Description of a build-out analysis and potential effects on wildlife habitat in the Lower Blue Planning Basin, Summit County, Colorado
David M. Theobald[1]
Natural Resource Ecology Laboratory
Colorado State University, Fort Collins, CO
80523
Introduction
A useful way to frame discussion of activities designed to conserve biodiversity in the planning realm is to ask: 1) where are the areas that have high conservation value? 2) what areas are at risk from development? And 3) what planning actions can be taken to conserve habitat? These questions provide a framework for a GIS-based methodology that was used to assist in evaluating the potential effects of development on wildlife habitat in the Lower Blue Planning Basin in Summit County, Colorado.
Methods
Mapping important habitat
Mapping important habitat areas is an
exercise in making trade-offs. The
practical reality of most planning situations is that there is limited spatial
data to work with. For example, the
distributions of only about 15% of the 104 vertebrates found in Summit County
have been mapped (not to mention invertebrates and plants).
The approach we took was to produce an important habitat (IH) map for Summit County that identifies areas of critical concern for conserving wildlife and natural communities. The IH is composed of four individual maps that identify areas that contain rare vegetation types, known areas of sensitive and rare species, areas of high neighborhood diversity, and/or habitat of economically important species. The composite IH map has values ranging from 0 (not important at all) to 4 (four indexes identify its importance). In practice, we have used a value of one or more to initiate development review (e.g., in Larimer County).
Rare vegetation types: This map identifies locations that contain
rare vegetation types, including all types from the Summit County wetlands map
(excluding irrigated meadow) and Aspen, Willow, Sage, and Water from a land
cover map produced from a classified Landsat TM image (30 m resolution). These vegetation types typically make up
less than 3-5% of the total area (individually).
Sensitive and rare species: This
map shows known locations of habitat for species listed as federally and state
threatened and endangered and state species of special concern. Data come from Colorado Division of
Wildlife’s habitat maps (Table 1), as well as Colorado Natural Heritage
Program’s potential conservation areas and element occurrences (with 400 m
buffer). Note that sage grouse is
likely to be moved in the near future from economically important species to
this map.
Table 1. Maps of known distributions of sensitive and rare species.
|
Species |
Activity
Area |
Description |
|
Bald
Eagle (Haliaeetus leucocephalus) |
Winter
range |
Those
areas where bald eagles have been observed between November 15 and April 1. |
|
Boreal
Toad (Bufo boreas boreas) |
Occurrences |
All locations
where a documented observation of any life stage of the boreal toad (toads,
tadpoles, and/or eggs) has taken place. These locations are represented as
point data and are buffered by 200 meters for protection purposes. |
|
Colorado
River Cutthroat Trout (Oncorhynchus clarki pleuriticus) |
Purity
A&B (buffered by 100m) |
Distribution
of the A & B purity grades of Colorado River Cutthroat trout. |
|
Golden
Eagle (Aquila chrysaetos) |
Nest Sites |
The location and a buffer zone
extending ¼ mile around a known active or inactive nest. Inactive nest sites
are nest sites that have been documented in the past 10 years to have been
used in nesting attempts and, at a minimum, eggs have been deposited in these
nests. |
|
Northern
Goshawk (Accipiter gentilis) |
Sites |
A specific location in
which a pair of goshawk have at least attempted to nest within the last five
years. Any nest location that can be directly tied to courtship, breeding, or
brooding behavior is considered active. A buffer zone of 1/4 mile extends
around an active nest site. |
|
Osprey (Pandion
haliaetus) |
Active
nest sites |
A specific location in which a pair of osprey have
at least attempted to nest within the last five years. Any nest location that
can be directly tied to courtship, breeding, or brooding behavior is
considered active. A buffer zone of 1/4 mile extends around an active nest
site. |
|
Otter
(Lutra canadensis) |
Overall
range and sightings |
An area which encompasses all mapped seasonal
activity areas within the observed range of a population of river otters. |
|
White-tailed
Ptarmigan (Lagopus leucurus altipetens) |
Winter
concentration areas |
That
part of the winter range where densities of birds are at least twice that of
the surrounding winter range. Winter range is defined as locations of birds
from late October to late May. |
High neighborhood species richness: This
map identifies locations that have the top 10% of the county in neighborhood
species richness. This map is produced
by combining the modeled distributions for all 103 vertebrate species found in
Summit County and finding those areas that contribute to the top 10%. The richness value for each species is
weighted by its biological rarity.[2]
Economically Important Species: This map identifies critical ranges for
species important to the local economy (Table 2).
Table 2. Species and activity areas included
in the economically-important habitat map.
|
Species |
Activity Area |
Description |
|
Elk (Cervus elaphus) |
Severe
winter range Migration
paths |
That part of the range of a species where 90 percent
of the individuals are located when the annual snowpack is at its maximum
and/or temperatures are at a minimum in the two worst winters out of ten. The
winter of 1983-84 is a good example of a severe winter. |
|
Mountain
Goat (Oreamnos americanus) |
Production
areas |
That
part of the home range of mountain goat occupied by females between May 15 to
June 30. |
|
Mule
Deer (Odocoileus hemionus) |
Severe
winter range |
That part of the overall range where 90% of the
individuals are located when the annual snowpack is at its maximum and/or
temperatures are at a minimum in the two worst winters out of ten. |
|
Sage
Grouse (Centrocercus urophasianus urophasianus) |
Overall
range |
An area that encompasses all mapped seasonal
activity areas within the observed range of a population of sage grouse. |
Build-out scenarios
Build-out analysis is used to examine probable future development intensities and patterns. Two products of a build-out analysis are maps showing development patterns that reflect different assumptions and tables that quantify the number of new units, residents, and acreage consumed. These patterns show what would likely result if development continues to occur according to current zoning ordinances and subdivision regulations until there are no more parcels to build on[3]. Typically a build-out scenario is created by calculating the number of total building units that can be built on a parcel as prescribed by zoning regulations.
One of the problems we encountered was to model scenarios adequately that require specific parcels to be identified. For example, if a reasonable guess is that only 25% of parcels eligible will be cluster developed, then which parcels should be selected? Rather than randomly selecting parcels that would likely be built, or developing a more complicated model to predict the probability of development, we chose to apply a scenario’s assumption across all applicable parcels. So, for the cluster development scenario, all eligible parcels are modeled as clustered. We do not presume that in reality any one planning action will affect all eligible parcels, but instead feel that this approach will give more insight into the strengths and weaknesses of each approach.
A second difficulty we encountered was that some approaches to modeling a scenario required site-level patterns to be specified. For example, where the location of development occurs in a cluster development is important in understanding any potential impacts. When possible, we avoided making modeling assumptions at the site-level.
A third difficulty was how to best portray the scenarios cartographically. We chose to use randomly located points (dot maps) within each parcel to reflect the number of units that could be built. This allowed the user to easily see different densities within a map (e.g., towns vs. rural areas) and to easily compare patterns between scenarios. Also, we did not show parcel boundaries to simplify the map visually, and to emphasize the pattern of development between parcels, rather than the pattern within a parcel.
We developed a range of scenarios for the Lower Blue Planning Basin (LBPB) that reflected not only baseline conditions, but also a number of regulations and development trends that likely will affect the development patterns.
CB
- Complete build-out (total acres):
This is the baseline scenario where we assumed that development will
utilize all possible units allowed under the zoning regulations currently in place. For each parcel, the number of additional
units possible were calculated, given the size
of the parcel, the number of current units, and the zoning designation were
calculated. Parcel maps need to be
checked to remove parcels that may have a zoning designation but are
right-of-ways (roads), public lands, parks or open space, or owned by home
owner associations. Also, some parcels
may have conservation easements on them that may limit the number of housing units
that can be built. A further complication,
especially when calculating parcel acreage, is that a parcel is not always
represented by a single polygon, or even adjacent polygons, in a GIS. Occasionally parcels are represented by
separate, disjunct polygons (e.g., split by a road right-of-way).
To calculate the build-out units, we first
created a table that had all possible zoning designations and calculated the
number of units per acre that were allowed for each zone (e.g., if 1 unit per
20 acres, then [UperAc] = 0.05).
Second, we joined the zoning table to the parcel theme using zone as the
common attribute. If the parcels did
not have a zone attribute, then spatial joining was used to attribute the
parcels.[4] Third, we calculated the total acres of each parcel. The complex parcels first must be identified, and then merged
together.[5] Finally, we calculated the total units that
could be built.[6] However, all scenarios do not incorporate
potential future units that are available to be built inside the Town of
Silverthorne’s current city limits.
CBN - Complete build-out (net acres): This scenario is based on the complete build-out but uses the developable acreage for each parcel, not the total acres. A number of factors typically reduce the actual amount of land that is available to build on, such as road right-of-ways, lot set backs, and environmental constraints. In this scenario the net developable land was calculated by constraining developable land by wetlands, steep slopes, and road right of ways.[7] The units that could be developed were then based on the net acres.[8] However, it is arguable, especially with large parcels (>10 acres), that these factors do not, in fact, constrain the number of units. Larger parcels offer a fair amount of room to configure a subdivision to maximize the number of units. When the building size of a building envelope approaches the size of the parcel, then it is more likely that these constraints will result in reduced numbers of units. The remaining scenarios used the total developable area rather than the net developable area to calculate the number of units.
S3M - Silverthorne three-mile annexation: This scenario reflects the likelihood that towns and cities frequently annex adjacent, unincorporated areas. Typically, this results in much higher densities in the annexed parcels. In Colorado, incorporated cities can annex unincorporated lands up to 3 miles from current city boundaries. The document that specifies the parcels that would be annexed and their future land use (called “the three-mile plan”) was acquired and the number of units were extracted for parcels that are identified in the plan[9].
DR35, DR80 - Density reductions (1 per 35, 1 per 80): This scenario reflects the possibility that some rural areas might develop at a lower density than what is currently zoned. For example, a large part of the rural area is zoned at 1 unit per 20 acres, but much of the recent development has occurred at a lower density, typically around 1 per 35 acres. Also, it is plausible that some areas will develop at an even lower density of 1 unit per 80 acres.
CD – Clustered Development:
Typically, clustered development rural land-use guidelines provide an
incentive to landowners of allowing additional housing units in compensation
for clustering development in a portion (typically 20-30%) of a large (>40
ac) parcel . In Summit County, the
Rural Land Use Subdivision provides an alternative development process for
rural land owners of parcels 70 acres or greater with A-1 zoning (1 per 20
units).[10] If 85% or more of the parcel is designated
as “open space”, then an additional 15% of the original units can be
built. These regulations have been
adopted to encourage more efficient use of land and to preserve agricultural
lands, wildlife habitat, historic sites, scenic quality, and rural character.
Site-scale planning is required to locate the
developed portion of a clustered development requires site-scale planning and
is beyond the scope of this type of analysis.
Instead, we chose to allow the units to spread randomly across the
entire parcel. However, when we
calculated the indicators, we reduced the impact of each housing unit in
proportion to the developed to open-space ratio. That is, the impact was averaged across the whole parcel, rather
than limiting the impact to just the developed area.
TDR25, TDR50 - Transfer of Development Rights
(25% and 50%): TDR attempts to manage the location of
growth by identifying areas where development is desired (“receiving areas”),
typically near urban areas with in-place infrastructure and where development
is discouraged (“sending areas”). In
the LBPB, we assumed that the receiving area was within the 3 miles of the Town
of Silverthorne, while the sending area was the remainder of the Basin. We arbitrarily chose two TDR situations that
reflect the transfer of all the units from 25% and 50% of the parcels to within
the 3 Mile Plan boundary.
PLA - Public Land Adjustment: We
also wanted to create a scenario reflecting the likely swapping of
public/private land in the area. Often
the land ownership pattern, especially in the western US is fragmented, often
by mining inholdings and homesteads. There are a number of parcels that are
likely to be traded between the federal government and the county, which is
designed to consolidate land holdings.
However, we were unable to acquire the data that specifies the
individual parcels that were targeted for trade, and therefore we were unable
to complete this scenario.
Landsape-level indicators of impact
In addition to producing a series of maps depicting the development patterns for each build-out scenario, we identified a few key indicators that could be used to evaluate the landscape-level effects of new development. First, the total number of units predicted under each scenario is a rough indicator of overall impact. A second indicator is total length of roads required to service development, excluding the primary road infrastructure. Estimates for road densities for future subdivisions were modeled by developing a relationship between housing density and road density for existing subdivisions in mountainous parts of Summit and Gunnison, Colorado (Table 3). For each subdivision, we did not include existing primary county roads that served other areas or driveways. We found a strong linear relationship (R2 0.86) between acres per housing unit (A) and road miles per housing unit (R):
(Eq.
1)
The predicted miles of roads for current development using Equation 1 was 201.7 miles, which is close to the measured current road mileage (excluding highways, primary roads, and trails) of 213.8 miles. Because there are very few existing clustered subdivisions, we assumed that the road miles for clustered subdivisions would be 33% of the roads miles for the number of units in the dispersed subdivision.
Table 3. Data on developed acres per housing unit and road miles per housing unit in Summit and Gunnison counties, Colorado.
|
County |
Acres
per unit |
Road
miles per unit |
County |
Acres
per unit |
Road
miles per unit |
|
Gunnison |
0.602 |
0.012 |
Summit |
0.937 |
0.025 |
|
Gunnison |
1.182 |
0.032 |
Summit |
1.916 |
0.034 |
|
Gunnison |
1.588 |
0.020 |
Summit |
2.004 |
0.033 |
|
Gunnison |
1.770 |
0.026 |
Summit |
2.984 |
0.042 |
|
Gunnison |
27.421 |
0.146 |
Summit |
6.889 |
0.071 |
|
Gunnison |
34.111 |
0.150 |
Summit |
18.765 |
0.184 |
|
Gunnison |
36.573 |
0.263 |
Summit |
29.380 |
0.245 |
|
Gunnison |
37.167 |
0.188 |
Summit |
45.617 |
0.387 |
|
Gunnison |
43.200 |
0.259 |
|
|
|
|
Gunnison |
44.750 |
0.222 |
|
|
|
Third, the total acres of IH that are effected by development was calculated. To account for the varying effects of different levels of housing density, we translated density into the proportion of a parcel that is affected by the zone of disturbance surrounding each housing unit. The zone of disturbance is calculated by assuming that changes in native vegetation and vegetation structure, predation from domestic pets, and wildlife behavior reduces the availability of habitat in the area surrounding a house.[11] We used a building effect distance of 100 m when calculating the zone of disturbance. This is a conservative estimate of impacts to native species found in the region, impacts of between 200 and 800 m have been documented for a range of species. The proportion disturbed increases rapidly with increasing density, so that 20% disturbed at 1 unit per 35 acres increases to 77% at 1 per 10 acres (see Table 4).
Table 4. Proportion of a parcel that is occupied by disturbance zone at different densities, assuming a 100 m building effect.
|
Housing density (acres per unit) |
Proportion of parcel within 100 m |
|
< 2.5 |
100% |
|
2.5 – 10 |
77% |
|
10 – 20 |
39% |
|
20-40 |
20% |
|
> 40 |
10% |
Results
The maps that depict the development patterns resulting from the nine build-out scenarios are shown in figures 1.1 and 1.2. Currently, the Lower Basin is at about 37% build-out as compared to scenario CB (Table 5). At the current rate of growth (1990-1999) in housing units (7-8% per year), build-out will likely be reached in roughly 20 years. Using the CB scenario as a baseline, the other scenarios range from 86% to 117% of total units. An unexpected result was that the number of units predicted by the net-developable scenario (CBN) was the lowest (86%), indicating that current site-development regulations are a strong tool to manage the magnitude of growth. Both the TDR50 and DR80 scenarios would result in an 11% decrease in total units in the LBPB (excluding the Town of Silverthorne). Only 14% of the parcels in the LBPB are eligible for clustered development, and the CD scenario would reduce the units by 3%.
The predicted total miles of road ranged from a low of 229.5 (CD) to a high of 392.0 miles (S3M). Clearly, road miles are reduced the most (37%) by limiting the roads associated with 35 acre development. This disproportionate effect of low-density development is also shown by the fact that although the CBN scenario has 14% fewer units, it resulted in only a 7% reduction in road miles. In contrast, road miles increased by 8% in the S3M scenario, but this likely reflects an overestimation of road miles because more urban development requires fewer roads than the average figure represented in the prediction.
Slightly over 63,000 acres (35%) of the LBPB were identified as IH, which is nearly half of all the IH in the county (Figure 2). Over 39% of IH is privately-owned land, and nearly 60% of IH is on or within 400 m of private land. The number of IH acres effected by current development is 2,205, while the scenarios range from a low of 3,348 acres (DR80) to a high of 5,186 acres (TDR25) -- a 52% and 135% increase, respectively.
At a finer-scale, the IH map was used as a filter to identify developable parcels that may affect the IH quality. In the LBPB, only 20% of all private parcels that could be further developed intersected the IH, but these occupied 90% of the private land in the LBPB. Nearly 30% of these parcels were effected less than 50%, involving 90% of the land area of developable parcels. There is a strong threshold at around 20% effected, where the majority (75%) of the developable area changes. Also, there was little differentiation between the effects predicted by the different scenarios. This suggests that the assumptions made for the scenarios are useful at a broad scale, but that at a finer-scale (per parcel), there is lower utility and a site-level analysis is required.
Table 5. The number of units projected for each build-out scenario. The units are for the Lower Blue Planning Basin (excluding the Town of Silverthorne), unless otherwise noted. Miles of road excludes primary and secondary infrastructure roads (highways).
|
Build-out scenario |
Units |
% Build-out |
Miles of Road |
Acres IH effected (units/ac) |
Efficiency (new units/new acres) |
|
Housing units in 1999 (excluding Silverthorne) |
3043 (1711) |
37% |
213.8 (act. 201.7) |
2205 |
- |
|
Complete
build-out |
8303 |
100% |
362.1 |
4860 |
1.98 |
|
Complete
build-out (net developable) |
7158 |
86% |
337.1 |
4794 |
1.58 |
|
Silverthorne
3-mile annexation |
9716 |
117% |
392.0 |
5045 |
2.34 |
|
Density
reduction (1 per 35 ac) |
7811 |
94% |
350.1 |
4919 |
1.75 |
|
Density
reduction (1 per 80 ac) |
7401 |
89% |
342.0 |
3368 |
1.29 |
|
Clustered
development (all parcels >=70 ac) |
8065 |
97% |
229.5 |
4161 |
1.2 |
|
TDR
25% at random |
7799 |
94% |
362.2 |
5186 |
1.59 |
|
TDR
50% at random |
7404 |
89% |
355.4 |
3648 |
3.02 |
Conclusion
The potential impact of development on biodiversity needs to be evaluated in relation to some development goal. If the development goal is to minimize impacts on biodiversity, then clustered development (especially with judicious placement of the developed portion) and reducing density (1 per 80) is the best direction. However, if the development goal is to maximize the number of units while minimizing the area of IWH effected, then the scenarios that concentrate growth near the Town of Silverthorne (TDR50 and S3M) are very efficient, while scenarios that effect low-density growth most (CD and DR80) were the least efficient. However, if clustered development is designed (at the site-level) to limit impacts on IH by locating the developed portion away from the critical habitat, the efficiencies for the clustered scenario should increase dramatically.
A synthetic scenario, drawing on the characteristics of each scenario that might result in the least impact, would look like the following. First, the existing set-backs and environmental constraints that limit the total number of units should be rigorously enforced. Second, pursue a TDR program that concentrates development in established service areas and away from habitat will lower impacts. Third, cluster development with careful site-level planning should substantially reduce the miles of roads needed and minimize disturbance on habitat.
Figure 1.1 Build-out scenarios.
Figure
1. 2 Build-out scenarios.
Figure 2. Composite Important Habitat map.