The myriad definitions of soil/ecosystem quality or health are often driven by ecosystem and management concerns, and they typically focus on the ability of the soil to provide functions relating to biological productivity and/or environmental quality. A variety of attempts have been made to create indices that quantify the complexities of soil quality and provide a means of evaluating the impact of various natural and anthropogenic disturbances. Though not without their limitations, indices can improve our understanding of the controls behind ecosystem processes and allow for the distillation of information to help link scientific and management communities. In terrestrial systems, indices were initially developed and modified for agroecosystems; however, the number of studies implementing such indices in nonagricultural systems is growing. Soil quality indices (SQIs) are typically composed of biological (and sometimes physical and chemical) parameters that attempt to reduce the complexity of a system into a metric of a soil’s ability to carry out one or more functions.
The indicators utilized in SQIs can be as varied as the studies themselves, reflecting the complexity of the soil and ecosystems in which they function. Regardless, effective soil quality indicators should correlate well with soil or ecosystem processes, integrate those properties and processes, and be relevant to management practices. Commonly applied biological indicators include measures associated with soil microbial activity or function (for example, carbon and nitrogen mineralization, respiration, microbial biomass, enzyme activity. Cost, accessibility, ease of interpretation, and presence of existing data often dictate indicator selection given the number of available measures. We employed a large number of soil biological, chemical, and physical measures, along with measures of vegetation cover, density, and productivity, in order to test the utility and sensitivity of these measures within various mineralized terranes. We were also interested in examining these relations in the context of determining appropriate reference conditions with which to compare reclamation efforts.
The purpose of this report is to present the data used to develop indices of soil and ecosystem quality associated with mineralized terranes (areas enriched in metal-bearing minerals), specifically podiform chromite, quartz alunite, and Mo/Cu porphyry systems. Within each of these mineralized terranes, a nearby unmineralized counterpart was chosen for comparison. The data consist of soil biological, chemical, and physical parameters, along with vegetation measurements for each of the sites described below. Synthesis of these data and index development will be the subject of future publications.
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The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft.\r\n\r\nElevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ds464","usgsCitation":"Yates, X., Nayegandhi, A., Brock, J., Sallenger, A., Klipp, E.S., and Wright, C.W., 2010, ATM Coastal Topography-Louisiana, 2001: UTM Zone 15 (Part 1 of 2): U.S. Geological Survey Data Series 464, HTML Document: DVD, https://doi.org/10.3133/ds464.","productDescription":"HTML Document: DVD","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":423295,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_97204.htm","linkFileType":{"id":5,"text":"html"}},{"id":13616,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/464/","linkFileType":{"id":5,"text":"html"}},{"id":118653,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_464.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90,\n 29.0439\n ],\n [\n -90,\n 29.2417\n ],\n [\n -90.9542,\n 29.2417\n ],\n [\n -90.9542,\n 29.0439\n ],\n [\n -90,\n 29.0439\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b14e4b07f02db6a43b0","contributors":{"authors":[{"text":"Yates, Xan","contributorId":78291,"corporation":false,"usgs":true,"family":"Yates","given":"Xan","email":"","affiliations":[],"preferred":false,"id":305102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":305099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":305097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sallenger, A. 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This volume is a compilation of the reports already provided to the Forest Service by the author in fiscal years 2006-2009 (October 2006-September 2009). Altogether, the reports describe the geology and locatable mineral resource potential of 57 properties offered in 10 land-exchange proposals. Approximately 41,084 acres were evaluated: 19,068 acres in Federal parcels and 22,016 acres in non-Federal parcels. The parcels are located in eight National Forests and one National Grassland in three States.\r\n\r\nLocatable Mineral Reports provide a summary of the geology and a subjective appraisal of the mineral resource potential of land parcels considered for exchange. Information in each report is based on a review of published maps and reports, unpublished data in U.S. Geological Survey files, the professional expertise of the writer, and interviews with other knowledgeable geoscientists. No visits were conducted to support the reports included in this volume. The mineral resource information provided is used in making relative comparisons of the potential future mineral value of lands being offered in an exchange and in appraising the value of the land. Future mineral potential value is subjectively expressed in qualitative terms using a three-tier nomenclature of 'high,' 'moderate,' and 'low.' In general, 'high' is applied where mineral deposits are present on the property or adjacent to it or there are other indications that the area has been mineralized. 'Moderate' is applied where mineralization is only suspected or where an area possesses some of the same geologic characteristics that are common to areas around known mineral deposits. A 'low' value is routinely applied to all remaining areas, with the understanding that the information required to prove the absence of any mineral resource potential will never be available. Copies of the reports reside in U.S. Geological Survey Mineral Resource Program and USDA Forest Service files.\r\n\r\nTen reports are included in this volume. They are grouped by State, then alphabetically by Forest. Each starts with a cover letter and title page. Geologic descriptions of properties, their mineral potential, and references make up the main body of each report. Legal descriptions of the property locations (either verbatim or paraphrased from descriptions supplied by the Forest Service) are included as attachments designated Exhibits A and B. Also included as attachments are the report request from the USDA Forest Service and any index maps, geologic maps, or other figures or illustrations that are provided for the convenience of the Forest Service minerals examiner. Page numbers for each individual report are retained: the larger number at the bottom of each page is the pagination for this volume.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101084","usgsCitation":"Wilson, A.B., 2010, Locatable Mineral Reports for Colorado, South Dakota, and Wyoming provided to the USDA Forest Service in Fiscal Years 2006-2009: U.S. Geological Survey Open-File Report 2010-1084, v, 111 p., https://doi.org/10.3133/ofr20101084.","productDescription":"v, 111 p.","onlineOnly":"Y","temporalStart":"2006-10-01","temporalEnd":"2009-09-30","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":125905,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1084.jpg"},{"id":401795,"rank":3,"type":{"id":36,"text":"NGMDB Index 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a68e4b07f02db63b2c6","contributors":{"authors":[{"text":"Wilson, Anna B. 0000-0002-9737-2614 awilson@usgs.gov","orcid":"https://orcid.org/0000-0002-9737-2614","contributorId":1619,"corporation":false,"usgs":true,"family":"Wilson","given":"Anna","email":"awilson@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":305089,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70202938,"text":"70202938 - 2010 - Development of a three-dimensional model of sedimentary texture in valley-fill deposits of Central Valley, California, USA","interactions":[],"lastModifiedDate":"2019-04-05T15:22:21","indexId":"70202938","displayToPublicDate":"2010-05-01T15:22:11","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Development of a three-dimensional model of sedimentary texture in valley-fill deposits of Central Valley, California, USA","docAbstract":"A three-dimensional (3D) texture model was developed to help characterize the aquifer system of Central Valley, California (USA), for a groundwater flow model. The 52,000-km2 Central Valley aquifer system consists of heterogeneous valley-fill deposits. The texture model was developed by compiling and analyzing approximately 8,500 drillers’ logs, describing lithologies up to 950 m below land surface. The lithologic descriptions on the logs were simplified into a binary classification of coarse- and fine-grained. The percentage of coarse-grained sediment, or texture, was then computed for each 15-m depth interval. The model was developed by 3D kriging of the percentage of coarse-grained deposits onto a 1.6-km spatial grid at 15-m depth intervals from land surface down to 700 m below land surface. The texture model reflects the known regional, spatial, and vertical heterogeneity in the aquifer system. The texture model correlates to sediment source areas, independently mapped geomorphic provinces, and factors affecting the development of alluvial fans, thus demonstrating the utility of using tcdrillers’ logs as a source of lithologic information. The texture model is upscaled to a layered groundwater flow model for use in defining the hydraulic properties of the aquifer system.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-009-0539-7","usgsCitation":"Faunt, C., Belitz, K., and Hanson, R.T., 2010, Development of a three-dimensional model of sedimentary texture in valley-fill deposits of Central Valley, California, USA: Hydrogeology Journal, v. 18, no. 3, p. 625-649, https://doi.org/10.1007/s10040-009-0539-7.","productDescription":"25 p.","startPage":"625","endPage":"649","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":362822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.057861328125,\n 34.88593094075317\n ],\n [\n -118.54248046874999,\n 34.88593094075317\n ],\n [\n -118.54248046874999,\n 40.70562793820589\n ],\n [\n -123.057861328125,\n 40.70562793820589\n ],\n [\n -123.057861328125,\n 34.88593094075317\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"3","noUsgsAuthors":false,"publicationDate":"2009-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Faunt, Claudia C. 0000-0001-5659-7529 ccfaunt@usgs.gov","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":150147,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia C.","email":"ccfaunt@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760553,"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":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760555,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200398,"text":"70200398 - 2010 - Depth-dependent sampling to identify short-circuit pathways to public-supply wells in multiple aquifer settings in the United States","interactions":[],"lastModifiedDate":"2018-10-16T14:18:58","indexId":"70200398","displayToPublicDate":"2010-05-01T14:18:43","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Depth-dependent sampling to identify short-circuit pathways to public-supply wells in multiple aquifer settings in the United States","docAbstract":"Depth-dependent water-quality and borehole flow data were used to determine where and how contamination enters public-supply wells (PSWs) at study sites in different principal aquifers of the United States. At each of three study sites, depth-dependent samples and wellbore flow data were collected from multiple depths in selected PSWs under pumping conditions. The chemistry of these depth-dependent samples, along with samples of the surface discharge from the PSWs, was compared to that of adjacent nested monitoring wells. The results of depth-dependent analyses from sites in Modesto (California), York (Nebraska), and Tampa (Florida) are summarized and compared. Although the exact mechanisms for transport of contaminants to the PSWs varied among these hydrogeologic settings, in all three settings the presence of wells or boreholes or natural preferential flow paths allowed water and contaminants to bypass substantial portions of the aquifer and to reach PSWs or depths in the aquifer more quickly than would have occurred in the absence of these short-circuiting flow paths. The chemistry and flow data from multiple depths was essential to developing an understanding of the dominant flow paths of contaminants to PSW in all three settings. This knowledge contributes to developing effective strategies for monitoring and protection.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-009-0531-2","usgsCitation":"Landon, M.K., Jurgens, B.C., Katz, B.G., Eberts, S.M., Burow, K.R., and Crandall, C.A., 2010, Depth-dependent sampling to identify short-circuit pathways to public-supply wells in multiple aquifer settings in the United States: Hydrogeology Journal, v. 18, no. 3, p. 577-593, https://doi.org/10.1007/s10040-009-0531-2.","productDescription":"17 p.","startPage":"577","endPage":"593","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":358406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"3","noUsgsAuthors":false,"publicationDate":"2009-10-20","publicationStatus":"PW","scienceBaseUri":"5c10c715e4b034bf6a7f50b8","contributors":{"authors":[{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Katz, Brian G. bkatz@usgs.gov","contributorId":1093,"corporation":false,"usgs":true,"family":"Katz","given":"Brian","email":"bkatz@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":748721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eberts, Sandra M. 0000-0001-5138-8293 smeberts@usgs.gov","orcid":"https://orcid.org/0000-0001-5138-8293","contributorId":127844,"corporation":false,"usgs":true,"family":"Eberts","given":"Sandra","email":"smeberts@usgs.gov","middleInitial":"M.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":748722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burow, Karen R. 0000-0001-6006-6667 krburow@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-6667","contributorId":1504,"corporation":false,"usgs":true,"family":"Burow","given":"Karen","email":"krburow@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748723,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crandall, Christy A. crandall@usgs.gov","contributorId":1091,"corporation":false,"usgs":true,"family":"Crandall","given":"Christy","email":"crandall@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":748724,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70003826,"text":"70003826 - 2010 - A consumer-resource approach to the density-dependent population dynamics of mutualism","interactions":[],"lastModifiedDate":"2021-01-18T12:46:54.67024","indexId":"70003826","displayToPublicDate":"2010-05-01T13:50:04","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A consumer-resource approach to the density-dependent population dynamics of mutualism","docAbstract":"Like predation and competition, mutualism is now recognized as a consumer resource (C-R) interaction, including, in particular, bi-directional (e.g., coral, plant- mycorrhizae) and uni-directional (e.g., ant-plant defense, plant-pollinator) C-R mutualisms. Here, we develop general theory for the density-dependent population dynamics of mutualism based on the C-R mechanism of interspecific interaction. To test the influence of C-R interactions on the dynamics and stability of bi- and uni-directional C-R mutualisms, we developed simple models that link consumer functional response of one mutualistic species with the resources supplied by another. Phase-plane analyses show that the ecological dynamics of C-R mutualisms are stable in general. Most transient behavior leads to an equilibrium of mutualistic coexistence, at which both species densities are greater than in the absence of interactions. However, due to the basic nature of C-R interactions, certain density-dependent conditions can lead to C-R dynamics characteristic of predator-prey interactions, in which one species overexploits and causes the other to go extinct. Consistent with empirical phenomena, these results suggest that the C-R interaction can provide a broad mechanism for understanding density-dependent population dynamics of mutualism. By unifying predation, competition, and mutualism under the common ecological framework of consumer-resource theory, we may also gain a better understanding of the universal features of interspecific interactions in general.","language":"English","publisher":"Ecological Society of America","doi":"10.1890/09-1163.1","usgsCitation":"Holland, J.N., and DeAngelis, D., 2010, A consumer-resource approach to the density-dependent population dynamics of mutualism: Ecology, v. 91, no. 5, p. 1286-1295, https://doi.org/10.1890/09-1163.1.","productDescription":"10 p.","startPage":"1286","endPage":"1295","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":382190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd49b1e4b0b290850ef567","contributors":{"authors":[{"text":"Holland, J. Nathaniel","contributorId":49912,"corporation":false,"usgs":true,"family":"Holland","given":"J.","email":"","middleInitial":"Nathaniel","affiliations":[],"preferred":false,"id":349040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":88015,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","affiliations":[],"preferred":false,"id":349041,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199496,"text":"70199496 - 2010 - Optimal pump and recharge management model for nitrate removal in the Warren groundwater basin, California","interactions":[],"lastModifiedDate":"2018-09-19T13:18:44","indexId":"70199496","displayToPublicDate":"2010-05-01T13:17:38","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2501,"text":"Journal of Water Resources Planning and Management","active":true,"publicationSubtype":{"id":10}},"title":"Optimal pump and recharge management model for nitrate removal in the Warren groundwater basin, California","docAbstract":"The town of Yucca Valley located in the southwest part of the Mojave Desert in southern California relies on groundwater pumping from the Warren groundwater basin as its sole source of water supply. This significant dependency has resulted in a large imbalance between groundwater pumpage and natural recharge, causing groundwater levels in the basin to decline more than 90 m from the late 1940s to 1994. Consequently, an artificial recharge program proposed by the Hi-Desert Water District, which provides water service to the town of Yucca Valley, was implemented for the purpose of recovering the groundwater levels; however, the rise in groundwater levels has caused nitrate
Mechanistic explanations of herbivore spatial distribution have focused largely on either resource‐related (bottom‐up) or predation‐related (top‐down) factors. We studied direct and indirect influences on the spatial distributions of Serengeti herbivore hotspots, defined as temporally stable areas inhabited by mixed herds of resident grazers. Remote sensing and variation in landscape features were first used to create a map of the spatial distribution of hotspots, which was tested for accuracy against an independent data set of herbivore observations. Subsequently, we applied structural equation modeling to data on soil fertility and plant quality and quantity across a range of sites. We found that hotspots in Serengeti occur in areas that are relatively flat and located away from rivers, sites where ungulates are less susceptible to predation. Further, hotspots tend to occur in areas where hydrology and rainfall create conditions of relatively low‐standing plant biomass, which, coupled with grazing, increases forage quality while decreasing predation risk. Low‐standing biomass and higher leaf concentrations of N, Na, and Mg were strong direct predictors of hotspot occurrence. Soil fertility had indirect effects on hotspot occurrence by promoting leaf Na and Mg. The results indicate that landscape features contribute in direct and indirect ways to influence the spatial distribution of hotspots and that the best models incorporated both resource‐ and predation‐related factors. Our study highlights the collective and simultaneous role of bottom‐up and top‐down factors in determining ungulate spatial distributions.
During the past 2 decades, the grizzly bear (Ursus arctos) population in the Greater Yellowstone Ecosystem (GYE) has increased in numbers and expanded its range. Early efforts to model grizzly bear mortality were principally focused within the United States Fish and Wildlife Service Grizzly Bear Recovery Zone, which currently represents only about 61% of known bear distribution in the GYE. A more recent analysis that explored one spatial covariate that encompassed the entire GYE suggested that grizzly bear survival was highest in Yellowstone National Park, followed by areas in the grizzly bear Recovery Zone outside the park, and lowest outside the Recovery Zone. Although management differences within these areas partially explained differences in grizzly bear survival, these simple spatial covariates did not capture site-specific reasons why bears die at higher rates outside the Recovery Zone. Here, we model annual survival of grizzly bears in the GYE to 1) identify landscape features (i.e., foods, land management policies, or human disturbances factors) that best describe spatial heterogeneity among bear mortalities, 2) spatially depict the differences in grizzly bear survival across the GYE, and 3) demonstrate how our spatially explicit model of survival can be linked with demographic parameters to identify source and sink habitats. We used recent data from radiomarked bears to estimate survival (1983–2003) using the known-fate data type in Program MARK. Our top models suggested that survival of independent (age ≥2 yr) grizzly bears was best explained by the level of human development of the landscape within the home ranges of bears. Survival improved as secure habitat and elevation increased but declined as road density, number of homes, and site developments increased. Bears living in areas open to fall ungulate hunting suffered higher rates of mortality than bears living in areas closed to hunting. Our top model strongly supported previous research that identified roads and developed sites as hazards to grizzly bear survival. We also demonstrated that rural homes and ungulate hunting negatively affected survival, both new findings. We illustrate how our survival model, when linked with estimates of reproduction and survival of dependent young, can be used to identify demographically the source and sink habitats in the GYE. Finally, we discuss how this demographic model constitutes one component of a habitat-based framework for grizzly bear conservation. Such a framework can spatially depict the areas of risk in otherwise good habitat, providing a focus for resource management in the GYE.
","language":"English","publisher":"The Wildlife Society","doi":"10.2193/2009-206","usgsCitation":"Schwartz, C.C., Haroldson, M.A., and White, G., 2010, Hazards affecting grizzly bear survival in the Greater Yellowstone Ecosystem: Journal of Wildlife Management, v. 74, no. 4, p. 654-667, https://doi.org/10.2193/2009-206.","productDescription":"14 p.","startPage":"654","endPage":"667","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":398123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.03857421875,\n 43.54854811091286\n ],\n [\n -109.248046875,\n 43.54854811091286\n ],\n [\n -109.248046875,\n 45.36758436884978\n ],\n [\n -112.03857421875,\n 45.36758436884978\n ],\n [\n -112.03857421875,\n 43.54854811091286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"74","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Schwartz, Charles C.","contributorId":55950,"corporation":false,"usgs":true,"family":"Schwartz","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":839660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":839661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Gary C.","contributorId":287795,"corporation":false,"usgs":false,"family":"White","given":"Gary C.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":839662,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70171012,"text":"70171012 - 2010 - Agronomic and environmental implications of enhanced s-triazine degradation","interactions":[],"lastModifiedDate":"2018-08-20T17:55:27","indexId":"70171012","displayToPublicDate":"2010-05-01T11:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3035,"text":"Pest Management Science","active":true,"publicationSubtype":{"id":10}},"title":"Agronomic and environmental implications of enhanced s-triazine degradation","docAbstract":"Novel catabolic pathways enabling rapid detoxification of s-triazine herbicides have been elucidated and detected at a growing number of locations. The genes responsible for s-triazine mineralization, i.e. atzABCDEF and trzNDF, occur in at least four bacterial phyla and are implicated in the development of enhanced degradation in agricultural soils from all continents except Antarctica. Enhanced degradation occurs in at least nine crops and six crop rotation systems that rely on s-triazine herbicides for weed control, and, with the exception of acidic soil conditions and s-triazine application frequency, adaptation of the microbial population is independent of soil physiochemical properties and cultural management practices. From an agronomic perspective, residual weed control could be reduced tenfold in s-triazine-adapted relative to non-adapted soils. From an environmental standpoint, the off-site loss of total s-triazine residues could be overestimated 13-fold in adapted soils if altered persistence estimates and metabolic pathways are not reflected in fate and transport models. Empirical models requiring soil pH and s-triazine use history as input parameters predict atrazine persistence more accurately than historical estimates, thereby allowing practitioners to adjust weed control strategies and model input values when warranted.
","language":"English","publisher":"Society of Chemical Industry","publisherLocation":"West Sussex, UK","doi":"10.1002/ps.1909","usgsCitation":"Krutz, L.J., Shaner, D.L., Weaver, M.A., Webb, R.M., Zablotowicz, R.M., Reddy, K.N., Huang, Y., and Thompson, S.J., 2010, Agronomic and environmental implications of enhanced s-triazine degradation: Pest Management Science, v. 66, no. 5, p. 461-481, https://doi.org/10.1002/ps.1909.","productDescription":"21 p.","startPage":"461","endPage":"481","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-016797","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":321278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2010-02-02","publicationStatus":"PW","scienceBaseUri":"574d643ae4b07e28b6683497","contributors":{"authors":[{"text":"Krutz, L. Jason","contributorId":169420,"corporation":false,"usgs":false,"family":"Krutz","given":"L.","email":"","middleInitial":"Jason","affiliations":[{"id":25506,"text":"USDA Agricultural Research Serv., Stoneville, MS","active":true,"usgs":false}],"preferred":false,"id":629531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shaner, Dale L.","contributorId":169419,"corporation":false,"usgs":false,"family":"Shaner","given":"Dale","email":"","middleInitial":"L.","affiliations":[{"id":25505,"text":"USDA Agricultural Research Service, Ft. Collins, CO","active":true,"usgs":false}],"preferred":false,"id":629530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weaver, Mark A.","contributorId":169422,"corporation":false,"usgs":false,"family":"Weaver","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":25507,"text":"USDA, Stoneville, MS","active":true,"usgs":false}],"preferred":false,"id":629532,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":629529,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zablotowicz, Robert M.","contributorId":169424,"corporation":false,"usgs":false,"family":"Zablotowicz","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":25507,"text":"USDA, Stoneville, MS","active":true,"usgs":false}],"preferred":false,"id":629534,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reddy, Krishna N.","contributorId":169425,"corporation":false,"usgs":false,"family":"Reddy","given":"Krishna","email":"","middleInitial":"N.","affiliations":[{"id":25507,"text":"USDA, Stoneville, MS","active":true,"usgs":false}],"preferred":false,"id":629535,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huang, Yanbo","contributorId":194197,"corporation":false,"usgs":false,"family":"Huang","given":"Yanbo","email":"","affiliations":[],"preferred":false,"id":629533,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thompson, Steven J.","contributorId":169426,"corporation":false,"usgs":false,"family":"Thompson","given":"Steven","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629536,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70230192,"text":"70230192 - 2010 - Sediment-hosted lead-zinc deposits in Earth history","interactions":[],"lastModifiedDate":"2022-04-04T15:27:10.820413","indexId":"70230192","displayToPublicDate":"2010-05-01T10:22:17","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Sediment-hosted lead-zinc deposits in Earth history","docAbstract":"Sediment-hosted Pb-Zn deposits can be divided into two major subtypes. The first subtype is clastic-dominated lead-zinc (CD Pb-Zn) ores, which are hosted in shale, sandstone, siltstone, or mixed clastic rocks, or occur as carbonate replacement, within a CD sedimentary rock sequence. This subtype includes deposits that have been traditionally referred to as sedimentary exhalative (SEDEX) deposits. The CD Pb-Zn deposits occur in passive margins, back-arcs and continental rifts, and sag basins, which are tectonic settings that, in some cases, are transitional into one another. The second subtype of sediment-hosted Pb-Zn deposits is the Mississippi Valley-type (MVT Pb-Zn) that occurs in platform carbonate sequences, typically in passive-margin tectonic settings.
Considering that the redox state of sulfur is one of the major controls on the extraction, transport, and deposition of Pb and Zn at shallow crustal sites, sediment-hosted Pb-Zn ores can be considered a special rock type that recorded the oxygenation of Earth’s hydrosphere. The emergence of CD and MVT deposits in the rock record between 2.02 Ga, the age of the earliest known deposit of these ores, and 1.85 to 1.58 Ga, a major period of CD Pb-Zn mineralization in Australia and India, corresponds to a time after the Great Oxygenation Event that occurred at ca 2.4 to 1.8 Ga. Contributing to the abundance of CD deposits at ca 1.85 to 1.58 Ga was the following: (1) enhanced oxidation of sulfides in the crust that provided sulfate to the hydrosphere and Pb and Zn to sediments; (2) development of major redox and compositional gradients in the oceans; (3) first formation of significant sulfate-bearing evaporites; (4) formation of red beds and oxidized aquifers, possibly containing easily extractable Pb and Zn; (5) evolution of sulfate-reducing bacteria; and (6) formation of large and long-lived basins on stable cratons.
Although MVT and CD deposits appeared for the first time in Earth history at 2.02 Ga, only CD deposits were important repositories for Pb and Zn in sediments between the Great Oxygenation Event, until after the second oxidation of the atmosphere in the late Neoproterozic. Increased oxygenation of the oceans following the second oxidation event led to an abundance of evaporites, resulting oxidized brines, and a dramatic increase in the volume of coarse-grained and permeable carbonates of the Paleozoic carbonate platforms, which host many of the great MVT deposits. The MVT deposits reached their maximum abundance during the final assembly of Pangea from Devonian into the Carboniferous. This was also a time for important CD mineral deposit formation along passive margins in evaporative belts of Pangea. Following the breakup of Pangea, a new era of MVT ores began with the onset of the assembly of the Neosupercontinent.
A significant limitation on interpreting the secular distribution of the deposits is that there is no way to quantitatively evaluate the removal of deposits from the rock record through tectonic recycling. Considering that most of the sedimentary rock record has been recycled, most sediment-hosted Pb-Zn deposits probably have also been destroyed by subduction and erosion, or modified by metamorphism and tectonism, so that they are no longer recognizable. Thus, the uneven secular distribution of sediment-hosted Pb-Zn deposits reflects the genesis of these deposits, linked to Earth’s evolving tectonic and geochemical systems, as well as an unknown amount of recycling of the sedimentary rock record.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/gsecongeo.105.3.593","usgsCitation":"Leach, D.L., Bradley, D., Huston, D., Pisarevsky, S.A., Taylor, R.D., and Gardoll, S., 2010, Sediment-hosted lead-zinc deposits in Earth history: Economic Geology, v. 105, no. 3, p. 593-625, https://doi.org/10.2113/gsecongeo.105.3.593.","productDescription":"33 p.","startPage":"593","endPage":"625","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":398012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"3","noUsgsAuthors":false,"publicationDate":"2010-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Leach, David L 0000-0001-6487-5584","orcid":"https://orcid.org/0000-0001-6487-5584","contributorId":220733,"corporation":false,"usgs":false,"family":"Leach","given":"David","email":"","middleInitial":"L","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":839444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradley, Dwight 0000-0001-9116-5289 bradleyorchard2@gmail.com","orcid":"https://orcid.org/0000-0001-9116-5289","contributorId":2358,"corporation":false,"usgs":true,"family":"Bradley","given":"Dwight","email":"bradleyorchard2@gmail.com","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":839445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huston, David","contributorId":261768,"corporation":false,"usgs":false,"family":"Huston","given":"David","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":839446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pisarevsky, Sergei A.","contributorId":62315,"corporation":false,"usgs":true,"family":"Pisarevsky","given":"Sergei","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":839447,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Ryan D. 0000-0002-8845-5290 rtaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":3412,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"rtaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":839448,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gardoll, S.","contributorId":94820,"corporation":false,"usgs":true,"family":"Gardoll","given":"S.","email":"","affiliations":[],"preferred":false,"id":839449,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199968,"text":"70199968 - 2010 - Evaluating remediation alternatives for mine drainage, Little Cottonwood Creek, Utah, USA","interactions":[],"lastModifiedDate":"2018-10-09T10:13:00","indexId":"70199968","displayToPublicDate":"2010-05-01T10:12:36","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1534,"text":"Environmental Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating remediation alternatives for mine drainage, Little Cottonwood Creek, Utah, USA","docAbstract":"The vast occurrence of mine drainage worldwide, documented in descriptive studies, presents a staggering challenge for remediation. Any tool that can move beyond descriptive study and helps to evaluate options for remediation in a way that maximizes improvements to the water quality of streams and minimizes cost of remediation could save valuable resources and time. A reactive solute transport model, calibrated from two detailed mass-loading studies in Little Cottonwood Creek (LCC), Utah, provides a tool to evaluate remediation options. Metal loading to LCC is dominated by discharge from two mine drainage tunnels. Discharge from an upstream tunnel has been treated by a fen to reduce metal loading. Discharge from the downstream tunnel (WDT) can be controlled because of a bulkhead that creates a mine pool. Simulations of remedial options for three compliance locations suggest that the water-quality standards for Cu and Zn at upstream and downstream compliance locations are met using various combinations of fen treatment and WDT regulation, but the complete compliance at the middle compliance location requires the highest level of fen treatment and the greatest regulation of WDT discharge. Reactive transport modeling is an useful tool for the evaluation of remedial alternatives in complex natural systems, where multiple hydrologic and geochemical processes determine metal fate.
","language":"English","publisher":"Springer Berlin Heidelberg","doi":"10.1007/s12665-009-0240-0","usgsCitation":"Kimball, B.A., and Runkel, R.L., 2010, Evaluating remediation alternatives for mine drainage, Little Cottonwood Creek, Utah, USA: Environmental Earth Sciences, v. 60, no. 5, p. 1021-1036, https://doi.org/10.1007/s12665-009-0240-0.","productDescription":"16p.","startPage":"1021","endPage":"1036","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":358196,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Little Cottonwood Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.9451904296875,\n 40.55085246740427\n ],\n [\n -111.9451904296875,\n 40.6504293761137\n ],\n [\n -111.76391601562499,\n 40.6504293761137\n ],\n [\n -111.76391601562499,\n 40.55085246740427\n ],\n [\n -111.9451904296875,\n 40.55085246740427\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"60","issue":"5","noUsgsAuthors":false,"publicationDate":"2009-08-07","publicationStatus":"PW","scienceBaseUri":"5c10c716e4b034bf6a7f50cf","contributors":{"authors":[{"text":"Kimball, Briant A. bkimball@usgs.gov","contributorId":533,"corporation":false,"usgs":true,"family":"Kimball","given":"Briant","email":"bkimball@usgs.gov","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":747521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":747522,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70230289,"text":"70230289 - 2010 - Displaying seismic deaggregation: The importance of the various sources","interactions":[],"lastModifiedDate":"2022-04-06T16:13:19.664095","indexId":"70230289","displayToPublicDate":"2010-05-01T09:51:50","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Displaying seismic deaggregation: The importance of the various sources","docAbstract":"Seismic hazard deaggregation has become a standard part of probabilistic seismic hazard assessment (PSHA). The first product of PSHA is calculation of the likely severity of ground motion at a given range of annual probability levels, and this is extremely important for seismic design of structures to be built at the site under examination. However, for full analysis of proposed structural designs, engineers also need to examine scenario events to produce detailed time histories. To select such scenarios, a deaggregation of the hazard is performed, whereby the details of sources that contribute to the annual frequency of exceeding specified levels of ground motion, or Pexc, are identified. A common format for such a deaggregation is shown in Figure 1. This relates to the 475-year peak ground acceleration (pga) at Wellington, New Zealand (41.28°S 174.77°E), and shows the distribution in magnitude and distance of sources that contribute to Pexc. Return period is approximately the reciprocal of Pexc. Stiff soil site conditions (Standards New Zealand 2004) were assumed.
The analysis in Figure 1 used the interim version of the updated seismic hazard model for New Zealand (Stirling et al. 2007), with the attenuation function developed by McVerry et al. (2007). Based on a Poisson time dependence model, a return period of 475 years corresponds to a 10% probability of exceedance in 50 years.
From Figure 1, it is apparent that for this site the main contribution to ground motion of this severity is from earthquakes of magnitude about 7.6 less than 10 km from the site (blue), and there is another strong contribution from larger events in the distance range 10 to 20 km (red). These correspond to the Wellington and Wairarapa faults, respectively (see Table 1). There are other events less than 10 km from the site and small contributions from other sources. At this site the major contributions are from specific faults nearby, which are readily identified. At sites where there is significant background seismicity, however, the plot will be much more complicated and not so easy to interpret.
Figure 1 deaggregates probabilistic pga at the site; other parameters are also commonly deaggregated in the same way, in particular response spectral acceleration at a variety of natural periods. But the figure has a major shortcoming in that it represents only one return period; to obtain a full appreciation of the various contributing sources it is necessary to perform a succession of analyses to cover the full range of return periods.
The variation of permeability with depth can be probed indirectly by various means, including hydrologic models that use geothermal data as constraints and the progress of metamorphic reactions driven by fluid flow. Geothermal and metamorphic data combine to indicate that mean permeability (k) of tectonically active continental crust decreases with depth (z) according to log k ≈ −14–3.2 log z, where k is in m2 and z in km. Other independently derived, crustal‐scale k–z relations are generally similar to this power‐law curve. Yet there is also substantial evidence for local‐to‐regional‐scale, transient, permeability‐generation events that entail permeabilities much higher than these mean k–z relations would suggest. Compilation of such data yields a fit to these elevated, transient values of log k ≈ −11.5–3.2 log z, suggesting a functional form similar to that of tectonically active crust, but shifted to higher permeability at a given depth. In addition, it seems possible that, in the absence of active prograde metamorphism, permeability in the deeper crust will decay toward values below the mean k–z curves. Several lines of evidence suggest geologically rapid (years to 103 years) decay of high‐permeability transients toward background values. Crustal‐scale k–zcurves may reflect a dynamic competition between permeability creation by processes such as fluid sourcing and rock failure, and permeability destruction by processes such as compaction, hydrothermal alteration, and retrograde metamorphism.
","language":"English","publisher":"Wiley","doi":"10.1111/j.1468-8123.2010.00278.x","usgsCitation":"Ingebritsen, S.E., and Manning, C.E., 2010, Permeability of the continental crust: Dynamic variations inferred from seismicity and metamorphism: Geofluids, v. 10, no. 1-2, p. 193-205, https://doi.org/10.1111/j.1468-8123.2010.00278.x.","productDescription":"13 p.","startPage":"193","endPage":"205","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":356041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"1-2","noUsgsAuthors":false,"publicationDate":"2010-05-07","publicationStatus":"PW","scienceBaseUri":"5b98b794e4b0702d0e844eaf","contributors":{"authors":[{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":740985,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manning, C. E.","contributorId":16987,"corporation":false,"usgs":true,"family":"Manning","given":"C.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":740986,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171009,"text":"70171009 - 2010 - Modeling the production, decomposition, and transport of dissolved organic carbon in boreal soils","interactions":[],"lastModifiedDate":"2018-10-11T18:26:18","indexId":"70171009","displayToPublicDate":"2010-05-01T07:45:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3419,"text":"Soil Science","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the production, decomposition, and transport of dissolved organic carbon in boreal soils","docAbstract":"The movement of dissolved organic carbon (DOC) through boreal ecosystems has drawn increased attention because of its potential impact on the feedback of OC stocks to global environmental change in this region. Few models of boreal DOC exist. Here we present a one-dimensional model with simultaneous production, decomposition, sorption/desorption, and transport of DOC to describe the behavior of DOC in the OC layers above the mineral soils. The field-observed concentration profiles of DOC in two moderately well-drained black spruce forest sites (one with permafrost and one without permafrost), coupled with hourly measured soil temperature and moisture, were used to inversely estimate the unknown parameters associated with the sorption/desorption kinetics using a global optimization strategy. The model, along with the estimated parameters, reasonably reproduces the concentration profiles of DOC and highlights some important potential controls over DOC production and cycling in boreal settings. The values of estimated parameters suggest that humic OC has a larger potential production capacity for DOC than fine OC, and most of the DOC produced from fine OC was associated with instantaneous sorption/desorption whereas most of the DOC produced from humic OC was associated with time-dependent sorption/desorption. The simulated DOC efflux at the bottom of soil OC layers was highly dependent on the component and structure of the OC layers. The DOC efflux was controlled by advection at the site with no humic OC and moist conditions and controlled by diffusion at the site with the presence of humic OC and dry conditions.
","language":"English","publisher":"Lippincott Williams & Wilkins, Inc.","doi":"10.1097/SS.0b013e3181e0559a","usgsCitation":"Fan, Z., Neff, J.C., and Wickland, K.P., 2010, Modeling the production, decomposition, and transport of dissolved organic carbon in boreal soils: Soil Science, v. 175, no. 5, p. 223-232, https://doi.org/10.1097/SS.0b013e3181e0559a.","productDescription":"10 p.","startPage":"223","endPage":"232","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-015251","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":321280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"574d65e2e4b07e28b6684868","contributors":{"authors":[{"text":"Fan, Zhaosheng","contributorId":169418,"corporation":false,"usgs":false,"family":"Fan","given":"Zhaosheng","affiliations":[{"id":25481,"text":"Univ. of Colorado, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":629522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neff, Jason C.","contributorId":169417,"corporation":false,"usgs":false,"family":"Neff","given":"Jason","email":"","middleInitial":"C.","affiliations":[{"id":25504,"text":"Univ. of Colorado, Coulder, CO","active":true,"usgs":false}],"preferred":false,"id":629521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wickland, Kimberly P. 0000-0002-6400-0590 kpwick@usgs.gov","orcid":"https://orcid.org/0000-0002-6400-0590","contributorId":1835,"corporation":false,"usgs":true,"family":"Wickland","given":"Kimberly","email":"kpwick@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":629520,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70044293,"text":"70044293 - 2010 - Fluvial processes and vegetation - Glimpses of the past, the present, and perhaps the future.","interactions":[],"lastModifiedDate":"2019-08-27T08:01:24","indexId":"70044293","displayToPublicDate":"2010-05-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Fluvial processes and vegetation - Glimpses of the past, the present, and perhaps the future.","docAbstract":"\"Most research before 1960 into interactions among fluvial processes, resulting landforms, and vegetation was descriptive. Since then, however, research has become more detailed and quantitative permitting numerical modeling and applications including agricultural-erosion abatement and rehabilitation of altered\nbottomlands. Although progress was largely observational, the empiricism increasingly yielded to objective recognition of how vegetation interacts with and influences geomorphic process. A review of advances relating fluvial processes and vegetation during the last 50 years centers on hydrologic reconstructions from\ntree rings, plant indicators of flow- and flood-frequency parameters, hydrologic controls on plant species, regulation of sediment movement by vegetation, vegetative controls on mass movement, and relations between plant cover and sediment movement. Extension of present studies of vegetation as a regulator of bottomland hydrologic and geomorphic processes may become markedly more sophisticated and widespread than at present. Research emphases that are\nlikely to continue include vegetative considerations for erosion modeling, response of riparian-zone forests to disturbance such as dams and water diversion, the effect of vegetation on channel and bottomland dynamics, and rehabilitation of stream corridors. Research topics that presently are receiving attention are the effect of woody vegetation on the roughness of stream corridors and, hence, processes of flood conveyance and flood-plain sedimentation, the development of a theoretical basis for rehabilitation projects as opposed to fully empirical approaches, the effect of invasive plant species on the dynamics of bottomland vegetation, the quantification of below-surface biomass and related soil-stability factors for use in erosion prediction models, and the effect of impoundments on downstream narrowing of channels and accompanying encroachment of vegetation. Bottomland vegetation partially controls and is controlled by fluvial-geomorphic processes. The purposes of this paper are to identify and review investigations that have related vegetation to bottomland features and\nprocesses, to distinguish the present status of these investigations, and to anticipate future research into how hydrologic and fluvial-geomorphic processes of bottomlands interact with vegetation.\"","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2009.11.018","usgsCitation":"Osterkamp, W.R., and Hupp, C.R., 2010, Fluvial processes and vegetation - Glimpses of the past, the present, and perhaps the future.: Geomorphology, v. 116, p. 274-285, https://doi.org/10.1016/j.geomorph.2009.11.018.","productDescription":"12 p.","startPage":"274","endPage":"285","numberOfPages":"12","ipdsId":"IP-013235","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":270789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270788,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geomorph.2009.11.018"}],"country":"United States","volume":"116","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"516689e3e4b0bba30b388bda","contributors":{"authors":[{"text":"Osterkamp, Waite R.","contributorId":8505,"corporation":false,"usgs":true,"family":"Osterkamp","given":"Waite","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":475247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":475246,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155508,"text":"70155508 - 2010 - A comparison of algal, macroinvertebrate, and fish assemblage indices for assessing low-level nutrient enrichment in wadeable Ozark streams","interactions":[],"lastModifiedDate":"2022-11-15T15:29:08.442893","indexId":"70155508","displayToPublicDate":"2010-05-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of algal, macroinvertebrate, and fish assemblage indices for assessing low-level nutrient enrichment in wadeable Ozark streams","docAbstract":"Biotic indices for algae, macroinvertebrates, and fish assemblages can be effective for monitoring stream enrichment, but little is known regarding the value of the three assemblages for detecting perturbance as a consequence of low-level nutrient enrichment. In the summer of 2006, we collected nutrient and biotic samples from 30 wadeable Ozark streams that spanned a nutrient-concentration gradient from reference to moderately enriched conditions. Seventy-three algal metrics, 62 macroinvertebrate metrics, and 60 fish metrics were evaluated for each of the three biotic indices. After a group of candidate metrics had been identified with multivariate analysis, correlation procedures and scatter plots were used to identify the four metrics having strongest relations to a nutrient index calculated from log transformed and normalized total nitrogen and total phosphorus concentrations. The four metrics selected for each of the three biotic indices were: algae—the relative abundance of most tolerant diatoms, the combined relative abundance of three species of Cymbella, mesosaprobic algae percent taxa richness, and the relative abundance of diatoms that are obligate nitrogen heterotrophs; macroinvertebrate—the relative abundance of intolerant organisms, Baetidae relative abundance, moderately tolerant taxa richness, and insect biomass; fish—herbivore and detritivore taxa richness, pool species relative abundance, fish catch per unit effort, and black bass (Micropterus spp.) relative abundance.
All three biotic indices were negatively correlated to nutrient concentrations but the algal index had a higher correlation (rho = −0.89) than did the macroinvertebrate and fish indices (rho = −0.63 and −0.58, respectively). Biotic index scores were lowest and nutrient concentrations were highest for streams with basins having the highest poultry and cattle production. Because of the availability of litter for fertilizer and associated increases in grass and hay production, cattle feeding capacity increases with poultry production. Studies are needed that address the synergistic effect of poultry and cattle production on Ozark streams in high production areas before ecological risks can be adequately addressed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2009.10.007","usgsCitation":"Justus, B., Petersen, J., Femmer, S.R., Davis, J., and Wallace, J.E., 2010, A comparison of algal, macroinvertebrate, and fish assemblage indices for assessing low-level nutrient enrichment in wadeable Ozark streams: Ecological Indicators, v. 10, no. 3, p. 627-638, https://doi.org/10.1016/j.ecolind.2009.10.007.","productDescription":"11 p.","startPage":"627","endPage":"638","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-006636","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":409354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Oklahoma","otherGeospatial":"Ozarks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.68715751122797,\n 35.36705469793361\n ],\n [\n -91.79401845584462,\n 35.97194095099876\n ],\n [\n -92.64201175828644,\n 36.183679007769214\n ],\n [\n -94.0898052014799,\n 36.13079795420306\n ],\n [\n -94.59998003384335,\n 36.055589865284134\n ],\n [\n -94.81370192307662,\n 35.574800228769234\n ],\n [\n -95.06878933925815,\n 34.83686115065606\n ],\n [\n -92.8143681205715,\n 34.62722402550767\n ],\n [\n -91.68715751122797,\n 35.361432508222435\n ],\n [\n -91.68715751122797,\n 35.36705469793361\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cdbfa9e4b08400b1fe13d1","contributors":{"authors":[{"text":"Justus, B. G. 0000-0002-3458-9656 bjustus@usgs.gov","orcid":"https://orcid.org/0000-0002-3458-9656","contributorId":2052,"corporation":false,"usgs":true,"family":"Justus","given":"B. G.","email":"bjustus@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":565610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petersen, James C. petersen@usgs.gov","contributorId":2437,"corporation":false,"usgs":true,"family":"Petersen","given":"James C.","email":"petersen@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":568020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Femmer, Suzanne R. sfemmer@usgs.gov","contributorId":2668,"corporation":false,"usgs":true,"family":"Femmer","given":"Suzanne","email":"sfemmer@usgs.gov","middleInitial":"R.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":false,"id":565612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Jerri V. jdavis@usgs.gov","contributorId":2667,"corporation":false,"usgs":true,"family":"Davis","given":"Jerri V.","email":"jdavis@usgs.gov","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":false,"id":565611,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallace, J. E.","contributorId":64771,"corporation":false,"usgs":true,"family":"Wallace","given":"J.","email":"","middleInitial":"E.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":568021,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194389,"text":"70194389 - 2010 - Revisions of rump fat and body scoring indices for deer, elk, and moose","interactions":[],"lastModifiedDate":"2017-11-27T14:48:12","indexId":"70194389","displayToPublicDate":"2010-05-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Revisions of rump fat and body scoring indices for deer, elk, and moose","docAbstract":"Because they do not require sacrificing animals, body condition scores (BCS), thickness of rump fat (MAXFAT), and other similar predictors of body fat have advanced estimating nutritional condition of ungulates and their use has proliferated in North America in the last decade. However, initial testing of these predictors was too limited to assess their reliability among diverse habitats, ecotypes, subspecies, and populations across the continent. With data collected from mule deer (Odocoileus hemionus), elk (Cervus elaphus), and moose (Alces alces) during initial model development and data collected subsequently from free-ranging mule deer and elk herds across much of the western United States, we evaluated reliability across a broader range of conditions than were initially available. First, to more rigorously test reliability of the MAXFAT index, we evaluated its robustness across the 3 species, using an allometric scaling function to adjust for differences in animal size. We then evaluated MAXFAT, rump body condition score (rBCS), rLIVINDEX (an arithmetic combination of MAXFAT and rBCS), and our new allometrically scaled rump-fat thickness index using data from 815 free-ranging female Roosevelt and Rocky Mountain elk (C. e. roosevelti and C. e. nelsoni) from 19 populations encompassing 4 geographic regions and 250 free-ranging female mule deer from 7 populations and 2 regions. We tested for effects of subspecies, geographic region, and captive versus free-ranging existence. Rump-fat thickness, when scaled allometrically with body mass, was related to ingesta-free body fat over a 38–522-kg range of body mass (r2 = 0.87; P < 0.001), indicating the technique is remarkably robust among at least the 3 cervid species of our analysis. However, we found an underscoring bias with the rBCS for elk that had >12% body fat. This bias translated into a difference between subspecies, because Rocky Mountain elk tended to be fatter than Roosevelt elk in our sample. Effects of observer error with the rBCS also existed for mule deer with moderate to high levels of body fat, and deer body size significantly affected accuracy of the MAXFAT predictor. Our analyses confirm robustness of the rump-fat index for these 3 species but highlight the potential for bias due to differences in body size and to observer error with BCS scoring. We present alternative LIVINDEX equations where potential bias from rBCS and bias due to body size are eliminated or reduced. These modifications improve the accuracy of estimating body fat for projects intended to monitor nutritional status of herds or to evaluate nutrition's influence on population demographics.
","language":"English","publisher":"Wiley","doi":"10.2193/2009-031","usgsCitation":"Cook, R.C., Cook, J.G., Stephenson, T.R., Myers, W.L., Mccorquodale, S.M., Vales, D.J., Irwin, L.L., Hall, P.B., Spencer, R.D., Murphie, S.L., Schoenecker, K.A., and Miller, P.J., 2010, Revisions of rump fat and body scoring indices for deer, elk, and moose: Journal of Wildlife Diseases, v. 74, no. 4, p. 880-896, https://doi.org/10.2193/2009-031.","productDescription":"17 p.","startPage":"880","endPage":"896","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":349383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.20019531249999,\n 36.527294814546245\n ],\n [\n -103.0078125,\n 36.527294814546245\n ],\n [\n -103.0078125,\n 49.06666839558117\n ],\n [\n -125.20019531249999,\n 49.06666839558117\n ],\n [\n -125.20019531249999,\n 36.527294814546245\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"74","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-12-13","publicationStatus":"PW","scienceBaseUri":"5a610abbe4b06e28e9c256cd","contributors":{"authors":[{"text":"Cook, Rachel C.","contributorId":19064,"corporation":false,"usgs":true,"family":"Cook","given":"Rachel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":723653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, John G.","contributorId":12903,"corporation":false,"usgs":true,"family":"Cook","given":"John","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":723654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stephenson, Thomas R.","contributorId":64114,"corporation":false,"usgs":true,"family":"Stephenson","given":"Thomas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":723655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Myers, Woodrow L.","contributorId":200876,"corporation":false,"usgs":false,"family":"Myers","given":"Woodrow","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mccorquodale, Scott M.","contributorId":62921,"corporation":false,"usgs":true,"family":"Mccorquodale","given":"Scott","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723657,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vales, David J.","contributorId":74662,"corporation":false,"usgs":true,"family":"Vales","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":723658,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Irwin, Larry L.","contributorId":105649,"corporation":false,"usgs":true,"family":"Irwin","given":"Larry","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723659,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hall, P. Briggs","contributorId":200877,"corporation":false,"usgs":false,"family":"Hall","given":"P.","email":"","middleInitial":"Briggs","affiliations":[],"preferred":false,"id":723660,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spencer, Rocky D.","contributorId":200878,"corporation":false,"usgs":false,"family":"Spencer","given":"Rocky","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":723661,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Murphie, Shannon L.","contributorId":200879,"corporation":false,"usgs":false,"family":"Murphie","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723662,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X schoeneckerk@usgs.gov","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":2001,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn","email":"schoeneckerk@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":723663,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Miller, Patrick J.","contributorId":200880,"corporation":false,"usgs":false,"family":"Miller","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":723664,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":98349,"text":"sir20105003 - 2010 - Flood of April and May 2008 in Northern Maine","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20105003","displayToPublicDate":"2010-04-28T00:00:00","publicationYear":"2010","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":"2010-5003","title":"Flood of April and May 2008 in Northern Maine","docAbstract":"Severe flooding occurred in Aroostook and Penobscot Counties in northern Maine between April 28 and May 1, 2008, and was most extreme in the town of Fort Kent. Peak streamflows in northern Aroostook County were the result of a persistent heavy snowpack that caused high streamflows when it quickly melted during the third week of April 2008. Snowmelt was followed by from two to four inches of rainfall over a 2-day period in northern Maine. Peak water-surface elevations resulting from the flood were obtained from 13 continuous-record streamgages and 63 surveyed high-water marks in Aroostook and Penobscot Counties. Peak streamflows were obtained from 20 sites on 15 streams through stage/discharge rating curves or hydraulic flow models. Peak water-surface elevations and streamflows were the highest ever recorded at seven continuous-record streamgages, which had between 25 and 84 years of record in northern Aroostook County. The annual exceedance probability (the percent chance of exceeding the streamflow recorded during the April/May 2008 flood during any given year) at six streamgages in northern Maine was equal to or less than 1 percent. \r\n\r\nData from flood-insurance studies published by the Federal Emergency Management Agency were available for five of the locations analyzed for the April/May 2008 flood and were compared to streamflows and observed peak water-surface elevations from the 2008 flood. Water-surface elevations that would be expected given the observed flow as applied to the effective flood insurance studies ranged from between 1 and 4 feet from the water-surface elevations observed during the 2008 flood. Differences were likely the result of up to 30 years of additional data for the calculation of recurrence intervals and the fact that hydraulic models used for the models had not previously been calibrated to a flood of this magnitude. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105003","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Lombard, P., 2010, Flood of April and May 2008 in Northern Maine: U.S. Geological Survey Scientific Investigations Report 2010-5003, iv, 17 p. , https://doi.org/10.3133/sir20105003.","productDescription":"iv, 17 p. ","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2008-04-28","temporalEnd":"2008-05-01","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":125900,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5003.jpg"},{"id":13598,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5003/","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -70.5,45 ], [ -70.5,48 ], [ -67,48 ], [ -67,45 ], [ -70.5,45 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4814e4b07f02db4dac15","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":23899,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela J.","affiliations":[],"preferred":false,"id":305055,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70202252,"text":"70202252 - 2010 - Seasonal H2O and CO2 ice cycles at the Mars Phoenix landing site: 1. Prelanding CRISM and HiRISE observations","interactions":[],"lastModifiedDate":"2019-02-18T12:54:17","indexId":"70202252","displayToPublicDate":"2010-04-27T12:52:31","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal H2O and CO2 ice cycles at the Mars Phoenix landing site: 1. Prelanding CRISM and HiRISE observations","docAbstract":"The condensation, evolution, and sublimation of seasonal water and carbon dioxide ices were characterized at the Mars Phoenix landing site from Martian northern midsummer to midspring (Ls ∼ 142° – Ls ∼ 60°) for the year prior to the Phoenix landing on 25 May 2008. Ice relative abundances and grain sizes were estimated using data from the Compact Reconnaissance Imaging Spectrometer for Mars and High Resolution Imaging Science Experiment aboard Mars Reconnaissance Orbiter and a nonlinear mixing model. Water ice first appeared at the Phoenix landing site during the afternoon in late summer (Ls ∼ 167°) as an optically thin layer on top of soil. CO2 ice appeared after the fall equinox. By late winter (Ls∼ 344°), the site was covered by relatively pure CO2 ice (∼30 cm thick), with a small amount of ∼100 μm diameter water ice and soil. As spring progressed, CO2 ice grain sizes gradually decreased, a change interpreted to result from granulation during sublimation losses. The combined effect of CO2 sublimation and decreasing H2O ice grain sizes allowed H2O ice to dominate spectra during the spring and significantly brightened the surface. CO2 ice disappeared by early spring (Ls ∼ 34°) and H2O ice by midspring (Ls ∼ 59°). Spring defrosting was not uniform and occurred more rapidly over the centers of polygons and geomorphic units with relatively higher thermal inertia values.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2009JE003340","usgsCitation":"Cull, S., Arvidson, R.E., Mellon, M.T., Wiseman, S.M., Clark, R.N., Titus, T.N., Morris, R., and McGuire, P.E., 2010, Seasonal H2O and CO2 ice cycles at the Mars Phoenix landing site: 1. Prelanding CRISM and HiRISE observations: Journal of Geophysical Research E: Planets, v. 115, no. E4, 14 p., https://doi.org/10.1029/2009JE003340.","productDescription":"14 p.","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":361319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"115","issue":"E4","noUsgsAuthors":false,"publicationDate":"2010-04-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Cull, Selby","contributorId":19100,"corporation":false,"usgs":true,"family":"Cull","given":"Selby","affiliations":[],"preferred":false,"id":757506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arvidson, Raymond E.","contributorId":106626,"corporation":false,"usgs":false,"family":"Arvidson","given":"Raymond","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":757507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mellon, Michael T.","contributorId":8603,"corporation":false,"usgs":false,"family":"Mellon","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":7037,"text":"Southwest Research Institute, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":757508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiseman, Sandra M.","contributorId":212719,"corporation":false,"usgs":false,"family":"Wiseman","given":"Sandra","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":757509,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Roger N. 0000-0002-7021-1220 rclark@usgs.gov","orcid":"https://orcid.org/0000-0002-7021-1220","contributorId":515,"corporation":false,"usgs":true,"family":"Clark","given":"Roger","email":"rclark@usgs.gov","middleInitial":"N.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":757510,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":757511,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morris, Richard V.","contributorId":167513,"corporation":false,"usgs":false,"family":"Morris","given":"Richard V.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":757512,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McGuire, Patrick E.","contributorId":71008,"corporation":false,"usgs":false,"family":"McGuire","given":"Patrick","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":757513,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70230290,"text":"70230290 - 2010 - Mg isotope constraints on soil pore-fluid chemistry: Evidence from Santa Cruz, California","interactions":[],"lastModifiedDate":"2022-04-06T16:17:22.640131","indexId":"70230290","displayToPublicDate":"2010-04-27T10:02:58","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Mg isotope constraints on soil pore-fluid chemistry: Evidence from Santa Cruz, California","docAbstract":"Mg isotope ratios (26Mg/24Mg) are reported in soil pore-fluids, rain and seawater, grass and smectite from a 90 kyr old soil, developed on an uplifted marine terrace from Santa Cruz, California. Rain water has an invariant 26Mg/24Mg ratio (expressed as δ26Mg>δ26Mg) at −0.79 ± 0.05‰, identical to seawater δ26Mg>δ26Mg. Detrital smectite (from the base of the soil profile, and therefore unweathered) has a δ26Mg\">δ26Mg value of 0.11‰, potentially enriched in 26Mg by up to 0.3‰ compared to the bulk silicate Earth Mg isotope composition (although within the range of all terrestrial silicates). The soil pore-waters show a continuous profile with depth for δ26Mg>δ26Mg, ranging from −0.99‰ near the surface to −0.43‰ at the base of the profile. Shallow pore-waters (<1 m) have δ26Mg>δ26Mg values that are similar to, or slightly lower than the rain waters. This implies that the degree of biological cycling of Mg in the pore-waters is relatively small and is quantified as <32%, calculated using the average Mg isotope enrichment factor between grass and rain (δ26Mggrass-δ26Mgrain>δ26Mggrass-δ26Mgrain) of 0.21‰. The deep pore-waters (1–15 m deep) have δ26Mg>δ26Mg values that are intermediate between the smectite and rain, ranging from −0.76‰ to −0.43‰, and show a similar trend with depth compared to Sr isotope ratios. The similarity between Sr and Mg isotope ratios confirms that the Mg in the pore-waters can be explained by a mixture between rain and smectite derived Mg, despite the fact that Mg and Sr concentrations may be buffered by the exchangeable reservoir. However, whilst Sr isotope ratios in the pore-waters span almost the complete range between mineral and rain inputs, Mg isotopes compositions are much closer to the rain inputs. If Mg and Sr isotope ratios are controlled uniquely by a mixture, the data can be used to estimate the mineral weathering inputs to the pore-waters, by correcting for the rain inputs. This isotopic correction is compared to the commonly used chloride correction for precipitation inputs. A consistent interpretation is only possible if Mg isotope ratios are fractionated either by the precipitation of a secondary Mg bearing phase, not detected by conventional methods, or selective leaching of 24Mg from smectite. There is therefore dual control on the Mg isotopic composition of the pore-waters, mixing of two inputs with distinct isotopic compositions, modified by fractionation. The data provide (1) further evidence for Mg isotope fractionation at the surface of the Earth and (2) the first field evidence of Mg isotope fractionation during uptake by natural plants. The coherent behaviour of Mg isotope ratios in soil environments is encouraging for the development of Mg isotope ratios as a quantitative tracer of both weathering inputs of Mg to waters, and the physicochemical processes that cycle Mg, a major cation linked to the carbon cycle, during continental weathering.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2010.04.021","usgsCitation":"Tipper, E.T., Gaillardet, J., Louvat, P., Capmas, F., and White, A.F., 2010, Mg isotope constraints on soil pore-fluid chemistry: Evidence from Santa Cruz, California: Geochimica et Cosmochimica Acta, v. 74, no. 14, p. 3883-3896, https://doi.org/10.1016/j.gca.2010.04.021.","productDescription":"14 p.","startPage":"3883","endPage":"3896","costCenters":[],"links":[{"id":398221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Cruz","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.10891723632812,\n 36.94495296068268\n ],\n [\n -121.93038940429688,\n 36.94495296068268\n ],\n [\n -121.93038940429688,\n 37.04092825594592\n ],\n [\n -122.10891723632812,\n 37.04092825594592\n ],\n [\n -122.10891723632812,\n 36.94495296068268\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"74","issue":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tipper, Edward T.","contributorId":289842,"corporation":false,"usgs":false,"family":"Tipper","given":"Edward","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":839881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaillardet, Jerome","contributorId":184199,"corporation":false,"usgs":false,"family":"Gaillardet","given":"Jerome","email":"","affiliations":[],"preferred":false,"id":839882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Louvat, Pascale","contributorId":289843,"corporation":false,"usgs":false,"family":"Louvat","given":"Pascale","email":"","affiliations":[],"preferred":false,"id":839883,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Capmas, Francoise","contributorId":289844,"corporation":false,"usgs":false,"family":"Capmas","given":"Francoise","email":"","affiliations":[],"preferred":false,"id":839884,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Arthur F. afwhite@usgs.gov","contributorId":3718,"corporation":false,"usgs":true,"family":"White","given":"Arthur","email":"afwhite@usgs.gov","middleInitial":"F.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":839885,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":98344,"text":"fs20103019 - 2010 - Modeling Climate Change and Sturgeon Populations in the Missouri River","interactions":[],"lastModifiedDate":"2012-02-02T00:14:34","indexId":"fs20103019","displayToPublicDate":"2010-04-27T00:00:00","publicationYear":"2010","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":"2010-3019","title":"Modeling Climate Change and Sturgeon Populations in the Missouri River","docAbstract":"The U.S. Geological Survey (USGS) Columbia Environmental Research Center (CERC), in collaboration with researchers from the University of Missouri and Iowa State University, is conducting research to address effects of climate change on sturgeon populations (Scaphirhynchus spp.) in the Missouri River. \r\n\r\nThe CERC is conducting laboratory, field, and modeling research to identify causative factors for the responses of fish populations to natural and human-induced environmental changes and using this information to understand sensitivity of sturgeon populations to potential climate change in the Missouri River drainage basin. Sturgeon response information is being used to parameterize models predicting future population trends. These models will provide a set of tools for natural resource managers to assess management strategies in the context of global climate change.\r\n\r\nThis research complements and builds on the ongoing Comprehensive Sturgeon Research Program (CSRP) at the CERC. The CSRP is designed to provide information critical to restoration of the Missouri River ecosystem and the endangered pallid sturgeon (S. albus). Current research is being funded by USGS through the National Climate Change Wildlife Science Center (NCCWSC) and the Science Support Partnership (SSP) Program that is held by the USGS and the U.S. Fish and Wildlife Service. The national mission of the NCCWSC is to improve the capacity of fish and wildlife agencies to respond to climate change and to address high-priority climate change effects on fish and wildlife. Within the national context, the NCCWSC research on the Missouri River focuses on temporal and spatial downscaling and associated uncertainty in modeling climate change effects on sturgeon species in the Missouri River. The SSP research focuses on improving survival and population estimates for pallid sturgeon population models.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20103019","usgsCitation":"Wildhaber, M.L., 2010, Modeling Climate Change and Sturgeon Populations in the Missouri River: U.S. Geological Survey Fact Sheet 2010-3019, 2 p., https://doi.org/10.3133/fs20103019.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":265,"text":"Environmental Research Center","active":false,"usgs":true}],"links":[{"id":125544,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2010_3019.jpg"},{"id":13593,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2010/3019/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b04e4b07f02db699542","contributors":{"authors":[{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":305044,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98336,"text":"ofr20101081 - 2010 - Nitrogen Loads in Groundwater Entering Back Bays and Ocean from Fire Island National Seashore, Long Island, New York","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"ofr20101081","displayToPublicDate":"2010-04-22T00:00:00","publicationYear":"2010","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":"2010-1081","title":"Nitrogen Loads in Groundwater Entering Back Bays and Ocean from Fire Island National Seashore, Long Island, New York","docAbstract":"Fire Island is a barrier island that lies south of central Long Island, N.Y. It is about 60 km (37 mi) long and 0.5 km (1/4 mi) wide and is bounded by the Great South Bay, Narrow Bay, and Moriches Bay estuaries to the north; by the Atlantic Ocean to the south; by Fire Island Inlet to the west; and by Moriches Inlet to the east (fig. 1). Fire Island National Seashore (FIIS) encompasses a 42-km (26-mi) length of Fire Island that is bordered by Robert Moses State Park to the west and Smith Point County Park to the east (fig. 2). Interspersed throughout FIIS are 17 residential beach communities that together contain about 4,100 homes.\r\n\r\nThe barrier island's summer population increases 50-fold through the arrival of summer residents and vacationers. The National Park Service (NPS) has established several facilities on the island to accommodate visitors to FIIS. About 2.2 million people visit at least one of the 17 communities and (or) Smith Point County Park, the waterways surrounding Fire Island, or a FIIS facility annually (National Park Service, 2007). Combined visitation on a peak-season weekend day can be as high as 100,000 (National Park Service, 2002).\r\n\r\nMost homes and businesses in the 17 barrier-island communities discharge untreated wastewater directly to the shallow (water-table) aquifer through private septic systems and cesspools; the NPS facilities discharge wastewater to this aquifer through leach fields and cesspools. (The community of Ocean Beach (fig. 2) has a treatment plant that discharges to tidewater.) Contaminants in sewage entering the shallow groundwater move through the flow system and are ultimately discharged to adjacent marine surface waters, where they can pose a threat to coastal habitats. A contaminant of major concern is nitrogen, which is derived from fertilizers and human waste. The continuous inflow of nitrogen to surface-water bodies can lead to increased production of phytoplankton and macroalgae, which in turn can cause oxygen depletion, decreases in size of estuarine fish and shellfish communities, and loss of submerged seagrass habitat through light limitation (Valiela and others, 1992).\r\n\r\nThe FIIS boundary extends roughly 1.2 km (0.8 mi) into the back-barrier estuaries of Great South Bay, Narrow Bay, and Moriches Bay (fig. 1). Within this estuarine zone are extensive areas of seagrass, shellfish, and finfish habitat, as well as intense recreational activity (Bokuniewicz and others, 1993). Management strategies for protection of these habitats require data on (1) concentrations and movement of nutrients and other human-derived contaminants that enter the groundwater system from on-site septic systems, and (2) aquifer characteristics and groundwater flow patterns. These data can then be used in three-dimensional flow models of the shallow aquifer system to predict the rates of groundwater discharge to the marine surface waters that bound Fire Island and the concentrations of nitrogen entering these water bodies from the aquifer's discharge zones.\r\n\r\nIn 2004, the U.S. Geological Survey (USGS), in cooperation with the NPS, began a 3-year investigation to (1) measure groundwater levels within four local study areas at FIIS, (2) collect groundwater samples from these areas for nutrient (nitrogen) analysis, (3) develop a three-dimensional model of the hydrologic system and adjacent saltwater bodies for groundwater-flow delineation and particle tracking, and (4) apply the results of groundwater-discharge simulations to calculate the annual nitrogen loads in these discharges, particularly those entering Great South Bay, which together with the other back bays receives an estimated 80 percent of the total groundwater discharge from Fire Island.\r\n\r\nThe four areas on which the investigation focused were the communities of Kismet and Robbins Rest, the NPS Visitor Center at Watch Hill, and the undeveloped Otis Pike Fire Island High Dune Wilderness (shown in panels A, B, C, and D in fig. 2); these were","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101081","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Schubert, C., deVries, M.P., and Finch, A.J., 2010, Nitrogen Loads in Groundwater Entering Back Bays and Ocean from Fire Island National Seashore, Long Island, New York: U.S. Geological Survey Open-File Report 2010-1081, 16 p., https://doi.org/10.3133/ofr20101081.","productDescription":"16 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":125893,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1081.jpg"},{"id":13584,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1081/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.33333333333333,40.53333333333333 ], [ -73.33333333333333,40.85 ], [ -72.76666666666667,40.85 ], [ -72.76666666666667,40.53333333333333 ], [ -73.33333333333333,40.53333333333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a51e4b07f02db629c59","contributors":{"authors":[{"text":"Schubert, Christopher 0000-0003-0705-3933 schubert@usgs.gov","orcid":"https://orcid.org/0000-0003-0705-3933","contributorId":1243,"corporation":false,"usgs":true,"family":"Schubert","given":"Christopher","email":"schubert@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":305026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"deVries, M. Peter pdevries@usgs.gov","contributorId":1555,"corporation":false,"usgs":true,"family":"deVries","given":"M.","email":"pdevries@usgs.gov","middleInitial":"Peter","affiliations":[],"preferred":true,"id":305027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finch, Anne J.","contributorId":102494,"corporation":false,"usgs":true,"family":"Finch","given":"Anne","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":305028,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70003440,"text":"70003440 - 2010 - Influence of tidal range on the stability of coastal marshland","interactions":[],"lastModifiedDate":"2021-02-16T16:51:31.79513","indexId":"70003440","displayToPublicDate":"2010-04-21T11:50:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Influence of tidal range on the stability of coastal marshland","docAbstract":"Early comparisons between rates of vertical accretion and sea level rise across marshes in different tidal ranges inspired a paradigm that marshes in high tidal range environments are more resilient to sea level rise than marshes in low tidal range environments. We use field‐based observations to propose a relationship between vegetation growth and tidal range and to adapt two numerical models of marsh evolution to explicitly consider the effect of tidal range on the response of the marsh platform channel network system to accelerating rates of sea level rise. We find that the stability of both the channel network and vegetated platform increases with increasing tidal range. Our results support earlier hypotheses that suggest enhanced stability can be directly attributable to a vegetation growth range that expands with tidal range. Accretion rates equilibrate to the rate of sea level rise in all experiments regardless of tidal range, suggesting that comparisons between accretion rate and tidal range will not likely produce a significant relationship. Therefore, our model results offer an explanation to widely inconsistent field‐based attempts to quantify this relationship while still supporting the long‐held paradigm that high tidal range marshes are indeed more stable.
","language":"English","publisher":"American Geophysical Union","usgsCitation":"Kirwan, M., and Guntenspergen, G.R., 2010, Influence of tidal range on the stability of coastal marshland: Journal of Geophysical Research, v. 115, no. F2, 11 p.","productDescription":"11 p.","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":383287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"F2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3b90e4b0c8380cd6264d","contributors":{"authors":[{"text":"Kirwan, Matthew L. 0000-0002-0658-3038","orcid":"https://orcid.org/0000-0002-0658-3038","contributorId":84060,"corporation":false,"usgs":true,"family":"Kirwan","given":"Matthew L.","affiliations":[],"preferred":false,"id":347299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":347298,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98334,"text":"tm2A10 - 2010 - A Natural History Summary and Survey Protocol for the Southwestern Willow Flycatcher","interactions":[],"lastModifiedDate":"2012-02-02T00:15:02","indexId":"tm2A10","displayToPublicDate":"2010-04-21T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2-A10","title":"A Natural History Summary and Survey Protocol for the Southwestern Willow Flycatcher","docAbstract":"The Southwestern Willow Flycatcher (Empidonax traillii extimus) has been the subject of substantial research, monitoring, and management activity since it was listed as an endangered species in 1995. When proposed for listing in 1993, relatively little was known about the flycatcher's natural history, and there were only 30 known breeding sites supporting an estimated 111 territories rangewide (Sogge and others, 2003a). Since that time, thousands of presence/absences surveys have been conducted throughout the historical range of the flycatcher, and many studies of its natural history and ecology have been completed. As a result, the ecology of the flycatcher is much better understood than it was just over a decade ago. In addition, we have learned that the current status of the flycatcher is better than originally thought: as of 2007, the population was estimated at approximately 1,300 territories distributed among approximately 280 breeding sites (Durst and others, 2008a). \r\n\r\nConcern about the Southwestern Willow Flycatcher on a rangewide scale was brought to focus by Unitt (1987), who described declines in flycatcher abundance and distribution throughout the Southwest. E. t. extimus populations declined during the 20th century, primarily because of habitat loss and modification from activities, such as dam construction and operation, groundwater pumping, water diversions, and flood control. In 1991, the U.S. Fish and Wildlife Service (USFWS) designated the Southwestern Willow Flycatcher as a candidate category 1 species (U.S. Fish and Wildlife Service, 1991). In July 1993, the USFWS proposed to list E. t. extimus as an endangered species and to designate critical habitat under the Act (U.S. Fish and Wildlife Service, 1993). A final rule listing E. t. extimus as endangered was published in February 1995 (U.S. Fish and Wildlife Service, 1995); critical habitat was designated in 1997 (U.S. Fish and Wildlife Service, 1997). The USFWS Service released a Recovery Plan for the Southwestern Willow Flycatcher in 2002 (U.S. Fish and Wildlife Service, 2002), and re-designated critical habitat in 2005 (U.S. Fish and Wildlife Service, 2005). \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/tm2A10","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the U.S. Fish and Wildlife Service","usgsCitation":"Sogge, M.K., Water Resources Division, U.S. Geological Survey, Ahlers, D., Bureau of Reclamation, Sferra, S.J., and U.S. Fish and Wildlife Service, 2010, A Natural History Summary and Survey Protocol for the Southwestern Willow Flycatcher: U.S. Geological Survey Techniques and Methods 2-A10, Report: iv, 38 p.; Appendices (doc, PDF, xls) , https://doi.org/10.3133/tm2A10.","productDescription":"Report: iv, 38 p.; Appendices (doc, PDF, xls) ","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":118631,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_2_a10.jpg"},{"id":13583,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/tm2a10/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd495de4b0b290850ef1a7","contributors":{"authors":[{"text":"Sogge, Mark K. 0000-0002-8337-5689 mark_sogge@usgs.gov","orcid":"https://orcid.org/0000-0002-8337-5689","contributorId":3710,"corporation":false,"usgs":true,"family":"Sogge","given":"Mark","email":"mark_sogge@usgs.gov","middleInitial":"K.","affiliations":[{"id":5079,"text":"Pacific Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":305020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":535025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahlers, Darrell","contributorId":68428,"corporation":false,"usgs":true,"family":"Ahlers","given":"Darrell","affiliations":[],"preferred":false,"id":305024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bureau of Reclamation","contributorId":127878,"corporation":true,"usgs":false,"organization":"Bureau of Reclamation","id":535024,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sferra, Susan J.","contributorId":57964,"corporation":false,"usgs":true,"family":"Sferra","given":"Susan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":305022,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"U.S. Fish and Wildlife Service","contributorId":128143,"corporation":true,"usgs":false,"organization":"U.S. Fish and Wildlife Service","id":535026,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}