Sustainable Urban Forestry Planning Models and Decision Making Dashboard

2017 | Richard Hauer, PhD, University of Wisconsin – Stevens Point 

Currently no easy to use model(s) and interactive dashboard exists for urban foresters to monitor urban forest programs effectively and efficiently and to implement findings into decision making. This project will create an easy to use approach to evaluate and track progress within urban forestry programs. Ultimately this will help communities identify programmatic areas to improve and lead to a sustainable urban forest program and tree population. An important foundation for this project comes from our knowledge of the approaches that 667 municipal urban forestry programs use to manage their urban forests (see http://www.uwsp.edu/cnr/Pages/Forestry—MTCUS.aspx). That study was initially created to develop a baseline status of urban forestry programs. We will identify which attributes are most important to evaluate program capacity. This outcome will then lead into the urban forestry dashboard system that allows an urban forest manager to visually evaluate how their municipal urban forestry program compares to internal goals and other comparable programs. A dashboard is a common way to present and evaluate important information, much like a car instrument panel (e.g., oil, temperature, RPM, speed) or medical health (e.g., blood treasure, cholesterol). Thus, communities will be able to assess their own urban forestry capacity and performance with a customized urban forestry sustainability index integrated as part of a planning tool. The anticipated outcome of this work will help urban forest planners create a story of the current state of their urban forestry program and envision how planned changes will impact their program’s sustainability index.

Publications:

Hauer, R. J., N. Timilsina, J. Vogt, B. C. Fischer, Z. Wirtz, W. Peterson. “A Volunteer and Partnership Baseline for Municipal Forestry Activity in the United States.” Arboriculture & Urban Forestry 44, no. 2 (2018): 87–100.