Street trees provide important ecosystem services, yet town managers and residents may have little to no knowledge of what is planted in their towns and therefore no idea of the services being provided. In New Jersey, the state Forest Service Community Forestry Program provides support to local governments and shade tree commissions to inventory their street trees with the goal of providing a data base that can be used to e.g. identify potential hazard trees, potential insect or disease problems, and potential areas for planting. A pilot project was designed to assess the feasibility of conducting a street tree inventory involving student researchers. Funding support was provided by the PSEG Institute for Sustainability Studies at Montclair State University, Montclair, NJ.
The sampling design was semi-random and centered around 2 main streets and all of the side streets associated with those main streets. A team of three students under supervision of a faculty member and a graduate student with experience in GIS surveyed each street tree for species, height, crown length, crown health, and general location (street or yard). For each tree a GPS location was recorded and a picture was taken. Once the data were collected, they were entered into a GIS data base.
Results/Conclusions
The final product was an interactive map showing the location of each tree surveyed on a street map of the town. Each tree was coded by color and circle size to indicate crown health and size respectively. Each circle has an active link that presents an information box showing the collected data for the tree. While this project was intended to work out the procedures for conducting a larger scale inventory, the ultimate goal is to be able to present to the residents of Montclair, NJ an interactive map of the street trees. Given the current threat of Emerald Ash Borer and its certified presence in the town, these data will also be usable to the town arborist to determine removal and treatment regimes for the ash trees that are present based on size, health, and location.