Improving recovery planning for threatened species through Bayesian belief networks

Abstract

Threatened species management is a priority in global conservation. Despite many international and national initiatives, this strategy faces challenges posed by a wide range of institutional and organizational factors that influence planning and effective implementation. Empirical research of this issue is scarce given the complexity of addressing management issues. Systems analysis and participatory modeling were applied in this study to construct a conceptualization of a management system in the context of Australian governmental programs. This allowed examination of the structure, key elements and dynamics in order to address two research questions: a) which management factors have most influence on implementation of recovery planning? and b) what modifications could be made to improve recovery planning effectiveness? The methods employed comprised stakeholder interviews, expert workshops and qualitative and quantitative analyses to estimate management performance and effectiveness. The management system model was constructed using a Bayesian belief network to assess the most influential factors: a) coordination among federal, state and territory agencies, b) inconsistency of strategies and programs across jurisdictions, c) management of threatened species on private land, d) incorporation of science into recovery planning, e) prioritization schemes of conservation action and f) funding for plan implementation. Recovery planning effectiveness could be improved by establishing mandatory monitoring and review reports, creating a national forum on threatened species, designing an appropriate insurance regime for volunteers and establishing a national management information system.