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Assessing extinction risk in the absence of species-level data: quantitative criteria for terrestrial ecosystems

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Abstract

The conservation of individual plant and animal species has been advanced greatly by the World Conservation Union’s (IUCN) development of objective, repeatable, and transparent criteria for assessing extinction risk, which explicitly separate the process of risk assessment from priority-setting. Here we present an analogous procedure for assessing the extinction risk of terrestrial ecosystems, which may complement traditional species-specific risk assessments, or may provide an alternative when only landscape-level data are available. We developed four quantitative risk criteria, derived primarily from remotely sensed spatial data, information on one of which must be available to permit classification. Using a naming system analogous to the present IUCN species-specific system, our four criteria were: (A) reduction of land cover and continuing threat, (B) rapid rate of land cover change, (C) increased fragmentation, and (D) highly restricted geographical distribution. We applied these criteria to five ecosystems covering a range of spatial and temporal scales, regions of the world, and ecosystem types, and found that Indonesian Borneo’s lowland tropical forests and the Brazilian Atlantic rainforest were Critically Endangered, while South Africa’s grasslands and Brazil’s Mato Grosso were Vulnerable. Furthermore, at a finer grain of analysis, one region of Venezuela’s coastal dry forests (Margarita Island) qualified as Vulnerable, while another (the Guasare River watershed) was Critically Endangered. In northern Venezuela, deciduous forests were classified as Endangered, semi-deciduous forests Vulnerable, and evergreen forests of Least Concern. We conclude that adoption of such a standardized system will facilitate globally comparable, repeatable geographic analyses that clearly separate risk assessment (a fundamentally scientific process), from the definition of conservation priorities, which should take into account additional factors, such as ecological distinctiveness, costs, logistics, likelihood of success, and societal preferences.

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Acknowledgments

We are grateful to the Fulbright Program, Yale School of Forestry and Environmental Studies, Yale’s Tropical Resources Institute, Fondo Nacional de Ciencia, Tecnología e Innovación (FONACIT, Agenda Biodiversidad, Segunda Fase), Fundación Polar, Instituto Venezolano de Investigaciones Científicas (IVIC), and Provita for their support. We also thank Larry Bonneau, Lisa Curran, Eric Dinerstein, Don Faber-Langendoen, Armando Hernández, Georgina Mace, Gary Meffe, Stuart Pimm, Carlos Portillo, David Skelly, Ron Smith, Dana Tomlin, and Jessica Wilkinson, for their valuable suggestions on earlier drafts of this manuscript. Our most sincere gratitude goes to Pablo Lacabana, Carlos Portillo, Fabián Carrasquel, and Alix Amaya for allowing us to use their land cover change analysis of northern central Venezuela. Carlos Portillo’s help was fundamental for assembling Table 4. Provita is a member of the Wildlife Trust Alliance.

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  1. Jennifer K. Balch

    Present address: School of Forestry & Environmental Studies, Yale University, 205 Prospect Street, New Haven, CT, 06511-2186, USA

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  1. Centro de Ecología, Instituto Venezolano de Investigaciones Científicas, Apartado 21827, Caracas, 1020-A, Venezuela

    Jon Paul Rodríguez, Jennifer K. Balch & Kathryn M. Rodríguez-Clark

  2. Provita, Apartado 47552, Caracas, 1041-A, Venezuela

    Jon Paul Rodríguez & Jennifer K. Balch

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  1. Jon Paul Rodríguez
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Correspondence to Jon Paul Rodríguez.

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Jon Paul Rodríguez and Jennifer K. Balch are contributed equally to this work

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Rodríguez, J.P., Balch, J.K. & Rodríguez-Clark, K.M. Assessing extinction risk in the absence of species-level data: quantitative criteria for terrestrial ecosystems. Biodivers Conserv 16, 183–209 (2007). https://doi.org/10.1007/s10531-006-9102-1

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