Uncompahgre and Grand Junction Combined Wildlife
Habitat– Outline of GIS Analysis Steps and Data Layers
GIS Analysis
The objective of the GIS analysis is to preliminarily identify
ecologically significant areas within the Uncompahgre & Grand
Junction Field Offices of the BLM based on wildlife features.
We conducted a two-phased process to identify wildlife habitat
priority areas in the Uncompahgre & Grand Junction Field Offices
of the BLM. First we compiled existing GIS data layers for a suite
of identified focal species. Using a simple analysis process, we
combined these data layers together to produce a Wildlife Habitat
map, which served as the basis for highlighting ecological priority
areas within the Forest.
Step 1: Identify Focal Species and Compile Data Layers
The first step in this process is to identify which ecological data
layers should be included in the GIS analysis. A focal species
approach was used to represent broader ecosystem concerns (Noss
and Cooperrider 1994). The following criteria were used to select a
comprehensive suite of focal species for this assessment (for more
information on the focal species and sensitive life stages, see
Appendix A):
Criteria for focal species selection
1) Spatially explicit and accurate habitat data is available for
the species,
2) The species is sensitive to route density, habitat
fragmentation, and other route impacts on its habitat.
3) The species is of special management concern (i.e., hunted
or listed species)
For each of the selected focal species we then identified specific
data layers for inclusion in the GIS analysis, representing key
seasonal, breeding or other significant habitat (Table 3). The
selection of data layers was largely based on habitat components
recognized by the Colorado Division of Wildlife (CDOW) as
having ‘high’ or ‘very high’ value in their compilation of wildlife
habitat data for the Roadless Areas Task Force, (CDOW, 2005).
These weights reflect the relative importance of the identified
habitat to that focal species. For those data layers for which
CDOW has not provided a value weight, we proposed weights
based on the relative significance of each habitat type for that
species, as described in the literature. All weights will be reviewed
by consulting experts.
Table 1 contains a list of focal species and data layers for the GIS
assessment of ecological values in the Uncompahgre and Grand
Junction Field Offices of the BLM. The selection of data layers
was largely based on habitat components recognized by CDOW as
having ‘high’ or ‘very high’ value (from CDOW’s compilation of
wildlife data layers for the Roadless Areas Task Force, Dec. 2005).
For those data layers for which CDOW has not provided a value
weight, our Analysis Team has proposed weights. All weights have
been reviewed during the expert interview process – resulting
changes to the weights are noted in the footnotes below the table.
Table 1: Focal species, data layers and weights used in the GIS
analysis of ecological values. Data sources are: Colorado Division
of Wildlife (CDOW – updated annually) U.S. Forest Service
(USFS – 2003), Southern Rockies Ecosystem Project (SREP 2005), and Colorado Natural Heritage Program (CNHP – updated
2008).
Focal
Species
Bald Eagle
Data Layers
Nest Sites
Source
CDOW
Winter Concentration Areas CDOW
Weight*
Very
High*
Very
Bighorn
Sheep
Summer Concentration
Areas
Occupied Watersheds
CDOW
CDOW
High*
Very
High*
High*
Very
High*
Very
High*
Very High
Potential Habitat
CDOW
Very High
Linkages
Migration Corridors
SREP
CDOW
Very High
Very
High*
High*
High*
Very
High*
High2
Migration Corridors
CDOW
Production Areas
CDOW
Winter Concentration Areas CDOW
Boreal
Toad
Canada
Lynx
Elk
Production Areas
CDOW
Severe Winter Range
CDOW
Winter Concentration Areas CDOW
Gunnison
Sage
Grouse
Mule Deer
Colorado
River
Cutthroat
Summer Concentration
Areas
Included in CNHP PCAs
(data layer is the same as
CDOW identified habitat)
CDOW
CNHP
Concentration Areas
CDOW
Severe Winter Range
CDOW
Winter Concentration Areas CDOW
Migration Corridor
CDOW
Occupied stream segments
CNHP
PCAs
Very
High*
(included
in PCAs)
High*
High*
Very
High*
Very
High*
Very
High*
Trout
* Starred weights reflect the habitat value rankings determined by CDOW’s compilation of wildlife data
layers for the Roadless Areas Task Force (Dec. 2005).
SREP linkage data is not being used for mule deer or elk. Instead,
we are using CDOW’s migration corridor data, which depicts
migration corridors more comprehensively across the entire forest,
rather than just those areas identified as high priority linkages in
Linking Colorado’s Landscapes.
To capture Colorado River Cutthroat Trout, we decided to use the
CNHP identified Potential Conservation Areas instead of CDOW’s
occupied watersheds data layer. The watersheds layer is
generalized and includes extensive downstream areas where the
trout is not present and that may not provide suitable trout habitat
(or are infested with competing invasive species). The PCA’s
capture all of the CDOW-mapped occupied stream segments while
omitting irrelevant portions of the watershed. Additional occupied
stream segments were mapped during the expert interview process.
Other species considered include Mexican spotted owl,
southwestern willow flycatcher, Uncompahgre fritillary butterfly,
Lincoln’s sparrow, Wilson’s warbler, and northern Goshawk –
however, we do not have appropriate Forest-wide data layers to
include them as focal species in the GIS assessment. One
Uncompahgre fritillary butterfly site is included as a Potential
Conservation Area by CNHP. The PCA’s also capture several
peregrine falcon nesting areas (CDOW identifies more, but these
are not being included in the analysis because peregrine falcon was
not selected as a focal species). Outside of those sites included as
PCA’s, we will rely upon the expert interview process and any
additional site-specific data provided by the biologists to integrate
these species into the final ecological assessment.
Habitat types weighted as ‘low’ or ‘moderate’ were excluded from
the ecological assessment. Several habitat types (i.e., bighorn
sheep winter range, black bear fall concentration areas, and moose
concentration areas) were originally assigned a ‘high’ weight, but
following the expert review process, these habitat types were
reassigned a ‘moderate’ ranking, and were therefore excluded from
the final analysis.
Following is a list of other data layers for use in the GIS
assessment.
Data Layer
Source
Weight
Potential Conservation
Colorado Natural
Very High
Areas (include all except
Heritage Program
S.USCOHP2*2092
because CDOW boreal
toad habitat is more
comprehensive and up-todate)
Wetlands
Included in CNHP
Very High
PCAs layer (more
select than pulling
out riparian and
wetland vegetation
types from known
vegetation layers)
Wetlands are being included in the analysis as a surrogate for
riparian species and as a means of minimizing impacts to streams
and watersheds.
Other data layers for use in determining access needs and
developing recommendations:
Data Layer
Source
Colorado Canyon Country
SRCA
Wilderness Proposal
Roads and Trails
UFO & GJFO
Recreation – Management Areas UFO & GJFO
and Sites
Rangeland – Allotments, Stock UFO & GJFO
Driveways and Pastures
Roadless areas were not included as a weighted layer in the GIS
analysis, as much of the area included in this data layer is already
captured by the weighted layers listed above, including roadless
areas as a surrogate for good quality habitat would be doublecounting these areas. The roadless areas and the wilderness layers
will be overlaid with the final GIS assessment and will be included
as an attribute in the Access database. Roadless Areas will also be
considered during recommendations development, as no new roads
or trails should be constructed in Roadless Areas.
GIS Analysis Step 2: Develop Wildlife and Watersheds Values
Layer
The next step in the analysis involved a process commonly referred
to as ‘map algebra’ whereby each input layer is assigned a
numerical weight so that all of the layers can be compiled – or
added – together into a single layer such that each analysis cell is
the sum of all of the input layers at that location. For this process,
we assigned a score of 10 to each ‘very high’ ranked input layer
and a score of ‘1’ to each ‘high’ ranked input layer. Medium and
Low ranked layers were ultimately assigned a score of zero and
thereby excluded from the analysis. It is important to note that this
assignment of numerical scores does not indicate that a ‘very high’
ranked layer is ten times more important than a ‘high’ ranked
layer. Instead, this scoring system was designed to create a twodigit code, where the first digit represents the summed ‘very high’
values of a given cell and the second digit represents the summed
‘high’ values of that cell. For example the score ‘12’ would
indicate that at that point there is one ‘very high’ ecological value
and two ‘high’ values present. To understand the significance of
these values, we must ultimately return to the original source data
– either in the GIS or downloaded into the accompanying Access
database. In this way, the two-digit scoring system flags areas with
multiple weighted ecological values, allowing the user to
immediately assess the cumulative ecological values at any given
location.
Having created the summed output layer, we were able to gauge
the range of cumulative scores across the BLM resource areas.
Through close examination of the data, we were able to identify
natural breaks in the data to define appropriate categories for
assigning ranks to the cumulative output scores (Table 6). Thus
defined, this categorization facilitates visual display of the data. A
score of zero (displayed as white space on the map) indicates that
none of the ecological values considered in the analysis are present
at that location.
Table 6: Final cumulative scores and associated ranks. These
scores do not represent a numerical value, but a two-digit code
indicating the number of ‘very high’ and ‘high’ ranked ecological
values present at given location.
A Score of: Corresponds to:
With a
Final Rank
of:
24 or
At least 3 ‘Very High’
greater
or
=
Very High
2 ‘Very High’ AND 4 or 5
‘High’
14 - 23
At least 2 ‘Very High’
or
=
High
1 ‘Very High’ AND 4 or 5
‘High’
4 – 13
At least 1 ‘Very High’
or
=
Medium
4 or 5 ‘High’
1–3
At least 1 ‘High’
=
Low
This cumulative wildlife habitat and watershed values map (Map
4) can be used for planning purposes to highlight areas with
multiple overlapping ecological priorities. However, planners
cannot rely on this information alone to make management
decisions or recommendations – while these compiled data can
help to identify areas of particular ecological concern, some habitat
areas must be individually considered regardless of the cumulative
ecological value suggested on the map. In all cases, planners must
refer back to the original input layers in order to formulate
appropriate management guidelines and decisions.
To facilitate this process, all of these data were downloaded into an
Access database, where the user can look up, for a given route or
area, the ecological values present at that location. This database
was then augmented with the information compiled during the
expert and community meetings (see following Section). Access is
a relational database system, allowing the user to create links
between a variety of data tables and create queries to better
understand relationships in the data. This database thereby assists
planners in considering a broad array of ecological and other data.
Finally, to further highlight ecological values in the Forest, we
conducted a neighborhood analysis on the wildlife habitat and
watershed values output layer. This GIS process computes an
output grid where the value at each location is a function of the
input cells within a specified neighborhood of the location. We
defined the neighborhood as a 10-cell radius circle, where the
output cell was calculated as the median of each neighborhood1.
This process calculates these focal statistics across the entire input
grid, thereby filtering out small variations in the data. Additional
filtering of the high priority ecological areas layer removed areas
1
This type of focal statistic is considered a low-pass filter which is useful for removing noise in the data.
less than 1,000 acres in size from the final map to highlight areas
of greatest ecological significances in the Forest (Map 5). These
highlighted areas provide a snapshot for identifying areas with
multiple ecological values; separate consideration must be given to
individual ecological values that may not be captured by the
cumulative map.