Setting Priorities Among Areas

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Conservation spending is not nearly enough to maintain even the current inadequate network of reserves and protected areas (James et al., 2001). The identification and prioritization of global conservation networks are a major focus of conservation dollars (Halpern et al., 2006). However, rankings inherently depend on the currency used to evaluate regions. A simple demonstration can be provided by ranking ecoregions, in this case by applying a greedy complementarity algorithm, to maximize the capture of seven possible currencies for mammalian conserva tion: species richness; total numbers of species extinctions predicted in the next 100 years from current Red List status [using the probabilities of extinction in Redding and Mooers (2006)]; two measures combining evolutionary uniqueness and present extinction risk [EDGE (Isaac et al., 2007) and ELEH (Redding and Mooers, 2006), both summed across species in the ecoregion]; evolutionary dynamism (indexed as the sum of the reciprocal of the terminal branch lengths of species in the ecoregion); evolutionary history (estimated as the total branch length in the phylogeny of the ecoregion's species, adjusted for polytomies as described above); and total latent risk (Cardillo et al., 2006). Species-rich areas are likely to sum to higher values and, hence, rank highly across all currencies. Nonetheless, Table 14.1 shows that rank order differs considerably even for similar measures designed to optimize the same currency (e.g., EDGE and ELEH). The biggest difference is between latent risk and numbers of extinctions. This is perhaps unsurprising, because latent risk gives high weights to species that are less threatened (although not all species were weighted for latent risk, weakening the comparison). A greedy algorithm makes choices based on maximizing the immediate gain in currency at each step and so may give globally suboptimal complementarity networks (Pressey et al., 1996). In addition, ecoregions are, in any case, larger than most current conservation-management units (Grenyer et al., 2006). Our aim here is simply to show that surrogacy among currencies may be low. Furthermore, other more subjective or hard-to-quantify criteria might also be considered important—for example, the ecological function of a species or lineage, its cultural significance, or its charismatic appeal to humans (Avise, 2005)—further impeding comparisons between areas with similar numbers of species.

Even if a currency can be agreed upon, a reserve network optimized for one clade is likely to be suboptimal for another (Grenyer et al., 2006). It is often tempting to use a single group as a surrogate for biodiversity

TABLE 14.1 Numbers of Ecoregions Jointly Ranked in the Top 50 (of a Total of 791) by

Each Pair of Currencies, According to Greedy Complementarity Searches

TABLE 14.1 Numbers of Ecoregions Jointly Ranked in the Top 50 (of a Total of 791) by

Each Pair of Currencies, According to Greedy Complementarity Searches

Richness

EDGE

ELEH

Extinctions

Diversification

Latent Risk

Evolutionary History

Richness 50

41

22

21

34

15

36

EDGE

50

26

22

33

17

39

ELEH

50

34

18

10

26

Extinctions

50

20

9

21

Diversification

50

16

30

Latent risk

50

16

Evolutionary

50

history

278 / T. Jonathan Davies et al.

as a whole, but other clades are likely to have very different—and equally complex—patterns of diversity and extinction risk. The lack of strong surrogacy among groups introduces extra uncertainty into the measured biodiversity value of the regions being considered. In addition, we have focused on conservation benefits rather than costs, but costs vary spatially by several orders of magnitude (Balmford et al., 2003a; Halpern et al., 2006). Cost-benefit models can suggest very different priorities from allocations based solely on perceived biodiversity value (Possingham et al., 2002). So, if we assume that rational decision making must consider both benefits and costs, perhaps the most sensible investment would be in intact but susceptible regions (Balmford et al., 2003a; Cardillo et al., 2006). Public health-care systems may provide a useful analogy: A balanced health-care strategy includes money for preventative medicine as well as for hospital wards and life support.

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