**IDENTIFYING MINIMUM SETS OF CONSERVATION SITES FOR REPRESENTING
BIODIVERSITY IN CANADA:**

**A COMPLEMENTARITY APPROACH**

**\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_**

**Kathryn Freemark**

**Harold Moore**

**David M. Forsyth**

**A.R.E. Sinclair**

**Denis White**

**Tom Barrett**

**R. L. Pressey**

**TECHNICAL REPORT SERIES No. xxx**

Headquarters **1999**

Canadian Wildlife Service

**\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_**

**IDENTIFYING MINIMUM SETS OF CONSERVATION SITES FOR REPRESENTING
BIODIVERSITY IN CANADA:**

**A COMPLEMENTARITY APPROACH**

**\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_**

**Kathryn Freemark**

National Wildlife Research Centre

Canadian Wildlife Service

Ottawa, ON K1A 0H3

Canada

**Harold Moore**

GeoInsight Limited

PO Box 24196

Hazeldean RPO

Kanata, ON K2M 2C3

Canada

**David M. Forsyth, A.R.E. Sinclair**

Centre for Biodiversity Research

University of British Columbia

Vancouver, BC V6T 1Z4

Canada

**Denis White**

U.S. Environmental Protection Agency

Corvallis, OR 97333

USA

**Tom Barrett, R. L. Pressey**

New South Wales National Parks & Wildlife Service

Armidale, NSW 2350

Australia

**TECHNICAL REPORT SERIES No. xxx**

Headquarters **1999**

Canadian Wildlife Service

This publication may be cited as:

Freemark, K., H.Moore, D.M. Forsyth, A.R.E. Sinclair, D.White,

T.Barrett and R.L. Pressey. 1999. Identifying minimum sets

of conservation sites for representing biodiversity in Canada: A

complementarity approach. Technical Report No. xxx, Canadian

Wildlife Service, Headquarters, Environment Canada, Ottawa K1A 0H3

**SUMMARY**

**Objectives**

-   To construct an equal-area geo-referenced sampling grid for Canada.

-   To digitise available range maps for common and COSEWIC species in
    Canada.

-   To identify important sites for biodiversity in Canada using a new
    statistical predictor of conservation value.

    **Methods**

-   An equal-area grid of 10,000 km2 hexagons was constructed from the
    truncated icosahedron on a Lambert azimuthal equal-area map
    projection.

-   The ranges of 697 common and COSEWIC mammals, birds, reptiles, and
    amphibians, and COSEWIC fish, plants, lepidoptera and molluscs were
    digitised within the equal-area grid.

-   The areas of 217 ecoregions were also digitised within the
    equal-area grid.

-   C-Plan, a conservation planning software program, was used to
    identify important conservation areas and minimum sets of sites
    required to represent either (i) each taxa once, and/or (ii) 12 % of
    the area of each ecoregion, using 10 combinations of taxa and
    ecoregions.

    **Results**

-   An equal-area grid of 1,455 10,000 km2 hexagons was constructed for
    Canada; 1,275 hexagons either completely or partially covered
    terrestrial Canada.

-   There were significant positive correlations between the
    irreplaceability of sites (hexagons) for most of the focal groups.

-   We identified four general areas of special importantance for
    biodiversity conservation in Canada; Okanagan Valley (British
    Columbia), mid-Prairies (Manitoba and Saskachewan) Niagara Peninsula
    (Ontario). Other important areas were also located near to the
    southern United States border.

-   Minimum set analyses indicated that all mammals could be represented
    in 16 hexagons, all birds in 14 hexagons, all amphibians and all
    reptiles in 9 hexagons each, and all COSEWIC species in 55 hexagons.
    12 % of all 217 ecoregions could be represented within 188 hexagons.
    All terrestrial vertebrates could be represented in 31 hexagons, and
    all terrestrial vertebrates and 12 % of all ecoregions in 187
    hexagons.

-   Of the sub-sets that we used as focal groups, using all mammals or
    all birds captured the greatest proportion of taxa in other focal
    groups.

    **Conclusions**

-   The most important sites for biodiversity conservation in Canada are
    located near the southern United States border. This is because (i)
    many non-COSEWIC species that are common in continental North
    America occur in southern Canada, and (ii) many COSEWIC species are
    also located in southern Canada. With increasing latitude there are
    fewer species, and these species have larger distributions (i.e.,
    are generally common).

-   Since there was high overlap in the distributions of important
    conservation sites between groups of taxa (birds, mammals, reptiles,
    and amphibians) deciding the location of protected areas on the
    basis of just one of these groups alone could also benefit other
    taxa.

-   The 12 % area-target for ecoregion alone did not protect all
    species, indicating that area-based targets may not represent all
    biodiversity.

-   The techniques developed during this study show considerable promise
    for identifying important areas for biodiversity conservation at
    different scales and in different parts of the globe. The principal
    limiting factor for the application of this methodology is the
    availability of suitable species distribution data.

**BACKGROUND**

Considerable attention has been focused on the conservation and
management of biodiversity in Canada, particularly since the Convention
on Biological Diversity was signed in 1993. A recent international
scientific review of biodiversity (Heywood & Watson, 1995), clearly
indicates that past and projected human induced stresses pose
significant risks to the biodiversity and functioning of ecosystems.
These and other agreements and reviews (e.g. Environment Canada, 1994;
CFS, 1997) emphasise the need to assess the status of biodiversity and
to better understand the causes and consequences of changes in
biodiversity. Furthermore, the economic benefits of conserving
biodiversity are beginning to be recognised and documented (Perrings et
al., 1995; Arrow et al., 1995).

Canada was the first industrialised nation to sign the Convention on
Biological Diversity. Canadians are concerned about the degradation of
ecosystems and loss of biodiversity from human activities for aesthetic,
economic, ecological, cultural and educational reasons (BCO, 1995;
Heywood & Watson, 1995). For example, degraded forest, agricultural and
aquatic ecosystems are less productive and require greater inputs if
they are to continue supporting the wildlife and human communities that
depend on them. All of these concerns are ultimately related to the loss
of genetic diversity, the primary raw material that is filtered by
natural selection, resulting in evolutionary and ecological adaptation
of biota to environmental conditions. Minimising additional loss of
biodiversity will provide the best assurance that biota will adapt to
the increasing rate and spatial extent of environmental change (Pratt &
Cairns, 1992), and that societal values can be sustained.

Achieving the vision outlined in the Canadian Biodiversity Strategy
(BCO, 1995) requires multiple-scale hierarchical approaches. Such
approaches are inter-disciplinary and should include contributions from
ecology, geography, agriculture and forest science, and social sciences
such as economics, sociology and land-use planning (White et al., 1998).
With collaboration from many perspectives, more appropriate databases
and analytic approaches can be formulated. More significantly, a
co-operative, cross-sectoral approach based on partnerships promises
better linkage between scientific perspectives and the spatial,
temporal, and political structure of decision-making (Lubchenco, 1995).
Clarifying the scientific status of biodiversity can set the stage for
moving the biodiversity debate from one primarily about the facts of the
issue to one about values (c.f. Williams & Gaston, 1994; Williams et
al., 1996).

In this project, we extend and apply new methods of spatial analysis for
geo-referenced data in order to identify important areas for achieving
national conservation goals. In other words, with limited resources to
study or conserve biodiversity, we ask where are the best places for
further investigation or conservation activity? At the national scale,
our analyses will identify priority regions for conservation effort.
Within regions, the study will identify locations of potential sites for
conservation efforts such as establishing a network of protected areas
representative of regional biodiversity, or implementing changes to
forestry or agricultural practices that could benefit biodiversity.
While protected areas are a key component to a biodiversity conservation
strategy, their long-term value will depend on sound stewardship in
remaining, and particularly adjacent, areas (Pressey et al., 1995;
Flather et al., 1997). To improve the network of protected areas in
Canada, comprehensive criteria need to be developed for determining
priority sites for further conservation action. Examples of such sites
might be areas supporting a high diversity of species, migratory
species, representative species, or unique species (BCO, 1995) that
occur outside current protected areas. This project will extend the
focus of biodiversity conservation and management beyond from multiple
single-species approaches to a single multiple-species approach.
Analyses will provide insights into the ability of sites to contribute
to the representation of biodiversity at the national scale, and
indicate gaps in existing conservation and management strategies. The
approaches developed will aid in the process of decentralising resource
management decision-making to the community level, while maintaining the
larger-scale perspective necessary for integrated planning to ensure
sustainable resource use.

**FACILITIES**

As a collaborative project, the facilities of a number of agencies were
used including GIS and computer analysis labs at the University of
British Columbia, the US-EPA in Corvallis, Oregon, the New South Wales
National Parks Wildlife Service in Australia, the Canadian Wildlife
Service and Gregory Geoscience Limited. The diversity of these
facilities permitted parallel analysis and quick turn around of output
products. Along with the hardware at these facilities were a number of
custom software packages and data sets.

**METHODS**

**GEOSPATIAL SAMPLING FRAMEWORK**

For large-scale studies of the distribution of biodiversity, an analysis
structure that provides comparability is most appropriate (see Conroy &
Noon, 1996, on issues of using habitat polygons). This study extends a
sampling framework that was designed to provide a regular, systematic,
hierarchical hexagonal spatial structure for environmental monitoring
and assessment by the U.S. Environmental Protection Agency (White et
al., 1992). The hexagon tessellation is attractive because it minimises
spatial distortion and, if constructed on an equal-area map projection,
provides an equal-area sample (White et al., 1992). Furthermore,
hexagons are generalisable to both larger and smaller spatial scales.
This becomes important for extending regional and national assessments
to continental and global scales. An equal-area grid also provides a
common spatial unit for comparison of diverse data types whereas
ecoregions, for example, are not comparable but by definition unique.
Equal-area units also minimise confounding due to species-area
relationships, a potential problem if other units such as ecoregions
(Moore, 1997) or counties (Dobson et al., 1997) are used.

The sampling framework (see map 1 in appendix) was a grid of hexagons,
each of 10,000 km2 developed for the US Environmental Protection Agency
(White et al., 1992; see also Csuti et al., 1997). Briefly, the grid was
constructed from the truncated icosahedron on a Lambert azimuthal
equal-area map projection. Compared to other possible approaches to
equal-area sampling this method has minimal distortion and deviation in
area (White et al. 1992). We chose the 10,000 km2 scale for our grid
because, in our judgement, it best suited the scale of the range data
available for the majority of taxa. There were 1275 hexagons that were
completely or partly enclosed by the terrestrial political boundaries of
Canada.

The grid provided an accounting mechanism that serves several purposes.
First, a single set of analysis units facilitated comparison of
different data sets. Second, the uncertainty inherent within available
range maps could be minimised by limiting the precision of location
assignment to this scale. Furthermore, concerns about the
confidentiality of precise locations of occurrence for some COSEWIC
species was alleviated by using a 10,000 km2 grid. Finally, there is a
strong argument for generalising species distributions from the precise
data of field observations in order to account for the biases in
observation locations and sightability**.**

The size of the hexagons thus reflects a compromise between the desire
for spatial detail and the constraints of reasonable spatial
representation of species life histories, data collection,
confidentially, and computational feasibility. Solutions to spatial
analyses can depend, of course, on the sizes of units used (Stoms,
1994).

**INPUT DATA**

*Range data*

Our range data for 796 taxa (Appendix 1; summary in Table 1) came from
two sources. The ranges of terrestrial mammals, birds, amphibians,
reptiles, fish, plants, molluscs and lepidoptera listed as endangered,
threatened, or vulnerable by the Committee on the Status of Endangered
Wildlife in Canada (hereinafter termed 'COSEWIC') were provided to us by
that organisation .Infornation contained in each COSEWIC species report
was used to generate range maps. For example , sometimes there was
specific coordinate data from field surveys which could be mapped
directly (most common with plant data). Other reports had range maps
attached which were digitized for GIS input. While still other reports
only had a discripition of the range which had to be transfered to maps
before digitizing at 1:1,000,000 scale. The ranges of 'common' (i.e. not
listed by COSEWIC) mammals, birds, amphibians and reptiles were
digitised from published range maps. For Mammals, Reptiles and
Amphibiansp paper range maps were provided by the Canadian Museum of
Nature from their publications \"Mammals of Canada\" and \"Introduction
to Canadian Amphibians and Reptiles\". For the common bird range maps
digital files for summer, winter and all-year ranges were provided by
the Canadian Wildlife Service (Ontario Region).In this study the summer
and all-year ranges were combined to represent the areas in Canada where
the species may be found breeding. Where range-maps specified
winter-only ranges for birds these areas were not included in our
analyses. Although marine species were excluded from our analyses, some
coastal bird species that also breed inland were included. The presence
or absence of taxa in each of the 1,275 hexagon was determined using GIS
overlay methods and formed the data used in subsequent analyses.
Examples of species richness distribution can be seen in map 2 in the
appendix.

**Table 1.** Number of common, endangered, threatened and vulnerable
taxa used in analyses.

Status

Taxonomic Group Common Endangered Threatened Vulnerable Total

Mammals 123 5 5 19 152

Birds 342 14 7 20 383

Amphibians 37 2 0 7 46

Reptiles 33 2 4 7 46

Fish - 4 15 39 58

Plants - 33 36 38 107

Molluscs - 1 1 0 2

Lepidoptera - 1 0 1 2

Total 535 62 68 131 796

*Ecoregions*

The representation of distinct ecological areas has been assumed to also
represent species diversity (e.g. Turner et al., 1992), but the limited
empirical evidence does not support this, at least at small scales
(Ferrier and Watson, 1997). In Canada, a conservation target of 12 % has
been specified for representing each of the country's ecosystems in
protected areas (Turner et al., 1992). Hence, a further objective of
this study was to evaluate the effectiveness of using a target of 12 %
of each ecoregion area for achieving representation of the 796 taxa
described above.

Canada has been classified into a total of 217 ecoregions (Appendix 2)
based upon spatial differences in both abiotic and biotic factors.
Ecoregions are "characterised by distinctive large order landforms or
assemblages of regional landforms, small order macro- or mesoclimates,
vegetation, soils, water, and regional human activity patterns/uses"
(Ecological Stratification Working Group, 1996). For a detailed
description of ecoregions see Ecological Stratification Working Group
(1996). The area of each ecoregion present within hexagons was
calculated from maps provided by the Agriculture and Agri-Food Canada,
Research Branch, Centre for Land and Biological Resources Research and
Environment Canada, State of the Environment Directorate, Ecozone
Analysis Branch, Ottawa/Hull.

*Focal groups*

We subdivided taxa and ecoregions into 10 'focal groups' in order to
expand and better interpret our analyses (Table 2). The four taxonomic
groups with comprehensive data for both common and COSEWIC species
(i.e., mammals, birds, amphibians and reptiles) were each a focal group.
This is because conservation decisions are frequently made on the basis
of one or more of these well-studied groups with the assumption that
other taxonomic groups might be similarly distributed (e.g., Kershaw et
al., 1994). In other words, we wished to test how well these four focal
groups act as surrogates for the distribution of taxa within other focal
groups. Since many protected areas and conservation strategies in North
America are based upon the location of legally defined endangered
species (Dobson et al., 1997; Flather et al., 1998), we used three
combinations of COSEWIC species as focal groups. We used COSEWIC Birds
as a focal group because a new federal program, termed 'Partners In
Flight', has been initiated to protect COSEWIC-listed birds in Canada
(Dunn, 1997). We used COSEWIC plants as a focal group because in the
absence of data for common plants we wished to explore how well plants
acted as a surrogate for other focal groups. We pooled all terrestrial
vertebrates (i.e., Mammals, Birds, Reptiles and Amphibians into a single
focal group, 'Vertebrates', in order to identify important sites for
vertebrate fauna in Canada.

We used the area of ecoregions as another focal group. As mentioned
earlier, the target for this focal group was to represent 12 % of the
area of each ecoregion. This was an approximation to the federal goal of
representing 12 % of Canada's ecosystems (Turner et al., 1992). We then
combined 'Vertebrates' and 'Ecoregions' into a single focal group,
'Vertebrates-Ecoregions', to explore how this combination affected the
identification of important sites.

**Table 2.** Description of the 10 focal groups used in analyses. *n* =
the number of taxa and/or ecoregions in the target (see text). For a
list of taxa and ecoregions see Appendices.

Name Target

Mammals Common, endangered, threatened, and vulnerable mammal ( *n* =
152).

Birds Common, endangered, threatened, and vulnerable birds (*n* = 383).

Amphibians Common, endangered, threatened, and vulnerable amphibians
(*n* = 46).

Reptiles Common, endangered, threatened, and vulnerable reptiles (*n* =
46).

Vertebrates Common, endangered, threatened, and vulnerable mammals,
birds, reptiles and amphibians (*n =* 627).

COSEWIC Endangered, threatened, and vulnerable mammals, birds,

amphibians, reptiles, fish, plants, molluscs and Lepidoptera (*n* =
261).

COSEWIC Birds Endangered, threatened, and vulnerable birds (*n* = 41).

COSEWIC plants Endangered, threatened, and vulnerable plants (*n* =
107).

Ecoregions 12 % of the area of each of 217 ecoregion ( *n* = 217).

Vertebrates-Ecoregions Common, endangered, threatened, and vulnerable
mammals, birds, reptiles and amphibians, and 12 % of the area of each
ecoregion ( *n* = 844).

*Analyses*

We used a recently developed predictor of conservation value, termed
*irrepleceability*, to identify important sites (i.e., 10,000 km2
hexagons) for the representation of focal groups (S. Ferrier, R.L.
Pressey and T.W. Barrett, New South Wales National Parks and Wildlife
Service, unpublished manuscript). Irrepleaceability is a statistical
approach to estimating the importance of a site to achieving a specified
conservation goal. If *Rx_included* is the number of representative
combinations that include site *x*, *Rx_excluded* is the number of
representative calculations that do not include site *x*, and
*Rx_removed* is the number of representative combinations that include
site *x* and would still be representative if site *x* was removed. The
calculation of irreplaceability for site *x*, *Irrx*, is thus:

$$\text{Irr}_{x} = \frac{(R_{x_{\text{included}}} - R_{x_{\text{removed}}})}{(R_{x_{\text{included}}} + R_{x_{\text{excluded}}})}$$

The predictor uses a statistical approach based on the central limit
theorem to estimate, for a given feature or combination of features, the
expected frequency distribution of the area protected by all possible
site combinations of a given size. The expected distribution is then
used to estimate the proportion, and hence number, of these combinations
that would achieve the specified target for the feature(s). The
individual taxa irreplaceabilities within a site are then added to give
a summed irreplaceability value for each site (S. Ferrier, R.L. Pressey
and T.W. Barrett, New South Wales National Parks and Wildlife Service,
unpublished manuscript).

We calculated summed irreplaceabilities for the focal groups listed in
Table 2. We then tested for the strength of focal group congruence in
summed irreplaceabilities using Spearman's rank correlation coefficients
(Zar, 1996).

All irreplaceability and minimum set analyses were performed using
C-Plan (Finkel, 1998; New South Wales National Parks and Wildlife
Service, PO Box 402, Armidale, NSW 2350, Australia). Statistical testing
was performed with SPSS® 8.0 (Norušis, 1998).

*Minimum-set algorithms*

We used heuristic algorithms to identify approximate minimum-set
solutions of sites required to represent combinations of taxa and
ecoregions. Although heuristic algorithms seldom provide optimal
solutions (Camm et al., 1996; Csuti et al., 1997), when the number of
sites is large and the reservation goal is complex (as was the case in
this study) heuristic algorithms can provide near-optimal solutions in
realistic periods of time (Pressey *et al*., 1996, 1997). Two general
classes of heuristic algorithm have been proposed (Csuti *et al*. 1997),
and the outcome of either depends both on the decision-rules of the
algorithm and the conservation target to which the algorithm is applied.
Richness-based algorithms start with the site containing the most
species and sequentially add sites with the most new species (e.g.,
Margules *et al*., 1988). A major disadvantage of richness-based
algorithms is that a site containing a species not present in other
sites may be ranked lower than a site containing several species more
common among unreserved sites. In contrast, rarity-based algorithms
select sites according to the rarity of species and thus tend to attain
the conservation goal with fewer sites (e.g., Kershaw *et al*., 1994;
Csuti et al., 1997). Our algorithms used summed irreplaceability values
(see above), a form of rarity-based algorithm, and employed the
following rule sequence. First, select the site with the highest summed
irreplaceability. Second, in the event of a tie, select the site with
the most additional taxa already represented. Third, if still a tie then
select the first site in the list. After each selection summed
irreplaceability was recalculated for the remaining sites (i.e., those
not yet represented in the solution set) for the features (taxa or
ecoregions) yet to be represented. This iteration was repeated until the
target representation of taxa was achieved. Our target for both
irreplaceability calculations and minimum set algorithms was to
represent taxa and/or 12 % of the area of ecoregions once and to
represent 12 % of the total area of each ecoregion.

*Surrogacy*

To investigate further the effects of focusing reservation efforts on a
single focal group of taxa, we calculated how many taxa in the other
focal groups were added at each iteration in the minimum set solutions
for each focal group (see also Dobson et al., 1997; Howard et al.,
1998). These data are presented as cumulative % of the taxa in each
other focal group represented through the sequence of site selection. We
then determined the number of additional sites required to achieve
representation of the taxa in the other focal groups with further
minimum set algorithms. This was achieved by including the minimum set
solutions from other focal groups as mandatory reservations prior to
initiating the new minimum set algorithm

**RESULTS**

*National patterns of richness and irreplaceability*

Patterns in the national distribution of species richness and summed
irreplaceability for the different focal groups are shown in (Maps 2 and
3 in the appendix). There is a consistent trend toward greater species
richness from north to south for all groups, with most species occurring
near the United States border. The highest summed irreplaceabilities
occurred in several nodes along the United States border. Summed
irreplaceability declined with increasing latitude. For all groups there
are fewer taxa in northern Canada (low species richness), and those taxa
are widely distributed between sites (low summed irreplaceability). In
contrast, near the United States border there are more species, many of
which are found within only one or several sites.

There was high congruence in both species richness and summed
irreplaceability between the focal groups, with significant (*P* \<
0.05) Spearman rank correlations for all comparisons (Table 3). Patterns
were similar for the focal groups (not shown). The strongest
correlations were between Birds and Mammals, Reptiles, Amphibians, and
COSEWICs. The weakest correlations were those with Ecoregions. Hence,
sites containing the most species for one focal group tended to contain
the most species for other focal groups. However, high species richness
or summed irreplaceability for a site was not always a good predictor
for other taxa (Figures 1-2).

**Table 3.** Summary of correlations between focal groups for species
richness and summed irreplaceability. Values are Spearman rank
correlation coefficients. *N* = 1,275 for all comparisons.

Birds Amphibians Reptiles Ecoregions

*Species richness*

Mammals 0.96 0.85 0.75 0.26

*P* \< 0.001 *P* \< 0.001 *P* \< 0.001 *P* \< 0.001

Birds 0.84 0.77 0.26

*P* \< 0.001 *P* \< 0.001 *P* \< 0.001

Amphibians 0.83 0.13

*P* \< 0.001 *P* \< 0.001

Reptiles 0.10

*P* = 0.001

*Summed Irreplaceability*

Mammals 0.48 0.52 0.52 0.30

*P* \< 0.001 *P* \< 0.001 *P* \< 0.001 *P* \< 0.001

Birds 0.41 0.51 0.25

*P* \< 0.001 *P* \< 0.001 *P* \< 0.001

Amphibians 0.81 0.23

*P* \< 0.001 *P* \< 0.001

Reptiles

![](media/image1.emf){width="7.478472222222222in"
height="7.728472222222222in"}

Figure 1. Focal group congruence in species richness between 1,275
10,000 km2 equal-area sites.

![](media/image2.emf){width="7.457638888888889in"
height="8.020833333333334in"}

**Figure 2.** Focal group congruence in summed irreplaceability between
1,275 10,000 km2 equal-area sites.

*Minimum set representations*

The implications of the above patterns for conservation strategies were
explored with minimum set algorithms that selected sites according to
their summed irreplaceability. Focal groups with strongly correlated
summed irreplaceabilities would thus be expected to represent each other
better than those with weak correlations. The location of sites required
to represent each species at least once (See map 4 in appendix for
examples) was congruent with the hotspots of summed irreplaceability
shown in Map 3. Remarkably few sites were required to represent taxa in
each focal group at least once, indicating the effectiveness of using
rarity-based measures like summed irreplaceability for identifying
priority conservation areas (Table 4).

The number of taxa in a focal group was not necessarily a good predictor
of how many sites were required to represent all taxa within that group.
For example, to represent all 107 COSEWIC plants required 28 sites, but
628 Vertebrates were represented within just 33 sites. Similarly, 383
Birds were represented in 14 sites, but 153 Mammals required 16 sites.
These differences arise from the spatial distribution of taxa that is
specific to each focal group.

An interesting result was that the 9 sites were required to represent 46
taxa each of Amphibians and Reptiles. However, only one of the nine
sites was common to both minimum sets, and this same site was also
present in the minimum sets for Birds and Mammals.

Almost 15 % of the available 1,275 sites were required to represent
Ecoregions. This was due to specifying an area-based target for
Ecoregions, rather than mere representation. One less site was required
to represent Vertebrates-Ecoregions; such a result occurs because of the
different summed irreplaceabilities associated with the additional
targets and because C-Plan does not identify optimal minimum sets.

*Accumulation of taxa in minimum sets*

Accumulation curves represent the cumulative number of features within
the focal group that are represented at each site selection. The rate of
accumulation of features was greatest in the first few site selections
(Figure 3). This arises from the selection algorithm first choosing

**Table 4.** Approximate minimum number of 10,000 km2 sites required to
achieve representation of features within 10 focal groups. The algorithm
used iteratively selected sites with the highest summed irreplaceability
until all features within that focal group were represented.

Focal group Number of taxa and/or Ecoregions Number of sites

Mammals 153 16

Birds 383 14

Amphibians 46 9

Reptiles 46 9

Vertebrates 628 31

COSEWIC 264 55

COSEWIC Birds 41 9

COSEWIC plants 107 28

Ecoregions 217 188

Vertebrates-Ecoregions 845 187

Since summed irreplaceability is primarily determined by the
distribution of the rarest features, the initially rapid rate of
accumulation indicates either that those sites also contained many
common features. Differences in the rates of accumulation between focal
groups were greatest in the initial two or three selections, but
thereafter the rates of accumulation generally converged.

*Surrogacy of focal groups*

The relative effectiveness of using a focal group, or combinations of
focal groups, as surrogates for representing other taxa is shown in
Table 5 and Figures 4-6. We considered the extent of representation of
Mammals, Birds, Reptiles, and Amphibians to be the critical test of
surrogacy; only for these groups was data available for common species,
and hence were most likely to approximate the actual distribution of
unsampled taxa (see Gaston, 1994).

Mammals and Birds achieved better representation of other focal groups
than did Reptiles or Amphibians (Figure 4). Although this result could
partly be attributed to fewer sites being required for the latter groups
(9 sites each compared to 16 and 14 for Mammals and Birds,
respectively), Mammals

( *n* = 153 taxa) achieved better representation of the other focal
groups (all \>80 %) than did Birds

( *n* = 383). Hence, it is the spatial array of taxa that is more
important in determining surrogacy. Mammals also achieved a high
representation of COSEWICs (almost 60 %), whereas most other focal
groups did poorer. Since Mammals, Birds, Reptiles and Amphibians
included their respective COSEWIC taxa, the relatively poor surrogacy of
these groups for COSEWICs must be due to low overlap with the COSEWICs
not included in those groups (i.e., fish, plants, molluscs and
Lepidoptera).

Given the small number of sites involved, the COSEWIC Birds and COSEWIC
Plants achieved very good representation of other focal groups (Figure
5). COSEWIC Plants was better overall than COSEWIC Birds. This result
further emphasises (i) the sensitivity of our minimum set algorithm to
the distributions of the rarest taxa, and (ii) that there was
considerable overlap in the distribution of these rare taxa.

Ecoregions as a focal group represented most (i.e., \>90 %) Mammals and
Birds (Figure 6), and also Amphibians and Reptiles (not shown for
clarity). However, since the 188 sites were almost 15 % of total
available sites, and relative to the equivalent number of sites selected
by Mammals, Birds, Reptiles and Amphibians (i.e., 16) the 12 % area
target for Ecoregions was an inefficient surrogate for the other
taxa-based focal groups. Vertebrates-Ecoregions was a better surrogate
for other focal-groups than Ecoregions, but still captured \< 80 % of
COSEWIC groups.

**Figure 3.** The relation between the cumulative number of sites
sampled and the cumulative number of taxa represented for a variety of
focal groups. Note that the scales differ between graphs. Sites were
selected iteratively according to highest summed irreplaceability.

**Table 5.** Summary of representation achieved for the 10 focal groups
by using another focal group as the selection group. To standardise for
the different number of taxa in focal groups, representation is shown as
per cent of taxa represented for a particular focal group. A dash
indicates that the focal group was a subset of the target focal group
and that representation, by definition, would be 100 %.

Focal group Mammals Birds Reptiles Amphibians Vertebrates COSEWIC
COSEWIC Birds COSEWIC Plants Ecoregions Vertebrates-Ecoregions

Mammals - 92 87 85 93 59 76 40 9 72

Birds 88 - 89 77 94 47 - 28 6 72

Reptiles 78 83 - 83 83 54 76 50 4 62

Amphibians 75 81 83 - 81 54 71 47 4 61

Vertebrates - - - - - 75 - 55 13 78

COSEWIC 100 99 98 100 99 - 100 100 17 78

COSEWIC Birds 74 93 78 72 86 46 - 34 3 65

COSEWIC Plants 86 91 91 94 90 82 80 - 10 69

Ecoregions 93 99 87 85 96 60 98 43 - 97

Vertebrates-Ecoregions - - - - - 78 - 61 - -

**Figure 4.** Cumulative representation of various focal groups achieved
when using Mammals, Birds, Reptiles and Amphibians focal groups as the
selection group. To standardise for the different number of taxa in
focal groups, representation is shown as per cent of taxa represented
for a particular focal group.

**Figure 5.** Cumulative representation of various focal groups achieved
when using COSEWIC,

**Figure 6.** Cumulative representation of various other focal groups
achieved when using **A**, Ecoregions, or **B**, Vertebrates-Ecoregions,
as the selection group. To standardise for the different number of
features in focal groups, representation is shown as per cent of taxa
represented for a particular focal group.

**RISK ASSESSMENT**

Results of irreplaceability and complementarity analyses were further
investigated to assess

potential risk to wildlife in priority locations in order to provide a
broad focus on parts of the

country where work is urgently needed at finer scales. Land use/land
cover within priority locations can be quantified using the AVHRR
classification as an index of anthropogenic stress. This along with
other measures of human activity can be used to produce an index of
human pressure on the environment (See maps 5 and 6 in the appendix) .

A Risk to Biodiversity Index model developed under the Geomatics
Development Program

(Moore 1997) based on the ecoregion framework of Canada was used with
equal area grid data (See Map 6 in the appendix). An overlay of existing
protected areas with the results of this analysis will reveal gaps in
the current coverage of conservation areas and thus, targets for more
detailed conservation activity such as the establishment of new
protected areas, or mitigation or restoration in areas at risk or
degraded from anthropogenic activities such as forestry, agriculture and
urban development. An overlay with ecoregions will identified important
ecoregions that are under represented in the current existing protected
areas network. Species at risk because they are under represented in
alternative solutions can also be identified, and other options
considered to meet their conservation needs.

**DISCUSSION**

*Important sites for biodiversity conservation in Canada*

Our analyses identified several general areas critical to the
maintenance of biodiversity in Canada. For reasons discussed below,
these areas are all located adjacent to the southern United States
border; (i) Vancouver Island, British Columbia; (ii) Fraser Valley,
British Columbia; (iii) Okanagan Valley, British Columbia; (iv) Niagara
Peninsula, Ontario.

Some of these important conservation areas contained endemic taxa (e.g.,
Vancouver Island marmot on Vancouver Island), most were apparently
determined by the presence of many edge-of-range taxa (e.g., for Mammals
see Banfield, 1974; Birds, Peterson, 1990; Amphibians and Reptiles,
Cook, 1984; fish, Scott and Crossman, 1973). That is, the southern
political border of Canada has resulted in many species that are
widespread in the United States being represented in only a few sites in
southern Canada. Hence, all of the highly irreplaceable sites were
contiguous with the southern United States border. Human activities
potentially deleterious to some taxa are also concentrated along this
border (H. Moore, unpublished data), possibly exacerbating the rarity of
some taxa (See map 5 in appendix).

*Implications for conservation management in Canada*

We emphasise that our results do not indicate absolute priority
locations for conservation activities, but rather identify locations
deserving of further investigation at smaller scales appropriate to
conservation activity. However, Erasmus et al. (1999) illustrate how
prioritising conservation areas at smaller spatial scales leads to
inefficiency, and that maximum efficiency is achieved by using
largest-scale analysis; this is the approach we have adopted here.
Hence, the question now becomes, given these apparently important sites,
what should be done about them?

One answer is to identify potential threats to biodiversity in these
sites. The appropriate analyses would require changes in scale, focusing
on discrete areas at which quantifiable threats to individual taxa, or
groups of taxa, might occur. Although such analyses are beyond the scope
of this study, similar analyses could be conducted at finer scales
within these sites. This would likely show that sites of high
irreplaceability are themselves composed of sites of variable
irreplaceability (i.e., it highlights the spatial heterogeneity of the
larger sites). It would then be possible to measure and map priorities
in terms of both irreplaceability and vulnerability, or risk of habitat
loss. Such sites are most in danger of loss or degradation and will have
the biggest negative impact on regional or national conservation goals
if they are lost or degraded (Pressey, 1997). We note that finer-scale
analyses would require data collected at a more appropriate scale than
that used here. While this is available for some species (e.g., most
COSEWICs), it is unavailable for many of the common species. However,
given the relatively small number of highly irreplaceable sites,
collecting such data would be a feasible project.

Since populations at the edge of a specie's range tend to have lower
densities compared to centre of the range (Lawton, 1993), and contract
(or expand) with changes in biotic and abiotic conditions, many of these
edge-of-range species in Canada are presently classified as endangered,
threatened or vulnerable. However, on a continental scale most of these
species would not receive such a classification. Although these
edge-of-range species have conservation value (Hunter and Hutchinson,
1994), most ecologists would agree that conservation budget would be
better directed towards preserving truly endangered taxa. However, we
recognise that most conservation decision-making occurs within
geopolitical frameworks (Erasmus et al., 1999), and that edge-of-range
species will likley continue to be a high priority for conservation in
Canada. However, a further possibility is to exclude locally-rare but
globally-common taxa and repeat the analyses presented here and then
compare results.

*Surrogacy of focal groups*

Because comprehensive surveys of biodiversity are prohibitively
time-consuming and expensive (Lawton et al., 1998), a critical question
in conservation planning is how well do sites selected on the basis of
more easily surveyed taxa, such as Birds and mammals, reflect the
distributions of other species? Given the rapid rate of habitat
modification or loss in many parts of the world, the answer to this
question has immediate application for locating protected areas
(Lombard, 1995; Faith and Walker, 1996; Howard et al., 1998; Reid, 1998;
Van Jaarsveld et al., 1998).

In Britain, species rich-areas (or 'hotspots') mapped at the 10 km2
scale generally do not coincide for different taxa, and many rare
species do not occur in the most species-rich sites (Prendergast et al.,
1993; see also Williams et al., 1996). A similar finding was reported
for the distributions of endangered species in the United States (Dobson
et al., 1997). However, the application of complementarity-based
reserve-selection procedures (Pressey et al., 1993) has shown that
despite low spatial congruence in species richness between taxa, sets of
priority areas selected using data on only one focal group can
collectively also represent important sites for other taxa (Howard et
al., 1998). Such a result is possible because the efficiency of a
network of protected areas depends upon not only species richness, but
also on how well they complement each other biologically. Furthermore,
site-selection algorithms based on rarity rather than species richness
consistently identify a lower number of sites required to achieve
representation of all species (Williams et al., 1996; Csuti et al.,
1997), suggesting that overlap in the distribution of rare species
between taxa may be an important determinant of surrogacy.

Our results indicate that the same sites tended to be identified as
highly irreplaceable when independently assessed for Mammals, Birds,
Reptiles, Amphibians, and COSEWICs. In other words, the sites most
important to each of these focal groups were identified independently.
This result arose from a combination of overlap in the distributions of
rare species (i.e., those of restricted distribution, both common and
COSEWIC) and the properties of the predictor, summed irreplaceability,
upon which our reserve selection procedure was based. Since the summed
irreplaceability of a site is determined largely by the number of rare
species within that site compared to other sites (S. Ferrier, R.L.
Pressey and T.W. Barret, unpublished manuscript), the overlap in the
distribution of edge-of-range species along the southern United States
border between the focal groups (see above) meant that the same sites
typically high summed irreplaceabilities for each group.

Hence, the four groups of taxa most likely to be used as surrogates in
conservation planning provided similar representations of other focal
groups. A practical implication of this finding is that conservation
strategies based on these groups could also represent have considerable
benefits for other taxa. However, we wish to emphasise that such an
outcome would depend on the actual sites selected.

There is also no guarantee that area-based targets of ecosystems will
protect all species. A key result of our analyses is that although the
minimum-set solution to achieve 12 % of the area of ecoregions required
188 sites, a significant number of COSEWICs were not represented within
these sites. This result emphasises that it is erroneous to assume that
protecting very large areas of land will protect all biodiversity. To
achieve the best representation of biodiversity, all available
information on species distributions needs to be incorporated into
decision-making.

*Future work*

This study has developed and applied methodology for analysing the
distributions of biotic and abiotic data in Canada. Our analyses were
restricted to common vertebrates and COSEWICs by the availability of
suitable range data. In the near future similar range maps are expected
for vascular plants and Lepidoptera. Also more specific bird information
will come from the recently digitized Breeding Bird Survey Route data
and the Breeding Bird Atlas data which make up the National Breeding
Bird Database. When these data become available, we suggest that our
analyses be repeated. While the priority sites identified in this study
will not change, additional important areas may also be identified.

The framework developed in this study enables a comprehensive analysis
of factors affecting the distribution of COSEWIC species (sensu Dobson
et al., 1997) to be conducted. Such a study would use statistical and
GIS methods to determine the relative impact of potentially deleterious
human activities (or correlates thereof) on the distribution of these
species as refinements to the Risk to Biodiversity model.

**BENEFITS**

-   Identification of priority locations for achieving national
    conservation goals in Canada. This project provides results for
    determining ecosystem representativeness and for identifying
    components of regional biodiversity that are poorly represented
    within existing conservation strategies.

-   Extension of conservation planning beyond rescuing rare, threatened
    or endangered species and restoring or rehabilitating ecosystems.
    Extensive effort and sums have been spent on a small number of
    species and ecosystems. While there are strong conservation
    arguments for preserving these species, the effort expended can
    easily become out of proportion to the contribution that these
    species make to genetic diversity, and therefore to the fitness of
    the biota to adapt to environmental change. In a time when resources
    for environmental management are decreasing, managing for species
    before they become threatened or endangered in addition to
    prioritising effort so that resources are allocated in proportion to
    risk and value can optimise conservation effectiveness (Pressey et
    al., 1993; Pulliam & Babbitt, 1997).

-   Improved knowledge and understanding of the distribution and
    co-occurrence of biodiversity (e.g. birds vs. mammals vs. endangered
    species) which can help to maximise protection of species at least
    cost and inconvenience to the public, provide a sounder scientific
    basis for ecosystem-based conservation planning, and provide a
    proactive mechanism for preventing future endangerment of more
    species (Dobson et al., 1997; Pulliam & Babbitt, 1997).

-   Production of a novel equal-area sampling framework for Canada which
    is generalizable to both larger and smaller spatial scales. The
    framework can help decentralise resource management decision making
    to the community level, while maintaining the regional and national
    perspective necessary for integrated planning to ensure sustainable
    resource use.

-   Multi-national, interagency co-operation in data sharing, knowledge
    integration, spatial analysis and technology transfer. This project
    has promoted collaboration among multiple disciplines, agencies and
    jurisdictions in Canada, the USA and Australia. Technically, it has
    enhanced analysis capability within Canada through installation and
    use of non-commercial software developed and tested in Australia.

-   Deployment of the equal-area sampling framework and C-Plan provides
    more quantitative and objective inputs to policy, planning and
    management at national, regional and ultimately international
    scales. For example, it enhances our knowledge regarding the
    importance of different sites in contributing to regional
    biodiversity of wildlife and other species at risk. For
    jurisdictions for which there are vegetation maps, similar analyses
    could be conducted to determine how conservation priorities based on
    habitat coverage compare to animal or plant species priorities.

    **DELIVERABLES**

    This technical report and digital outputs have been produced that
    can be used by Geomatics Canada and Canadian Wildlife Service to
    communicate in a format that is both useful as a reference to
    researchers and accessible to policy makers and managers. Products
    include:

-   a digital hexagon sampling grid for Canada

-   maps of priority sites for biodiversity conservation in Canada

-   graphs of cumulative number of sites and cumulative number of
    species included in complementarity analyses

-   graphs of cumulative number of other species groups included in
    cumulative number of sites selected for a given species group,

-   documentation of data sources, methods, results, discussion, and
    significant limitations and conclusions.

**MARKETING PLAN**

The scientific nature of processes and analytical results produced
through this work is of interest to the wildlife conservation
disciplines and the geomatics discipline. Here one of the main marketing
tools to be used to reach this group is scientific publications, both
national and international, such as this technical report.

Also, results of this work as well as the new equal-area sample grid
were provided to government web sites such as the Environment Canada
Green Lane and the Natural Resources Canada CEONet.

The data and new grid have also been added to the EcoMAP database and
GIS system and is being marketed as an integral part of the system.

**Intellectual Property**

Under the contract to GeoInsight Corporation for this project, the
ownership of the intellectual property has been defined as:

1\. The intellectual property rights of any raw data supplied to the
project by contributing agencies will remain with those agencies unless
otherwise agreed upon.

2\. The intellectual property rights of value-added data developed by
the contractor such as the new comprehensive ecosystem framework or
integrated data sets will belong to the contractor.

3\. The intellectual property of the final summarized EcoMAP products
will remain with the contractor. However, each contributing agency will
be given access to copies for their own internal use.

4\. The intellectual property rights of all products developed for the
Internet will belong to any agency wishing to display it on the
Internet.

**ACKNOWLEDGEMENT**

We thank Matthew Watts for programming C-Plan.

**REFERENCES**

Arrow, K., B. Bolin, et al. 1995. Economic Growth, Carrying Capacity,
and the Environment.

*Science* **268**: 520 521.

Banfield, A.W.F. 1977. The Mammals of Canada. University of Toronto
Press, Toronto.

BCO, 1995. Canadian Biodiversity Strategy: Canada's Response to the
Convention on

> Biological Diversity. Biodiversity Convention Office, Environment
> Canada, Hull, Quebec.

Camm, J.D.; S. Polasky; A. Solow; B. Csuti. 1996. A note on optimal
algorithms for reserve site

selection. *Biological Conservation* **62**: 115-125.

CFS. 1997. Biodiversity in the Forest: Implementing the Canadian
Biodiversity Strategy. Science

Branch, Canadian forest Service, Natural Resources Canada, Ottawa.

Church, R.L.; D.M. Stoms; F.W. Davis; 1996. Reserve selection as a
maximal covering location

problem*. Biological Conservation* **76**: 105-112.

Conroy, M. J. and B. R. Noon, 1996. Mapping of species richness for
conservation of biological

diversity: conceptual and methodological issues. *Ecological
Applications* **6**: 763-773.

Cook, F.R. 1984. Introduction to Canadian Reptiles and Amphibians.
National Museum of Natural Sciences, Ottawa.

Commission for Environmental Cooperation. 1997. Ecological regions of
North America:

> toward a common perspective. Commission for Environmental Cooperation,
> Montréal. 71pp.

Csuti, B.; S. Polasky; P.H. Williams; R,L. Pressey; J.D. Camm; M.
Kershaw; A.R. Kiester; B.

> Downs; R. Hamilton; M. Huso; K. Sahr. 1997. A comparison of reserve
> selection algorithms using data on terrestrial vertebrates in Oregon.
> *Biological Conservation* **80**: 83-97.

Dobson, A.P.; J.P. Rodriguez; W.M. Roberts; D.S. Wilcove. 1997.
Geographic distribution of

endangered species in the United States. *Science* **275**: 550-553.

Dunn, E. H., 1997. Setting priorities for conservation, research and
monitoring of Canada's

> landbirds. Technical Report No. 293, Canadian Wildlife Service,
> Headquarters, Environment Canada, Hull, Quebec.

Ecological Stratification Working Group. 1996. A national ecological
framework for Canada.

> Agriculture and Agri-Food Canada, Research Branch, Centre for Land and
> Biological Resources Research and Environment Canada, State of the
> Environment Directorate, Ecozone Analysis Branch, Ottawa/Hull.

Environment Canada. 1994. Biodiversity in Canada: A Science Assessment
for Environment

Canada. Ottawa, ON. 245 pp.

Erasmus, B.F.N.; S. Freitag; K.J. Gaston; B.H. Erasmus; A.S. Van
Jaarsveld. 1999. Scale and conservation planning in the real world.
*Proceedings of the Royal Society of London B* **266**: 315-319.

Faith, D.P.; P.A. Walker. 1996. How do indicator groups provide
information about the relative biodiversity of different sets of areas?
On hotspots, complementarity and pattern-based approaches. *Biodiversity
Letters* **3**: 18-25.

Ferrier, S.; G. Watson. 1997. An evaluation of the effectiveness of
environmental surrogates and

> modelling techniques in predicting the distribution of biological
> diversity. Biodiversity Group, Environment Australia. 193pp.

Finkel, E. 1998. Software helps Australia manage forest debate.
*Science* **281**: 1789-1791.

Flather, C.H., K.R. Wilson, D.J. Dean and W.C. McComb, 1997. Identifying
gaps in

> conservation networks: Of indicators and uncertainty in
> geographic-based analyses. *Ecological* *Applications* **7**: 531-542.

Flather, C.H.; M.S. Knowles; I.A. Kendall. 1998. Threatened and
endangered species

geography. *BioScience* **48**: 365-376.

Gaston, K.J. 1994. Rarity. Chapman and Hall, London.

Heywood, V. H. and R. T. Watson, 1995. Global biodiversity assessment.
Cambridge University

Press, New York.

Howard, P.C.; P. Viskanic; T.R.B. Davenport; F.W. Kigenyi; M. Baltzer;
C.J. Dickinson; J.S.

> Lwanga; R.A. Matthews; A. Balmford. 1998. Complementarity and the use
> of indicator groups for reserve selction in Uganda. *Nature* **394**:
> 472-475.

Jelinski, D.E. 1997. On genes and geography: a landscape perspective on
genetic variation in

natural plant populations. *Landscape & Urban Planning* **39**: 11-23.

Kershaw, M.; P.H. Williams; G.C. Mace. 1994. Conservation of
Afrotropical antelopes:

consequences and efficiency of using different site selection methods
and diversity

> criteria. *Biodiversity and Conservation* **3**: 354-372.

Kiester, A. R., J. M. Scott, B. Csuti, R. Noss, B. Butterfield, K. Sahr
and D. White, 1996.

Conservation prioritization using GAP data. *Conservation Biology*
**10**: 1332-1342.

Lawton, J.H. 1993. Range, population abundance and conservation*. Trends
in Ecology and Evolution* **8**: 409-413.

Lawton, J.H. 1995. Population Dynamic Principles. In Lawton, J.H.; R.M.
May (Eds.). Extinction Rates. Oxford University Press, Oxford.

Lawton, J.H.; D.E. Bignell; B. Bolton; G.F. Bloemers; P. Eggleton; P.M.
Hammond; M. Hodda;

> R.D. Holt; T.B. Larsen; N.A. Mawdsley; N.E. Stork; D.S. Srivastava;
> A.D. Watt. 1998. Biodiversity inventories, indicator taxa and effects
> of habitat modification in tropical forest. *Nature* **391**: 72-76.

Lombard, A.T. 1995. The problems with multi-species conservation: do
hotspots, ideal reserves

and existing reserves coincide? *South African Journal of Zoology*
**30**: 145-163.

Lubchenco, J., 1995. The role of science in formulating a biodiversity
strategy. BioScience,

Supplement: 7-9.

Margules, C.R.; A.O. Nicholls; R.L. Pressey. 1988. Selecting networks of
reserves to maximize

biological diversity. *Biological Conservation* **43**: 63-76.

McNeely, J. A., K. R. Miller, W. V. Reid, R. A. Mittermeier & T. B.
Werner, 1990. Conserving

the World's Biological Diversity. International Union for the
Conservation of Nature,

> Gland, Switzerland; the World Resources Institute, Conservation
> International, World Wide Fund for Nature, and the World Bank,
> Washington, D.C.

Moore, H.D. et al, 1997. Risk to Biodiversity

Moore, H.D. et al, 1998. EcoMAP, Ecological Mapping Applications and
Protocol,

Norušis, M.J. 1998. SPSS® 8.0 Guide to Data Analysis. Prentice Hall, New
Jersey.

Peterson, R.T. 1990. A Field Guide to Western Birds. Third edition.
Houghton Mifflin, Boston.

Perrings, C., K. G. Maler, et al. (eds.). 1995. Biodiversity Loss:
Economic and Social Issues.

Cambridge University Press, Cambridge, UK.

Prendergast, J.R.; R.M. Quinn; J.H. Lawton; B.C. Eversham; D.W. Gibbons.
1993. Rare

> species, the coincidence of diversity hotspots and conservation
> strategies. *Nature* **365**: 335-7.

Pratt, J. R. and J. Cairns Jr., 1992. Ecological risks associated with
the extinction of species.

Pages 93-117 in J. Cairns, Jr., B. R. Niederlehner & D. R. Orvos (ed.).
Predicting

> Ecosystem Risk. Princeton Scientific Publishing Co., Princeton, New
> Jersey.

Pressey, R. L. 1997. Priority conservation areas: towards an operational
difinition for regional

assessments. Pages 337-357 in J.J. Pigram and R.C. Sundell (eds.).
National Parks and

> Protected Areas: Selectioin, Delimitation and Management. Centre for
> Water Policy Research, University of New England, Armidale, Australia

Pressey, R. L. 1998. Algorithms, politics and timber: an example of the
role of science in a

public, political negotiation process over new conservation areas in
production forests.

> Pages 73-87 in R. Wills and R. J. Hobbs (ed.). Ecology for Everyone:
> Communicating Ecology to Scientists, the Public and the Politicians.
> Surrey Beatty & Sons, Sydney, Australia.

Pressey, R.L; K.H. Taffs. In review. Priority conservation areas: a
definition for the real world

applied to western New South Wales. *Biological Conservation*.

Pressey, R.L.; I.R. Johnson; P.D. Wilson. 1994. Shades of
irreplaceability: towards a measure of

the contribution of sites to a reservation goal. *Biodiversity and
Conservation* **3**: 242-262.

Pressey, R.L; H.P. Possingham; J.R. Day. 1997. Effectiveness of
alternative heuristic algorithms

> for identifying minimum requirements for conservation reserves.
> *Biological Conservation* **80**: 207-219.

Pressey, R.L; H.P. Possingham; C.R. Margules. 1996. Optimality in
reserve selection

algorithms: When does it matter and how much? *Biological Conservation*
**76**: 259-267.

Pressey, R. L., C. J. Humphries, C. R. Margules, R. I. Vane-Wright and
P. H. Williams, 1993.

Beyond opportunism: key principles for systematic reserve selection.
*Trends in Ecology*

*and Evolution* **8**: 124-128.

Pressey, R. L., S. Ferrier, C.D. Hutchinson, D.P. Sivertsen and G.
Manion, 1995. Planning for

negotiation: using an interactive geographic information system to
explore alternative

protected area networks. Pages 23-33 in D. A. Saunders, J. L. Craig & E
.M. Mattiske

> (ed.). Nature Conservation 4: The Role of Networks, Surrey Beatty &
> Sons, Sydney, Australia.

Pulliam, H. R. and B. Babbitt, 1997. Science and the protection of
endangered species. *Science*

**275**: 499-500.

Reid, W.V. 1998. Biodiversity hotspots. *Trends in Ecology and
Evolution* **13**: 275-280.

Ryti, R.T. 1992. Effect of the focal taxon on the selection of nature
reserves. *Ecological Applications* **2**: 404-410.

Scott, W. B.; E. J. Crossman. 1973. Freshwater fishes of Canada.
*Fisheries Research Board of Canada Bulletin* **184**: 1-966.

Stoms, D., 1994. Scale dependence of species richness maps.
*Professional Geographer* **46**: 346-

358\.

Turner, A.M.; C.D.A. Rubec; E.B. Wiken. 1992. Canadian ecosystems: a
systems approach to

their conservation. *Developments in Landscape Management and Urban
Planning* **7**:

> 117-127.

Van Jaarsveld, A.S.; S. Freitag; S.L. Chown; C. Muller; S. Koch; H.
Hull; C. Bellamy; M. Krüger; S. Endrödy-Younga; M.W. Mansell; C.H.
Scholtz. 1998. Biodiversity assessment and conservation strategies.
*Science* **279**: 2106-2108.

White, D.; A.J. Kimerling; W.S. Overton. 1992. Cartographic and
geometric components of a

> global sampling design for environmental monitoring*Cartography and
> Geographic Information Systems* **19**: 5-22.

White, D, E.M. Preston, K.E. Freemark and A.R. Kiester. 1998. A
hierarchical framework for

conserving biodiversity. Chapter in Landscape Ecological Analysis:
Issues and

> Applications. J.M. Klopatek and R.H. Gardner (eds.). Springer-Verlag,
> NY. In press

Williams, P.; D. Gibbons; C. Margules; A. Rebelo; C. Humphries; R.
Pressey. 1996. A

comparison of richness hotspots, rarity hotspots, and complementary
areas for

conserving diversity of British Birds. *Conservation Biology* **10**:
155-174.

Williams, P.H.; K.J. Gaston, 1994. Measuring more of biodiversity: Can
higher-taxon

richness predict wholesale species richness? *Biological Conservation*
**67**: 211-217.

Williams, P. H., G. T. Prance, C. J. Humphries and K. S. Edwards, 1996.
Promise and problems

in applying quantitative complementary areas for representing the
diversity of some

Neotropical plants (families Dichapetalaceae, Lecythidaceae,
Caryocaraceae,

> Chrysobalanaceaeand Proteaceae). *Biological Journal of the Linnaeus
> Society* **58**: 125-157.

Williams, P. H., K. J. Gaston and C. J. Humphries, 1997. Mapping
biodiversity value worldwide:

combining higher-taxon richness from different groups. *Proceedings of
the Royal Society*

> *of London* *B* **264**: 141-148.

Zar, J.H. 1996. Biostatistical Analysis. Third edition. Prentice-Hall,
New Jersey.

**Appendix 1. Summary of taxa used in analyses (number of taxa).**

**A. Reptiles (46)**

**(i) Common Reptiles (33)**

Atlantic Ridley *Lepidochelys kempi*

northern brown snake *Storeria dekayi dekayi*

Butler\'s garter snake *Thamnophis butleri*

common garter snake *Thamnophis sirtalis*

common snapping turtle *Chelydra serpentina*

eastern ribbon snake *Thamnophis sauritus*

eastern box turtle *Terrapene caolina*

fox snake *Elaphe vulpina*

gopher snake *Pituophis melanoleucus*

green turtle *Chelonia mydas*

map turtle *Graptemys geographica*

milk snake *Lampropeltis triangulum*

night snake *Hypsiglena torquata*

northern alligator lizard *Gerrhonotus coeruleus*

northern water snake *Nerodia sipedon*

northwestern garter snake *Thamnophis elegans*

painted turtle *Chrysemys picta*

plains garter snake *Thamnophis radix*

queen snake *Regina septemvitta*

racer *Coluber constrictor*

redbelly snake *Storeria occipitomaculata*

ringneck snake *Diadophis punctatus*

rubber boa snake *Charina bottae*

sharptail snake *Contia tenuis*

short-horned lizard *Phrynosoma douglassi*

smooth green snake *Opheodrys vernalis*

stinkpot *Sternotherus odoratus*

timber rattlesnake *Crotalus horridus*

western skink *Eumeces skiltonianus*

western rattlesnake *Crotalus viridis*

western garter snake *Thamnophis elegans*

western pond turtle *Clemmys marmorata*

western hognose snake *Heterodon nasicus*

**(ii) Endangered Reptiles (2)**

blue racer *Coluber constrictor foxi*

Lake Erie water snake *Nerodia sipedon insularum*

**(iii) Threatened Reptiles (4)**

Eastern massasauga rattlesnake *Sistrurus catenatus*

Blanding's turtle (Nova Scotia) *Emydoidea blandingi*

Spiny softshell turtle *Trionyx spiniferus*

black rat snake *Elaphe obsoleta obsoleta*

**(iv) Vulnerable Reptiles (7)**

eastern hognose snake *Heterodon platyrhinos*

eastern short-horned lizard *Phrynosoma douglassi*

eastern yellow-bellied racer *Coluber constrictor flaviventris*

northern prairie skink *Eumeces septentrionalis*

spotted turtle *Clemmys guttata*

wood turtle *Clemmys insculpta*

five-lined skink *Eumeces fasciatus*

**B. Amphibians (46)**

**(i) Common Amphibians (38)**

American toad *Bufo americanus*

blue spotted salamander *Ambystoma laterale*

bullfrog *Rana catesbeiana*

clouded salamander *Aneides ferreus*

diploid grey treefrog *Hyla chrysoscelis*

northern dusky salamander *Desmognathus fuscus*

eastern newt *Notophthalmus viridescens*

eschscholtz\'s salamander *Ensatina eschscholtzii*

eastern redback salamander *Plethodon cinereus*

four-toed salamander *Hemidactylium scutatum*

green frog *Rana clamitans*

great plains toad *Bufo cognatus*

jefferson salamander *Ambystoma jeffersonianum*

long-toe salamander *Ambystoma macrodactylum*

mink frog *Rana septentrionalis*

mudpuppy *Necturus maculosus*

northern leopard frog *Rana pipiens*

northern cricket frog *Acris crepitans*

northwestern salamander *Ambystoma gracile*

pacific tree frog *Hyla regilla*

pickerel frog *Rana palustris*

plains spadefoot toad *Spea bombifrons*

red-legged frog *Rana aurora*

roughskin newt *Taricha granulosa*

spotted frog *Rana pretiosa*

spring peeper *Pseudacris crucifer*

spring salamander *Gyrinophilus porphyriticus*

striped chorus frog *Pseudacris maculata*

tailed frog *Ascaphus truei*

tetraploid grey treefrog *Hyla versicolor*

tiger salamander *Ambystoma tigrinum*

northern two-lined salamander *Eurycea bislineata*

western toad *Bufo boreas*

wood frog *Rana sylvatica*

Woodhouse\'s toad *Bufo woodhousei*

western redback salamander *Plethodon vehiculum*

yellow-spotted salamander *Ambystoma aculatum*

**(ii) Endangered Amphibians (2)**

Blanchard\'s cricket frog *Acris crepitans blanchardi*

northern leopard frog (B.C. pop.) *Rana pipiens*

**(iii) Threatened Amphibians (0)**

**(iv) Vulnerable Amphibians (7)**

Fowler\'s Toad *Bufo fowleri*

Pacific giant salamander *Dicamptodon tenebrosus*

Smallmouth salamander *Ambystoma texanum*

Northern leopard frog *Rana pipiens*

coeurd\'Alene salamander *Plethodon idahoensis*

mountain dusky salamander *Desmognathus orcophaeus*

great basin spadefoot toad *Spea intermontanus*

**C. Mammals (152)**

**(i) Common Mammals (123)**

Virginia opossum *Didelphis virginiana*

masked shrew *Sorex cinereus*

dusky shrew *Sorex obscurus*

vagrant shrew *Sorex vagrans*

American water shrew *Sorex palustris*

Bendire\'s shrew *Sorex bindirii*

smokey shrew *Sorex fumeus*

Arctic shrew *Sorex arcticus*

Trowbridge\'s shrew *Sorex trowbridgii*

pigmy shrew *Microsorex hoyi*

short-tailed shrew *Blarina brevicauda*

least shrew *Cryptotis parva*

American shrew-mole *Neürotrichus gibbsii*

Pacific coast mole *Scapanus orarius*

hairy-tailed mole *Parascalops breweri*

star-nosed mole *Condylura cristata*

little brown bat *Myotis lucifugus*

Yuma bat *Myotis yumanensis*

Keen\'s bat *Myotis keenii*

long-eared bat *Myotis evotis*

long-legged bat *Myotis volans*

California bat *Myotis californicus*

small-footed bat *Myotis leibii*

silver-haired bat *Lasionycteris noctivagans*

Townsend\'s big-eared bat *Plecotus townsendii*

eastern pipistrelle *Pipistrellus subflavus*

big brown bat *Eptesicus fuscus*

evening bat *Nycticeius humeralis*

red bat *Lasiurus borealis*

hoary bat *Lasiurus cinerus*

big free-tailed bat *Tadarida macrotis*

American pika *Ochotona princeps*

eastern cottontail *Sylvilagus floridanus*

snowshoe hare *Lepus americanus*

Arctic hare *Lepus arcticus*

white-tailed jack rabbit *Lepus townsendii*

mountain beaver *Aplodontia rufa*

eastern chipmunk *Tamias striatus*

least chipmunk *Eutamias minimus*

yellow pine chipmunk *Eutamias amoenus*

Townsend\'s chipmunk *Entamias townsendii*

red-tailed chipmunk *Eutamias ruficaudus*

woodchuck *Marmota monax*

yellow-bellied marmot *Marmota flaviventris*

hoary marmots *Marmota caligata*

Richardson\'s ground squirrel *Spermophilus richardsonii*

Columbian ground squirrel *Spermophilus columbianus*

Arctic ground squirrel *Spermophilus parryii*

thirteen-lined ground squirrel *Spermophilus tridecemlineatus*

Franklin\'s ground squirrel *Spermophilus franklinii*

golden-mantled ground squirrel *Spermophilus lateralis*

grey or black squirrel *Sciurus carolinensis*

fox squirrel *Sciurus niger*

American red squirrel *Tamiasciurus hudsonicus*

Douglas\'s squirrel *Tamiasciurus douglasii*

northern flying squirrel *Glaucomys sabrinus*

northern pocket gopher *Thomomys talpoides*

olive-backed pocket mouse *Perognathus fasciatus*

great basin pocket mouse *Perognathus parvus*

American beaver *Castor canadensis*

deer mouse *Peromyscus maniculatus*

Sitka mouse *Peromyscus sitkensis*

white-footed mouse *Peromyscus leucopus*

Cascade deer mouse *Peromyscus oreas*

northern grasshopper mouse *Onychomys leucogaster*

bushy-tailed wood rat *Neotoma cinerea*

red-backed vole *Clethrionomys rutilus*

western red-backed vole *Clethrionomys occidentalis*

Gapper\'s red-backed vole *Clethrionomys gapperi*

brown lemming *Lemmus lemmus*

southern bog lemming *Synaptomys cooperi*

northern bog lemming *Synaptomys borealis*

heather vole *Phenacomys intermedius*

collared lemming *Dicrostonyx torquatus*

Ungava lemming *Dicrostonyx hudsonius*

Muskrat *Ondrata zibethicus*

sagebush vole *Lagurus curtatus*

Richardson\'s water vole *Arvicola richardsoni*

prairie vole *Microtus ochrogaster*

singing vole *Microtus miurus*

meadow vole *Microtus pennsylvanicus*

Monane vole *Microtus montanus*

Townsend\'s vole *Microtus townsendii*

tundra vole *Microtus oeconomus*

long-tailed vole *Microtus longicaudus*

rock vole *Microtus chrotorrhinus*

chestnut-cheeked vole *Microtus xanthognathus*

creeping vole *Microtus oregoni*

Pacific jumping mouse *Zapus trinotatus*

western jumping vole mouse *Zapus princeps*

meadow jumping vole mouse *Zapus hudsonius*

woodland jumping vole mouse *Napaeozapus insignis*

American porcupine *Erethizon dorsatum*

Coyote *Canis latrans*

Wolf *Canis lupus*

Arctic fox *Alopex lagopus*

red fox *Vulpes vulpes*

American black bear *Ursus americanus*

Raccoon *Procyon lotor*

American marten *Martes americana*

Fisher *Martes pennanti*

Ermine *Mustela erminea*

long-tailed weasel *Mustela frenata*

least weasel *Mustela nivalis*

American mink *Mustela vison*

Wolverine *Gulo gulo*

American badger *Taxidea taxus*

western spotted skunk *Spilogale gracilis*

Striped skunk *Mephitis mephitis*

river otter *Lontra canadensis*

cougar *Felis concolor*

lynx *Lynx lynx*

bobcat *Lynx rufus*

caribou *Rangifer tarandus*

mule deer *Odocoileus hemionus*

white-tailed deer *Odocoileus virginianus*

moose *Alces alces*

wapiti *Cervus elaphus*

pronghorn *Antilocapra americana*

mountain goat *Oreamnos americanus*

muskox *Ovibos moschatus*

bighorn sheep *Ovis canadensis*

Dall\'s sheep *Ovis dalli*

**(ii) Endangered Mammals (5)**

Peary Banks Island *Rangifer tarandus pearyi*

Peary High Arctic *Rangifer tarandus pearyi*

Vancouver Island marmot *Marmota vancouverensis*

Marten (Newfoundland) *Martes americana*

Wolverine (eastern population) *Gulo gulo*

**(iii) Threatened Mammals (5)**

Wood bison *Bison bison athabascae*

Caribou (Low Arctic Peary) *Rangifer tarandus pearyi*

Woodland caribou *Rangifer tarandus caribou*

Townsend's mole *Scapanus townsendii*

Pacific water shrew *Sorex bendirii*

**(iv) Vulnerable Mammals (19)**

Black Tailed Prairie Dog *Cynomys ludovicianus*

Eastern Mole *Scalopus aquaticus*

Fringed Bat *Myotis thysanodes*

Gaspé Shrew *Sorex gaspensis*

Grey fox *Urocyon cinereoargenteus*

Grizzly bear *Ursus arctos*

Keen's Long-eared bat *Myotis keenii*

Nuttall's cottontail *Sylvilagus nuttallii*

Ord's Kangaroo rat *Dipodomys ordii*

Pallid bat *Antrozous pallidus*

Plains pocket gopher *Geomys bursarius*

Polar bear *Ursus maritimus*

Southern flying squirrel *Glaucomys volans*

Spotted bat *Euderma maculata*

Western harvest mouse *Reithrodontomys megalotis*

Woodland caribou *Rangifer tarandus caribou*

Queen Charlotte's ermine *Mustela erminea haidarum*

New Foundland wolverine *Gulo gulo*

Woodland vole *Microtus pinetorum*

**D. Birds (383)**

**(i) Common Birds (342)**

American Black Duck *Anas rubripes*

Green-winged Teal *Anas crecca*

Alder Flycatcher *Empidonax alnorum*

American Avocet *Recurvirostra americana*

American Bittern *Botaurus lentiginosus*

American Coot *Fulica americana*

American Crow *Corvus brachyrhynchos*

American Dipper *Cinclus mexicanus*

American Goldfinch *Carduelis tristis*

American Kestrel *Falco sparverius*

American Redstart *Setophaga ruticilla*

American Robin *Turdus migratorius*

American Wigeon *Anas americana*

American Woodcock *Scolopax minor*

Anna\'s Hummingbird *Calypte anna*

Arctic Tern *Sterna paradisea*

Atlantic Brant *Branta bernicla*

American Tree Sparrow *Spizella arborea*

American White Pelican *Pelecanus erythrorhynchos*

Bald Eagle *Haliaeetus leucocephalus*

Barrow\'s Goldeneye *Becephala islandica*

Baird\'s Sparrow *Ammodramus bairdii*

Bank Swallow *Riparia riparia*

Barn Swallow *Hirundo rustica*

Baird\'s Sandpiper *Calidris bairdii*

Black-and-White Warbler *Mniotilta varia*

Black-billed Cuckoo *Coccyzus erythopthalmus*

Black-billed Magpie *Pica pica*

Black-bellied Plover *Pluvialis squatarola*

Buff-breasted Sandpiper *Tryngites subruficollis*

Bay-breasted Warbler *Dendoica castanea*

Black-backed Woodpecker *Picoides arcticus*

Black-capped Chickadee *Parus atricapillus*

Black-crowned Night Heron *Nycticorax nycticorax*

Barred Owl *Strix varia*

Belted Kingfisher *Ceryle alcyon*

Bewick\'s Wren *Thromanes bewickii*

Blue-gray Gnatcatcher *Polioptila caerulea*

Brown-headed Cowbird *Molothrus ater*

Black-headed Grosbeak *Pheuticus melanocephalus*

Blackburnian Warbler *Dendroica fusca*

Blue Jay *Cyanocitta cristata*

Blackpoll Warbler *Dendroica striata*

Black Scoter *Melanitta nigra*

Black Swift *Cypseloides niger*

Black Tern *Chlidonias niger*

Blue Grouse *Dendragapus obscurus*

Bobolink *Dolichonyx oryzivorus*

Boreal Chickadee *Parus hudsonicus*

Bonaparte\'s Gull *Larus philadelphia*

Boreal Owl *Aegolius funereus*

Bohemian Waxwing *Bombycilla garrulus*

Brandt\'s Cormorant *Phalacrocorax penicillatus*

Brewer\'s Blackbird *Euphagus cyanocephalus*

Brown Creeper *Certhia americana*

Brewer\'s Sparrow *Spizella breweri*

Brown Thrasher *Toxostoma rufum*

Black-throated Blue Warbler *Dendroica caerulescens*

Black-throated Green Warbler *Dendroica virens*

Band-tailed Pigeon *Columba fasciata*

Black-throated Gray Warbler *Dendroica nigrescens*

Bufflehead *Bucephala albeola*

Broad-winged Hawk *Buteo platypterus*

Blue-winged Teal *Anas discors*

Blue-winged Warbler *Vermivora pinus*

Cassin\'s Finch *Carpodacus cassinii*

Canada Goose *Branta canadensis*

California Gull *Larus californicus*

Calliope Hummingbird *Stellula calliope*

Canvasback *Aythya valisineria*

Canyon Wren *Catherpes mexicanus*

Canada Warbler *Wilsonia canadensis*

Carolina Wren *Thryothorus ludovicianus*

Chestnut-backed Chickadee *Parus rufescens*

Chestnut-collared Longspur *Calcarius ornatus*

Clay-colored Sparrow *Spizella pallida*

Cedar Waxwing *Bombycilla cedrorum*

Chipping Sparrow *Spizella passerina*

Chimney Swift *Aeronautes saxatalis*

Cinnamon Teal *Anas cyanoptera*

Clark\'s Grebe *Aechmophorus clarkii*

Clark\'s Nutcracker *Nucifraga columbiana*

Cliff Swallow *Hirundo pyrrhonota*

Cape May Warbler *Dendroica tigrina*

Common Bushtit *Psaltriparus minimus*

Common Goldeneye *Bucephala clangula*

Common Grackle *Quiscalus quiscula*

Cooper\'s Hawk *Accipiter cooperii*

Common Loon *Gavia immer*

Common Merganser *Mergus merganser*

Common Moorhen *Gallinula chloropus*

Common Nighthawk *Chordeiles minor*

Connecticut Warbler *Oporornis agilis*

Common Poorwill *Phalaenoptilus nuttalii*

Common Raven *Corvus corax*

Common Redpoll *Carduelis flammea*

Common Snipe *Gallinago gallinago*

Common Tern *Sterna hirundo*

Common Yellowthroat *Geothlypis trichas*

Common Ringed Plover *Charadrius hiaticula*

Chestnut-sided Warbler *Dendroica pensylvanica*

Chuck-will\'s-widow *Caprimulgus carolinensis*

Double-crested Cormorant *Pelecanus erythorhynchos*

Dark-eyed Junco *Junco hyemalis*

Dickcissel *Spiza americana*

Downy Woodpecker *Picoides pubescens*

Dusky Flycatcher *Empidonax oberholseri*

Dunlin *Calidris alpina*

Eastern Bluebird *Sialia sialis*

Eared Grebe *Podiceps nigricollis*

Eastern Kingbird *Tyrannus tyrannus*

Eastern Meadowlark *Sturnella magna*

Eastern Phoebe *Sayornis phoebe*

Eastern Screech Owl *Otus asio*

Eastern Wood-Pewee *Contopus sordidulus*

Evening Grosbeak *Coccothraustes vespertinus*

Field Sparrow *Spizella pusilla*

Fox Sparrow *Passerella iliaca*

Forster\'s Tern *Sterna forsteri*

Franklin\'s Gull *Larus pipixcan*

Gadwall *Anas strepera*

Great Crested Flycatcher *Myiarchus crinitus*

Golden-crowned Kinglet *Regulus satrapa*

Golden-crowned Sparrow *Zonotrichia atricapilla*

Gray-cheeked Thrush *Catharus minimus*

Great Gray Owl *Strix nebulosa*

Great Horned Owl *Bubo virginianus*

Glaucous Gull *Larus hyperboreus*

Green-backed Heron *Butorides striatus*

Golden Eagle *Aquila chrysaetos*

Gray Jay *Perisoreus canadensis*

Gray Catbird *Dumetella carolinensis*

Greater Scaup *Aythya marila*

Grasshopper Sparrow *Ammodramus savannarum*

Greater Yellowlegs *Tringa melanoleuca*

Great Blue Heron *Ardea herodias*

Greater White-fronted Goose *Anser albifrons*

Golden-winged Warbler *Vermivora chrysoptera*

Gyrfalcon *Falco rusticolus*

Hammond\'s Flycatcher *Empidonax hammondii*

Harlequin Duck *Histrionicus histrionicus*

Harris\' Sparrow *Zonotrichia querula*

Hairy Woodpecker *Picoides villosus*

Herring Gull *Larus argentatus*

Hermit Thrush *Catharus guttatus*

House Finch *Carpodacus mexicanus*

Horned Grebe *Podiceps auritus*

Horned Lark *Eremophila alpestris*

Hooded Merganser *Lophodytes cucullatus*

Hoary Redpoll *Carduelis hornemanni*

House Wren *Troglodytes troglodytes*

Hudsonian Godwit *Limosa haemastica*

Hutton\'s Vireo *Vireo huttoni*

Iceland Gull *Larus glaucoides*

Indigo Bunting *Passerina cyanea*

Killdeer *Charadrius vociferus*

Lapland Longspur *Calcarius lapponicus*

Lark Bunting *Calamospiza melanocorys*

Lark Sparrow *Chondestes grammacus*

Lazuli Bunting *Passerina amoena*

Long-billed Dowitcher *Limnodromus scolopaceus*

Le Conte\'s Sparrow *Ammodramus leconteii*

Least Flycatcher *Empidonax minimus*

American Golden-Plover *Pluvialis dominica*

Long-eared Owl *Asio otus*

Least Sandpiper *Calidris minutilla*

Lesser Scaup *Aythya affinis*

Lewis\' Woodpecker *Melanerpes lewis*

Lesser Yellowlegs *Tringa flavipes*

Lincoln\'s Sparrow *Melospiza lincolnii*

Loggerhead Shrike *Lanius ludovicianus*

Lesser Snow Goose *Chen caerulescens*

Marbled Godwit *Limosa fedoa*

Mallard *Anas platyrhynchos*

Magnolia Warbler *Dendroica magnolia*

Marsh Wren *Cistothorus palustris*

McCown\'s Longspur *Calcarius mccownii*

Mew Gull *Larus canus*

Merlin *Falco columbarius*

MacGillivray\'s Warbler *Oporornis tolmiei*

Mountain Bluebird *Sialia currucoides*

Mountain Chickadee *Parus gambeli*

Mourning Dove *Zenaida macroura*

Mourning Warbler *Oporornis philadelphia*

Nashville Warbler *Vermivora ruficapilla*

Northern Cardinal *Cardinalis cardinalis*

Northwestern Crow *Corvus caurinus*

Northern Flicker *Colaptes auratus*

Northern Goshawk *Accipiter gentilis*

Northern Harrier *Circus cyaneus*

Northern Hawk Owl *Surnia ulula*

Northern Mockingbird *Mimus polyglottos*

Northern Oriole *Icterus galbula*

Northern Parula *Parula americana*

Northern Pintail *Anas acuta*

Northern Pygmy-Owl *Glaucidium gnoma*

Northern Waterthrush *Seiurus noveboracensis*

Northern Wheatear *Oenanthe oenanthe*

Northern Rough-winged Swallow *Stelgidopteryx serripennis*

Northern Shoveler *Anas clypeata*

Northern Shrike *Lanius excubitor*

Northern Saw-whet Owl *Aegolius acadicus*

Orange-crowned Warbler *Vermivora celata*

Oldsquaw *Clangula hyemalis*

Orchard Oriole *Icterus spurius*

Olive-sided Flycatcher *Contopus borealis*

Osprey *Pandion haliaetus*

Ovenbird *Seiurus aurocapillus*

Pacific Loon *Gavia pacifica*

Pied-billed Grebe *Podilymbus podiceps*

Peregrine Falcon *Falco peregrinus*

Pectoral Sandpiper *Calidris melanotos*

Philadelphia Vireo *Vireo philadelphicus*

Pine Grosbeak *Pinicola enucleator*

Pine Siskin *Carduelis pinus*

Pine Warbler *Dendroica pinus*

Pileated Woodpecker *Dryocopus pileatus*

Palm Warbler *Dendroica palmarum*

Prairie Falcon *Falco mexicanus*

Purple Finch *Carpodacus purpureus*

Purple Martin *Progne subis*

Purple Sandpiper *Calidris maritima*

Pygmy Nuthatch *Sitta pygmaea*

Rose-breasted Grosbeak *Pheuticus ludovicianus*

Ring-billed Gull *Larus delawarensis*

Red-breasted Merganser *Mergus serrator*

Red-breasted Nuthatch *Sitta canadensis*

Red-breasted Sapsucker *Sphyrapicus ruber*

Red-bellied Woodpecker *Melanerpes carolinus*

Ruby-crowned Kinglet *Regulus calendula*

Red Crossbill *Loxia curvirostra*

Redhead *Aythya americana*

Red Knot *Calidris canutus*

Red Phalarope *Phalaropus fulicaria*

Red-eyed Vireo *Vireo olivaceus*

Rough-legged Hawk *Buteo lagopus*

Ring-necked Duck *Aythya collaris*

Red-necked Grebe *Podiceps grisegena*

Red-necked Phalarope *Phalaropus lobatus*

Red-naped Sapsucker *Sphyrapicus nuchalis*

Rock Ptarmigan *Lagopus mutus*

Rock Wren *Salpinctes obsoletus*

Rufous-sided Towhee *Pipilo erythrophthalmus*

Red-tailed Hawk *Buteo jamaicensis*

Ruby-throated Hummingbird *Archilochus colubris*

Red-throated Loon *Gavia stellata*

Rusty Blackbird *Euphagus carolinus*

Ruddy Duck *Oxyura jamaicensis*

Ruffed Grouse *Bonasa umbellus*

Rufous Hummingbird *Selasphorus rufus*

Ruddy Turnstone *Arenaria interpres*

Red-winged Blackbird *Agelaius phoeniceus*

Sandhill Crane *Grus canadensis*

Sage Grouse *Centrocercus urophasianus*

Sabine\'s Gull *Xema sabini*

Sanderling *Calidris alba*

Say\'s Phoebe *Sayornis saya*

Savannah Sparrow *Passerculus sandwichensis*

Short-billed Dowitcher *Limnodromus griseus*

Scarlet Tanager *Piranga olivacea*

Semipalmated Plover *Charadrius semipalmatus*

Semipalmated Sandpiper *Calidris pusilla*

Sedge Wren *Cistothorus platensis*

Sharp-tailed Grouse *Tympanuchus phasianellus*

Siberian Tit *Parus cinctus*

Smith\'s Longspur *Calcarius pictus*

Snow Bunting *Plectrophenax nivalis*

Snowy Owl *Nyctea scandiaca*

Sora *Porzana carolina*

Solitary Sandpiper *Tringa solitaria*

Song Sparrow *Melospiza melodia*

Solitary Vireo *Vireo solitarius*

Spruce Grouse *Dendragapus canadensis*

Sprague\'s Pipit *Anthus spragueii*

Spotted Sandpiper *Actitus macularia*

Sharp-shinned Hawk *Accipiter striatus*

Stellar\'s Jay *Cyanocitta stelleri*

Stilt Sandpiper *Calidris himantopus*

Sharp-tailed Sparrow *Ammodramus caudacutus*

Surfbird *Aphriza virgata*

Surf Scoter *Melanitta perspicillata*

Swainson\'s Hawk *Buteo swainsoni*

Swamp Sparrow *Melospiza georgiana*

Swainson\'s Thrush *Catharus ustulatus*

Tennessee Warbler *Vermivora peregrina*

Townsend\'s Solitaire *Myadestes townsendi*

Townsend\'s Warbler *Dendroica townsendi*

Tree Swallow *Tachycineta bicolor*

Trumpeter Swan *Cygnus buccinator*

Three-toed Woodpecker *Picoides tridactylus*

Tufted Titmouse *Parus bicolor*

Turkey Vulture *Cathartes aura*

Upland Sandpiper *Bartramia longicauda*

Vaux\'s Swift *Chaetura vauxi*

Varied Thrush *Ixoreus naevius*

Veery *Catharus fuscescens*

Vesper Sparrow *Pooecetes gramineus*

Violet-green Swallow *Tachycineta thalassina*

Viginia Rail *Rallus limicola*

American Pipit *Anthus rubescens*

Wandering Tattler *Heteroscelus incanus*

Warbling Vireo *Vireo gilvus*

White-breasted Nuthatch *Sitta carolinensis*

White-crowned Sparrow *Zonotrichia leucophrys*

Western Bluebird *Sialia mexicana*

Pacific-slope Flycatcher *Empidonax difficilis*

Western Grebe *Aechmophorus occidentalis*

Western Kingbird *Tyrannus verticalis*

Western Meadowlark *Sturnella neglecta*

Western Screech Owl *Otus kennicottii*

Western Tanager *Piranga ludoviciana*

White-eyed Vireo *Vireo griseus*

Western Wood-Pewee *Contopus sordidulus*

Whimbrel *Numenius phaeopus*

Tundra Swan *Cygnus columbianus*

White-headed Woodpecker *Picoides albolarvatus*

Willow Flycatcher *Empidonax trailii*

Willet *Catoptrophorus semipalmatus*

Wilson\'s Phalarope *Phalaropus tricolor*

Willow Ptarmigan *Lagopus lagopus*

Williamson\'s Sapsucker *Sphyrapicus thyroideus*

Wilson\'s Warbler *Wilsonia pusilla*

Winter Wren *Troglodytes troglodytes*

Wood Duck *Aix sponsa*

Wood Thrush *Hylocichla mustelina*

Whip-poor-will *Caprimulgus vociferus*

White-rumped Sandpiper *Calidris fuscicollis*

White-throated Sparrow *Zonotrichia albicollis*

White-throated Swift *Aeronautes saxatalis*

White-winged Crossbill *Loxia leucoptera*

White-winged Scoter *Melanitta fusca*

Yellow-breasted Chat *Icteria virens*

Yellow-billed Cuckoo *Coccyzus americanus*

Yellow-bellied Flycatcher *Empidonax flaviventris*

Yellow-billed Loon *Gavia adamsii*

Yellow-bellied Sapsucker *Sphyrapicus varius*

Yellow Rail *Coturnicops noveboracensis*

Yellow-headed Blackbird *Xanthocephalus anthocephalus*

Yellow-rumped Warbler *Dendroica coronata*

Yellow-throated Vireo *Vireo flavifrons*

Yellow Wagtail *Motacilla flava*

Yellow Warbler *Dendroica petechia*

**(iii) Endangered Birds (14)**

whooping crane *Grus americana*

northern bobwhite *Colinus virginianus*

harlequin duck *Histrionicus histrionicus*

anatum peregrine falcon *Falco peregrinus anatum*

acadian flycatcher *Empidonax virescens*

burrowing owl *Athene cunicularia*

spotted owl *Strix occidentalis*

mountain plover *Charadrius montanus*

piping plover *Charadrius wilsonia*

king rail *Rallus elegans*

loggerhead shrike (Eastern) *Lanius ludovicianus*

Henslow\'s sparrow *Ammodramus henslowii*

sage thrasher *Oreoscoptes montanus*

prothonotary warbler *Protonotaria citrea*

**(iv) Threatened Birds (7)**

Yellow-breasted chat (B.C.) *Icteria virens*

sage grouse (Prairie) *Centrocercus urophasianus*

marbled murrelet *Brachyramphus marmoratus*

loggerhead shrike (Prairie) *Lanius ludovicianus*

roseate tern *Sterna dougallii*

hooded warbler *Wilsonia citrina*

white-headed woodpecker *Picoides albolarvatus*

**(iv) Vulnerable Birds (20)**

Ancient Murrelet *Synthliboramphus antiquus*

Barn Owl *Tyto alba*

Caspian Tern *Sterna caspia*

Cerulean Warbler *Dendroica cerulea*

Ferruginous Hawk *Buteo regalis*

Flammulated Owl *Otus flammeolus*

Ivory Gull *Pagophila eburnea*

Least Bittern *Ixobrychus exilis*

Long-billed Curlew *Numenius americanus*

Louisiana Waterthrush *Seiurus motacilla*

Pacific Great Blue Heron *Ardea herodias fannini*

Peale's Peregrine Falcon *Falco peregrinus pealei*

Prairie Warbler *Dendroica discolor*

Queen Charlotte Goshawk *Accipiter gentilis laingi*

Red-headed Woodpecker *Melanerpes erythrocephalus*

Red-shouldered Hawk *Buteo lineatus*

Ross' Gull *Rhodostethia rosea*

Short-eared Owl *Asio flammeus*

Tundra Peregrine Falcon *Falco peregrinus tundrius*

Yellow-breasted Chat *Icteria virens*

**E. Plants (107)**

**(i) Endangered Plants (33)**

Gattinger\'s agalinis *Agalinis gattingeri*

Skinner\'s agalinis *Agalinis skinneriana*

deltoid balsamroot *Balsamorhiza deltoidea*

water-plantain buttercup *Ranunculus alismaefolius var. alismaefolius*

Long\'s braya *Braya longii*

eastern prickly pear cactus *Opuntia humifusa*

slender bush clover *Lespedeza virginica*

pink coreopsis *Coreopsis rosea*

southern maidenhair fern *Adiantum capillus-veneris*

white prairie gentian *Gentiana alba*

small white lady\'s-slipper *Cypripedium candidum*

seaside birds-foot lotus *Lotus formosissimus*

Furbish\'s lousewort *Pedicularis furbishiae*

prairie lupine *Lupinus lepidus var. lepidus*

pink wilkwort *Polygala incarnata*

hoary mountain mint *Pycnanthemum incanum*

eastern mountain avens *Geum peckii*

slender mouse-ear-cress *Halimolobos virgata*

Western prairie white fringed orchid *Platanthera praeclara*

heart-leaved plantain *Plantago cordata*

large whorled pogonia *Isotria verticillata*

small whorled pogonia *Isotria medeoloides*

wood poppy *Stylophorum diphyllum*

Engelmann\'s quillwort *Isoetes engelmannii*

thread-leaved sundew *Drosera filiformis*

cucumber tree *Magnolia acuminata*

drooping trillium *Trillium flexipes*

water-pennywort *Hydrocotyle umbellata*

spotted wintergreen *Chimaphila maculata*

seaside centipede lichen *Heterodermia stitchensis*\
bearded owl-clover *Triphysaria versicolor ssp versicolor*

tiny cryptanthe *Cryptantha minima*

bluehearts *Buchnera americana*

**(ii) Threatened Plants (36)**

Blue ash *Fraxinus quadrangulata*

Anticosti aster *Aster anticostensis*

White-top aster *Aster curtus*

White wood aster *Aster divaricatus*

american chestnut *Castanea dentata*

colicroot *Aletris farinosa*

deerberry *Vaccinium stamineum*

mosquito fern *Azolla mexicana*

Western blue flag *Iris missouriensis*

Plymouth gentian *Sabatia kennedyana*

American ginseng *Panax quinquefolium*

Goat's-rue *Tephrosia virginiana*

Golden crest *Lophiola aurea*

Golden seal *Hydrastis canadensis*

Round-leaved greenbrier *Smilax rotundifolia*

Van Brunt's Jacob's ladder *Polemonium van-bruntiae*

Small-flowered lipocarpha *Lipocarpha micrantha*

Red mulberry *Morus rubra*

Golden paintbrush *Castilleja levisecta*

Sweet pepperbrush *Clethra alnifolia*

Nodding pogonia *Triphora trianthophora*

Redroot *Lachnanthes caroliana*

False hop sedge *Carex lupuliformis*

Western spiderwort *Tradescantia occidentalis*

Pitcher's thistle *Cirsium pitcheri*

Athabasca thrift *Armeria maritima interior*

Kentucky coffee tree *Gymnocladus dioica*

Purple twayblade *Liparis liliifolia*

Sand verbena *Abronia micrantha*

Bird's-foot violet *Viola pedata*

Yellow montane violet *Viola praemorsa praemorsa*

American water-willow *Justicia americana*

Tyrrell's willow *Salix planifolia tyrrellii*

Blunt-lobed woodsia *Woodsia obtusa*

Apple moss *Bartramia stricta*

hairy prairie-clover *Dalea villosa var. villosa*

**(iii) Vulnerable Plants (38)**

Giant helleborine *Epipactis gigantea*

Cryptic paw lichen *Nephroma occultum*

Oldgrowth specklebelly lichen *Pseudocyphellaria rainierensis*

Seaside bone lichen *Hypogymnia heterophylla*

American columbo *Frasera caroliniensis*

Bathurst aster *Aster subulatus var. obtusifolius*

Bolander's quillwort *Isoëtes bolanderi*

Branched bartonia *Bartonia paniculata*

Broad beech fern *Phegopteris hexagonoptera*

Climbing prairie rose *Rosa setigera*

Dense blazing star *Liatris spicata*

Dwarf hackberry *Celtis tenuifolia*

Eastern prairie white fringed orchid *Platanthera leucophaea*

False rue-anemone *Isopyrum biternatum*

Few-flowered club-rush *Scirpus verecundus*

Fernald's milk-vetch *Astragalus robbinsii var. fernaldii*

Green dragon *Arisaema dracontium*

Gulf of St. Lawrence aster *Aster laurentianus*

Hare-footed locoweed *Oxytropis lagopus*

Hill's pondweed *Potamogeton hillii*

Hop tree *Ptelea trifoliata*

Indian plantain *Cacalia plantaginea*

Long's bulrush *Scirpus longii*

Macoun's Meadowfoam *Limnanthes macounii*

New Jersey rush *Juncus caesariensis*

Phantom orchid *Cephalanthera austinae*

Provancher's fleabane *Erigeron philadelphicus provancheri*

Shumard oak *Quercus shumardii*

Smooth goosefoot *Chenopodium subglabrum*

Swamp rose mallow *Hibiscus moscheutos*

Victorin's gentian *Gentiana victorinii*

Victorin's water hemlock *Cicuta maculata var. victorinii*

Western silver-leaf aster *Virgulus sericeus*

Wild hyacinth *Camassia scilloides*

Lilaeopsis *Lilaeopsis chinensis*

Soapweed *Yucca glauca*

Buffalograss *Buchloë dacyloides*

Coastal wood fern *Dryopteris arguta*

**F. Fish (58)**

**(i) Endangered Fish (4)**

Nooksack dace *Rhinichthys* sp.

Salish sucker *Catostomus* sp.

Aurora trout *Salvelinus fontinalis timagamiensis*

Acadian whitefish *Coregonus huntsmani*

**(ii) Threatened Fish (15)**

Blackfin cisco *Coregonus nigripinnis*\
Shortjaw cisco *Coregonus zenithicus\
*Shortnose cisco *Coregonus reighardi*\
Channel darter *Percina copelandi*\
Eastern sand darter *Ammocrypta pellucida*\
Margined madtom *Noturus insignis*

Black redhorse *Moxostoma duquesnei*\
Copper redhorse *Moxostoma hubbsi*\
Great Lakes deepwater sculpin *Myoxocephalus thompsoni*\
Shorthead sculpin *Cottus confusus\
*Enos Lake stickleback *Gasterosteus* sp.\
Lake Simcoe whitefish *Coregonus clupeaformis*\
Lake Utopia dwarf smelt *Osmerus* sp*.*\
Texada (Benthic) stickleback *Gasterosteus* sp*.*\
Texada (Limnetic) stickleback *Gasterosteus* sp*.*

**(iii) Vulnerable Fish (39)**

Banded killifish *Fundulus diaphanus*

Bering wolffish *Anarhichas orientalis*\
Bigmouth buffalo *Ictiobus cyprinellus*

Bigmouth shiner *Notropis dorsalis*

Black buffalo *Ictiobus niger*

Blackline prickleback *Acantholumpenus mackayi*

Blackstripe topminnow *Fundulus notatus*

Brindled madtom *Noturus miurus*

Central stoneroller *Campostoma anomalum*

Charlotte unarmoured stickleback *Gasterosteus aculeatus*

Cultus pygmy sculpin *Cottus* sp*.*

Chestnut lamprey *Ichthyomyzon castaneus*

Fourhorn sculpin *Myoxocephalus quadricornis*

Giant stickleback *Gasterosteus* sp.

Green sturgeon *Acipenser medirostris*

Greenside darter *Etheostoma blennioides*

Lake chubsucker *Erimyzon sucetta*

Lake lamprey *Lampetra macrostoma*

Northern brook lamprey *Ichthyomyzon fossor*

Orangespotted sunfish *Lepomis humilis*

Pugnose minnow *Opsopoeodus emilae*

Pugnose shiner *Notropis anogenus*

Redbreast sunfish *Lepomis auritus*

Redside dace *Clinostomus elongatus*

River redhorse *Moxostoma carinatum*

Rosyface shiner *Notropis rubellus*

Shortnose sturgeon *Acipenser brevirostrum*

Silver chub *Macrhybopsis storeriana*

Silver shiner *Notropis photogenis*

Speckled dace *Rhinichthys osculus*

Spotted gar *Lepisosteus oculatus*

Spotted sucker *Minytrema melanops*

Spring cisco *Coregonus* sp.

Squanga whitefish *Coregonus* sp.

Umatilla dace *Rhinichthys umatilla*

Western silvery minnow *Hybognathus argyritis*

White sturgeon *Acipenser transmontanus*

Kiyi *Coregonus kiyi*

Warmouth *Lepomis gulosus*

**G. Molluscs (2)**

**(i) Endangered Mollusc (1)**

Hotwater physa *Physella wrighti*

**(ii) Threatened Mollusc (1)**

Banff Springs snail *Physella johnsoni*

**H. Lepidoptera (2)**

**(i) Endangered Lepidopteran (1)**

Maritime ringlet butterfly *Coenonympha tullia nipisiquit*

**(ii) Vulnerable Lepidopteran (1)**

Monarch butterfly *Danaus plexippus*

**Appendix 2. Summary of ecoregions used in analyses.**

**Name Total area (km2)**

Ellesmere and Devon Island IceCaps 35261

Ellesmere and Devon Island IceCaps 24970

Ellesmere and Devon Island IceCaps 12852

Ellesmere and Devon Island IceCaps 51449

Baffin Mountains 97976

Baffin Islands Coastal lowlands 11113

Torngat Mountains 33661

Ellesmere Mountains 58170

Eureka Hills 94118

Ellesmere Mountains 15687

Sverdrup Islands Lowland 85456

Parry Islands Plateau 74073

Lancaster Plateau 113189

Banks Island Coastal Plain 12165

Banks Island Lowland 49864

Amundsen Gulf Lowlands 99652

Shaler Mountains 23453

Victoria Islands Lowland 193406

Prince of Wales Island Lowland 19894

Boothia Peninsula Plateau 38050

Gulf of Boothia Plateau 28902

Borden Peninsula Plateau 35078

Melville Peninsula Plateau 117169

Baffin Island Uplands 75871

Foxe Basin Plain 62976

Pangnirtung Upland 42061

Hall Peninsula Upland 33340

Meta Incognita Peninsula 85932

Baffin Upland 15275

Wager Bay Plateau 249338

Northern Ungava Peninsula 38051

Yukon Coastal Plain 6768

Tuktoyuktuk Coastal Plain 26135

Anderson River Plain 16327

Dease Arm Plain 54746

Coronation Hills 55885

Bluenose Lake Plain 21540

Bathurst Hills 13948

Queen Maud Gulf Lowland 65260

Chantrey Inlet Lowland 22548

Takijua Lake Upland 111497

Garry Lake Lowland 80717

Back River Plain 36267

Dubwant Lake Plain/Upland 51449

Maguse River Upland 76942

Southampton Island Plain 41696

Central Ungava Peninsula 153436

Ottawa islands 805

Belcher Islands 6670

Mackenzie Delta 8643

Peel River Plateau 57668

Great Bear Lake Plain 102579

Fort MacPherson Plain 28308

Colville Hills 18842

Norman Range 40198

Mackenzie River Plain 15283

Grandin Plains 9194

Franklin Mountains 6070

Keller Lake Plain 25482

Great Slave Lake Plain 36181

Nahani Plateau 11502

Sibbeston Lake Plain 12809

Horn Plateau 23271

Hay River Lowland 120134

Northern Alberta Uplands 58262

Muskwa Plateau 22888

Northern Alberta Uplands 12352

Coppermine River Upland 129017

Tazin Lake Upland 111718

Kazan River Upland 169910

Selwyn Lake Upland 185692

La Grande Hills 121693

Southern Ungava Peninsula 79339

New Quebec Central Plateau 180259

Ungava Bay Basin 85979

George Plateau 21878

Kingarutuk-Fraser River 64394

Smallwood Reservoir-Michikamau 84617

Coastal Barrens 11602

Mecatina River 6070

Kingarutuk-Fraser River 2848

Eagle Plateau 13142

Mecatina River 2496

Harp Lake 3094

Nipishish Lake 4961

Mecatina River 45874

Athabasca Plain 76241

Churchill River Upland 188196

Hayes River Upland 136520

Lac Seul Upland 143445

Lake of the Wooods 44768

Rainy River 3468

Thunder Bay-Quetico 26910

Lake Nipigon 92759

Big Trout Lake 108389

Abitibi Plains 186730

Lac Temiscaminque Lowland 90049

Algonquin-Lake Nipissing 76784

Southern Laurentians 170129

Riviere Rupert Plateau 90366

Central Laurentians 207537

Anticosti Island 9834

Mecatina Plateau 101482

Paradise River 19437

Lake Melville 20764

Strait of Belle Isle 3796

Northern Peninsula 10793

Long Range Mountains 6265

Southwestern Newfoundland 13355

Long Range Mountains 6403

Long Range Mountains 2972

Central Newfoundland 30640

Northeastern Newfoundland 9833

Maritime Barrens 43571

Avalon Forest 457

South Avalon-Burin Oceanic Barrens 3110

Appalachians 71801

Chaleur Uplands 25093

Northern New Brunswick Highlands 5076

Saint John River Valley 4617

Southern New Brunswick Uplands 14039

Maritime Lowlands 31647

Fundy Coast 9102

Southwest Nova Scotia Uplands 16692

Atlantic Coast 11342

Annapolis- Minas Lowlands 4802

South-central Nova Scotia Uplands 6403

Nova Scotia Highlands 18202

Cape Breton Highlands 2287

Prince Edward Island 8552

Iles-de-la-Madeleine 1189

St-Laurent Lowlands 46783

Frontenac Axis 1212

Manitoulin-Lake Simcoe 84218

Lake Erie Lowland 43600

Slave River Lowland 48662

Clear Hills Upland 42896

Peace Lowland 67182

Mid-Boreal Uplands 7729

Mid-Boreal Uplands 3201

Mid-Boreal Uplands 11578

Wabasca Lowland 49498

Western Boreal 10960

Mid-Boreal Uplands 24696

Western Alberta Upland 71819

Western Alberta Upland 1583

Mid-Boreal Uplands 118026

Mid-Boreal Lowland 90236

Boreal Transition 98170

Mid-Boreal Uplands 6724

Mid-Boreal Uplands 3162

Mid-Boreal Uplands 8458

Mid-Boreal Uplands 5207

Mid-Boreal Uplands 4619

Interlake Plain 39295

Aspen Parkland 170315

Moist Mixed Grassland 98430

Fescue Grassland 14824

Mixed Grassland 132170

Cypress Upland 8351

Aspen Parkland 2172

Lake Manitoba Plain 32497

Boreal Transition 1473

Boreal Transition 628

British-Richardson Mountains 25380

Old Crow Basin 14011

Old Crow Flats 5546

North Ogilvie Mountains 37239

Eagle plains 19322

Mackenzie Mountains 81664

Selwynn Mountains 68000

Klondike Plateau 36483

St.Elias Mountains 23320

Ruby Ranges 21636

Yukon Plateau -Central 25463

Yukon Plateau -North 54101

Yukon Southern Lakes 33668

Pelly Mountains 33553

Yukon-Stikine Highlands 23618

Boreal Mountains and Plateaus 100147

Liard Basin 32397

Hyland Highland 24629

Northern Canadian Rocky Mountains 35998

Mount Logan 3982

Northern Coastal Mountains 2724

Northern Coastal Mountains 24051

Nass Basin 5362

Queen Charlotte Ranges 6895

Queen Charlotte Lowland 2618

Mass Ranges 12269

Coastal Gap 46242

Pacific Ranges 58184

Western Vancouver Island 18910

Eastern Vancouver Island 13173

Georgia-Puget Basin 1401

Lower Mainland 4516

Cascade Ranges 285

Skeena Mountains 21942

Omineca Mountains 33523

Central Canadian Rocky Mountains 35525

Bulkley Ranges 2784

Fraser Plateau 88975

Fraser Basin 44677

Chilcotin Ranges 11617

Columbia Mountains and Highlands 87616

Western Continental Ranges 23291

Eastern Continental Ranges 38879

Interior Transition Ranges 14880

Thompson-Okanagan Plateau 37549

Okanagan Range 4446

Okanagan Highland 1149

Selkirk-Bitterroot Foothills 7806

Southern Rocky Mountain Trench 7619

Northern Continental Divide 15634

Coastal Hudson Bay Lowland 58492

Hudson Bay Lowland 128478

James Bay Lowlands 171019

**Appendix 3. Colour Maps**

Map 1 Equal area hex. grid for Canada.

Map 2 Sample maps of species richness displayed by equal area.

Map 3 Sample maps of summed irrelaceability.

Map 4 Sample maps of minimum set analysis results.

Map 5 Maps of human pressure sources.

Map 6 Maps of human pressure index and risk to biodiversity model