Which tree species thrives best on the edge: a comparison of three communities in Steckle Woods, Kitchener-Waterloo, Ontario


This study examined which species can best survive along the edge of a woodlot in Kitchener-Waterloo, ON. Data was collected in 2017, by measuring the distance of trees and saplings from three different sample points in four separate communities of the woodland. Tree Community 1 is along the edge of the forest, Tree Community 2 and 3 respectively are found more towards the centre of the forest, and Tree Community 4 is a pine plantation.

The focus of this experiment is on Tree Community 1. The results showed that a higher relative frequency and density of any species were able to thrive in Tree Community 1 even while facing the edge effect in the ecotone. The findings of this experiment helped to recommend types of tree species to be planted in Tree Community 1. Soil types should be compared between all four communities to further understand the niches within each area, and what factors influences the growth of each species.


Succession is the change of a species’ Tree Community overtime (Faculty of Environment, 2016). This concept is the main focus of this experiment, with the intent of seeing impact on tree species.

The edge effect occurs when two different areas or biomes blend together (Maya Gonzalez, 2010). As they blend, they create an area called an ecotone. An ecotone is the overlapping parts of the two areas (Gorham, 2006).

A woodlot is referred to as a collection of trees which do not meet the qualifications to be classified as a forest (Piermaria Corona, 2011). Steckle Woods is an example of secondary succession, which means that the ecosystem is developing after a partial disturbance within the area (Faculty of Environment, 2016). There are four stages of secondary succession: initial, early secondary forest, late secondary forest, and mature forest (Edith Villa-Galaviz, 2012).

Which tree species thrives best on the edge: a comparison of threecommunities in Steckle Woods, Kitchener-Waterloo

Steckle Woods is an upland woodlot that has been redeveloping since a forest fire in 1805, but the woodlot has existed since before European settlement (Waterloo Region Nature, 2017). The eastern section was bought by the city and surrounds three sides of the Steckle Woods (Faculty of Environment, 2016).

Over the years, the growth of visitors to the woodland has resulted in a negative impact on species growth. It has become a popular hiking area with designated trails that were implemented by the city (MTBR, 2017). With more frequent visitors and development of the surrounding area, there has been negative impact on Steckle Woods as the species are increasingly stressed by external factors, such as pollution and human interactions (Faculty of Environment, 2016).

Through this study, the type of tree species that grows best in different tree communities and the impact of surrounding areas on the forest can be assessed (Selman, 1993). Many species can be found within the woodlot such as: Acer sacchrum (Sugar maple), Ostrya virginiana (Ironwood), Quercus rubra (Red oak), Tilia americana (Basswood), Fraxinus americana (White ash), Rhamnus (Buckthorn), Cornus alternifolia (Alternating dogwood), Prunus serotine (Black cherry), Pinus resinosa (Red pine), Pinus strobus (White pine), and Fagus grandifolia (American beech) (Tree Canada, 2017).

Considering the four tree communities found within the Steckle Woods woodlot in Waterloo, Ontario, this experiment will allow for an understanding on why a certain tree type has better growth success in the area than others.  The results may also provide better insight into the effects of the soil in the area or the effects of the area on tree species.

Every species of tree has a different niche, and resulting requirements, to thrive within a specific area. The edge effect may have an impact on the growth of certain trees in an ecotone, the transitional area of vegetation between two different tree communities, or along the exterior edge of the woodlot due to missing requirements to fill its niche.

If a tree species can successfully thrive on the edge of the woodlot, then a higher relative density and frequency will be observed in tree communities nearest the woodlot edge rather than those found further into the woodlot. A single transect line was examined in four tree communities within the woodlot. The main focus of this study is on the Tree Community closest to the woodlot edge in an attempt to analyze what tree species can successfully survive along the edge and why.

1. Method

1.1 Study Area

The experiment took place at four different tree communities within the Steckle Woods woodlot in Waterloo, Ontario on October 2nd, 2017 at 12:00pm. Tree Community 1 (43°24’28.05″N 80°28’2.26″W) lies along the edge of the woodlot.

Fig 1. 2017 points of study map which shows the locations of each
community studied in the Steckle’s Woods woodlot.

It experiences many of the edge effects such as increased light, higher winds, etc. Deeper into the woodlot is where Tree Community 2 (43°24’25.95″N 80°27’57.29″W) can be found. This Tree Community is the only area where Black Cherry trees are found. Tree Community 3 (43°24’23.00″N 80°27’50.72″W) is similar to Tree Community 2 in that they are both found in the centre of the woodlot.

Tree Community 4 (43°24’20.21″N 80°27’46.61″W) was chosen due to its unique feature of being a pine plantation, which makes it more abundant in coniferous trees. It was important to have diversity in the site selections to ensure a more representative sample size of the woodlot as a whole. By choosing multiple tree communities at different depths of the woodlot, there was a random selection of tree species and soil types available for comparison.

1.2 Materials and Procedures

First, a location that was a good representation of the tree communities was chosen. Once this was decided, a 45m transect line was laid out perpendicular to the path using a measuring tape and compass. (Faculty of Environment, 2016).

Fig. 2 Diagram showing how to arrange the
experiment and track the quadrants where
each sapling and tree is found (Faculty of
Environment, 2016)

Next, a sample point was marked at 5m, 20m, and 35m, and divided into four quadrants (Figure 2) (Faculty of Environment, 2016). In each quadrant, the nearest live sapling and tree (within 25m of the sample point) were identified.

This method was also used in a European experiment, looking at Poland and Switzerland where they sampled, tracked, and identified trees found in 5 plots of land (Jan Wunder, 2008). They defined a sapling with a diameter tape length of 3-10cm and a tree’s diameter at breast height (DBH) was over 10cm. The distance was recorded for each sapling and tree from the sample point. The DBH of each tree using the DBH tape. Using the field guide ‘Trees in Canada’, species were identified and recorded for each tree and sapling.

1.3 Analytical Techniques

All recorded data was compiled into charts using Excel, and then calculations were completed to easily interpret the information. The relative density was calculated using the equation  where . Relative frequency was calculated using the equation


Relative frequency was calculated using the equation

where –

2. Results

After reviewing the relative frequencies (Figure 3) we can easily see many things. Community 1 grows more red oak and ironwood trees, than community 2, but more sugar maples are found in community 1. However, Black cherry, White ash, and American beech trees are only found in one of the three communities, none of which are community 1. This helps us learn about the niches within each community, and why certain species grow where they do.


Fig 3. 2017 Tree Species Comparison of Relative Frequency (%) in Steckle Woods. This graph shows the relative frequency of each tree species found in four neighboring tree communities of the Steckle Woods woodlot (Table 1 in Appendix A).
Fig 4. 2017 Tree Species Comparison of Relative Density (%) in Steckle’s
Woods. This graph shows the relative density of each tree species found
in three separate communities of the Steckle’s Woods woodlot (Table 2
in Appendix A).

The relative frequencies of each tree species (Figure 3), shows that Sugar Maple trees are the most frequent in Tree Community 1, 2, and 3, but are not at all found in Tree Community 4. Black Cherry trees are found in Tree Community 2, but the majority are found in Tree Community 4.

White Ash trees are specific to Tree Community 3 while Red and White Pine trees are specific to Tree Community 4 due to this area being a pine tree plantation. The relative densities of each tree species (Figure 4), appear similar to the frequencies of each tree species except in Tree Community 1. Sugar Maple may have the highest frequency in Tree Community 1, but Ironwood has a slightly higher density.

The density of Red Oak trees and Basswood trees found in Tree Community 1 also diminish, even though they are the second and third most frequent tree species. As for the other three Tree Communities, the most frequent tree species are also the densest.

Tree Community 3 and 4 have specific niches for three particular tree species to grow. This niche does not provide any benefit in studying which tree species is most successful along the edge of the woodlot and why.

Tree Community 1 and 2, however, are more comparable as they both contain Ironwood trees, Red Oak trees, Sugar Maple trees, and Basswood trees. By comparing Tree Community 1 and 2, it is possible to observe similarities that may indicate why the eastern part of the woodlot is more desirable for these particular species of trees to grow. Tree Community 1 does not contain any Black Cherry trees while Tree Community 2 does.

This information could help determine what differences occur between the two Tree Communities that prevents Black Cherry trees from growing along the edge of the woodlot.

3. Discussion

The Sugar Maple tree species has the highest relative frequency by 29%, but the Ironwood tree species has the highest relative density in Tree Community 1 by 3%. Sugar Maples have a higher relative density in Tree Community 2, which indicates that they grow better in that particular area and soil.

This would indicate that while Ironwood trees are not nearly as common as Sugar Maple trees in Tree Community 1, they have a more successful long-term growth rate, making them the best tree species to plant along the edge of the woodlot. Red Oak trees also have a higher relative frequency in Tree Community 1 than all other communities, but at a lower relative density in Tree Community 1.

Although this allows them to be successful in Tree Community 1, they may not grow as big, which may not as beneficial in the long term. Black cherry trees only grow in Tree Community 2, but never in Tree Community 1, which makes them unsuccessful to grow on the edge of the woodlot overall. Black Cherry trees may require a specific type of soil, lighting, or surrounding environment that is only offered in Tree Community 2 and 4.

From the findings of this experiment, there is an increased knowledge regarding the recommended tree species to be planted in Tree Community 1. The city should continue to plant more Ironwood, and occasionally Sugar Maples or Red Oaks. This information could be applied to the broader Waterloo region when choosing which tree species are planted along woodlot edges nearest development areas.

Further research should include considering the soil type found along the edge of the woodlot, how much light is accessible by trees in this area of the woodlot compared to others, or the amount of coverage, which may impact the amount of rainfall that reaches the woodlot floor. This type of research would provide further input regarding the success of certain tree species along the woodlot edge.

Soil type within the area, for example, plays an important role in which tree species can or cannot grow, as each species needs different levels of nitrogen, and phosphorous (O. Nicolitch, 2016). In a similar study, two Amazonian tree communities that were approximately 1400km apart with lowland tropical forests were compared to determine the differences in species growth from one area to another (NIGEL C. A. PITMAN, 2002).

Our experiment compared four communities to determine the differences, but the communities were slightly closer together, measuring approximately 1200km between Tree Community 1 and 4. Another study looked at the chemical build of Ironwood species compared to others to discover what factors lead to contrasts in the growth of this species (David S. Seigler, 2005).

Their study found that Ironwoods are more generalized and can grow in a wider range of locations than many other tree species as a result of their chemical compound and ability to adapt to unique environments. Our experiment conducted for this report did not look at the chemical structure of the species but demonstrates that Ironwoods thrive better in less specific environments than other species.

Our experiment results were confined to a sample of the broader Waterloo woodlot. We used a single transect line at each Tree Community, which raises limitations to our study that may have affected our results. With this in mind, we suggest a future study conduct more transects within the woodlot but on different communities on the edge and interior to further validate results.

Despite the limitations, a better understanding of tree growth when facing the edge effect was still gained. The Ironwood tree species is most successful on the edge of the woodlot, as it has a high density and frequency compared to Ironwoods found in other communities.


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