TERRESTRIAL NATURAL HERITAGE SYSTEM STRATEGY

TERRESTRIAL NATURALHERITAGE SYSTEM STRATEGY

APPENDIX E:EVALUATING AND DESIGNING

TERRESTRIAL NATURAL HERITAGE SYSTEMS

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T a b l e o f C o n T e n T s

1.0 IntroductIon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.2 Study Area definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.0 dAtA collectIon And PrePArAtIon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.1 technology required . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.2 Habitat and land use definition. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

3.0 evAluAtIng tHe terreStrIAl nAturAl HerItAge SyStem . . . . . . . . . . . . . . . . . .11

3.1 Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

3.2 distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

3.3 Quantity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12

4.0 tArget SyStem deSIgn model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

4.1 value Surface Approach (raster Analysis) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

4.2 mapping the target tnH System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

4.3 tnH target System design Steps (a to m) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

5.0 reSultS (of tHe trcA ProceSS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

5.1 Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

5.2 distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

5.3 Quantity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

6.0 refInementS to tHe tArget tnH SyStem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

6.1 terrestrial refinements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

6.2 Integration with other ecological, Political and Social criteria . . . . . . . . . . . . . . . . . . . . . . . 3

6.3 further Application of models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

7.0 AcknowledgementS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

8.0 defInItIonS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

9.0 referenceS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

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C H A P T E R

1tAbleS, fIgureS, mAPS, And APPendIceS

table 1: Summary of habitat type and land use definitions used to delineate polygons

table 2: criteria layers in the value surface analysis

table 3: Assumptions built into the value system analysis process

figure 1: criteria overlay and addition to create a total score value surface

map 1: expanding (buffering) existing natural cover by 30 meters

Appendix e-1: landscape analysis methodology

Appendix e-2: target system design model- value surface criteria

Appendix e-3: layers used for each raster criteria

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1 . 0 I n T R o D U C T I o n

1 . 1 P U R P o s e

based on the distribution of species and vegetation communities within its jurisdiction, the trcA

determined that the existing biodiversity within its area of jurisdiction would not withstand

the impact of projected urbanization in the region. trcA set targets for quality, distribution

and quantity of natural cover that would contribute to sustainability of the region (see “Setting

terrestrial natural System targets”, trcA 2007a). to achieve these targets would require an

expansion of the system. trcA used predictive modeling to raise the awareness of municipalities,

watershed councils and other stakeholders, of the need to expand the natural system in light of

projected future growth. the concept was generally supported and trcA developed a raster-based

model that would assist in determining the appropriate placement of the expansion of the system to

most efficiently meet the targets.

this report follows “Setting terrestrial natural System targets” (trcA 2006 a) to explain the more

technical side of the initiative; it details the tools and methods used for evaluating and designing

natural system scenarios. It provides enough detail to assist other agencies and groups in using gIS

to replicate the process in their own work.

1 . 2 s T U D y a R e a D e f I n I T I o n

the study area is defined by the boundary of the toronto and region conservation Authority

jurisdiction, which encompasses the etobicoke, miimico, Humber, don, Highland, rouge, Petticoat,

duffins and carruthers river watersheds, and the lake ontario shoreline from mississauga to

Ajax. the statistics and calculations presented in this report are based on data collected within this

study area, including habitat patches that straddle both the trcA watershed and neighbouring

watersheds. However, this methodology has been designed to be transferable to other jurisdictions

and at varying scales such as a municipality, watershed, or subwatershed.

2 . 0 D a T a C o l l e C T I o n a n D P R e P a R a T I o n

2 . 1 T e C h n o l o g y R e q U I R e D

In a region of rapid land use change, analyzing the landscape must be based on the most recent

information possible. the data required for this landscape level approach include remote-sensed

imagery and digitized habitat patches. Polygons can be digitized using Arcview gIS software ‘on

screen’, if digital aerial photography is available, or using

hard copy aerial photos on a digitizing tablet. once more

recent digital aerial photography is made available, updates to

polygon boundaries can be made to reflect and track changes

in land use. other sources of data, such as ecological land

classification data can be used in place of remotely sensed

broad habitat categories, where this exists.

the landscape Analysis (vector-based) model (Appendix e-1) was created using custom scripts and

dialogs written in Avenue using Arcview 3.2 with Spatial Analyst. the System design (raster-based)

model was created using Arcmap (8.2 or greater) with Spatial Analyst and model builder. the

software was run on a Pc platform or winXP oS.

2 . 2 h a b I T a T a n D l a n D U s e D e f I n I T I o n

before a natural system can be evaluated it is necessary to define

the categories of land cover that will be used in the analysis (as

listed in table 1). trcA has mapped four broad categories of

natural cover, namely forest, successional (which is included

with forest when evaluating natural cover), wetland, cultural

meadow, and shoreline habitats such as beach, dune, or bluff.

urban and agricultural cover is also digitized as two broad land

use categories. these broad categories should not be confused with the more detailed, field-collected

vegetation communities also used in tnH Program protocols and reports (see trcA 2006 b and c).

Habitat patch A distinct, separately mapped block (polygon) of one type of natural cover. Thus, a block of forest and an abutting block of wetland are two separate habitat patches.

Urban land coverIn creating this layer, both the digitized urban cover and the extent of urban cover as shown in municipal official plans were combined.

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trcA most recently mapped habitat patches according to the four categories using 2002 digital

ortho-rectified aerial (spring) photography at a scale of 1:4000. main roads and wide trails were

considered breaks in habitat patches if they were 25 meters wide or more. road surfaces were then

considered an “urban” land use, as per the definition of “urban” in table 1 (refer to Appendix e-2

for a more detailed description of habitat types and land use types used for the landscape level of

analysis). wide rivers were also considered to be separate habitat patches; no width threshold was

used, but where rivers or creeks created an obvious break in the canopy at a scale of 1: 4000, habitat

polygons were divided. thus, discrete habitat patch polygons were digitized and interpreted as

forest, successional, wetland, meadow and beach/bluff.

other layers required for the analysis are a detailed road layer, watercourse layer, and water body

layer (See Appendix e-3 for a list of all layers used in the raster analysis).

Table 1: Summary of the habitat type and land use patch definitions used to delineate polygons.

HAbITAT TYPE oR LAND USE

CoMMUNITY TYPES CoNSIDERED MINIMUM PATCH SIzE

Forest coniferous, mixed, deciduous forest communities,b plantations, treed-swamps * treed swamps were included here because of the challenge in consistent interpretation at a remote sensing level, and that forest and swamps provide many of the same functions for avifauna.

0.5 ha based on ELC guide using 1:10 000 air photos, can be slightly smaller when using 1:4000 scale as a base and when small patch is deemed valuable to system

Successional cultural woodlands and thickets. These are digitized separate from forest, but are included within the forest category for the evaluation of natural cover quality.


Wetland shallow marsh, meadow marsh, shallow aquatic ponds (where water is known to be less than 2 m deep), thicket swamps and treed-swamps where known to exist; meadow marsh often indistinguishable from drier meadows cannot always be mapped accurately unless known to exist

no limit was set; wetlands often occur naturally as small pockets in the landscape; if discernable at 1:4000, it is mapped

Meadow old field habitat or cultural meadows, natural tallgrass prairie, sand barren and sometimes meadow marsh are included in this category


beach/bluff natural barren coastal habitats not corresponding to other habitat types, including natural beach, coastal dunes and bluffs

no limit was set; beach/bluff habitats often occur as small features in the landscape; if a beach/bluff type is discernable at a scale of 1:4000 it is mapped

Agricultural croplands, fruit tree plantations, and pastures (may also include golf courses and aggregate extraction pits within a rural matrix)

no minimum sizes are assigned to agricultural and urban land use types

Urban “urban” areas are considered any part of the landscape that has been modified primarily for human use other than agriculture/forestry; includes residential, commercial, industrial land, roads. Also includes manicured areas such as cemeteries, golf courses, and parkland (due to intensity of management and potential negative impacts on natural areas).

no minimum sizes are assigned to agricultural and urban land use types

3 . 0 e v a l U a T I n g T h e T e R R e s T R I a l n a T U R a l h e R I T a g e s y s T e m

A number of parameters were considered to describe the natural system in the TRCA region

(Appendix E-1) but three were selected to evaluate and set objectives or targets for the TNH

System. These measures, the quality, distribution and quantity of natural cover, were chosen

because they summarize the bulk of the changes in the natural cover of the Toronto region

over the last few centuries. The following explains how all three measures are interdependent

and how each is considered in relation to the others.

3 . 1 q U a l I T y

this “quality” measure is defined here by trcA as the natural system quality, as seen from the air

(remote-sensed), and serves as a proxy (or predictor) of the species composition and the condition

of ecosystems, as seen from the ground. based on terrestrial landscape ecology principles, system

quality begins with quality of individual patches, which is calculated from their size, shape, and

matrix (the land cover around them). the natural system quality is determined by considering the

quality of all patches together as a system. the presence or absence, abundance and the diversity

of species and vegetation communities (including Species of concern) tends to be determined by

patch quality.

the evaluation of quality was conducted using a landscape analysis model (lAm) to summarize

the natural system’s potential to support Species of concern by calculating size, shape and matrix

influence of all individual patches. then the patch results are considered across the region together

as a system. for details on the lAm, see Appendix e-1.

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3 . 2 D I s T R I b U T I o n

this is defined by trcA as the distribution of a certain quality of patches or natural cover across

the landscape. therefore, considering the interdependence of these measures, the distribution is not

just about distributing natural cover but about distributing a given quality of the natural cover. for

example, natural cover may be well distributed but its quality may not necessarily support Species

of concern if the patches are not of an appropriate size, shape and matrix. therefore it is also

important to consider the distribution of different levels of quality of natural cover/habitat patches

across the region.

to evaluate distribution, trcA has overlaid grids of various square sizes on scenarios of natural

cover and both calculated the amount of natural cover per grid square and visually assessed the

distribution of natural cover and habitat quality. A centroid method was also used to represent the

center of mass of natural cover (or of Species of concern data) in the region. given the stratified

character of the natural cover within the trcA jurisdiction distribution needs to be considered at

different scales. distribution will be further assessed at more local scales, for example, through the

watershed and subwatershed planning processes.

3 . 3 q U a n T I T y

Quantity is also the amount of natural cover proportional to the total land surface area of the

region. Also an interdependent factor, quantity is the amount of natural cover required to achieve

the desired quality distribution explained above.

Quantity is calculated as the per cent natural cover for the region, but is also calculated in hectares.

4 . 0 T a R g e T s y s T e m D e s I g n m o D e l

the natural systems evaluation process described above allows for the ability to assess the

“function” of any scenario of natural cover and, in particular, to determine if a scenario meets the

set targets for quality, distribution and quantity. If the targets were not met by the existing natural

system scenario then the next step is to increase or reconfigure the natural cover land base to be

protected in the most effective location to meet the targets.

early on, trcA had used a technique of digitally expanding (buffering) all existing habitat patches

in the region incrementally to demonstrate the utility of predictive modeling and raise awareness of

the need for expanding the natural system. A second benefit from that exercise was that it provided

the first study on what scenario of natural cover increase would represent a more sustainable

distribution of Species of concern. It was not until the 30 meter expansion (buffering) (figure 1)

was applied that improvements in quality were noteworthy from a sustainable system perspective.

this 30 meter buffer around every existing patch cumulatively added up to 91000 hectares, or

thirty-seven per cent, of the region’s surface being in natural cover. It was hoped that a third benefit

would come from the combination of this buffering exercise and the use of the lAm: that the

trcA’s official target system could be designed for the region. However, although the lAm is able

to evaluate different natural cover scenarios, the technology is not suited for strategically selecting

the best suited or most ecologically functional locations where natural cover might be expanded,

and therefore its ability to be used for developing a target system was limited. A different method, a

raster-based model, was then chosen to evaluate the entire surface of the trcA jurisdiction for the

potential to contribute to achieving the targets.

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Map 1 : Expanding (buffering) existing natural cover by 30 meters

4 . 1 v a l U e s U R f a C e a P P R o a C h ( R a s T e R a n a l y s I s )

Expansion of the System

designing the targeted tnH system involved dividing the entire landscape into a grid of cells, or “

pixels”. In this case, the pixels are 10 x 10 meters. (we could have used 5 x 5 m, but this would take

longer for the model to run (decreasing utility), and some of the data layers used are limited to a 10

x 10 m resolution).this pixel size provides a suitable level of detail, and ensures that small habitat

patches, particularly wetlands, are well represented.

each of the pixels receives a value for eighteen peer reviewed criteria that were developed to closely

match the objectives of the targets and to build on existing protection mechanisms and policies.

therefore both ecological and land use/ownership (feasibility) criteria were selected (table 2). refer

to Appendix e-2 for the scoring system used for each criteria layer.

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Table 2: Criterion layers in the value surface analysis

ECoLoGICAL LAYERS

Total Score (‘Quality’) *

Distance from Urban Areas

Proximity to Natural Areas

Distance from Roads

Interior Forest

Proximity of a Forest to a Wetland

Proximity of a Wetland to a Forest

Proximity to a Watercourse

Proximity to a Waterbody

PLANNINg AND OWNERShIP LAyERS

Provincially Significant Wetlands (PSW)

Areas of Natural and Scientific Interest (ANSI)

Environmentally Significant Areas (ESA)

Valley and Stream Corridors (Areas regulated by TRCA under Ontario Reg. 158 – Fill/Fill extension lines)

TRCA Property

greenbelt Plan

Oak Ridges Moraine Conservation Plan

Niagara Escarpment Plan

Rouge Park

Note: i) Existing natural cover included in the analysis includes Forest and Wetland cover only.ii) A description of each layer and why it was selected is available in Appendix E-3.* Landscape analysis polygons converted to pixel, thus giving a score to pixels falling within existing habitat boundaries only.

these criterion layers were ‘overlaid’, and the sum of the scores for each grid cell for each

criterion provides a range of cell values across the landscape that increase in value as values for

protection or restoration increase (figure 2). Several assumptions were built into this process

that limit where restoration and protection can take place based on existing land uses in the

trcA (table 3).

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Figure 2 : Criteria overlay and addition to create a Total Score Value Surface

Table 3: Assumptions built into the value system analysis process

Assumption #1 Out of the many layers used in the raster analysis, only those existing forest and wetland patches (> 0.5 ha) were used. Old field meadow habitat was assumed to require the same level of effort to restore as agricultural fields. (See Appendix E-2 for a detailed list of layers used under each criteria)

Assumption #2 For existing urban areas: i) Expansion of the existing TNh system cannot occur into an already developed urban area. ii) All existing habitat identified within the urban boundary that abut the target system are included in the final system, regardless of their scores.

4 . 2 m a P P I n g T h e T a R g e T T n h s y s T e m

Prompted by the present state of natural cover distribution in the region, and by observed and

documented trends in biodiversity decline, targets for quality, distribution and quantity of natural

cover were set, (for setting targets see, trcA, 2006 a - Setting terrestrial natural System targets).

the next step was to proceed and develop scenarios in the design and mapping of the target tnH

System that would achieve the targets.

the trcA approach considers the terrestrial needs of the toronto region over a one hundred year

timeframe and considers the function of the region as an ecosystem, not just that of the natural

cover. rather than just selecting high value existing areas to be protected, this approach allows the

trcA to examine a full range of values and select as many areas as are needed to achieve the targets

set for quality, distribution and quantity. this means that on occasion some areas that support

no existing natural cover but are strategically located to contribute to the future achievement of

the targets, may score higher in the raster value surface than some areas with existing cover that

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are perhaps very small and poorly located. therefore, not all existing natural cover will be included

in the targeted system, and conversely much land will be selected for restoration that currently

does not support natural features. this is an important concept of the system design process as it

is aimed at considering existing land development patterns to obtain the most benefit from land

protection to achieve the long-term targets for quality and distribution. Still, the larger and the

more rounded (compact shape) the existing natural cover, the higher it will score against areas that

do not currently support natural cover.

the raster (value surface) methodology described in Sec 4.1 automatically and uniformly evaluates all pixels in the entire trcA jurisdiction based on their potential to contribute to the achievement of the targets for quality and distribution. the next step was to select the appropriate pixels (lands) that together as a system fulfill the quality, distribution and quantity targets most. the text that follows explains how this was done by selecting from the highest scoring pixels downward until the area selected composed a tnH system that met the targets of quality and distribution.

If urban and agricultural land uses also change in the future, then these changes will impact the

future natural cover and the potential to achieve the targets. therefore, for every scenario designed

it is important to consider and model the extent and distribution of agricultural and urban land

cover projected for the timeframe of the exercise. In the process explained below, every scenario

explored is therefore designed and evaluated with urban and agricultural projections. the trcA

is looking 100 years into the future and considered the Province’s greenbelt and 30 year growth

Plan boundaries for the region as the predicted urban land cover over that timeframe. the design

process follows, including some notes on the trcA results specifically; for example, trcA looked

at existing natural cover and two modeled scenarios.

4 . 3 T n h T a R g e T s y s T e m D e s I g n s T e P s ( a T o m )

Evaluation – Existing Natural Cover

a) Interpret aerial photography and digitize (or map digitally) into the 5 habitat categories

(forest, successional, wetland, meadow, beach/bluff)

b) Prepare or acquire urban land cover and policy layers (urban, urbanizing, greenbelt, rouge

Park etcetera)

c) evaluate current system conditions using the lAm (this layer is later converted from

vector to raster and is then used in the value surface/raster analysis as one of the criteria

used to design the system (See Sec. 4.1).

d) does the existing system scenario meet the targets for quality and distribution? If yes, then

the existing system is the (minimum) target system for the study area. If it does not, from

either the quality or distribution perspective, then continue on to designing a modeled

scenario.

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(a, b) Habitat categories and land use layers

(a, b) Existing conditions for the region

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(c) Evaluated terrestrial natural cover (land uses shown)

Design - Modeled Scenario 1

e) raster Analysis using ecological and feasibility criteria and assumptions

f) while the model is driven by targets for quality (size, shape, matrix influence) and

distribution of natural cover; the model requires an initial quantity of natural cover as a

first input. Select the highest scoring pixels that add up to the desired starting percentage.

convert this to shapefile to create ‘raster Selection’

the trcA example: trcA began with thirty per cent of the entire value surface. thirty per

cent was used based, in part, on the literature, including the great lakes remedial Action Plan

Framework (environment canada, ontario ministry of natural resources, and ontario ministry of

environment 1998), and preliminary trcA buffering exercises that indicated that at least thirty

percent would be required to achieve a sustainable system (see Section 4). therefore, the highest

scoring thirty per cent of the pixels were selected for the first scenario.

g) take ‘Existing Forest, Wetland, Beach/Bluff’ layer and intersect this with Raster

Selection. essentially this will select all forests and wetlands that abut the Raster

Selection. Add these polygons to the Raster Selection to create the Scenario 1 System.

this process avoids creating patches that have been only partially selected (bisected)

through the process of converting from raster to vector.

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(e, f) Raster selection in neon green.

(g) Forest & wetland patches (in red) abutting the raster selection

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Evaluation – Modeled Scenario 1

h) evaluate the modeled Scenario 1 TNH System for quality using the lAm. evaluate

distribution. Have the quality and distribution targets been met? Again, if yes, then

Scenario 1 is the (minimum) target system for the study area. If not, from either the quality

or distribution perspective, then continue on to designing a modeled Scenario 2 that deals

with the quality or distribution limitations of Scenario 1. this may comprise selecting a

higher percent cover or making adjustments to the model, or adding criteria, and so on; the

exact modifications required depend on the cause of the limitation.

(h) Scenario 1 evaluated.

the trcA example: results showed that in this stage of the process Scenario 1 was not meeting

targets for distribution. existing conditions within the trcA jurisdiction illustrated a distribution

challenge with natural cover poorly represented in the south, compared to the north. the north

supported natural cover of a higher quality, which tended to attract more natural cover in any

modeling scenario. these areas have the highest biodiversity value and the greatest opportunity

to expand; therefore logically they can and should be expanded upon where possible. However,

this would not address the need for distributing more natural cover within the urban area where

patches tend to be smaller, poorly connected and of a generally lower quality. the feasibility of

expanding existing natural cover is limited within this area but because there are opportunities

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for an expansion to the natural cover that were not captured, Scenario 1 did not qualify as the

target System. we proceeded with developing a Scenario 2 by first adding a further step in the

methodology to address distribution, as explained below.

Design - Modeled Scenario 2

i) Prepare the modification for quality or distribution.

the trcA example: to address the distribution concerns caused by the constraints of the urban

area, trcA then included in the next scenario all meadows in the urban area that were not included

in Scenario 1 but intersected with (abutted) the natural system in Scenario 1. by virtue of being

connected to the larger system, contributing to patch size, the abutting meadows have a higher

ecological value than those that are separated in the earlier scenario.

j) the existing natural cover layer from step (a) was used again but this time the meadows

in the rural area were removed and the urban meadows included to result in an ‘Existing

Forest, Wetland, Beach/Bluff with urban meadows’ layer.

(j) Existing natural cover from step (a)

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(j) Existing natural cover with urban meadows kept.

k) take Existing Forest, Wetland, Beach/Bluff with urban meadows and intersect this with

Raster Selection. essentially this will take all forests and wetlands, and meadow patches,

within the urban area only, that abut with the Raster Selection. these will then be added

to create the ‘Scenario 2 TNH System’.

(k) Urban meadows intersecting Raster Selection shown in red

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Evaluation – Modeled Scenario 2

l) the identified Scenario 2 TNH system is then run through the landscape analysis to

determine whether or not targets for quality and distribution are met. If targets for

both quality and distribution are met, then proceed to step (m). If targets for quality or

distribution are not met, then run a new scenario with modifications of the model as

required for quality or distribution, until the targets are met.

(l) Evaluated Scenario 2

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Selection of Target System

m) the scenario that meets the targets is adopted as the working draft of the tnH target

System. Proceed through the next phases of fine scale revision and integration discussed in

Section 5.

(m) Scenario 2 selected as target system

In summary, the mapping of the target tnH system contains three main components:

1. the procedure begins with the target setting process that sets quality, distribution and

quantity targets (see trcA, 2006 a - target setting),

2. the system design model is then used to automatically select the best locations for

protection and restoration (Section 4),

3. the landscape analysis model is then used to evaluate the resulting system for quality and

distribution (Appendix e-1) and the results are compared to the targets to determine if they

have been achieved.

the results of modeling the best possible quality, distribution and quantity of natural cover to

design a target system are described next using the trcA process as a case study.

5 . 0 R e s U l T s ( o f T h e T R C a P R o C e s s )

the targeted system is described here in terms of quality, distribution and quantity of natural cover.

As was explained in Section 3, none of these three interdependent measures (or results) could be

considered separately from the next two measures.

5 . 1 q U a l I T y

Scenario 2 achieved the desired quality, in the ‘good’ quality range (or 11 to 12 range for the “total

score” of the lAm) so that on average, the resulting patches would be of a high enough quality to

support viable populations of regional Species of concern according to trcA findings (kilgour, 2003).

5 . 2 D I s T R I b U T I o n

the selected scenario achieves the best distribution possible in the trcA jurisdiction, considering

the limitations posed by the extensive (and relatively static) urban cover in the southern portion.

the outcome was to select a scenario that included as much natural cover in the urban area as

possible despite being below an optimal distribution of “good” patch quality. most natural cover

will be concentrated in the northern portions where urbanization has not proceeded to in the past.

true to the trcA’s intention to distribute natural cover and Species of concern across its entire

jurisdiction, including to the south, all opportunities for protection and restoration there should

be pursued even though they do not appear in the targeted system scenario. the l-ranks are broad

categories of the total scores, therefore, although most patches will increase or decrease in total

score, the l-ranks may not reflect these changes unless they are substantial or a patch was near

the threshold. thus the ranks are more geared to evaluating large landscape at a glance and total

scores are relevant for determining local benefits. Although the existing urban cover may prevent

the model from enlarging patches until they reach a higher l-rank but those patches can show

improvements in total scores.

C H A P T E R

5

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5 . 3 q U a n T I T y

the quantity, resulting from striving for a well-distributed, “good” quality natural cover, in the

trcA jurisdiction has required that thirty percent of the region’s surface area be natural. Again, the

targeted system can only be achieved by reaching all three targets together.

6 . 0 R e f I n e m e n T s T o T h e T a R g e T T n h s y s T e m

6 . 1 W a T e R s h e D P l a n n I n g

trcA, as part of its commitment to working with its partners and stakeholders to determine the

ideal target system for the region, has and will continue to refine the mapping of the natural system

at smaller scales through more detailed examination, including the following:

w that the tnH target system adequately conforms with protected areas identified in

municipal official plans and policies – including all land areas within Provincially

and locally Significant wetlands, Areas of natural and Scientific Interest (AnSI),

environmentally Significant Areas (eSA) and lands identified as natural heritage systems,

environmental Protection Areas (ePAs) and any other lands identified for protection in

official plans

w that all known patches that support populations of regional Species of concern and

vegetation communities of concern are included in the targeted tnH system

w that all patches of high quality (ranking l1-l3) are captured as part of the system

w that all known opportunities to achieve the regional targets in existing urban and urbanizing

areas are not lost. this may include exploring naturalization opportunities within urban

parks and golf courses that may have been overlooked at the coarser regional scale.

Note: To date, most of the above were refined using digital overlays, yet where digital layers were not available,

refinements were assessed visually.

for trcA lands with a management plan, we have considered public use areas as not opportunities.

for lands with no plan we clipped out existing infrastructure and public use areas (i.e. picnic areas).

As you said, it would be a good idea to add a caveat that as these areas go through the detailed

public management plan development process these areas can be reexamined to determine if the

uses are appropriate (e.g. if the area is better to be restored than kept as a public area)

C H A P T E R

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the regional tnH target system will be refined at the watershed and subwatershed planning

phases, including integrating the terrestrial system with other natural heritage components

(i.e. aquatics, sensitive ground water areas, etc.). the methodology described here may include

hydrological and aquatic habitat criteria to define a complete natural heritage system. the new

generation of integrated watershed and subwatershed plans will benefit from this multi-disciplined

effort and will consider all values both social and ecological. An effort is also being made to

ensure compatibility between the trcA defined system with those being defined by neighboring

conservation Authorities, non-profit organizations, and the Province of ontario.

6 . 2 R e f I n e m e n T s T h R o U g h I m P l e m e n T a T I o n

once the target system is determined through modeling, the target system map becomes the

“master plan”. the implementation mechanisms will allow for some flexibility in how the target

system is achieved at various scales over time.

the trcA uses site-specific information (including

ecological data, land use designations, and ownership) to

inform site decisions and to inform the development of

landscape-scale models. Site specific information was not

available for all natural cover within the region when the

design of the regional target system was undertaken, nor

was it expected to be available as this would be an enormous

task. while the benefits and indispensability of modeling

in assisting land use planning decisions were recognized,

so were the limitations of working at such a large scale. In

particular, as models generally do, the trcA models simplify ecological data and site character. on

one hand, such simplification is necessary in order to communicate complex principles to decision-

makers and stakeholders, and to report on complex ecosystems in a manner that can facilitate

decision-making. but refinements are needed at smaller scales (watershed, subwatershed, secondary

plan, etc.) in order to improve on the applicability of the target system at all scales.

refinements can occur as part of the implementation of the target system, in two ways:

1. through ongoing revisions of detailed land use mapping and restoration activities; and,

2. through ongoing ground-truthing of the model’s results by conducting biological

inventories.

the site-level ground-truthing occurs either in response to a local issue or as part of the regional

monitoring program. the field level work adds the details of species composition, which are

dependent on aspects of the landscape (soils, topography, moisture regime, local matrix influence,

etc.) that could not be determined from aerial photography, especially not for such a large study

area. more local information on ecological function, ownership and land designations will reveal

Future WorkThe LAM (which is used to measure quality) was based primarily on using avifauna as a surrogate for terrestrial biodiversity (which includes other fauna and flora species). Future analysis will ensure that other species are also being adequately considered by the modeling.

207

challenges and opportunities in achieving the target system and may lead to refinements to the

target system line.

Any changes in the target system boundary at all scales need to be considered in light of alternatives

that would assist in achieving the targets for quality, distribution and quantity.

6 . 3 I n T e g R a T I o n W I T h o T h e R e C o l o g I C a l , P o l I T I C a l a n D s o C I a l C R I T e R I a

the resulting target terrestrial natural Heritage System is the centerpiece of the terrestrial natural

Heritage System Strategy (trcA, 2006 d). the implementation section of the Strategy outlines

a detailed process by which this methodology will both be integrated with other values and be

implemented over time. refer to this document for details on future refinement of this model and

tools for implementation.

6 . 4 f U R T h e R a P P l I C a T I o n o f m o D e l s

the technology used in the design and evaluation of natural system scenarios can be used for the

implementation of the target natural system. the raster-based model can be used to compare lands

within the target system for the purpose of planning restoration and land securement increments.

7 . 0 a C K n o W l e D g e m e n T s

Support for the trcA terrestrial natural Heritage Program has been provided by: environment

canada, the richard Ivey foundation, the Salamander foundation, the r. Samuel mclaughlin

foundation, the george cedric metcalf charitable foundation, the Schad foundation, the

Helen mccrea Peacock foundation, the J.P. bickell foundation, unilever canada, greater toronto

Airport Authority, and the following municipal Partners: city of toronto, regional municipality

of durham, regional municipality of Peel, regional municipality of york, township of Adjala-

tosorontio, and town of mono.

C H A P T E R

7

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8 . 0 D e f I n I T I o n s

Natural Cover

Area of land occupied by naturally and culturally occurring vegetation that is not characterized as

agricultural, cultural or urban land uses, or water bodies. can be dominated by native and non-

native vegetation. does not include manicured areas such as parkland or golfcourses (however,

parkland or golfcourses may support patches of natural cover within their boundaries). existing

natural cover includes lands in the terrestrial natural heritage system that as of 2002 were existing

forest (including thicket), wetland, meadow, and beach/bluff patches. Potential natural cover is

lands in the terrestrial natural heritage system that are not existing natural cover, but that are

needed to achieve the trcA’s targets.

Forest

forest is a term frequently used, but seldom defined. for the trcA’s system, forest is defined

as a “natural habitat dominated by trees”. the first Approximation of the ecological land

classification (elc) System (lee et al. 1998) considers forest habitat to be an area that has greater or

equal to 60% tree cover. the elc System distinguishes between “cultural” plantations, and natural

deciduous, coniferous or mixed forest, and suggests a minimum forest patch or polygon size of 0.5

ha based on 1:10 000 aerial photos. for the landscape analysis minimum forest patch size has been

set at 0.5 ha, although smaller patches may be mapped because digital aerial photography allows for

a 1:4000 base scale. within an urbanizing landscape such small patches can be highly valuable to

some wildlife as an oasis, or as stepping stone or stopover habit (Hale et al. 2001).

A natural forest typically features several layers, including the canopy, understorey, and herbaceous,

as well as standing dead trees and fallen woody debris. by this definition, treed lawns, cemeteries,

backyards, etc., do not have a forest structure and are not considered as a functioning forest,

despite providing a variety of biological and environmental benefits. In contrast, plantations which

usually display basic forest structure (albeit greatly simplified), are not natural forest, although

they still provide many forest functions. depending on how they are managed, their composition

C H A P T E R

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210

and structure can improve over time, especially when native tree or herbaceous species colonize

under the planted canopy and start to form secondary growth. many plantations in the trcA

jurisdiction support species of concern, some of which are not currently found in other habitats.

where they are adjacent to forests, plantations contribute to the increase of the total forest area and

the amount of interior habitat.

for the landscape analysis of forest habitat patches, forest plantations, successional growth, the

three major forest types defined in the elc system (coniferous, deciduous and mixed), and swamp

forests were digitized as uniform forest layers without distinction and were treated as forest

polygons. Including successional growth in the forest category for the evaluation means that

polygons with less than 60% tree cover get incorporated (i.e. savannah, woodland or successional

lands end up being considered forest). tree-dominated swamps are mapped and evaluated as forest

in part because they are difficult to discern in aerial photo interpretation, and because they provide

many wildlife values associated with forest (e.g. forest interior conditions).

theoretically, a study area, such as a subwatershed, could have full coverage of field-collected

vegetation community polygons. In that case the ecological land classification codes might be

used to define the polygons. Suggestions include: fom, fod, foc, Swm, Swd, Swc and cuP

(cuP only if mid-aged or older)

Successional

digitized separately from forest, but included in the landscape analysis of forest habitat, these

polygons have less than 60% forest cover (see above Forest).



used to define the polygons. Suggestions include: cuw, cuH, tPw, cut, cuH, cuS, tPS, cbS,

SbS and Sbt.

Wetland

wetlands include shallow marsh, meadow marsh, shallow aquatic systems, swamps, bogs and fens.

Aquatic and wetland sites where water is known to be 2 m or less in depth are considered to be

marsh or shallow water, according to the mnr wetland and elc definitions. where water depth

is thought to be deeper than 2 m or unknown, only the perimeter marsh vegetation is mapped

as wetland and the remaining area if large enough is classified as open water. meadow marsh

is often indistinguishable from ordinary meadow on aerial photographs and cannot always be

accurately mapped as wetland unless a wet meadow is known to exist there. Swamp communities

are dominated either by shrubs or trees. thicket swamps (shrub-dominated wetlands) are easier to

discern than treed swamps when remotely sensed and are usually mapped as wetland polygons.

no limit was set on the size of wetlands to be mapped, since they often naturally occur as small

pockets in the landscape. If a wetland habitat is discernable at a scale of 1:4000, it is mapped.

211



used to define the polygons. Suggestions include: mAS, mAm, SAS, SAm, SAf, Swt, but not oAo.

Meadow

“meadow” generally refers to old field habitat, fallow field, pasture or open areas that are mowed

occasionally, such as highway and transmission corridors. native tallgrass prairie, open sand

barren, and sometimes meadow marsh are also considered as “meadow” in the landscape analysis

because these are difficult to distinguish from old field in air photo interpretation. old fields are

considered to have high restoration potential for native vegetation communities. However, in order

to ensure that any naturally occurring native open communities are not overlooked, individual sites

should be inventoried in advance of any old field restoration plans. Such natural meadow types will

be covered by more detailed mapping of vegetation communities.

As with forest, the minimum size for meadow to be included and mapped as habitat was set at 0.5

ha., although, again, smaller patches may be mapped due to some of the unique habitat types that

fall under the meadow category.



used to define the polygons. Suggestions include: cum, Sbo, tPo, and Sbo.

Beach/Bluff

this category includes natural barren coastal habitats that do not correspond to any of the other

major habitat type categories. It includes natural beach, coastal dunes, and bluffs.

no limit was set on the size of beach/bluff communities to be mapped, since they often naturally

occur as small features in the landscape. If a beach/bluff patch is discernable at a scale of 1:4000, it

is mapped.



used to define the polygons. Suggestions include: bbo, bbS, bbt, Sdo, SdS, Sdt, blo, blt, blS,

clo, clS and clt.

Rural/Agricultural

rural/Agricultural lands include croplands, fruit tree plantations (orchards), and pastures. they

do not include fallow fields, which are mapped as meadows. like meadows, agricultural lands are

considered to have potential for forest restoration (recognizing that the constraints analysis may

indicate that much of this area is not available). golf courses and aggregate lands embedded in this

area are also mapped as rural/agricultural, but not so when embedded within an urban area.

212

Urban

for the purpose of the landscape evaluation “urban” areas are considered to be any part of

the landscape that has been modified primarily for a human use other than agriculture. this

includes residential, commercial, and industrial land. It also includes manicured areas such as

cemeteries, golf courses, and parkland, because the intensity of management and use of these areas

is considered to have many potential negative impacts on nearby natural areas. In some cases

manicured parks within the urban areas may be analyzed as having restoration/naturalization

potential.

213

9 . 0 R e f e R e n C e s

Andren, H. 1994. effects of Habitat fragmentation on birds and mammals in landscapes with

different Proportions of Suitable Habitat: A review. Oikos 71: 355-366.

environment canada, ontario ministry of natural resources, and ontario ministry of environment.

1998. A framework for guiding Habitat rehabilitation in great lakes Areas of concern. minister of

Public works and government Services canada.

fahrig, l. 1997. relative effects of Habitat loss and fragmentation on Population extinction.

Journal of Wildlife Management 61(3): 603-610.

fahrig, l. 1998. when does fragmentation of breeding habitat Affect Population Survival?

Ecological Modelling 105: 273-292.

fahrig, l. 2001. How much Habitat is enough? Biological Conservation 100: 65-74.

fahrig, l. 2002. effect of Habitat fragmentation on the extinction threshold: A Synthesis.

Ecological Applications 12(2): 346-353.

fahrig, l., J. H. Pedlar, S. e. Pope, P. d. taylor, and J. f. wegner. 1995. effect of road traffic on

amphibian density. biological conservation 73: 177-182.

Hale, M.L., P.W.W. Lurz, M.D.F. Shirley, S. Rushton, R.M. Fuller, and K. Wolff. 2001. Impact

of landscape management on the genetic Structure of red Squirrel Populations. Science 293(5538):

2157-2336.

kilgour, b. 2003. Landscape and Patch Character as a Determinant of Occurrence of Eighty Selected Bird

Species in the Toronto area. A report prepared for the trcA. Jacques-whitford ltd., 2003.

lee, J. t., S. J. woddy, and S. thompson. 2001.

targeting sites for conservation: a patch based ranking scheme to assess conservation potential.

Jounral of environmental management 61: 367-380.

lee, J. t., n. bailey, and S. thompson. 2002a.

using geographic Information Systems to identify and target sites for creation and restoration native

woodlands: a case study of the chiltern Hills, uk. Journal of environmental management 64: 25-34.

lee, H. t., w.d. bakowsky, J. riley, J. bowles, m. Puddister, P. uhlig and S. mcmurray. 1998.

ecological land classification for Southern ontario: first Approximation and its Application.

ontario ministry of natural resources, South-central Science Section, Science development and

transfer branch. ScSS field guide fg.

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lee, m., l. fahrig, k. freemark, and d.J. currie. 2002b. Importance of Patch Scale vs landscape

Scale on Selected forest birds. Oikos 96(1):110-118.

lindenmayer, d.b. and J.f. franklin. 2002. conserving forest biodiversity: A comprehensive

multi-scaled Approach. Island Press, washington d.c.

mcgarigal k. and w.c. mccomb. 1995. relationships between landscape structure and breeding

birds in the oregon coast range. ecological monographs 65(3): 235-260.

ministry of municipal Affairs and Housing. 1994. niagara escarpment Plan. Queen’s Printer for

ontario, toronto, on.

ministry of municipal Affairs and Housing. 2002. oak ridges moraine conservation Plan.

Queen’s Printer for ontario, toronto, on.

ministry of municipal Affairs and Housing. 2003. Shape the future: central ontario Smart

growth Panel. Queen’s Printer for ontario, toronto, on.

trcA. 2003. centreville creek Subwatershed Plan: characterization report, draft. toronto and

region conservation Authority, toronto, on.

trcA. 2007 a. Setting terrestrial natural System targets. toronto and region conservation

Authority, toronto, on.

trcA. 2007 b. terrestrial natural Heritage Program Scoring and ranking methodology, draft.

toronto and region conservation Authority, toronto, on.

trcA. 2007 c. terrestrial natural Heritage Program data collection Protocol. toronto and

region conservation Authority, toronto, on.

trcA. 2007 d. toronto and region terrestrial natural Heritage System Strategy. toronto and

region conservation Authority, toronto, on. draft, April 2004.

villard, m.A., m.k. trzcinski, and g. merriam. 1999. fragmentation effects on forest birds:

relative Influence of woodland cover and configuration on landscape occupancy. Conservation

Biology 13(4): 774-783.

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Appendix E-1 – Landscape Analysis Methodology

C o n T e n T

w Introduction

w Patch Quality evaluation- Size, Shape, matrix Influence and total Score

w System Quality evaluation

w references

I n T R o D U C T I o n

the following explains the methodology, or landscape Analysis model, used to evaluate the quality

of patches and eventually that of the system. A wide range of measures are now used in landscape

ecology (see mcgarigal and mccomb 1995), and a large number of these were carefully scrutinized

before a choice was made on those thought to be most relevant for the trcA’s regional landscape

context. the trcA has taken this methodology through an extensive peer review process both

internally and seeking the external review of respected individuals within the sphere of ontario’s

conservation biology field. technical workshops and consultation for the terrestrial natural

Heritage System Strategy (trcA, 2007 d), of which this methodology is a centerpiece, also provided

a sounding board for the methods presented here.

once the major habitat and land use types have been digitized figure 1 – Step 1), the analysis is

undertaken using a vector-based approach in Arcview gIS software (figure 1 – Step 2) with the

Spatial Analyst addition. once the model is calibrated, habitat patches in a study area obtain a

score and rank according to their respective qualities (discussed below). because this analysis can

be undertaken through remote-sensing, and because representation of vegetation communities,

flora, and fauna tend to be strongly correlated with these attributes, the landscape analysis is a

fundamental part of the trcA terrestrial natural Heritage Program (trcA 2001; normand &

towle, 2001).

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Figure 1: Running the Landscape Analysis Model

Landscape Analysis Model

Figure 1: Running the Landscape Analysis Model

Data Collection & Preparation• Field Inventory Programme• Volunteer Monitoring Program

Data Collection & Preparation• Air photo interpretation and digitizing

Research into landscape metrics• Vegetation community and species are scored and ranked according to habitat dependence, local occurrence, etc, from both collected data and literature to determine levels of concern (TRCA, 2006- Scoring & Ranking). This information, including remotely sensed patch data, fed into the development of the measures of Size, Shape, & Matrix In�uence.

Evaluating the Existing conditionsLandscape Analysis Model (LAM)• Total Patch Scores (current conditions) derived from evaluation of patches based solely on the landscape metrics of Size / Shape, & Matrix In�uence. (These measures can be strongly correlated to values for Quality)

Results of the Landscape Analysis Model are converted into raster and used in the System Design Modelling (see Main document)

STEP 1 STEP 2

P a T C h q U a l I T y e v a l U a T I o n

In the landscape analysis model (lAm) each discrete habitat patch in the study area is scored for

three landscape ecology measures: size, shape, and matrix influence. these measures are widely

applied in the field of landscape ecology to evaluate habitat patches in fragmented landscapes. each

measure is discussed below. Scripts were then written in Arcview gIS in order to run the landscape

analysis model across the region.

Patch Size

for biodiversity and the maintenance of ecosystem integrity, large habitat patches are preferable

because:

1) they can support bigger populations of species, thus promoting their viability;

2) they have the capacity to support area-sensitive and forest interior species;

217

3) they are better buffered from negative external influences;

4) they likely feature a greater diversity of habitat types; and,

5) they have a greater capacity to maintain and promote a variety of natural ecological

processes. (see forman, 1995; bennett, 1999).

Size is the number of hectares occupied by a habitat patch (polygon). even when patches straddle

the boundary of the study area, size is calculated for the entire patch, not just the portions that fall

within the study area. Scores for size were based on numerous literature sources, such as Hounsell

(1989), and trcA raw data of species and patches.

wetlands and beach/bluff are scored higher for size than forests and meadows because they provide

equal level of ecological function at smaller sizes. for example, wetlands and beach habitat patches

are much more capable of supporting habitat-dependent, native plant Species of concern at much

smaller sizes than could forest patches. this scoring based on value for function brings wetlands

and beaches on an equal footing with forests and meadows to acknowledge that healthy natural

systems are made up of a mosaic of communities and the interactions between them. for example,

small marshes provide habitat for breeding frog populations that then disperse as adults to much

more extensive forest patches, but neither habitat on its own would sustain the frog populations.

Hence the decision not to set a minimum size for wetlands while doing so for forests (table 1 in

main Appendix e text).

wetland scores were based on numerous literary sources, such as cadman et al. (1987), and trcA

raw data of species and patches. beach/bluff habitat is treated similarly to wetland habitat. Scores

are assigned to the patch size classes for each habitat type are listed in table 1.

Patch Shape

Patch shape is a measure of its exposure to external influences, especially the negative edge effects

resulting from habitat fragmentation. generally, the more convoluted or linear the habitat

patch, the higher the ratio of edge to area and the higher will be its exposure to these influences

(forman, 1995).

Shape is scored as a patch’s perimeter (edge)-to-area ratio (P/A). to compensate for the increase

in perimeter with increasing patch size, a corrected shape calculation is used: (0.282 x Perimeter)/

(Area) ½ (baker, 1997). the resulting scores for each habitat patch are multiplied by a factor of

ten to provide numbers that are easier to interpret e.g. a perfect circle (the best possible shape for

reduction of edge to area) would be P/A = 100. As in the case for the size measure, patches that

extend outside of the study area boundary are measured in their entirety, not just the portions of

the patch that fall into the study area. the patch shape values were assigned a score as listed in

table 2. the values were broken down over the 5 scores based on the literature on landscape ecology

and on qualitative analysis of maps of trcA raw data of species and patches.

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Patch Matrix Influence

matrix influence is a measure of the positive or negative influence that a patch receives from its

surroundings. land uses, especially urbanization, adjacent to a patch can exert pressure or impacts

that can have a profound effect on its biodiversity (lindenmayer and franklin, 2002). conversely, a

patch can have a synergistic and beneficial relationship with other natural cover in its surrounding

area, and to a lesser degree with agricultural lands. In other

words, a patch’s score for “matrix influence” reflects the degree

to which the surrounding land cover and land uses threaten or

contribute to its biological integrity and diversity.

the trcA measures the character of the matrix within a 2 km radius out from the outside edge of

each habitat patch. the 2 km radius of influence extends beyond the limit of a study area (region

or watershed, for example) in situations where habitat is adjacent to the boundary delimitation.

the radius length of 2 km was chosen because:

1) it is considered to be a potential distance traveled daily from the matrix in a foraging

circuit by predatory species associated with edge effects, such as raccoons, foxes, feral cats,

cowbirds (negative influence);

2) it is the distance within which most genetic exchange and species dispersal can be expected

from most flora and fauna species (positive influence); and,

3) it is a distance that could be considered reasonable by people to travel from to visit a

natural area for recreational purposes, by walking, cycling or driving (negative influence).

(see Austen et al. 2001; Austen and bradstreet 1996; Hames et al. 2001; norris & Stutchbury 2001;

Haddad 2000; Askins et al. 1987; robbins et al. 1989)

In scoring for matrix influence, land cover types are calculated as a percentage of the total area

within 2 km from the edge of each habitat patch. for the purposes of this calculation three

categories of land cover are used: natural, agricultural and urban, each receiving a base value of

either +1, 0 or -1 on the gradient of influence. natural cover surrounding a patch is considered

to have a positive influence and receive a value of +1. Included in this category are patches of the

major habitat types (forest, wetland, beach/bluff and meadows), as well as open water in the form of

lakes, rivers, and ponds. Agricultural land cover can have negative impacts such as pesticide runoff,

but they also allow for the movement of many species between patches and across the landscape,

in particular for amphibian movements between forests and wetlands. As a result they score 0

points as the mid point on a continuum. urban land cover does not provide a connectivity function

for most species. In fact, due to pollution, refuse, recreational pressures, the presence of dogs and

cats, invasive species, etc., urban areas in general can be considered harmful to natural habitats.

therefore urban areas receive a base point of - 1.

the percent of each of the land cover types is measured within the 2 km matrix, and each is

multiplied by the base point value. from a biodiversity conservation perspective, the perfect patch

surroundings would be 100 percent natural (for example, wetland X would be situated within an

MatrixRefers to the general character of land uses in an area.

219

extensive mosaic of forests and wetlands, measuring at least 2 km out from the edge of wetland X)

and would receive a matrix score of 100, while the lowest possible score is -100 for a natural habitat

patch “immersed” within an expanse of urban land uses. the matrix values were broken evenly into

five scores (e.g. -100 to -60), using even breaks (40 point intervals).

Table 1: Scoring for size, shape, and matrix influence of habitat patches

SCoRESIzE (HA) FoRESTS, MEADoWS

SIzE (HA)WETLANDS, bEACH/bLUFF

SHAPE (P/A) MATRIX

1 <2 <1 ≥500 -100 to - 60

2 ≥2 ≥1 ≥300 < -20

3 ≥10 ≥3 ≥200 -20 to + 20

4 ≥50 ≥10 ≥125 > +20

5* ≥250 ≥20 ≥100 +60 to 100

*A score for patches greater than 250 ha was included to reflect restored conditions where such patches were possible, and to allow for application of the model to other jurisdictions.

Patch Total Score

total score for each patch is then calculated by combining the scores for size, shape, and matrix

influence, and is used as a surrogate for, or summary of, the ‘quality’ of a habitat patch as seen from

the air. but size, shape and matrix influence are assigned different weights in the total score based

on their importance in how much each affects ecological function (in other words, how each helps

or hinders species populations within patches).

of the three criteria, size is the most important patch attribute in an urbanizing landscape, both

because large patches are more likely to provide more options for dealing with crises (resilience),

and because negative edge effects (related to shape and matrix influence) generally penetrate less as

patch size increases. Preliminary studies using extensive data from trcA jurisdiction have shown

that the most important characteristic of a habitat patch for avian biodiversity is its size (kilgour,

2003), probably because size relates to the amount of space required for species to find resources

and remain in viable populations. the second factor is matrix influence; shape is also a factor

in contributing to the quality of a habitat patch, but to a lesser degree. As a result, when adding

size, shape, and matrix influence together for a total landscape score, the size criterion is given an

additional weighting on a sliding scale from small to large patches. thus for a small habitat patch

each landscape criterion (size, shape, matrix influence) may have relatively equal weighting, while

for a larger patch the size score may be weighted more than shape and matrix influence. forest and

meadow patches are weighted differently from wetland and beach/bluff patches (tables 2 and 3).

note: a multiplier of 3 is used in the calculation of total Score. for example, for a forest patch with

the following scores: size = 5; shape = 3; and matrix = 4 (i.e. assume patch is 250 ha, see table 2), the

following equation would be used to calculate total score: 5(50%)*3 + 3(25%)*3 … 4(25%)*3 = 12.75.

220

Table 2: Weighting system for total score in forest, meadow

SIzE (HA) % SIzE % SHAPE % MATRIX

> 0 33% 33% 33%

≥10 40% 30% 30%

≥ 50 45% 27.5% 27.5%

≥250 50% 25% 25%

≥500 55% 22.5% 22.5%

≥1000 65% 17.5% 17.5%

≥2000 75% 12.5% 12.5%

Table 3: Weighting system for total score in wetland and beach/bluff habitats

SIzE (HA) % SIzE % SHAPE % MATRIX

≥0 33.3% 33.3% 33.3%

≥3 40% 30% 30%

≥10 45% 27.5% 27.5%

≥20 50% 25% 25%

Patch Rank Calibration

the patch scores were then grouped into five ranks (l-ranks or local ranks), based on the range

of possible total scores from 0 to 15 points. l1 is the highest rank and l5 the lowest (table 4). the

purpose of ranking is to simplify the evaluation of the natural system and assist decision-making

by breaking down the range of scores into categories of patches with similar function. to avoid the

conventional approach of having two ranks, “good” or “bad”, in which good received the protection

and bad was expendable, trcA took more of a graduated approach with 5 ranks. Initially, the

ranks were calibrated based on even breaks in the scoring but when these breaks were applied to the

region’s natural system, the patch ranks across the region did not correspond to the distribution of

species across the region. then the inventory of field data from across the region became the basis

for calibrating ranks (table 4 and map 1). Patches for which there were data were used to calibrate

the ranks and therefore to rank all other patches of similar character throughout the region that

had not yet been inventoried.

Table 4: Habitat patch total score ranking system (size, shape, and matrix influence)

PATCH CHARACTER SCoRE RANk ‘QUALITY’ CoNDITIoN PATCH CoLoUR

Regional SoC 13-15 L1 Excellent Dark green

Regional SoC 11-12 L2 good Light green

Regional SoC 9-10 L3 Fair Orange

Urban SoC 6-8 L4 Poor Beige

No SoC 0-5 L5 Very Poor Brown

221

Map 1: Species Points (L1 to L3) and Land Use Character

Break between L3 and L4 Patches

field-inventoried patches that were found to support regional Species of concern were ranked l1

to l3 (l = local rank) and all other patches of similar quality, therefore with the same range of total

scores, were also ranked l1 to l3. field-inventoried patches that did not support regional Species of

concern were ranked l4 or l5, and all other patches of similar quality (total score) were also ranked

l4 or l5. thus, the model was calibrated to represent the threshold in species representation, which

increased dramatically from l4 to l3 patches. generally, patches in the urban matrix ranked l4 or

l5 and did not support regional Species of concern. morningside Park is an exception in that it

supports patches whose size compensates for the very negative surrounding matrix influence. the

initial calibration was later supported through a statistical evaluation of a subset of avian Species of

concern (kilgour 2003) and generally through further inventories and assessment at various scales

from site to region.

Break between L4 and L5 Patches

the l4 and l5 ranks were calibrated using the presence and absence of urban Species of concern,

species that are found within the urban envelope but are sparse. field-inventoried patches that were

found to support urban Species of concern were ranked l4 and all other patches of similar quality,

therefore with the same range of total scores, were also ranked l 4. field-inventoried patches that

did not support urban Species of concern were ranked l5, and all other patches of similar quality

(total score) were also ranked l5. Again field inventories since the initial calibration has provided

general support for the calibration.

222

Breaks between L1, L2 and L3 Patches

the rural portion of the trcA jurisdiction supported a full range of patch scores and a

corresponding full range of species. A number of regional Species of concern were distributed

across the rural portion of the trcA jurisdiction, some to the edge of the urban envelope, where

patch total scores were generally average (scoring 9 to 10). And a smaller number of Species of

concern were generally restricted to habitat patches with total scores that were above average for

the trcA jurisdiction (patch total scores were generally higher than 10). the latter were generally

located on the oak ridges moraine and duffins watershed. that mapping of species regionally as

well as literature on species area-sensitivity used in scoring species provided a further break between

l1, l2 and l3 patches.

Systems Quality Evaluation

evaluating the natural system quality is done by depicting the result of all patches as one

functioning unit in the landscape. one method used is a histogram that illustrates, as shown below

in map 2, the number (frequency distribution) of hectares falling into each rank (l1 to l5) and from

which a median natural system quality can be derived. other ways to demonstrate the system quality

is by showing number of patches per rank or by showing total score frequency instead of ranks.

Histograms for existing and modeled scenarios are then evaluated against the objectives to be met

and the set targets (see Appendix d, Setting Terrestrial Natural System Targets).

Map 2: Targeted Terrestrial Natural Heritage System (TRCA Jurisdiction)

223

R e f e R e n C e s

Askins, r. A., m. J. Phibrick, and d. S. Sugeno. 1987. relationship between the regional abundance

of forest and the composition of forest bird communities. biological conservation 39: 129-152.

Austen, m. J. w. and m. S. w. bradstreet. 1996. the effects of fragmentation on forest birds and

plants in southern ontario: recommendations for woodland conservation and restoration. long

Point bird observatory. Port rowan, ontario. 43pp.

Austen, m. J. w., c. m. francis, d. m. burke, m. S. bradstreet. 2001. landscape context and

fragmentation effects on forest birds in Southern ontario. the condor 103: 701-714.

baker, w. l. 1997. the r.le Programs: a set of grAA programs for the quantitative analysis of

landscape structure. version 2.2. department of geography and recreation, university of wyoming,

82071.

bennett, A/f. 1999. linkages in the landscape: the role of corridors and connectivity in wildlife

conservation. Iucn, gland, Switzerland.

cadman, m.d., P.f.J. eagles and f.m. Helleiner. 1987. Atlas of the breeding birds of ontario.

unversity of waterloo Press, waterloo, canada.

forman, r.t.t. 1995. land mosaics: the ecology of landscapes and regions. cambridge

university Press.

Haddad, n. 2000. corridor length and patch colonization by a butterfly Junonia coenia. conservation

biology 14(3): 738-745.

Hames, r. S., k. v. rosenberg, J. d. lowe, and A. A. dhondt. 2001. Site reoccupation in fragmented

landscapes: testing predictions of metapopulation theory. Journal of Animal ecology 70(2): 182-190.

Hounsell, S. w. 1989. methods for assessing the sensitivity of forest birds and their habitats to

transmission line disturbances. ontario Hydro.

kilgour, b. 2003. landscape and patch character as a determinant of occurrence of eighty selected

bird species in the toronto area. A report prepared for the trcA. Jacques-whitford ltd., 2003.

lindenmayer, d.b. and J.f. franklin. 2002. conserving forest biodiversity: A comprehensive multi-

scaled Approach. Island Press, washington d.c.

mcgarigal k. and w.c. mccomb. 1995. relationships between landscape structure and breeding

birds in the oregon coast range. ecological monographs 65(3): 235-260.

224

normand, l. and k. towle, 2001. Seeing the forest for the landscape: the toronto and region

conservation Authority’s terrestrial natural Heritage Approach. federation of ontario naturalists

conference Proceedings: woods talk: community Action to conserve ontario’s woodlands.

norris, d. r. and b. J. m. Stutchbury. 2001. extraterritorial movements of a forest songbird in a

fragmented landscape. conservation biology 15(3): 729-736.

robbins, c. S., d. k. dawson, b. A. dowell. 1989. Habitat area requirements of breeding forest

birds of the middle Atlantic States. wildlife monographs 103: 1-34.

225

Appendix E-2 – Target System Design Model -Value Surface Criteria

the raw score breakdowns across the raster score scale of 1 to 10 for ecological criteria and 0 to 10

for feasibility criteria varies under each criterion. Some breakdowns are linear (eg. increments of 1.5

under Patch Quality); others are somewhat exponential (eg. distance from urban areas). “distance

from” and “proximity to” criteria tend to have the same breakdowns and, as much as possible, the

breakdowns are similar across feasibility criteria. In all of these, the scoring was conducted with

as much relevance to ecology and planning on the ground as possible. Score ranges began with

1 in ecological criteria because the entire surface available for terrestrial natural cover expansion

held some value while score ranges for feasibility criteria began at 0 because where there was no

supporting designation, there would be no contribution to feasibility. the design approach was

peer reviewed.

CRITERIA RATIoNALE VALUE RANGE(DISTANCE IN M)

PoTENTIAL To EXPAND QUANTITY oF NATURAL CoVER

ECoLoGICAL CRITERIA

Patch Quality – Total Scores

This criterion makes use of the quality or total scores assigned to every patch in the region (the weighted addition of the individual patch scores for size, shape and matrix influence). Total scores are translated from the raw vector score (scored on a scale of 1-15) to a raw raster shape score (on a scale of 1-10). This criterion assumes that the higher the total score is for a particular habitat patch, the more valuable it is for the target system. The maximum value of 10 points is associated with the highest total score values.

NoAddresses existing conditions only. Will value existing patches with higher total (size, shape, matrix influence) scores.

Raw Total ScoreScore

0-1.5 1

1.5-3 2

3-4.5 3

4.5-6 4

6-7.5 5

7.5-9 6

9-10.5 7

10.5-12 8

12-13.5 9

13.5-15 10

226



Distance from urban areas

This criterion is related to “matrix influence” in that it assumes that the further away a natural area is from an existing urban area, the better. The maximum value of 10 points is associated with distances of 2 km or more, this number being the distance considered in the landscape measure for matrix influence, which in turn was based on a rough estimate of how far certain negative impacts (i.e. urban faunal predators, human visitors, and their pets) can move in a landscape, the benefit of having additional natural cover within 2 km of an existing patch for biodiversity, and how far most visitors are likely to go in order to use a local natural area on a frequent basis, e.g. daily.

YesShows preference for areas that are far from urbanization targeting the more rural areas for an increase in natural cover; if cover is increased in these areas, matrix influence will be improved in areas where new habitat is added, and the biodiversity will benefit from this as well. Distribution of habitat will be influenced in a negative way, adding more natural cover to the north and away from the urban fringe.

Proximity to natural areas

This measures the proximity of natural habitat patches, up to a distance of 2 km. Like the former layer, this is also essentially a matrix measure, although this one assumes that nearby natural areas are beneficial to a habitat patch. The ways in which they can be beneficial are numerous, including support of a breeding pair or a population because of close access to additional resources, provision of pollination services and seed sources, etc (Austen et al., 2001; Norris & Stutchbury, 2001; Askins et al,. 1987; Robbins et al,. 1989). Natural areas within the study area which are very close to each other (0 to 10 m) score the maximum of 10, while areas more than 2 km away from each other receive a score of 0.

YesShows preference for areas that are in close proximity to or connected to other natural patches; this criterion will mainly serve at improving the matrix influence of a patch, and potentially the size, shape and connectivity of patches may also be improved. This criterion will also affect the distribution of natural cover by encouraging more habitat to be built up in areas where existing natural cover is high, in the northern, more rural portions of the Region.

Distance Score

0-10 1

10-30 2

30-60 3

60-120 4

120-200 5

200-300 6

300-500 7

500-1000 8

1000-2000 9

2000 + 10

Distance Score

0-10 10

10-30 9

30-60 8

60-120 7

120-200 6

200-300 5

300-500 4

500-1000 3

1000-2000 2

2000 + 1

227



Distance from roads

Roads pose a negative influence on terrestrial natural heritage as a result of pollutant run-off, noise, etc., as well as acting as barriers to the movement of many species for example, those which refuse to cross open areas due to the threat of exposure to desiccation, predation, etc (Fahrig et al. 1995). Areas that are 1 km or more away from a road receive a score of 10 for this layer. For the TRCA jurisdiction, a layer with all major roads was utilized

YesValues areas far from roads; will improve the distribution of natural cover in TRCA region due to the grid network of roads. The shape of habitat patches will also be improved through rounding out or squaring of patches farther from network of roads.

Interior Forest Core habitats or interior forest habitat (defined as areas greater than 100 m from the forest edge) are important, as many species will find difficulties in areas that are near the edge, due to the effects listed above. For this reason, existing interior forest is highly valued and it is given a maximum score of ten points. Also, all forest 100 m moving back out from the interior forest boundary is given maximum points. The reasoning for this is because interior forest would not exist if the surrounding 100 m ‘buffer’ of forest is not maintained. This will promote better patch shapes (for patches with interior forest) by not valuing linear convolutions or appendages that do not contribute to interior forest on larger patches.

NoAddresses existing interior forest only. Will protect existing cover only.

Distance Score

0-100 1

100-200 2

200-300 3

300-400 4

400-500 5

500-600 6

600-700 7

700-800 8

800-900 9

1000+ 10

Distance from edgeScore

100 + 10

Distance Scoreback out from 100 m forest interior line

100-0 10

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Proximity of a wetland to a forest

This layer takes into consideration the need for species to have close proximity of wetlands to forests to provide summer, spring and winter habitat. Wetland habitat that is in close proximity to forest habitat is given a maximum score of ten points. The value breakdown goes from immediate adjacency (given a maximum score of 10) to a distance of greater than 2 km (score of 0). This distance of 2 km is both the distance used for the matrix influence, and the approximate width of concessions, where roads break connectivity for these species.Species requiring or benefiting from the close proximity of wetlands and forests include: amphibians such as spring peepers, wood frogs, grey treefrogs, eastern newts, spotted and blue-spotted salamanders; reptiles such as garter and ribbon snakes; birds such as wood ducks, hooded mergansers, broad-winged hawks, barred owls, screech owls, Acadian flycatchers, Eastern phoebes, and mourning warblers; mammals such as beavers, raccoons, white-tailed deer, and eastern chipmunks.

NoAddresses existing forest and wetland cover only. Will value existing cover only

Proximity of a forest to a wetland

This layer is the inverse of the previous, valuing forest immediately adjacent to wetlands (and out 10 m) with a maximum score of ten. The value breakdown is the same as the above layer.(gibbs 1998a, 1998b; Pope et al. 2000; Lamoureux et al. 1999; guerry and hunter 2002; Lehtinen et al. 1999).

NoAddresses existing forest and wetland cover only. Will value existing cover only

Distance Score

0-10 10

10-30 9

30-60 8

60-120 7

120-200 6

200-300 5

300-500 4

500-1000 3

1000-2000 2

2000 + 1

Distance Score

0-10 10

10-30 9

30-60 8

60-120 7

120-200 6

200-300 5

300-500 4

500-1000 3

1000-2000 2

2000 + 1

229



Proximity to a watercourse (with a fill line)

There is value to being in close proximity to a watercourse or water body. Water bodies include lakes and ponds of all sizes, and any open water or wetland system, not including swamp forests (see below). Some positive influences of riparian or water features on terrestrial are nutrient exchange, source of drinking water, breeding areas, and the connectivity function provided by valleys, and the influence extends beyond the riparian, and on to tablelands. The nature of this influence changes within this area, but at the scale we are working at, it is difficult to be more precise, and to tease out the different positive influences of riparian on terrestrial. Therefore, all areas that were determined to be within or in proximity to water features were given maximum points. Proximity to a watercourse was based on distance to those lands regulated by TRCA under Ontario Regulation 158 (defined by the ‘fill line’).

YesShows preference for areas within fill line and 30 m beyond fill line, but also values areas up to 200 m beyond fill line. Will affect natural cover distribution in a negative way due to the greater abundance of watercourses in the headwater areas to the north in the TRCA region. This criterion will also improve the matrix influence, patch size and connectivity around watercourses.

Proximity to a watercourse or water body (without a fill line)

In those areas where a ‘fill line’ does not exist (not regulated by TRCA under Ontario Regulation 158), areas that were determined to be within or in proximity (up to 120 m) to a watercourse or water body were given maximum points. With regards to the interface between aquatic and terrestrial ecosystems, it is assumed that the most ecologically beneficial placement of new natural cover would be within 200 m from a water feature.

YesValues areas 120 m out from a water course or water body where there is no existing fill line Will affect natural cover distribution in a negative way due to the greater abundance of watercourses and water bodies in the headwater areas to the north of the TRCA region. This criterion will also improve the matrix influence, patch size and connectivity around water courses and bodies.

Distance to ScoreFill Line

Within Fill Line 10

0 to 30 10

30 to 200 9,8,7,6, 5,4,3, 2,1 (even breaks)

>=200 0

Distance to ScoreWC?Wb

0 to 120 10

120 to 200 9,8,7,6, 5,4,3, 2,1 (even breaks)

>=200 0

230



FEASIBILITY CRITERIA

PSW This layer addresses the opportunities where expansion of the existing TNh System can and might be possible due to the presence of a Provincially Significant Wetland (PSW). A PSW provides some means of protection to the landscape due to current policies, and this ‘protection’ currently extends beyond the PSW feature out to 120 m. According to Section 2.1 of the Provincial Policy Statement (PPS), development or site alterations will not be allowed within a significant wetland. Development applications within 120 m of a PSW must show through an Environmental Impact Statement (EIS) that there will be no negative impact on the feature or its function.

YesAwards value for existing PSWs and shows preference for lands within 120 m of the feature to build up on existing cover. This criterion will affect distribution in a negative way due to the more northerly location of the majority of PSWs in the TRCA region. Matrix influence in the vicinity of PSWs will be improved.

ANSI This layer addresses the opportunities where expansion of the existing TNh System might be possible due to the presence of an Area of Natural and Scientific Interest (ANSI). An ANSI provides some means of protection to the landscape due to current policies, and this ‘protection’ currently extends beyond the feature. According to the Nh Reference Manual for Section 2.3 Does reference number change in new PPS? of the PPS, development applications within an ANSI will not be allowed. Development applications within 10 m of an ANSI must show through an EIS that there will be no negative impact on the feature or its function.

YesAwards value for existing ANSIs and shows preference for lands within 10 m of the feature to build up on existing cover. This criterion will affect distribution in a negative way due to the more northerly location of the majority of ANSI sites in the TRCA region. Size and shape of patches as well as matrix influence in the vicinity of ANSIs will be improved.

Distance Score

Within Feature 10

0 to 120 8

120+ 0

Distance Score

Within Feature 10

0 to 10 8

10+ 0

231



ESA This layer addresses the opportunities where expansion of the existing TNh System can and might be possible due to the presence of an Environmentally Significant Area (ESA). An ESA provides some means of protection to the landscape due to current policies, and this ‘protection’ currently extends beyond the feature. According to the Nh Reference Manual for Section 2.3Does reference number change in new PPS? of the PPS, development applications within an ESA will not be allowed. Development applications within 10 m of an ESA must show through an EIS that there will be no negative impact on the feature or its function.

YesAwards value for existing ESAs and shows preference for lands within 10 m of the feature to build up on existing cover. This criterion will affect distribution in a negative way due to the more northerly location of the majority of ESAs in the TRCA region. Size and shape of patches as well as matrix influence in the vicinity of ESAs will be improved.

Fill/Fill Extension This layer addresses the opportunities where expansion of the existing TNh System might be possible due to the influence that the TRCA has in this area.

YesShows preference for areas within 10 m of the fill/fill extension line feature to build up on existing cover. This criterion will weakly affect distribution in a negative way due to the greater abundance of watercourses associated with fill/fill extension lines in the headwater areas (along ORM) to the north in the TRCA region. Size of patches as well as matrix influence in the vicinity will be improved. Shape is affected in a negative way because most fill lines form long, linear boundaries around valley systems (unfavourable shape).

Distance Score

Within Feature 10

0 to 10 8

10+ 0

Distance Score

Within Feature 10

Outside Feature 0

232



TRCA property This layer addresses the opportunities where expansion of the existing TNh might be possible due to the mandate that the TRCA has to manage its own lands according to conservation principles.

YesShows preference for lands within 10 m of TRCA-owned lands to build up on existing cover. This criterion will affect distribution in a negative way due to the more northerly location of the majority of TRCA properties in the TRCA region. Size of patches and matrix influence in the vicinity of TRCA property will be improved.

Greenbelt Plan This layer addresses the opportunities where expansion of the existing TNh System might be possible due to the influence of being contained within the Natural heritage System in lands identified in the Ontario greenbelt Plan (MMAh, 2005b

YesShows preference for lands classified as Natural heritage System in the greenbelt Plan to build up on existing cover. This criterion will affect distribution in a negative way due to geographical location of the greenbelt in the TRCA region. Size and shape of patches as well as matrix influence on and in the vicinity will be improved.

oRM This layer addresses the opportunities where expansion of the existing TNh System might be possible due to the influence of the Oak Ridges Moraine (ORM) Conservation Plan (MMAh, 2002)

YesShows preference for lands classified as Core and Corridor Areas in the ORM CP to build up on existing cover. This criterion will affect distribution in a negative way due to geographical location of the ORM in the TRCA region. Size and shape of patches as well as matrix influence on and in the vicinity will be improved.

Niagara Escarpment

This layer addresses the opportunities where expansion of the existing TNh System might be possible due to the influence of the Niagara Escarpment Plan (NEC, 2005)

YesShows preference for lands classified as Natural and Protection Areas in the Niagara Escarpment Plan to build up on existing cover. This criterion will affect distribution in a negative way due to geographical location of the Niagara Escarpment in the TRCA region. Size and shape of patches as well as matrix influence on and in the vicinity will be improved.

Distance Score

Within Feature 10

Outside Feature 0

Designation Score

greenbelt NhS 10

Outside Feature 0

Designation Score

Core 10

Corridor 0

Countryside Area 7

Settlement Area 3

Designation Score

Natural Area 10

Protection Area 8

Rural Area 8

233



Rouge Park (South of Steeles)

This layer addresses the opportunities where expansion of the existing TNh System might be possible due to the influence of the Rouge Park. *Note: Although ecological criteria have been developed (Schollen, 2003) to define the comprehensive of Rouge Park North, detailed field data is required- beyond the scope of this analysis.

YesShows preference for lands classified as within the Rouge Park boundary to build up on existing cover. This criterion will affect distribution in a more positive way due to geographical location of the Rouge Park in the TRCA region. Size and shape of patches as well as matrix influence on and in the vicinity will be improved.

Designation Score

Within Park Boundary 10

Outside Park 0

234

R e f e R e n C e s

ministry of municipal Affairs and Housing. 2002. oak ridges moraine conservation Plan. Queen’s

Printer for ontario, toronto, on.

ministry of municipal Affairs and Housing. 2005. greenbelt Plan. Queen’s Printer for ontario,

toronto, on.

niagara escarpment commission, 2005. niagara escarpment Plan. Queen’s Printer for ontario,

toronto, on.

Schollen and company Inc. 2003. rouge north Implementation manual. trcA, terra

geographical Studies, unterman mcPhail Associates, Aquafor beech ltd.

235

Appendix E-3- Information layers needed to run analysis

CRITERIoN (RASTER) LAYER INPUT LAYERS

1 Distance to Natural Area Natural Cover (2002)

2 Distance from Roads Major Roads Layer

3 Distance from Urban Natural heritage Land Use Areas - “Built up Area”

4 Interior Forest generated from Natural Cover (2002)

5

Proximity of Forest to Wetlands Natural Cover (2002) - Wetlands are used to create a straight line distance grid. Forest & Successional polygons are then merged and multiplied by the distance grid.

6 Proximity of Wetland to Forest Natural Cover (2002) - Forest and successional polygons are merged and used to create a straight line distance grid. Wetland polygons are then merged and multiplied by the distance grid.

7

Watercourses in a fill line

TRCA’s fill line is used to create a straight line distance grid *

8

Watercourses outside a fill line

Watercourses outside of a fill line are clipped and used to generate straight line distance grid *

9 ANSI ANSI shapefile *

10 ESAs Environmentally Sensitive Areas *

11 Valley & Stream Corridor TRCA Fill and fill extenstion mapping *

12 greenbelt Landuse Natural heritage Areas defined by the greenbelt Plan *

13 Niagara Escarpment NEC Landuse (MNR)

14 Oak Ridges Morraine ORM Landuse (MNR)

15 Provincially Significant Wetlands PSWs (MNR) *

16 Rouge Park Rouge Park boundary *

17 TRCA Property TRCA Property Layer *

* The latest versions available in 2002.

Documents

TERRESTRIAL NATURAL HERITAGE SYSTEM STRATEGY