{"pageNumber":"1728","pageRowStart":"43175","pageSize":"25","recordCount":184617,"records":[{"id":70003670,"text":"70003670 - 2011 - Rapid cooling rates at an active mid-ocean ridge from zircon thermochronology","interactions":[],"lastModifiedDate":"2021-01-07T21:26:35.20802","indexId":"70003670","displayToPublicDate":"2011-11-09T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Rapid cooling rates at an active mid-ocean ridge from zircon thermochronology","docAbstract":"

Oceanic spreading ridges are Earth's most productive crust generating environment, but mechanisms and rates of crustal accretion and heat loss are debated. Existing observations on cooling rates are ambiguous regarding the prevalence of conductive vs. convective cooling of lower oceanic crust. Here, we report the discovery and dating of zircon in mid-ocean ridge dacite lavas that constrain magmatic differentiation and cooling rates at an active spreading center. Dacitic lavas erupted on the southern Cleft segment of the Juan de Fuca ridge, an intermediate-rate spreading center, near the intersection with the Blanco transform fault. Their U–Th zircon crystallization ages (29.3− 4.6+ 4.8 ka; 1σ standard error s.e.) overlap with the (U–Th)/He zircon eruption age (32.7 ± 1.6 ka) within uncertainty. Based on similar 238U−230Th disequilibria between southern Cleft dacite glass separates and young mid-ocean ridge basalt (MORB) erupted nearby, differentiation must have occurred rapidly, within ~ 10–20 ka at most. Ti-in-zircon thermometry indicates crystallization at 850–900 °C and pressures > 70–150 MPa are calculated from H2O solubility models. These time-temperature constraints translate into a magma cooling rate of ~ 2 × 10− 2 °C/a. This rate is at least one order-of-magnitude faster than those calculated for zircon-bearing plutonic rocks from slow spreading ridges. Such short intervals for differentiation and cooling can only be resolved through uranium-series (238U–230Th) decay in young lavas, and are best explained by dissipating heat convectively at high crustal permeability.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2010.12.022","usgsCitation":"Schmitt, A., Perfit, M.R., Rubin, K.H., Stockli, D.F., Smith, M.C., Cotsonika, L.A., Zellmer, G.F., and Ridley, W., 2011, Rapid cooling rates at an active mid-ocean ridge from zircon thermochronology: Earth and Planetary Science Letters, v. 302, no. 3-4, p. 349-358, https://doi.org/10.1016/j.epsl.2010.12.022.","productDescription":"10 p.","startPage":"349","endPage":"358","numberOfPages":"10","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":204189,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Juan de Fuca ridge and the Blanco transform fault intersection","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -132.5830078125,\n 42.13082130188811\n ],\n [\n -124.8046875,\n 42.13082130188811\n ],\n [\n -124.8046875,\n 50.875311142200765\n ],\n [\n -132.5830078125,\n 50.875311142200765\n ],\n [\n -132.5830078125,\n 42.13082130188811\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"302","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a80e4b07f02db649443","contributors":{"authors":[{"text":"Schmitt, Axel K.","contributorId":69287,"corporation":false,"usgs":true,"family":"Schmitt","given":"Axel K.","affiliations":[],"preferred":false,"id":348262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perfit, Michael R.","contributorId":29123,"corporation":false,"usgs":true,"family":"Perfit","given":"Michael","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":348260,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubin, Kenneth H.","contributorId":90864,"corporation":false,"usgs":true,"family":"Rubin","given":"Kenneth","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":348264,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stockli, Daniel F.","contributorId":78073,"corporation":false,"usgs":true,"family":"Stockli","given":"Daniel","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":348263,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Matthew C.","contributorId":32287,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":348261,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cotsonika, Laurie A.","contributorId":98869,"corporation":false,"usgs":true,"family":"Cotsonika","given":"Laurie","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":348266,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zellmer, Georg F.","contributorId":93615,"corporation":false,"usgs":true,"family":"Zellmer","given":"Georg","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":348265,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ridley, W. Ian 0000-0001-6787-558X","orcid":"https://orcid.org/0000-0001-6787-558X","contributorId":17269,"corporation":false,"usgs":true,"family":"Ridley","given":"W. Ian","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":348259,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70003642,"text":"70003642 - 2011 - Projected evolution of California's San Francisco Bay-Delta-River System in a century of continuing climate change","interactions":[],"lastModifiedDate":"2017-10-30T12:45:36","indexId":"70003642","displayToPublicDate":"2011-11-09T00:00:00","publicationYear":"2011","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":"Projected evolution of California's San Francisco Bay-Delta-River System in a century of continuing climate change","docAbstract":"Background Accumulating evidence shows that the planet is warming as a response to human emissions of greenhouse gases. Strategies of adaptation to climate change will require quantitative projections of how altered regional patterns of temperature, precipitation and sea level could cascade to provoke local impacts such as modified water supplies, increasing risks of coastal flooding, and growing challenges to sustainability of native species. Methodology/Principal Findings We linked a series of models to investigate responses of California's San Francisco Estuary-Watershed (SFEW) system to two contrasting scenarios of climate change. Model outputs for scenarios of fast and moderate warming are presented as 2010–2099 projections of nine indicators of changing climate, hydrology and habitat quality. Trends of these indicators measure rates of: increasing air and water temperatures, salinity and sea level; decreasing precipitation, runoff, snowmelt contribution to runoff, and suspended sediment concentrations; and increasing frequency of extreme environmental conditions such as water temperatures and sea level beyond the ranges of historical observations. Conclusions/Significance Most of these environmental indicators change substantially over the 21st century, and many would present challenges to natural and managed systems. Adaptations to these changes will require flexible planning to cope with growing risks to humans and the challenges of meeting demands for fresh water and sustaining native biota. Programs of ecosystem rehabilitation and biodiversity conservation in coastal landscapes will be most likely to meet their objectives if they are designed from considerations that include: (1) an integrated perspective that river-estuary systems are influenced by effects of climate change operating on both watersheds and oceans; (2) varying sensitivity among environmental indicators to the uncertainty of future climates; (3) inevitability of biological community changes as responses to cumulative effects of climate change and other drivers of habitat transformations; and (4) anticipation and adaptation to the growing probability of ecosystem regime shifts.","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0024465","usgsCitation":"Cloern, J.E., Knowles, N., Brown, L.R., Cayan, D., Dettinger, M., Morgan, T., Schoellhamer, D., Stacey, M., van der Wegen, M., Wagner, R.W., and Jassby, A.D., 2011, Projected evolution of California's San Francisco Bay-Delta-River System in a century of continuing climate change: PLoS ONE, v. 6, no. 9, Article e24465; 13 p., https://doi.org/10.1371/journal.pone.0024465.","productDescription":"Article e24465; 13 p.","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":474899,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0024465","text":"Publisher Index Page"},{"id":204285,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary-watershed","volume":"6","issue":"9","noUsgsAuthors":false,"publicationDate":"2011-09-21","publicationStatus":"PW","scienceBaseUri":"4f4e4a9ae4b07f02db65d95e","contributors":{"authors":[{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":348122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knowles, Noah 0000-0001-5652-1049 nknowles@usgs.gov","orcid":"https://orcid.org/0000-0001-5652-1049","contributorId":1380,"corporation":false,"usgs":true,"family":"Knowles","given":"Noah","email":"nknowles@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":348121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":348123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cayan, Daniel","contributorId":17752,"corporation":false,"usgs":true,"family":"Cayan","given":"Daniel","affiliations":[],"preferred":false,"id":348125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dettinger, Michael D. 0000-0002-7509-7332","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":31743,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael D.","affiliations":[],"preferred":false,"id":348127,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morgan, Tara L. 0000-0001-5632-5232","orcid":"https://orcid.org/0000-0001-5632-5232","contributorId":29124,"corporation":false,"usgs":true,"family":"Morgan","given":"Tara L.","affiliations":[],"preferred":false,"id":348126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":348120,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stacey, Mark T.","contributorId":13367,"corporation":false,"usgs":true,"family":"Stacey","given":"Mark T.","affiliations":[],"preferred":false,"id":348124,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"van der Wegen, Mick","contributorId":76455,"corporation":false,"usgs":true,"family":"van der Wegen","given":"Mick","affiliations":[],"preferred":false,"id":348130,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wagner, R. Wayne","contributorId":40339,"corporation":false,"usgs":true,"family":"Wagner","given":"R.","email":"","middleInitial":"Wayne","affiliations":[],"preferred":false,"id":348128,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jassby, Alan D.","contributorId":66403,"corporation":false,"usgs":true,"family":"Jassby","given":"Alan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":348129,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70005076,"text":"70005076 - 2011 - Pythons in Burma: Short-tailed python (Reptilia: Squamata)","interactions":[],"lastModifiedDate":"2021-05-20T21:24:57.314434","indexId":"70005076","displayToPublicDate":"2011-11-09T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3147,"text":"Proceedings of the Biological Society of Washington","active":true,"publicationSubtype":{"id":10}},"title":"Pythons in Burma: Short-tailed python (Reptilia: Squamata)","docAbstract":"Short-tailed pythons, Python curtus species group, occur predominantly in the Malayan Peninsula, Sumatra, and Borneo. The discovery of an adult female in Mon State, Myanmar, led to a review of the distribution of all group members (spot-mapping of all localities of confirmed occurrence) and an examination of morphological variation in P. brongersmai. The resulting maps demonstrate a limited occurrence of these pythons within peninsular Malaya, Sumatra, and Borneo with broad absences in these regions. Our small samples limit the recognition of regional differentiation in the morphology of P. brongersmai populations; however, the presence of unique traits in the Myanmar python and its strong allopatry indicate that it is a unique genetic lineage, and it is described as Python kyaiktiyo new species.","language":"English","publisher":"Biological Society of Washington","publisherLocation":"Washington, D.C.","doi":"10.2988/10-34.1","usgsCitation":"Zug, G.R., Gotte, S.W., and Jacobs, J.F., 2011, Pythons in Burma: Short-tailed python (Reptilia: Squamata): Proceedings of the Biological Society of Washington, v. 124, no. 2, p. 112-136, https://doi.org/10.2988/10-34.1.","productDescription":"25 p.","startPage":"112","endPage":"136","numberOfPages":"25","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":204387,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Myanmar","state":"Mon State","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 96.822509765625,\n 12.91890657418042\n ],\n [\n 99.140625,\n 12.91890657418042\n ],\n [\n 99.140625,\n 17.738222936441765\n ],\n [\n 96.822509765625,\n 17.738222936441765\n ],\n [\n 96.822509765625,\n 12.91890657418042\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a74e4b07f02db6446ae","contributors":{"authors":[{"text":"Zug, George R.","contributorId":76874,"corporation":false,"usgs":true,"family":"Zug","given":"George","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":351943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gotte, Steve W. 0000-0001-5509-4495 sgotte@usgs.gov","orcid":"https://orcid.org/0000-0001-5509-4495","contributorId":4481,"corporation":false,"usgs":true,"family":"Gotte","given":"Steve","email":"sgotte@usgs.gov","middleInitial":"W.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":351941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobs, Jeremy F.","contributorId":41130,"corporation":false,"usgs":true,"family":"Jacobs","given":"Jeremy","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":351942,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70005926,"text":"sir20115181 - 2011 - Seasonal seepage investigation on an urbanized reach of the lower Boise River, southwestern Idaho, water year 2010","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"sir20115181","displayToPublicDate":"2011-11-09T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5181","title":"Seasonal seepage investigation on an urbanized reach of the lower Boise River, southwestern Idaho, water year 2010","docAbstract":"The U.S. Geological Survey in cooperation with the Idaho Department of Water Resources Treasure Valley Comprehensive Aquifer Management Planning effort investigated seasonal groundwater gains and losses on the Boise River, Idaho, starting in November 2009 through August 2010. The investigation was conducted using seepage runs in 11 subreaches over a 14-mile reach from downstream of the inactive streamgage, Boise River below Diversion Dam (U.S. Geological Survey station No. 13203510) to the active Boise River at Glenwood Bridge streamgage (U.S. Geological Survey station No. 13206000). The seepage runs measured mainstem discharge, and significant tributary contributions and diversions along the reach. In addition, an evaluation of the groundwater hydraulic gradient was simultaneously conducted through shallow groundwater mini-piezometers adjacent to the river during February (low stream discharge) and May (high stream discharge) measurement timeframes. November discharge estimates, representative of autumn, had gains and losses that varied by subreach with an overall net gain of 42 ± 8 cubic feet per second (ft3/s). This finding compares favorably to a previous U.S. Geological Survey seepage investigation in November 1996 that found a gaining reach with an estimated gain of 52 ft3/s. This finding also is supported by a U.S. Geological Survey investigation in the study reach in November 1971 that estimated a gain of 74 ft3/s, which largely came from groundwater. The February discharge estimates, representative of winter conditions, showed variability in the reach with a net gain of 52 ft3/s with an uncertainty estimate of ± 7 ft3/s, which is consistent with the low stream discharge findings from November 2009. This finding is further supported by the differential hydraulic head measured at transect sites that qualitatively indicated groundwater to surface-water movement with few exceptions. The May discharge estimates, representative of the spring-time conditions, were gaining or potentially gaining in all but one of the upper subreaches between Boise River below Diversion Dam and Boise River near MK Nature Center sites, with seepage run results supported by hydraulic head differentials indicating a groundwater to surface-water movement. The lower end of the study reach between Boise River near MK Nature Center and Boise River at Glenwood Bridge sites showed more variability with observed hydraulic head differentials that partially supported the potential gains or losses in the reach. Overall, the reach had a calculated net gain of 24 ± 51 ft3/s and, therefore, this estimate may or may not reflect the actual conditions in the reach. The groundwater gains and losses in August, representative of summer conditions, varied in both the upper and lower parts of the reach, with a net loss of -88 ± 69 ft3/s. Overall, the reach experienced a net gain from groundwater at low stream discharges (November and February), a net loss to groundwater at moderately high stream discharge (August), and an ambiguous finding at a higher stream discharge (May). The hydraulic head differentials measured between the groundwater and surface water largely supported the calculated gain and loss estimates in the subreaches, with a potential for groundwater to surface-water movement at low stream discharge in February, and variability during high stream discharge conditions in May.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115181","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Williams, M.L., 2011, Seasonal seepage investigation on an urbanized reach of the lower Boise River, southwestern Idaho, water year 2010: U.S. Geological Survey Scientific Investigations Report 2011-5181, iv, 24 p., https://doi.org/10.3133/sir20115181.","productDescription":"iv, 24 p.","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":116688,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5181.jpg"},{"id":101753,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5181/","linkFileType":{"id":5,"text":"html"}}],"state":"Idaho","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abde4b07f02db673e0f","contributors":{"authors":[{"text":"Williams, Marshall L. mlwilliams@usgs.gov","contributorId":1444,"corporation":false,"usgs":true,"family":"Williams","given":"Marshall","email":"mlwilliams@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353477,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70005919,"text":"70005919 - 2011 - Changes in nutrient dynamics of midcontinent greater white-fronted geese during spring migration","interactions":[],"lastModifiedDate":"2021-05-17T16:59:22.500406","indexId":"70005919","displayToPublicDate":"2011-11-09T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Changes in nutrient dynamics of midcontinent greater white-fronted geese during spring migration","docAbstract":"

Waterfowl and other migratory birds commonly store nutrients at traditional staging areas during spring for later use during migration and reproduction. We investigated nutrient‐storage dynamics in the midcontinent population of greater white‐fronted geese (Anser albifrons; hereafter white‐fronted geese) at spring staging sites in the Rainwater Basin of Nebraska during February–April and in southern Saskatchewan during April–May, 1998 and 1999. In Nebraska, lipid content of white‐fronted geese did not increase, and protein content changed little over time for most age and sex categories. In Saskatchewan, lipids increased 11.4 g/day (SE = 1.7) and protein content increased 1.6 g/day (SE = 0.6) in the sample of adult geese collected over a 3‐week period. A study conducted during 1979–1980 in the Rainwater Basin reported that white‐fronted geese gained 8.8–17.7 g of lipids per day during spring, differing greatly from our results 2 decades later. In addition, lipid levels were less in the 1990s compared to spring 1980 for adult geese nearing departure from staging sites in Saskatchewan. This shift in where geese acquired nutrient stores from Nebraska to more northern staging sites coincided with a decrease in availability of waste corn in Nebraska, their primary food source while staging at that stopover site, and an increase in cultivation of high‐energy pulse crops in Saskatchewan. White‐fronted geese exhibited flexibility in nutrient dynamics during spring migration, likely in response to landscape‐level variation in food availability caused by changes in agricultural trends and practices. Maintaining a wide distribution of wetlands in the Great Plains may allow spring‐staging waterfowl to disperse across the region and facilitate access to high‐energy foods over a larger cropland base.

","language":"English","publisher":"The Wildlife Society","publisherLocation":"Bethesda, MD","doi":"10.1002/jwmg.223","usgsCitation":"Pearse, A.T., Alisauskas, R., Krapu, G.L., and Cox, R.R., 2011, Changes in nutrient dynamics of midcontinent greater white-fronted geese during spring migration: Journal of Wildlife Management, v. 75, no. 8, p. 1716-1723, https://doi.org/10.1002/jwmg.223.","productDescription":"8 p.","startPage":"1716","endPage":"1723","temporalStart":"1998-02-01","temporalEnd":"1999-05-31","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":204210,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Nebraska, Saskatchewan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.951171875,\n 51.138001488062564\n ],\n [\n -104.30419921875,\n 51.138001488062564\n ],\n [\n -104.30419921875,\n 53.15994678846807\n ],\n [\n -109.951171875,\n 53.15994678846807\n ],\n [\n -109.951171875,\n 51.138001488062564\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.25,\n 40.212440718286466\n ],\n [\n -97.14111328125,\n 40.212440718286466\n ],\n [\n -97.14111328125,\n 41.66470503009207\n ],\n [\n -101.25,\n 41.66470503009207\n ],\n [\n -101.25,\n 40.212440718286466\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","issue":"8","noUsgsAuthors":false,"publicationDate":"2011-08-22","publicationStatus":"PW","scienceBaseUri":"4f4e49e2e4b07f02db5e4d63","contributors":{"authors":[{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":353467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alisauskas, Ray T.","contributorId":20883,"corporation":false,"usgs":true,"family":"Alisauskas","given":"Ray T.","affiliations":[],"preferred":false,"id":353470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krapu, Gary L. 0000-0001-8482-6130 gkrapu@usgs.gov","orcid":"https://orcid.org/0000-0001-8482-6130","contributorId":3074,"corporation":false,"usgs":true,"family":"Krapu","given":"Gary","email":"gkrapu@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":353468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cox, Robert R. Jr.","contributorId":6575,"corporation":false,"usgs":true,"family":"Cox","given":"Robert","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":353469,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70003910,"text":"70003910 - 2011 - Quantifying the fire regime distributions for severity in Yosemite National Park, California, USA","interactions":[],"lastModifiedDate":"2021-04-28T16:06:16.44102","indexId":"70003910","displayToPublicDate":"2011-11-09T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the fire regime distributions for severity in Yosemite National Park, California, USA","docAbstract":"

This paper quantifies current fire severity distributions for 19 different fire-regime types in Yosemite National Park, California, USA. Landsat Thematic Mapper remote sensing data are used to map burn severity for 99 fires (cumulatively over 97 000 ha) that burned in Yosemite over a 20-year period. These maps are used to quantify the frequency distributions of fire severity by fire-regime type. A classification is created for the resultant distributions and they are discussed within the context of four vegetation zones: the foothill shrub and woodland zone; the lower montane forest zone; the upper montane forest zone and the subalpine forest zone. The severity distributions can form a building block from which to discuss current fire regimes across the Sierra Nevada in California. This work establishes a framework for comparing the effects of current fires on our landscapes with our notions of how fires historically burned, and how current fire severity distributions differ from our desired future conditions. As this process is refined, a new set of information will be available to researchers and land managers to help understand how fire regimes have changed from the past and how we might attempt to manage them in the future.

","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF09060","usgsCitation":"Thode, A., van Wagtendonk, J., Miller, D.J., and Quinn, J.F., 2011, Quantifying the fire regime distributions for severity in Yosemite National Park, California, USA: International Journal of Wildland Fire, v. 20, no. 2, p. 223-239, https://doi.org/10.1071/WF09060.","productDescription":"17 p.","startPage":"223","endPage":"239","numberOfPages":"17","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":204490,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.06134033203125,\n 37.477037796698056\n ],\n [\n -119.11102294921875,\n 37.477037796698056\n ],\n [\n -119.11102294921875,\n 38.156156969924915\n ],\n [\n -120.06134033203125,\n 38.156156969924915\n ],\n [\n -120.06134033203125,\n 37.477037796698056\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adce4b07f02db6862f8","contributors":{"authors":[{"text":"Thode, Andrea E.","contributorId":31896,"corporation":false,"usgs":false,"family":"Thode","given":"Andrea E.","affiliations":[],"preferred":false,"id":349427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Wagtendonk, Jan W. 0000-0002-0788-2654","orcid":"https://orcid.org/0000-0002-0788-2654","contributorId":98269,"corporation":false,"usgs":true,"family":"van Wagtendonk","given":"Jan W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":349429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, D. 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Adsorption equilibrium was achieved in 500-1000 h although dissolved uranium concentrations increased over thousands of hours owing to changes in aqueous chemical composition driven by sediment-water reactions. A nonelectrostatic surface complexation reaction, >SOH + UO22+ + 2CO32- = >SOUO2(CO3HCO3)2-, provided the best fit to experimental data for each sediment sample resulting in a range of conditional equilibrium constants (logKc) from 21.49 to 21.76. Potential differences in uranium adsorption properties could be assessed in plots based on the generalized mass-action expressions yielding linear trends displaced vertically by differences in logKc values. Using this approach, logKc values for seven sediment samples were not significantly different. However, a significant difference in adsorption properties between one sediment sample and the fines (<0.063 mm) of another could be demonstrated despite the fines requiring a different reaction stoichiometry. Estimates of logKc uncertainty were improved by capturing all data points within experimental errors. The mass-action expression plots demonstrate that applying models outside the range of conditions used in model calibration greatly increases potential errors.","language":"English","publisher":"ACS Publications","doi":"10.1021/es202677v","usgsCitation":"Stoliker, D., Kent, D.B., and Zachara, J.M., 2011, Quantifying differences in the impact of variable chemistry on equilibrium uranium(VI) adsorption properties of aquifer sediments: Environmental Science & Technology, v. 45, no. 20, p. 8733-8740, https://doi.org/10.1021/es202677v.","productDescription":"8 p.","startPage":"8733","endPage":"8740","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":474902,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/es202677v","text":"Publisher Index 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Chemical Society (ACS)","authors":"Stoliker Deborah L., Kent Douglas B., Zachara John M.","journalName":"Environmental Science & Technology","publicationDate":"10/15/2011","auditedOn":"3/4/2016","publiclyAccessibleDate":"9/16/2011"},"contributors":{"authors":[{"text":"Stoliker, Deborah L. dlstoliker@usgs.gov","contributorId":2954,"corporation":false,"usgs":true,"family":"Stoliker","given":"Deborah L.","email":"dlstoliker@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":351810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kent, Douglas B. 0000-0003-3758-8322 dbkent@usgs.gov","orcid":"https://orcid.org/0000-0003-3758-8322","contributorId":1871,"corporation":false,"usgs":true,"family":"Kent","given":"Douglas","email":"dbkent@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes 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successions of central and nothern Madagascar","docAbstract":"

New detrital zircon U–Pb age data obtained from various quartzite units of three spatially separated supracrustal packages in central and northern Madagascar, show that these units were deposited between 1.8 and 0.8 Ga and have similar aged provenances. The distribution of detrital zircon ages indicates an overwhelming contribution of sources with ages between 2.5 and 1.8 Ga. Possible source rocks with an age of 2.5 Ga are present in abundance in the crustal segments (Antananarivo, Antongil and Masora Domains) either side of a purported Neoproterozoic suture (“Betsimisaraka Suture Zone”). Recently, possible source rocks for the 1.8 Ga age peak have been recognised in southern Madagascar. All three supracrustal successions, as well as the Archaean blocks onto which they were emplaced, are intruded by mid-Neoproterozoic magmatic suites placing a minimum age on their deposition. The similarities in detrital pattern, maximum and minimum age of deposition in the three successions, lend some support to a model in which all of Madagascar's Archaean blocks form a coherent crustal entity (the Greater Dharwar Craton), rather than an amalgamate of disparate crustal blocks brought together only during Neoproterozoic convergence. However, potential source terranes exist outside Madagascar and on either side of the Neoproterozoic sutures, so that a model including a Neoproterozoic suture in Madagascar cannot be dispelled outright.

","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.precamres.2011.04.004","usgsCitation":"De Waele, B., Thomas, R., Macey, P., Horstwood, M.S., Tucker, R.D., Pitfield, P., Schofield, D.I., Goodenough, K.M., Bauer, W., Key, R.M., Potter, C., Armstrong, R.A., Miller, J.A., Randriamananjara, T., Ralison, V., Rafahatelo, J.M., Rabarimanana, M., and Bejoma, M., 2011, Provenance and tectonic significance of the Palaeoproterozoic metasedimentary successions of central and nothern Madagascar: Precambrian Research, v. 189, no. 1-2, p. 18-42, https://doi.org/10.1016/j.precamres.2011.04.004.","productDescription":"25 p.","startPage":"18","endPage":"42","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":474901,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://nora.nerc.ac.uk/id/eprint/14345/1/De_Waele_et_al.pdf","text":"External Repository"},{"id":204386,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Madagascar","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[49.54352,-12.46983],[49.80898,-12.89528],[50.05651,-13.55576],[50.21743,-14.75879],[50.47654,-15.22651],[50.37711,-15.70607],[50.20027,-16.00026],[49.86061,-15.41425],[49.67261,-15.7102],[49.86334,-16.45104],[49.77456,-16.87504],[49.49861,-17.10604],[49.43562,-17.95306],[49.04179,-19.11878],[48.54854,-20.49689],[47.93075,-22.3915],[47.54772,-23.78196],[47.09576,-24.94163],[46.28248,-25.17846],[45.40951,-25.60143],[44.83357,-25.3461],[44.03972,-24.98835],[43.76377,-24.46068],[43.69778,-23.57412],[43.34565,-22.7769],[43.25419,-22.05741],[43.4333,-21.33648],[43.89368,-21.16331],[43.89637,-20.83046],[44.37433,-20.07237],[44.4644,-19.43545],[44.23242,-18.96199],[44.04298,-18.33139],[43.96308,-17.40994],[44.31247,-16.8505],[44.44652,-16.21622],[44.94494,-16.17937],[45.50273,-15.97437],[45.87299,-15.79345],[46.31224,-15.78002],[46.88218,-15.21018],[47.70513,-14.5943],[48.00521,-14.09123],[47.86905,-13.66387],[48.29383,-13.78407],[48.84506,-13.08917],[48.86351,-12.48787],[49.19465,-12.04056],[49.54352,-12.46983]]]},\"properties\":{\"name\":\"Madagascar\"}}]}","volume":"189","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a91e4b07f02db6567c9","contributors":{"authors":[{"text":"De Waele, B.","contributorId":42004,"corporation":false,"usgs":false,"family":"De Waele","given":"B.","email":"","affiliations":[],"preferred":false,"id":351171,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Ronald J.","contributorId":25371,"corporation":false,"usgs":false,"family":"Thomas","given":"Ronald J.","affiliations":[],"preferred":false,"id":351168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macey, P. 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A.","contributorId":77101,"corporation":false,"usgs":false,"family":"Miller","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":351176,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Randriamananjara, T.","contributorId":78948,"corporation":false,"usgs":false,"family":"Randriamananjara","given":"T.","email":"","affiliations":[],"preferred":false,"id":351177,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Ralison, V.","contributorId":27326,"corporation":false,"usgs":false,"family":"Ralison","given":"V.","email":"","affiliations":[],"preferred":false,"id":351169,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Rafahatelo, J. M.","contributorId":18984,"corporation":false,"usgs":false,"family":"Rafahatelo","given":"J.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":351166,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Rabarimanana, M.","contributorId":47179,"corporation":false,"usgs":false,"family":"Rabarimanana","given":"M.","affiliations":[],"preferred":false,"id":351174,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Bejoma, M.","contributorId":101154,"corporation":false,"usgs":false,"family":"Bejoma","given":"M.","email":"","affiliations":[],"preferred":true,"id":351180,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70005917,"text":"sir20115163 - 2011 - New U.S. Geological Survey method for the assessment of reserve growth","interactions":[],"lastModifiedDate":"2018-07-31T10:21:05","indexId":"sir20115163","displayToPublicDate":"2011-11-08T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5163","title":"New U.S. Geological Survey method for the assessment of reserve growth","docAbstract":"Reserve growth is defined as the estimated increases in quantities of crude oil, natural gas, and natural gas liquids that have the potential to be added to remaining reserves in discovered accumulations through extension, revision, improved recovery efficiency, and additions of new pools or reservoirs. A new U.S. Geological Survey method was developed to assess the reserve-growth potential of technically recoverable crude oil and natural gas to be added to reserves under proven technology currently in practice within the trend or play, or which reasonably can be extrapolated from geologically similar trends or plays. This method currently is in use to assess potential additions to reserves in discovered fields of the United States. The new approach involves (1) individual analysis of selected large accumulations that contribute most to reserve growth, and (2) conventional statistical modeling of reserve growth in remaining accumulations. This report will focus on the individual accumulation analysis.\r\nIn the past, the U.S. Geological Survey estimated reserve growth by statistical methods using historical recoverable-quantity data. Those statistical methods were based on growth rates averaged by the number of years since accumulation discovery. Accumulations in mature petroleum provinces with volumetrically significant reserve growth, however, bias statistical models of the data; therefore, accumulations with significant reserve growth are best analyzed separately from those with less significant reserve growth. Large (greater than 500 million barrels) and older (with respect to year of discovery) oil accumulations increase in size at greater rates late in their development history in contrast to more recently discovered accumulations that achieve most growth early in their development history. Such differences greatly affect the statistical methods commonly used to forecast reserve growth.\r\nThe individual accumulation-analysis method involves estimating the in-place petroleum quantity and its uncertainty, as well as the estimated (forecasted) recoverability and its respective uncertainty. These variables are assigned probabilistic distributions and are combined statistically to provide probabilistic estimates of ultimate recoverable quantities. Cumulative production and remaining reserves are then subtracted from the estimated ultimate recoverable quantities to provide potential reserve growth. In practice, results of the two methods are aggregated to various scales, the highest of which includes an entire country or the world total. The aggregated results are reported along with the statistically appropriate uncertainties.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115163","usgsCitation":"Klett, T., Attanasi, E.D., Charpentier, R., Cook, T.A., Freeman, P., Gautier, D.L., Le, P., Ryder, R., Schenk, C.J., Tennyson, M., and Verma, M., 2011, New U.S. Geological Survey method for the assessment of reserve growth: U.S. Geological Survey Scientific Investigations Report 2011-5163, iv, 8 p., https://doi.org/10.3133/sir20115163.","productDescription":"iv, 8 p.","onlineOnly":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":116490,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5163.png"},{"id":101699,"rank":100,"type":{"id":15,"text":"Index 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Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some major advances and challenges. First, significant advances have been made in representation, scaling, and characterization of disturbances that should be included in regional modeling efforts. Second, there is a need to develop effective and comprehensive process‐based procedures and algorithms to quantify the immediate and long‐term impacts of disturbances on ecosystem succession, soils, microclimate, and cycles of carbon, water, and nutrients. Third, our capability to simulate the occurrences and severity of disturbances is very limited. Fourth, scaling issues have rarely been addressed in continental scale model applications. It is not fully understood which finer scale processes and properties need to be scaled to coarser spatial and temporal scales. Fifth, there are inadequate databases on disturbances at the continental scale to support the quantification of their effects on the carbon balance in North America. Finally, procedures are needed to quantify the uncertainty of model inputs, model parameters, and model structures, and thus to estimate their impacts on overall model uncertainty. Working together, the scientific community interested in disturbance and its impacts can identify the most uncertain issues surrounding the role of disturbance in the North American carbon budget and develop working hypotheses to reduce the uncertainty

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Woods Hole, MA 02543.","active":true,"usgs":false}],"preferred":false,"id":697300,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Luo, Yiqi","contributorId":177420,"corporation":false,"usgs":false,"family":"Luo","given":"Yiqi","email":"","affiliations":[],"preferred":false,"id":697301,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Potter, Christopher 0000-0002-2300-6670","orcid":"https://orcid.org/0000-0002-2300-6670","contributorId":103151,"corporation":false,"usgs":true,"family":"Potter","given":"Christopher","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":697302,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Oeding, Jennifer joeding@usgs.gov","contributorId":4070,"corporation":false,"usgs":true,"family":"Oeding","given":"Jennifer","email":"joeding@usgs.gov","affiliations":[],"preferred":true,"id":697303,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70173630,"text":"70173630 - 2011 - Restoration of the fire-grazing interaction in Artemisia filifolia shrubland of the Southern Great Plains, North America","interactions":[],"lastModifiedDate":"2016-06-07T15:31:28","indexId":"70173630","displayToPublicDate":"2011-11-08T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Restoration of the fire-grazing interaction in Artemisia filifolia shrubland of the Southern Great Plains, North America","docAbstract":"

1. Patterns of landscape heterogeneity are crucial to the maintenance of biodiversity in shrublands and grasslands, yet management practices in these ecosystems typically seek to homogenize landscapes. Furthermore, there is limited understanding of how the interaction of ecological processes, such as fire and grazing, affects patterns of heterogeneity at different spatial scales.

\n

2. We conducted research in Artemisia filifolia (Asteraceae) shrublands located in the southern Great Plains of North America to determine the effect of restoring the fire–grazing interaction on vegetation structure. Data were collected for 3 years in replicated pastures grazed by cattle Bos taurus where the fire–grazing interaction had been restored (fire and grazing = treatment pastures) and in pastures that were grazed but remained unburned (grazing only, no fire = control pastures). The effect of the fire–grazing interaction on heterogeneity (variance) of vegetation structure was assessed at scales from 12·5 m2 to 609 ha.

\n

3. Most measurements of vegetation structure within treatment pastures differed from control pastures for 1–3 years after being burned but were thereafter similar to the values found in unburned control pastures.

\n

4. Treatment pastures were characterized by a lower amount of total heterogeneity and a lower amount of heterogeneity through time.

\n

5. Heterogeneity of vegetation structure tended to decrease as the scale of measurement increased in both treatment and control pastures. There was deviation from this trend, however, in the treatment pastures that exhibited much higher heterogeneity at the patch scale (mean patch size = 202 ha) of measurement, the scale at which patch fires were conducted.

\n

6.Synthesis and applications. Vegetation structure in A. filifolia shrublands of our study was readily altered by the fire–grazing interaction but also demonstrated substantial resilience to these effects. The fire–grazing interaction also changed the total amount of heterogeneity characterizing this system, the scale at which heterogeneity in this system was expressed and the amount of heterogeneity expressed through time. Land managers seeking to impose a shifting mosaic of heterogeneity on this vegetation type can do so by restoring the fire–grazing interaction with potential conservation benefits similar to what has been achieved in other ecosystems where historic cycles of disturbance and rest have been restored.

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Detection of aboveground surface flooding relied on the well-documented and distinct signature of decreased backscatter in Synthetic Aperture Radar (SAR), which is indicative of inundated marsh in the Gulf of Mexico. Even though decreases in backscatter were distinctive, the multiplicity of possible interactions between changing flood depths and canopy height yielded complex SAR-based representations of the marshes.\nValidated by comparison to inland water levels, success of inundation mapping was primarily related to the operational frequencies of the SAR used to perform the mapping. Success of mapping was based on frequency of correspondence between satellite- and ground-based data. Overall, the most successful mapping (83 percent correspondence) was derived from Phased Array type L-band SAR (PALSAR), while mapping derived from C-band Advanced SAR (ASAR) was less successful (≤61 percent correspondence). Exceptions to the low performance of ASAR-based mapping (defined as >76 percent correspondence) occurred when water levels were well below or above ground, occurring over spatially extensive portions of the ASAR scene.\nWhen mapping day-to-day coastal inundation extents, results indicate that SAR systems operating at C-band frequencies are not as effective as those operating at L-band frequencies; however, multiple factors not related to frequency also reduced the effectiveness of C-Band in detecting subcanopy inundation. 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Publicsupply use accounted for about 70 percent of the total water withdrawn. Other categories of use included industrial, rural domestic, livestock, general irrigation, and aquaculture (table 2). Water-use data collected at 5-year intervals from 1960 to 2005 indicate water withdrawals in Webster Parish decreased substantially from 1970 to 1980; surface-water withdrawals for industrial use decreased from about 37 to 0 Mgal/d because of a paper mill closure in 1979. From 1980 to 2000, total water withdrawals in the parish ranged from 7 to 8 Mgal/d (fig. 2). This fact sheet summarizes basic information on the water resources of Webster Parish, La. Information on groundwater and surface-water availability, quality, development, use, and trends is based on previously published reports listed in the Selected References section.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20113088","collaboration":"In cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., and Griffith, J.M., 2011, Water resources of Webster Parish: U.S. Geological Survey Fact Sheet 2011-3088, 6 p., https://doi.org/10.3133/fs20113088.","productDescription":"6 p.","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":116535,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3088.gif"},{"id":94688,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3088/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Webster Parish;Upland Terrace Aquifer;Sparta Aquifer;Carrizo-wilcox Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.58333333333333,32.25 ], [ -93.58333333333333,33 ], [ -93.16666666666667,33 ], [ -93.16666666666667,32.25 ], [ -93.58333333333333,32.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49f4e4b07f02db5f06ec","contributors":{"authors":[{"text":"Prakken, Lawrence B.","contributorId":73978,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","affiliations":[],"preferred":false,"id":353447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffith, Jason M. 0000-0002-8942-0380 jmgriff@usgs.gov","orcid":"https://orcid.org/0000-0002-8942-0380","contributorId":2923,"corporation":false,"usgs":true,"family":"Griffith","given":"Jason","email":"jmgriff@usgs.gov","middleInitial":"M.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353446,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70005899,"text":"fs20113087 - 2011 - Water resources of Bossier Parish","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"fs20113087","displayToPublicDate":"2011-11-07T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-3087","title":"Water resources of Bossier Parish","docAbstract":"In 2005, about 15.8 million gallons per day (Mgal/d) of water were withdrawn in Bossier Parish, Louisiana, including 4.12 Mgal/d from groundwater sources and about 11.7 Mgal/d from surface-water sources. Public-supply use accounted for about 78 percent (12.4 Mgal/d) of the total water withdrawn. Other categories of use included industry, rural domestic, livestock, rice irrigation, general irrigation, and aquaculture. Based on water-use data collected at 5-year intervals from 1960 to 2005, water withdrawals in the parish increased from 4.96 to 15.8 Mgal/d. This fact sheet summarizes basic information on the water resources of Bossier Parish, La. Information on groundwater and surface-water availability, quality, development, use, and trends is based on previously published reports listed in the Selected References section.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20113087","collaboration":"In cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., and Griffith, J.M., 2011, Water resources of Bossier Parish: U.S. Geological Survey Fact Sheet 2011-3087, 6 p., https://doi.org/10.3133/fs20113087.","productDescription":"6 p.","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":116536,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3087.gif"},{"id":94689,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3087/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Bossier Parish;Red River Alluvial Aquifer;Upland Terrace Aquifer;Sparta Aquifer;Carrizo-wilcox Aquifer;Red River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94,32 ], [ -94,33 ], [ -93.33333333333333,33 ], [ -93.33333333333333,32 ], [ -94,32 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0ce4b07f02db5fc981","contributors":{"authors":[{"text":"Prakken, Lawrence B.","contributorId":73978,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","affiliations":[],"preferred":false,"id":353449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffith, Jason M. 0000-0002-8942-0380 jmgriff@usgs.gov","orcid":"https://orcid.org/0000-0002-8942-0380","contributorId":2923,"corporation":false,"usgs":true,"family":"Griffith","given":"Jason","email":"jmgriff@usgs.gov","middleInitial":"M.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353448,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70005886,"text":"ofr20111267 - 2011 - Assessment of Hyporheic Zone, Flood-Plain, Soil-Gas, Soil, and Surface-Water Contamination at the McCoys Creek Chemical Training Area, Fort Gordon, Georgia, 2009-2010","interactions":[],"lastModifiedDate":"2016-12-08T14:53:31","indexId":"ofr20111267","displayToPublicDate":"2011-11-07T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1267","title":"Assessment of Hyporheic Zone, Flood-Plain, Soil-Gas, Soil, and Surface-Water Contamination at the McCoys Creek Chemical Training Area, Fort Gordon, Georgia, 2009-2010","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon, Georgia, assessed the hyporheic zone, flood plain, soil gas, soil, and surface water for contaminants at the McCoys Creek Chemical Training Area (MCTA) at Fort Gordon, from October 2009 to September 2010. The assessment included the detection of organic contaminants in the hyporheic zone, flood plain, soil gas, and surface water. In addition, the organic contaminant assessment included the analysis of organic compounds classified as explosives and chemical agents in selected areas. Inorganic contaminants were assessed in soil and surface-water samples. The assessment was conducted to provide environmental contamination data to the U.S. Army at Fort Gordon pursuant to requirements of the Resource Conservation and Recovery Act Part B Hazardous Waste Permit process. Ten passive samplers were deployed in the hyporheic zone and flood plain, and total petroleum hydrocarbons (TPH) and octane were detected above the method detection level in every sampler. Other organic compounds detected above the method detection level in the hyporheic zone and flood-plain samplers were trichloroethylene, and cis- and trans- 1, 2-dichloroethylene. One trip blank detected TPH below the method detection level but above the nondetection level. The concentrations of TPH in the samplers were many times greater than the concentrations detected in the blank; therefore, all other TPH concentrations detected are considered to represent environmental conditions. Seventy-one soil-gas samplers were deployed in a grid pattern across the MCTA. Three trip blanks and three method blanks were used and not deployed, and TPH was detected above the method detection level in two trip blanks and one method blank. Detection of TPH was observed at all 71 samplers, but because TPH was detected in the trip and method blanks, TPH was censored and, therefore, only 7 of the 71 samplers were reported as detecting TPH. In addition, benzene, toluene, ethylbenzene, and total xylene were detected above the method detection level in 22 samplers. Other compounds detected above the method detection level included naphthalene, octane, undecane, tridecane, 1,2,4-trimethylbenzene, trichloroethylene, perchloroethylene, chloroform, and 1,4-dichlorobenzene. Subsequent to the soil-gas survey, five locations with elevated contaminant mass were selected and a passive sampler was deployed at those locations to detect the presence of organic compounds classified as explosives or chemical agents. No explosives or chemical agents were detected above the method detection level, but some compounds were detected below the method detection level but above the nondetection level. Dimethyl disulfide, benzothiazole, chloroacetophenones, and para-chlorophenyl methyl sulfide were all detected below the method detection level but above the nondetection level. The compounds 2,4-dinitrotoluene, and para-chlorophenyl methyl sulfone were detected in samplers but also were detected in trip blanks and are not considered as present in the MCTA. The same five locations that were selected for sampling of explosives and chemical agents were selected for soil sampling. Metal concentrations in composite soil samples collected at five locations from land surface to a depth of 6 inches did not exceed the U.S. Environmental Protection Agency Regional Screening Levels for Industrial Soil. Concentrations in some compounds were higher than the South Carolina Department of Health and Environmental Control background levels for nearby South Carolina, including aluminum, arsenic, barium, beryllium, chromium, copper, iron, lead, manganese, nickel, and potassium. A surface-water sample was collected from McCoys Creek and analyzed for volatile organic compounds, semivolatile organic compounds, and inorganic compounds (metals). No volatile organic compounds and (or) semivolatile organic compounds were detected at levels above the maximum contaminant level of the U.S. Environmental Protection Agency (USEPA) National Primary Drinking Water Standard, and no inorganic compounds exceeded the maximum contaminant level of the USEPA National Primary Drinking Water Standard or the Georgia In-Stream Water-Quality Standard. Iron was the only inorganic compound detected in the surface-water sample (578 micrograms per liter) that exceeded the USEPA National Secondary Drinking Water Standard of 300 micrograms per liter.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111267","collaboration":"Prepared in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon","usgsCitation":"Guimaraes, W.B., Falls, W.F., Caldwell, A.W., Ratliff, W.H., Wellborn, J.B., and Landmeyer, J., 2011, Assessment of Hyporheic Zone, Flood-Plain, Soil-Gas, Soil, and Surface-Water Contamination at the McCoys Creek Chemical Training Area, Fort Gordon, Georgia, 2009-2010: U.S. Geological Survey Open-File Report 2011-1267, v, 14 p.; Tables, https://doi.org/10.3133/ofr20111267.","productDescription":"v, 14 p.; Tables","temporalStart":"2009-10-01","temporalEnd":"2010-09-30","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":116534,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1267.jpg"},{"id":94687,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1267/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Georgia","city":"Augusta","otherGeospatial":"Coastal Plain Physiographic Province, Fort Gordon, Mccoys Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.42355346679688,\n 33.247301699949205\n ],\n [\n -82.42355346679688,\n 33.54940663754663\n ],\n [\n -82.01774597167969,\n 33.54940663754663\n ],\n [\n -82.01774597167969,\n 33.247301699949205\n ],\n [\n -82.42355346679688,\n 33.247301699949205\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abbe4b07f02db672931","contributors":{"authors":[{"text":"Guimaraes, Wladmir B. wbguimar@usgs.gov","contributorId":3818,"corporation":false,"usgs":true,"family":"Guimaraes","given":"Wladmir","email":"wbguimar@usgs.gov","middleInitial":"B.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falls, W. Fred 0000-0003-2928-9795 wffalls@usgs.gov","orcid":"https://orcid.org/0000-0003-2928-9795","contributorId":107754,"corporation":false,"usgs":true,"family":"Falls","given":"W.","email":"wffalls@usgs.gov","middleInitial":"Fred","affiliations":[],"preferred":false,"id":353442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Andral W. 0000-0003-1269-5463 acaldwel@usgs.gov","orcid":"https://orcid.org/0000-0003-1269-5463","contributorId":3228,"corporation":false,"usgs":true,"family":"Caldwell","given":"Andral","email":"acaldwel@usgs.gov","middleInitial":"W.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ratliff, W. Hagan","contributorId":60347,"corporation":false,"usgs":true,"family":"Ratliff","given":"W.","email":"","middleInitial":"Hagan","affiliations":[],"preferred":false,"id":353441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wellborn, John B.","contributorId":24822,"corporation":false,"usgs":true,"family":"Wellborn","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":353440,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Landmeyer, James 0000-0002-5640-3816 jlandmey@usgs.gov","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":3257,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James","email":"jlandmey@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353438,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70004986,"text":"70004986 - 2011 - Predicting phenology by integrating ecology, evolution and climate science","interactions":[],"lastModifiedDate":"2021-02-26T14:46:03.667626","indexId":"70004986","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","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":"Predicting phenology by integrating ecology, evolution and climate science","docAbstract":"

Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology – the timing of life‐history events. Phenology has well‐demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species’ reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1365-2486.2011.02515.x","usgsCitation":"Pau, S., Wolkovich, E., Cook, B., Davies, T., Kraft, N., Bolmgren, K., Betancourt, J.L., and Cleland, E., 2011, Predicting phenology by integrating ecology, evolution and climate science: Global Change Biology, v. 17, no. 12, p. 3633-3643, https://doi.org/10.1111/j.1365-2486.2011.02515.x.","productDescription":"11 p.","startPage":"3633","endPage":"3643","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"links":[{"id":204216,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"12","noUsgsAuthors":false,"publicationDate":"2011-09-19","publicationStatus":"PW","scienceBaseUri":"4f4e4a1ae4b07f02db6063d7","contributors":{"authors":[{"text":"Pau, Stephanie","contributorId":86094,"corporation":false,"usgs":true,"family":"Pau","given":"Stephanie","affiliations":[],"preferred":false,"id":351771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolkovich, Elizabeth M.","contributorId":69288,"corporation":false,"usgs":true,"family":"Wolkovich","given":"Elizabeth M.","affiliations":[],"preferred":false,"id":351767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Benjamin I.","contributorId":81237,"corporation":false,"usgs":true,"family":"Cook","given":"Benjamin I.","affiliations":[],"preferred":false,"id":351769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davies, T. Jonathan","contributorId":84062,"corporation":false,"usgs":true,"family":"Davies","given":"T. Jonathan","affiliations":[],"preferred":false,"id":351770,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kraft, Nathan J. B.","contributorId":86471,"corporation":false,"usgs":true,"family":"Kraft","given":"Nathan J. B.","affiliations":[],"preferred":false,"id":351772,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bolmgren, Kjell","contributorId":80001,"corporation":false,"usgs":true,"family":"Bolmgren","given":"Kjell","affiliations":[],"preferred":false,"id":351768,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":351766,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cleland, Elsa E.","contributorId":92790,"corporation":false,"usgs":true,"family":"Cleland","given":"Elsa E.","affiliations":[],"preferred":false,"id":351773,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70004035,"text":"70004035 - 2011 - Predator removal enhances waterbird restoration in Chesapeake Bay (Maryland)","interactions":[],"lastModifiedDate":"2021-02-12T21:33:06.999435","indexId":"70004035","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1462,"text":"Ecological Restoration","active":true,"publicationSubtype":{"id":10}},"title":"Predator removal enhances waterbird restoration in Chesapeake Bay (Maryland)","docAbstract":"This report represents an update to an earlier report(Erwin et al. 2007a) on wildlife restoration on the largest dredge material island project in the United States underway in Talbot County, Maryland (Figure 1) in the mid–Chesapeake Bay region, referred to as the Paul Sarbanes Ecosystem Restoration Project at Poplar Island (www.nab.usace.army.mil/projects/Maryland/PoplarIsland/documents.html). An important component of this largescale restoration effort focused on water birds, as many of these species have undergone significant declines in the Chesapeake region over the past 30 years (Erwin et al. 2007b). The priority waterbird species include common terns (Sterna hirundo), least terns (S. antillarum), snowy egrets (Egretta thula), and ospreys (Pandion haliaetus). Although significant numbers of common terns (more than 800 pairs in 2003), least terns (62 pairs in 2003), snowy egrets (50 or more pairs by 2005), and ospreys (7 to 10 pairs) have nested on Poplar Island since early 2000, tern productivity especially had been strongly limited by a combination of red fox (Vulpes vulpes) and great horned owl (Bubo virginianus) predation. Fox trapping began in 2004, and four were removed that year; no more evidence of fox presence was found in 2005 or subsequently. The owls proved to be more problematic.","language":"English","publisher":"University of Wisconsin Press","publisherLocation":"Madison, WI","doi":"10.3368/er.29.1-2.20","usgsCitation":"Erwin, R.M., McGowan, P.C., and Reese, J., 2011, Predator removal enhances waterbird restoration in Chesapeake Bay (Maryland): Ecological Restoration, v. 29, no. 1-2, p. 20-21, https://doi.org/10.3368/er.29.1-2.20.","productDescription":"2 p.","startPage":"20","endPage":"21","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":204287,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.6461181640625,\n 38.35027253825765\n ],\n [\n -75.8441162109375,\n 38.35027253825765\n ],\n [\n -75.8441162109375,\n 39.66491373749128\n ],\n [\n -76.6461181640625,\n 39.66491373749128\n ],\n [\n -76.6461181640625,\n 38.35027253825765\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"1-2","noUsgsAuthors":false,"publicationDate":"2011-04-13","publicationStatus":"PW","scienceBaseUri":"4f4e4b08e4b07f02db69b4cc","contributors":{"authors":[{"text":"Erwin, R. Michael 0000-0003-2108-9502","orcid":"https://orcid.org/0000-0003-2108-9502","contributorId":57125,"corporation":false,"usgs":true,"family":"Erwin","given":"R.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":350249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":350248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reese, Jan","contributorId":102752,"corporation":false,"usgs":true,"family":"Reese","given":"Jan","affiliations":[],"preferred":false,"id":350250,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70003802,"text":"70003802 - 2011 - Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models","interactions":[],"lastModifiedDate":"2021-01-07T20:06:01.681955","indexId":"70003802","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models","docAbstract":"

A Bayesian network model has been developed to simulate a relatively simple problem of wave propagation in the surf zone (detailed in Part I). Here, we demonstrate that this Bayesian model can provide both inverse modeling and data-assimilation solutions for predicting offshore wave heights and depth estimates given limited wave-height and depth information from an onshore location. The inverse method is extended to allow data assimilation using observational inputs that are not compatible with deterministic solutions of the problem. These inputs include sand bar positions (instead of bathymetry) and estimates of the intensity of wave breaking (instead of wave-height observations). Our results indicate that wave breaking information is essential to reduce prediction errors. In many practical situations, this information could be provided from a shore-based observer or from remote-sensing systems. We show that various combinations of the assimilated inputs significantly reduce the uncertainty in the estimates of water depths and wave heights in the model domain. Application of the Bayesian network model to new field data demonstrated significant predictive skill (R2 = 0.7) for the inverse estimate of a month-long time series of offshore wave heights. The Bayesian inverse results include uncertainty estimates that were shown to be most accurate when given uncertainty in the inputs (e.g., depth and tuning parameters). Furthermore, the inverse modeling was extended to directly estimate tuning parameters associated with the underlying wave-process model. The inverse estimates of the model parameters not only showed an offshore wave height dependence consistent with results of previous studies but the uncertainty estimates of the tuning parameters also explain previously reported variations in the model parameters.

","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.coastaleng.2010.11.002","usgsCitation":"Plant, N.G., and Holland, K.T., 2011, Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models: Coastal Engineering, v. 58, no. 3, p. 256-266, https://doi.org/10.1016/j.coastaleng.2010.11.002.","productDescription":"11 p.","startPage":"256","endPage":"266","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":204256,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e7da","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":348949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holland, K. Todd","contributorId":68748,"corporation":false,"usgs":true,"family":"Holland","given":"K.","email":"","middleInitial":"Todd","affiliations":[],"preferred":false,"id":348950,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70005276,"text":"70005276 - 2011 - Probability of detecting perchlorate under natural conditions in deep groundwater in California and the Southwestern United States","interactions":[],"lastModifiedDate":"2021-02-23T15:52:40.639899","indexId":"70005276","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Probability of detecting perchlorate under natural conditions in deep groundwater in California and the Southwestern United States","docAbstract":"We use data from 1626 groundwater samples collected in California, primarily from public drinking water supply wells, to investigate the distribution of perchlorate in deep groundwater under natural conditions. The wells were sampled for the California Groundwater Ambient Monitoring and Assessment Priority Basin Project. We develop a logistic regression model for predicting probabilities of detecting perchlorate at concentrations greater than multiple threshold concentrations as a function of climate (represented by an aridity index) and potential anthropogenic contributions of perchlorate (quantified as an anthropogenic score, AS). AS is a composite categorical variable including terms for nitrate, pesticides, and volatile organic compounds. Incorporating water-quality parameters in AS permits identification of perturbation of natural occurrence patterns by flushing of natural perchlorate salts from unsaturated zones by irrigation recharge as well as addition of perchlorate from industrial and agricultural sources. The data and model results indicate low concentrations (0.1-0.5 μg/L) of perchlorate occur under natural conditions in groundwater across a wide range of climates, beyond the arid to semiarid climates in which they mostly have been previously reported. The probability of detecting perchlorate at concentrations greater than 0.1 μg/L under natural conditions ranges from 50-70% in semiarid to arid regions of California and the Southwestern United States to 5-15% in the wettest regions sampled (the Northern California coast). The probability of concentrations above 1 μg/L under natural conditions is low (generally <3%).","language":"English","publisher":"American Chemical Society Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/es103103p","usgsCitation":"Fram, M.S., and Belitz, K., 2011, Probability of detecting perchlorate under natural conditions in deep groundwater in California and the Southwestern United States: Environmental Science & Technology, v. 45, no. 4, p. 1271-1277, https://doi.org/10.1021/es103103p.","productDescription":"7 p.","startPage":"1271","endPage":"1277","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":204538,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"45","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-01-19","publicationStatus":"PW","scienceBaseUri":"4f4e4ae4e4b07f02db689f37","contributors":{"authors":[{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":352197,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70003702,"text":"70003702 - 2011 - Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models","interactions":[],"lastModifiedDate":"2021-01-07T20:07:40.784844","indexId":"70003702","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models","docAbstract":"Prediction of coastal processes, including waves, currents, and sediment transport, can be obtained from a variety of detailed geophysical-process models with many simulations showing significant skill. This capability supports a wide range of research and applied efforts that can benefit from accurate numerical predictions. However, the predictions are only as accurate as the data used to drive the models and, given the large temporal and spatial variability of the surf zone, inaccuracies in data are unavoidable such that useful predictions require corresponding estimates of uncertainty. We demonstrate how a Bayesian-network model can be used to provide accurate predictions of wave-height evolution in the surf zone given very sparse and/or inaccurate boundary-condition data. The approach is based on a formal treatment of a data-assimilation problem that takes advantage of significant reduction of the dimensionality of the model system. We demonstrate that predictions of a detailed geophysical model of the wave evolution are reproduced accurately using a Bayesian approach. In this surf-zone application, forward prediction skill was 83%, and uncertainties in the model inputs were accurately transferred to uncertainty in output variables. We also demonstrate that if modeling uncertainties were not conveyed to the Bayesian network (i.e., perfect data or model were assumed), then overly optimistic prediction uncertainties were computed. More consistent predictions and uncertainties were obtained by including model-parameter errors as a source of input uncertainty. Improved predictions (skill of 90%) were achieved because the Bayesian network simultaneously estimated optimal parameters while predicting wave heights.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.coastaleng.2010.09.003","usgsCitation":"Plant, N.G., and Holland, K.T., 2011, Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models: Coastal Engineering, v. 58, no. 1, p. 119-130, https://doi.org/10.1016/j.coastaleng.2010.09.003.","productDescription":"12 p.","startPage":"119","endPage":"130","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":204217,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e7e4","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":348413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holland, K. Todd","contributorId":68748,"corporation":false,"usgs":true,"family":"Holland","given":"K.","email":"","middleInitial":"Todd","affiliations":[],"preferred":false,"id":348414,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70003693,"text":"70003693 - 2011 - Preface: Multiscale feedbacks in ecogeomorphology","interactions":[],"lastModifiedDate":"2017-05-23T12:19:32","indexId":"70003693","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Preface: Multiscale feedbacks in ecogeomorphology","docAbstract":"Geomorphic systems are known to exhibit nonlinear responses to physical–biological feedbacks (Thornes, 1985; Baas, 2002; Reinhardt et al., 2010). These responses make understanding and/or predicting system response to change highly challenging. With growing concerns over ecosystem health, a pressing need exists for research that tries to elucidate these feedbacks (Jerolmack, 2008; Darby, 2010; National Research Council, 2010). A session was convened at the Fall 2008 meeting of the American Geophysical Union (AGU) to provide an outlet for some of this truly interdisciplinary and original research, which is central to understanding geomorphic and ecological dynamics. The session attracted over 39 contributions, which were divided into two well-attended oral sessions and a very busy poster session. This special issue presents new research from the AGU session, which highlights clear physical–biological feedbacks. The aim is to bring together contrasting perspectives on biological and geomorphic feedbacks in a diversity of physiographic settings, ranging from wetlands and estuaries, through rivers, to uplands. These papers highlight biological and physical feedbacks which involve the modulation or amplification of geomorphic processes. These papers will be of interest to a core geomorphology audience, and should also draw attention from the fields of ecohydraulics, hydroecology, ecohydrology, ecomorphology, biogeochemistry and biogeography, and biogeomorphology as well as the more traditional fields of hydrology, ecology and biology. In this preface to the special issue, we a) review past contributions to the emerging field of ecogeomorphology and related disciplines, b) provide some context for how this topical special issue came to fruition, and c) summarize the contributions to this special issue.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.geomorph.2011.01.002","usgsCitation":"Wheaton, J.M., Gibbins, C., Wainwright, J., Larsen, L., and McElroy, B., 2011, Preface: Multiscale feedbacks in ecogeomorphology: Geomorphology, v. 126, no. 3-4, p. 265-268, https://doi.org/10.1016/j.geomorph.2011.01.002.","productDescription":"4 p.","startPage":"265","endPage":"268","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":204537,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e503","contributors":{"authors":[{"text":"Wheaton, Joseph M.","contributorId":29126,"corporation":false,"usgs":true,"family":"Wheaton","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":348371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbins, Chris","contributorId":18501,"corporation":false,"usgs":true,"family":"Gibbins","given":"Chris","affiliations":[],"preferred":false,"id":348370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wainwright, John","contributorId":6578,"corporation":false,"usgs":true,"family":"Wainwright","given":"John","email":"","affiliations":[],"preferred":false,"id":348369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Laurel G. lglarsen@usgs.gov","contributorId":1987,"corporation":false,"usgs":true,"family":"Larsen","given":"Laurel G.","email":"lglarsen@usgs.gov","affiliations":[],"preferred":false,"id":348368,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McElroy, Brandon 0000-0002-9683-4282","orcid":"https://orcid.org/0000-0002-9683-4282","contributorId":90453,"corporation":false,"usgs":true,"family":"McElroy","given":"Brandon","email":"","affiliations":[],"preferred":false,"id":348372,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70005868,"text":"sir20115192 - 2011 - Pharmaceutical compounds in Merrimack River water used for public supply, Lowell, Massachusetts, 2008-09","interactions":[],"lastModifiedDate":"2012-03-08T17:16:42","indexId":"sir20115192","displayToPublicDate":"2011-11-03T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5192","title":"Pharmaceutical compounds in Merrimack River water used for public supply, Lowell, Massachusetts, 2008-09","docAbstract":"This report presents results of a study conducted by the U.S. Geological Survey (USGS), in cooperation with the Massachusetts Department of Environmental Protection, to determine the occurrence of 14 commonly used human-health pharmaceutical compounds and fecal-indicator bacteria in Merrimack River water used as a drinking-water source by 135,000 residents in eastern Massachusetts. The study was designed to complement the USGS National Water-Quality Assessment Program's Source Water-Quality Assessment, which identifies patterns of occurrence of 280 primarily unregulated organic wastewater contaminants in source water used by community water systems and determines whether these patterns also occur in treated drinking water prior to distribution. The study involved periodic collection and analysis of raw Merrimack River water and treated drinking water over the course of 1 year. Water samples were collected periodically without regard to flow regime or antecedent weather conditions at the Lowell Regional Water Utility's Merrimack River intake upstream from Lowell, Mass. The same parcel of water was then sampled as finished water following treatment. Despite the presence of many potential sources of contamination in the drinking-water source area, only 2 of the 14 pharmaceutical analytes were detected at reportable concentrations in the source-water samples, and these occurred in only one set of periodic samples. Acetaminophen, a nonprescription analgesic, and caffeine were detected in the September source-water samples at concentrations of 0.084 and 0.068 micrograms per liter, respectively. Three other compounds-carbamazepine, an antiepileptic; cotinine, a metabolite of nicotine; and diphenhydramine, a nonprescription antihistamine-were detected in source-water samples, but at concentrations too low to be reliably quantified. None of the 14 pharmaceuticals was found in the finished water at a reportable concentration, defined as two times the long-term detection limit used by the analytical laboratory. In addition to the pharmaceutical analyses, measurements of fecal-indicator bacteria (Escherichia coli) concentrations and several physical characteristics were made on all source-water samples. Values for these constituents were consistently within State standards. It is possible that the monthly sampling schedule missed hydrologic events that would have transported greater concentrations of sewage contaminants to the sampling site, or that the large flow volume of the river at the study site effectively diluted the contaminant signal, but it is also likely that recent efforts to separate stormwater- and wastewater-discharge systems in the reaches upstream from the Lowell Regional Water Utility have greatly reduced the potential for sewage contamination at the intake.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115192","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Massey, A.J., and Waldron, M.C., 2011, Pharmaceutical compounds in Merrimack River water used for public supply, Lowell, Massachusetts, 2008-09: U.S. Geological Survey Scientific Investigations Report 2011-5192, vi, 14 p., https://doi.org/10.3133/sir20115192.","productDescription":"vi, 14 p.","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":116486,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5192.gif"},{"id":94619,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5192/","linkFileType":{"id":5,"text":"html"}}],"state":"Massachusetts","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73,42 ], [ -73,44.5 ], [ -70,44.5 ], [ -70,42 ], [ -73,42 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b08e4b07f02db69bbb3","contributors":{"authors":[{"text":"Massey, Andrew J. 0000-0003-3995-8657 ajmassey@usgs.gov","orcid":"https://orcid.org/0000-0003-3995-8657","contributorId":1862,"corporation":false,"usgs":true,"family":"Massey","given":"Andrew","email":"ajmassey@usgs.gov","middleInitial":"J.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waldron, Marcus C. mwaldron@usgs.gov","contributorId":1867,"corporation":false,"usgs":true,"family":"Waldron","given":"Marcus","email":"mwaldron@usgs.gov","middleInitial":"C.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353425,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70005871,"text":"ofr20111290 - 2011 - Conservation Effects Assessment Project-Wetlands assessment in California's Central Valley and Upper Klamath River Basin","interactions":[],"lastModifiedDate":"2017-05-10T09:50:17","indexId":"ofr20111290","displayToPublicDate":"2011-11-02T18:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1290","title":"Conservation Effects Assessment Project-Wetlands assessment in California's Central Valley and Upper Klamath River Basin","docAbstract":"Executive Summary-Ecosystem Services Derived from Wetlands Reserve Program Conservation Practices in California's Central Valley and Oregon's Upper Klamath River Basin. The Wetlands Reserve Program (WRP) is one of several programs implemented by the U.S. Department of Agriculture (USDA). Since the WRP's inception in 1990, it has resulted in the restoration of approximately 29,000 hectares in California's Central Valley (CCV) and roughly 12,300 hectares in Oregon's Upper Klamath River Basin (UKRB). Both the CCV and UKRB are agricultural dominated landscapes that have experienced extensive wetland losses and hydrological alteration. Restored habitats in the CCV and UKRB are thought to provide a variety of ecosystem services, but little is known about the actual benefits afforded. The U.S. Geological Survey (USGS) California Cooperative Fish and Wildlife Unit in collaboration with the USDA Natural Resources Conservation Service surveyed 70 WRP sites and 12 National Wildlife Refuge sites in the CCV, and 11 sites in the UKRB to estimate ecosystem services provided. In the CCV, sites were selected along three primary gradients; (1) restoration age, (2) management intensity, and (3) latitude (climate). Sites in the UKRB were assessed along restoration age and management intensity gradients where possible. The management intensity gradient included information about the type and frequency of conservation practices applied at each site, which was then ranked into three categories that differentiated sites primarily along a hydrological gradient. Information collected was used to estimate the following ecosystem services: Soil and vegetation nutrient content, soil loss reduction, floodwater storage as well as avian, amphibian, fish, and pollinator use and habitat availability. Prior to this study, very little was known about WRP habitat morphology in the CCV and UKRB. Therefore in this study, we described these habitats and related them to ecosystem services provided. Our results indicate that although WRP in the CCV and UKRB provide a number of benefits, there may be management mediated trade-offs among ecosystem services. In this report, we considered ecosystem services at the site-specific scale; however, future work will extend to include effects of WRP relative to surrounding cropland.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111290","usgsCitation":"2011, Conservation Effects Assessment Project-Wetlands assessment in California's Central Valley and Upper Klamath River Basin: U.S. Geological Survey Open-File Report 2011-1290, vi, 115 p.; Appendices, https://doi.org/10.3133/ofr20111290.","productDescription":"vi, 115 p.; Appendices","startPage":"i","endPage":"128","numberOfPages":"134","additionalOnlineFiles":"N","ipdsId":"IP-030781","costCenters":[{"id":150,"text":"California Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":116305,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1290.png"},{"id":94612,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1290/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123,35 ], [ -123,41 ], [ -119,41 ], [ -119,35 ], [ -123,35 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b05e4b07f02db699dfb","contributors":{"editors":[{"text":"Duffy, Walter G. wgd7001@usgs.gov","contributorId":66750,"corporation":false,"usgs":true,"family":"Duffy","given":"Walter","email":"wgd7001@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":false,"id":508292,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Kahara, Sharon N.","contributorId":35577,"corporation":false,"usgs":true,"family":"Kahara","given":"Sharon","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":508291,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Records, Rosemary M.","contributorId":111772,"corporation":false,"usgs":true,"family":"Records","given":"Rosemary","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":508293,"contributorType":{"id":2,"text":"Editors"},"rank":3}]}} ,{"id":70003315,"text":"70003315 - 2011 - Pore-throat sizes in sandstones, siltstones, and shales: Reply","interactions":[],"lastModifiedDate":"2021-01-05T15:21:13.629027","indexId":"70003315","displayToPublicDate":"2011-11-02T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":701,"text":"American Association of Petroleum Geologists Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Pore-throat sizes in sandstones, siltstones, and shales: Reply","docAbstract":"In his discussion of my article (Nelson, 2009), W. K. Camp takes issue with the concept that buoyancy is not the dominant force in forming and maintaining the distribution of gas in tight-gas accumulations (Camp, 2011). I will restrict my response to the issues he raised regarding buoyant versus nonbuoyant drive and to a few comments regarding water saturation and production. I claim that the pressure generated in petroleum source rocks (Pg), instead of the buoyancy pressure (Pb), provides the energy to charge most tight sandstones with gas. The arguments are fourfold: (1) buoyant columns of sufficient height seldom exist in low-permeability sand-shale sequences, (2) tight-gas systems display a pressure profile that declines instead of increases upward, (3) gas is pervasive in overpressured systems, and (4) source rocks can generate pore pressures sufficiently high to charge tight sandstones.","language":"English","publisher":"American Association of Petroleum Geologists (AAPG)","publisherLocation":"Tulsa, OK","doi":"10.1306/12141010159","usgsCitation":"Nelson, P.H., 2011, Pore-throat sizes in sandstones, siltstones, and shales: Reply: American Association of Petroleum Geologists Bulletin, v. 95, no. 8, p. 1448-1453, https://doi.org/10.1306/12141010159.","productDescription":"6 p.","startPage":"1448","endPage":"1453","numberOfPages":"6","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":204511,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adae4b07f02db6855c1","contributors":{"authors":[{"text":"Nelson, Philip H. pnelson@usgs.gov","contributorId":862,"corporation":false,"usgs":true,"family":"Nelson","given":"Philip","email":"pnelson@usgs.gov","middleInitial":"H.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":346865,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}