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Wednesday, April 11 • 2:00pm - 2:15pm
SYMPOSIA-15: Integration of Landscape and Social Factors That Predict Attitudes Toward Roadside Vegetation Management

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AUTHORS: Daniel Hale*, Anita T. Morzillo – University of Connecticut

ABSTRACT: Trimming or removing trees near roadside power lines is necessary to prevent power outages, but often leads to dissention among residents. Roadside vegetation management is part of a complex social-ecological decision-making system that takes place across all types of land use, and from urban to rural areas. However, little knowledge exists about resident attitudes toward vegetation management. Our objective is to understand the social and landscape factors that influence attitudes toward roadside vegetation management. Surveys were mailed to Connecticut residents in two study areas that range across urban-to-rural gradients. Survey data and other landscape factors (e.g., tree cover) were mapped and quantified at various scales. We used the machine-learning algorithm random forest to evaluate how attitudes toward vegetation management were influenced by social and landscape variables. Results suggest that the majority of respondents were favorable for the perception that those who do vegetation management are accountable, contribute to greater public safety, and minimize power outages. Respondents indicate a perception that vegetation management for reliable power is of great importance. These attitudes are influenced by social factors such as willingness to allow changes to roadside trees, prioritization of reduced outages, knowledge about trees, and patterns of basic beliefs about the environment. Results also suggest that although demographic variables vary according to urban and rural places, attitudes toward vegetation management may not be strongly predicted by landscape factors. This research offers insights on the complex factors linked with attitudes toward trees and their management across the heterogeneous landscape.

Wednesday April 11, 2018 2:00pm - 2:15pm CDT
Spire Parlor