9. DATA USE
How To Obtain the Data
Appropriate and Inappropriate Use of these
Current Uses of CA-GAP Data
How To Obtain the Data
The CA-GAP database has a wide potential set of applications for
conservation planning, biogeographical research, and education.
It is the goal of the Gap Analysis Program and the BRD to make the
data and associated information as widely available as possible.
While a CD-ROM of the data will be the most convenient way to obtain
the data, it may also be downloaded via the Internet from the national
GAP home page at:
The home page
will also provide, over the long term, the status of our state's
project, future updates, data availability, and contacts. At the
time of this project's completion, a CD-ROM of the final report
and data will be available at a nominal cost.
Department of Fish and Game will be the long-term custodian of the
CA-GAP database, both for its distribution and its maintenance.
Ultimately it is anticipated they will establish a web site for
users to download the data. Check the CA-GAP web site at:
for links to
the Fish and Game site.
will also be distributed on a CD-ROM. The CD-ROM disk will contain
this report, GIS coverages (except see note below) and TM image
mosaics, all metadata, an interactive atlas version with a customized
graphical user interface to run ARCVIEW software to make routine
queries of the database that are relevant to gap analysis.
Note: At the time of this report, access to the 1:100,000
scale land stewardship/management layer compiled for CA-GAP is restricted
to subscribers of the state's Teale Data Center. Therefore it will
not be distributed either through GAP or California Department of
Fish and Game. Those interested in acquiring the coverage for a
fee are directed to the Teale Data Center GIS Solutions Group,
http://www.gislab.teale.ca.gov/ or (916) 263-1767, for details.
Check the CA-GAP or the Fish and Game web sites, however, for the
current status for this layer. As an alternative, CA-GAP has compiled
a 1:2,000,000 scale version from unrestricted public-domain data.
This lower resolution version is being distributed without restriction.
Check the CA-GAP web site listed above for access.
data have been processed successfully on a computer system at the
University of California, Santa Barbara, no warranty expressed or
implied is made regarding the accuracy or utility of the data on
any other system or for general or scientific purposes, nor shall
the act of distribution constitute any such warranty. This disclaimer
applies both to individual use of the data and aggregate use with
other data. It is strongly recommended that these data are directly
acquired from a USGS Biological Resources Division server (see above
for approved data providers) and not indirectly through other sources
which may have changed the data in some way. It is also strongly
recommended that careful attention be paid to the content of the
metadata file associated with these data. The Biological Resources
Division and the University of California, Santa Barbara shall not
be held liable for improper or incorrect use of the data described
and/or contained herein.
were compiled with regard to the following standards. Please be
aware of the limitations of the data. These data are meant to be
used at a scale of 1:100,000 or smaller (such as 1:250,000 or 1:500,000)
for the purpose of assessing the conservation status of vertebrate
species and vegetation cover types over large geographic regions.
The data have not been assessed for statistical accuracy. Data evaluation
and improvement is ongoing. The Biological Resources Division and
the University of California, Santa Barbara make no claim as to
the data's suitability for other purposes. This is writable data
which may have been altered from the original product if not obtained
from a designated data distributor identified above.
of all information sources used to assemble gap analysis data layers
is central to the scientific defensibility of the Gap Analysis Program.
The information used to describe gap analysis data is called metadata.
Metadata are information about data. Metadata contain information
about the source(s), lineage, content, structure, and availability
of a data set. Metadata also describe intentions, limitations, and
potential uses, allowing for the informed and appropriate application
of the data. Descriptions of metadata function have recently been
published by the Federal Geographic Data Committee (FGDC 1994, 1995).
The GAP metadata
standards have been closely matched to the FGDC standards to ensure
current and future compatibility. As the FGDC standards evolve beyond
the current publication, we anticipate corresponding refinements
in GAP documentation. The format of the GAP metadata consists of
eight major documentation sections (Table 9-1) containing one or
more metadata elements. Each element is named (e.g. Map Projection
Name), and the "Type" of entry (text, integer, date, time)
and "Domain" of the entry (i.e. x > 0) are also defined.
Table 9-1. Metadata
Data Element Categories
Information: What the data set is called, file format description.
Quality Information: Accuracy, consistency, and data sources.
Data Organization Information: Data structure - raster, vector,
Reference Information: Coordinate units, map projection, spatial
and Attribute Information: Attribute codes and reference citations.
Information: How to order the data, on-line access, transfer size.
Reference Information: Date of the metadata, contact for metadata
Information: General data contact, mail, voice, fax, web, e-mail.
metadata will increase as electronic networks expand across the
national and international scene and more requests are made for
distribution of information. As the number of users and the diversity
of disciplines and programs sharing the data expand, the information
carried by metadata will become increasingly important. One of the
goals in defining today's metadata standards is to anticipate these
information via Internet, an HTML verson of the GAP metadata standards
(Cogan and Edwards 1994) is available from the Gap web page. The
For a version
of the current FGDC Metadata Standards (8 June 1994)
http://www.fgdc.gov/Metadata/Metadata.html. The standard is
also available by anonymous file transfer protocol (FTP) from:
www.fgdc.gov (18.104.22.168) under /pub/metadata.
and Inappropriate Use of These Data
is created with a specific end use or uses in mind. This is especially
true for GIS data, which is expensive to produce and must be directed
to meet the immediate program needs. For gap analysis, minimum standards
were set (see a Handbook for Gap Analysis, Scott et al. 1993) to
meet program objectives. These standards include: scale or resolution
(1:100,000 or 100 hectare minimum mapping unit), accuracy (80% accurate
at 95% confidence), and format (ARC/INFO coverage tiled to the 30'x60'
however, that GAP would be the first, and for many years likely
the only, source of statewide biological GIS maps, the data were
created with the expectation that they would be used for other applications.
Therefore, we list below both appropriate and inappropriate uses.
This list is in no way exhaustive but should serve as a guide to
assess whether a proposed use can or cannot be supported by GAP
data. For most uses, it is unlikely that GAP will provide the only
data needed, and for uses with a regulatory outcome, field surveys
should verify the result. In the end it will be the responsibility
of each data user to determine if GAP data can answer the question
being asked, and if they are the best tool to answer that question.
First we must address the issue of appropriate scale to which these
data may be applied. These data were produced with an intended application
at the ecoregion level, that is geographic areas from several hundred
thousand to millions of hectares in size. The data provide a coarse-filter
approach to analyses, meaning that not every occurrence of every
plant community or animal habitat is mapped, only larger, more generalized
distributions. The data are also based on the USGS 1:100,000 scale
of mapping in both detail and precision. When determining whether
to apply GAP data to a particular use, there are two primary questions:
do you want to use the data as a map for the particularly geographic
area, or do you wish to use the data to provide context for a particular
area? The distinction can be made with the following example: You
could use GAP land cover to determine the approximate amount of
oak woodland occurring in a county, or you could map oak woodland
with aerial photography to determine the exact amount. You then
could use GAP data to determine the approximate percentage of all
oak woodland in the region or state that occurs in the county, and
thus a sense of how important the county's distribution is to maintaining
that plant community.
Uses: The above example illustrates two appropriate uses of
the data; as a coarse map for a large area such as a county, and
to provide context for finer-level maps. Specific case-study examples
are provided at the end of the chapter, but following is a general
list of applications:
(Councils of Government) planning
habitat conservation planning
- County comprehensive
- Large area
resource management planning
evaluation of potential impacts or benefits of major projects
or plan initiatives on biodiversity, such as utility or transportation
corridors, wilderness proposals, regional open space and recreation
relative amounts of management responsibility for specific biological
resources among land stewards to facilitate cooperative management
- Basic research
on regional distributions of plants and animals and to help target
both specific species and geographic areas for needed research.
impact assessment for large projects or military activities.
of potential economic impacts from loss of biological resource
at all levels and for both students and citizens.
Uses: It is far easier to identify appropriate uses than inappropriate
ones, however, there is a "fuzzy line" that is eventually
crossed when the differences in resolution of the data, size of
geographic area being analyzed, and precision of the answer required
for the question are no longer compatible. Examples include:
- Use of the
data to map small areas (less than thousands of hectares) typically
requiring mapping resolution at 1:24,000 scale and using aerial
photographs or ground surveys.
GAP data with other data finer than 1:100,000 scale to produce
new hybrid maps or answer queries.
specific areal measurements from the data finer than the nearest
thousand hectares (minimum mapping unit size and accuracy affect
exact boundaries for regulation or acquisition.
definite occurrence or non-occurrence of any feature for an exact
geographic area (for land cover, the percent accuracy will provide
a measure of probability).
abundance, health, or condition of any feature.
a measure of accuracy of any other data by comparison with GAP
the data in any way and redistributing them as a GAP data product.
- Using the
data without acquiring and reviewing the metadata and this report.
Uses of CA-GAP Data
of the CA-GAP land-cover database have already been used in a number
of planning and research applications. We include a sampler of those
uses here to stimulate the interest and creativity of potential
In 1993, the
CA-GAP data were used to assist the Southern California Association
of Governments (SCAG) develop the open space element of their comprehensive
regional plan (Crowe 1996). The distribution of vulnerable plant
community types were compared with the pattern of land use zoning
in the combined general plans of the jurisdictions in the 6 county
area. This information was used to highlight plant communities that
were not only vulnerable because of land management status but also
because of permitted land uses. The results for the portion of the
SCAG area in the Southwestern California region have been updated
in Appendix 6-1. Relatively large proportions of several types are
zoned for development. Other organizations, such as The Nature Conservancy,
are also using CA-GAP data in their planning studies.
habitat types and plant communities layer from CA-GAP has been used
in a variety of applications beyond gap analysis. Wildlife management
studies have included several species, such as the desert tortoise,
bighorn sheep, and mountain lion. Several applications are related
to fire (e.g., fire impacts on vegetation, fuels loading and fire
risk (Sapsis et al. 1996), correlations with lightning strikes,
and mapping of fire regimes. The California Air Resources Board
is coordinating a study of natural, or biogenic, emissions by modeling
rates for different GAP land-cover types. A common limitation for
many of these studies has been the absence of data on canopy size
and density, which has required users to make generalizations about
database has been applied in several studies to identify potential
sites for additional biodiversity management areas to fill gaps
in the representation of native biodiversity. The purpose of these
published studies was development of methods and evaluation of a
range of alternatives. They all stop short of making formal recommendations
for designation, which would require more political discussion on
both the objectives and solutions. Several studies used draft data
on predicted wildlife distributions in Southwestern California to
develop maximal covering location models for identifying priority
sites (Church et al. 1996, Gerrard et al. 1997). This type of model
was later modified as part of a procedure proposed to the U. S.
Forest Service for systematically using gap analysis data to identify
likely sites for new Research Natural Areas (Moritz et al. 1997).
This class of models is designed to represent the most species or
communities in a given number of sites. Davis et al. (1996) developed
the Biodiversity Management Area Selection model to explore a range
of alternative sets of sites based on varying assumptions to meet
different representation goals for plant communities and vertebrates
in the Sierra Nevada region. CA-GAP was the only source of information
that exhaustively mapped these measures of biodiversity across all
stewardships in the region.
"reserve selection" models described above take a rather static
perspective in conservation planning, others have taken a dynamic
approach by modeling urban growth scenarios and its potential impacts
on biodiversity. Various approaches to modeling urbanization have
been developed at University of California, Davis, Berkeley, Santa
Barbara, and Santa Cruz (Cogan 1997), and Harvard (Steinitz et al.
1996, White et al. 1997). CA-GAP data on land-cover and management
were used either as constraints on development (e.g., existing reserves)
or as effects.