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Samples were submitted for contract laboratory analysis as part of a study examining the occurrence of chromium and natural and anthropogenic hexavalent Chromium, Cr(VI) in groundwater. Data will be used to estimate naturally-occurring background Cr(VI) concentrations upgradient, near the plume margins, and downgradient from a mapped Cr(VI) contamination plume near Hinkley, CA (Izbicki and Groover, 2016). These Contract Lab results are part of the data release including grain-size distribution, photographic and associated chemical and mineral analysis data for 36 sediment core and alluvium samples as well as Scanning Electron Microscopy analysis on select grains from magnetic and heavy mineral separates collected...
Categories: Data;
Tags: California,
Hinkley,
atomic emission spectroscopy,
background level,
chemical analysis,
The ecosystems of the San Francisco Bay estuary are influenced by the salinity of its waters, which in turn depends on flushing by freshwater inflows from the western slopes of the Sierra Nevada. Estimates of full-natural flows in eight major rivers that flush the Bay are analyzed here by extended empirical-orthogonal-function analyses to characterize distinct ‘modes’ of seasonal flow and runoff variability. These modes provide a clear identification of the seasons in which the various rivers respond to hydroclimatic forcings and the seasons during which the rivers most strongly affect San Francisco Bay salinities. About 60 percent of the runoff variability is shared by the rivers over the course of a year but season-to-season...
Categories: Publication;
Types: Citation;
Tags: California,
Climate,
Estuarine salinity,
San Francisc
Predicted probability of marten year-round occurrence derived from future (2076-2095) climate projections and vegetation simulations. Projected marten distribution was created with Maxent (Phillips et al. 2006) using marten detections (N = 102, spanning 1993 – 2011) and eight predictor variables: mean potential evapotranspiration, mean annual precipitation, mean fraction of vegetation carbon burned, mean forest carbon (g C m2), mean fraction of vegetation carbon in forest, understory index (fraction of grass vegetation carbon in forest), average maximum tree LAI, and modal vegetation class. Future climate drivers were generated using statistical downscaling (simple delta method) of general circulation model projections,...
Future winter (January – March) precipitation (mm; averaged over 2046-2065) at a 4 km x 4 km spatial resolution using future climate projections provided through CMIP3 (http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php). Future climate drivers were generated using statistical downscaling (simple delta method) of general circulation model projections, in this case MIROC 3.2 medres (Hasumi and Emori 2004) under the A2 emission scenario (Naki?enovi? et al. 2000). The deltas (differences for temperatures and ratios for precipitation) were used to modify PRISM 4km historical baseline (Daly et al. 1994). Note: The MC1 model is described in data basin (http://databasin.org/climate-center/features/mc1-dynamic-global-vegetation-model)....
Clay percentage was summarized from SSURGO and STATSGO tabular data, joined to source feature data from the NRCS, and then converted to an 800m raster using the cell center to assign the values. This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified...
Clay percentage was summarized from SSURGO and STATSGO tabular data, joined to source feature data from the NRCS, and then converted to an 800m raster using the cell center to assign the values. This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified...
This data set is a digital general soil association map developed by the National Cooperative Soil Survey. It consists of a broad based inventory of soils and nonsoil areas that occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. The soil maps for STATSGO are compiled by generalizing more detailed soil survey maps. Where more detailed soil survey maps are not available, data on geology, topography, vegetation, and climate are assembled, together with Land Remote Sensing Satellite (LANDSAT) images. Soils of like areas are studied, and the probable classification and extent of the soils are determined. Map unit composition for a STATSGO map is determined by transecting...
This product is one of a set of mapped model simulation results generated for a project called "Global Climate Change and California: Potential Implications for Ecosystems, Health, and the Economy". The project was conducted by the Electrical Power Research Institute (EPRI) and funded by the California Energy Commission's Public Interest Energy Research (PIER) Program. The project was the most detailed study ever undertaken on the potential effect of climate change on California. The work examined a broad array of potentially affected sectors as well as the interactions between climate change and increased population, economic growth, and technological change. It considered a wide range of climate change scenarios,...
Agreement in predicted marten year-round distribution derived from future (2046-2065) climate projections and vegetation simulations using 3 GCMs (Hadley CM3 (Johns et al. 2003), MIROC (Hasumi and Emori 2004), and CSIRO Mk3 (Gordon 2002)) under the A2 emissions scenario (Naki?enovi? et al. 2000). Projected marten distribution was created with Maxent (Phillips et al. 2006) using marten detections (N = 302, spanning 1990 – 2011) and eight predictor variables: mean potential evapotranspiration, mean annual precipitation, mean fraction of vegetation carbon burned, mean forest carbon (g C m2), mean fraction of vegetation carbon in forest, understory index (fraction of grass vegetation carbon in forest), average maximum...
Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
These data are .csv files of tagged sea otter re-sighting locations (henceforth, resights) collected in the field using a combination of VHF radio telemetry and direct observation using high powered (80x) telescopes. Sea otters were tracked by shore or boat-based observers from the date of tagging until the time of radio battery failure, the animal’s death, or the end of the project, whichever comes first. The frequency of re-sighting was opportunistic, depending on logistical factors such as coastal access, but generally ranged from daily to weekly. Location coordinates are reported latitude and longitude as well as X and Y coordinates in the projection/datum California Teale-Albers NAD 1927. The file contains...
Categories: Data;
Types: Citation;
Tags: California,
Santa Barbara Channel Islands,
Santa Barbara County,
Southern sea otter,
movement patterns,
These data identify, in general, the areas where final critical habitat for Erigeron parishii (Parish's daisy) occur.
The source of this coverage data set is the fish biodiversity maps created for The Nature Conservancy (TNC) as part of their Hexagon Project. Professor Peter Moyle and his graduate student, Paul Randall, of the Department of Wildlife and Fisheries Conservation Biology at the University of California, Davis were hired to produce range maps for all known fish species that presently occur in California. Each coverage denotes a separate fish species (refer to the species coverage key below). The polygons are estimated to be accurate at a scale of roughly 1:1,000,000. Other California fish species distributions can be found in a gallery at: http://app.databasin.org/app/pages/galleryPage.jsp?id=099b47b7394f47b6b42764829e8a8f09
The source of this coverage data set is the fish biodiversity maps created for The Nature Conservancy (TNC) as part of their Hexagon Project. Professor Peter Moyle and his graduate student, Paul Randall, of the Department of Wildlife and Fisheries Conservation Biology at the University of California, Davis were hired to produce range maps for all known fish species that presently occur in California. Each coverage denotes a separate fish species (refer to the species coverage key below). The polygons are estimated to be accurate at a scale of roughly 1:1,000,000. Other California fish species distributions can be found in a gallery at: http://app.databasin.org/app/pages/galleryPage.jsp?id=099b47b7394f47b6b42764829e8a8f09
The source of this coverage data set is the fish biodiversity maps created for The Nature Conservancy (TNC) as part of their Hexagon Project. Professor Peter Moyle and his graduate student, Paul Randall, of the Department of Wildlife and Fisheries Conservation Biology at the University of California, Davis were hired to produce range maps for all known fish species that presently occur in California. Each coverage denotes a separate fish species (refer to the species coverage key below). The polygons are estimated to be accurate at a scale of roughly 1:1,000,000. Other California fish species distributions can be found in a gallery at: http://app.databasin.org/app/pages/galleryPage.jsp?id=099b47b7394f47b6b42764829e8a8f09
The source of this coverage data set is the fish biodiversity maps created for The Nature Conservancy (TNC) as part of their Hexagon Project. Professor Peter Moyle and his graduate student, Paul Randall, of the Department of Wildlife and Fisheries Conservation Biology at the University of California, Davis were hired to produce range maps for all known fish species that presently occur in California. Each coverage denotes a separate fish species (refer to the species coverage key below). The polygons are estimated to be accurate at a scale of roughly 1:1,000,000. Other California fish species distributions can be found in a gallery at: http://app.databasin.org/app/pages/galleryPage.jsp?id=099b47b7394f47b6b42764829e8a8f09
The source of this coverage data set is the fish biodiversity maps created for The Nature Conservancy (TNC) as part of their Hexagon Project. Professor Peter Moyle and his graduate student, Paul Randall, of the Department of Wildlife and Fisheries Conservation Biology at the University of California, Davis were hired to produce range maps for all known fish species that presently occur in California. Each coverage denotes a separate fish species (refer to the species coverage key below). The polygons are estimated to be accurate at a scale of roughly 1:1,000,000. Other California fish species distributions can be found in a gallery at: http://app.databasin.org/app/pages/galleryPage.jsp?id=099b47b7394f47b6b42764829e8a8f09
The source of this coverage data set is the fish biodiversity maps created for The Nature Conservancy (TNC) as part of their Hexagon Project. Professor Peter Moyle and his graduate student, Paul Randall, of the Department of Wildlife and Fisheries Conservation Biology at the University of California, Davis were hired to produce range maps for all known fish species that presently occur in California. Each coverage denotes a separate fish species (refer to the species coverage key below). The polygons are estimated to be accurate at a scale of roughly 1:1,000,000. Other California fish species distributions can be found in a gallery at: http://app.databasin.org/app/pages/galleryPage.jsp?id=099b47b7394f47b6b42764829e8a8f09
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