Understanding interactions between urban development policies and GHG emissions: A case study in Stockholm Region

Human-induced urban growth and sprawl have implications for greenhouse gas (GHG) emissions that may not be included in conventional GHG accounting methods. Improved understanding of this issue requires use of interactive, spatial-explicit social–ecological systems modeling. This paper develops a comprehensive approach to modeling GHG emissions from urban developments, considering Stockholm County, Sweden as a case study. GHG projections to 2040 with a social–ecological system model yield overall greater emissions than simple extrapolations in official climate action planning. The most pronounced difference in emissions (39% higher) from energy use single-residence buildings resulting from urban sprawl. And this difference is not accounted for in the simple extrapolations. Scenario results indicate that a zoning policy, restricting urban development in certain areas, can mitigate 72% of the total emission effects of the model-projected urban sprawl. The study outcomes include a decision support interface for communicating results and policy implications with policymakers.

     

A Spatial Model to Estimate Habitat Fragmentation and Its Consequences on Long-Term Persistence of Animal Populations

The increasing use of the landscape by humans has led to important diminutions of natural surfaces. The remaining patches of wild habitat are small and isolated from each other among a matrix of inhospitable land-uses. This habitat fragmentation, by disabling population movements and stopping their spread to new habitats, is a major threat to the survival of numerous plant and animal species. We developed a general model, adaptable for specific species, capable of identifying suitable habitat patches within fragmented landscapes and investigating the capacity of populations to move between these patches. This approach combines GIS analysis of a landscape, with spatial dynamic modeling. Suitable habitat is identified using a threshold area to perimeter ratio. Potential movement pathways of species between habitat patches are modeled using a cellular automaton. Habitat connectivity is estimated by overlaying habitat patches with movement pathways. The maximum potential population is calculated within and between connected habitat patches and potential risk of inbreeding within meta-populations is considered. The model was tested on a sample map and applied to scenario maps of predicted land-use change in the Peoria Tri-county region (IL). It (1) showed area of natural area alone was insufficient to estimate the consequences on animal populations; (2) underscored the necessity to use approaches investigating the effect of land-use change spatially through the landscape and the importance of considering species-specific life history characteristics; and (3) highlighted the model's potential utility as an indicator of species likelihood to be affected negatively by land-use scenarios and therefore requiring detailed investigation.     

Long-Term Impacts of Land-Use Change on Non-Point Source Pollutant Loads for the St. Louis Metropolitan Area, USA

A land-use-change simulation model (LEAM) and a non-point-source (NPS) water quality model (L-THIA) were closely coupled as LEAMwq in order to determine the long-term implications of various degree of urbanization on NPS total nitrogen (TN), total suspended particles (TSP), and total phosphorus (TP) loads. A future land-use projection in the St. Louis metropolitan area from 2005 to 2030 using three economic growth scenarios (base, low, and high) and a long-term precipitation dataset were used to predict the mean annual surface runoff and mean annual NPS pollutant loads in the region. Results show mean annual TN increases of 0.21%, 0.13%, and 0.14% by 2030 compared to 2000 under the base, high, and low scenarios, respectively. TSP and TP showed similar trends with different magnitudes. Corresponding changes in annual mean surface runoff were shown to be lower than expected, which might be attributed to the small-scale conversion pattern of land uses. In the most dramatic change (high growth) scenario, the runoff would increase across time but at varying rates, and temporal pollutant loads would result in a more complicated pattern than in the other scenarios. This is attributed to the complex interactions between event mean concentrations of pollutants and the magnitude of changes in land-use acreages. By integrating L-THIA with LEAM, LEAMwq was found to be a useful planning tool to illustrate in a quick and simple manner how future water quality is connected to decision-making on future land-use change.     

A dynamic model of the spatial spread of an infectious disease: the case of fox rabies in Illinois

A spatially explicit computer model is developed to examine the dynamic spread of fox rabies across the state of Illinois and to evaluate possible disease control strategies. The ultimate concern is that the disease will spread from foxes to humans through the pet population. Modeling the population dynamics of rabies in foxes requires comprehensive ecological and biological knowledge of the fox and pathogenesis of the rabies virus. Variables considered including population densities, fox biology, home ranges, dispersal rates, contact rates, and incubation periods, can greatly effect the spread of disease. Accurate reporting of these variables is paramount for realistic construction of a spatial model. The spatial modeling technique utilized is a grid-based approach that combines the relevant geographic condition of the Illinois landscape (typically described in a georeferenced database system) with a nonlinear dynamic model of the phenomena of interest in each cell, interactively connected to the other appropriate cells (usually adjacent ones). The resulting spatial model graphically links data obtained from previous models, fox biology, rabies information and landscape parameters using various hierarchical scales and makes it possible to follow the emergent patterns and facilitates experimental stimulus/result data collection techniques. Results of the model indicate that the disease would likely spread among the native healthy fox population from East to West and would occur in epidemiological waves radiating from the point of introduction; becoming endemic across the State in about 15 years. Findings also include the realization that while current hunting pressures can potentially wipe out the fox in the State, some level of hunting pressure can be effectively utilized to help control the disease. This revised version was published online in July 2006 with corrections to the Cover Date.     

Assessing hydrological impact of potential land use change through hydrological and land use change modeling for the Kishwaukee River basin (USA)

We connected a cellular, dynamic, spatial urban growth model and a semi-distributed continuous hydrology model to quantitatively predict streamflow in response to possible future urban growth at a basin scale. The main goal was to demonstrate the utility of the approach for informing public planning policy and investment choices. The Hydrological Simulation Program-Fortran (HSPF) was set up and calibrated for the Kishwaukee River basin in the Midwestern USA and was repeatedly run with various land use scenarios generated either by the urban growth model (LEAMluc) or hypothetically. The results indicate that (1) the land use scenarios generated by LEAMluc result in little changes in total runoff but some noticeable changes in surface flow; (2) the argument that low flows tend to decrease with more urbanized areas in a basin was confirmed in this study but the selection of indicators for low flows can result in misleading conclusions; (3) dynamic simulation modeling by connecting a distributed land use change model and a semi-distributed hydrological model can be a good decision support tool demanding reasonable amount of efforts and capable of long-term scenario-based assessments.