Demographics, population, housing, income, education, schools, and geography for ZIP Code 93111 (Santa Barbara, CA). Interactive charts load automatically as you scroll for improved performance.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 93117 (Goleta, CA). Interactive charts load automatically as you scroll for improved performance.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 93441 (Los Olivos, CA). Interactive charts load automatically as you scroll for improved performance.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 93436 (Lompoc, CA). Interactive charts load automatically as you scroll for improved performance.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 93254 (New Cuyama, CA). Interactive charts load automatically as you scroll for improved performance.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 93427 (Buellton, CA). Interactive charts load automatically as you scroll for improved performance.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 93013 (Carpinteria, CA). Interactive charts load automatically as you scroll for improved performance.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 93440 (Los Alamos, CA). Interactive charts load automatically as you scroll for improved performance.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 93429 (Casmalia, CA). Interactive charts load automatically as you scroll for improved performance.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 93434 (Guadalupe, CA). Interactive charts load automatically as you scroll for improved performance.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

Tax rate area boundaries and related data based on changes filed with the Board of Equalization per Government Code 54900 for the specified assessment roll year. The data included in this map is maintained by the California State Board of Equalization and may differ slightly from the data published by other agencies. BOE_TRA layer = tax rate area boundaries and the assigned TRA number for the specified assessment roll year; BOE_Changes layer = boundary changes filed with the Board of Equalization for the specified assessment roll year; Data Table (C##_YYYY) = tax rate area numbers and related districts for the specified assessment roll year

This dataset provides leaf images and measurements of leaf traits (area, wet weight, dry weight, leaf mass per area, leaf water content) and leaf pigments (chlorophyll) and species information as sampled from meadow, shrub, and tree from Santa Barbara California, USA. Samples were collected from plots within the Dangermond Preserve, Sedgwick Reserve, and Carpinteria Salt March Reserve during the period of February 23, 2022 to September 27, 2022 for the 2022 NASA Surface Biology Geology (SBG) High Frequency Time series (SHIFT) campaign. The associated data package contains image scans used for the leaf area calculations as well as python processing code used to calculate the area. A comma-separated value (CSV) formatted file includes plot-level leaf area (cm2), wet weight (g), leaf mass area (LMA, g leaf dry mass per meter square), leaf water content (LWC, (wet weight - dry weight/wet weight, %)), chlorophyll fluorescence ratio (CFR), and chlorophyll content (CHL).

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

The Santa Barbara Channel MBON tracks long-term patterns in species abundance and diversity. This dataset contains counts of fish (including cryptic fish, which are deliberately sought out) produced by integrating data from four contributing projects working in the kelp forests of the Santa Barbara Channel, USA.

This dataset includes three entities, two data tables and R code. The main data table contains counts of organisms, the area over which that number was counted and the height above the bottom. Data were collected by human observation (divers using SCUBA) during regular surveys. The column labeled “count” records the number of organisms found in each plot/transect at a given timestamp.. A second data table contains place names and geolocation for sampling sites. Information is sufficient for the calculation of fish density, which is left to the user. Sample R-code is included (third entity) to illustrate generation of a basic table of areal density by taxa and sampling site. See Methods for information on integration and data processing

The four contributing projects are two research projects: the Santa Barbara Coastal LTER (SBC LTER) and the Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO), and the kelp forest monitoring program of the Santa Barbara Channel National Park, and the San Nicolas Island monitoring program supported by USGS. Together, these projects have recorded data for more than 200 species at approximately 100 sites on both the mainland coast and on the Santa Barbara Channel Islands. Sampling began in 1982 and is ongoing.

The California Department of Conservation, Division of Oil, Gas and Geothermal Resources publishes a GIS feature class of well locations and its associated records across the state for use by the public. Data provided are projected in Teal Albers California North American Datum of 1983 for shapefiles and WGS84 Web Mercator projection for web feature service. Well Attributes include API Number, Operator Well Number, Well Status, Well Type, Operator Code, Operator Name, Lease Name, Field Name, Area Name, District, County, Section, Township, Range, Base Meridian, Latitude, Longitude, Elevation, Total Depth, Redrill Footage, Redrill Cancel Flag, Location Description, Comments, GIS Source, Dry Hole, Confidential Well, Directionally Drilled, Hydraulically Fractured, BLM Well, EPA Well, Spud Date, Completion Date, Abandoned Date.Well location values were collected using a submeter-accurate gps receiver (i.e., Trimble GeoXT). Some of the data provided herein are also displayed in the Division's WellFinder application (http://maps.conservation.ca.gov/doggr/index.html).

The Santa Barbara Channel MBON tracks long-term patterns in species abundance and diversity. This dataset contains counts of algae and invertebrates (both sessile and mobile) by integrating data from four contributing projects working in the kelp forests of the Santa Barbara Channel, USA. This dataset includes three entities, two data tables and R code. The main data table number of organisms and the area over which that number was counted for calculation of areal abundance. Data were collected by human observation (divers using SCUBA) during regular surveys. The column labeled “count” records the number of organisms found at a given timestamp. The algae and invertebrate counts record the number of taxa found in each plot, including quad (small square plots such as 1 or 2 m2) and swath (large linear plots such as 60 m2). See Methods for information on integration and data processing. A second data table contains place names and geolocation for sampling sites. Information is sufficient for the calculation of density, which is left to the user. Sample R-code is included (third entity) to illustrate generation of a basic table of areal density by taxa and sampling site. See Methods for information on integration and data processing The four contributing projects are two research projects: the Santa Barbara Coastal LTER (SBC LTER) and the Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO), and the kelp forest monitoring program of the Santa Barbara Channel National Park, and the San Nicolas Island monitoring program supported by USGS. Together, these projects have recorded data for more than 200 species at approximately 100 sites on both the mainland coast and on the Santa Barbara Channel Islands. Sampling began in 1982 and is ongoing.

Constituents of beach pore water and parameters for calculating residence times are reported for two beaches in the Santa Barbara area, Isla Vista Beach and East Campus Beach, from July 2012 to June 2013. This dataset reports beach pore water concentrations of ammonium and nitrate, total dissolved Nitrogen and Carbon, particulate Nitrogen and Carbon, Radon, salinity, conductance, Oxygen and water temperature. Residence time ("Tau") can be calculated from Radon-222 activities in nearshore seawater, in pore water and at equilibrium, which are presented in a second table (also available in published paper).

  Results from these data were reported in:

   Goodridge, 
    B. M. and J. M. Melack. 2014. Temporal evolution and variability of
    dissolved inorganic nitrogen in beach pore water revealed using radon residence times.
    Environmental Science and Technology, 48: 14211-14218. DOI:10.1021/es504017j

The Gap Fire burned from 2008-07-01 to 2008-07-28, Lizard's Mouth area of Los Padres National Forest, Santa Barbara County. Approximately 9544 acres were burned (information per http://cdfdata.fire.ca.gov). This dataset contains a KML polygon showing the extent of the fire on 2008-07-09, and was acquired by request from the
Geospatial Multi-Agency Coordination Group (GeoMAC, http://www.geomac.gov).

 These data are based upon input from incident
      intelligence sources, Global Positioning System (GPS) data, and infrared (IR)
      imagery. See methods for more information.

These data were generated from a one-time experiment in support of a coral ecophysiology manuscript; published in

   Edmunds, PJ (2011) Limnology and Oceanography 56: 2402-2410
        doi: 10.4319/lo.2011.56.6.2402

  I tested the hypothesis that the effects of high pCO2
        and temperature on massive Porites spp. (Scleractinia) are
        modified by heterotrophic feeding (zooplanktivory). Small colonies of massive Porites spp. from the back reef of
        Moorea, French Polynesia, were incubated for 1 month under combinations of temperature (29.3 C vs. 25.6 C),
        pCO2 (41.6 vs. 81.5 Pa), and feeding regimes (none vs. ad libitum access to live Artemia spp.), with the response
        assessed using calcification and biomass. Area-normalized calcification was unaffected by pCO2, temperature, 
        and the interaction between the two, although it increased 40% with feeding. Biomass increased 35% with feeding
        and tended to be higher at 25.6 C compared to 29.3 C, and as a result, biomass-normalized calcification
        statistically was unaffected by feeding, but was depressed 12-17% by high pCO2, with the effect accentuated at
        25.6 C. These results show that massive Porites spp. has the capacity to resist the effects on calcification of
        1 month exposure to 81.5 Pa pCO2 through heterotrophy and changes in biomass. Area-normalized calcification
        is sustained at high pCO2 by a greater biomass with a reduced biomass-normalized rate of calcification. This
        mechanism may play a role in determining the extent to which corals can resist the long-term effects of ocean
        acidification.