity for using a consistent size fraction in downcore paleoceanographic studies. In addition, we compare downcore records of δ18O and Mg/Ca from pink and white G. ruber in a decadal-resolution 1000-year sedimentary record from the Pigmy Basin. Based on this comparison we conclude that pink G. ruber is calcifying in warmer waters than co-occurring white G. ruber, suggesting differences in the relative seasonal distribution and depth habitat of the two varieties.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Micropaleontology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.marmicro.2011.10.002","issn":"03778398","usgsCitation":"Richey, J.N., Poore, R.Z., Flower, B.P., and Hollander, D.J., 2012, Ecological controls on the shell geochemistry of pink and white Globigerinoides ruber in the northern Gulf of Mexico: implications for paleoceanographic reconstruction: Marine Micropaleontology, v. 82-83, p. 28-37, https://doi.org/10.1016/j.marmicro.2011.10.002.","productDescription":"10 p.","startPage":"28","endPage":"37","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":213790,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marmicro.2011.10.002"},{"id":241449,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.9,18.2 ], [ -97.9,30.4 ], [ -81.0,30.4 ], [ -81.0,18.2 ], [ -97.9,18.2 ] ] ] } } ] }","volume":"82-83","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a054de4b0c8380cd50d41","contributors":{"authors":[{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":5182,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":436796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poore, Richard Z. rpoore@usgs.gov","contributorId":345,"corporation":false,"usgs":true,"family":"Poore","given":"Richard","email":"rpoore@usgs.gov","middleInitial":"Z.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":436795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flower, Benjamin P.","contributorId":100620,"corporation":false,"usgs":true,"family":"Flower","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":436798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hollander, David J.","contributorId":11421,"corporation":false,"usgs":true,"family":"Hollander","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":436797,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044174,"text":"70044174 - 2012 - Magnetostratigraphy susceptibility for the Guadalupian Series GSSPs (Middle Permian) in Guadalupe Mountains National Park and adjacent areas in West Texas","interactions":[],"lastModifiedDate":"2013-04-22T10:44:52","indexId":"70044174","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"Magnetostratigraphy susceptibility for the Guadalupian Series GSSPs (Middle Permian) in Guadalupe Mountains National Park and adjacent areas in West Texas","docAbstract":"Here we establish a magnetostratigraphy susceptibility zonation for the three Middle Permian Global boundary Stratotype Sections and Points (GSSPs) that have recently been defined, located in Guadalupe Mountains National Park, West Texas, USA. These GSSPs, all within the Middle Permian Guadalupian Series, define (1) the base of the Roadian Stage (base of the Guadalupian Series), (2) the base of the Wordian Stage and (3) the base of the Capitanian Stage. Data from two additional stratigraphic successions in the region, equivalent in age to the Kungurian–Roadian and Wordian–Capitanian boundary intervals, are also reported. Based on low-field, mass specific magnetic susceptibility (χ) measurements of 706 closely spaced samples from these stratigraphic sections and time-series analysis of one of these sections, we (1) define the magnetostratigraphy susceptibility zonation for the three Guadalupian Series Global boundary Stratotype Sections and Points; (2) demonstrate that χ datasets provide a proxy for climate cyclicity; (3) give quantitative estimates of the time it took for some of these sediments to accumulate; (4) give the rates at which sediments were accumulated; (5) allow more precise correlation to equivalent sections in the region; (6) identify anomalous stratigraphic horizons; and (7) give estimates for timing and duration of geological events within sections.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geological Society, London, Special Publications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Geological Society","publisherLocation":"London, UK","doi":"10.1144/SP373.1","usgsCitation":"Wardlaw, B.R., Ellwood, B.B., Lambert, L.L., Tomkin, J.H., Bell, G.L., and Nestell, G.P., 2012, Magnetostratigraphy susceptibility for the Guadalupian Series GSSPs (Middle Permian) in Guadalupe Mountains National Park and adjacent areas in West Texas: Geological Society, London, Special Publications, v. 373, p. 21-21, https://doi.org/10.1144/SP373.1.","startPage":"21","endPage":"21","numberOfPages":"1","additionalOnlineFiles":"N","ipdsId":"IP-034315","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":271339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271338,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1144/SP373.1"}],"country":"United States","state":"Texas","volume":"373","noUsgsAuthors":false,"publicationDate":"2012-08-14","publicationStatus":"PW","scienceBaseUri":"51765beae4b0f989f99e00fb","contributors":{"authors":[{"text":"Wardlaw, Bruce R. bwardlaw@usgs.gov","contributorId":266,"corporation":false,"usgs":true,"family":"Wardlaw","given":"Bruce","email":"bwardlaw@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":474985,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellwood, Brooks B.","contributorId":44814,"corporation":false,"usgs":false,"family":"Ellwood","given":"Brooks","email":"","middleInitial":"B.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":474988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lambert, Lance L.","contributorId":9550,"corporation":false,"usgs":true,"family":"Lambert","given":"Lance","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":474986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tomkin, Jonathan H.","contributorId":85860,"corporation":false,"usgs":true,"family":"Tomkin","given":"Jonathan","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":474990,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bell, Gordon L.","contributorId":69639,"corporation":false,"usgs":true,"family":"Bell","given":"Gordon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":474989,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nestell, Galina P.","contributorId":22651,"corporation":false,"usgs":false,"family":"Nestell","given":"Galina","email":"","middleInitial":"P.","affiliations":[{"id":12734,"text":"University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":474987,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70032379,"text":"70032379 - 2012 - Methylation of Hg downstream from the Bonanza Hg mine, Oregon","interactions":[],"lastModifiedDate":"2013-03-25T14:25:41","indexId":"70032379","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Methylation of Hg downstream from the Bonanza Hg mine, Oregon","docAbstract":"Speciation of Hg and conversion to methyl-Hg were evaluated in stream sediment, stream water, and aquatic snails collected downstream from the Bonanza Hg mine, Oregon. Total production from the Bonanza mine was >1360t of Hg, during mining from the late 1800s to 1960, ranking it as an intermediate sized Hg mine on an international scale. The primary objective of this study was to evaluate the distribution, transport, and methylation of Hg downstream from a Hg mine in a coastal temperate climatic zone. Data shown here for methyl-Hg, a neurotoxin hazardous to humans, are the first reported for sediment and water from this area. Stream sediment collected from Foster Creek flowing downstream from the Bonanza mine contained elevated Hg concentrations that ranged from 590 to 71,000ng/g, all of which (except the most distal sample) exceeded the probable effect concentration (PEC) of 1060ng/g, the Hg concentration above which harmful effects are likely to be observed in sediment-dwelling organisms. Concentrations of methyl-Hg in stream sediment collected from Foster Creek varied from 11 to 62ng/g and were highly elevated compared to regional baseline concentrations (0.11-0.82ng/g) established in this study. Methyl-Hg concentrations in stream sediment collected in this study showed a significant correlation with total organic C (TOC, R2=0.62), generally indicating increased methyl-Hg formation with increasing TOC in sediment. Isotopic-tracer methods indicated that several samples of Foster Creek sediment exhibited high rates of Hg-methylation. Concentrations of Hg in water collected downstream from the mine varied from 17 to 270ng/L and were also elevated compared to baselines, but all were below the 770ng/L Hg standard recommended by the USEPA to protect against chronic effects to aquatic wildlife. Concentrations of methyl-Hg in the water collected from Foster Creek ranged from 0.17 to 1.8ng/L, which were elevated compared to regional baseline sites upstream and downstream from the mine that varied from <0.02 to 0.22ng/L. Aquatic snails collected downstream from the mine were elevated in Hg indicating significant bioavailability and uptake of Hg by these snails. Results for sediment and water indicated significant methyl-Hg formation in the ecosystem downstream from the Bonanza mine, which is enhanced by the temperate climate, high precipitation in the area, and high organic matter.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.apgeochem.2011.09.019","issn":"08832927","usgsCitation":"Gray, J.E., Hines, M.E., Krabbenhoft, D.P., and Thoms, B., 2012, Methylation of Hg downstream from the Bonanza Hg mine, Oregon: Applied Geochemistry, v. 27, no. 1, p. 106-114, https://doi.org/10.1016/j.apgeochem.2011.09.019.","startPage":"106","endPage":"114","numberOfPages":"9","onlineOnly":"N","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":241306,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213657,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeochem.2011.09.019"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.694382,43.049322 ], [ -123.694382,43.748281 ], [ -122.995377,43.748281 ], [ -122.995377,43.049322 ], [ -123.694382,43.049322 ] ] ] } } ] }","volume":"27","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5619e4b0c8380cd6d354","contributors":{"authors":[{"text":"Gray, John E. jgray@usgs.gov","contributorId":1275,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jgray@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":435874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hines, Mark E.","contributorId":43180,"corporation":false,"usgs":true,"family":"Hines","given":"Mark","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":435876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":435875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thoms, Bryn","contributorId":95278,"corporation":false,"usgs":true,"family":"Thoms","given":"Bryn","email":"","affiliations":[],"preferred":false,"id":435877,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044008,"text":"70044008 - 2012 - Probabilistic Relationships between Ground‐Motion Parameters and Modified Mercalli Intensity in California","interactions":[],"lastModifiedDate":"2013-04-02T11:35:00","indexId":"70044008","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic Relationships between Ground‐Motion Parameters and Modified Mercalli Intensity in California","docAbstract":"We use a database of approximately 200,000 modified Mercalli intensity (MMI) observations of California earthquakes collected from USGS \"Did You Feel It?\" (DYFI) reports, along with a comparable number of peak ground-motion amplitudes from California seismic networks, to develop probabilistic relationships between MMI and peak ground velocity (PGV), peak ground acceleration (PGA), and 0.3-s, 1-s, and 3-s 5% damped pseudospectral acceleration (PSA). After associating each ground-motion observation with an MMI computed from all the DYFI responses within 2 km of the observation, we derived a joint probability distribution between MMI and ground motion. We then derived reversible relationships between MMI and each ground-motion parameter by using a total least squares regression to fit a bilinear function to the median of the stacked probability distributions. Among the relationships, the fit to peak ground velocity has the smallest errors, though linear combinations of PGA and PGV give nominally better results. We also find that magnitude and distance terms reduce the overall residuals and are justifiable on an information theoretic basis. For intensities MMI≥5, our results are in close agreement with the relations of Wald, Quitoriano, Heaton, and Kanamori (1999); for lower intensities, our results fall midway between Wald, Quitoriano, Heaton, and Kanamori (1999) and those of Atkinson and Kaka (2007). The earthquakes in the study ranged in magnitude from 3.0 to 7.3, and the distances ranged from less than a kilometer to about 400 km from the source.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/0120110156","usgsCitation":"Worden, C., Wald, D.J., and Rhoades, D., 2012, Probabilistic Relationships between Ground‐Motion Parameters and Modified Mercalli Intensity in California: Bulletin of the Seismological Society of America, v. 102, no. 1, p. 204-221, https://doi.org/10.1785/0120110156.","productDescription":"18 p.","startPage":"204","endPage":"221","numberOfPages":"18","additionalOnlineFiles":"N","ipdsId":"IP-008260","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":270463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270462,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120110156"}],"country":"United States","state":"California","volume":"102","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-02-15","publicationStatus":"PW","scienceBaseUri":"515bfdf8e4b075500ee5ca8a","contributors":{"authors":[{"text":"Worden, C.B.","contributorId":20103,"corporation":false,"usgs":true,"family":"Worden","given":"C.B.","email":"","affiliations":[],"preferred":false,"id":474609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":474608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rhoades, D.A.","contributorId":45121,"corporation":false,"usgs":true,"family":"Rhoades","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":474610,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046352,"text":"70046352 - 2012 - Upper Klamath Basin Landsat Image for August 19, 2006: Path 44 Row 31","interactions":[],"lastModifiedDate":"2013-06-10T11:38:29","indexId":"70046352","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Upper Klamath Basin Landsat Image for August 19, 2006: Path 44 Row 31","docAbstract":"This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046352","usgsCitation":"Snyder, D.T., 2012, Upper Klamath Basin Landsat Image for August 19, 2006: Path 44 Row 31, Dataset, https://doi.org/10.3133/70046352.","productDescription":"Dataset","costCenters":[],"links":[{"id":273508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273506,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/erosl1t_08192006_p44r31_l5_usgs_1_NAD83.xml"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.382600,41.991760 ], [ -123.382600,43.492919 ], [ -120.601579,43.492919 ], [ -120.601579,41.991760 ], [ -123.382600,41.991760 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6f56ee4b0097a7158e60f","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":479539,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"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":"

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.

","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":70032262,"text":"70032262 - 2012 - Nonlinear effects of group size on the success of wolves hunting elk","interactions":[],"lastModifiedDate":"2020-12-03T19:37:07.184022","indexId":"70032262","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":981,"text":"Behavioral Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Nonlinear effects of group size on the success of wolves hunting elk","docAbstract":"

Despite the popular view that social predators live in groups because group hunting facilitates prey capture, the apparent tendency for hunting success to peak at small group sizes suggests that the formation of large groups is unrelated to prey capture. Few empirical studies, however, have tested for nonlinear relationships between hunting success and group size, and none have demonstrated why success trails off after peaking. Here, we use a unique dataset of observations of individually known wolves (Canis lupus) hunting elk (Cervus elaphus) in Yellowstone National Park to show that the relationship between success and group size is indeed nonlinear and that individuals withholding effort (free riding) is why success does not increase across large group sizes. Beyond 4 wolves, hunting success leveled off, and individual performance (a measure of effort) decreased for reasons unrelated to interference from inept hunters, individual age, or size. But performance did drop faster among wolves with an incentive to hold back, i.e., nonbreeders with no dependent offspring, those performing dangerous predatory tasks, i.e., grabbing and restraining prey, and those in groups of proficient hunters. These results suggest that decreasing performance was free riding and that was why success leveled off in groups with >4 wolves that had superficially appeared to be cooperating. This is the first direct evidence that nonlinear trends in group hunting success reflect a switch from cooperation to free riding. It also highlights how hunting success per se is unlikely to promote formation and maintenance of large groups.

","language":"English","doi":"10.1093/beheco/arr159","issn":"10452249","usgsCitation":"MacNulty, D., Smith, D., Mech, L.D., Vucetich, J., and Packer, C., 2012, Nonlinear effects of group size on the success of wolves hunting elk: Behavioral Ecology, v. 23, no. 1, p. 75-82, https://doi.org/10.1093/beheco/arr159.","productDescription":"8 p.","startPage":"75","endPage":"82","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474823,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/beheco/arr159","text":"Publisher Index Page"},{"id":242644,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214888,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1093/beheco/arr159"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.1484375,\n 43.96119063892024\n ],\n [\n -109.64355468749999,\n 43.96119063892024\n ],\n [\n -109.64355468749999,\n 45.82879925192134\n ],\n [\n -112.1484375,\n 45.82879925192134\n ],\n [\n -112.1484375,\n 43.96119063892024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-09-29","publicationStatus":"PW","scienceBaseUri":"505a6783e4b0c8380cd7337f","contributors":{"authors":[{"text":"MacNulty, D.R.","contributorId":7661,"corporation":false,"usgs":true,"family":"MacNulty","given":"D.R.","email":"","affiliations":[],"preferred":false,"id":435317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, D.W.","contributorId":24726,"corporation":false,"usgs":true,"family":"Smith","given":"D.W.","email":"","affiliations":[],"preferred":false,"id":435318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":435321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vucetich, J.A.","contributorId":36098,"corporation":false,"usgs":true,"family":"Vucetich","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":435319,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Packer, C.","contributorId":45532,"corporation":false,"usgs":true,"family":"Packer","given":"C.","email":"","affiliations":[],"preferred":false,"id":435320,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70032250,"text":"70032250 - 2012 - Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation","interactions":[],"lastModifiedDate":"2018-09-21T12:39:12","indexId":"70032250","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation","docAbstract":"

Determination of the size of the gas emission zone, the locations of gas sources within, and especially the amount of gas retained in those zones is one of the most important steps for designing a successful methane control strategy and an efficient ventilation system in longwall coal mining. The formation of the gas emission zone and the potential amount of gas-in-place (GIP) that might be available for migration into a mine are factors of local geology and rock properties that usually show spatial variability in continuity and may also show geometric anisotropy. Geostatistical methods are used here for modeling and prediction of gas amounts and for assessing their associated uncertainty in gas emission zones of longwall mines for methane control.

This study used core data obtained from 276 vertical exploration boreholes drilled from the surface to the bottom of the Pittsburgh coal seam in a mining district in the Northern Appalachian basin. After identifying important coal and non-coal layers for the gas emission zone, univariate statistical and semivariogram analyses were conducted for data from different formations to define the distribution and continuity of various attributes. Sequential simulations performed stochastic assessment of these attributes, such as gas content, strata thickness, and strata displacement. These analyses were followed by calculations of gas-in-place and their uncertainties in the Pittsburgh seam caved zone and fractured zone of longwall mines in this mining district. Grid blanking was used to isolate the volume over the actual panels from the entire modeled district and to calculate gas amounts that were directly related to the emissions in longwall mines.

Results indicated that gas-in-place in the Pittsburgh seam, in the caved zone and in the fractured zone, as well as displacements in major rock units, showed spatial correlations that could be modeled and estimated using geostatistical methods. This study showed that GIP volumes may change up to 3 MMscf per acre and, in a multi-panel district, may total 9 Bcf of methane within the gas emission zone. Therefore, ventilation and gas capture systems should be designed accordingly. In addition, rock displacements within the gas emission zone are spatially distributed. From an engineering and practical point of view, spatial distributions of GIP and distributions of rock displacements should be correlated with in-mine emissions and gob gas venthole productions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2011.10.010","issn":"01665162","usgsCitation":"Karacan, C.O., Olea, R., and Goodman, G., 2012, Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation: International Journal of Coal Geology, v. 90-91, p. 50-71, https://doi.org/10.1016/j.coal.2011.10.010.","productDescription":"22 p.","startPage":"50","endPage":"71","ipdsId":"IP-031033","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":474676,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4589251","text":"External Repository"},{"id":242409,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214664,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.coal.2011.10.010"}],"volume":"90-91","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a28b3e4b0c8380cd5a320","contributors":{"authors":[{"text":"Karacan, Cevat O. 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":67742,"corporation":false,"usgs":true,"family":"Karacan","given":"Cevat","email":"","middleInitial":"O.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":435243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":26436,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":435241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goodman, G.","contributorId":29233,"corporation":false,"usgs":true,"family":"Goodman","given":"G.","email":"","affiliations":[],"preferred":false,"id":435242,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046355,"text":"70046355 - 2012 - Upper Klamath Basin Landsat Image for September 20, 2006: Path 44 Row 31","interactions":[],"lastModifiedDate":"2013-06-10T12:43:51","indexId":"70046355","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Upper Klamath Basin Landsat Image for September 20, 2006: Path 44 Row 31","docAbstract":"This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046355","usgsCitation":"Snyder, D.T., 2012, Upper Klamath Basin Landsat Image for September 20, 2006: Path 44 Row 31, Dataset, https://doi.org/10.3133/70046355.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273524,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/erosl1t_09202006_p44r31_l5_usgs_1_NAD83.xml"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.382600,41.991760 ], [ -123.382600,43.492919 ], [ -120.601579,43.492919 ], [ -120.601579,41.991760 ], [ -123.382600,41.991760 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6f571e4b0097a7158e63b","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":479542,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}