A comparison of taxonomic distinctness versus richness as criteriafor setting conservation priorities for North American birds

Stephen Polasky a,*, Blair Csuti b, Christian A. Vossler c, and S. Mark Meyers d

aDepartment of Applied Economics, University of Minnesota, St. Paul, MN 55108, USAbOregon Zoo, 4001 SW Canyon Road, Portland, OR 97221-2799, USA

cDepartment of Agricultural, Resource and Managerial Economics, Cornell University, Ithaca, NY 14853-7801, USAdDepartment of Geosciences, Oregon State University, Corvallis, OR 97331, USA

Received 4 November 1999; received in revised form 1 April 2000; accepted 5 June 2000

Abstract

In choosing sites for a conservation reserve network, representation of the greatest number of species in the sites selected is a

common objective. This approach implicitly assumes that all species have equal conservation value. An alternative objective is torepresent the greatest genetic diversity in selected sites. This approach gives greater weight to species that are more genetically dis-tinct. Such species tend to contain more unique genetic material, which would be lost if such species became extinct. In this paper,

we calculate a diversity measure for a given set of species based on the branch length of the phylogenetic tree for the set. We usegenetic distances between bird species in 147 genera based on the results of DNA hybridization research. Distribution informationfor bird species in the US comes from the Breeding Bird Survey. We compare resulting conservation reserve networks when the

objective is the number of genera represented versus the diversity of genera represented. We find that the dierent objectives pro-duce notably similar results. # 2000 Elsevier Science Ltd. All rights reserved.

1. Introduction

With certain caveats, the protection of natural areasin conservation reserves is a simple yet eective way toconserve global biological diversity. Because of com-peting demands for natural resources, few jurisdictionsare able to dedicate more than a small fraction of theirtotal area to conservation reserves. The ecient selec-tion of these reserves, is, therefore, a matter of concern.As Margules (1989, p. 10) observed, Techniques formanaging reserve systems to prevent extinctions will notmaintain diversity if the reserve systems being manageddo not contain the full range of species in the firstplace. Pressey (1994) points out that most existingnatural areas were not selected with the intention ofmaximizing the amount of biological diversity repre-sented within them.In recent years, reserve selection algorithms have been

used to choose reserve networks eciently (e.g. Margules

et al., 1988; Nicholls and Margules 1993; Church et al.1996; Csuti et al. 1997; Ando et al., 1998). These exer-cises typically use the objective of representing thegreatest number of species, though some studies take asan objective conserving a given percentage of a landcover type. Several authors (e.g. May, 1990, Vane-Wright et al., 1991; Faith, 1992, 1994; Solow et al.,1993; Weitzman, 1992; Williams and Humphries, 1994)have suggested that the total amount of phylogeneticdiversity represented in a set of species is an additionalcriterion that should be considered when selecting nat-ural areas. Behind this suggestion is the notion thatgenetically distinct species should count more than spe-cies with close genetic neighbors. Losing a species with-out close relatives tends to lead to a greater loss ofgenetic information than losing species with close rela-tives. When the unit of account is genetic material, pre-venting extinction of genetically unique species has ahigher priority than saving a species closely related toother surviving species.While this notion is appealing, the lack of phyloge-

netic distance data for large numbers of species hasimpeded the application of this concept. In this paper,

0006-3207/00/$ - see front matter # 2000 Elsevier Science Ltd. All rights reserved.PI I : S0006-3207(00 )00103-8

Biological Conservation 97 (2001) 99105

www.elsevier.com/locate/biocon

* Corresponding author. Tel.: +1-612-625-9213; fax: +1-612-625-

2729.

E-mail address: spolasky@dept.agecon.umn.edu (S. Polasky).

we take advantage of a large existing phylogenetic dataset compiled by Sibley and Ahlquist (1990) for birdspecies. We combine this data with distributional dataon bird species in the US, from the US Fish and Wild-life Services Breeding Bird Survey, to compare theresults of richness-driven versus phylogenetic diversity-driven conservation reserve site selection.

2. Data and methods

2.1. Distribution of North American birds

In response to widespread concern over the decline ofsongbirds in North America (Price et al., 1995), the USFish and Wildlife Service, with the cooperation of theCanadian Wildlife Service, pioneered a yearly, systematicseries of bird survey routes, which we will refer to here-after as sites, in the United States and Canada known asthe Breeding Bird Survey (BBS) (Robbins et al., 1986).The first survey, in 1966, included only 60 sites. At present,however, there are around 3000 sites surveyed annually.Dr. Raymond J. OConnor and his colleagues at the

University of Maine, Orono compiled BBS data for theyears 19811990 for use in biogeographic analysis(OConnor et al., 1996). The US (excluding Alaska andHawaii) was overlain with a grid of hexagonal cells,each measuring 635 km2 (White et al., 1992). To reduceover-sampling of certain geographic areas, particularlyin the eastern US, only one site per hexagon was chosen.Sites with fewer than 7 years of data were also elimi-nated from the analysis (OConnor et al., 1996), redu-cing the total number of sites to 1223. These dataprovide distributional information for 531 NorthAmerican bird species in 241 genera.

2.2. Phylogenetic distance

The monumental work of Sibley and Ahlquist (1990)provides phylogenetic distances between birds of theworld based on a measure of DNADNA hybridization(T50H values). Sibley and Ahlquist were most con-cerned with higher order phylogeny and taxonomy.They did not report many of the interspecific distanceswithin a genus. In order to secure a larger sample, weelected to use intergeneric data available for 167 generaof North American birds. The data for intergeneric dis-tances were taken from branch lengths of UPGMAphylogenetic trees of birds reported in Sibley and Ahl-quist (1990, pp. 838870). Of these 167 genera, 147 arerepresented in the distributional data set described earlier.Of the 531 species included in the distributional data,70% (n=373) are included in these 147 genera. Notethat by the nature of phylogenetic data, the phyloge-netic distance between any species in one genus to anyspecies in another genus is the same.

For a set of genera, phylogenetic diversity is definedas the branch length of the phylogenetic tree thatincludes only those genera. In a phylogenetic tree,assuming a constant rate of DNA changes for all taxa,the branch length is proportional to the time of the splitfrom a common ancestor. Longer branch lengths corre-spond to greater evolutionary time and, presumably,genetically more unique taxonomic groups. Includingmore genera adds additional branches to the tree. Addingrelatively diverse genera adds relatively long branches tothe tree.For a simple example of calculating phylogenetic

diversity, consider the group of five genera representedin Fig. 1. Phylogenetic diversity for a group of genera iscalculated by adding all the relevant branch lengthsbetween all genera, without double counting. Thediversity measure for the set including genera 1 and 2,D(1, 2), is equal to 2A. The diversity measure for the setincluding genera 1 and 3, D(1, 3), is equal to 2A+2B.For genera 1, 2 and 3, the diversity measure, D(1, 2, 3),is 3A+2B. Adding genera to a set with closely relatedgenera does not add much to the diversity measure.Adding genus 2 to the set with genera 1 and 3 adds onlyA. However, adding genus 2 to a set that includes gen-era 4 and 5 adds A+B+C+D: D(4, 5)=2E; D(2, 4,5)=A+B+C+D+2E.While it is easy to understand the phylogenetic diver-

sity given a phylogenetic tree, it proved easier to have analternative method in writing a computer program tocalculate diversity. An equivalent, though less obvious,way to calculate the diversity measure of a set is as follows.

Fig. 1. Phylogenetic tree for set of five genera.

100 S. Polasky et al. / Biological Conservation 97 (2001) 99105

The phylogenetic diversity of a set is equal to the max-imum distance between any two members of the set,plus half the sum over all other members of the set(excluding the two with the maximum distance) of thedistance between it and its nearest neighbor in the set.Calculation via this method requires only a matrix ofpairwise distances between members of the set ratherthan the phylogenetic tree itself. In Table 1, we repre-sent the information contained in a phylogenetic tree inFig. 1 as a 55 matrix. To calculate D(1, 2, 3) via thismethod, note that the maximum distance is between 3and 1 (or 2), which is 2A+2B. Adding in the nearestneighbor distance between 2 (or 1) and the set consistingof 3 and 1 (or 2) is 2A, half of which is A. Therefore,D(1, 2, 3)=2A+2B+A=3A+2B, as stated above. Werecorded the branch lengths from the phylogenetic tree ofSibley and Ahlquist in a 147147 matrix of the pairwisedistances (taxonomic distinctness) between genera inour sample (available on request from the authors).Because of the nature of the data, there was consider-able redundancy in this matrix. For example, all generain the largest family, Fringillidae, are equidistant fromall genera in all other families of the Passeroidea.

2.3. Prioritization algorithm

In previous work, we compared the eciency andspatial solutions of several dierent reserve selectionalgorithms (Csuti et al., 1997). Optimization algorithmsfrom operations research, usually based on branch-and-bound integer programming techniques, can often findslightly better solutions than iterative heuristic algorithms,also known as greedy algorithms (e.g. Church et al.,1996; Pressey et al., 1996, 1997). However, optimizationalgorithms can present computational diculties (Presseyet al., 1996). In particular, it is dicult to solve optimi-zation algorithms when the objective is to maximize adiversity measure based on the branch lengths of thephylogenetic tree for species represented in the set ofchosen sites. For this reason, we have used a greedyheuristic algorithm to choose reserve sites. The greedyalgorithm we use begins by picking the site with thegreatest diversity value, or greatest number of genera,depending upon the objective. Next, it picks a secondsite that adds the greatest additional diversity (numberof genera) to that already contained in the first site. At

each subsequent step, the algorithm picks the site thatcontributes the greatest increase in the diversity measure(number of genera) of any remaining sites, until themaximum diversity measure (number of genera) isachieved. The general pattern of site selection using agreedy algorithm or an optimization algorithm tends tobe similar (Csuti et al., 1997).

3. Results

In this section, we compare the results using thegreedy algorithm applied to the reserve site selectionproblem, using the BBS distribution data and the Sibleyand Ahlquist (1990) phylogenetic distance data, for thecase when the objective is to maximize the number ofrepresented genera versus the genetic diversity measure.Table 2 shows the results when the objective is to max-imize the genetic diversity measure. It takes 15 sites torepresent all 147 genera using the greedy algorithm tomaximize the increase in the genetic diversity measure ateach step. Much of the diversity is represented after thefirst few sites are included. The first site represents 58% ofthe diversity present in the 147 genera. Over 90% of thetotal diversity is represented with six sites. The percentageof genera represented is slightly lower: 50% in one siteand 87% in six sites. The diversity accumulation curve,which illustrates the rapid initial accumulation and theslower approach to complete representation, is shown inFig. 2.Table 3 shows the results when the objective is to

maximize the number of genera represented. Not sur-prisingly, selecting sites to maximize the increase in thenumber of genera represented at each step as comparedto selecting sites to maximize the increase in diversity ateach step results in initially faster accumulation of generarepresented but less diversity. It is surprising, however,that it takes more sites, 16 versus 15, to represent allgenera. This result is an artifact of using the greedyalgorithm on this particular data set.Using an algorithm that could find the minimum

number of sites to represent all genera would result in asolution with 15, or possibly fewer, sites in total. Theaccumulation curve when maximizing the increase in thenumber of genera represented at each step is shown in Fig.3. The general pattern is similar to that shown in Fig. 2.

Table 1

55 distance matrix1 2 3 4 5

1 0 2A 2(A+B) 2(A+B+C) 2(A+B+C)

2 2A 0 2(A+B) 2(A+B+C) 2(A+B+C)

3 2(A+B) 2(A+B) 0 2(A+B+C) 2(A+B+C)

4 2(A+B+C) 2(A+B+C) 2(A+B+C) 0 2E

5 2(A+B+C) 2(A+B+C) 2(A+B+C) 2E 0

S. Polasky et al. / Biological Conservation 97 (2001) 99105 101

The spatial pattern of the sites selected by the twoalgorithms is shown in Figs. 4 and 5. It is striking howsimilar the geographic pattern of the selections is usingthe two objectives. The same site was selected first underboth objectives. Overall, 12 sites were chosen under bothobjectives, though not always in the same order. Forexample, the second site selected for maximizing richnesswas selected sixth when maximizing phylogenetic diver-sity. Both solutions display the influence of the principleof complementarity (Pressey et al., 1993). Sites chosentend to sample distant and ecologically divergent regions,presumably with considerably dierent avifaunas. In bothsolutions, sites in close proximity to earlier selectionswere chosen late in the selection process.

While the sites highlighted in Figs. 4 and 5 are indi-cative of high priority sites for US breeding birds, it isimportant to be cautious about using these results inderiving actual conservation strategies. A system ofreserves to conserve avifauna would also need to con-sider migratory stopovers and wintering areas (some ofwhich lie outside the US). The results are based on thecurrent presence of species at sites but do not take intoaccount the quality of habitat at various sites and whe-ther viable populations can be maintained at a givensite. These results also do not say anything aboutpriority sites for other taxonomic groups.

4. Discussion

The results of choosing reserves on the basis of adiversity measure based on phylogenetic diversity versussimple richness are remarkably similar. The set of siteschosen under the two objectives largely overlaps. Thepattern of accumulation under the two objectives is alsoquite similar. These results suggest that the more com-plicated objective of maximizing phylogenetic diversityrepresented in a reserve network is reasonably wellaccomplished simply by representing the maximumrichness in the network.Although these results arise from a data set using a

specific taxonomic group (birds) in a specific geographicarea (the US, excluding Alaska and Hawaii), there isreason to believe that the similarity of results under thetwo dierent objectives is more general. Following fromthe definitions of the two measures, richness and phylo-genetic diversity at a site (or collection of sites) should

Table 2

Accumulation of diversity and genera when prioritizing for phyloge-

netic distance

Site number Diversity measure Number of genera

1 352.4 74

2 433.7 93

3 471.8 102

4 503.8 113

5 527.3 118

6 548.2 128

7 562.3 133

8 572.3 137

9 579.4 139

10 584.8 141

11 589.7 143

12 594.3 144

13 597.3 145

14 600.2 146

15 602.2 147

Fig. 2. Accumulation curve when prioritizing for phylogenetic distance.

102 S. Polasky et al. / Biological Conservation 97 (2001) 99105

be positively correlated. As more taxa are progressivelyadded both richness and phylogenetic diversity willincrease. Measures that do not use branch length butare based on the number of branching nodes, such asused by Vane-Wright et al. (1991), also increase as taxaare added and should be positively correlated to rich-ness as well. The results of Nee and May (1997) showthat increasing the number of species conserved increa-ses phylogenetic diversity conserved (see especially Fig.2, Nee and May 1997, p. 693). Because sites that havemore genera tend to have greater phylogenetic diversity,the same set of sites would tend to be selected regardlessof which objective is used. For this not to be the case,

those sites with relatively many genera must also haverelatively closely related genera so that the greaternumber of branches represented by the greater numberof genera still translates into small total branch length.For example, Hacker et al. (1998) report that Mada-gascar scores well relative to continental sites on taxonrichness for African primates but scores poorly oncharacter diversity, which is based on the number ofbranching nodes in an evolutionary tree, because onlylemurs are present. In general, however, both Williamsand Humphries (1996) and Hacker et al. (1998) foundthat taxon richness and character diversity showed asimilar pattern across sites.Looking at the geographic distribution of the sites

selected by either solution shows that a majority of theselected sites were on the coast or near the borders ofthe US with Mexico or Canada. Few sites were selectedfrom the interior. The selection of sites at the peripheryof the study area most likely reflects the presence ofperipheral species at the edge of their range. Two sites inFlorida, two in Texas, and two in Arizona all are likelyto contribute regular records of tropical species (tro-gons, parrots, anhingas) at the northern edge of theirrange. For this reason, it is important to consider theresults of a study of one geographic area, particularlywhen based on political rather than biogeographicboundaries, in the context of studies of other areas.Consideration of conservation eorts in other places(e.g. Canada, Mexico, or the Caribbean) may wellchange conservation priorities in the USWe agree with May (1990), Vane-Wright et al. (1991),

and others that phylogenetic dierence between taxamerits recognition when selecting biological reserves.However, as a practical matter, taxonomic richness may

Table 3

Accumulation of diversity and genera when prioritizing for the num-

ber of genera

Site number Diversity measure Number of genera

1 352.4 74

2 420.8 96

3 462.7 106

4 494.8 116

5 511.9 124

6 535.4 129

7 545.4 133

8 554.3 136

9 561.6 138

10 568.7 140

11 587.0 142

12 589.0 143

13 592.0 144

14 594.7 145

15 599.3 146

16 602.2 147

Fig. 3. Accumulation curve when prioritizing for number of genera.

S. Polasky et al. / Biological Conservation 97 (2001) 99105 103

serve as a good proxy for phylogenetic diversity for thepurpose of choosing reserve sites. Given that data onrichness is both more available and easier to work withthan data on phylogenetic diversity, those that work onsetting conservation priorities need not be defensiveabout maximizing richness as their objective.

Acknowledgements

This research was made possible by a grant for thestudy of Decision Making and Valuation for Environ-mental Policy from the US Environmental ProtectionAgency/National Science Foundation to Woods Hole

Fig. 4. Sites selected when prioritizing for phytogenetic diversity.

Fig. 5. Sites selected when prioritizing for genus richness.

104 S. Polasky et al. / Biological Conservation 97 (2001) 99105

Oceanographic Institutions Center for Marine Policy.Additional funding was provided by the StrategicEnvironmental Research and Development Program tosupport activities of the Biodiversity Research Consortium.We thank Dr. Raymond J. OConnor, Department ofWildlife Ecology, University of Maine, Orono, for pro-viding compiled Breeding Bird Survey data.

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