Low‐density rural home development is the fastest‐growing form of land use in the United States since 1950. This “exurban” development (∼6–25 homes/km2) includes urban fringe development (UFD) on the periphery of cities and rural residential development (RRD) in rural areas attractive in natural amenities. This paper synthesizes current knowledge on the effects of UFD and RRD. We present two case studies and examine the patterns of biodiversity response and the ecological mechanisms that may underlie these responses. We found that many native species have reduced survival and reproduction near homes, and native species richness often drops with increased exurban densities. Exotic species, some human‐adapted native species, and species from early successional stages often increase with exurban development. These relationships are sometimes nonlinear, with sharp thresholds in biodiversity response. These effects may be manifest for several decades following exurban development, so that biodiversity is likely still responding to the wave of exurban expansion that has occurred since 1950. The location of exurban development is often nonrandom relative to biodiversity because both are influenced by biophysical factors. Consequently, the effects on biodiversity may be disproportionately large relative to the area of exurban development. RRD is more likely than UFD to occur near public lands; hence it may have a larger influence on nature reserves and wilderness species. The ecological mechanisms that may underlie these responses involve alteration of habitat, ecological processes, biotic interactions, and increased human disturbance. Research on the patterns and mechanisms of biodiversity remains underdeveloped, and comparative and experimental studies are needed. Knowledge resulting from such studies will increase our ability to understand, manage, and mitigate negative impacts on biodiversity.

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Land use is rapidly expanding in the Greater Yellowstone Ecosystem, primarily from growth in the number of rural homes. There is a need to project possible future land use and assess impacts on nature reserves as a guide to future management. We assessed the potential biodiversity impacts of alternative future land use scenarios in the Greater Yellowstone Ecosystem. An existing regression-based simulation model was used to project three alternative scenarios of future rural home development. The spatial patterns of forecasted development were then compared to several biodiversity response variables that included cover types, species habitats, and biodiversity indices. We identified the four biodiversity responses most at risk of exurban development, designed growth management policies to protect these areas, and tested their effectiveness in two alternative future scenarios. We found that the measured biodiversity responses, including riparian habitat, elk winter range, migration corridors, and eight other land cover, habitat, and biodiversity indices, are likely to undergo substantial conversion (between 5% and 40%) to exurban development by 2020. Future habitat conversion to exurban development outside the region's nature reserves is likely to impact wildlife populations within the reserves. Existing growth management policies will provide minimal protection to biodiversity in this region. We identified specific growth management policies, including incentives to cluster future growth near towns, that can protect "at risk" habitat types without limiting overall growth in housing.

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This paper uses wildfires in the Sierra Nevada area of California to estimate the relationship between housing and fire suppression costs. We investigated whether the presence of homes was associated with increased costs of firefighting after controlling for the effects of potential confounding variables including fire size, weather, terrain and human factors such as road access. This paper investigates wildfires in a way that other published studies have not; we analysed costs at the daily level, retaining information that would have been lost had we aggregated the data. We used linear mixed models to estimate the effects of homes on daily costs while incorporating within-fire variation. We conclude that the expected increase in the log daily cost with each unit increase in the log count of homes within 6 miles (~9.7 km) of an active fire is 0.07 (P = 0.005). The findings of this study are in agreement with most other previous empirical studies that have investigated the relationship between fire suppression costs and housing using cumulative fire costs and more generalised data on home locations. The study adds to mounting evidence that increases in housing lead to increases in fire suppression costs.