Interpolating resident attitudes toward exurban roadside forest management

Abstract

Knowledge about spatial patterns of human dimensions data within landscape ecology is nascent despite its importance in natural resources management. We explored this topic within the context of utility roadside forest management, a complex situation involving ecological, cultural, and aesthetic aspects of forests and reliable power. We applied spatial interpolation to investigate patterns of human attitudes toward roadside vegetation management data across an exurban landscape. Mail surveys (n = 1962) were used to collect social science data from residents in four areas of Connecticut, USA. For each area, three attitudes variables were evaluated for spatial autocorrelation using Moran’s I statistic. Based on identified autocorrelation distance or scale, attitudes were interpolated using inverse distance weighting. Model validation of interpolated surfaces was completed using root mean square error. Significant spatial autocorrelation was present for five of 12 study area-attitude pairings (one focused on professionalism; two focused on safety; three focused on tradeoffs between reliable power and maintaining trees) at distances ranging from 200 to 2400 m. Accuracy of interpolations varied among study areas, suggesting that the choice of spatial scale of analysis influenced model results. Social processes influencing attitudes were spatially heterogeneous, existing at disparate scales for the same variables in different locations. Collectively, “enough” roadside forest may exist to ameliorate intermittent vegetation management aesthetically, yet underlying social processes influencing roadside forest outcomes likely are not mutually exclusive. Interpolation assumptions often applied toward ecological studies did not work well for social processes studied in this analysis.