thesis report for region

Effects of Urban Development on Vegetation Communities at the Edges of Regional Woodlands

William Van Hemessen

Candidate for Master of Environmental Studies School of Planning, University of Waterloo

May, 2013

Effects of Urban Development on Vegetation Communities at the Edges of Regional Woodlands – William Van Hemessen

Table of Contents

EXECUTIVE SUMMARY 2

1.0 INTRODUCTION 3

1.1 Background 3

1.2 Policy Context 5

1.3 Focus of this Study 7

2.0 METHODOLOGY 9

2.1 Research Design and Site Selection 9

2.2 Data Collection 12

2.3 Data Analysis 14

3.0 RESULTS 16

3.1 Edge effects observed in Regional woodlands 16

3.2 Overview of Statistical Results 17

3.3 Effects of urbanization are highly variable from habitat to habitat 18

3.4 Effects of adjacent land use type 19

3.5 Edge effects and time since urban development 22

3.6 Effects of edge treatment 25

4.0 IMPLICATIONS 27

4.1 Relevance to municipal policy 27

5.0 CONCLUSIONS 32

5.1 Summary 32

5.2 Limitations and Further Research 33

REFERENCES 34

APPENDIX A – Descriptions of Study Sites 37

LIST OF TABLES

Table 1 Number of edge segments adjacent to each land use type in the Region 9

Table 2 List of sampling locations 12

Table 3 List of vegetation community metrics (dependent variables) included in the analysis 14

Table 4 List of land use variables included in the analysis 14

Table 5 List of other variables included in the analysis 15

Table 6 Mean biodiversity values at 1m and 20m from the woodland edge 16

Table 7 Results of generalized linear models run for each biodiversity variable 17

Table 8 Effects of Site ID on the biodiversity metrics studied 18

Table 9 Mean biodiversity values for each woodland surveyed 19

Table 10 Effects of adjacent land use type on the biodiversity metrics studied 20

Table 11 Effects of adjacent land use age on the biodiversity metrics studied 22

Table 12 Effects of edge treatment on the biodiversity metrics studied 25


LIST OF FIGURES

Figure 1 Map of woodland habitat fragments in Waterloo, Kitchener and Cambridge 10

Figure 2 The vegetation survey protocol used for this study 13

Figure 3 Examples of different land use categories 15

Figure 4 Mean non-native species proportion at 1m from the woodland edge for transects adjacent to different land use types

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Figure 5 Mean floristic quality at 1m from the woodland edge for transects adjacent to different land use types

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Figure 6 Mean Sorensen Index for transects adjacent to land uses of different ages 23

Figure 7 Mean non-native species proportion at 1m from the edge for transects adjacent to land uses of different ages

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Figure 8 Mean floristic quality at 1m from the edge for transects adjacent to land uses of different ages

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Figure 9 Mean Sorensen Index for transects adjacent to different edge treatments 25


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Acknowledgements

Funding for this project was provided in part by the Region of Waterloo as part of the Community Environmental Fund. Funding was also provided by the Province of Ontario and the University of Waterloo. Research was conducted under the supervision of Dr. Michael Drescher at the University of Waterloo. Dr. Paul Eagles also provided useful guidance during the course of this project. I would also like to acknowledge the assistance of my contact at the Region, Chris Gosselin.


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Executive Summary

This report summarizes the findings of a research project conducted by a graduate student in the School of Planning at the University of Waterloo. The project aimed to explore how human land use characteristics affected understory vegetation diversity at the edges of woodland habitat fragments.

The edges of woodland habitat fragments in the cities of Waterloo, Kitchener and Cambridge were surveyed. All

of these habitats were Core Environmental Features in the Region’s Greenlands Network according to Map 4 of the 2010 Regional Official Plan (ROP). Fifteen edge segments were surveyed in seven different woodlands. Urban land uses adjacent to each edge segment were characterized. The effects of adjacent land use characteristics on vegetation diversity were then explored.

RESULTS & RECOMMENDATIONS

Woodland habitat fragments in the Region exhibit edge effects consistent with other ecosystems worldwide that

have experienced urbanization. Vegetation communities at the edge differ significantly from those in the interior: edges have higher species richness, greater prevalence of non-native species and lower floristic quality.

The most important factor determining the state of vegetation communities at woodland edges is the inherent

state of the woodland itself. This means that the effects of land use change on edge vegetation depend largely on the existing conditions in a given habitat. Therefore, a case-by-case approach to habitat conservation is recommended. The policies in the Regional Official Plan and the Greenlands Network Implementation Guideline requiring Environmental Impact Statements to be submitted for development proposals near environmental features more than satisfy this recommendation.

The type of land use adjacent to a woodland significantly affects the prevalence of non-native species and the

floristic quality at the edge. Low-density residential land uses are associated with an increased prevalence of non-native species but also with higher floristic quality, while industrial and commercial land uses are associated with a lower prevalence of non-native species and lower floristic quality. Policies which encourage the use of native species for landscaping and gardening would mitigate the introduction of non-native species and ameliorate floristic quality in woodlands adjacent to all land use types. These recommendations are partially satisfied by policies in the Greenlands Network Implementation Guideline.

It is uncertain whether edge treatment (buffer zone, fence or no treatment) has any significant effect on

understory vegetation communities. Results suggest that buffer zones have little impact on species richness, non-native species prevalence, or floristic quality at the edge. Nonetheless, it is clear that buffer zones do help mitigate impacts on many other ecological functions aside from vegetation communities.

Results also suggest that vegetation communities recover over time after urban development. Vegetation

communities at woodland edges exhibited greater change within 20 years of development than within 40 years or beyond 40 years. It appears that woodland edges experience a large initial disturbance after development occurs, but edge communities approach a state similar to the habitat interior over time. To mitigate initial disturbance, and to promote the recovery of edge vegetation communities, policies that minimize the impacts of construction activities on natural habitats should be maintained or enhanced. Developers and landowners should also be encouraged to use native species in landscaping and gardening activities.


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1.0 Introduction

1.1 Background

This research was conducted as part of a graduate research project in the School of Planning at the University of Waterloo. As the project was funded in part by the Region of Waterloo’s Community Environmental Fund, it was agreed that this report would be prepared and submitted to the municipality following the completion of data analysis. This report outlines the research conducted, highlights the most important results and offers interpretations of the data relevant to land use planning in the Region.

The Region of Waterloo is a highly urbanized part of Ontario. Roughly 84 percent of the population lives in urban

areas (Statistics Canada, 2013). The Region is also rapidly growing, projected to reach 712,000 residents by 2029 with an annual growth rate of 1.7 percent (Region of Waterloo, 2006a; 2009). Almost all of this population growth will occur in the cities of Kitchener, Waterloo and Cambridge, and new developments will be built to accommodate this increase. Although the Region has a proactive approach to growth management, outward physical expansion of the Region’s urban areas is almost certain to continue for the foreseeable future.

The likelihood of continued urbanization at the Region’s urban peripheries means that many fragments of

natural habitat will soon have urban land uses occurring at their edges. Urbanization remains, arguably, the single most important force of environmental change in the Region. Woodlands are a particularly vulnerable resource considering that currently 19 percent of the Grand River watershed is covered by forests and the Conservation Authority maintains targets of 30 percent forest cover for the Grand watershed and 15 percent for each sub-watershed (Grand River Conservation Authority, 2004). Conservation and expansion of forests—and other natural habitats—in the Region is therefore a conservation priority which is reflected in Regional planning policies (see Section 1.2).

Conservation of urban woodlands is challenging because these ecosystems inevitably endure a larger number of

environmental stressors than non-urban woodlands. Environmental changes related to urbanization include: habitat fragmentation and isolation, alterations to hydrological and biogeochemical regimes, microclimate generation, recreational use by humans, biological invasions and pressures associated with human activities adjacent to forests. Organisms react to these forces in vastly different ways. Some species thrive while others decline. Therefore, the species assemblages observed in a habitat offer a snapshot of the selective pressures that have impacted that ecosystem (Shipley, 2010). By studying species assemblages, ecologists can learn about the sources, intensities and types of stressors affecting a habitat.

This study set out to survey species assemblages in Regional woodlands in order to explore the effects of human

land use characteristics on those ecosystems. Specifically, this study focused on species assembly at woodland edges. Woodland edges are important because they exhibit edge effects: changes in biodiversity and environmental conditions that are caused by the pressures of adjacent land uses (Laurance & Yensen, 1991). Edge effects arise when environmental change occurs at the edge of a habitat and puts selective pressure on the organisms that live there. Organisms that unable to tolerate these new conditions die off, while others thrive. Frequently, new organisms are introduced that are more tolerant of new conditions and, in many cases, behave invasively. Edge effects, in summary, reflect a complex system of species selection and introduction that produce unique species assemblages at the habitat edge.

The premise of this study is that habitat edges with more intense edge effects are less healthy. Edge effects were

quantified using four biodiversity variables (see Section 2.1). Woodland edges adjacent to different human land uses were observed in order to explore whether certain land use characteristics had more of an impact on woodland ecosystems. Research by other authors suggests that some edge characteristics, particularly the prevalence of


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invasive non-native species, is affected by the type of human land use occurring adjacent to the habitat (Moran, 1984; Cutway & Ehrenfeld, 2009). The effect of different edge treatments—protective measures such as fences and buffer zones dividing natural habitats from urban developments—was also examined. Current municipal regulations require buffer zones between natural habitats and urban developments (see Section 1.2), but there is little evidence of whether they are effective at mitigating various adverse impacts on ecosystems. This study sought to determine their efficacy. The final factor that was analyzed was the time period in which the adjacent land use was developed.

If different land use types, ages and edge treatments affect woodland edges differently, it suggests that the

impacts of urbanization can be mitigated through land use planning decisions. Sections 1.2 and 1.3 of this report provide an overview of relevant municipal policies and describe how this study relates to them. Section 4 discusses how the results can inform land use planning policies in the Region. Note that this study had a relatively narrow focus—understory vegetation communities at woodland edges—and the results should be interpreted with this understanding.

WHY PROTECT BIODIVERSITY?

This research largely focused on biodiversity as a way of quantifying edge communities and it should be explained why protecting biodiversity should be a concern for Regional policy-makers. The Region of Waterloo’s urban woodlands have significant ecological, social and economic value. Their ecological value stems from the provision of habitat for diversity of species. A wealth of natural heritage data recorded over many decades illustrates the historical and present biological diversity of the Region’s ecosystems. This diversity remains visible in the Region’s natural habitats today. Woodlands in Kitchener, Waterloo and Cambridge provide habitat for thousands of plant and animal species, including a number of rare species and species at risk. Even the relatively small-scale surveys conducted for this study identified a number of significant species, such as squawroot (Conopholis americana) and butternut (Juglans cinerea) in local woodlands. Larger-scale studies have identified and will no doubt continue to identify even more significant species.

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The social and economic value of urban woodlands derives from the provision of ecosystem services. Ecosystem

services are the inherent activities and functions of ecosystems that humans derive some benefit from. The erosion prevention qualities of a vegetated riparian zone along a stream are an example of an ecosystem service, as is the capacity of a forest to sequester atmospheric carbon emitted by human activities. Attempts have been made to quantify the value of ecosystem services in economic terms. For example, the value of a riparian zone for erosion prevention could be visualized as equivalent to the cost of building cement edges along the same stretch of stream. Ecosystem services provided by forests in the Grand River watershed are discussed in the Grand River Conservation Authority’s (GRCA) Watershed Forest Plan for the Grand River (2004). Section 3.2 of the plan identifies ecosystem services as some of the benefits of urban forests. In Section 3.3, the plan also recognizes that ecosystem services can be evaluated in economic terms:

“Services” provided by the forests – the many benefits outlined in the introduction to this plan –

are even harder to quantify than forest products. It is almost certain, though, that the services have a greater economic impact than forest products in this watershed. Services include the cleansing of air and water; sheltering crops, livestock, and buildings; moderating streamflow; carbon sequestration; and others. There is even an argument that can be made that the “quality of life” benefits that trees and forests bestow on a community make it more attractive as a place to live and work, and therefore could be the basis for attracting employers to the area.

- A Watershed Forest Plan for the Grand River, s. 3.3, p. 109 (GRCA, 2004)

1 “Significant species” in this case refers to species that are 1) nationally or provincially rare, or 2) considered to be regionally significant based on the list approved by Regional Council in 1999.


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It is evident that the ecological, social and economic benefits of forests are well-known to municipal policy-makers and this is reflected in Regional planning policies. The next section outlines the relevant municipal planning policies.

1.2 Policy Context

A review of municipal policy makes it clear that the Region is cognizant of the adverse impacts of urban development on natural habitats and has a proactive approach to mitigating them. The Region has a long history of natural heritage conservation. Environmentally Sensitive Areas (ESA’s)—including many woodland habitats—were identified in the Region as early as the 1960’s and Regional policy continues to recognize the significance of natural habitats as well as the potential impacts of urban development. The Regional Official Plan (ROP) includes policies for implementing a “Greenlands Network”, which serves to protect significant environmental features in the Region. Concerning woodland habitats, forest management plans have prepared by both the Regional Municipality and the Grand River Conservation Authority (GRCA). Furthermore, municipal policies concerning forest management must adhere to provincial policies including the most recent Provincial Policy Statement (2005), the Forestry Act and the Endangered Species Act among others.

The Regional Forest Management Plan (RFMP) defines how the Region’s woodland habitats will be managed

based on a consolidation and interpretation of provincial policies, conservation authority policies and the 2006 Regional Official Policies Plan. Although a new official plan was introduced in 2010

1, the 2006 RFMP remains the

current forest management plan for the Region. The Grand River Conservation Authority’s Watershed Forest Plan for the Grand River (2004) also directs the management of woodland habitats in the Region. These two documents, along with the ROP, define key forest management goals for the Region. The RFMP states the following management goal for Regional forests:

To conserve, enhance, and where feasible, restore woodland ecosystems to reflect the native

biodiversity of the respective parts of the Region of Waterloo in which the Regional Forest tracts are located while at the same time accommodating appropriate recreational, educational, social activities which do not jeopardise the health or sustainability of the forests.

- Regional Forest Management Plan, s. 1.1, p. 6 (Region of Waterloo, 2006c)

This goal is further broken down into sets of ecological, social, educational, legal and economic objectives. The ecological objectives are:

To place the highest level of protection, conservation and management on Regional Forests that contain: ESPAs, Significant Woodlands, or other parts of the Natural Habitat Network.

To conserve native species and habitats representative of the Region’s native biodiversity with particular attention to habitats and species within Regional Forests that exhibit any of the following characteristics: Carolinian habitat, Old Growth trees and Woodlands, Rare Species, Significant Wildlife Habitat, Interior Forest Habitat, Wetlands, Groundwater Recharge/Discharge Zones, High Quality Forest Habitat, Slopes and Valleys, Creeks and Streams, Locally Significant Species, Wildlife Corridors, Unusual Habitat.

To maintain and enhance healthy, sustainable forest ecosystems with a range of successional stages and diversity of forest communities.

To restore plantations with low vigour and low ecological function to healthy woodlands consisting of representative native species.

1 Note that, although the remainder of this study refers to the 2010 Regional Official Plan, the new plan is not in effect due to an appeal at the Ontario Municipal Board.


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To carry out active management activities using suitable techniques including ecological restoration and silvicultural prescriptions (i.e. tree cutting, prescribed burning), and where feasible implement measures to control or eradicate introduced species that threaten the health and integrity of Regional Forests.

- Regional Forest Management Plan, s. 1.1.1, p. 6 (Region of Waterloo, 2006c)

The “Natural Habitat Network” in this case refers to the network laid out in the Regional Official Plan. In the

most recent ROP (2010) it is termed the “Greenlands Network,” however the effect of the RFMP remains the same. The Greenlands Network includes “Landscape Level Systems”, “Core Environmental Features” and “Supporting Environmental Features” that are to be managed according to the policies in Chapter 7 of the ROP. Core Environmental Features (CEF’s) are woodlands, wetlands and other habitats of Regional significance. According to the ROP, “Core Environmental Features form key habitat for native flora and fauna and represent the most significant elements of the regional landscape in terms of maintaining biodiversity and important ecological functions.” The goals and objectives of the Greenlands Network are outlined in Chapter 7 of the ROP. The overall goal is to “work with the Province, Area Municipalities, the Grand River Conservation Authority and private landowners to maintain, enhance and restore a comprehensive Greenlands Network within the region” (Regional Official Plan, c. 7, p. 93, Region of Waterloo, 2010).

The ROP goes on to outline 104 specific objectives for the Regional Greenlands Network. For the purposes of this

study, these objectives have been distilled into the following items:

Environmental impact statements are to be prepared where land development would affect an environmental feature in the Greenlands Network (ROP c. 7, ss. 7.G.1,2,3,4)

Delineation of environmental features is to be conducted during the preparation of Environmental Impact Statements (ROP c. 7, ss. 7.A.6,7,8)

Buffer zones with a minimum with of 10m are to be located around the boundaries of environmental features. (ROP c. 7, ss. 7.B.9, 7.C.10)

Delineating linkages between environmental features (ROP c. 7, ss. 7.E.6,7,8).

The ROP requires that these items be implemented according to the Regional Greenlands Network Implementation Guideline (ROP c. 7, s. 7.A.4). A draft of the guideline was prepared by Regional staff in 2011 and contains detailed implementation protocols for Environmental Impact Statements (EIS’s), delineation of environmental features, buffer zone design and identification of linkages. According to the guideline, EIS’s should address the following ecological aspects:

Delineation of environmental features

Occurrences and habitat of provincially or federally at risk species

Occurrences and habitat of regionally significant species

Habitats of provincial or regional significances (wetlands, ANSI’s, environmental sensitive areas, etc)

Surface and subsurface hydrological features

Other significant ecological features

- Distilled from s. B.I of the Greenlands Network Implementation Guideline (Region of Waterloo, 2011) The guideline also gives a detailed rationale a set of considerations for the width of buffer zones around environmental features. Notably, although the minimum buffer width is 10m, the recommended width ranges from 10 to 190m depending on the types of environmental stressors it is intended to mitigate, including:

Herbicide drift

Fertilizer inputs

Other agricultural pollutants


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Stormwater runoff

Outdoor cats

Human intrusions (dumping, composting, etc)

Recreational use

Light pollution

- Distilled from s. B.IV of the Greenlands Network Implementation Guideline (Region of Waterloo, 2011) Note that species introduction—a major focus of this study—is not included in this list, which is not to say that it is not a consideration for buffer zone design. However, some information about the effect of buffers on species introduction could be provided by this study.

This study should serve to inform some aspects of the Region’s Greenlands Network policies as they pertain to

vegetation communities in woodland habitats, including new considerations for EIS’s and buffer zone design. These could include:

Determining if the effects of urban development on vegetation communities in woodlands are generalizable.

Determining the compatibility of certain land uses with adjacent woodland habitats.

Understanding the effect of buffer zones on vegetation at the edges of woodland habitats.

Understanding how vegetation communities in woodlands change over time after experiencing urban development.

The focus of this study is explained in more detail in the next section of this report. For an interpretation of how the results relate to Region policy, refer to Section 4.

1.3

Focus of This Study The Regional Official Plan and Regional Forest Management Plan aim, in part, to prevent adverse impacts on

natural habitats in the Region through proper management. Some potential impacts that threaten natural habitats are outlined in Section 3.3.3 of the RFMP:

Adverse environmental impacts on elements of the Natural Habitat Network include:

fragmentation; significant increase in perimeter-to-area ratios; disruption of corridors and ecological linkages; disruption of ecological relationships; alteration of the structure, functions, or ecological interrelationships of a natural habitat which sustain representative community associations or populations of significant species; compaction or trampling of soils; and increased potential for the introduction of invasive non-native species.

- Regional Forest Management Plan, s. 3.3.3, p. 14 (Region of Waterloo, 2006b) Of the specific impacts listed above, the latter four were the focus of this study. That is: “disruption of ecological

relationships”; “alteration of the structure, functions or ecological interrelationships” of woodlands; impacts on “representative community associations or populations of significant species”; “compaction or trampling of soils”; and “introduction of invasive non-native species”. The premise of this study was that these impacts, if present, should be reflected in changes to vegetation communities, which would be most visible at the edges of woodlands in the Region. Specifically, the following vegetation community metrics were analyzed:

Species richness: the number of species that occur at the habitat edge.


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Similarity of edge and interior vegetation communities: calculated using the Sorensen Index. Edge communities that are more similar to the interior of the habitat are assumed to be less impacted.

Species evenness: how equitably distributed species are at the habitat edge. Low evenness can be a reflection of species invasion.

Prevalence of non-native species: quantified as 1) the proportion of species at the edge that are non-native and 2) the proportion of ground covered by non-native species.

Floristic quality: An index reflecting the degree to which an edge community resembles a natural (less disturbed) state.

The overall effects of urbanization on vegetation communities in natural habitats have been well-established

(see Section 1.1). More pertinent questions from a Regional management perspective are whether certain characteristics of urban development have more intense adverse impacts. Specifically, the following characteristics of urban development were explored:

Land Use Type: Do certain types of land uses (ex: industrial, commercial, low-density residential) have greater impacts on edge vegetation communities?

Land Use Age: How do edge vegetation communities change over time after urban development? Do edge communities that experienced development during certain time periods exhibit more impacts than others?

Edge Treatment: Current Regional regulations require buffer zones to be delineated between natural habitats and new urban land uses, but many natural areas are divided from human land uses only by fences or have no treatment at all. How effective are buffer zones at mitigating adverse impacts of urban development on edge vegetation communities?

Other research by local institutions has studied these impacts as well. For example, Wendy McWilliam’s 2007

dissertation explored residential impacts along a range of woodland edges in the Region.1 McWilliam’s study

explored the effectiveness of different edge treatments and municipal policies at mitigating intrusive activities of residents. However, her study had two limitations: 1) it included only woodland edges adjacent to low-density residential land uses and 2) it looked only for presence or absence of observable human impacts. This present study includes a wider range of land uses and uses a quantitative approach to characterizing human impacts on ecological communities.

1 McWilliam, WJ. 2007. Residential Encroachment within Suburban Forests: Are Ontario Municipal Policies Sufficient for Protecting Suburban

Forested Natural Areas for the Long Term? PhD dissertation, University of Waterloo, Waterloo, Ontario, Canada.


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2.0 Methods

2.1 Research Design and Site Selection

Preparatory work this project began in March, 2012. Before field work could begin, it was necessary to consider variables of interest, determine a reasonable sample size, identify specific woodlots to survey and design an efficient but detailed vegetation survey protocol. IDENTIFYING WOODLAND PATCHES

This project began by identifying all extant patches of woodland in the cities of Waterloo, Kitchener and Cambridge. Woodland patches were identified using orthoimagery, and their boundaries were traced in order to create a shapefile consisting of polygons for each woodland. Woodland patches were digitized manually rather than using a pre-existing shapefile because existing datasets did not necessarily show the true edge of the woodland. This shapefile contained exactly 100 woodland polygons (see Figure 1). The mean woodland size was 15.2 hectares, with the smallest patch measuring 1.1 hectares and the largest measuring 139.1 hectares. DETERMINING LAND USE VARIABLES TO INCLUDE

Human land uses were characterized around the edges of each woodland. Three land use variables were included in the study: land use type, land use age and edge treatment (see Table X). In order to determine the types of land uses occurring adjacent to woodland patches in the Region, the woodland polygons shapefile was layered on top of a regional land use shapefile. Eleven land use types were found to occur adjacent to the woodlands in the shapefile (Table X). Of these land uses, five were ultimately included in the study, however they were lumped into three categories (see below).

The perimeters of the 100 woodland patches identified in the Region were divided into edge segments. Edge

segments were first defined based on geometry: corners meeting at an angle of 90 degrees or less formed the first division points between edge segments. Those segments were then further divided based on their adjacent land use type. Overall, this yielded 581 edge segments along the perimeters of the 100 woodland patches in the shapefile (Table 1).

Table 1: Number of edge segments adjacent to each land use type in the Region before and after filters were applied.

Land Use Type Number of Segments Number of Segments (Post-filter)

Open Space 191 88

Low-density Residential 165 78

Road 96 48

Industrial 32 11

Agricultural 27 9

Other 20 9

Medium-density Residential 19 7

Institutional 9 2

High-density Residential 8 2

Commercial 6 2

Golf Course 6 2

Extraction Activities 2 0

TOTAL 581 258


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These 581 edge segments were then filtered in order to normalize as many characteristics as possible between the remaining segments. First, entire woodland patches were excluded based on age, hydrological conditions and canopy density. The age of each woodland patch was reasonably determinable based on historical orthoimagery: the earliest imagery available for the region dated from 1955, so patches that were not visible in the earliest orthoimagery were excluded, ensuring that all patches were older than 58 years. Woodlands that contained significant areas of wetland or were adjacent to a waterway or other wet area were also excluded in order to minimize the effects of hydrological gradients on the data. Finally, woodlands that appeared to have sparse or highly variable canopy density (based on orthoimagery) were excluded. In total, 59 of the initial 100 woodland patches were excluded from the study, with 41 remaining. This resulted in 257 of the initial 581 edge segments being excluded. Further filters were then applied to individual edges. First, edges with a length shorter than 50m were excluded. Second, edges located on private property or where ownership was uncertain were removed. Through these two filters, an additional 66 edge segments were excluded leaving 258 edges from which the edges ultimately surveyed in the field were selected (Table 1).

It was determined that there needed to be at least three different edge segments adjacent to each land use type

in order for that land use to be included in the study. It was decided that combining medium and high-density residential edges into a single category would yield enough edges for study. It was also decided to combine both commercial and industrial edges into one category. This resulted in three land use categories that were ultimately included in the study: low-density residential, higher-density residential (including medium and high-density housing) and industrial/commercial (see Table 4).

Determining the age of adjacent land uses was done using historical orthoimagery (see Section 2.2). Imagery was

available for the years 2009, 1993, 1971, 1955 and 1955. It was determined that land use age could reasonably be estimated within 20-year intervals using this imagery, therefore land use age was categorized as either younger (less than 20-years old), middle-aged (20 to 40-years old) and older (more than 40-years old) (see Table 4).

A large variety of edge treatments were present along the edges of woodlands in the Region. A wide range of

buffer zones of varying widths were observed, as well as different heights and types of fences. There were also a number of fence/buffer combinations where property lines were defined by fences with a buffer zone between the fence and the woodland. However, many of these treatment types were found along only one edge in the region. Therefore, despite the wide variety, all of the edges defined by a buffer zone were placed into one category regardless of the buffer width or presence of fences. Edges with only a fence or with no treatment at all retained their own categories (see Table 4). DETERMINING SAMPLE SIZE

Sample size in this case was defined as the number of transects that would be surveyed. Statistical models (see Section 2.3) were tested using randomly generated data with sample sizes ranging from 10 to 60 transects for each land use category (30 to 180 transects total). It was determined that these models were statistically powerful with sample sizes as small as 75 transects.

Although a larger sample size is always preferable, certain time and labour constraints were identified. It was

acknowledged that the number of transects surveyed should be reasonably accomplishable by a single researcher in a single season. In this case, the survey season was defined as June 1

st to August 31

st, 2012. Preliminary tests of field

survey methods (see Section 2.2) suggested a mean survey time of approximately 20 minutes per quadrat or 40 minutes per transect. It was ultimately decided that a sample size of 40 transects per land use category was ideal. This resulted in a total of 240 quadrats being surveyed, which amounted to 80 hours of field work not including travel time and time spent at each woodlot measuring edges and laying out transects.


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IDENTIFYING SPECIFIC WOODLOTS TO SURVEY

Of the 258 edge segments that were identified as having the characteristics necessary for vegetation surveys, 101 were adjacent to the three land use type categories included in the study. Of these segments, 78 were adjacent to low-density residential, 10 were adjacent to high-density residential and 13 were adjacent to industrial and commercial areas. It had already been determined that at each of these categories should be represented by at least three edge segments in the data analysis, although it was attempted to survey five segments per category. Therefore, from these three groups of edge segments, five were randomly selected from each group using a random number generator and ArcMap. These fifteen final edge segments also represented all categories of adjacent land use age and edge treatment. Field surveys were then conducted in these fifteen edge segments.

The fifteen edge segments that were surveyed in the field were located along the perimeters of seven different

natural areas in the Region. Table 2 lists the natural areas in which surveys were conducted; their locations are illustrated in Figure 1. The field survey results for each woodland can be found in Appendix A.

Table 2: List of sampling locations.

Site Name Municipality Number of Edge Segments Surveyed

Homer Watson Park Kitchener 1

Cambridge Centre Woodlot Cambridge 2

McLennan Park Kitchener 2

Stanley Park Kitchener 1

Steckle’s Woods Kitchener 1

Strasburg Woods Kitchener 3

Sugarbush Park Waterloo 4

2.2 Data Collection VEGETATION SURVEY METHODS

Data collection in the field was conducted from June to August, 2012. Understory plant communities along 15 edges in seven different woodlands were surveyed. Vegetation was surveyed within 240 quadrats along 120 transects. Dividing each quadrat into 25 sub-units resulted in a total of 5,600 sampling units in which plant species were identified.

Figure 2 illustrates how the vegetation surveys were carried out. The survey design involved running transects from the edge of the woodlot (defined as the line connecting the trunks trees extending farthest from the centre of the woodlot) towards the interior of the woodlot. These transects were 20m in length. Eight transects were surveyed for each woodland edge. The origin of each transect was placed randomly along the edge: edges were measured and eight random distances along them were generated using GIS. The azimuth (compass direction) of a transect was always perpendicular to the habitat edge.

Quadrats measuring 1m by 1m were placed at 1m and 20m marks along each transect (1m and 20m from the woodland edge). Each 1m-mark quadrat was defined as an “edge” observation and each 20m-mark quadrat was defined as an “interior” observation. “Interior” in this case does not necessarily reflect a scientific definition of interior habitat. Rather, these interior quadrats can be better thought of as “closer to the interior” relative to the edge quadrats and were used only to calculate the gradient of environmental change as one approaches the edge of the habitat. Each quadrat was divided into 25 sub-units with dimensions of 20cm by 20cm, which were used to determine the cover of each species identified in the quadrat.


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Figure 2: The vegetation survey protocol used for this study.

Field surveys began by measuring the length of the edge being surveyed and flagging the origins of each of the eight transects. At each of these points of origin, observations were made about the adjacent human land uses. The type of land use was recorded as well as the type of edge treatment (barrier) dividing the human land use from the woodlot (see Table 4). A 20m measuring tape was then drawn out perpendicularly to the edge at each point of origin. A wooden quadrat square was placed at each sampling point (1m from the edge and 20m from the edge) and meter sticks were used to delineate each of the sub-units within the quadrat.

Within each quadrat, all species of plant with living branches occurring below 1m above the ground were identified. Their presence or absence within each sub-unit was then noted in order to derive estimates of cover. This procedure was followed for every transect. On rare occasions, a quadrat would fall directly on an obstacle, usually large trees. In these cases, the quadrat was moved to the right as necessary to avoid the obstacle. LAND USE DATA COLLECTION

At each transect point of origin, observations about the adjacent human land uses were noted. The information recorded was the adjacent land use type and edge treatment. Land use type was generally already known (see Section 2.1), but groundproofing was used in order to confirm this information. Edge treatment was recorded as either a buffer zone, fence or no treatment. A buffer zone was identified as a distinct band of open space located between the edge of the woodland and the edge of the adjacent human land use. Buffer zones were distinguished from the woodland habitat by having little to no canopy cover. Edge treatment was classified as a buffer zone even if there was a fence along the edge of the human land uses. Land use age was determined using historical orthoimagery (see Section 2.1) and habitat size was determined using ArcGIS.


14

2.3 Data Analysis

From the field data, eleven variables were calculated which described plant community characteristics. These were broken down into two sets (see Table 3). The first set of five variables described alpha-diversity at 1m from the woodland edge. These were calculated for each of the “edge” quadrats along each transect. The second set of variables consisted of six measures of similarity or difference between the “edge” and “interior” quadrats along each transect (“beta-diversity” metrics). The final set of eleven dependent variables is listed in Table 3. These variables were compared against five independent variables: three land use variables (Table 4) and two other variables (Table 5). Examples of some categories are illustrated in Figure 3.

Various statistical methods were used to explore relationships in the dataset. Generalized linear models were

used to identify significant effects of land use variables on each biodiversity variable. Pearson correlation was used to find significant relationships between habitat size and each biodiversity variable. Where a land use variable was found to have a significant effect, post-hoc tests, such as Fisher’s least significant difference test, were used to compare means between different categories of that land use variable. Significant effects were quantified further using multinomial logistical regression models. Results are described in the next section.

Table 3: List of vegetation community metrics (dependent variables) used in the analysis.

VARIABLE NOTATION EXPLANATION

Set

1: A

lpha

-div

ers

ity

Me

tric

s

Species Richness (edge) Sedge Number of species observed at 1m from the edge.

Shannon’s Evenness Index (edge) Eedge

Describes how evenly distributed species are at 1m from the edge; a low value indicates that one species dominates; a high value indicates more equitable distribution.

Proportion of species that are non-native (edge) NNedge Proportion of all species observed at 1m from the edge that are non-native.

Non-native species cover (edge) Ncovedge Proportion of total species cover covered by non-native species at 1m from the edge.

Floristic Quality Index (edge) FQIedge Floristic quality at 1m from the edge.

Set

2: B

eta

-div

ers

ity M

etr

ics Sorensen Index Sor

Similarity in species composition between the edge and interior quadrats; the inverse of beta-diversity.

Difference in species richness Sdiff Percent change in number of species observed as one approaches the edge.

Difference in Shannon’s Evenness Index Ediff Difference in species evenness between the edge and interior.

Difference in proportion of non-native species NNdiff Percent change in number of non-native species observed as one approaches the edge.

Difference in Non-native species cover NNcovdiff Difference in non-native species cover between the edge and interior.

Difference in Floristic Quality FQIdiff Difference in floristic quality between the edge and interior.

Table 4: List of land use variables included in the analysis.

VARIABLE CATEGORIES EXPLANATION

Adjacent land use type Industrial/Commercial

High-density Residential

Low-density Residential

The human land use type occurring immediately adjacent to the origin of each transect.

Adjacent land use age <20 years

20-40 years

>40 years

The age of the human land use occurring immediately adjacent to the origin of each transect.

Edge treatment None

Fence

Buffer Zone

The type of barrier, if any, dividing human land uses from the woodlot at each transect origin.


15

Table 5: List of other variables included in the study.

VARIABLE EXPLANATION

Woodlot ID The name of the woodlot in which the quadrat or transect was located.

Woodlot Size The area (hectares) of the woodlot in which the quadrat or transect was located.

[Figure 3 will be here]


16

3.0 Summary of Results

3.1 Edge Effects Observed in Regional Woodlands

Many of the edge effects observed in Regional woodlands are consistent with what would be expected based on the current scientific understanding of edge effects. Species richness was generally higher closer to the edge of the woodland and a greater proportion of species were non-native; the area of ground covered by non-native species was also higher closer to the edge. Floristic quality was generally lower close to the edge compared to the interior of the woodland. Table 6 shows how the five biodiversity metrics varied between the edge and interior of the woodlands studied.

Table 6: Mean biodiversity values for “edge” quadrats and “interior quadrats.

Metric Mean “Edge” Value Mean “Interior” Value Change (interior to edge)

Species Richness 6.44 5.42 18.80%

Species Evenness 0.67 0.68 -0.02%

Proportion Non-native 0.40 0.23 17.00%

Non-native Species Cover 0.45 0.22 23.00%

Floristic Quality Index 1.66 3.47 52.20%

Species richness was 18.8% higher in “edge” quadrats than “interior” quadrats. This means that there are generally more species present at the edges of Regional woodlands than in the interiors. On average, 6.44 different species were observed at 1m from the edge and 5.42 species were observed at 20m from the edge. This is a well-known phenomenon of habitat edges. There tend to be more species closer to the edge because these areas are closer to propagule sources. Species richness was higher at the edge than the interior in all but one woodland (Homer Watson Park had higher species richness in the interior).

Species evenness, a measure of how equitably distributed species are in a community, was slightly lower in

“edge” quadrats than “interior” quadrats. However, this difference was insignificant. Species evenness can sometimes be lower at woodland edges because it reflects the degree of invasion of invasive species. However, there was no correlation between species evenness and either the proportion of non-native species or non-native species cover. This indicates that species evenness is more strongly affected by variables that were not explored in this study.

Non-native species are more prevalent at woodland edges than the interior. The proportion of species that were

non-native was 17% higher in “edge” quadrats than “interior” quadrats. This means that a greater proportion of species are non-native at the edges of Regional woodlands than in the interiors. On average, 40% of species at 1m from the edge were non-native and 23% of species at 20m from the edge were non-native. The percent cover of non-native species was 23% higher in “edge” quadrats than “interior” quadrats. This means that area of ground covered by non-native species is higher at the edges of Regional woodlands than in the interiors. On average, 45% of total vegetative cover at 1m from the edge consisted of non-native species and 22% of total vegetative cover at 20m from the edge consisted of non-native species. Like species richness, this reflects the greater proximity of the edge to propagule sources, which enables the introduction of new species. These propagule sources can include, but are not limited to, human activities at woodland edges, such as gardening. Non-native species were more prevalent at 1m from the edge than at 20m from the edge in all but one woodland (Steckle’s Woods exhibited a greater prevalence of non-native species in its interior than at its edge).


17

Floristic quality was 52.2% lower in “edge” quadrats than “interior” quadrats. On average, the floristic quality index (FQI) was 1.66 at 1m from the edge and 3.47 at 20m from the edge. This reflects the lower levels of disturbance in the interiors of Regional woodlands compared to the edges. Again, this is a well-established type of edge effect in the scientific literature.

These results indicate that Regional woodlands experience the same edge effects as other habitats worldwide.

They have more species and a greater prevalence of non-native species at their edges due to the proximity of propagule sources. They also experience higher levels of disturbance at their edges compared to their interiors, which is reflected in biodiversity.

3.2 Overview of Statistical Results

Eleven generalized linear models were run in order to determine significant effects of four independent variables (site, land use type, land use age and edge treatment) on each biodiversity variable. Figure X shows the results of each model. These models identified eleven significant effects at α = 0.05. However, in order to account for the relatively large number of comparisons (i.e.: 189 pairwise comparisons between categories of each factor), the models were repeated using Bonferroni-correction. Only one significant effect was identified in the models when using a Bonferroni-corrected alpha value. This indicates simply that there is a small probability that the other ten significant effects may be random (i.e.: false positives). Nonetheless, in the following sections, all significant effects at α = 0.05 are reported.

Table 7: Results of generalized linear models run for each biodiversity variable. The value given is the probability of that effect. Only p-values less than 0.05 are shown; all other values are not significant (p > 0.05).

SED Sdiff SSor EED Ediff NNED NNdiff NNcovED NNcovdiff FQIED FQIdiff

Site ID 0.000* - 0.008 - - 0.002 - - - 0.038 0.012

Land Use Type - - - - - 0.016 - - - 0.011 -

Land Use Age - - 0.026 - - 0.025 - - - 0.020 -

Edge Treatment - - 0.033 - - - - - - - -

SED = Species richness at 1m from the edge Sdiff = Difference in species richness between 20m from the edge and 1m from the edge SSor = Similarity in species composition between the edge and interior quadrats (Sorensen Index); higher values are more similar EED = Species evenness at 1m from the edge (Simpson’s Evenness Index); higher values are less even Ediff = Difference in species evenness between 20m from the edge and 1m from the edge NNED = Proportion of species at 1m from the edge that are non-native NNdiff = Difference in proportion of non-native species between 20m from the edge and 1m from the edge NNcovED = Non-native species cover as a proportion of total vegetative cover at 1m from the edge NNcovdiff = Difference in non-native species cover between 20m from the edge and 1m from the edge FQIED = Floristic Quality Index (FQI) at 1m from the edge FQIdiff = Difference in Floristic Quality Index (FQI) between 20m from the edge and 1m from the edge *Effect is significant at α = 0.0003 (Bonferroni-corrected alpha).

Table 7 indicates that each of the four factors included in the statistical models significantly affect at least one of

the eleven biodiversity metrics:

Site ID affects species richness at 1m from the woodland edge, similarity between the edge and interior (Sorensen Index), non-native species proportion at 1m from the edge, floristic quality (FQI) at 1m from the edge and the difference in FQI between the edge and interior.

The adjacent land use type affects non-native species proportion and FQI at 1m from the edge.


18

The age of adjacent land uses affects the similarity between the edge and interior, non-native species proportion at 1m from the edge and FQI at 1m from the edge

Edge treatment affects the similarity between the edge and interior

Note that the only effect that was significant after applying Bonferroni-correction was the effect of Site ID on species richness at 1m from the woodland edge. Five biodiversity variables were not significantly affected by any of the factors included in the models. These were:

The difference in species richness between the edge and interior

Species evenness (Simpson’s E) at 1m from the edge

The difference in species evenness between the edge and interior

The difference in non-native species proportion between the edge and interior

Non-native species cover at 1m from the edge

The difference in non-native species cover between the edge and interior This should not be interpreted to mean that urban development does not affect these aspects of vegetation communities. It simply means that the factors that affect these variables were beyond the scope of this study.

The following sections explore the effects of each land use factor in more detail.

3.3 Intrinsic habitat conditions are the most important factor

Statistical models indicate that most of the variation in vegetation community characteristics can be explained by the habitat itself. For the five key biodiversity variables measured—species richness, species evenness, non-native species proportion, non-native species cover and floristic quality index—the most significant effect was found to be that of the “Site ID” factor. That is to say that 1) there is more variation between woodlands than within woodlands and 2) there is more variation between individual woodlands than between land use characteristics. This indicates that individual woodlands respond to the effects of human land use activities differently. Table 8 shows the effect of the Site ID factor on each of the biodiversity variables studied.

Table 8: Effects of Site ID on the biodiversity metrics studied. Blank cells indicate no significant effect.1

SED Sdiff SSor EED Ediff NNED NNdiff NNcovED NNcovdiff FQIED FQIdiff

Significance (p) 0.000* - 0.008 - - 0.002 - - - 0.038 0.012

SED = Species richness at 1m from the edge Sdiff = Difference in species richness between 20m from the edge and 1m from the edge SSor = Similarity in species composition between the edge and interior quadrats (Sorensen Index); higher values are more similar EED = Species evenness at 1m from the edge (Simpson’s Evenness Index); higher values are less even Ediff = Difference in species evenness between 20m from the edge and 1m from the edge NNED = Proportion of species at 1m from the edge that are non-native NNdiff = Difference in proportion of non-native species between 20m from the edge and 1m from the edge NNcovED = Non-native species cover as a proportion of total vegetative cover at 1m from the edge NNcovdiff = Difference in non-native species cover between 20m from the edge and 1m from the edge FQIED = Floristic Quality Index (FQI) at 1m from the edge FQIdiff = Difference in Floristic Quality Index (FQI) between 20m from the edge and 1m from the edge 1 Results of generalized linear models for each biodiversity metric.

* Effect is significant with Bonferroni-correction.

Table 9 shows the mean of each biodiversity metric for each of the seven woodlands surveyed. More detailed

descriptions of biodiversity patterns observed in each woodland can be found in Appendix A.


19

Table 9: Mean biodiversity values for each woodland surveyed.

Woodland SED SIN SSor EED EIN NNED NNIN NNcovED NNcovIN FQIED FQIIN

Cambridge Centre Woodlot 7.200 6.067 0.068 0.750 0.685 0.322 0.120 0.391 0.068 1.516 4.843

Homer Watson Park 6.125 8.875 0.109 0.758 0.560 0.581 0.353 0.604 0.396 1.192 2.698

McLennan Park 6.000 4.933 0.138 0.671 0.670 0.415 0.259 0.458 0.340 1.742 3.026

Stanley Park 10.429 5.286 0.143 0.497 0.618 0.514 0.323 0.639 0.352 0.753 2.579

Steckle’s Woods 9.500 7.000 0.107 0.598 0.744 0.202 0.251 0.271 0.259 2.786 3.446

Strasburg Woods 5.292 4.875 0.183 0.680 0.745 0.376 0.219 0.441 0.235 1.746 2.941

Sugarbush Park 5.581 4.484 0.135 0.670 0.674 0.420 0.203 0.458 0.147 1.668 3.831

SED = Species richness at 1m from the edge SIN = Species richness at 20m from the edge SSor = Similarity in species composition between the edge and interior quadrats (Sorensen Index); higher values are more similar EED = Species evenness at 1m from the edge (Simpson’s Evenness Index); higher values are less even EIN = Species evenness at 20m from the edge (Simpson’s Evenness Index); higher values are less even NNED = Proportion of species at 1m from the edge that are non-native NNIN = Proportion of species at 20m from the edge that are non-native NNcovED = Non-native species cover as a proportion of total vegetative cover at 1m from the edge NNcovIN = Non-native species cover as a proportion of total vegetative cover at 20m from the edge FQIED = Floristic Quality Index (FQI) at 1m from the edge FQIIN = Floristic Quality Index (FQI) at 20m from the edge

CONCLUSION ON EFFECTS OF SITE ID

The overall environmental state of a woodland is more important than human land use activities for affecting

vegetation communities at the edge. Interestingly, the size of the woodland was found to have no significant effect on any of the biodiversity metrics studied except for species richness (larger habitats were found to harbour more species, which is not unexpected). It is more likely that other habitat-scale environmental variables play the most important roles (ex: historical disturbance, hydrological change, presence of earthworms, etc). It is likely that the legacy of historical disturbances, such as logging, agriculture or artificial selection for certain species (ex: sugar maple, a species commonly selected for in our region), will continue to be reflected in edge vegetation communities both before and after it has experienced urbanization.

3.4 Effects of Adjacent Land Use Type

Statistical models showed that the type of land use adjacent to the woodland edge had a significant effect on two of the biodiversity variables studied. Different land use types were found to have different effects on non-native species proportion at 1m from the woodland edge and floristic quality (FQI) at 1m from the edge. Table 10 summarizes the results of the models.

EFFECT ON NON-NATIVE SPECIES PREVALENCE

The proportion of species that were non-native was calculated for each quadrat. Figure 3 shows how the mean non-native species proportion at 1m from the edge varied between different land use types adjacent to the woodland. Non-native species were least prevalent adjacent to industrial and commercial areas and most prevalent adjacent to low-density residential areas. The mean non-native species proportion was visibly higher only for low-density residential land use. On average, 42% of species 1m from the edge adjacent to low-density residential areas were non-native, compared to 38% for industrial, commercial and higher-density residential areas.

Note that a post-hoc protected Fisher’s least significant difference (LSD) test found no significant differences

between these means. A multinomial logistical regression model was run, which calculated a Nagelkerke pseudo-R2

statistic of 0.471, indicating only a weak relationship between land use type and non-native species prevalence.


20

However, this is likely a reflection of the relatively small sample size used for this study (108 transects). More comprehensive surveys would most likely reveal similar, more statistically significant results.

Table 10: Effects of adjacent land use type on the biodiversity metrics studied. Blank cells indicate no significant effect.1

SED Sdiff SSor EED Ediff NNED NNdiff NNcovED NNcovdiff FQIED FQIIN

Significance (p) - - - - - 0.016 - - - 0.011 -


Figure 4: Mean non-native species proportion at 1m from the woodland edge for transects adjacent to different land use types.

Regardless of the differences between means, the proportion of species that are non-native is relatively high for

all land uses. Roughly 2 out of 5 species recorded 1m from the edge of woodlands in the Region are non-native. Previous research (ex: Cutway & Ehrenfeld, 2009) has also found increased prevalence of non-native species adjacent to residential areas than other land uses. This is usually associated with the activities of urban residents (i.e.: gardening, landscaping, recreational use of woodlands). McWilliam (2007) observed that a high degree of non-native species introduction in Regional woodlands was related to residential activities. It is likely that low-density residential areas act as large propagule reservoirs due to the gardening and landscaping activities of their residents. Note, however, that increased prevalence of non-native species is not necessarily detrimental to woodland health. Non-native species become a problem when they behave invasively. Therefore, preventing residents from planting potentially invasive species should be an effective way of mitigating the effect of low-density residential areas on woodland edges.

0.384 0.385

0.420

0

0.1

0.2

0.3

0.4

0.5

Industrial/Commercial High-density Residential Low-density Residential

No

n-n

ati

ve

Sp

ec

ies

Pro

po

rtio

n

Adjacent Land Use Type


21

EFFECT ON FLORISTIC QUALITY

The floristic quality index (FQI) is a measure of how closely a vegetation community resembles an undisturbed community. Habitats that have a large number of non-native, weedy or generalist species have low FQI scores, while those with few non-native species and higher numbers of specialist species have higher scores. FQI is most useful as a way of comparing communities, rather than as a single value. Figure 4 shows the mean floristic quality at 1m from the edge for each of the three land use categories. Floristic quality was lowest adjacent to industrial and commercial areas and highest adjacent to low-density residential areas.

Note that, as with non-native species prevalence, a post-hoc protected Fisher’s LSD test found no significant

differences between these means. A multinomial logistical regression model calculated a Nagelkerke pseudo-R2

statistic of 0.983, which suggests a strong relationship between land use and floristic quality. The failure of post-hoc tests to find differences between means is likely a reflection of the relatively small sample size used for this study (108 transects). As with non-native species prevalence, more comprehensive surveys would most likely reveal similar, more statistically significant results.

The higher floristic quality adjacent to low-density residential areas stands in contrast to the higher prevalence

of non-native species adjacent to that land use, since non-native species lower the FQI score of a community. A look at the species identified in transects adjacent to low-density residential areas reveals that, while there are large numbers of non-native species, the native species present tend to have high coefficients of conservatism (a value reflecting how specialized a species is). In rare cases, this reflects the use of native species as horticultural plants, such as foamflower (Tiarella cordifolia). However, in the majority of cases, it is due to species of high conservation value naturally occurring at the woodland edge, such as the prevalence of Canada waterleaf (Hydrophyllum canadense) at the edge of Sugarbush Park in Waterloo, or ostrich fern (Matteuccia struthiopteris) in McLennan Park in Kitchener. A prudent conclusion is that a more comprehensive sample of woodlands needs to be surveyed in order to resolve the relationship between land use and floristic quality.

Figure 5: Mean floristic quality at 1m from the woodland edge for transects adjacent to different land use types.

CONCLUSION ON EFFECTS OF ADJACENT LAND USE TYPE

Non-native species are more prevalent at woodland edges adjacent to low-density residential land uses and highest at woodland edges adjacent to industrial and commercial land uses.

1.528

1.688 1.745

0

0.5

1

1.5

2

Industrial/Commercial Low-density Residential High-density Residential

Flo

ris

tic

Qu

ali

ty I

nd

ex

(F

QI)

Adjacent Land Use Type


22

Floristic quality is lowest adjacent to industrial land uses and highest adjacent to higher-density residential land uses.

A more comprehensive study with a larger sample of natural areas is necessary to confirm these effects with greater statistical significance.

3.5 Effects of Time since Urban Development

Statistical models indicated that the age of land uses adjacent to the woodland edge had a significant effect on three of the biodiversity variables studied. The age of the land use was found to affect the similarity between the woodland edge and woodland interior (Sorensen Index), non-native species proportion at 1m from the woodland edge and floristic quality (FQI) at 1m from the edge. Table 11 summarizes the results of the models.

Table 11: Effects of adjacent land use age on the biodiversity metrics studied. Blank cells indicate no significant effect.1


Significance (p) - - 0.026 - - 0.025 - - - 0.020 -


EFFECT ON SIMILARITY BETWEEN EDGE AND INTERIOR

The Sorensen Index is a measure of similarity between two ecological communities. It is defined as the proportion of all species found in two communities that are shared between both communities. In this case, Sorensen Index was used to quantify the similarity between “edge” communities (those at 1m from the woodland edge) and “interior” communities (those at 20m from the woodland edge). It is used as a way of quantifying the intensity of an edge effect; low similarity indicates that the edge and interior communities differ considerably, and therefore the edge effect is more intense.

Figure 5 shows how the mean Sorensen Index differed between different land use age categories. Transects

adjacent to younger land uses (less than 20 years-old) had the lowest mean Sorensen Index, while those adjacent to older land uses (more than 40 years-old) had the highest values. A post-hoc protected Fisher’s LSD test determined that the differences between means were significant (α = 0.05).

These results suggest that woodland edges adjacent to younger land uses exhibit more intense edge effects,

while those adjacent to older land uses exhibit less intense edge effects. This could be that edge effects adjacent to older land uses extend deeper into the woodland than survey methods were able to capture. However, if this were the case, species richness, non-native species prevalence and floristic quality would be expected to be lower adjacent to older land uses than younger ones, which is not the case (non-native species prevalence is higher and floristic quality is lower adjacent to younger land uses). It is much more likely that communities adjacent to younger land uses are more significantly altered from their initial state than those adjacent to older land uses.


23

Figure 6: Mean Sorensen Index for transects adjacent to land uses of different ages.

EFFECT ON NON-NATIVE SPECIES PREVALENCE

Time since urban development was shown to have a significant effect on the proportion of species that were non-native at 1m from the woodland edge. Figure 6 shows the mean non-native species proportion at 1m from the edge for land use age classes.

Figure 7: Mean non-native species proportion at 1m from the edge for transects adjacent to land uses of different ages.

Non-native species prevalence was highest adjacent to younger developments (less than 20 years-old) where

42.5% of species observed were non-native. It was lowest adjacent to land uses between 20 and 40 years old (37.7% of species). A post-hoc protected Fisher’s LSD test determined that the means for younger land uses and middle-aged land uses differed significantly, while the mean for older land uses did not (α = 0.05). It is unclear why this pattern was observed. Most likely it is a statistical anomaly due to the relatively small number of transects surveyed adjacent to land uses more than 40 years-old. Furthermore, land uses more than 40 years-old were located adjacent

0.101

0.144 0.154

0

0.05

0.1

0.15

0.2

<20 years old 20-40 years old >40 years old

So

ren

sen

In

de

x

Age of Adjacent Land Use

0.425 0.377 0.407

0

0.1

0.2

0.3

0.4

0.5


No

n-n

ati

ve S

pe

cie

s P

rop

ort

ion



24

to only two of the woodlands studied (McLennan Park and Sugarbush Park). A larger number of transects and woodlands located adjacent to older land uses would likely have yielded a more accurate mean for edges that experienced urban development more than 40 years ago.

EFFECT ON FLORISTIC QUALITY

The floristic quality index (FQI) was calculated for each quadrat. Statistical models indicated that the age of land uses adjacent to the woodland significantly affected floristic quality at 1m from the edge of the woodland. Figure 7 shows the mean FQI at 1m from the edge for three different land use age classes.

Figure 8: Mean floristic quality at 1m from the edge for transects adjacent to land uses of different ages.

Floristic quality was lowest adjacent to land uses younger than 20 years-old (FQI = 1.391) and highest adjacent to

land uses more than 40 years-old (FQI = 1.981). A post-hoc protected Fisher’s LSD test indicated that none of these means differed significantly. However, a multinomial logistical regression model calculated a Nagelkerke pseudo-R

2

statistic of 0.983, suggesting a strong relationship between land use age and floristic quality. It is likely, therefore, that a larger sample size would yield the same results but with statistically significant differences between means. This relationship reflects the relationship between land use age and Sorensen Index. It appears that floristic quality is more depressed adjacent to younger developments than older ones.

These results seem somewhat counter-intuitive. It appears that, over time after urban development, woodland

edge communities become more similar to their interiors, non-native species prevalence decreases and floristic quality improves. Importantly, this does not necessarily indicate that vegetation communities at woodland edges recover after urban development; however, the evidence does support this conjecture. It is entirely possible that edges experience a large initial disturbance when urban development occurs—experiencing a high degree of species introduction and extirpation—then shift towards a state more similar to their interiors over time. The exception occurs when edge communities experience biological invasions. There was no significant relationship between non-native species cover, and land use age, and plant communities exhibiting a high degree of invasion by species such as garlic mustard (Alliaria petiolata) and European buckthorn (Rhamnus cathartica) were observed adjacent to land uses of all ages.

1.391

1.677

1.981

0

0.5

1

1.5

2


Flo

risti

c Q

uali

ty I

nd

ex (

FQ

I)



25

CONCLUSION ON EFFECTS OF TIME SINCE URBAN DEVELOPMENT

Edge communities experience a high degree of initial disturbance during and after urban development, which is reflected in species composition, non-native species prevalence and floristic quality.

Edge communities recover slightly over time after they experience urban development—species composition becomes more similar to the interior, non-native species decrease in prevalence and floristic quality improves.

Post-development recovery of edge communities is impeded if the edge experiences biological invasion.

3.6 Effects of Edge Treatment

Statistical models indicated that edge treatment has a significant effect on only one of the biodiversity variables

included in the study—similarity between the edge and interior of the woodland, measured using the Sorensen Index (see Table 12). Figure 8 shows the mean Sorensen Index for different edge treatment categories.

Table 12: Effects of edge treatment on the biodiversity metrics studied. Blank cells indicate no significant effect.1


Significance (p) - - 0.033 - - - - - - - -


Figure 9: Mean Sorensen Index for transects adjacent to different edge treatments.

0.131

0.143

0.129

0

0.05

0.1

0.15

0.2

None Fence Buffer

So

ren

sen

In

de

x

Edge Treatment


26

Sorensen Index was highest where woodlands were divided from human land uses by a fence (0.143). There was little difference between edges with buffer zones (0.129) and edges with no treatment (0.131). A post-hoc protected Fisher’s LSD test indicated that none of these means were significantly different (α = 0.05). A multinomial logistical regression model calculated a Nagelkerke pseudo-R

2 statistic of 0.607 suggesting only a moderate

relationship between edge treatment and Sorensen Index. This suggests that the apparent effect of edge treatment on Sorensen Index is a statistical anomaly.

CONCLUSION ON EFFECTS OF EDGE TREATMENT

Edge treatment is a minor factor in determining the state of understory vegetation diversity at the edges of urban woodlands.


27

4.0 Interpretation

4.1 Relevance to Municipal Policy IMPORTANCE OF A CASE-BY-CASE APPROACH TO NATURAL HABITAT PROTECTION

The most important factor affecting vegetation communities at the edges of woodlands in this study was the intrinsic effect of the woodland itself (see Section 3.3). All woodlands are affected by urban development, but how vegetation communities change in response to urbanization depends more on the initial conditions in the woodland than on the characteristics of land use change adjacent to the edge. This means that the initial biological state of a woodland must be known in order to comprehensively evaluate the potential impacts of any development.

Essentially, it is not possible to generalize about the effects of a particular type of land use change on all

woodlands. Conservation strategies for a woodland should not be approached by asking “how will the characteristics of this development impact this habitat?” but rather “what specific features of this habitat are at risk?” Significant features in this case include species or species assemblages that are Regionally significant, at risk or of particular cultural or charismatic value. When these features have been identified, the characteristics of the proposed development can be considered.

The current policies in the 2010 Regional Official Plan (ROP) pertaining to the Greenlands Network, as well as the

Greenlands Network Implementation Guideline, demonstrate that the Region already takes this approach to habitat conservation. The requirement that an environmental impact statement (EIS) be submitted for proposed developments near environmental features in the Greenlands Network satisfies the recommendation given above.

Specifically, the following policies in the Greenlands Network Implementation Guideline serve to satisfy this

recommendation:

Guideline for a Full Environmental Impact Statement A Full Environmental Impact Statement required pursuant to the policies of the ROP and/or the Provincial Policy Statement and/or an Area Municipal Official Plan will consist of the following: […] (s. B.I.3) Information on the environmental features identified in 2.1 on the subject property and on adjacent or contiguous lands as defined in the ROP, Area Municipal Official Plans or secondary plans which might also be affected or that might reasonably be expected to be affected, either directly or indirectly, by the proposed development or site alteration, namely:

(s. B.I.3.1) detailed mapping of the environmental feature(s) and nearby related natural features at an appropriate scale showing any boundary interpretations recommended by the applicant; (s. B.I.3.2) mapping and description of ecological communities within the environmental features identified in 2.1 in the study area on and contiguous to the site proposed for development or site alteration by qualified professionals during the appropriate season(s) using the current published version of


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Ecological Land Classification (ELC), with such mapping and description taken to the vegetation type level with dominant, abundant, and significant species keyed to the mapped communities; (s. B.I.3.3) assessment of the quality of vegetation in the study area with reference to successional state, predicted successional pathway, assessment of natural regeneration, habitat specialization, degree of disturbance, presence of pathogens, and presence and extent of invasive plant species using qualitative description as well as quantitative measures such as the Floristic Quality Assessment Index (FQAI); (s. B.I.3.4) a comprehensive inventory, conducted by qualified professionals in the appropriate seasons, of species occurring in the study area, including but not limited to:

(s. B.I.3.4.1) vegetation in spring (May), summer (July), and late summer (August-early September), using commonly acceptable sampling and recording methods, […]

In addition, it is recommended that expert local naturalists and residents be consulted with respect to the flora and fauna of the site.

- Greenlands Network Implementation Guideline, s. B.I (Region of Waterloo, 2011)

The guideline also requires that the EIS identify potential adverse impacts on the features outlined above, describe mitigation strategies and consider alternatives to the proposed land use change. Recommendations:

1. The findings of this study strongly support the Region’s approach to woodland habitat conservation in

the ROP and Greenlands Network Implementation Guideline, particularly the guidelines for Environmental Impact Statements.

EFFECTS OF DIFFERENT LAND USE TYPES

There is evidence to suggest that the type of land use that occurs adjacent to a woodland habitat determines to some degree the impacts on understory vegetation communities. Non-native species are most prevalent adjacent to low-density residential areas, likely because residents engage in gardening and landscaping activities that serve as propagule sources for non-native species. This can become a problem when invasive species are introduced into the woodland, but is otherwise not necessarily a negative impact.

Conversely, although low-density residential areas are associated with an increased prevalence of non-native

species, they are also associated with higher floristic quality in adjacent woodland edges compared to higher-density residential, industrial and commercial land uses. This may be either because 1) low-density residential land uses have less intense impacts on the native flora of woodlands, or 2) residential activities introduce both non-native species and high-quality native species into woodlands.

The results of this study suggest that different land use types almost certainly have different impacts on

woodland habitats, not only on vegetation community composition but on other ecological communities and functions.


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Recommendations: 1. The type of land use proposed and the potential impacts on natural habitats unique to that land use should

be considered in Environmental Impact Statements.

2. The potential impacts of proposed land uses should be balanced with potential benefits. Ex: low-density residential land uses may be more likely to introduce invasive non-native species into natural habitats, but they may be more suitable than other land uses for providing linkages between natural habitats.

3. The impacts of human land uses on non-native species prevalence and floristic quality could be

ameliorated through programs encouraging the use of native species for landscaping and gardening. Policies that require developers to use only native, non-invasive species for landscaping could also be beneficial.

4. An ideal policy would require that species used for landscaping in new developments reflect extant

vegetation communities in nearby environmental features, or use species that are complementary to adjacent habitats.

EFFECTIVENESS OF BUFFER ZONES

The results of this study suggest that the type of barrier dividing a woodland from human land uses has little effect on vegetation community composition at the woodland’s edge. Note, however, that this study focused only on a relatively narrow element of woodland ecosystems—understory vegetation diversity at the edge—and the treatment of buffer zones was relatively broad (see “Limitations”, s. 4.2). This research concludes that buffer zones are not a major factor in mitigating the effects of land use change on understory vegetation communities.

One possible reason for this is that, while buffers prevent the introduction of non-native species from human

land uses, they themselves serve as sources of non-native or weedy species in some cases. Planting native species that are complementary to adjacent habitats in buffer zones could minimize this outcome. This recommendation is already included as an item in the Greenlands Network Implementation Guideline:

(s. B.IV.4.3) Opportunities for net ecological enhancement or wherever feasible, for restoration of the ecological functions of the Core Environmental Feature. Objective: To improve the form and function of an environmental feature and enhance its ecological integrity, a buffer should: […]

use locally appropriate native species reflective of historic vegetation communities and of varying successional stages to complement habitat functions of the environmental feature (e.g., upland deciduous forest species around wetlands)

- Greenlands Network Implementation Guideline, s. B.IV (Region of Waterloo, 2011)

Furthermore, although this research suggests their effectiveness for mitigating changes to vegetation

communities is uncertain, it is well-known that buffer zones are effective at mitigating impacts on other ecological features and functions, and this has been demonstrated in other research. This understanding is clearly demonstrated by Regional staff in s. B.IV.5 of the Greenlands Network Implementation Guideline, which distills existing research on buffer zones:


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(s. B.IV.5) Design of Buffers […] While it may not be possible to eliminate all edge effects, appropriate delineation, design, and maintenance of buffers can reduce their impact. Table 2 lists potential edge effects, and identifies suggested buffer widths to prevent, minimise or mitigate them. . If the buffer recommended in an Environmental Impact Statement differs significantly from the recommended value, this would need to be justified with reference to relevant scientific literature or by the professional opinion of a qualified professional. Table 2: Range of Edge Effects and Suggested Buffer Widths

Stressor Suggested Buffer Width Reference Notes

Herbicide drift from agricultural lands

>6 m to 9 m Strip at edge of cultivated fields

Boutin and Jobin, 1998. Cites other studies suggesting 5 m to 10 m.

Nitrate 16 m to 104 m Basnyat et al., 1999. Objective was >90 percent nitrate removal.

Non-point source agricultural pollutants

16.3 m grass/woody strip (riparian)

Lee et al., 2003. Removed >97 percent of sediment, narrower (7 m) grass provided some benefits.

Residential stormwater 15 m; 23 m to 30 m on slopes greater than 12 percent

Woodard and Rock, 1995. Groundcover type also very important.

Urban cats 190 m Haspel and Calhoon, 1991.

Predation rates on wildlife variable.

Lawn-related (e.g., wood piles, composting)

19 m to 38 m Matlack, 1993. Fencing may achieve same results in less width.

Recreation-related (e.g., camping, hacked trees)

67 m to 130 m Matlack, 1993.

Human disturbance on nesting Great Blue Herons

100 m Rodgers and Smith, 1995. Erwin, 1989.

Flush distance was 32 m plus 5.5 m standard deviation, plus 40 m to mitigate antagonistic behaviour.

Introduction of artificial nocturnal light levels

N/A - Species specific response dependent on a number of factors such as type of light, intensity, duration.

Outen (2002) Review of the literature identifies impacts on mammal, bird, bat, fish, amphibian, insect behaviour.

(Source: adapted from Canadian Wildlife Service, 2004, Outen, 2002)

- Greenlands Network Implementation Guideline, s. B.IV.5 (Region of Waterloo, 2011)

Recommendations:

1. Current policies in the ROP and Greenlands Network Implementation Guideline that require buffer zones to be delineated around environmental features should be maintained.

2. Native species that complement vegetation communities in adjacent natural habitats should be planted in

buffer zones. The item in s. B.IV.4.3 of the Greenlands Network Implementation Guideline satisfies this recommendation.


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3. The effectiveness of buffers for preventing changes to vegetation communities in natural habitats is uncertain, but their effectiveness for mitigating impacts to other ecological features and functions is clear, as evidenced in s. B.IV.5 of the Greenlands Network Implementation Strategy.

RECOVERY OF VEGETATION COMMUNITIES AFTER URBAN DEVELOPMENT

The results of this study give some evidence that vegetation communities at woodland edges recover over time

after the initial disturbance of urban development, unless they experience biological invasions by non-native species. It seems reasonable that construction activities associated with urban development would be one of the largest single stressors a habitat will experience—larger than the long-term effects of new land uses at its edges. This may explain why the impacts of urbanization appear more intense shortly after development than longer after development.

The policy solutions to these findings should focus on mitigating the immediate impacts associated with

construction activities. Longer-term solutions should focus on preventing species invasions and encouraging the use of native species for landscaping in new developments.

Recommendations:

1. Maintain and enhance existing policies that serve to mitigate the effects of construction activities on natural habitats (ex: limiting the use of fill soil and aggregates in proximity to natural habitats, preventing intrusions of construction equipment into natural habitats).

2. Encourage the use of native species for landscaping in new developments; particularly species that reflect

extant vegetation communities in nearby habitats or species that complement these communities.


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5.0 Conclusions

5.1 Summary

Woodland habitat fragments in the Region exhibit edge effects consistent with other ecosystems worldwide that have experienced urbanization. Vegetation communities at the edge differ significantly from those in the interior: edges have higher species richness, greater prevalence of non-native species and lower floristic quality. This research asked whether these effects vary significantly between different land use factors.

Understory vegetation community composition at woodland edges in the Region is affected by three

characteristics of adjacent land uses: land use type, land use age and edge treatment. The prevalence of non-native species, floristic quality and the compositional similarity between edge and interior communities are all affected by these land use factors.

The most important factor determining the state of vegetation communities at woodland edges is the inherent

state of the woodland itself. This means that the effects of land use change on edge vegetation depend largely on the existing conditions in a given habitat. Therefore, a case-by-case approach to habitat conservation, where potential impacts of development proposals on individual woodlands are assessed, is recommended. The policies in the Regional Official Plan and the Greenlands Network Implementation Guideline requiring Environmental Impact Statements for development proposals near environmental features more than satisfies this recommendation.

The type of land use adjacent to a woodland appears to significantly affect the prevalence of non-native species

and floristic quality at the edge. Low-density residential land uses are associated with an increased prevalence of non-native species but also with higher floristic quality, while industrial and commercial land uses are associated with a lower prevalence of non-native species and lower floristic quality. The effects of any land use on these variables would be best mitigated through policies which encourage the use of native species for landscaping and gardening, particularly species which complement extant vegetation communities in adjacent habitats. These recommendations are satisfied by policies in the Greenlands Network Implementation Guideline.

It is uncertain whether edge treatment (buffer zone, fence or no treatment) has any significant effect on

understory vegetation communities. Results suggest that buffer zones have little impact on species richness, non-native species prevalence, or floristic quality at the edge. However, it cannot be said with certainty whether this means that buffer zones are ineffective at mitigating impacts on species composition. A more comprehensive study with a larger sample of different buffer types may be able to determine this with more certainty. Nonetheless, it is clear that buffer zones do help mitigate impacts on many other ecological functions besides vegetation communities.

Results also suggest that vegetation communities recover over time after urban development. Vegetation

communities at woodland edges exhibit greater change within 20 years of development than within 40 years or beyond 40 years. It appears that woodland edges experience a large initial disturbance after development occurs, but over time, edge communities begin to approach a state similar to the habitat interior. To mitigate initial disturbance, and to promote the recovery of edge vegetation communities, it is recommended that policies be maintained that minimize the impacts of construction activities on natural habitats. It is also recommended that developers and landowners be encouraged to use native species in landscaping and gardening activities.


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5.2 Limitations and Further Research LIMITATIONS

This research explored only one element of urban woodland ecosystems: understory vegetation communities at woodland edges. Therefore, the results should be approached with this in mind. The relationships between land use, edge treatment and vegetation community composition are useful in situations where conservation of woodland vegetation is of primary importance. However, many other aspects of woodland ecosystems can be adversely impacted by urban development; and the relationships between land use change and these ecological aspects may be very different from the results of this study.

Furthermore, the categorization of land use variables in this study was fairly broad. Firstly, only three categories

of land use were included, and two of these were condensed from two or more land uses. Edge treatment, too, consisted of only three fairly broad categories (ex: buffer zones with different widths and characteristics could have been differentiated). This was largely due to the sample size limitations—a longer-term study with more resources available for research could have sampled a larger number of transects in more natural areas. Nonetheless, it is believed that the results of this study are accurate.

In summary, these results should not necessarily change the current natural habitat conservation priorities

expressed in Regional policies. That is to say that conserving understory vegetation communities is a priority that should be balanced with other conservation priorities, such as improving habitat connectivity, protecting ecosystems from pollutants, preventing hydrological change, etc… In some cases, this means that land use decisions affecting woodland habitats in the Region may go against the recommendations of this study.

FURTHER RESEARCH

As mentioned above, this research explores a rather narrow aspect of habitat conservation in the Region. A more comprehensive study on this topic could include a larger sample of transects, more study sites and more refined land use categories. There is also much research to be done on other ecological aspects of woodland ecosystems (ex: invasive species, taxa other than plants) and other types of ecosystems (ex: wetlands, meadows). A similar study but with a focus on comparing various buffer zone characteristics would prove useful.

It is the researcher’s opinion that any effective environmental management plan will include a significant

monitoring component. The Region is extremely progressive in its environmental management policies. In particular, the objectives and implementation guidelines for the Greenlands Network are extremely ambitious and remarkably advanced compared to other municipalities. However, monitoring the outcomes of these policies on the ecosystems they affect will serve to improve these policies by incorporating new information. Academic research, such as this study, can partially fulfill this goal, but active monitoring by Regional staff is recommended.


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References Cutway, HB; Ehrenfeld, JG. 2009. Exotic plant invasions in forested wetlands: effects of adjacent urban land use

type. Urban Ecosystems 12, 371-390. Eisenhauer, N; Partsch, S; Parkinson, D; Scheu, S. (2007). Invasion of a deciduous forest by earthworms: Changes in

soil chemistry, microflora, microarthropods and vegetation. Soil Biology & Biochemistry 39(5), 1099-1110. Frelich, LE; Hale, CM; Scheu, S; Holdsworth, AR; Heneghan, L; Bohlen, PJ; Reich, PB. (2006). Earthworm invasion into

previously earthworm-free temperate and boreal forests. Biological Invasions 8, 1235-1245. Grand River Conservation Authority. (2004). A Watershed Forest Plan for the Grand River. Grand River Conservation

Authority, Cambridge, Ontario. Laurance, WF; Yensen, E. 1991. Predicting the Impacts of Edge Effects in Fragmented Habitats. Biological

Conservation 55, 77-92. McWilliam, WJ. 2007. Residential Encroachment within Suburban Forests: Are Ontario Municipal Policies Sufficient

for Protecting Suburban Forested Natural Areas for the Long Term? PhD dissertation, University of Waterloo, Waterloo, Ontario, Canada.

Moran, MA. 1984. Influence of adjacent land use on understory vegetation of New York forests. Urban Ecology 8,

329-340. Ontario Ministry of Municipal Affairs and Housing. (2005). Provincial Policy Statement. Ontario Ministry of Municipal

Affairs and Housing, Toronto, Ontario. Region of Waterloo. (2006a). Regional Growth Management Strategy. Department of Planning, Housing and

Community Services, Region of Waterloo, Kitchener, Ontario. Region of Waterloo. (2006b). Regional Official Policies Plan. Region of Waterloo, Kitchener, Ontario. Region of Waterloo. (2006c). Regional Forest Management Plan: Overview and Approach 2007-2026. Region of

Waterloo, Kitchener, Ontario. Region of Waterloo. (2009). Population and Employment Forecasts 2006-2029. Department of Planning, Housing

and Community Services, Region of Waterloo, Kitchener, Ontario. Region of Waterloo. (2010). Regional Official Plan, as approved with, with modifications on Dec. 22, 2010. Region of

Waterloo, Kitchener, Ontario. Region of Waterloo. (2011). Greenlands Network Implementation Guideline. Region of Waterloo, Kitchener, Ontario. Shipley, B. (2010). From Plant Traits to Vegetation Structure: Chance and selection in the assembly of ecological

communities. Cambridge University Press, Cambridge, UK. Statistics Canada. (2013). 2011 Community profiles for Waterloo (City), Kitchener (City), Cambridge (City), Woolwich

(Township), Wellesley (Township), Wilmot (Township) and North Dumfries (Township). Retrieved 3 March, 2013 from http://www12.statcan.gc.ca/census-recensement/2011/dp-pd/prof/index.cfm?Lang=E&MM.

http://www12.statcan.gc.ca/census-recensement/2011/dp-pd/prof/index.cfm?Lang=E&MM


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Appendices


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Appendix A Descriptions of Study Sites

Cambridge Centre Woodlot

This woodlot is visible on aerial photos dating back to 1935 and likely existed prior to the twentieth century. Since the 1950’s it has seen increasing urbanization. Industrial and commercial areas were built along its eastern edge in the 1980’s and 90’s. More recently, residential areas along Lena Crescent were constructed adjacent to the woodlot. Adjacent residential construction was ongoing as recently as 2009. This site includes areas of upland deciduous forest typical of the region with species such as beech, sugar maple, red oak and shagbark hickory. There is a large area of lowland forest that could be considered an ephemeral swamp.

Municipality: Cambridge Area: 17 ha Transects Surveyed: 24 (8 later omitted) Species Recorded: 64 (77% native, 23% non-native, 2.00 species/m

2)


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EDGE CHARACTERISTICS

Three edges were surveyed in this woodlot; one was adjacent to high-density residential land use, one adjacent to low-density residential land use and another adjacent to industrial land use. The last edge segment was deemed too highly degraded to provide any useful data and was omitted from the final data analysis, so only two edge segments (16 transects) were ultimately included from this woodlot. The high-density residential area was separated from the woodlot by a buffer zone, while the low-density residential area was separated by a fence. Biodiversity Patterns: Species richness was higher at 1m from the edge than at 20m from the edge. The mean species richness at 1m was 7.200 species, while the mean species richness at 20m was 6.067 species. This woodlot exhibited the least similarity between “edge” and “interior” quadrats of all the woodlots surveyed (Sorensen Index = 0.068). Species evenness was slightly higher at 1m from the edge (E = 0.750) than at 20m from the edge (E = 0.685). Non-native species were more prevalent at 1m from the edge than at 20m from the edge. On average, 32.2% of species at 1m from the edge were non-native, representing 39.1% of total vegetative cover; at 20m from the edge, 12.0% of species were non-native, representing 6.8% of total vegetative cover. This woodlot exhibited the lowest prevalence of non-native species in its “interior” (20m from the edge) of all woodlots surveyed. Floristic quality was on average lower at 1m from the edge (FQI = 1.516) than at 20m from the edge (FQI = 4.843). Dominant Species: Sixty-four species were recorded along these edges, of which 77% were native and 23% were non-native. At 1m from the high-density residential edge, the most abundant species were garlic mustard (Alliaria petiolata) with 67% cover, red raspberry (Rubus strigosus) with 41% cover and riverbank grape (Vitis riparia) with 38% cover. At 20m from the edge, the most abundant species were eastern white cedar (Thuja occidentalis) with 21% cover and spotted jewelweed (Impatiens capensis) with 20% cover. At 1m from the low-density residential edge, the most abundant species were Kentucky bluegrass (Poa pratensis) and giant goldenrod (Solidago gigantea), both with 22% cover, and crown vetch (Securigera varia) with 21% cover. At 20m from the edge, the most abundant species was skunk cabbage (Symplocarpus foetidus) with 38% cover. NOTABLE OBSERVATIONS

One regionally significant species, flowering raspberry (Rubus odoratus), was recorded here. It is unclear whether this species is naturally occurring or planted; it is a commonly cultivated species but this occurrence was separated from the nearest residential backyard by a fence and there were no visible signs of introduction by residents. In the City of Cambridge’s Official Plan it is zoned Industrial, however it is shown as a Core Environmental Feature on Map 4 of the 2010 Regional Official Plan. SPECIES OBSERVED FAMILY SCIENTIFIC NAME COMMON NAME

CC

1 NATIVE STATUS

2

Sapindaceae Acer rubrum Red Maple 4 Y

Ranunculaceae Actaea pachypoda White Baneberry 6 Y

Apiaceae Aegopodium podagraria Goutweed 0 N

Brassicaceae Alliaria petiolata Garlic Mustard 0 N

Araceae Arisaema triphyllum Jack-in-the-Pulpit 5 Y

Cyperaceae Carex sp. Sedges 5 Y

Betulaceae Carpinus caroliniana American Hornbeam 6 Y

Amaranthaceae Chenopodium album Lamb's-quarters 0 N

Onagraceae Circaea lutetiana Enchanter's Nightshade 3 Y

Lamiaceae Clinopodium vulgare Wild Basil 4 Y

Asparagaceae Convallaria majalis Lily-of-the-Valley 0 N

Cornaceae Cornus alternifolia Pagoda Dogwood 6 Y

Cornaceae Cornus racemosa Grey Dogwood 5 Y

Apiaceae Daucus carota Queen Anne's-Lace 0 N

Dryopteridaceae Dryopteris carthusiana Spinulose Wood Fern 5 Y


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FAMILY SCIENTIFIC NAME COMMON NAME

CC1

NATIVE STATUS2

Dryopteridaceae Dryopteris cristata Crested Wood Fern 7 Y

Orchidaceae Epipactis helleborine Helleborine Orchid 0 N

Equisetaceae Equisetum arvense Field Horsetail 0 Y

Asteraceae Erigeron pulchellus Robin's Plantain 7 Y

Asteraceae Eurybia macrophylla Large-leaf Aster 5 Y

Rhamnaceae Frangula alnus Glossy Buckthorn 0 N

Oleaceae Fraxinus americana White Ash 4 Y

Oleaceae Fraxinus pennsylvanica Green Ash 3 Y

Geraniaceae Geranium maculatum Spotted Geranium 6 Y

Geraniaceae Geranium robertianum Herb-Robert 0 N

Rosaceae Geum macrophyllum Large-leaf Avens 9 Y

Brassicaceae Hesperis matronalis Dame's-Rocket 0 N

Hypericaceae Hypericum perforatum Common St. John's-wort 0 N

Balsaminaceae Impatiens capensis Jewelweed 4 Y

Urticaceae Laportea canadensis Canada Wood Nettle 6 Y

Asteraceae Leucanthemum vulgare Oxeye Daisy 0 N

Caprifoliaceae Lonicera canadensis Canada Honeysuckle 6 Y

Asparagaceae Maianthemum canadense Canada Mayflower 5 Y

Onocleaceae Matteuccia struthiopteris Ostrich Fern 5 Y

Onocleaceae Onoclea sensibilis Sensitive Fern 4 Y

Oxalidaceae Oxalis stricta Wood Sorrel 0 Y

Vitaceae Parthenocissus vitacea Virginia Creeper 0 Y

Plantaginaceae Plantago major Round-leaf Plantain 0 Y

Poaceae Poa pratensis Kentucky Bluegrass 0 Y

Salicaceae Populus balsamifera Balsam Poplar 4 Y

Salicaceae Populus tremuloides Trembling Aspen 2 Y

Rosaceae Prunus virginiana Choke Cherry 2 Y

Pyrolaceae Pyrola elliptica Shinleaf 5 Y

Fagaceae Quercus macrocarpa Bur Oak 5 Y

Ranunculaceae Ranunculus abortivus Little-leaf Buttercup 2 Y

Rhamnaceae Rhamnus cathartica European Buckthorn 0 N

Grossulariaceae Ribes americanum American Gooseberry 4 Y

Grossulariaceae Ribes lacustre Swamp Gooseberry 7 Y

Rosaceae Rubus strigosus Common Raspberry 1 Y

Rosaceae Rubus odoratus Flowering Raspberry * 3 Y

Rosaceae Rubus pubescens Dwarf Raspberry 4 Y

Fabaceae Securigera varia Crown Vetch 0 N

Asteraceae Solidago canadensis Canada Goldenrod 1 Y

Asteraceae Solidago gigantea Giant Goldenrod 4 Y

Araceae Symplocarpus foetidus Skunk Cabbage 7 Y

Asteraceae Taraxacum officinale Dandelion 0 N

Cupressaceae Thuja occidentalis Eastern White Cedar 4 Y

Saxifragaceae Tiarella cordifolia Foamflower 6 Y

Anacardiaceae Toxicodendron radicans Poison Ivy 5 Y

Fabaceae Trifolium repens Field Clover 0 N

Ulmaceae Ulmus americana American Elm 3 Y

Adoxaceae Viburnum trilobum Highbush Cranberry 5 Y

Violaceae Viola sp. Violet 3 Y

Vitaceae Vitis riparia Riverbank Grape 0 Y

* Denotes a regionally significant species. 1 Coefficient of conservatism: 0 is weedy or non-native, 10 is highest (Source: Natural Heritage Information Centre, 2012; some

species were classed by me). 2 Y = native, N = non-native (Source: Natural Heritage Information Centre, 2012).


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Homer Watson Park

Homer Watson Park is part of a larger system of parks located along the Grand River in the south end of

Kitchener. The portion of the park surveyed for this project is located between Manitou Drive, Wabanaki Drive and Wilson Avenue. The forest has existed since at least the 1930’s and parts of it could likely be considered old-growth. Some large and striking red oak and eastern hemlock trees occur here.

Municipality: Kitchener Area: 23 ha Transects Surveyed: 8 Species Recorded: 40 (70% native, 30% non-native, 2.50 species/m

2)


Only one edge was surveyed in Homer Watson Park. The adjacent land use type was primarily light industrial with some commercial uses. Most of this edge was divided from the adjacent human land uses by a fence.


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Biodiversity Patterns: Homer Watson Park was the only woodlot surveyed that exhibited higher species richness in its “interior” than at its edge. On average, 6.125 species were observed at 1m from the edge, while 8.875 species were observed at 20m from the edge. On average, the similarity between the “edge” and “interior” quadrats was low (Sorensen Index = 0.109). Species evenness was, on average, higher at 1m from the edge (E = 0.758) than at 20m from the edge (E = 0.560). Non-native species were more prevalent at 1m from the edge than at 20m from the edge. On average, 58.1% of species at 1m from the edge were non-native, representing 60.4% of total vegetative cover, compared to 35.3% of species at 20m from the edge, or 39.6% of total vegetative cover. Interestingly, Homer Watson Park exhibited the greatest prevalence of non-native species in its “interior” of all the woodlands surveyed. The most abundant non-native species were garlic mustard (Alliaria petiolata) and Herb-Robert (Geranium robertianum), the former of which is considered highly invasive. Floristic quality was lower at 1m from the edge (FQI = 1.192) than at 20m from the edge (FQI = 2.698). Dominant Species: Forty species were recorded along this edge, of which 70% were native and 30% were non-native. The most abundant species at 1m from the edge were garlic mustard (Alliaria petiolata) at 31% cover and Herb-Robert (Geranium robertianum) at 25% cover. The most abundant species at 20m from the edge were garlic mustard with 64% cover, sedges (Carex spp.) with 47% cover, Herb-Robert with 26% cover and poison ivy (Toxicodendron radicans) with 21% cover. NOTABLE OBSERVATIONS

One regionally significant species, Virginia stickseed (Hackelia virginiana), was recorded here. The understory of

the forest is dominated by a “sedge mat,” a characteristic of healthy Carolinian woodlots. SPECIES OBSERVED FAMILY SCIENTIFIC NAME COMMON NAME

CC

1 NATIVE STATUS

2

Sapindaceae Acer saccharum Sugar Maple 4 Y


Araliaceae Aralia nudicaulis Wild Sarsaparilla 4 Y


Berberidaceae Caulophyllum thalictroides Blue Cohosh 5 Y

Papaveraceae Chelidonium majus Greater Celandine 0 N

Onagraceae Circaea alpina Dwarf Enchanter's Nightshade 6 Y




Rubiaceae Galium mollugo Upright Bedstraw 0 N


Rosaceae Geum laciniatum Slashed Avens 4 Y

Boraginaceae Hackelia virginiana Virginia Stickseed * 5 Y

Hypericaceae Hypericum mutilum Dwarf St. John's-wort 5 Y

Lamiaceae Leonurus cardiaca Motherwort 0 N


Asparagaceae Maianthemum racemosum False Solomon's-seal 4 Y

Apiaceae Osmorhiza claytonii Sweet Cicely 5 Y

Phrymaceae Phryma leptostachya Lopseed 6 Y

Poaceae Poa sp. Bluegrass 1 Y

Asteraceae Prenanthes altissima Tall Rattlesnakeroot 5 Y

Rosaceae Prunus serotina Black Cherry 3 Y


Fagaceae Quercus rubra Red Oak 6 Y




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Fabaceae Securigera varia Crown Vetch 0 N

Rubiaceae Sherardia arvensis Field Madder 0 N

Solanaceae Solanum dulcamara Blue Nightshade 0 N

Asteraceae Solidago caesia Blue-stem Goldenrod 5 Y


Asteraceae Solidago flexicaulis Zig-zag Goldenrod 6 Y



Plantaginaceae Veronica officinalis Common Speedwell 0 N

Plantaginaceae Veronica serpyllifolia Thyme-leaved Speedwell 0 N






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McLennan Park

This five-hectare woodland fragment is located in the eastern corner of McLennan Park with access points from the park itself and Blackhorne Drive. It is primarily upland deciduous forest with species typical of the Region including red maple, eastern hemlock, white ash and green ash.


2)


Two edges were surveyed in the McLennan Park woodlot, both of which were adjacent to low-density residential land use. The northeast edge was mostly not separated from adjacent land uses by either a fence or buffer zone, although a few backyards had fences. The south edge was entirely separated from adjacent land uses by a fence


44

Biodiversity Patterns: Like most other woodlands, the McLennan Park forest had higher species richness at its “edge” than in its “interior”. There was low similarity between the edge and interior quadrats (Sorensen Index = 0.138). On average, 6 species were observed at 1m from the edge and 4.933 species were observed at 20m from the edge. On average, species evenness was virtually the same at 1m from the edge (E = 0.671) as at 20m from the edge (E = 0.670). Non-native species were also more prevalent at the “edge” than the “interior”. On average, 41.5% of species at 1m from the edge were non-native, or45.8% of total vegetative cover, compared to 25.9% of species, or 34% of total vegetative cover, at 20m from the edge. Floristic quality was lower at 1m from the edge (FQI = 1.742) than at 20m from the edge (FQI = 4.843). Dominant Species:. At 1m from the northeast edge, the most abundant species were garlic mustard (Alliaria petiolata) with 55% cover and spotted jewelweed (Impatiens capensis) with 51% cover. These were also the most abundant species at 20m from the edge, but in reverse order with jewelweed covering 60% and garlic mustard covering 56%. At 1m from the south edge, the most abundant species were garlic mustard with 30% cover, periwinkle (Vinca minor) with 23% cover and choke cherry (Prunus virginiana) with 20% cover. At 20m from the edge, the most abundant species was garlic mustard with 31% cover. NOTABLE OBSERVATIONS

Several butternut (Juglans cinerea) trees were observed in this woodlot. Butternut is listed as endangered both

federally and provincially. All of the trees observed in McLennan Park were infected with butternut canker, although little canopy dieback was visible. SPECIES OBSERVED FAMILY SCIENTIFIC NAME COMMON NAME

CC

1 NATIVE STATUS

2

Sapindaceae Acer saccharinum Silver Maple 5 Y

Sapindaceae Acer spicatum Mountain Maple 6 Y



Asteraceae Arctium lappa Giant Burdock 0 N


Aristolochiaceae Asarum canadense Wild Ginger 6 Y

Asteraceae Bidens frondosa Large-leaved Beggarticks 3 Y

Urticaceae Boehmeria cylindrica Small-spike False-nettle 4 Y




Dryopteridaceae Dryopteris sp. Wood Fern 5 Y

Asteraceae Erigeron philadelphicus Philadelphia Fleabane 1 Y




Rosaceae Geum aleppicum Yellow Avens 2 Y

Lamiaceae Glechoma hederacea Creeping Charlie 0 N

Xanthorrhoeaceae Hemerocallis fulva Day Lily 0 N

Brassicaceae Hesperis matronalis Dame's-Rocket 0 N

Asparagaceae Hosta sp. Hosta 0 N


Juglandaceae Juglans cinerea Butternut * 6 Y

Lamiaceae Lamium maculatum Spotted Deadnettle 0 N





45


CC1

NATIVE STATUS2

Lamiaceae Melissa officinalis Lemon Balm 0 N



Urticaceae Pilea pumila Clearweed 5 Y


Ranunculaceae Ranunculus recurvatus Hooked Crowsfoot 4 Y



Papaveraceae Sanguinaria canadensis Bloodroot 5 Y



Oleaceae Syringa vulgaris Lilac 0 N




Liliaceae Trillium grandiflorum White Trillium 5 Y

Urticaceae Urtica dioica Stinging Nettle 2 Y


Apocynaceae Vinca minor Periwinkle 0 N





46

Stanley Park

Only the northern block of Stanley Park was included in this study (the area north of River Road East). The woodland is bisected by a stream and is dominated by transitional lowland-upland forest.


2)


One edge was surveyed in Stanley Park. This edge was adjacent to high-density residential land use and was not divided from human land uses by either a fence or a buffer zone. Biodiversity Patterns: Stanley Park had the highest “edge” species richness of all the woodlands surveyed. On average, 10.429 species were observed at 1m from the edge and 5.286 species were observed at 20m from the


47

edge. This is largely due to species escaping cultivation from gardens in the adjacent apartment complex. There was low similarity between “edge” and “interior” quadrats (Sorensen Index = 0.143). Species evenness was, on average, lower at 1m from the edge (E = 0.497) than at 20m from the edge (E = 0.618). Non-native species were more prevalent at the “edge” than in the “interior”. On average, 51.4% of species at 1m from the edge were non-native, or 63.9% of total vegetative cover, compared to 32.3% of species, or 35.2% of total vegetative cover, at 20m from the edge. Stanley Park had the lowest floristic quality at both the “edge” and “interior” of all the woodlands surveyed. The FQI was 0.753 at 1m from the edge and 2.579 at 20m from the edge. This indicates that weedy, generalist species are more prevalent in this woodland, and it may suggest that Stanley Park is the most disturbed of all the woodlands included in this study. Dominant Species: At 1m from the edge, the most abundant species were garlic mustard (Alliaria petiolata) with 78% cover, Kentucky bluegrass (Poa pratensis) with 23% cover and violets (Viola sp.) with 21% cover. At 20m from the edge, the most abundant species were spotted jewelweed (Impatiens capensis) with 89% cover and garlic mustard with 69% cover. NOTABLE OBSERVATIONS

No unusual species or other features of note were observed in this woodland.

SPECIES OBSERVED FAMILY SCIENTIFIC NAME COMMON NAME

CC

1 NATIVE STATUS

2

Sapindaceae Acer negundo Boxelder Maple 0 Y






Asteraceae Erigeron philadelphicus Philadelphia Fleabane 1 Y



Rubiaceae Galium mollugo Upright Bedstraw 0 N




Lamiaceae Glechoma hederacea Creeping Charlie 0 N



Oleaceae Ligustrum vulgare European Privet 0 N

Boraginaceae Myosotis scorpioides Forget-me-not 0 N


Polygonaceae Persicaria maculosa Spotted Lady's-thumb 0 N







Asteraceae Solidago gigantea Giant Goldenrod 4 Y



Asteraceae Tussilago farfara Colt's Foot 0 N



48


CC1

NATIVE STATUS2





49

Steckle’s Woods

This 27-hectare woodland fragment was the largest woodland included in this study. The woodland is primarily upland deciduous forest and includes a large number of impressive red oaks, beeches and sugar maples. There is an extensive network of formal and informal trails throughout the woodland, which accounts for the heavy degree of invasion by species such as garlic mustard in the woodland interior. Nonetheless, there remains an impressive diversity of native herbaceous species.


2)

EDGE CHARACTERISTICS Biodiversity Patterns: Like most other woodlands, Steckle’s Woods exhibited higher species richness at its “edge” than in its “interior”. On average, 9.5 species were observed at 1m from the edge and 7 species were observed at 20m from the edge. There was low similarity between “edge” and “interior” quadrats (mean Sorensen Index =


50

0.107). Species evenness was, on average, lower at 1m from the edge (E = 0.598) than at 20m from the edge (E = 0.744). Steckle’s Woods had the lowest prevalence of non-native species at its “edge” of any of the woodlands surveyed (though not in its “interior”). It was also the only woodland in which non-native species were more prevalent in the “interior” than at the “edge”. On average, 20.2% of species at 1m from the edge were non-native, representing 27.1% of total vegetative cover, compared to 25.1% of species, or 25.9% of total vegetative cover, at 20m from the edge. This is due to the heavy presence of garlic mustard (Alliaria petiolata), a well-known invasive species, in the woodland’s interior. Nonetheless, floristic quality was still lower at 1m from the edge (FQI = 2.786) than at 20m from the edge (FQI = 3.446). Dominant Species: One edge was surveyed at Steckle’s Woods. This edge was adjacent to primarily industrial land uses and was separated from these land uses by a wide buffer zone. The most abundant species recorded at 1m from the edge were European buckthorn (Rhamnus cathartica) with 36% cover, choke cherry (Prunus virginiana) with 31% cover, field brome-grass (Bromus arvensis) with 21% cover and large-flowered bellwort (Uvularia grandiflora) with 21% cover. The most abundant species at 20m from the edge were white trillium (Trillium grandiflorum) with 30% cover and garlic mustard (Alliaria petiolata) with 24% cover. NOTABLE OBSERVATIONS

Steckle’s Woods had the highest number of species recorded per square meter of any of the woodlots studied

(2.81 species/m2). One regionally significant species was recorded in Steckle’s Woods: squawroot (Conopholis

americana), a unique plant that parasitizes the roots of trees in the beech family (Fagaceae). A large number of these plants were observed. There are some remarkably large trees in the woodlot and it supports a diversity of wildlife, especially birds. Steckle’s Woods exhibited a high degree of garlic mustard invasion and this may prove to have a large impact on biodiversity in the future.


CC

1 NATIVE STATUS

2


Ranunculaceae Actaea rubra Red Baneberry 5 Y


Apocynaceae Apocynum androsaemifolium Spreading Dogbane 3 Y



Poaceae Bromus arvensis Field Bromegrass 0 N

Cyperaceae Carex albursina White Bear Sedge 7 Y


Juglandaceae Carya cordiformis Bitternut Hickory 6 Y


Lamiaceae Clinopodium vulgare Wild Basil 4 Y

Orobanchaceae Conopholis americana Squawroot * 9 Y


Liliaceae Erythronium americanum Yellow Trout Lily 5 Y

Celastraceae Euonymus obovatus Running Strawberry-bush 6 Y

Rosaceae Fragaria virginiana Wild Strawberry 2 Y


Rosaceae Geum canadense White Avens 3 Y

Ranunculaceae Hepatica acutiloba Sharp-lobed Hepatica 5 Y




Betulaceae Ostrya virginiana Hophornbeam 4 Y



51


CC1

NATIVE STATUS2




Grossulariaceae Ribes cynosbati Prickly Gooseberry 4 Y



Smilacaceae Smilax herbacea Smooth Carrion Flower 5 Y


Asteraceae Solidago caesia Blue-stem Goldenrod 5 Y


Liliaceae Streptopus lanceolatus Twisted-stalk 7 Y

Asteraceae Tanacetum vulgare Tansy 0 N


Ranunculaceae Thalictrum dioicum Early Meadow-rue 5 Y

Malvaceae Tilia americana Basswood 4 Y

Melanthiaceae Trillium grandiflorum White Trillium 5 Y

Colchicaceae Uvularia grandiflora Great Bellflower 6 Y

Adoxaceae Viburnum lentago Nannyberry 4 Y






52

Strasburg Woods

The western half of this five-hectare woodland is shown as low-density residential land use in the Regional Official Plan (ROP) and it may be privately owned. The woodland is primarily upland deciduous forest with small pockets of ephemeral wetlands in the western portion. There is also an area of red pine plantation at the centre of the woodland. The most common tree species are typical of the region including sugar maple and green ash.


2)


Three edges were surveyed at Strasburg Woods. Of these, two were adjacent to high-density residential land uses and one was adjacent to commercial land uses. Most of these land uses were not separated from the woodlot by a fence or buffer zone, however a few areas did have fences. The western edge of the woodlot was adjacent to commercial land uses and had neither a fence nor a buffer zone. The northern edge of the woodlot was adjacent to


53

high-density residential land uses and was separated from these land uses by a fence. The southern edge of the woodlot was adjacent to high-density residential land uses and was separated in some places by a fence, although many sections had no edge treatment at all. Biodiversity Patterns: Like most other woodlands, Strasburg Woods exhibited higher species richness at its “edge” than in its “interior”. However, despite the high sampling density (24 quadrats), Strasburg Woods exhibited the lowest mean species richness in both its “edge” and “interior” of any of the woodlands surveyed. On average, 5.292 species were observed at 1m from the edge, while 4.875 species were observed at 20m from the edge. Similarity between “edge” and “interior” quadrats was higher in Strasburg Woods than any other woodlot, but it was still quite low (mean Sorensen Index = 0.183). Species evenness was, on average, slightly lower at 1m from the edge (E = 0.680) than at 20m from the edge (E = 0.745). Non-native species were more prevalent at the “edge” of the woodland than the “interior”. On average, 37.6% of species at 1m from the edge were non-native, representing 44.1% of total vegetative cover, compared to 21.9% of species, or 23.5% of total vegetative cover, at 20m from the edge. Floristic quality was, like other woodlands, lower at 1m from the edge (FQI = 1.746) than at 20m from the edge (FQI = 2.941). Dominant Species: At 1m from the western edge, the most abundant species were European buckthorn (Rhamnus cathartica) with 63% cover, and red-osier dogwood (Cornus sericea) with 26% cover. At 20m from the edge, the most abundant species was European buckthorn with 37% cover. At 1m from the northern edge, the most abundant species were ostrich fern (Matteuccia struthiopteris) with 48% cover, garlic mustard (Alliaria petiolata) with 38% cover and choke cherry (Prunus virginiana) with 20% cover. At 20m from the edge, the most abundant species were enchanter’s nightshade (Circaea lutetiana) with 36% cover and ostrich fern with 22% cover. At 1m from the southern edge, the most abundant species were European buckthorn with 27% cover and garlic mustard with 21% cover. At 20m from the edge, the most abundant species were European buckthorn with 31% cover and sedge species (Carex spp.) with 26% cover. NOTABLE OBSERVATIONS

Several occurrences of butternut (Juglans cinerea) were observed in Strasburg Woods. This is a federally and provincially endangered species. Many dead individuals were recorded and all of the living individuals were infected by butternut canker. As mentioned above, Strasburg Woods exhibited low species richness compared to other woodlands surveyed. Vegetative cover was also comparatively low, with large areas of bare ground. There are various possible reasons for this: it may be a legacy of past disturbances, such as agriculture, or it may be due to soil compaction from recreational activities within the woodland. It may also be a symptom of a heavy earthworm invasion, which are known to impact vegetation density (see, for example, Frelich et al., 2006; Eisenhauer et al., 2007).


CC

1 NATIVE STATUS

2



Ranunculaceae Anemone virginiana Thimbleweed 4 Y

Apocynaceae Apocynum androsaemifolium Spreading Dogbane 3 Y



Cyperaceae Carex intumescens Bladder Sedge 6 Y



Asteraceae Cirsium vulgare Bull Thistle 0 N


Cornaceae Cornus sericea Red-osier Dogwood 2 Y



54


CC1

NATIVE STATUS2

Fagaceae Fagus grandifolia Beech 6 Y

Rosaceae Fragaria virginiana Wild Strawberry 2 Y




Rosaceae Geum canadense White Avens 3 Y



Juglandaceae Juglans cinerea Butternut * 6 Y









Poaceae Poa sp. Bluegrass 1 Y

Salicaceae Populus grandidentata Bigtooth Aspen 5 Y




Ranunculaceae Ranunculus acris Meadow Buttercup 0 N


Anacardiaceae Rhus typhina Staghorn Sumac 1 Y




Salicaceae Salix discolor Pussy Willow 3 Y




Asteraceae Solidago sp. Goldenrod 1 Y


Plantaginaceae Veronica serpyllifolia Thyme-leaved Speedwell 0 N




* Denotes a regionally significant species 1 Coefficient of conservatism: 0 is weedy or non-native, 10 is highest (Source: Natural Heritage Information Centre, 2012; some



55

Sugarbush Park

This 12-hectare woodland was the only woodland surveyed in the City of Waterloo. As its name suggests, it was historically a sugar bush, and the diversity of tree species reflects historical selection for sugar maple as this species is disproportionately dominant. Other species include basswood, white ash and green ash.

Municipality: Waterloo Area: 12 ha Transects Surveyed: 32 Species Recorded: 76 (62% native, 38% non-native, 1.19 species/m

2)


Four edge segments were surveyed at Sugarbush Park, the most of any of the woodlots studied. This accounts for the high number of species recorded here, however the number of species recorded per square meter was low (1.19 species/m

2). Two edge segments were adjacent to low-density residential land use, one was adjacent to high-

density residential land use and one was adjacent to commercial land use. The northern edge of the woodlot was adjacent to low-density residential land use. Most of the properties adjacent to the woodlot along this edge were


56

divided from it by a fence, however some had no edge treatment. The southern edge of the woodlot was also adjacent to low-density residential land use. Most of the properties along this edge neither a fence nor a buffer zone dividing them from the woodlot, although a few did have fences. The western edge of the woodlot was divided into two segments: the northern segment was adjacent to high-density residential land use and the southern segment was adjacent to commercial land use. Neither of these land uses was divided from the woodland by either a fence or a buffer. Biodiversity Patterns: Like most other woodlands, Sugarbush Park exhibited lower species richness at its “edge” than in its “interior”. On average, 5.581 species were observed at 1m from the edge, compared to 4.484 species at 20m from the edge. Similarity between “edge” and “interior” quadrats was low (mean Sorensen Index = 0.135). On average, species evenness was virtually the same at 1m from the edge (E = 0.670) as at 20m from the edge (E = 0.674). Non-native species were more prevalent at the “edge” of the woodland than the “interior”. On average, 42% of species at 1m from the edge were non-native, or 45.8% of total vegetative cover, compared to 20.3% of species, or 14.7% of total vegetative cover, at 20m from the edge. Floristic quality was lower at 1m from the edge (FQI = 1.668) than at 20m from the edge (FQI = 3.831). Dominant Species: At 1m from the northern edge, the most abundant species were Herb-Robert (Geranium robertianum) with 37% cover, periwinkle (Vinca minor) with 33% cover and choke cherry (Prunus virginiana) with 31% cover. At 20m from the edge, the most abundant species was sugar maple (Acer saccharum) with 44% cover. At 1m from the southern edge, the most abundant species were periwinkle with 29% cover, Canada waterleaf (Hydrophyllum canadense) with 24% cover and violets (Viola sp.) with 22% cover. At 20m from the edge, the most abundant species were sugar maple with 35% cover, Herb-Robert with 23% cover and Canada waterleaf with 22% cover. At 1m from the high-density residential edge, the most abundant species were Herb-Robert with 37% cover and sugar maple with 30% cover. At 20m from the edge, the most abundant species were sugar maple with 44% cover and choke cherry with 20% cover. At 1m from the commercial edge, the most abundant species was Virginia-creeper (Parthenocissus vitacea) with 23% cover. At 20m from the edge, the most abundant species was running strawberry-bus (Euonymus obovatus) with 23% cover. NOTABLE OBSERVATIONS

The large beds of Canada waterleaf (Hydrophyllum canadense) are a remarkable feature. Although not considered a rare species, it is unusual to see this plant in such prevalence.


CC

1 NATIVE STATUS

2

Sapindaceae Acer ginnala Amur Maple 0 N





Amaryllidaceae Allium tricoccum Wild Leek 7 Y

Ranunculaceae Aquilegia vulgaris Garden Columbine 0 N




Asclepiadaceae Asclepias syriaca Common Milkweed 0 Y


Berberidaceae Caulophyllum thalictroides Blue Cohosh 5 Y



Onagraceae Circaea alpina Dwarf Enchanter's Nightshade 6 Y



57


CC1

NATIVE STATUS2

Asteraceae Cirsium arvense Field Thistle 0 N

Asparagaceae Convallaria majalis Lily-of-the-Valley 0 N


Cornaceae Cornus racemosa Grey Dogwood 5 Y

Rosaceae Crataegus punctata Dotted Hawthorn 4 Y




Euphorbiaceae Euphorbia peplus Petty Spurge 0 N



Rubiaceae Galium triflorum Fragrant Bedstraw 4 Y



Rosaceae Geum macrophyllum Large-leaf Avens 9 Y

Xanthorrhoeaceae Hemerocallis fulva Day Lily 0 N

Hydrophyllaceae Hydrophyllum canadense Canada Waterleaf 8 Y

Hydrophyllaceae Hydrophyllum virginianum Virginia Waterleaf 6 Y

Aquifoliaceae Ilex aquifolium English Holly 0 N

Asteraceae Lactuca serriola Wild Lettuce 0 N





Asteraceae Matricaria discoidea Pineapple-weed 0 N


Boraginaceae Myosotis scorpioides Forget-me-not 0 N

Betulaceae Ostrya virginiana Hophornbeam 4 Y



Polygonaceae Persicaria maculosa Spotted Lady's-thumb 0 N


Plantaginaceae Plantago major Round-leaf Plantain 0 Y


Salicaceae Populus tremuloides Trembling Aspen 2 Y

Lamiaceae Prunella vulgaris Heal-all 5 Y






Grossulariaceae Ribes sativum Garden Currant 0 N

Rosaceae Rosa X sp. Cultivated Rose 0 N

Rosaceae Rubus idaeus Common Raspberry 1 Y

Adoxaceae Sambucus racemosa Red Elderberry 5 Y





Rosaceae Sorbus aucuparia European Rowan 0 N

Liliaceae Streptopus lanceolatus Twisted-stalk 7 Y

Oleaceae Syringa vulgaris Lilac 0 N


58


CC1

NATIVE STATUS2


Malvaceae Tilia americana Basswood 4 Y

Malvaceae Tilia cordata European Linden 0 N

Ulmaceae Ulmus rubra Slippery Elm 6 Y


Apocynaceae Vinca minor Periwinkle 0 N





Effects of Urbanization on Vegetation Diversity at the Edges of Regional Woodlands William Van Hemessen Candidate for Master of Environmental Studies School of Planning, University of Waterloo May, 2013

thesis report for region

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