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Species richness and biodiversity conservation priorities in British Columbia, Canada Kathryn E. Freemark, Mark Meyers, Denis White, Leanna D. Warman, A. Ross Kiester, and Pago Lumban-Tobing
Abstract: Patterns in the geographic distribution of seven species groups were used to identify important areas for conservation in British Columbia, Canada. Potential priority sites for conservation were determined using an integer programming algorithm that maximized the number of species represented in the minimum number of sites. Sweep analyses were used to determine how well the set of priority sites identified for each species group represented the other species groups. Although areas of highest species richness were different for each species group, they all included sites in the southern interior of British Columbia, where there is limited protection. Furthermore, less than 13% of the distribution ranges for 23 of 25 bird species of special conservation concern were located within existing protected areas. Species at risk of extinction were poorly represented (26%–42%) in priority sets of sites selected for amphibians, reptiles, birds, and mammals, since these sites were generally scattered throughout the province. However, priority sites for species at risk represented 72%–91% of the species in other groups. Therefore, conservation activities in sites identified for such species have the potential to benefit many other species. These sites could be investigated in more detail to augment existing conservation and protection efforts in British Columbia. Résumé : Les patrons de répartition géographique de sept groupes d’espèces nous ont servi à identifier des zones importantes pour la conservation en Colombie-Britannique, Canada. Nous avons déterminé les sites prioritaires potentiels pour la conservation à l’aide d’un algorithme de programmation à nombres entiers qui maximise le nombre d’espèces représentées dans le nombre minimum de sites. Des analyses de balayage ont permis de déterminer avec quel succès l’ensemble de sites prioritaires établi pour chacun des groupes d’espèces représente les autres groupes d’espèces. Bien que les zones de richesse spécifique maximale diffèrent d’un groupe d’espèces à un autre, elles incluent toutes des sites de l’intérieur des terres dans le sud de la Colombie-Britannique, où la protection est limitée. De plus, moins de 13 % des aires de répartition de 23 des 25 espèces d’oiseaux qui sont des sujets de préoccupation pour la conservation sont situées dans les zones actuellement protégées. Les espèces à risque de disparition sont mal représentées (26 % – 42 %) dans les ensembles prioritaires de sites retenus pour les amphibiens, les reptiles, les oiseaux et les mammifères, puisque ces sites sont généralement éparpillés dans toute la province. Cependant, les sites prioritaires pour les espèces à risque représentent 72 % – 91 % des espèces des autres groupes. Les activités de conservation dans les sites identifiés pour ces espèces à risque sont donc potentiellement bénéfiques à plusieurs autres espèces. Ces sites de ColombieBritannique pourraient être étudiés plus en détail afin d’y accroître les efforts actuels de conservation et de protection. [Traduit par la Rédaction]
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Introduction It is generally accepted in the conservation literature that existing protected areas will not adequately protect biodiversity over the long term. Although there are multiple reasons for this assertion that vary regionally, the main factors are (i) many protected areas have been identified on an ad hoc or opportunistic basis (Pressey 1994), (ii) these areas are too small to maintain populations of species within them
(Diamond 1975), and (iii) they are scattered and lack connectivity that allows for species dispersal and migration (Diamond 1975). Therefore, protected areas must be augmented with additional areas that are managed for conservation of regional biodiversity (Kerr and Cihlar 2004). With limited resources available for conservation, it is imperative to prioritize allocation of this effort. Computer algorithms have been developed with that purpose in mind (see reviews in Margules and Pressey 2000;
Received 3 May 2005. Accepted 21 November 2005. Published on the NRC Research Press Web site at http://cjz.nrc.ca on 10 January 2006. K.E. Freemark.1,2 National Wildlife Research Centre, Environment Canada, Ottawa, ON K1A 0H3, Canada. S.M. Meyers. Department of Geosciences, Oregon State University, Corvallis, OR 97331, USA. D. White. US Environmental Protection Agency, Corvallis, OR 97333, USA. L.D. Warman. Biodiversity Research Centre, University of British Columbia, Vancouver, BC V6T 1Z4, Canada. A.R. Kiester. Biodiversity Futures Consulting, 5550 SW Redtop, Corvallis, OR 97333, USA. P. Lumban-Tobing. ING Clarion, 230 Park Avenue, New York, NY 10169, USA. 1 2
Corresponding author (e-mail:
[email protected]). Present address: Knowledge Integration Strategies Division, Strategic Information Integration Directorate, Environment Canada, 70 Cremazie Street, Gatineau (Hull), QC K1A 0H3, Canada.
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doi:10.1139/Z05-172
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Cabeza and Moilanen 2001). These algorithms are used to identify the most efficient or cost effective areas that achieve the conservation goals of a region. The algorithms use geo-referenced species distribution data within a matrix of sites that define a region (Margules et al. 2002). The spatially explicit solutions provide a set of sites that represent all of the targeted biodiversity in the minimum amount of area based on the concept of complementarity (Vane-Wright et al. 1991; Pressey et al. 1993). The solutions are flexible so that there are choices for selecting priority areas to minimize the conflict between conservation and competing land uses (Margules et al. 2002). One method of incorporating flexibility is to identify the consequences of removing particular sites from the solution by rerunning the algorithm after excluding sites from selection (Margules et al. 2002). Another method that can include flexibility is simulated annealing, where the algorithm begins with a random set of sites and then swaps sites in and out while measuring the change in cost (Andelman and Willig 2002). The swapped site is carried forward to the next iteration if it decreases the cost and increases or maintains the biodiversity included in the reserve system. Flexibility is accomplished by running a simulated annealing scenario multiple times while measuring the percentage of times that each site is selected (i.e., site irreplaceability). In this study, we apply the maximal covering, integer programming method (Church et al. 1996; Kiester et al. 1996; Arthur et al. 1997; White et al. 1999) to identify important areas for achieving conservation goals in the province of British Columbia in Canada. This algorithm provides an optimal method for identifying reserve networks (Underhill 1994; Csuti et al. 1997) and incorporates flexibility by identifying the options for conservation as solution sets, where each set of a fixed number of sites has the same optimal level of complementarity. Although greater than 12% of the province has been protected in both provincial and national parks collectively, much of British Columbia’s biodiversity is not located within the system of parks (Scudder 2000, 20023). Therefore, these methods can be used to ask “Where are the best places within British Columbia for further investigation or conservation activity, such as extending the network of existing protected areas to better represent 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 adjacent areas and the matrix as a whole (Pressey et al. 1995; Flather et al. 1997; Margules et al. 2002; Kerr and Cihlar 2004). Surrogates or indicators for biodiversity, such as individual taxa, species assemblages, vegetation types, and environmental classes, have been used in priority site selection (cf. Margules et al. 2002), since it is time consuming and expensive to obtain species data for all biodiversity within a region. However, the success of such surrogates at representing other species within a region is varied (Kerr 1997; Howard et al. 1998; Ricketts et al. 1999; Andelman and Fagan 2000;
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Lawler et al. 2003; Warman et al. 2004a). These types of analyses may be dependent on the surrogate groups evaluated (Andelman and Fagan 2000; Manne and Williams 2003), methodology used to examine surrogate performance (Reyers and van Jaarsveld 2000; Warman et al. 2004a), geographical characteristics of the region (Ryti 1992; Andelman and Fagan 2000), and the scale of the study (Garson et al. 2002; Warman et al. 2004b). Owing to the lack of any general consensus on the value of surrogates in conservation planning, it is important to evaluate the effectiveness of surrogates for biodiversity regionally. In this study, we identified patterns of species richness and important sites for maintaining different taxonomic groups, bird species of special conservation concern, and species at risk of extinction within British Columbia. Then we examined the suitability of each species group to act as a surrogate for other groups of species, particularly for species at risk of extinction, since these species are a national priority for conservation within Canada. We also assessed whether the existing protected areas in the province overlap with ranges of bird species of special conservation concern. These migratory bird species are the focus for the international Partners in Flight program in British Columbia (Canadian Landbird Conservation Working Group 1996).4 The goal of this program is to ensure that populations of native Canadian landbirds, which are generally not threatened currently, remain viable over the long term across their range of habitats. We demonstrate how a complementarity analysis could benefit a national conservation program such as this.
Methods Species data We included all native bird, mammal, reptile, and amphibian species resident or breeding in British Columbia. Introduced and incidental species were excluded. Bird species of special conservation concern to the Partners in Flight program of the Canadian Wildlife Service and the Provincial Government of British Columbia were identified according to Dunn (1997) and grouped in their own category (SOC birds). SOC bird species were identified based on jurisdictional responsibility (i.e., those species for which 50% of their breeding range occurs in Canada and thus Canada has high conservation responsibility), population trend, and threats. Endangered, threatened, and special concern species based on 1998 designations by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) were also grouped as an individual category. Endangered species are those that are facing imminent extirpation or extinction nationally (Committee on the Status of Endangered Wildlife in Canada 2004). Threatened species are likely to become endangered if limiting factors are not reversed. Special concern species are those that may become threatened or endangered because of a combination of biological characteristics and identified threats. We included 18 amphibians, 15 reptiles, 274 birds, 102 mammals, 59 COSEWIC species, and 25 SOC birds in our
3
G.G.E. Scudder. 2002. Biodiversity conservation and protected areas in British Columbia. Unpublished report for the Sierra Legal Defense Fund, Vancouver, B.C. [online]. Available from http://www.biodiv.ca/centre/hotspots [cited 26 September 2005]. 4 Canadian Landbird Conservation Working Group. 1996. Framework for landbird conservation in Canada. Unpublished report for Partners in Flight, Canadian Wildlife Service, Environment Canada, Ottawa. © 2006 NRC Canada
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analyses.5 Species range maps for mammals, reptiles, and amphibians were developed by digitally scanning pages from Peterson Field Guides, Western Reptiles and Amphibians (Stebbins 1985), Peterson Field Guides, Mammals (Burt and Grossenheider 1980), and Mammals of North America (Hall 1981). Permission to scan the range maps was obtained from Houghton Mifflin Company, Dr. Robert Stebbins, and John Wiley and Sons, Inc. Scanned maps were calibrated into an appropriate map projection using identifiable control points (e.g., provincial intersections). We used digital range maps for birds that were produced by Welsh et al. (1999). The range maps were the best available and most comprehensive data for these species at the time of our study. The COSEWIC data were obtained from the Species at Risk Branch, Canadian Wildlife Service, Environment Canada (Gatineau (Hull), Quebec), and were based on occurrences and distributions of species. Equal-area sampling framework We constructed a standard Environmental Monitoring and Assessment Program (EMAP) hexagon grid (White et al. 1999; White 2000) of an approximate area of 640 km2, with a centre-point to centre-point spacing of approximately 27 km, to cover the province. The resulting grid contained 1589 hexagons. The map of British Columbia was derived from Digital Charts of the World (Environmental Systems Research Institute, Inc. 1992). Digital maps of species ranges were overlaid with the hexagon grid to detect the presence of species within each grid cell covering the province. The intersection of these two map layers resulted in a list of hexagons that represented the range for any given species. For mammals, a combined range from the two data sources was used to identify hexagons. Hexagon by species occurrence matrices were developed for each taxonomic group or species group, each of which consisted of a list of hexagon numbers followed by a series of ones and zeros that represent whether a species occurred in a hexagon (1) or did not (0). These hexagonal matrices were used for each of our analyses. We refer to hexagons as “sites” in the remainder of this paper. Species richness The species richness analysis was the first step in summarizing spatial data for the terrestrial vertebrates, providing an illustration of species diversity for the entire province. Species richness for each site was calculated by counting the number of different species in each site without regard to area occupied. Sites were ranked and sorted into four to five classifications for display. Data analysis for species richness was completed for each taxonomic group, SOC birds, and COSEWIC species. Site prioritization We used an integer programming approach to the “maximal location covering problem” (Church et al. 1996) for our prioritization analysis as an algorithmic method of reserve selection (Kiester et al. 1996; White et al. 1999). Maximal 5
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location covering models are more efficient than iterative algorithms because they identify optimal sets of sites simultaneously that maximize the conservation objectives (Church et al. 1996). We used IBM’s Optimizing Subroutine Library (OSL version 2.0 for AIX RISC/6000, Optimization Program Development Department, IBM Corporation, Kingston, New York) for prioritization computations. The goal was to determine the minimum number of sites that taken together have at least one occurrence of every species. This minimum set of sites (i.e., solution set) has an optimum level of complementarity (i.e., combined species richness) for a species group, but there is no prioritization of the sites within a solution set. The optimization algorithm was performed for incremental sizes of the solution set (i.e., the total number of sites in the solution set was increased by one hexagon). For each incremental solution set size, the algorithm found the sets of sites whose combined species richness was maximum (Arthur et al. 1997, Kiester et al. 1996; White et al. 1999). At size one, the algorithm found the single individual site, or all of the individual sites in cases where there were more than one, that had the greatest species richness. At size two, the algorithm found all of the sets of two sites (i.e., pairs) that jointly had the greatest species richness. At size three, it found all of the triples of hexagons that had the greatest combined species richness, and so forth. The size of the solution sets was incremented until all species were represented in one or more sites. At any size, the identification of sets of sites was limited to finding the first 1001 solution sets, in cases in which there were more than 1001 solution sets possible. It should be noted that, for example, sets of two sites with the combined greatest species richness may or may not have included a site that individually had the greatest species richness, and likewise for any larger solution set size (Underhill 1994). At each incremental solution set size, there can be more than one set of sites having the same combined species richness (e.g., up to 1001 solutions sets in our analyses). In these cases, there may be some sites that occur in each solution set and some that only occur in some solution sets. Sites occurring in every solution set are considered to be “irreplaceable”, meaning that they have to be included in the final set of sites for the solution to be optimally inclusive of all species (Pressey et al. 1993, 1994). Furthermore, each solution set, for any solution size, contains sites that have similar, though not necessarily identical, contributions to the combined species richness as sites in other solution sets. These alternative sites can form a group from which only one site is necessary to be included in an optimal solution that contains the minimum number of sites to represent all species (Csuti et al. 1997). Generally, members of such groups are located in close proximity because of overlapping species ranges, but this is not always the case. These closely related groups of sites that were, at least in part, interchangeable between solution sets were mapped in the same color in Fig. 2 to indicate that only one of them participated in any single solution. However, these maps suggest that
Table S1 is available on the Web site or may be purchased from the Depository of Unpublished Data, Document Delivery, CISTI, National Research Council Canada, Ottawa, ON K1A 0R6, Canada. DUD 4063. For more information on obtaining material, refer to http://cisti-icist. nrc-cnrc.gc.ca/irm/unpub_e.shtml. © 2006 NRC Canada
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there are optimal solutions that may not exist (i.e., it is not always the case that any combination of sites, one of each color, constitutes an optimal solution). Sweep analysis The first step in this analysis was to identify the priority sites for one species group and then calculate how much of any other species group was incidentally represented in the priority sites (Kiester et al. 1996; White et al. 1999; Warman et al. 2004a). For example, we identified the set of sites with the highest combined species richness for reptile species (i.e., 100% of the reptile species occur within these sites) and then counted the number of mammal species that also occurred in those sites. That is, we counted the number of mammals that are “swept along” in sites selected for reptiles. Although the number of target species included in the selected sites increases at each stage of the algorithm, the number of non-target species that are swept along does not necessarily increase because the group of sites selected at each stage of the algorithm can be a completely different set than those selected at the previous stage (see previous section for description of the selection procedure). This analysis measured the maximum representation of non-target species in sites selected for target species groups (Lawler et al. 2003). We also evaluated how well a set number of sites selected for one species group represented the non-target species groups (i.e., nth partial coverage). For example, we identified the five sites with the highest combined species richness for reptile species and then counted the number of mammal species that also occurred in those sites. We chose five sites as the standard because this was the smallest number of sites selected to represent all species in two of the species groups (i.e., both amphibians and reptiles). This analysis provided a standard comparison of non-target species representation (Lawler et al. 2003). Gap analysis We estimated the proportion of SOC bird ranges within the province that coincided with protected areas to provide a representation of gaps in protection of these species (cf. Scott et al. 1993; Kiester et al. 1996; Warman et al. 2004a). SOC bird ranges were overlaid with an ArcInfo® coverage of protected areas produced by the province (Protected Areas Strategy 1998), available from the British Columbia Ministry of Sustainable Resource Management. The protected areas map layer included national parks, provincial parks, wildlife reserves, wilderness areas, and Land and Resource Management Plan (LRMP) protected areas. LRMP protected areas occur on crown land and were identified by regional multi-stakeholder groups by considering all of the possible resource values of an area. In many regions, the LRMP protected areas have since been designated as provincial parks.
Results Species richness Species richness for vertebrates declined from south to north and from the interior towards the coast (Fig. 1), except for amphibians (Fig. 1a), which showed high species richness on the southwest coast of the mainland. COSEWIC species had the highest species richness in four geographic locations:
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the Queen Charlotte Islands, the southern tip of Vancouver Island, the southwest mainland, and the Okanagan Valley (Fig. 1f). Species richness for all bird species was greatest in the south-central and southeastern areas of the province (Fig. 1c), whereas the richest areas for SOC birds, a subset of all birds, were slightly west of these areas (Fig. 1d). Site prioritization Both amphibians (Fig. 2a) and reptiles (Fig. 2b) required five sites to represent all species, which is the least number of sites compared with the priority sets of sites for other species groups (Table 1). COSEWIC species (Fig. 2f) required the greatest number of sites (i.e., 18 hexagons) to represent all species. The priority locations were scattered throughout the province for all species groups except for reptiles (Fig. 2b), which were confined to the most southerly latitudes. Few sites were irreplaceable (i.e., had no alternative sites) in the priority solutions for each species group (Table 1). The COSEWIC species group had the largest number of irreplaceable sites (i.e., seven hexagons). Irreplaceable sites are identified in Fig. 2 as individual sites that have a unique colour. Sweep analysis A general trend in the sweep analyses was that sites selected for complete coverage of other species groups represented COSEWIC species poorly (26%–42% of species; Fig. 3). In contrast, the set of 18 sites selected for all COSEWIC species represented 72%–91% of species in other groups (Fig. 3f), with the highest average proportional representation (87%) of all the groups considered in our analyses. Furthermore, when restricting the priority site selection to five sites, COSEWIC species represented 68%–89% of species in other groups, thereby again providing one of the best surrogates (Table 2). With complete coverage of all birds in 14 sites (Fig. 3c), birds represented the greatest number of species in other taxonomic groups (78%–92%, excluding SOC birds because this group is a subset of all birds; average proportional representation was 83%), although they did poorly at representing COSEWIC species (28% of species). However, when restricting the priority site selections to five, mammals represented the greatest number of species (74%–91%) in other taxonomic groups (Table 2). Furthermore, with seven sites providing complete coverage for mammal species (Fig. 3e), mammals represented 70%–92% of species in other groups, which was second to birds. The five sites providing complete coverage for amphibians were tied with the seven sites for mammals (average proportional representation of 82%), representing 74%–88% of species in other taxonomic groups. However, both mammals and amphibians did poorly at representing COSEWIC species (34% and 40% of species, respectively). Birds provided the worst surrogate group (58%–88% of species in other groups) when selections were restricted to the first five sites (Table 2). An interesting result to note was that the first five selected sites for mammals (Table 2) represented a greater proportion of COSEWIC species (42%) than all seven sites that provided complete coverage of mammals (Fig. 3e). In fact, only the incidental representation of birds, SOC birds, and mammals increased with the addition of two more sites to the © 2006 NRC Canada
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Can. J. Zool. Vol. 84, 2006
Fig. 1. Species richness (i.e., number of species per 640 km2 hexagon) in British Columbia of (a) amphibians, (b) reptiles, (c) birds, (d) bird species of concern (SOC birds), (e) mammals, and (f) Committee on the Status of Endangered Wildlife in Canada (COSEWIC) species.
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Fig. 2. Priority sites in British Columbia for (a) amphibians, (b) reptiles, (c) birds, (d) SOC birds, (e) mammals, and (f) COSEWIC species. The subsets of sites identified by different colours are groups from which only one site participates in any of the optimal combinations of minimum sets for species representation. Sites in each group are not interchangeable, as they are each part of a particular set of sites that form an optimal solution. Irreplaceable sites are individual sites that have a unique colour.
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Table 1. The number of sites and number of irreplaceable sites in the priority solutions that represent 100% of the species in each species group. Species group
Number of sites/ groups of sites
Number of irreplaceable sites
Amphibians Reptiles Birds SOC birds Mammals COSEWIC
5 5 14 6 7 18
0 1 2 1 1 7
Note: SOC birds, bird species of concern; COSEWIC, Committee on the Status of Endangered Wildlife in Canada.
first five selected; the incidental representation of both amphibians and reptiles decreased. Gap analysis The ranges of SOC birds were generally not well represented (0%–12.5%) in the existing protected areas network (Table 3). Greater than 12.5% of the ranges of both the Smith’s Longspur and the Loggerhead Shrike overlap with provincial parks. However, the Smith’s Longspur has a range restricted to the extreme northwest of the province and the northern limit of the Loggerhead Shrike’s western range just enters British Columbia. Therefore, the proportional overlap with parks in British Columbia does not provide an accurate representation of protection gaps for these two species.
Discussion Our study provides an important step in identifying priorities for conservation in British Columbia since it is the first complementarity analysis to be performed for the province in its entirety. Some of the areas that have been highlighted by our work, such as sites in the southern interior and the southern coast of British Columbia, have also been identified as priorities for conservation by other studies using different data sets (Scudder 20023; Kerr and Cihlar 2004; Warman et al. 2004a). Therefore, the influence of both scale (Garson et al. 2002; Warman et al. 2004b) and accuracy of the species range data may be minimal. Some of the areas that have been identified by our analyses have not been documented by other studies, such as sites in the northwest corner of the province. Thus, our study provides insights into the ability of previously unidentified sites to contribute to the representation of biodiversity within the province, and identifies gaps in existing conservation strategies. The southern portion of British Columbia, in particular the southern interior (Okanagan Valley) and south coast (southern Vancouver Island and Lower Mainland), has the highest species richness in the province for terrestrial vertebrate species (Fig. 1). Furthermore, at least two sites from the set of priority sites for each species group are located in these two areas (Fig. 2), some of which are irreplaceable. Unfortunately, these areas are afforded little protection in both provincial and national parks relative to other areas of the province, in part because of extensive human development. Our analyses identify that the northwest corner of the province, which has not been a focus for conservation strate-
gies in British Columbia, is also an important area for biodiversity in British Columbia. Both birds and mammals require at least two sites from this area for a complete complementarity set of sites for conservation (Fig. 2). This result may be particularly useful to the Partners in Flight program for identifying an important but previously unknown area for SOC birds that will require further study or conservation effort. Future conservation activities, including habitat restoration, stewardship, and education, should focus on these and other areas in British Columbia that have been identified as priorities but are lacking current protection. Analyses of biodiversity performed elsewhere in Canada show patterns similar to ours in British Columbia. In Quebec, Garson et al. (2002) found that both species at risk and birds are located in the most southerly areas of the province where there is little protection because these areas are heavily populated. Sarakinos et al. (2001) found that sites selected for species at risk, using a complementarity algorithm, do not coincide with existing protected areas in Quebec. The species richness patterns and priority sites identified in both British Columbia and Quebec are also consistent with those at the national scale (Freemark et al. 2000; Kerr and Cihlar 2004; Warman et al. 2004a). These studies can help managers to understand how regional-scale perspectives can complement a national-scale biodiversity conservation strategy. The approach should aid in the process of decentralizing resource management decision making to the community level by helping communities understand their importance in a larger region, while maintaining those larger scale perspectives necessary for integrated planning to ensure conservation and sustainable resource use. The similarity of results of the biodiversity and complementarity studies in Canadian provinces and the nation as a whole is likely a consequence of the strong latitudinal gradient in species distribution within North America (Simpson 1964). As a result, species richness in Canada is greatest along its southern international border. Not surprisingly, this region is also the richest in species at risk, which generally have very small distributions within Canada, since they are at the northern limits of their range (Rodrigues and Gaston 2002; Kerr and Cihlar 2004). What is somewhat surprising, however, is that species at risk (COSEWIC-listed species) provide a useful surrogate for other species in British Columbia, but that the reciprocal relation does not occur. This result has also been documented elsewhere in North America (Garson et al. 2002; Lawler et al. 2003; Warman et al. 2004a). Although the converse conclusion has also been noted, these studies either examined how well endangered species from one surrogate group represented another endangered species group (Dobson et al. 1997; Andelman and Fagan 2000) or how well endangered species within one taxonomic group represented common species from the same taxonomic group (Bonn et al. 2002). Therefore, these studies are not directly comparable with ours. In addition to the effect of the latitudinal gradient in species distributions, the studies that identify species at risk as potentially useful surrogates for biodiversity may be a consequence of the species included in the category of “species at risk”. These three studies (Garson et al. 2002; Lawler et al. 2003; Warman et al. 2004a), along with ours, consisted of listed species across taxonomic groups, which included © 2006 NRC Canada
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Fig. 3. Sweep analyses for (a) amphibians, (b) reptiles, (c) birds, (d) SOC birds, (e) mammals, and (f) COSEWIC species. The curves trace the percentages of species from other species groups that are incidentally represented or “swept along” in successive optimal solutions for the target species group. The legend applies to all graphs (i.e., each species group is shown in the same colour in each graph).
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Can. J. Zool. Vol. 84, 2006 Table 2. The proportion of species in non-target species groups (column headings) represented by sets of five priority sites for target species groups (row headings). Non-target species group (sweepees) Target species group (sweepers)
Amphibians
Reptiles
Birds
Mammals
SOC birds
COSEWIC
Average (excluding SOC birds and COSEWIC)
Amphibians Reptiles Birds Mammals SOC birds COSEWIC
1.00 0.77 0.80 0.88 0.76 0.89
0.74 1.00 0.58 0.74 0.63 0.73
0.85 0.78 0.96 0.91 0.92 0.78
0.88 0.84 0.88 0.98 0.86 0.84
0.79 0.67 0.92 0.82 0.96 0.68
0.40 0.42 0.20 0.42 0.24 0.73
0.82 0.79 0.76 0.84 0.75* 0.81
Note: The values along the diagonal are not equal to 1.00 because these proportions are based on the first five sites selected for the “sweepers”, which do not provide complete coverage for all target species (except for amphibians and reptiles). *Excludes “birds” species group, since SOC birds are a subset of all birds.
Table 3. The percentages of range overlap with protected areas for SOC birds in British Columbia. Common name
Scientific name
Total range (km2)
Percentage of range protected
Smith’s Longspur Loggerhead Shrike* Lewis’s Woodpecker Band-tailed Pigeon Spotted Owl Hutton’s Vireo Blue Grouse American Dipper Northern Goshawk Olive-sided Flycatcher Snow Bunting Short-eared Owl Flammulated Owl Tree Swallow Black Swift Western Grebe Blackpoll Warbler Eared Grebe Rusty Blackbird Canyon Wren Sage Thrasher Common Grackle Nelson’s Sharp-tailed Sparrow Purple Martin
Calcarius pictus (Swainson, 1832) Lanius ludovicianus L., 1766 Melanerpes lewis (G.R. Gray, 1849) Patagioenas fasciata (Say, 1823) Strix occidentalis (Xantus de Vesey, 1860) Vireo huttoni Cassin, 1851 Dendragapus obscurus (Say, 1823) Cinclus mexicanus Swainson, 1827 Accipiter gentilis (L., 1758) Contopus cooperi (Nuttall, 1831) Plectrophenax nivalis (L., 1758) Asio flammeus (Pontoppidan, 1763) Otus flammeolus (Kaup, 1853) Tachycineta bicolor (Vieillot, 1808) Cypseloides niger (Gmelin, 1789) Aechmophorus occidentalis (Lawrence, 1858) Dendroica striata (Forster, 1772) Podiceps nigricollis Brehm, 1831 Euphagus carolinus (Muller, 1776) Catherpes mexicanus (Swainson, 1829) Oreoscoptes montanus (Townsend, 1837) Quiscalus quiscula (L., 1758) Ammodramus nelsoni Allen, 1875 Progne subis (L., 1758)
10 100 400 278 300 102 100 65 700 56 500 850 200 926 000 946 500 946 500 940 500 936 400 78 000 886 400 561 700 351 800 634 900 385 900 535 200 65 200 36 900 52 400 23 100 2 800
61.3 59.7 12.5 12.3 12.2 11.9 10.9 10.8 10.6 10.6 10.6 10.5 10.5 10.5 10.3 9.9 9.7 9.6 9.4 5.6 4.9 1.6 0.5 0.0
*Considered to be “accidental” within the province by the British Columbia government.
plants and, for three of the four studies, invertebrates. Manne and Williams (2003) found that indicator species with small mean range sizes from across taxonomic groups provide good indicators for other species. Our results support their conclusion, because distributions of species at risk in Canada generally have small mean range sizes. However, widespread threatened species may not be as successful (Manne and Williams 2003). The inclusion of plants in the indicator group also seems to increase its success at representing other species (Ryti 1992; Kati et al. 2004; Manne and Williams 2003). Hence, the diversity of COSEWIClisted species used in our analyses may have a large influence on their surrogacy value relative to other taxonomic groupings of species.
The grid cell size used for analyses is another factor that could potentially affect our results. Species at risk generally have small ranges that may be artificially increased by the 640 km2 grid cell size relative to those with larger ranges (Lawler et al. 2003), which could increase their success as a surrogate group relative to other species groups. Furthermore, the grid overlay on range maps of species with larger ranges can decrease the precision of the range boundaries, and thus introduce errors in the allocation of species to sites. If this error is significant, it could influence the relative surrogacy values of different species groups. Although it has been noted that the success of species at risk as surrogates could be influenced by the number of sites selected relative to other taxonomic groups (Dobson et al. © 2006 NRC Canada
Freemark et al.
1997; Warman et al. 2004a), we found that species at risk performed equally well when comparing surrogacy in the first five sites selected for each species group. However, because there are three factors that could affect our results regarding the success of species at risk as surrogates for other terrestrial vertebrates, we cannot assume that our results would be reproduced if a different group of species at risk (e.g., including only terrestrial vertebrate species at risk) or a smaller grid size was used. Furthermore, our results are based on a set of species that were identified by COSEWIC in 1998. As new species are added and hopefully others removed from the COSEWIC lists, complementarity analyses will need to be redone to sequentially build on a comprehensive biodiversity strategy for British Columbia. Two other indicator groups, birds and mammals, seem to represent other species reasonably well in British Columbia. This result is promising, as there is generally better knowledge of species distributions for birds and mammals. The success of these taxa as indicators in other studies has varied (e.g., Howard et al. 1998; Reyers et al. 2000; Lawler et al. 2003; Warman et al. 2004a), which is likely an outcome of the scales of the analyses, methods used to measure indicator performance, the regions where the studies occurred, and potentially data quality. Since the data used in our analyses are based on range maps published on or before 1999, the comparisons of the relative surrogacy value of taxonomic groups will need to be reassessed as newer and more refined data become available. However, it is likely, even with better data that both birds and mammals will still poorly represent species at risk within British Columbia given that many of these species are found in more northerly latitudes than COSEWIC-listed species. Therefore, unless species at risk are specifically included in the process of identifying priority sites, neither of these two taxonomic groups should be used as indicators for biodiversity as a whole within British Columbia. Birds and mammals, however, may provide relatively useful surrogates for individual groups of species, such as SOC birds (Table 2). These types of analyses could help refine priorities for conservation programs in British Columbia, such as Partners in Flight. Individual species of SOC birds that are not adequately represented by sites for other taxonomic groups could be given higher priorities than those that are represented by surrogate taxa, for instance, when the surrogate taxa are priorities for another conservation organization. Further refinement could be based on identifying the species that are also not well protected in British Columbia (Table 3). In this regard, different conservation programs could work together towards a common goal using a complementarity approach to focus their efforts on species that will not be incidentally included by other conservation efforts. Since there are limited resources available for conservation, this strategy needs to be given full consideration for conserving biodiversity in British Columbia. Our complementarity analyses prioritized sites (hexagons) so that they had the greatest positive cumulative impact for further research and management of biological diversity. However, refinements are needed to address issues of data quality, viable populations, and reserve design. Selecting only one geographic representation of each species, as was the case in our study, will not be enough to ensure the persis-
29
tence of most species. To improve the network of protected areas within the province or Canada more broadly, comprehensive criteria need to be developed for determining priority sites for further conservation action (Pressey et al. 1993). Examples of such sites might be areas supporting a high diversity of species, migratory species, representative species, or unique species (Biodiversity Convention Office 1995) that occur outside current protected areas. Analyses could be more instructive if species adequately represented in protected areas were disregarded in the selection procedure (cf. Kiester et al. 1996); remaining species would then be used to identify additional sets of locations required to complete the network of conservation areas. Once the criteria are identified, the methodology used in this study could be applied at both regional and national scales to locate areas for future conservation activity within British Columbia or elsewhere in Canada.
Acknowledgements This work was inspired by the efforts of the Biodiversity Research Consortium. We thank Lisa Venier for providing the digital range maps for birds. This work was funded by the National Wildlife Research Centre of the Canadian Wildlife Service, and, in part, by the US Environmental Protection Agency (EPA). It has been subjected to the US EPA’s peer and administrative review and approved for publication. Approval does not signify that the contents reflect the views of the US EPA, nor does mention of trade names or commercial products constitute endorsement or recommendation for use. The views are solely those of the authors.
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