Learn More About Urban Street Trees in the BIA

Curious how many urban street trees are in your area?

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Contents

Introduction

An urban street tree (UST) is any street facing tree which, collectively, make up a significant layer of an urban forest (UF). The St. Catharines UF is a lot closer to home than you may think. The City of St. Catharines describes an UF as “…the collection of trees and shrubs that are growing within a city. It may contain any kind of woody plant vegetation growing in or around our homes”. Nurturing the UF requires a great deal of care, planning and maintenance. When we invest in trees, and other natural infrastructure, we invest in a Nature-based Solution (NbS) that is proven to build community health & resilience and mitigate various climate change impacts (e.g., heat island effect, flooding, desertification, etc.).

USTs provide a range of benefits & opportunities for the St. Catharines Downtown BIA. Trees are important to the Downtown as they provide much needed shade and beautification & act as important infrastructure (known as green infrastructure). This helps encourage people to stay longer and also enhances the overall experience of being Downtown, increasing the likelihood of return visitors while improving liveability. USTs are a crucial natural asset for the City of St. Catharines, residents, businesses, and everyone else who calls the Garden City home. 

Project Background

The tree inventory began with one simple question: how can we bring more trees downtown?

This led to a tree inventory under the direction of the St. Catharines Downtown Association’s
(SCDA) Executive Director, Rachel Braithwaite. Through an internship opportunity with Niagara College’s Environmental Management & Assessment Program, two interns, Aditi Kerawala & Sean Parkinson, were selected to conduct an inventory of the BIA, including an inventory of the existing tree infrastructure. This inventorying process and initial research question was supported by discussions with the SCDA’S Streetscape & Sustainability Committee, comprised of local business owners, community leaders, and the SCDA staff. Around the same time, a motion was put forward by Councillor Kevin Townsend, to plant 100,000 trees over the next 10 years (e.g., average of 10,000/year).

In March of 2022, Lindsay Taylor, Niagara College alumni, was hired as a summer Sustainability Coordinator for the SCDA to expand this research and draft a Tree Report. Working alongside fellow summer Sustainability & Events Coordinator, Sean Parkinson, Taylor drafted a sampling & analysis plan that would enhance the existing tree surveying data and provide a sustainability evaluation of the UST academic literature and popular press (see methodology below). Two new SCDA interns, Poonam Gautam and Lina Garcia, were brought on board to assist with the field surveying and data management.

During this process, the team found that the majority of the USTs downtown were younger, smaller trees. Trees begin providing the community value when they reach a large size and have a dense canopy.

The research question needed to change: how can we ensure that USTs reach maturity?

Tree Report

Recommendations

Throughout the research process, various stakeholders from the SCDA’s Streetscape & Sustainability Committee, City of St. Catharines, Niagara Region, Niagara College, Downtown Guelph Business Association and Waterloo’s Asset Management Team provided guidance and feedback on the direction of the following recommendations. Click each icon to learn more!

Data Summary

Mapping

The following maps were made using QGIS – A Free and Open Source Geographic Information System.

Methodology

Field sampling took place every Wednesday from May 18th, 2022, to June 22nd, 2022. This work was conducted by two SCDA interns, Poonam Gautam & Lina Garcia. For each UST within the BIA, the interns would record:

Georeference Tree Species Diameter at Breast Height (cm) Health Assessment

The georeference was recorded in UTM (Projection NAD83 17N) using the UTM/Lat-Lon Android App. To identify the tree species the interns were provided an introductory module on tree identification, introduced to various tree ID apps including iNaturalist and Seek, and relied on John Laird Farrar’s “Trees in Canada” ID book. DBH (cm) was recorded using a DBH measuring tape provided by Trish Haynes through Niagara College’s Environmental Labs. To complete the tree health assessment, the interns assessed 5 qualitative markers including:

Bark Wounds: visible damage to trunk of tree Codominance: trunk splits into two   Unbalanced Canopy: canopy is lopsided   Dead Branches: branches without foliage   No Annual Growth: branches show no signs of annual growth

Note: Health Assessment is for reference purposes only. A health assessment should be completed by a certified arborist.

When 4 of 5 markers were present, the tree was deemed a ‘Hazard Tree’. Field sheets were digitised using Excel and stored on the SCDA Google Drive. Further data analyses would include the use of Excel for an in-house statistical analysis & i-Tree for a multi-parameter value assessment.

The in-house analysis focused on classing the trees into four intervals:

Class I: Under 10 cm Class II: 10 cm to Under 25 cm Class III: 25 cm to Under 50 cm Class IV: Greater than 50 cm

These intervals, alongside other general statistics & i-Tree data, were used to establish a baseline for the BIA. This information was then compared to Guelph’s BIA through a benchmarking exercise.

Size Class Intervals

Saplings = Class I (Under 10 cm) Young Trees= Class II (10 cm to Under 25 cm) Adult Mature Trees = Class III (25 cm to Under 50 cm) Large Mature Trees = Class IV (Greater than 50 cm)

Class Intervals	2016 Frequency	2022 Frequency	Change from 2016 to 2022
Class I (10 cm and under)	76	95	+ 19
Class II (10 to under 25 cm)	104	83	– 21
Class III (25 to under 50 cm)	53	72	+ 19
Class IV (50 cm and greater)	9	6	– 3

Key Values & Statistics

6.2 cm was the DBH most often recorded in 2022 (i.e., the mode). There is also a low population variance & standard deviation and a left-skewed distribution. These indicators, combined with the data range, describe the UST population as predominantly young trees (e.g., Class I, lower Class II) with fewer making it to maturity (e.g., Class III & Class IV).

Tree Report