Valuing the benefits of the urban forest: a spatial hedonic approach

This paper measures the benefits of the urban forest by examining its effect on housing prices. A Geographic Information System is used to develop a measure of the urban forest, the Normalised Difference Vegetation Index, from satellite imagery and to construct other variables from a variety of sources. Spatial hedonic housing price models for the Indianapolis/Marion County area are estimated. The models indicate that greener vegetation around a property has a positive, significant effect on housing price, holding everything else constant. This effect is dominated by measures at the neighborhood level. These findings indicate that property owners value the urban forest, at least in part, by the premium they pay to live in neighborhoods with greener, denser vegetation. These findings also indicate that public action to maintain and enhance the urban forest may be warranted. Planners and urban foresters can use these findings to inform public and policy debates over urban forestry programs and proposals.     

An Aquifer Vulnerability Assessment of the Paluxy Aquifer, Central Texas, USA, Using GIS and a Modified DRASTIC Approach

D epth to water, net Recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, and Conductivity of the aquifer). Using such an approach allows one to investigate the potential for groundwater contamination on a regional, rather than site-specific, scale. Based upon data from variables such as soil permeability, depth to water, aquifer hydraulic conductivity, and topography, subjective numerical weightings have been assigned according to the variable's relative importance in regional groundwater quality. The weights for each variable comprise a GIS map layer. These map layers are combined to formulate the final groundwater pollution potential map. Using this method of investigation, the pollution potential map for the study area classifies 47% of the area as having low pollution potential, 26% as having moderate pollution potential, 22% as having high pollution potential, and 5% as having very high pollution potential.     

Forecasting relative impacts of land use on anadromous fish habitat to guide conservation planning.

Land use change can adversely affect water quality and freshwater ecosystems, yet our ability to predict how systems will respond to different land uses, particularly rural-residential development, is limited by data availability and our understanding of biophysical thresholds. In this study, we use spatially explicit parcel-level data to examine the influence of land use (including urban, rural-residential, and vineyard) on salmon spawning substrate quality in tributaries of the Russian River in California. We develop a land use change model to forecast the probability of losses in high-quality spawning habitat and recommend priority areas for incentive-based land conservation efforts. Ordinal logistic regression results indicate that all three land use types were negatively associated with spawning substrate quality, with urban development having the largest marginal impact. For two reasons, however, forecasted rural-residential and vineyard development have much larger influences on decreasing spawning substrate quality relative to urban development. First, the land use change model estimates 10 times greater land use conversion to both rural-residential and vineyard compared to urban. Second, forecasted urban development is concentrated in the most developed watersheds, which already have poor spawning substrate quality, such that the marginal response to future urban development is less significant. To meet the goals of protecting salmonid spawning habitat and optimizing investments in salmon recovery, we suggest investing in watersheds where future rural-residential development and vineyards threaten high-quality fish habitat, rather than the most developed watersheds, where land values are higher.     

Effects of roof and rainwater characteristics on copper concentrations in roof runoff

Copper sheeting is a common roofing material used in many parts of the world. However, copper dissolved from roof sheeting represents a source of copper ions to watersheds. Researchers have studied and recently developed a simple and efficient model to predict copper runoff rates. Important input parameters include precipitation amount, rain pH, and roof angle. We hypothesized that the length of a roof also positively correlates with copper concentration (thus, runoff rates) on the basis that runoff concentrations should positively correlate with contact time between acidic rain and the copper sheet. In this study, a novel system was designed to test and model the effects of roof length (length of roof from crown to the drip edge) on runoff copper concentrations relative to rain pH and roof angle. The system consisted of a flat-bottom copper trough mounted on an apparatus that allowed run length and slope to be varied. Water of known chemistry was trickled down the trough at a constant rate and sampled at the bottom. Consistent with other studies, as pH of the synthetic rainwater decreased, runoff copper concentrations increased. At all pH values tested, these results indicated that run length was more important in explaining variability in copper concentrations than was the roof slope. The regression equation with log-transformed data (R ² = 0.873) accounted for slightly more variability than the equation with untransformed data (R ² = 0.834). In log-transformed data, roof angle was not significant in predicting copper concentrations.     

Exploring barriers to home gardening in Ohio households

Scholars have noted that race and ethnicity, socio-economic status (SES) as well as other socio-demographic factors may limit participation in local food systems based on the historic and structured patterns of inequalities that remain in communities promoting alternative agriculture and food (agrifood) activities. However, few empirical studies have examined the barriers which prevent people from participating in local food system activities. This paper uses survey data from the 2008 Ohio Survey of Food, Agriculture and Environmental Issues to consider whether barriers such as interest, time, financial resources, geography and space impact the participation of households in home gardening. Results from logistic regression show that SES, the availability of space and housing type are important factors which limit or enable household participation in home gardening. This paper contributes to our understanding of the barriers that prevent households from participating in home gardening, a form of food system localisation that, while a potentially powerful way to transform the agrifood system, has been underexamined in its own right.