Making Robust Policy Decisions Using Global Biodiversity Indicators

• DOI: 10.1371/journal.pone.0041128
• Publication Date: 2012-07-19T10:25:54Z
• Authors: Emily Nicholson; Ben Collen; Alberto Barausse; Julia L. Blanchard; Brendan T. Costelloe; Kathryn M. E. Sul...; Fiona M. Underwood; Robert W. Burn; Steffen Fritz; Julia P. G. Jones; Louise McRae; Hugh P. Possingham; E. J. Milner-Gulland
• Keywords: 0106 biological sciences; 570; Conservation of Natural Resources; Time Factors; 1300 Biochemistry; 330; International Cooperation; Science; Genetics and Molecular Biology; Public Policy; Environment; 01 natural sciences; 1100 Agricultural and Biological Sciences; 11. Sustainability; Animals; Humans; Biomass; 14. Life underwater; Ecosystem; Research; Q; R; Biodiversity; Models, Theoretical; 15. Life on land; 001; 300; Multidisciplinary Sciences; 13. Climate action; Africa; Science & Technology - Other Topics; Medicine; Research Article

In order to influence global policy effectively, conservation scientists need to be able to provide robust predictions of the impact of alternative policies on biodiversity and measure progress towards goals using reliable indicators. We present a framework for using biodiversity indicators predictively to inform policy choices at a global level. The approach is illustrated with two case studies in which we project forwards the impacts of feasible policies on trends in biodiversity and in relevant indicators. The policies are based on targets agreed at the Convention on Biological Diversity (CBD) meeting in Nagoya in October 2010. The first case study compares protected area policies for African mammals, assessed using the Red List Index; the second example uses the Living Planet Index to assess the impact of a complete halt, versus a reduction, in bottom trawling. In the protected areas example, we find that the indicator can aid in decision-making because it is able to differentiate between the impacts of the different policies. In the bottom trawling example, the indicator exhibits some counter-intuitive behaviour, due to over-representation of some taxonomic and functional groups in the indicator, and contrasting impacts of the policies on different groups caused by trophic interactions. Our results support the need for further research on how to use predictive models and indicators to credibly track trends and inform policy. To be useful and relevant, scientists must make testable predictions about the impact of global policy on biodiversity to ensure that targets such as those set at Nagoya catalyse effective and measurable change.