Lakeshore Zoning has Heterogeneous Ecological Effects: An Application of a Coupled Economic-Ecological Model
Housing growth has been widely shown to be negatively correlated with wildlife populations, avian richness, anadromous fish, and exotic invasion. Zoning is the most frequently used public policy to manage housing development and is often motivated by a desire to protect the environment. Zoning is also pervasive, taking place in all 50 states. One relevant question that has received little research concerns the effectiveness of zoning to meet ecological goals. In this paper, we examined whether minimum frontage zoning policies have made a positive impact on the lakes they were aimed to protect in Vilas County, Wisconsin, USA. We used an economic model that estimated when a given lot will be subdivided and how many new lots will be created as a function of zoning. Using the economic model, we simulated the effects of multiple zoning scenarios on lakeshore development. The simulated development patterns were then input to ecological models that predicted the amount of coarse woody debris (CWD) and the growth rate of bluegills as a function of residential density. Comparison of the ecological outcomes under different simulated zoning scenarios quantified the effect of zoning policies on residential density, CWD, and bluegill growth rates. Our results showed that zoning significantly affected residential density, CWD counts, and bluegill growth rates across our study area, although the effect was less clear at the scale of individual lake. Our results suggest that homogeneous zoning (i.e., for a county) is likely to have mixed results when applied to a heterogeneous landscape. Further, our results suggest that zoning regimes with a higher minimum shoreline frontage are likely to have larger ecological effects when applied to lakes that are less developed.
Van Butsic, David J. Lewis, and Volker C. Radeloff 2010. Lakeshore zoning has heterogeneous ecological effects: an application of a coupled economic-ecological model. Ecological Applications 20:867–879. http://dx.doi.org/10.1890/09-0722.1