Recent work has demonstrated that the topological properties of real river networks deviate significantly from predictions of Shreve's random model. At the same time the property of mean self-similarity postulated by Tokunaga's model is well supported by data. Recently, a new class of network model called random self-similar networks (RSN) that combines self-similarity and randomness has been introduced to replicate important topological features observed in real river networks. We investigate if the hypothesis of statistical self-similarity in the RSN model is supported by data on a set of 30 basins located across the continental United States that encompass a wide range of hydroclimatic variability. We demonstrate that the generators of the RSN model obey a geometric distribution, and self-similarity holds in a statistical sense in 26 of these 30 basins. The parameters describing the distribution of interior and exterior generators are tested to be statistically different and the difference is shown to produce the well-known Hack's law. The inter-basin variability of RSN parameters is found to be statistically significant. We also test generator dependence on two climatic indices, mean annual precipitation and radiative index of dryness. Some indication of climatic influence on the generators is detected, but this influence is not statistically significant with the sample size available. Finally, two key applications of the RSN model to hydrology and geomorphology are briefly discussed.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2009JF001609","usgsCitation":"Troutman, B.M., Mantilla, R., and Gupta, V.K., 2010, Testing statistical self-similarity in the topology of river networks: Journal of Geophysical Research F: Earth Surface, v. 115, no. F3, F03038: 12 p., https://doi.org/10.1029/2009JF001609.","productDescription":"F03038: 12 p.","ipdsId":"IP-018290","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":475686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2009jf001609","text":"Publisher Index Page"},{"id":344563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"F3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2010-09-25","publicationStatus":"PW","scienceBaseUri":"5984364ce4b0e2f5d46653ed","contributors":{"authors":[{"text":"Troutman, Brent M.","contributorId":195329,"corporation":false,"usgs":false,"family":"Troutman","given":"Brent","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":706768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mantilla, Ricardo","contributorId":195330,"corporation":false,"usgs":false,"family":"Mantilla","given":"Ricardo","email":"","affiliations":[],"preferred":false,"id":706769,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gupta, Vijay K.","contributorId":195331,"corporation":false,"usgs":false,"family":"Gupta","given":"Vijay","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":706770,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70154946,"text":"70154946 - 2010 - Assessment and management of ecological integrity: Chapter 12","interactions":[],"lastModifiedDate":"2017-05-31T16:30:21","indexId":"70154946","displayToPublicDate":"2010-07-14T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Assessment and management of ecological integrity: Chapter 12","docAbstract":"Assessing and understanding the impacts of human activities on aquatic ecosystems has long been a focus of ecologists, water resources managers, and fisheries scientists. While traditional fisheries management focused on single-species approaches to enhance fish stocks, there is a growing emphasis on management approaches at community and ecosystem levels. Of course, as fisheries managers shift their attention from narrow (e.g., populations) to broad organizational scales (e.g., communities or ecosystems), ecological processes and management objectives become more complex. At the community level, fisheries managers may strive for a fish assemblage that is complex, persistent, and resilient to disturbance. Aquatic ecosystem level objectives may focus on management for habitat quality and ecological processes, such as nutrient dynamics, productivity, or trophic interactions, but a long-term goal of ecosystem management may be to maintain ecological integrity. However, human users and social, economic, and political demands of fisheries management often result in a reduction of ecological integrity in managed systems, and this conflict presents a principal challenge for the modern fisheries manager.
The concepts of biotic integrity and ecological integrity are being applied in fisheries science, natural resource management, and environmental legislation, but explicit definitions of these terms are elusive. Biotic integrity of an ecosystem may be defined as the capability of supporting and maintaining an integrated, adaptive community of organisms having a species composition, diversity, and functional organization comparable to that of a natural habitat of the region (Karr and Dudley 1981). Following that, ecological integrity is the summation of chemical, physical, and biological integrity. Thus, the concept of ecological integrity extends beyond fish and represents a holistic approach for ecosystem management that is especially applicable to aquatic systems. The more general term, ecological condition, refers to the state of the physical, chemical, and biological characteristics of the environment and the processes and interactions that connect them. While the concept of ecological integrity may appear unambiguous, its assessment and practice are much less clear.
Ecological integrity made its debut in the USA with the Clean Water Act (CWA) of 1972 (Federal Water Pollution Control Act, as amended through Public Law 107–303, November 27, 2002), which states only one objective, “to restore and maintain the chemical, physical, and biological integrity of the Nation’s waters.” This legislation compelled resource managers to focus on chemical pollution from point effluent sources, such as industrial and municipal outflows, as well as give attention to diffuse, chronic, and watershed effects on ecological integrity. Further, the CWA allowed pursuit of restoration programs in degraded water bodies and catalyzed the science and practice of restoration ecology.
The term ecosystem health is often raised in discussions of ecological integrity. Perhaps it is natural to anthropomorphize our concern for personal health to ecosystems, so it becomes a useful metaphor for understanding the concept of ecological integrity. However, whether or not an ecosystem should be considered an entity, such as a superorganism, is a debate without end that began with early ecologists and continues today (Clements 1916; Suter 1993; Simon 1999a). Regardless, the ecosystem is indeed a natural unit with a level of organization and properties beyond the collection of those species that occupy it and presents the most appropriate spatial and organizational scale in which to assess and study ecological integrity. Streams and rivers serve as integrators of chemical, physical, and biological conditions across the landscape, and while the theory and practice associated with ecological integrity of aquatic systems is easily applied to flowing waters and is emphasized in this chapter, they are broadly applicable among all aquatic systems.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Inland fisheries management in North America","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","usgsCitation":"Kwak, T.J., and Freeman, M., 2010, Assessment and management of ecological integrity: Chapter 12, chap. of Inland fisheries management in North America, p. 353-394.","productDescription":"42 p.","startPage":"353","endPage":"394","ipdsId":"IP-015959","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":340930,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591183bbe4b0e541a03c1a94","contributors":{"authors":[{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694469,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045080,"text":"70045080 - 2010 - Temporal variations in Global Seismic Stations ambient noise power levels","interactions":[],"lastModifiedDate":"2020-09-14T15:19:15.098046","indexId":"70045080","displayToPublicDate":"2010-07-14T00:00:00","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":"Temporal variations in Global Seismic Stations ambient noise power levels","docAbstract":"Recent concerns about time-dependent response changes in broadband seismometers have motivated the need for methods to monitor sensor health at Global Seismographic Network (GSN) stations. We present two new methods for monitoring temporal changes in data quality and instrument response transfer functions that are independent of Earth seismic velocity and attenuation models by comparing power levels against different baseline values.
Our methods can resolve changes in both horizontal and vertical components in a broad range of periods (∼0.05 to 1,000 seconds) in near real time. In this report, we compare our methods with existing techniques and demonstrate how to resolve instrument response changes in long-period data (>100 seconds) as well as in the microseism bands (5 to 20 seconds).
High quality broadband data recorded by the GSN are fundamental to characterizing a wide range of Earth science issues including: the size and rupture of large earthquakes (e.g., Tsai et al. 2005); imaging the interior of the Earth (e.g., Van der Hilst et al. 1997); tracking global climate variation (Aster et al. 2008); and monitoring calving glaciers (Ekström et al.2003, 2006a).
Recent studies based on theoretical Earth models (Ekström et al. 2006b; Davis and Berger 2007) suggest that broadband seismometer gain levels can vary with time. This has also been confirmed, for the STS-1 sensor, experimentally (Yuki and Ishihara 2002). It therefore has become necessary to systematically check for temporal changes in amplitude at GSN stations. Many of these changes are frequency-dependent in nature and not a priori predictable (Ekström et al. 2006b). Robust methods that can be applied to a large number of stations in a broad range of frequency bands are necessary.
Freshwater fisheries exist among diverse ecosystems and fauna, provide societal benefits, and are influenced by human activities. Fisheries scientists assess the status and sustainability of fisheries by multiple approaches, including abundance and condition indices, population parameters, community indices, modeling, and surveys of habitat and human dimensions. The future sustainability of freshwater fisheries is limited not by available methods but by society’s will.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Berkshire Encyclopedia of Sustainability","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Berkshire Publishing Group","publisherLocation":"Great Barrington, MA","usgsCitation":"Kwak, T.J., 2010, Fisheries indicators, freshwater, chap. of Berkshire Encyclopedia of Sustainability.","ipdsId":"IP-032599","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":340913,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://oxfordindex.oup.com/view/10.1093/acref/9780190622664.013.0582?rskey=3MsnWi&result=355"},{"id":340914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591183bae4b0e541a03c1a92","contributors":{"authors":[{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564389,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70189132,"text":"70189132 - 2010 - Genetic diversity and variation of mitochondrial DNA in native and introduced bighead carp","interactions":[],"lastModifiedDate":"2017-06-30T14:23:57","indexId":"70189132","displayToPublicDate":"2010-07-14T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Genetic diversity and variation of mitochondrial DNA in native and introduced bighead carp","docAbstract":"The bighead carp Hypophthalmichthys nobilis is native to China but has been introduced to over 70 countries and is established in many large river systems. Genetic diversity and variation in introduced bighead carp have not previously been evaluated, and a systematic comparison among fish from different river systems was unavailable. In this study, 190 bighead carp specimens were sampled from five river systems in three countries (Yangtze, Pearl, and Amur rivers, China; Danube River, Hungary; Mississippi River basin, USA) and their mitochondrial 16S ribosomal RNA gene and D-loop region were sequenced (around 1,345 base pairs). Moderate genetic diversity was found in bighead carp, ranging from 0.0014 to 0.0043 for nucleotide diversity and from 0.6879 to 0.9333 for haplotype diversity. Haplotype analysis provided evidence that (1) multiple haplotype groups might be present among bighead carp, (2) bighead carp probably originated from the Yangtze River, and (3) bighead carp in the Mississippi River basin may have some genetic ancestry in the Danube River. The analysis of molecular variance showed significant genetic differentiation among these five populations but also revealed limited differentiation between the Yangtze and Amur River bighead carp. This large-scale study of bighead carp genetic diversity and variation provides the first global perspective of bighead carp in the context of biodiversity conservation as well as invasive species control and management.
","language":"English","publisher":"American Fisheries Society","doi":"10.1577/T09-158.1","usgsCitation":"Li, S., Yang, Q., Xu, J., Wang, C., Chapman, D., and Lu, G., 2010, Genetic diversity and variation of mitochondrial DNA in native and introduced bighead carp: Transactions of the American Fisheries Society, v. 139, no. 4, p. 937-946, https://doi.org/10.1577/T09-158.1.","productDescription":"10 p.","startPage":"937","endPage":"946","ipdsId":"IP-021466","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":343236,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"139","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-01-09","publicationStatus":"PW","scienceBaseUri":"5957635ae4b0d1f9f051b6b7","contributors":{"authors":[{"text":"Li, Si-Fa","contributorId":36821,"corporation":false,"usgs":true,"family":"Li","given":"Si-Fa","email":"","affiliations":[],"preferred":false,"id":703103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Qin-Ling","contributorId":194060,"corporation":false,"usgs":false,"family":"Yang","given":"Qin-Ling","email":"","affiliations":[],"preferred":false,"id":703104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xu, Jia-Wei","contributorId":194061,"corporation":false,"usgs":false,"family":"Xu","given":"Jia-Wei","email":"","affiliations":[],"preferred":false,"id":703105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Cheng-Hui 0000-0001-9508-7425","orcid":"https://orcid.org/0000-0001-9508-7425","contributorId":194062,"corporation":false,"usgs":false,"family":"Wang","given":"Cheng-Hui","email":"","affiliations":[],"preferred":false,"id":703106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":703107,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lu, Guoping","contributorId":38203,"corporation":false,"usgs":true,"family":"Lu","given":"Guoping","email":"","affiliations":[],"preferred":false,"id":703108,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70046831,"text":"70046831 - 2010 - Geodetic evidence for en echelon dike emplacement and concurrent slow slip during the June 2007 intrusion and eruption at Kilauea volcano, Hawaii","interactions":[],"lastModifiedDate":"2021-05-06T15:15:21.26287","indexId":"70046831","displayToPublicDate":"2010-07-13T16:28:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7514,"text":"Journal of Geophysical Research - Solid Earth","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Geodetic evidence for en echelon dike emplacement and concurrent slow slip during the June 2007 intrusion and eruption at Kīlauea volcano, Hawaii","title":"Geodetic evidence for en echelon dike emplacement and concurrent slow slip during the June 2007 intrusion and eruption at Kilauea volcano, Hawaii","docAbstract":"A series of complex events at Kīlauea Volcano, Hawaii, 17 June to 19 June 2007, began with an intrusion in the upper east rift zone (ERZ) and culminated with a small eruption (1500 m3). Surface deformation due to the intrusion was recorded in unprecedented detail by Global Positioning System (GPS) and tilt networks as well as interferometric synthetic aperture radar (InSAR) data acquired by the ENVISAT and ALOS satellites. A joint nonlinear inversion of GPS, tilt, and InSAR data yields a deflationary source beneath the summit caldera and an ENE-striking uniform-opening dislocation with ~2 m opening, a dip of ∼80° to the south, and extending from the surface to ~2 km depth. This simple model reasonably fits the overall pattern of deformation but significantly misfits data near the western end of an inferred dike-like source. Three more complex dike models are tested that allow for distributed opening including (1) a dike that follows the surface trace of the active rift zone, (2) a dike that follows the symmetry axis of InSAR deformation, and (3) two en echelon dike segments beneath mapped surface cracks and newly formed steaming areas. The en echelon dike model best fits near-field GPS and tilt data. Maximum opening of 2.4 m occurred on the eastern segment beneath the eruptive vent. Although this model represents the best fit to the ERZ data, it still fails to explain data from a coastal tiltmeter and GPS sites on Kīlauea's southwestern flank. The southwest flank GPS sites and the coastal tiltmeter exhibit deformation consistent with observations of previous slow slip events beneath Kīlauea's south flank, but inconsistent with observations of previous intrusions. Slow slip events at Kīlauea and elsewhere are thought to occur in a transition zone between locked and stably sliding zones of a fault. An inversion including slip on a basal decollement improves fit to these data and suggests a maximum of ~15 cm of seaward fault motion, comparable to previous slow-slip events.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2009JB006658","usgsCitation":"Montgomery-Brown, E., Sinnett, D.K., Poland, M., Segall, P., Orr, T., Zebker, H., and Mikijus, A., 2010, Geodetic evidence for en echelon dike emplacement and concurrent slow slip during the June 2007 intrusion and eruption at Kilauea volcano, Hawaii: Journal of Geophysical Research - Solid Earth, v. 115, no. B7, B07405, 15 p., https://doi.org/10.1029/2009JB006658.","productDescription":"B07405, 15 p.","ipdsId":"IP-016100","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"links":[{"id":475688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2009jb006658","text":"Publisher Index Page"},{"id":275030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kilauea Volcano","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.798371,19.05835 ], [ -155.798371,19.54759 ], [ -155.016307,19.54759 ], [ -155.016307,19.05835 ], [ -155.798371,19.05835 ] ] ] } } ] }","volume":"115","issue":"B7","noUsgsAuthors":false,"publicationDate":"2010-07-13","publicationStatus":"PW","scienceBaseUri":"51e519ebe4b069f8d27ccafa","contributors":{"authors":[{"text":"Montgomery-Brown, E. K.","contributorId":81722,"corporation":false,"usgs":false,"family":"Montgomery-Brown","given":"E. K.","affiliations":[],"preferred":false,"id":480411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sinnett, D. K.","contributorId":16680,"corporation":false,"usgs":false,"family":"Sinnett","given":"D.","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":480405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poland, Michael 0000-0001-5240-6123","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":49920,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":480409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Segall, P.","contributorId":44231,"corporation":false,"usgs":false,"family":"Segall","given":"P.","affiliations":[],"preferred":false,"id":480408,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orr, Tim R. 0000-0003-1157-7588","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":26365,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":480407,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zebker, H.","contributorId":25276,"corporation":false,"usgs":false,"family":"Zebker","given":"H.","affiliations":[],"preferred":false,"id":480406,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mikijus, Asta 0000-0002-2286-1886","orcid":"https://orcid.org/0000-0002-2286-1886","contributorId":80431,"corporation":false,"usgs":true,"family":"Mikijus","given":"Asta","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":480410,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":98509,"text":"sir20105126 - 2010 - Hydrogeologic framework of the middle San Pedro watershed, southeastern Arizona","interactions":[],"lastModifiedDate":"2018-04-02T15:21:50","indexId":"sir20105126","displayToPublicDate":"2010-07-13T00:00:00","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":"2010-5126","title":"Hydrogeologic framework of the middle San Pedro watershed, southeastern Arizona","docAbstract":"Water managers in rural Arizona are under increasing pressure to provide sustainable supplies of water despite rapid population growth and demands for environmental protection. This report describes the results of a study of the hydrogeologic framework of the middle San Pedro watershed. The components of this report include: (1) a description of the geologic setting and depositional history of basin fill sediments that form the primary aquifer system, (2) updated bedrock altitudes underlying basin fill sediments calculated using a subsurface density model of gravity data, (3) delineation of hydrogeologic units in the basin fill using lithologic descriptions in driller's logs and models of airborne electrical resistivity data, (4) a digital three-dimensional (3D) hydrogeologic framework model (HFM) that represents spatial extents and thicknesses of the hydrogeologic units (HGUs), and (5) description of the hydrologic properties of the HGUs. The lithologic interpretations based on geophysical data and unit thickness and extent of the HGUs included in the HFM define potential configurations of hydraulic zones and parameters that can be incorporated in groundwater-flow models. \r\n\r\nThe hydrogeologic framework comprises permeable and impermeable stratigraphic units: (1) bedrock, (2) sedimentary rocks predating basin-and-range deformation, (3) lower basin fill, (4) upper basin fill, and (5) stream alluvium. The bedrock unit includes Proterozoic to Cretaceous crystalline rocks, sedimentary rocks, and limestone that are relatively impermeable and poor aquifers, except for saturated portions of limestone. The pre-basin-and-range sediments underlie the lower basin fill but are relatively impermeable owing to cementation. However, they may be an important water-bearing unit where fractured. Alluvium of the lower basin fill, the main water-bearing unit, was deposited in the structural trough between the uplifted ridges of bedrock and (or) pre-basin-and-range sediments. Alluvium of the upper basin fill may be more permeable than the lower basin fill, but it is generally unsaturated in the study area. \r\n\r\nThe lower basin fill stratigraphic unit was delineated into three HGUs on the basis of lithologic descriptions in driller?s logs and one-dimensional (1D) electrical models of airborne transient electromagnetic (TEM) surveys. The interbedded lower basin fill (ILBF) HGU represents an upper sequence having resistivity values between 5 and 40 ohm-m identified as interbedded sand, gravel, and clay in driller?s logs. Below this upper sequence, fine-grained lower basin fill (FLBF) HGU represents a thick silt and clay sequence having resistivity values between 5 and 20 ohm-m. Within the coarse-grained lower basin fill (CLBF) HGU, which underlies the silt and clay of the FLBF, the resistivity values on logs and 1D models increase to several hundred ohm-m and are highly variable within sand and gravel layers. These sequences match distinct resistivity and lithologic layers identified by geophysical logs in the adjacent Sierra Vista subwatershed, suggesting that these sequences are laterally continuous within both the Benson and Sierra Vista subwatersheds in the Upper San Pedro Basin. \r\n\r\nA subsurface density model based on gravity data was constructed to identify the top of bedrock and structures that may affect regional groundwater flow. The subsurface density model contains six layers having uniform density values, which are assigned on the basis of geophysical logs. The density values for the layers range between 1.65 g/cm3 for unsaturated sediments near the land surface and 2.67 g/cm3 for bedrock. Major features include three subbasins within the study area, the Huachuca City subbasin, the Tombstone subbasin, and the Benson subbasin, which have no expression in surface topography or lithology. Bedrock altitudes from the subsurface density model defined top altitudes of the bedrock HGU. \r\n\r\nThe HFM includes the following HGUs in ascending stratigr","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105126","collaboration":"Prepared in Cooperation with the Arizona Department of Water Resources","usgsCitation":"Dickinson, J.E., Kennedy, J.R., Pool, D.R., Cordova, J., Parker, J.T., Macy, J.P., and Thomas, B., 2010, Hydrogeologic framework of the middle San Pedro watershed, southeastern Arizona: U.S. Geological Survey Scientific Investigations Report 2010-5126, viii, 36 p. , https://doi.org/10.3133/sir20105126.","productDescription":"viii, 36 p. ","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":125933,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5126.jpg"},{"id":13899,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5126/","linkFileType":{"id":5,"text":"html"}}],"scale":"1","projection":"Universal Transverse Mercator","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 31.5,-110.83333333333333 ], [ 31.5,32.833333333333336 ], [ -109.16666666666667,32.833333333333336 ], [ -109.16666666666667,-110.83333333333333 ], [ 31.5,-110.83333333333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4ee4b07f02db627a32","contributors":{"authors":[{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pool, D. R.","contributorId":75581,"corporation":false,"usgs":true,"family":"Pool","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":305581,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cordova, Jeffrey T. jcordova@usgs.gov","contributorId":1845,"corporation":false,"usgs":true,"family":"Cordova","given":"Jeffrey T.","email":"jcordova@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":false,"id":305578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parker, John T.","contributorId":97886,"corporation":false,"usgs":true,"family":"Parker","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":305582,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Macy, J. P.","contributorId":41913,"corporation":false,"usgs":true,"family":"Macy","given":"J.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":305580,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thomas, Blakemore","contributorId":99660,"corporation":false,"usgs":true,"family":"Thomas","given":"Blakemore","affiliations":[],"preferred":false,"id":305583,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":98510,"text":"sim3064 - 2010 - Seismicity of the Earth 1900-2007","interactions":[{"subject":{"id":98510,"text":"sim3064 - 2010 - Seismicity of the Earth 1900-2007","indexId":"sim3064","publicationYear":"2010","noYear":false,"title":"Seismicity of the Earth 1900-2007"},"predicate":"SUPERSEDED_BY","object":{"id":70208267,"text":"sim3446 - 2020 - Seismicity of the Earth 1900–2018","indexId":"sim3446","publicationYear":"2020","noYear":false,"title":"Seismicity of the Earth 1900–2018"},"id":1}],"supersededBy":{"id":70208267,"text":"sim3446 - 2020 - Seismicity of the Earth 1900–2018","indexId":"sim3446","publicationYear":"2020","noYear":false,"title":"Seismicity of the Earth 1900–2018"},"lastModifiedDate":"2020-02-11T06:46:50","indexId":"sim3064","displayToPublicDate":"2010-07-13T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3064","title":"Seismicity of the Earth 1900-2007","docAbstract":"This map illustrates more than one century of global seismicity in the context of global plate tectonics and the Earth's physiography. Primarily designed for use by earth scientists and engineers interested in earthquake hazards of the 20th and early 21st centuries, this map provides a comprehensive overview of strong earthquakes since 1900. The map clearly identifies the location of the 'great' earthquakes (M8.0 and larger) and the rupture area, if known, of the M8.3 or larger earthquakes. The earthquake symbols are scaled proportional to the moment magnitude and therefore to the area of faulting, thus providing a better understanding of the relative sizes and distribution of earthquakes in the magnitude range 5.5 to 9.5. Plotting the known rupture area of the largest earthquakes also provides a better appreciation of the extent of some of the most famous and damaging earthquakes in modern history. All earthquakes shown on the map were carefully relocated using a standard earth reference model and standardized location procedures, thereby eliminating gross errors and biases in locations of historically important earthquakes that are often found in numerous seismicity catalogs.\r\n","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sim3064","usgsCitation":"Tarr, A.C., Villasenor, A.H., Furlong, K.P., Rhea, S., and Benz, H.M., 2010, Seismicity of the Earth 1900-2007: U.S. Geological Survey Scientific Investigations Map 3064, 1 Sheet: 74.49 x 36.00 inches, https://doi.org/10.3133/sim3064.","productDescription":"1 Sheet: 74.49 x 36.00 inches","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":125934,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3064.jpg"},{"id":13900,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3064/","linkFileType":{"id":5,"text":"html"}}],"scale":"25000000","projection":"Robinson","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e6e4b07f02db5e7768","contributors":{"authors":[{"text":"Tarr, Arthur C. atarr@usgs.gov","contributorId":1925,"corporation":false,"usgs":true,"family":"Tarr","given":"Arthur","email":"atarr@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":305585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villasenor, Antonio H. 0000-0001-8592-4832","orcid":"https://orcid.org/0000-0001-8592-4832","contributorId":38186,"corporation":false,"usgs":true,"family":"Villasenor","given":"Antonio","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":305587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Furlong, Kevin P. 0000-0002-2674-5110","orcid":"https://orcid.org/0000-0002-2674-5110","contributorId":19576,"corporation":false,"usgs":false,"family":"Furlong","given":"Kevin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":305586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rhea, Susan","contributorId":81110,"corporation":false,"usgs":true,"family":"Rhea","given":"Susan","email":"","affiliations":[],"preferred":false,"id":305588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":305584,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70044350,"text":"70044350 - 2010 - The PRISM3D paleoenvironmental reconstruction","interactions":[],"lastModifiedDate":"2013-04-25T09:39:53","indexId":"70044350","displayToPublicDate":"2010-07-13T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"The PRISM3D paleoenvironmental reconstruction","docAbstract":"The Pliocene Research, Interpretation and Synoptic Mapping (PRISM) paleoenvironmental reconstruction is an internally consistent and comprehensive global synthesis of a past interval of relatively warm and stable climate. It is regularly used in model studies that aim to better understand Pliocene climate, to improve model performance in future climate scenarios, and to distinguish model-dependent climate effects. The PRISM reconstruction is constantly evolving in order to incorporate additional geographic sites and environmental parameters, and is continuously refined by independent research findings. The new PRISM three dimensional (3D) reconstruction differs from previous PRISM reconstructions in that it includes a subsurface ocean temperature reconstruction, integrates geochemical sea surface temperature proxies to supplement the faunal-based temperature estimates, and uses numerical models for the first time to augment fossil data. Here we describe the components of PRISM3D and describe new findings specific to the new reconstruction. Highlights of the new PRISM3D reconstruction include removal of Hudson Bay and the Great Lakes and creation of open waterways in locations where the current bedrock elevation is less than 25m above modern sea level, due to the removal of the West Antarctic Ice Sheet and the reduction of the East Antarctic Ice Sheet. The mid-Piacenzian oceans were characterized by a reduced east-west temperature gradient in the equatorial Pacific, but PRISM3D data do not imply permanent El Niño conditions. The reduced equator-to-pole temperature gradient that characterized previous PRISM reconstructions is supported by significant displacement of vegetation belts toward the poles, is extended into the Arctic Ocean, and is confirmed by multiple proxies in PRISM3D. Arctic warmth coupled with increased dryness suggests the formation of warm and salty paleo North Atlantic Deep Water (NADW) and a more vigorous thermohaline circulation system that may have provided the enhanced ocean heat transport necessary to move warm surface water to the Arctic. New deep ocean temperature data also suggests greater warmth and further southward penetration of paleo NADW.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Stratigraphy","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Micropaleontology Press","usgsCitation":"Dowsett, H., Robinson, M., Haywood, A., Salzmann, U., Hill, D., Sohl, L., Chandler, M., Williams, M., Foley, K., and Stoll, D., 2010, The PRISM3D paleoenvironmental reconstruction: Stratigraphy, v. 7, no. 2-3, p. 123-139.","productDescription":"17 p.","startPage":"123","endPage":"139","numberOfPages":"17","ipdsId":"IP-022960","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":271452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"517a506de4b072c16ef14b48","contributors":{"authors":[{"text":"Dowsett, H.","contributorId":44303,"corporation":false,"usgs":true,"family":"Dowsett","given":"H.","email":"","affiliations":[],"preferred":false,"id":475341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, M.","contributorId":50272,"corporation":false,"usgs":true,"family":"Robinson","given":"M.","affiliations":[],"preferred":false,"id":475343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haywood, A.M.","contributorId":101050,"corporation":false,"usgs":true,"family":"Haywood","given":"A.M.","email":"","affiliations":[],"preferred":false,"id":475348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salzmann, U.","contributorId":95711,"corporation":false,"usgs":true,"family":"Salzmann","given":"U.","email":"","affiliations":[],"preferred":false,"id":475347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hill, Daniel","contributorId":67790,"corporation":false,"usgs":true,"family":"Hill","given":"Daniel","affiliations":[],"preferred":false,"id":475346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sohl, L.E.","contributorId":45917,"corporation":false,"usgs":true,"family":"Sohl","given":"L.E.","email":"","affiliations":[],"preferred":false,"id":475342,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chandler, M.","contributorId":28884,"corporation":false,"usgs":true,"family":"Chandler","given":"M.","email":"","affiliations":[],"preferred":false,"id":475340,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Mark","contributorId":15098,"corporation":false,"usgs":true,"family":"Williams","given":"Mark","affiliations":[],"preferred":false,"id":475339,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Foley, K.","contributorId":55315,"corporation":false,"usgs":true,"family":"Foley","given":"K.","email":"","affiliations":[],"preferred":false,"id":475344,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stoll, D.K.","contributorId":66088,"corporation":false,"usgs":true,"family":"Stoll","given":"D.K.","email":"","affiliations":[],"preferred":false,"id":475345,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":98506,"text":"sir20105045 - 2010 - Alluvial Diamond Resource Potential and Production Capacity Assessment of Ghana","interactions":[],"lastModifiedDate":"2012-02-10T00:11:52","indexId":"sir20105045","displayToPublicDate":"2010-07-10T00:00:00","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":"2010-5045","title":"Alluvial Diamond Resource Potential and Production Capacity Assessment of Ghana","docAbstract":"In May of 2000, a meeting was convened in Kimberley, South Africa, and attended by representatives of the diamond industry and leaders of African governments to develop a certification process intended to assure that rough, exported diamonds were free of conflictual concerns. This meeting was supported later in 2000 by the United Nations in a resolution adopted by the General Assembly. By 2002, the Kimberley Process Certification Scheme (KPCS) was ratified and signed by both diamond-producing and diamond-importing countries. Over 70 countries were included as members at the end of 2007.\r\n\r\nTo prevent trade in 'conflict' diamonds while protecting legitimate trade, the KPCS requires that each country set up an internal system of controls to prevent conflict diamonds from entering any imported or exported shipments of rough diamonds. Every diamond or diamond shipment must be accompanied by a Kimberley Process (KP) certificate and be contained in tamper-proof packaging. \r\n\r\nThe objective of this study was to assess the alluvial diamond resource endowment and current production capacity of the alluvial diamond-mining sector in Ghana. A modified volume and grade methodology was used to estimate the remaining diamond reserves within the Birim and Bonsa diamond fields. The production capacity of the sector was estimated using a formulaic expression of the number of workers reported in the sector, their productivity, and the average grade of deposits mined. This study estimates that there are approximately 91,600,000 carats of alluvial diamonds remaining in both the Birim and Bonsa diamond fields: 89,000,000 carats in the Birim and 2,600,000 carats in the Bonsa. \r\n\r\nProduction capacity is calculated to be 765,000 carats per year, based on the formula used and available data on the number of workers and worker productivity. Annual production is highly dependent on the international diamond market and prices, the numbers of seasonal workers actively mining in the sector, and environmental conditions, which influence seasonal farming. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105045","collaboration":"Prepared in cooperation with the Geological Survey Department,\r\nMinerals Commission, \r\nand Precious Minerals Marketing Company of Ghana\r\nunder the auspices of the U.S. Department of State","usgsCitation":"Chirico, P., Malpeli, K., Anum, S., and Phillips, E.C., 2010, Alluvial Diamond Resource Potential and Production Capacity Assessment of Ghana: U.S. Geological Survey Scientific Investigations Report 2010-5045, iv, 25 p. , https://doi.org/10.3133/sir20105045.","productDescription":"iv, 25 p. ","costCenters":[{"id":410,"text":"National Center","active":false,"usgs":true}],"links":[{"id":125931,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5045.jpg"},{"id":13895,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5045/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -20,5 ], [ -20,20 ], [ 13,20 ], [ 13,5 ], [ -20,5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adee4b07f02db687526","contributors":{"authors":[{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":305570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":305571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anum, Solomon","contributorId":91587,"corporation":false,"usgs":true,"family":"Anum","given":"Solomon","email":"","affiliations":[],"preferred":false,"id":305573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Emily C.","contributorId":65189,"corporation":false,"usgs":true,"family":"Phillips","given":"Emily","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":305572,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":98500,"text":"fs20103044 - 2010 - Gulf of Mexico Climate-History Calibration Study","interactions":[],"lastModifiedDate":"2012-02-10T00:11:53","indexId":"fs20103044","displayToPublicDate":"2010-07-09T00:00:00","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":"2010-3044","title":"Gulf of Mexico Climate-History Calibration Study","docAbstract":"Reliable instrumental records of past climate are available for about the last 150 years only. To supplement the instrumental record, reconstructions of past climate are made from natural recorders such as trees, ice, corals, and microfossils preserved in sediments. These proxy records provide information on the rate and magnitude of past climate variability, factors that are critical to distinguishing between natural and human-induced climate change in the present. However, the value of proxy records is heavily dependent on calibration between the chemistry of the natural recorder and of the modern environmental conditions. The Gulf of Mexico Climate and Environmental History Project is currently undertaking a climate-history calibration study with material collected from an automated sediment trap. The primary focus of the calibration study is to provide a better calibration of low-latitude environmental conditions and shell chemistry of calcareous microfossils, such as planktic Foraminifera. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20103044","usgsCitation":"Spear, J.W., and Poore, R.Z., 2010, Gulf of Mexico Climate-History Calibration Study: U.S. Geological Survey Fact Sheet 2010-3044, 2 p., https://doi.org/10.3133/fs20103044.","productDescription":"2 p.","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":118477,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2010_3044.jpg"},{"id":13888,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2010/3044/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100,20 ], [ -100,32 ], [ -80,32 ], [ -80,20 ], [ -100,20 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a81e4b07f02db64a241","contributors":{"authors":[{"text":"Spear, Jessica W. jspear@usgs.gov","contributorId":3619,"corporation":false,"usgs":true,"family":"Spear","given":"Jessica","email":"jspear@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":305542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poore, Richard Z. rpoore@usgs.gov","contributorId":345,"corporation":false,"usgs":true,"family":"Poore","given":"Richard","email":"rpoore@usgs.gov","middleInitial":"Z.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":305541,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98505,"text":"sir20105105 - 2010 - Simulated groundwater flow in the Ogallala and Arikaree aquifers, Rosebud Indian Reservation area, South Dakota – Revisions with data through water year 2008 and simulations of potential future scenarios","interactions":[],"lastModifiedDate":"2021-12-14T19:52:30.499727","indexId":"sir20105105","displayToPublicDate":"2010-07-09T00:00:00","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":"2010-5105","title":"Simulated groundwater flow in the Ogallala and Arikaree aquifers, Rosebud Indian Reservation area, South Dakota – Revisions with data through water year 2008 and simulations of potential future scenarios","docAbstract":"The Ogallala and Arikaree aquifers are important water resources in the Rosebud Indian Reservation area and are used extensively for irrigation, municipal, and domestic water supplies. Drought or increased withdrawals from the Ogallala and Arikaree aquifers in the Rosebud Indian Reservation area have the potential to affect water levels in these aquifers. This report documents revisions and recalibration of a previously published three-dimensional, numerical groundwater-flow model for this area. Data for a 30-year period (water years 1979 through 2008) were used in steady-state and transient numerical simulations of groundwater flow. In the revised model, revisions include (1) extension of the transient calibration period by 10 years, (2) the use of inverse modeling for steady-state calibration, (3) model calibration to base flow for an additional four surface-water drainage basins, (4) improved estimation of transient aquifer recharge, (5) improved delineation of vegetation types, and (6) reduced cell size near large capacity water-supply wells. In addition, potential future scenarios were simulated to assess the potential effects of drought and increased groundwater withdrawals.
The model comprised two layers: the upper layer represented the Ogallala aquifer and the lower layer represented the Arikaree aquifer. The model’s grid had 168 rows and 202 columns, most of which were 1,640 feet (500 meters) wide, with narrower rows and columns near large water-supply wells. Recharge to the Ogallala and Arikaree aquifers occurs from precipitation on the outcrop areas. The average recharge rates used for the steady-state simulation were 2.91 and 1.45 inches per year for the Ogallala aquifer and Arikaree aquifer, respectively, for a total rate of 255.4 cubic feet per second (ft3/s). Discharge from the aquifers occurs through evapotranspiration, discharge to streams as base flow and spring flow, and well withdrawals. Discharge rates for the steady-state simulation were 171.3 ft3/s for evapotranspiration, 74.4 ft3/s for net outflow to streams and springs, and 11.6 ft3/s for well withdrawals. Estimated horizontal hydraulic conductivity used for the numerical model ranged from 0.2 to 84.4 feet per day (ft/d) in the Ogallala aquifer and from 0.1 to 4.3 ft/d in the Arikaree aquifer. A uniform vertical hydraulic conductivity value of 4.2x10-4 ft/d was estimated for the Ogallala aquifer. Vertical hydraulic conductivity was estimated for five zones in the Arikaree aquifer and ranged from 8.8x10-5 to 3.7 ft/d. Average rates of recharge, maximum evapotranspiration, and well withdrawals were included in the steady-state simulation, whereas the time-varying rates were included in the transient simulation.
Inverse modeling techniques were used for steady-state model calibration. These methods were designed to estimate parameter values that are, statistically, the most likely set of values to result in the smallest differences between simulated and observed hydraulic heads and base-flow discharges. For the steady-state simulation, the root mean square error for simulated hydraulic heads for all 383 wells was 27.3 feet. Simulated hydraulic heads were within ±50 feet of observed values for 93 percent of the wells. The potentiometric surfaces of the two aquifers calculated by the steady-state simulation established initial conditions for the transient simulation. For the transient simulation, the difference between the simulated and observed means for hydrographs was within ±40 feet for 98 percent of 44 observation wells.
A sensitivity analysis was used to examine the response of the calibrated steady-state model to changes in model parameters including horizontal and vertical hydraulic conductivity, evapotranspiration, recharge, and riverbed conductance. The model was most sensitive to recharge and maximum evapotranspiration and least sensitive to riverbed and spring conductances.
To simulate a potential future drought scenario, a synthetic recharge record was created, the mean of which was equal to 64 percent of the average estimated recharge rate for the 30-year calibration period. This synthetic recharge record was used to simulate the last 20 years of the calibration period under drought conditions. Compared with results of the calibrated model, decreases in hydraulic-head values for the drought scenario at the end of the simulation period were as much as 39 feet for the Ogallala aquifer. To simulate the effects of potential increases in pumping, well withdrawal rates were increased by 50 percent from those estimated for the 30-year calibration period for the last 20 years of the calibration period. Compared with results of the calibrated model, decreases in hydraulic-head values for the scenario of increased pumping at the end of the simulation period were as much as 13 feet for the Ogallala aquifer.
This numerical model is suitable as a tool to help understand the flow system, to help confirm that previous estimates of aquifer properties were reasonable, and to estimate aquifer properties in areas without data. The model also is useful to help assess the effects of drought and increases in pumping by simulations of these scenarios, the results of which are not precise but may be considered when making water management decisions.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105105","collaboration":"Prepared in cooperation with the Rosebud Sioux Tribe","usgsCitation":"Long, A.J., and Putnam, L.D., 2010, Simulated groundwater flow in the Ogallala and Arikaree aquifers, Rosebud Indian Reservation area, South Dakota – Revisions with data through water year 2008 and simulations of potential future scenarios: U.S. Geological Survey Scientific Investigations Report 2010-5105, viii, 54 p., https://doi.org/10.3133/sir20105105.","productDescription":"viii, 54 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2007-10-01","temporalEnd":"2008-09-30","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":118481,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5105.jpg"},{"id":392872,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_93504.htm"},{"id":13894,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5105/","linkFileType":{"id":5,"text":"html"}}],"scale":"1","projection":"Universal Transverse Mercator","country":"United States","state":"South Dakota","otherGeospatial":"Arikaree aquifer, Ogallala aquifer, Rosebud Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.2881,\n 42.96\n ],\n [\n -100.1711,\n 42.96\n ],\n [\n -100.1711,\n 43.6456\n ],\n [\n -101.2881,\n 43.6456\n ],\n [\n -101.2881,\n 42.96\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e568","contributors":{"authors":[{"text":"Long, Andrew J. 0000-0001-7385-8081 ajlong@usgs.gov","orcid":"https://orcid.org/0000-0001-7385-8081","contributorId":989,"corporation":false,"usgs":true,"family":"Long","given":"Andrew","email":"ajlong@usgs.gov","middleInitial":"J.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Putnam, Larry D. ldputnam@usgs.gov","contributorId":990,"corporation":false,"usgs":true,"family":"Putnam","given":"Larry","email":"ldputnam@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":305569,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98503,"text":"ofr20101144 - 2010 - Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios","interactions":[{"subject":{"id":98503,"text":"ofr20101144 - 2010 - Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios","indexId":"ofr20101144","publicationYear":"2010","noYear":false,"title":"Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios"},"predicate":"SUPERSEDED_BY","object":{"id":98900,"text":"sir20105233 - 2010 - A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios","indexId":"sir20105233","publicationYear":"2010","noYear":false,"title":"A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios"},"id":1}],"supersededBy":{"id":98900,"text":"sir20105233 - 2010 - A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios","indexId":"sir20105233","publicationYear":"2010","noYear":false,"title":"A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios"},"lastModifiedDate":"2012-02-02T00:15:01","indexId":"ofr20101144","displayToPublicDate":"2010-07-09T00:00:00","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":"2010-1144","title":"Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios","docAbstract":"The Energy Independence and Security Act of 2007 (EISA), Section 712, authorizes the U.S. Department of the Interior to develop a methodology and conduct an assessment of the Nation's ecosystems focusing on carbon stocks, carbon sequestration, and emissions of three greenhouse gases (GHGs): carbon dioxide, methane, and nitrous oxide. The major requirements include (1) an assessment of all ecosystems (terrestrial systems, such as forests, croplands, wetlands, shrub and grasslands; and aquatic ecosystems, such as rivers, lakes, and estuaries), (2) an estimation of annual potential capacities of ecosystems to increase carbon sequestration and reduce net GHG emissions in the context of mitigation strategies (including management and restoration activities), and (3) an evaluation of the effects of controlling processes, such as climate change, land use and land cover, and wildlfires. The purpose of this draft methodology for public review is to propose a technical plan to conduct the assessment. \r\nWithin the methodology, the concepts of ecosystems, carbon pools, and GHG fluxes used for the assessment follow conventional definitions in use by major national and international assessment or inventory efforts. In order to estimate current ecosystem carbon stocks and GHG fluxes and to understand the potential capacity and effects of mitigation strategies, the method will use two time periods for the assessment: 2001 through 2010, which establishes a current ecosystem GHG baseline and will be used to validate the models; and 2011 through 2050, which will be used to assess future potential conditions based on a set of projected scenarios. The scenario framework is constructed using storylines of the Intergovernmental Panel on Climate Change (IPCC) Special Report Emission Scenarios (SRES), along with initial reference land-use and land-cover (LULC) and land-management scenarios. An additional three LULC and land-management mitigation scenarios will be constructed for each storyline to enhance carbon sequestration and reduce GHG fluxes in ecosystems. Input from regional experts and stakeholders will be solicited to construct realistic and meaningful scenarios. \r\nThe methods for mapping the current LULC and ecosystem disturbances will require the extensive use of both remote-sensing data and in-situ (for example, forest inventory data) to capture and characterize landscape-change events. For future potential LULC and ecosystem disturbances, key drivers such as socioeconomic, policy, and climate assumptions will be used in addition to biophysical data. The product of these analyses will be a series of maps for each future year for each scenario. These annual maps will form the basis for estimating carbon storage and GHG emissions. For terrestrial ecosystems, carbon storage, carbon-sequestration capacities, and GHG emissions under the current and projected future conditions will be assessed using the LULC and ecosystem-disturbance estimates in map format with a spatially explicit biogeochemical ensemble modeling system that incorporates properties of management activities (such as tillage or harvesting) and properties of individual ecosystems (such as elevation, vegetation characteristics, and soil attributes). For aquatic ecosystems, carbon burial in sediments and GHG fluxes are functions of the current and projected future stream flow and sediment transports, and therefore will be assessed using empirical modeling methods. Validation and uncertainty analysis methods described in the methodology will follow established guidelines to assess the quality of the assessment results. \r\nThe U.S. Environmental Protection Agency's Level II ecoregions map (which delineates 24 ecoregions for the Nation) will be the practical instrument for developing and delivering assessment results. Consequently, the ecoregion will be the reporting unit of the assessment because the mitigation scenarios, assessment results, validation, and uncertainty analysis will be","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101144","usgsCitation":"Bergamaschi, B., Bernknopf, R., Clow, D., Dye, D., Faulkner, S., Forney, W., Gleason, R., Hawbaker, T., Liu, J., Liu, S., Prisley, S., Reed, B., Reeves, M., Rollins, M., Sleeter, B., Sohl, T., Stackpoole, S., Stehman, S., Striegl, R.G., Wein, A., and Zhu, Z., 2010, Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios: U.S. Geological Survey Open-File Report 2010-1144, xviii, 196 p.; Appendices, https://doi.org/10.3133/ofr20101144.","productDescription":"xviii, 196 p.; Appendices","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":118486,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1144.jpg"},{"id":13891,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1144","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a90e4b07f02db656127","contributors":{"editors":[{"text":"Zhu, Zhi-Liang zzhu@usgs.gov","contributorId":3636,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhi-Liang","email":"zzhu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":505753,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":1448,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian A.","email":"bbergama@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":305548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernknopf, Richard","contributorId":51701,"corporation":false,"usgs":true,"family":"Bernknopf","given":"Richard","affiliations":[],"preferred":false,"id":305557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clow, David","contributorId":21920,"corporation":false,"usgs":true,"family":"Clow","given":"David","affiliations":[],"preferred":false,"id":305552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dye, Dennis","contributorId":54159,"corporation":false,"usgs":true,"family":"Dye","given":"Dennis","affiliations":[],"preferred":false,"id":305558,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Faulkner, Stephen 0000-0001-5295-1383","orcid":"https://orcid.org/0000-0001-5295-1383","contributorId":65439,"corporation":false,"usgs":true,"family":"Faulkner","given":"Stephen","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":305560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Forney, William","contributorId":23509,"corporation":false,"usgs":true,"family":"Forney","given":"William","affiliations":[],"preferred":false,"id":305553,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gleason, 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Matthew","contributorId":72347,"corporation":false,"usgs":true,"family":"Rollins","given":"Matthew","affiliations":[],"preferred":false,"id":305563,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sleeter, Benjamin","contributorId":48927,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","affiliations":[],"preferred":false,"id":305556,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Sohl, Terry 0000-0002-9771-4231","orcid":"https://orcid.org/0000-0002-9771-4231","contributorId":81861,"corporation":false,"usgs":true,"family":"Sohl","given":"Terry","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":305564,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stackpoole, 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Division","active":true,"usgs":true}],"preferred":false,"id":305549,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":305546,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Zhu, Zhi-Liang","contributorId":70726,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhi-Liang","affiliations":[],"preferred":false,"id":305562,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":98501,"text":"ofr20101120 - 2010 - Thermal Imaging of the Waccasassa Bay Preserve: Image Acquisition and Processing","interactions":[],"lastModifiedDate":"2012-02-10T00:11:53","indexId":"ofr20101120","displayToPublicDate":"2010-07-09T00:00:00","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":"2010-1120","title":"Thermal Imaging of the Waccasassa Bay Preserve: Image Acquisition and Processing","docAbstract":"Thermal infrared (TIR) imagery was acquired along coastal Levy County, Florida, in March 2009 with the goal of identifying groundwater-discharge locations in Waccasassa Bay Preserve State Park (WBPSP). Groundwater discharge is thermally distinct in winter when Floridan aquifer temperature, 71-72 degrees F, contrasts with the surrounding cold surface waters. Calibrated imagery was analyzed to assess temperature anomalies and related thermal traces. The influence of warm Gulf water and image artifacts on small features was successfully constrained by image evaluation in three separate zones: Creeks, Bay, and Gulf. Four levels of significant water-temperature anomalies were identified, and 488 sites of interest were mapped. Among the sites identified, at least 80 were determined to be associated with image artifacts and human activity, such as excavation pits and the Florida Barge Canal. Sites of interest were evaluated for geographic concentration and isolation. High site densities, indicating interconnectivity and prevailing flow, were located at Corrigan Reef, No. 4 Channel, Winzy Creek, Cow Creek, Withlacoochee River, and at excavation sites. In other areas, low to moderate site density indicates the presence of independent vents and unique flow paths. A directional distribution assessment of natural seep features produced a northwest trend closely matching the strike direction of regional faults. Naturally occurring seeps were located in karst ponds and tidal creeks, and several submerged sites were detected in Waccasassa River and Bay, representing the first documentation of submarine vents in the Waccasassa region. Drought conditions throughout the region placed constraints on positive feature identification. Low discharge or displacement by landward movement of saltwater may have reduced or reversed flow during this season. Approximately two-thirds of seep locations in the overlap between 2009 and 2005 TIR night imagery were positively re-identified in 2009. These results indicate a 33 percent chance of feature omission in the 2009 imagery. This assessment of seep location and distribution contributes to an understanding of the underlying geology, the role of fault and fracture patterns, and the presence of both interconnected and constrained flow paths in the region. The maps and evaluations will enhance Park management efforts, interpretation of Park resources, and increase understanding of the combined effects of land and water use on the coastal lowlands, estuarine habitats, and natural resources of WBPSP. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101120","collaboration":"Prepared in cooperation with Waccasassa Bay Preserve State Park and Florida Springs Initiative","usgsCitation":"Raabe, E.A., and Bialkowska-Jelinska, E., 2010, Thermal Imaging of the Waccasassa Bay Preserve: Image Acquisition and Processing: U.S. Geological Survey Open-File Report 2010-1120, vii, 91 p., https://doi.org/10.3133/ofr20101120.","productDescription":"vii, 91 p.","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":118485,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1120.jpg"},{"id":13889,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1120/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.33333333333333,29 ], [ -83.33333333333333,29.466666666666665 ], [ -82.5,29.466666666666665 ], [ -82.5,29 ], [ -83.33333333333333,29 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a57e4b07f02db62e915","contributors":{"authors":[{"text":"Raabe, Ellen A. eraabe@usgs.gov","contributorId":2125,"corporation":false,"usgs":true,"family":"Raabe","given":"Ellen","email":"eraabe@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":305543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bialkowska-Jelinska, Elzbieta","contributorId":35408,"corporation":false,"usgs":true,"family":"Bialkowska-Jelinska","given":"Elzbieta","email":"","affiliations":[],"preferred":false,"id":305544,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98498,"text":"ofr20101135 - 2010 - Initial Results from a Study of Climatic Changes and the Effect on Wild Sheep Habitat in Selected Study Areas of Alaska","interactions":[],"lastModifiedDate":"2012-02-10T00:10:06","indexId":"ofr20101135","displayToPublicDate":"2010-07-08T00:00:00","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":"2010-1135","title":"Initial Results from a Study of Climatic Changes and the Effect on Wild Sheep Habitat in Selected Study Areas of Alaska","docAbstract":"Climate change theorists have projected striking changes in local weather on earth due to increases in temperature. These predicted changes may cause melting glaciers and ice caps, rising sea levels, increasing desertification and other environmental changes which seem likely to affect presumed indicator species as harbingers of more significant changes. Wild sheep, even though they are one of the more successful mammalian taxa since Pleistocene times, exhibit a suite of adaptations to glacier driven environments which may be presumed to render them sensitive to environmental changes. The authors began investigation with these assumptions by comparing changes, as determined by satellite imagery, in glacier extent in our study areas in Denali National Park, Alaska, during the last 30 years. Our findings showed the extent of glacial retreat in Alaska during this time period was approximately 40-50 percent as measured by ablation zone and retreat of terminal moraines. During the first half of this 30-year period, Dall sheep (Ovis dalli dalli) populations were stable at historically recorded highs. In the early to mid-1990s, Dall sheep populations in Alaska declined from an historical estimated high of 75,000 sheep to the presently estimated 40-50,000. The declines seemed to be weather related, on the basis of the presumption that lamb survival rates are primarily weather-mediated in Alaska. Changes in local weather appear, at this point, to be correlated with oscillation in the Pacific Current in the Northern Pacific ocean. Of course, changes in local weather affect forage abundance and quality seasonally. In investigating a possible linkage of weather to seasonal forage abundance and quality, we also investigated changes in snow and ice extent and distribution, as well as increased water runoff associated with permafrost and depleted glaciers. Databases were assembled from a wide variety of remotely sensed satellite data, ground-based observations, and historical data bases relating to Dall sheep habitats in selected study areas. Alaska's sheep habitats are typified by long, narrow bands of mountainous uplifts generally arrayed west-to-east, and perpendicular to prevailing south-to-north weather-front movements. Classic Dall sheep habitat occurs on snow-shadowed slopes within these narrow mountainous habitats. On the basis of these data, we offer an explanatory hypothesis relating Dall sheep welfare to weather and climate-influenced nutrition and a monitoring scheme, which should produce data sufficient to test the robustness of this hypothesis. If correlated with population changes, the methods used in our comparative observations may provide long-term monitoring tools for wildlife managers and be applicable in other widely-dispersed wild sheep habitats. If no significant correlations emerge from our modeling exercises, the notion that wild sheep are a sufficiently sensitive species to be seen as an indicator species will have to be reexamined. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101135","usgsCitation":"Pfeifer, E., Ruhlman, J., Middleton, B., Dye, D., and Acosta, A., 2010, Initial Results from a Study of Climatic Changes and the Effect on Wild Sheep Habitat in Selected Study Areas of Alaska: U.S. Geological Survey Open-File Report 2010-1135, iv, 39 p.; Appendices, https://doi.org/10.3133/ofr20101135.","productDescription":"iv, 39 p.; Appendices","onlineOnly":"Y","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":125930,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1135.jpg"},{"id":13886,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1135/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -150.33333333333334,63.166666666666664 ], [ -150.33333333333334,63.666666666666664 ], [ -149,63.666666666666664 ], [ -149,63.166666666666664 ], [ -150.33333333333334,63.166666666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e886","contributors":{"authors":[{"text":"Pfeifer, Edwin epfeifer@usgs.gov","contributorId":569,"corporation":false,"usgs":true,"family":"Pfeifer","given":"Edwin","email":"epfeifer@usgs.gov","affiliations":[],"preferred":true,"id":305534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruhlman, Jana","contributorId":93013,"corporation":false,"usgs":true,"family":"Ruhlman","given":"Jana","email":"","affiliations":[],"preferred":false,"id":305538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middleton, Barry","contributorId":38119,"corporation":false,"usgs":true,"family":"Middleton","given":"Barry","affiliations":[],"preferred":false,"id":305535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dye, Dennis","contributorId":54159,"corporation":false,"usgs":true,"family":"Dye","given":"Dennis","affiliations":[],"preferred":false,"id":305536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Acosta, Alex aacosta@usgs.gov","contributorId":73557,"corporation":false,"usgs":true,"family":"Acosta","given":"Alex","email":"aacosta@usgs.gov","affiliations":[],"preferred":false,"id":305537,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037196,"text":"70037196 - 2010 - Impacts of exotic mangrove forests and mangrove deforestation on carbon remineralization and ecosystem functioning in marine sediments","interactions":[],"lastModifiedDate":"2026-01-30T15:56:01.29745","indexId":"70037196","displayToPublicDate":"2010-07-08T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of exotic mangrove forests and mangrove deforestation on carbon remineralization and ecosystem functioning in marine sediments","docAbstract":"To evaluate how mangrove invasion and removal can modify short-term benthic carbon cycling and ecosystem functioning, we used stable-isotopically labeled algae as a deliberate tracer to quantify benthic respiration and C-flow over 48 h through macrofauna and bacteria in sediments collected from (1) an invasive mangrove forest, (2) deforested mangrove sites 2 and 6 years after removal of above-sediment mangrove biomass, and (3) two mangrove-free control sites in the Hawaiian coastal zone. Sediment oxygen consumption (SOC) rates averaged over each 48 h investigation were significantly greater in the mangrove and mangrove removal site experiments than in controls and were significantly correlated with total benthic (macrofauna and bacteria) biomass and sedimentary mangrove biomass (SMB). Bacteria dominated short-term C-processing of added microalgal-C and benthic biomass in sediments from the invasive mangrove forest habitat and in the 6-yr removal site. In contrast, macrofauna were the most important agents in the short-term processing of microalgal-C in sediments from the 2-yr mangrove removal site and control sites. However, mean faunal abundance and C-uptake rates in sediments from both removal sites were significantly higher than in control cores, which collectively suggest that community structure and short-term C-cycling dynamics of sediments in habitats where mangroves have been cleared can remain fundamentally different from un-invaded mudflat sediments for at least 6-yrs following above-sediment mangrove removal. In summary, invasion by mangroves can lead to dramatic shifts in benthic ecosystem function, with sediment metabolism, benthic community structure and short-term C-remineralization dynamics being affected for years following invader removal.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-7-2129-2010","issn":"18106277","usgsCitation":"Sweetman, A.K., Middelburg, J.J., Berle, A.M., Bernardino, A.F., Schander, C., Demopoulos, A.W., and Smith, C.R., 2010, Impacts of exotic mangrove forests and mangrove deforestation on carbon remineralization and ecosystem functioning in marine sediments: Biogeosciences, v. 7, no. 7, p. 2129-2145, https://doi.org/10.5194/bg-7-2129-2010.","productDescription":"17 p.","startPage":"2129","endPage":"2145","costCenters":[],"links":[{"id":475691,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-7-2129-2010","text":"Publisher Index Page"},{"id":382036,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"7","noUsgsAuthors":false,"publicationDate":"2010-07-08","publicationStatus":"PW","scienceBaseUri":"505a38eae4b0c8380cd61729","contributors":{"authors":[{"text":"Sweetman, A. K.","contributorId":52432,"corporation":false,"usgs":true,"family":"Sweetman","given":"A.","middleInitial":"K.","affiliations":[],"preferred":false,"id":459849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Middelburg, J. J.","contributorId":105417,"corporation":false,"usgs":true,"family":"Middelburg","given":"J.","middleInitial":"J.","affiliations":[],"preferred":false,"id":459852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berle, A. M.","contributorId":57695,"corporation":false,"usgs":true,"family":"Berle","given":"A.","middleInitial":"M.","affiliations":[],"preferred":false,"id":459851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernardino, A. F.","contributorId":53632,"corporation":false,"usgs":true,"family":"Bernardino","given":"A.","middleInitial":"F.","affiliations":[],"preferred":false,"id":459850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schander, C.","contributorId":12719,"corporation":false,"usgs":true,"family":"Schander","given":"C.","email":"","affiliations":[],"preferred":false,"id":459846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Demopoulos, A. W.J.","contributorId":50638,"corporation":false,"usgs":true,"family":"Demopoulos","given":"A.","middleInitial":"W.J.","affiliations":[],"preferred":false,"id":459848,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, C. R.","contributorId":32876,"corporation":false,"usgs":true,"family":"Smith","given":"C.","middleInitial":"R.","affiliations":[],"preferred":false,"id":459847,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70156102,"text":"70156102 - 2010 - Sub-weekly to interannual variability of a high-energy shoreline","interactions":[],"lastModifiedDate":"2021-03-17T12:20:47.309201","indexId":"70156102","displayToPublicDate":"2010-07-07T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Sub-weekly to interannual variability of a high-energy shoreline","docAbstract":"Sixty-one Global Positioning System (GPS), sub-aerial beach surveys were completed at 7 km long Ocean Beach, San Francisco, CA (USA), between April 2004 and March 2009. The five-year time series contains over 1 million beach elevation measurements and documents detailed changes in beach morphology over a variety of spatial, temporal, and physical forcing scales. Results show that seasonal processes dominate at Ocean Beach, with the seasonal increase and decrease in wave height being the primary driver of shoreline change. Storm events, while capable of causing large short-term changes in the shoreline, did not singularly account for a large percentage of the overall observed change. Empirical orthogonal function (EOF) analysis shows that the first two modes account for approximately three-quarters of the variance in the data set and are represented by the seasonal onshore/offshore movement of sediment (60%) and the multi-year trend of shoreline rotation (14%). The longer-term trend of shoreline rotation appears to be related to larger-scale bathymetric change. An EOF-based decomposition technique is developed that is capable of estimating the shoreline position to within one standard deviation of the range of shoreline positions observed at most locations along the beach. The foundation of the model is the observed relationship between the temporal amplitudes of the first EOF mode and seasonally-averaged offshore wave height as well as the linear trend of shoreline rotation. This technique, while not truly predictive because of the requirement of real-time wave data, is useful because it can predict shoreline position to within reasonable confidence given the absence of field data once the model is developed at a particular site.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2010.05.011","usgsCitation":"Hansen, J., and Barnard, P.L., 2010, Sub-weekly to interannual variability of a high-energy shoreline: Coastal Engineering, v. 57, no. 11-12, p. 959-972, https://doi.org/10.1016/j.coastaleng.2010.05.011.","productDescription":"13 p.","startPage":"959","endPage":"972","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-011159","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":306838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Ocean Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.51815795898436,\n 37.68708070686609\n ],\n [\n -122.49412536621094,\n 37.68708070686609\n ],\n [\n -122.49412536621094,\n 37.78102667641841\n ],\n [\n -122.51815795898436,\n 37.78102667641841\n ],\n [\n -122.51815795898436,\n 37.68708070686609\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"11-12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d45734e4b0518e354694f5","contributors":{"authors":[{"text":"Hansen, Jeff E.","contributorId":146437,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff E.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":567872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":567871,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70044347,"text":"70044347 - 2010 - Sensitivity of the Greenland Ice Sheet to Pliocene sea surface temperatures","interactions":[],"lastModifiedDate":"2013-05-10T08:48:18","indexId":"70044347","displayToPublicDate":"2010-07-07T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity of the Greenland Ice Sheet to Pliocene sea surface temperatures","docAbstract":"The history of theGrIS (Greenland Ice Sheet), particularly in warm climates of the pre-Quaternary, is poorly known. IRD (ice-rafted debris) records suggest that the ice sheet has existed, at least transiently, since theMiocene and potentially since as long ago as the Eocene. As melting of the GrIS is a key uncertainty in future predictions of climate and sea-level, understanding its behaviour and role within the climate system during pastwarm periods could provide important constraints. The Pliocene has been identified as a key period for understanding warmer than modern climates. Detailed micropalaeontological analyses of the mid-Piacenzian Warm Period (3.264-3.025 Ma) have produced a series of SST (sea-surface temperature) reconstructions (PRISM2-AVE, PRISM2-MAX, PRISM2-MIN and\nPRISM3).Use of these different SSTswithin theHadley CentreGCM(GeneralCirculationModel) and BASISM (BritishAntarctic Survey Ice Sheet Model), consistently show large reductions of Pliocene Greenland ice volumes compared to modern. The changes in climate introduced by the use of different SST reconstructions do change the predicted ice volumes, mainly through precipitation feedbacks. However, the models show a relatively low sensitivity of modelled Greenland ice volumes to different mid-Piacenzian SST reconstructions, with the largest SST induced changes being 20% of Pliocene ice volume or less than a metre of sea-level rise.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Stratigraphy","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"National Environment Research Council","usgsCitation":"Hill, D.J., Dolan, A.M., Haywood, A.M., Hunter, S.J., and Stoll, D.K., 2010, Sensitivity of the Greenland Ice Sheet to Pliocene sea surface temperatures: Stratigraphy, v. 7, no. 2-3, p. 111-121.","startPage":"111","endPage":"121","numberOfPages":"12","ipdsId":"IP-022759","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":272166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272165,"type":{"id":11,"text":"Document"},"url":"https://nora.nerc.ac.uk/12794/1/Hill_111-122.pdf"}],"country":"Greenland","volume":"7","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518e16e0e4b05ebc8f7cc2f3","contributors":{"authors":[{"text":"Hill, Daniel J.","contributorId":80993,"corporation":false,"usgs":true,"family":"Hill","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":475333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dolan, Aisling M.","contributorId":30117,"corporation":false,"usgs":true,"family":"Dolan","given":"Aisling","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":475331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haywood, Alan M.","contributorId":86663,"corporation":false,"usgs":true,"family":"Haywood","given":"Alan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":475334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunter, Stephen J.","contributorId":55711,"corporation":false,"usgs":true,"family":"Hunter","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":475332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stoll, Danielle K.","contributorId":88236,"corporation":false,"usgs":true,"family":"Stoll","given":"Danielle","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":475335,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156577,"text":"70156577 - 2010 - Assimilating models and data to enhance predictions of shoreline evolution","interactions":[],"lastModifiedDate":"2021-10-26T15:55:17.530257","indexId":"70156577","displayToPublicDate":"2010-07-05T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Assimilating models and data to enhance predictions of shoreline evolution","docAbstract":"A modeling system that considers both long- and short-term process-driven shoreline change is presented. The modeling system is integrated into a data assimilation framework that uses sparse observations of shoreline change to correct a model forecast and to determine unobserved model variables and free parameters. Application of the assimilation algorithm also provides quantitative statistical estimates of uncertainty that can be applied to coastal hazard and vulnerability assessments. Significant attention is given to the estimation of four non-observable quantities using the data assimilation framework that utilizes only one observable process (i.e. ,shoreline change). The general framework discussed here can be applied to many other geophysical processes by simply changing the model component to one applicable to the processes of interest.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of 32nd International Conference on Coastal Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"32nd International Conference on Coastal Engineering","conferenceDate":"June 30-July 5 2010","conferenceLocation":"Shanghai, China","language":"English","publisher":"International Conference on Coastal Engineering","doi":"10.9753/icce.v32.sediment.91","usgsCitation":"Long, J.W., and Plant, N.G., 2010, Assimilating models and data to enhance predictions of shoreline evolution, in Proceedings of 32nd International Conference on Coastal Engineering, Shanghai, China, June 30-July 5 2010, 6 p., https://doi.org/10.9753/icce.v32.sediment.91.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-024580","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":475692,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.9753/icce.v32.sediment.91","text":"Publisher Index Page"},{"id":307339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2011-01-31","publicationStatus":"PW","scienceBaseUri":"55dc402be4b0518e354d10d9","contributors":{"editors":[{"text":"Smith, Jane McKee","contributorId":146956,"corporation":false,"usgs":false,"family":"Smith","given":"Jane","email":"","middleInitial":"McKee","affiliations":[],"preferred":false,"id":569562,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lynett, Patrick","contributorId":24298,"corporation":false,"usgs":true,"family":"Lynett","given":"Patrick","affiliations":[],"preferred":false,"id":569563,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":569560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":569561,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98493,"text":"fs20103047 - 2010 - Estuaries of the Greater Everglades Ecosystem: Laboratories of Long-term Change","interactions":[],"lastModifiedDate":"2012-02-02T00:14:44","indexId":"fs20103047","displayToPublicDate":"2010-07-03T00:00:00","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":"2010-3047","title":"Estuaries of the Greater Everglades Ecosystem: Laboratories of Long-term Change","docAbstract":"Restoring the greater Everglades ecosystem of south Florida is arguably the largest ecosystem restoration effort to date. A critical goal is to return more natural patterns of flow through south Florida wetlands and into the estuaries, but development of realistic targets requires acknowledgement that ecosystems are constantly evolving and changing in response to a variety of natural and human-driven stressors.\r\n\r\nExamination of ecosystems over long periods of time requires analysis of sedimentary records, such as those deposited in the wetlands and estuaries of south Florida. As sediment accumulates, it preserves information about the animals and plants that lived in the environment and the physical, chemical, and climatic conditions present. One of the methods used to interpret this information is paleoecology-the study of the ecology of previously living organisms. \r\n\r\nPaleoecologic investigations of south Florida estuaries provide quantitative data on historical variability of salinity and trends that may be applied to statistical models to estimate historical freshwater flow. These data provide a unique context to estimate future ecosystem response to changes related to restoration activities and predicted changes in sea level and temperature, thus increasing the likelihood of successful and sustainable ecosystem restoration.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20103047","usgsCitation":"Wingard, G., Hudley, J., and Marshall, F., 2010, Estuaries of the Greater Everglades Ecosystem: Laboratories of Long-term Change: U.S. Geological Survey Fact Sheet 2010-3047, 4 p., https://doi.org/10.3133/fs20103047.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":125855,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2010_3047.jpg"},{"id":13879,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2010/3047/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67eb16","contributors":{"authors":[{"text":"Wingard, G.L.","contributorId":79981,"corporation":false,"usgs":true,"family":"Wingard","given":"G.L.","email":"","affiliations":[],"preferred":false,"id":305517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudley, J.W.","contributorId":18872,"corporation":false,"usgs":true,"family":"Hudley","given":"J.W.","affiliations":[],"preferred":false,"id":305516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marshall, F.E.","contributorId":103380,"corporation":false,"usgs":true,"family":"Marshall","given":"F.E.","email":"","affiliations":[],"preferred":false,"id":305518,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98488,"text":"sir20105102 - 2010 - Simulation of Groundwater Mounding Beneath Hypothetical Stormwater Infiltration Basins","interactions":[],"lastModifiedDate":"2012-03-08T17:16:13","indexId":"sir20105102","displayToPublicDate":"2010-07-02T00:00:00","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":"2010-5102","title":"Simulation of Groundwater Mounding Beneath Hypothetical Stormwater Infiltration Basins","docAbstract":"Groundwater mounding occurs beneath stormwater management structures designed to infiltrate stormwater runoff. Concentrating recharge in a small area can cause groundwater mounding that affects the basements of nearby homes and other structures. Methods for quantitatively predicting the height and extent of groundwater mounding beneath and near stormwater\r\n\r\nFinite-difference groundwater-flow simulations of infiltration from hypothetical stormwater infiltration structures (which are typically constructed as basins or dry wells) were done for 10-acre and 1-acre developments. Aquifer and stormwater-runoff characteristics in the model were changed to determine which factors are most likely to have the greatest effect on simulating the maximum height and maximum extent of groundwater mounding. Aquifer characteristics that were changed include soil permeability, aquifer thickness, and specific yield. Stormwater-runoff variables that were changed include magnitude of design storm, percentage of impervious area, infiltration-structure depth (maximum depth of standing water), and infiltration-basin shape. Values used for all variables are representative of typical physical conditions and stormwater management designs in New Jersey but do not include all possible values. Results are considered to be a representative, but not all-inclusive, subset of likely results.\r\n\r\nMaximum heights of simulated groundwater mounds beneath stormwater infiltration structures are the most sensitive to (show the greatest change with changes to) soil permeability. The maximum height of the groundwater mound is higher when values of soil permeability, aquifer thickness, or specific yield are decreased or when basin depth is increased or the basin shape is square (and values of other variables are held constant). Changing soil permeability, aquifer thickness, specific yield, infiltration-structure depth, or infiltration-structure shape does not change the volume of water infiltrated, it changes the shape or height of the groundwater mound resulting from the infiltration. An aquifer with a greater soil permeability or aquifer thickness has an increased ability to transmit water away from the source of infiltration than aquifers with lower soil permeability; therefore, the maximum height of the groundwater mound will be lower, and the areal extent of mounding will be larger.\r\n\r\nThe maximum height of groundwater mounding is higher when values of design storm magnitude or percentage of impervious cover (from which runoff is captured) are increased (and other variables are held constant) because the total volume of water to be infiltrated is larger. The larger the volume of infiltrated water the higher the head required to move that water away from the source of recharge if the physical characteristics of the aquifer are unchanged. The areal extent of groundwater mounding increases when soil permeability, aquifer thickness, design-storm magnitude, or percentage of impervious cover are increased (and values of other variables are held constant).\r\n\r\nFor 10-acre sites, the maximum heights of the simulated groundwater mound range from 0.1 to 18.5 feet (ft). The median of the maximum-height distribution from 576 simulations is 1.8 ft. The maximum areal extent (measured from the edge of the infiltration basins) of groundwater mounding of 0.25-ft ranges from 0 to 300 ft with a median of 51 ft for 576 simulations. Stormwater infiltration at a 1-acre development was simulated, incorporating the assumption that the hypothetical infiltration structure would be a pre-cast concrete dry well having side openings and an open bottom. The maximum heights of the simulated groundwater-mounds range from 0.01 to 14.0 ft. The median of the maximum-height distribution from 432 simulations is 1.0 ft. The maximum areal extent of groundwater mounding of 0.25-ft ranges from 0 to 100 ft with a median of 10 ft for 432 simulations.\r\n\r\nSimulated height and extent of groundwater mounding associ","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105102","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Carleton, G.B., 2010, Simulation of Groundwater Mounding Beneath Hypothetical Stormwater Infiltration Basins: U.S. Geological Survey Scientific Investigations Report 2010-5102, vii, 64 p.; 1 Appendix (xls), https://doi.org/10.3133/sir20105102.","productDescription":"vii, 64 p.; 1 Appendix (xls)","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":125556,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5102.jpg"},{"id":13874,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5102/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e48d1e4b07f02db54762a","contributors":{"authors":[{"text":"Carleton, Glen B. 0000-0002-7666-4407 carleton@usgs.gov","orcid":"https://orcid.org/0000-0002-7666-4407","contributorId":3795,"corporation":false,"usgs":true,"family":"Carleton","given":"Glen","email":"carleton@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":305498,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70200019,"text":"70200019 - 2010 - Coupled arsenotrophy in a hot spring photosynthetic biofilm at Mono Lake, California","interactions":[],"lastModifiedDate":"2018-10-10T15:41:02","indexId":"70200019","displayToPublicDate":"2010-07-01T15:40:21","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Coupled arsenotrophy in a hot spring photosynthetic biofilm at Mono Lake, California","docAbstract":"Red-pigmented biofilms grow on rock and cobble surfaces present in anoxic hot springs located on Paoha Island in Mono Lake. The bacterial community was dominated (∼ 85% of 16S rRNA gene clones) by sequences from the photosynthetic Ectothiorhodospiragenus. Scraped biofilm materials incubated under anoxic conditions rapidly oxidized As(III) to As(V) in the light via anoxygenic photosynthesis but could also readily reduce As(V) to As(III) in the dark at comparable rates. Back-labeling experiments with 73As(V) demonstrated that reduction to 73As(III) also occurred in the light, thereby illustrating the cooccurrence of these two anaerobic processes as an example of closely coupled arsenotrophy. Oxic biofilms also oxidized As(III) to As(V). Biofilms incubated with [14C]acetate oxidized the radiolabel to 14CO2 in the light but not the dark, indicating a capacity for photoheterotrophy but not chemoheterotrophy. Anoxic, dark-incubated samples demonstrated As(V) reduction linked to additions of hydrogen or sulfide but not acetate. Chemoautotrophy linked to As(V) as measured by dark fixation of [14C]bicarbonate into cell material was stimulated by either H2 or HS−. Functional genes for the arsenate respiratory reductase (arrA) and arsenic resistance (arsB) were detected in sequenced amplicons of extracted DNA, with about half of the arrA sequences closely related (∼98% translated amino acid identity) to those from the family Ectothiorhodospiraceae. Surprisingly, no authentic PCR products for arsenite oxidase (aoxB) were obtained, despite observing aerobic arsenite oxidation activity. Collectively, these results demonstrate close linkages of these arsenic redox processes occurring within these biofilms.
Oxyanions of the group 15 element arsenic, arsenate [As(V)] and arsenite [As(III)], have been known for millennia to be potent poisons. Despite its well-established toxicity to life, the phenomenon of arsenic resistance was discovered whereby some microorganisms maintain an otherwise “normal” existence in the presence of high concentrations of As(V) or As(III) (17, 29, 31). More recently it has become recognized that certain representatives from the bacterial and archaeal domains can actually exploit the electrochemical potential of the As(V)/As(III) redox couple (+130 mV) to gain energy for growth. This can be achieved either by employing As(III) as an autotrophic electron donor or by using As(V) as a respiratory electron acceptor (18, 21, 34). The latter phenomenon, although most commonly associated with chemoheterotrophy, can also employ inorganic substances like sulfide or H2. Indeed, As(V)-respiring anaerobes displaying a capacity for chemoautotrophy with these electron donors have been isolated and described (5, 7, 16). We recently reported that photoautotrophy is supported by As(III) in anoxic biofilms located in hot springs on Paoha Island in Mono Lake, CA (15). This process represented a novel means of As(III) oxidation achieved via anoxygenic photosynthesis occurring in certain photosynthetic bacteria (i.e., Ectothiorhodospira) and possibly within some cyanobacteria as well (e.g., “Oscillatoria”).
Whether or not a microbial habitat is overtly oxic or anoxic, or temporally shifts between these two states over a diel cycle, critical energy linkages between aerobes and anaerobes have long been known for the biogeochemical cycles of key elements, such as sulfur, iron, and nitrogen. Most prominently studied is the case of nitrogen, whereby an ecological coupling exists between the processes of nitrification and denitrification (9, 10, 28). The former process provides energy to aerobic nitrifiers, while the latter process consumes the nitrate produced by this reaction, thereby meeting the energy needs of the denitrifiers.
For arsenic, the detection of both As(III) oxidation and As(V) reduction in oxic and anoxic incubations of freshly collected periphyton suggested that an analogous coupled process may also occur for this element (12). Similarly, several uncontaminated soils in Japan displayed a capacity for either As(V) reduction or As(III) oxidation upon arsenic oxyanion amendment and whether they were incubated under oxic or anoxic conditions (39). A defined coculture consisting of an aerobic As(III) oxidizer (strain OL1) and an anaerobic As(V) respirer (strain Y5) was shown to function in this fashion under manipulated laboratory conditions of oxygen tension (26). We pursued the phenomenon of coupled arsenic metabolism further by using materials collected from the hot spring biofilms in Mono Lake, but we focused on examination of the cycling of arsenic under anoxic conditions.
In this paper we report results obtained by manipulated incubations of red-pigmented biofilms found in the hot springs of Paoha Island. Preliminary community characterizations of these biofilms show that they are dominated by Bacteria from the genus Ectothiorhodospira but also harbor an assemblage of Archaea related to the Halobacteriacaea. Incubation results have demonstrated the presence of the following arsenic metabolic activities: respiratory As(V) reduction, photosynthetic anaerobic As(III) oxidation, and aerobic As(III) oxidation, along with the ecophysiological conditions under which they occur. Surprisingly, we were unable to obtain authentic PCR products for arsenite oxidase genes (aoxB), despite observing aerobic As(III) oxidation activity. These biofilms serve as a model system for how anaerobic cycling of arsenic can be sustained with oxidation of As(III) by anoxygenic photosynthesis coupled to regeneration of this electron donor via dissimilatory As(V) reduction. The significance that such a light-driven anaerobic ecosystem may have played in the Archean Earth is discussed.
","language":"English","publisher":"American Society for Microbiology Journals","doi":"10.1128/AEM.00545-10","usgsCitation":"Hoeft, S.E., Kulp, T.R., Han, S., Lanoil, B., and Oremland, R.S., 2010, Coupled arsenotrophy in a hot spring photosynthetic biofilm at Mono Lake, California: Applied and Environmental Microbiology, v. 76, no. 14, p. 4633-4639, https://doi.org/10.1128/AEM.00545-10.","productDescription":"7 p.","startPage":"4633","endPage":"4639","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":475693,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2901740","text":"External Repository"},{"id":358255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mono Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.148,37.940 ], [ -119.148,38.075 ], [ -118.909,38.075 ], [ -118.909,37.940 ], [ -119.148,37.940 ] ] ] } } ] }","volume":"76","issue":"14","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10c6b6e4b034bf6a7f4668","contributors":{"authors":[{"text":"Hoeft, Shelley E.","contributorId":54077,"corporation":false,"usgs":true,"family":"Hoeft","given":"Shelley","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":747829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulp, Thomas R.","contributorId":15948,"corporation":false,"usgs":true,"family":"Kulp","given":"Thomas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":747830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Han, Sukkyun","contributorId":95739,"corporation":false,"usgs":true,"family":"Han","given":"Sukkyun","email":"","affiliations":[],"preferred":false,"id":747831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lanoil, Brian","contributorId":29683,"corporation":false,"usgs":true,"family":"Lanoil","given":"Brian","email":"","affiliations":[],"preferred":false,"id":747832,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oremland, Ronald S. 0000-0001-7382-0147 roremlan@usgs.gov","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":931,"corporation":false,"usgs":true,"family":"Oremland","given":"Ronald","email":"roremlan@usgs.gov","middleInitial":"S.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":747833,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168805,"text":"70168805 - 2010 - Resilience of Alaska’s boreal forest to climatic change","interactions":[],"lastModifiedDate":"2016-03-04T13:13:44","indexId":"70168805","displayToPublicDate":"2010-07-01T14:15:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1170,"text":"Canadian Journal of Forest Research","active":true,"publicationSubtype":{"id":10}},"title":"Resilience of Alaska’s boreal forest to climatic change","docAbstract":"This paper assesses the resilience of Alaska’s boreal forest system to rapid climatic change. Recent warming is associated with reduced growth of dominant tree species, plant disease and insect outbreaks, warming and thawing of permafrost, drying of lakes, increased wildfire extent, increased postfire recruitment of deciduous trees, and reduced safety of hunters traveling on river ice. These changes have modified key structural features, feedbacks, and interactions in the boreal forest, including reduced effects of upland permafrost on regional hydrology, expansion of boreal forest into tundra, and amplification of climate warming because of reduced albedo (shorter winter season) and carbon release from wildfires. Other temperature-sensitive processes for which no trends have been detected include composition of plant and microbial communities, long-term landscape-scale change in carbon stocks, stream discharge, mammalian population dynamics, and river access and subsistence opportunities for rural indigenous communities. Projections of continued warming suggest that Alaska’s boreal forest will undergo significant functional and structural changes within the next few decades that are unprecedented in the last 6000 years. The impact of these social–ecological changes will depend in part on the extent of landscape reorganization between uplands and lowlands and on policies regulating subsistence opportunities for rural communities.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Forest Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"National Research Council of Canada","publisherLocation":"Ottawa","doi":"10.1139/X10-074","usgsCitation":"Chapin, F., McGuire, A.D., Ruess, R.W., Hollingsworth, T.N., Mack, M., Johnstone, J., Kasischke, E., Euskirchen, E., Jones, J.B., Jorgenson, M., Kielland, K., Kofinas, G., Turetsky, M., Yarie, J., Lloyd, A., and Taylor, D., 2010, Resilience of Alaska’s boreal forest to climatic change: Canadian Journal of Forest Research, v. 40, no. 7, p. 1360-1370, https://doi.org/10.1139/X10-074.","productDescription":"11 p.","startPage":"1360","endPage":"1370","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-021191","costCenters":[{"id":199,"text":"Coop Res Unit 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Model simulation showed that the greatest effect on the existing saltwater plume occurred from reducing recharge, suggesting recharge may be a more important consideration in saltwater intrusion management than estimated rates of sea‐level rise. Saltwater intrusion management would benefit from improved constraints on recharge rates by using model‐independent, local precipitation and evapotranspiration data, and improving estimates of confining unit hydraulic properties.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 21st Salt Water Intrusion Meeting, Azores, Portugal, 2010","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","usgsCitation":"Payne, D.F., 2010, Effects of climate change on saltwater intrusion at Hilton Head Island, SC. 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Non-consumptive effects of predators are increasingly recognized as important drivers of community assembly and structure. Specifically, habitat selection responses to top predators during colonization and oviposition can lead to large differences in aquatic community structure, composition and diversity. 2. These differences among communities due to predators may develop as communities assemble, potentially altering the relative quality of predator vs. predator-free habitats through time. If so, community assembly would be expected to modify the subsequent behavioural responses of colonists to habitats containing top predators. Here, we test this hypothesis by manipulating community assembly and the presence of fish in experimental ponds and measuring their independent and combined effects on patterns of colonization by insects and amphibians. 3. Assembly modified habitat selection of dytscid beetles and hylid frogs by decreasing or even reversing avoidance of pools containing blue-spotted sunfish (Enneacanthus gloriosus). However, not all habitat selection responses to fish depended on assembly history. Hydrophilid beetles and mosquitoes avoided fish while chironomids were attracted to fish pools, regardless of assembly history. 4. Our results show that community assembly causes taxa-dependent feedbacks that can modify avoidance of habitats containing a top predator. Thus, non-consumptive effects of a top predator on community structure change as communities assemble and effects of competitors and other predators combine with the direct effects of top predators to shape colonization. 5. This work reinforces the importance of habitat selection for community assembly in aquatic systems, while illustrating the range of factors that may influence colonization rates and resulting community structure. 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