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. 2009 Aug 27;4(8):e6807.
doi: 10.1371/journal.pone.0006807.

Integrating economic costs and biological traits into global conservation priorities for carnivores

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Integrating economic costs and biological traits into global conservation priorities for carnivores

Rafael Dias Loyola et al. PLoS One. .

Abstract

Background: Prioritization schemes usually highlight species-rich areas, where many species are at imminent risk of extinction. To be ecologically relevant these schemes should also include species biological traits into area-setting methods. Furthermore, in a world of limited funds for conservation, conservation action is constrained by land acquisition costs. Hence, including economic costs into conservation priorities can substantially improve their conservation cost-effectiveness.

Methodology/principal findings: We examined four global conservation scenarios for carnivores based on the joint mapping of economic costs and species biological traits. These scenarios identify the most cost-effective priority sets of ecoregions, indicating best investment opportunities for safeguarding every carnivore species, and also establish priority sets that can maximize species representation in areas harboring highly vulnerable species. We compared these results with a scenario that minimizes the total number of ecoregions required for conserving all species, irrespective of other factors. We found that cost-effective conservation investments should focus on 41 ecoregions highlighted in the scenario that consider simultaneously both ecoregion vulnerability and economic costs of land acquisition. Ecoregions included in priority sets under these criteria should yield best returns of investments since they harbor species with high extinction risk and have lower mean land cost.

Conclusions/significance: Our study highlights ecoregions of particular importance for the conservation of the world's carnivores defining global conservation priorities in analyses that encompass socioeconomic and life-history factors. We consider the identification of a comprehensive priority-set of areas as a first step towards an in-situ biodiversity maintenance strategy.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Global pattern of carnivore species richness.
Figure 2
Figure 2. Irreplaceability patterns in the four different conservation planning scenarios.
Spatial patterns of irreplaceability in the four different conservation planning scenarios: minimum ecoregion (A), cost-effective (B), highly vulnerable (C), and a combined scenario (D) that considered both species vulnerability (estimated from their biological traits) and economic costs. Irreplaceability values are the frequency of ecoregions in 100 optimal solutions for the entire 236 species of carnivores found in 661 ecoregions of the world. Values range from yellow (low) to red (high); countries in grey have no native carnivores.
Figure 3
Figure 3. Key ecoregion sets for representing the World's carnivores in the four different conservation planning scenarios.
Minimum sets of ecoregions for representation of the World's carnivores in the four different conservation planning scenarios: minimum ecoregion (A), cost-effective (B), highly vulnerable (C), and a combined scenario (D) considering both species vulnerability (estimated from their biological traits) and economic costs.
Figure 4
Figure 4. General randomization procedure used to generate vulnerability costs based on species biological traits.
This was done this way: for each ecoregion we calculated the mean value of a particular biological trait (e.g. body size) based on the species occurring there – see the pattern of species richness on the upper part of the figure. Then, we resampled without replacement the same number of species found in the ecoregion from the species pool in order to calculate an expected mean value for each biological trait included in this study. This was done 1000 times, and the expected distributions of trait values were compared with those actually observed within each ecoregion. We were then able to evaluate if a given ecoregion had trait values higher or lower then we would expect if species were able to occupy all the geographical space. These values were submitted to a statistical z transformation in order to be compared and analyzed together.

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