4.1. The Peoria Tri-County Region
Peoria is a central Illinois city of about 300,000 people, nestled in the Illinois River valley and surrounded on all sides by prime farmland. It sits roughly at the center of a three-county region dominated by the city. The Illinois River bisects this region and much of the river’s banks are made up of high and steep bluffs that are a visual amenity and provide important ecosystem services, such as habitat for several plant and animal species, and filtration for storm-water runoff draining towards the river. At the time of our engagement with the regional planning process in the tri-county region, a key concern was rapid loss of rich farmland as a result of sprawling urban development across the region [
18]. Discussions were well underway in one of the counties with regard to protecting farmland by zoning a minimum 40-acre lot size (just over 16 hectares).
Our initial discussions with stakeholders identified the river bluffs as providing a variety of critical ecosystem services. Development on these bluffs would destroy vegetation that is a large part of the ecosystem services provided and reduce the stability of the steep slopes. Cutting and filling slopes to construct structures could result in landslides that would not only further degrade the bluff ecosystem but also threaten the structures built there.
Among the various land-use futures simulated as part of the regional planning process, one assumed that current development patterns and trends would continue into the future; another assumed that the 40-acre zoning regulation would be implemented to protect farmland. Overlaying each of these future land-use patterns on a map of the region showed that both scenarios involved development on the river bluff; these areas are attractive for a number of reasons—location, views, accessibility. Implementing the 40-acre zoning regulation, however, resulted in significantly larger amounts of development on the river bluff. Large amounts of development that would have otherwise taken place on prime farmland was being, in a sense, driven towards the river bluffs.
In discussions, stakeholders indicated that the findings were reasonable and intuitive [
19]; this unintended consequence had just not occurred to anyone thus far. It was not for lack of expertise and knowledge but rather because few if any stakeholders had a holistic view that would have allowed them to make these connections. Based on these discussions, the decision was made to put the zoning initiative on hold. Instead, a ravine overlay district was developed and put in place to cover the river bluffs; associated regulations were formulated to ensure that future development would be at an intensity and of a kind that would not threaten the ecosystem services. With protections for the bluffs in place, work began on the 40-acre zoning regulation. Implementing bluff protection before enacting the zoning changes ensured that both the bluffs and farmland would be protected. The importance of farmland protection did not change; the question became how to accomplish that goal without compromising other local ecosystem services.
4.2. McHenry County
McHenry County is a fast-growing area on the northwest edge of the Chicago metropolitan area. Our engagement with regional planning in the county was as part of a state government initiative to protect what was termed legacy resources: for instance, prime farmland, unique landscapes, pristine water resources, as well as different kinds of cultural resources. Since many of these resources provide important ecosystem services, we were able to use and refine the approach applied in Peoria. At the time of our engagement, the county government was also engaged in developing a comprehensive plan to deal with the exploding growth they had begun to witness.
As part of this effort, we characterized a number of ecosystem services using data gathered from a variety of local, state, and federal sources. These sources included the McHenry County Conservation District, Illinois Department of Natural Resources, the Illinois Department of Agriculture, and the US Geological Survey. In public reviews of some of our initial characterizations, participants pointed out several instances where the data did not reflect ground realities. This input was taken into account as the initial characterizations were revised and refined. Some of the ecosystem services considered based on stakeholder input and data availability were:
Prime farmland: Areas receiving scores above 90, as assessed by the U.S. Department of Agriculture’s Natural Resources Conservation Service using the Land Evaluation Site Assessment (LESA) method. Evaluation is based on data from the National Cooperative Soil Survey, often called the largest and most valuable natural resource database in the world [
20].
Wetlands: Areas, identified in the McHenry County Advanced Identification (ADID) project in 1999, exhibiting exceptionally high quality biological and habitat functions.
Threatened and endangered species: Quarter-sections (blocks of land 1/4 mile square) that are found by the Illinois Department of Natural Resources to contain at least one individual member of these species. Data is only available at such aggregate levels to protect the exact location where the individuals were observed. These data could not be verified by local stakeholders.
Habitat: A combination of existing forested lands and vegetated lands required to maintain connectivity among forest patches. Rather than characterize habitat for a particular local species, we used the approach described by Aurambout
et al. [
6] which generally characterizes habitat requirements for a medium-sized mammal with a specific home range and assumed behaviors.
Future land-use patterns were simulated for a number of scenarios but two are described here. The first scenario assumed that current development patterns and trends would continue into the future. The second scenario assumed that a long sought after wish of the people of McHenry would become true and that, in 2011, a new highway interchange would be constructed in the southwestern corner of the county. Residents of the county complain that theirs is the only county without an interchange on an interstate highway (though there are some just outside the county borders). In addition, the scenario assumes that two new stations would be built that would allow commuter rail (Metra) connections from deeper in the county. We will refer to these two scenarios as the business-as-usual and the enhanced-transportation scenario.
Figure 1 shows land-use patterns simulated for the year 2030 in the business-as-usual scenario. New areas of residential development are shown in yellow, commercial areas in red. The simulation forecasts that the majority of new residential growth will occur in the southeast quadrant of the county, which is not unexpected because downtown Chicago and other job centers lie to the southeast and are connected by commuter rail and federal highways. Growth is also clustered around the small towns in the county and along major transportation routes.
Figure 1.
Summary of land-use change in the business-as-usual scenario. Yellow areas represent new residential development in 2030. Red areas represent new commercial development in 2030.
Figure 1.
Summary of land-use change in the business-as-usual scenario. Yellow areas represent new residential development in 2030. Red areas represent new commercial development in 2030.
Future land-use patterns simulated in the enhanced-transportation scenario indicate more growth around the new interchange and less in other parts. While this might be expected to happen in a general sense, the locations for and extents of these gains and losses relative to business-as-usual is not something that can be intuited.
Figure 2 is a map that depicts these differences. It compares the two scenarios after aggregating the new acreage in each scenario to quarter sections (1/4 mile square). We find that stakeholders can better comprehend differences among scenarios when the information is aggregated to these larger spatial units. Each quarter section is colored based on the difference between the acreage forecasted in the two scenarios. Quarter-sections colored blue see more acres developed in the enhanced-transportation scenario, while those colored red see more acres developed in the business-as-usual scenario. The intensity of the color depicts the magnitude: darker means greater change. The preponderance of blue quarter-sections in the southwest corner of the county in Fig. 3 indicates more acres developed in this location in the enhanced-transportation scenario; the red quarter sections nearby and around the rest of the county indicate greater acres developed in the business-as-usual scenario. The red quarter sections are essentially places where development would have taken place if the transportation improvements had not been made.
Figure 2.
Difference between two scenarios in terms of acreage added in each quarter section. Blue areas have more acreage in the enhanced-transportation scenario, red areas more acreage in the business-as-usual scenario. Darker colors mean greater differences.
Figure 2.
Difference between two scenarios in terms of acreage added in each quarter section. Blue areas have more acreage in the enhanced-transportation scenario, red areas more acreage in the business-as-usual scenario. Darker colors mean greater differences.
Since land-use change is simulated at a fine spatial resolution (i.e., 30 × 30 meters), it can be aggregated to any desired spatial unit—watershed, school district, governmental jurisdiction, natural-area corridor, and traffic analysis zone—and comparisons can be made between scenarios using that unit of spatial analysis.
Figure 3 is a comparison of acres developed in watersheds between the business-as-usual and the enhanced-transportation scenarios. Watersheds close to the new interchange see more development while watersheds elsewhere see less. This suggests that in the future, if the interchange is built, then particular attention will have to be paid to the extent and nature of development in these watersheds.
Figure 3.
Difference between two scenarios in terms of new development in watersheds. Blue areas have more acreage in the enhanced-transportation scenario, red areas more acreage in the business-as-usual scenario.
Figure 3.
Difference between two scenarios in terms of new development in watersheds. Blue areas have more acreage in the enhanced-transportation scenario, red areas more acreage in the business-as-usual scenario.
In general, participants in the process found the resulting land-use change scenarios plausible. Where these scenarios were not plausible, either the simulation was incorrect or participants had to give up closely held beliefs. For instance, development along a major arterial (Illinois Route 47, in the middle of the southern part of the county) was much less than was expected. Input data and model assumptions were scrutinized and it turned out that the traffic associated with this particular road was incorrectly represented and the road was less attractive to development. In another example, several small towns in the vicinity of the proposed new interchange expected to see significant development if the interchange were to be built. The amount and location of new development in the enhanced-transportation scenario was not as much as expected and appeared counter-intuitive to them. As discussions of this apparent error in the simulation evolved among participants, the logic of why this was happening was revealed: development was being drawn to the road directly connected to the new interchange rather than the road on which these towns were located. Given this explanation, participants found it easier to believe in the scenario.
With characterizations of ecosystem services and future land-use patterns in hand, we now assess future impacts on these ecosystem services. Rather than use the simple overlay as we did in the Peoria case above, in McHenry we used the more fine-grained approach described earlier for all except one of the ecosystem services studied. To recap: the development likelihood scores for areas associated with an ecosystem service, which are computed internally within the land-use change model, can be used as a measure of the pressure on these areas to change use. This measure can be used to identify areas that are most under pressure or to understand how the pressure to change varies between scenarios.
4.2.1. Prime farmlands
As discussed earlier, areas with LESA scores above 90 were designated prime farmland. The amount of prime farmland that had high development likelihood scores (the top 25%) was slightly higher (1,400 acres or 567 hectares) in the enhanced-transportation scenario but the location and the configuration of these areas is quite different.
Figure 4 captures the differences between the two scenarios in terms of the development likelihood of prime farmlands. Red areas will be under greater development pressure in the enhanced-transportation scenario, blue areas under greater pressure in the business-as-usual scenario. Not only are the two areas located very differently (red areas are concentrated in the southwest corner; blue areas are spread out over the rest of the county) but the configuration of these is very different: the red areas are consolidated (and thus more valuable) while the blue areas are extremely fragmented.
Figure 4.
Difference between two scenarios in terms of development pressure on prime farmlands. Blue areas will experience greater development pressure in the business-as-usual scenario, red areas will experience greater pressure in the enhanced-transportation scenario.
Figure 4.
Difference between two scenarios in terms of development pressure on prime farmlands. Blue areas will experience greater development pressure in the business-as-usual scenario, red areas will experience greater pressure in the enhanced-transportation scenario.
4.2.2. Wetlands
The area of wetlands that had high development likelihood scores (the top 25%) was slightly lower (380 acres or 154 hectares) in the enhanced-transportation scenario. Building the interchange and the railway stations could reduce the amount of wetlands under threat of development but this difference represents just under 1% of the total area of wetlands in the county. The table in
Figure 5 shows the distribution of the region’s wetlands in four different categories of development pressure; the map shows how the impact will be differentially located in space with red areas under greater development pressure in the enhanced-transportation scenario, while blue areas under greater pressure in the business-as-usual scenario. The impacts of development are concentrated in the southwest corner of the county in the enhanced-transportation scenario.
Figure 5.
Difference between two scenarios in terms of development pressure on wetlands. Blue areas will experience greater development pressure in the business-as-usual scenario, red areas will experience greater pressure in the enhanced-transportation scenario.
Figure 5.
Difference between two scenarios in terms of development pressure on wetlands. Blue areas will experience greater development pressure in the business-as-usual scenario, red areas will experience greater pressure in the enhanced-transportation scenario.
4.2.3. Threatened and endangered species
As seen in
Figure 6, the enhanced-transportation scenario will result in development pressure on 21 of the many quarter-sections where threatened and endangered species have been found. All these areas likely to develop are located in the southwest corner of the county, which is not surprising. None of these areas is under greater development pressure in the business-as-usual scenario.
Figure 6.
Difference between two scenarios in terms of development pressure on areas containing threatened and endangered species. Red areas will experience greater development pressure in the enhanced-transportation scenario.
Figure 6.
Difference between two scenarios in terms of development pressure on areas containing threatened and endangered species. Red areas will experience greater development pressure in the enhanced-transportation scenario.
4.2.4. Habitat
In
Figure 7, the areas shown in pale green were identified as important core and connective habitat using the approach described earlier. Overlaid on these areas is future development as simulated in the business-as-usual scenario and differentiated over time: current development is in light gray and future development is in black. This suggests that future development is likely to eat away at the margins of these habitat areas in some locations. In two locations in the southeastern part of the county, however, significant portions of connective habitat are likely to be destroyed. These impacts are likely to happen later in the simulation time horizon, i.e., closer to the year 2030. There were not significant differences when the enhanced-transportation scenario was overlaid on the habitat areas; a bit more habitat was destroyed around the new interchange, while slightly less destroyed in other parts of the region.
4.2.5. Summary
Our assessment identifies locations across the county where specific ecosystem services are likely to be affected by future urban development. Some of the consequences of knowing this have emerged in conversations with stakeholders. For instance, the current McHenry County conservation ordinance essentially constrains development on most of the land in the county because there was not a basis for being more selective. The information developed in this assessment allows the ordinance to be applied more stringently and at the same time more focused spatially. Also, with the knowledge provided by this assessment, policymakers choosing among policy and investment options can take into consideration areas that will be affected if these options are implemented.
Figure 7.
Sensitive habitat areas and future land-use patterns in the business-as-usual scenario. Green areas are habitat areas. Grey areas depict current and near-term urban development; black areas are development that takes place later in the simulation.
Figure 7.
Sensitive habitat areas and future land-use patterns in the business-as-usual scenario. Green areas are habitat areas. Grey areas depict current and near-term urban development; black areas are development that takes place later in the simulation.
This kind of assessment also allows policy and investment choices to be made with broader sustainability considerations. These choices are usually weighed using very narrow cost-benefit criteria and in the face of appeals to emotions: “We’re the only county in Illinois to not have a highway interchange.” The total acreage of land involved in delivering many ecosystem services is increased only slightly if the highway interchange is built, and doing so will relieve the pressure on critical lands in other parts of the county. On the other hand, as seen above, the areas in the southwest corner of the county that are affected by this public investment are larger and less fragmented than in other parts of the county and are, for that reason, more valuable. Such judgments are possible because stakeholders can see the differential impacts across space; these kinds of ideas had not emerged in any of the regional conversations before this assessment was made available even if some of the conclusions may appear obvious in a general sense. A new interchange is no longer a priority.