Assessing diverse evidence to improve conservation decision-making

Alec Philip Christie, William Morgan, Nick Salafsky, Thomas White, Robyn Irvine, Nicolas Boenisch, Rafael Morais Chiaravalloti, Kate Kincaid, Ali Mohammed Rezaie and Hiromi Yamashita

No ujk6n, OSF Preprints from Center for Open Science

Abstract: Meeting the urgent need to protect and restore ecosystems requires effective decision-making through wisely considering a range of evidence. However, weighing and assessing evidence to make complex decisions is challenging, particularly when evidence is of diverse types, subjects, and sources, and varies greatly in its quality and relevance. To tackle these challenges, we present the Balance Evidence Assessment Method (BEAM), an intuitive way to weigh and assess the evidence relating to the core assumptions underpinning the planning and implementation of conservation projects, strategies, and actions. Our method directly tackles the question of how to bring together diverse evidence whilst assessing its relevance, reliability, and strength of support for a given assumption, which can be mapped, for example to a Theory of Change. We consider how simple principles and safeguards in applying this method could help to respectfully, and equitably, include more local forms of knowledge when assessing assumptions, such as by ensuring diverse groups of individuals contribute and assess evidence. The method can be flexibly applied within existing decision-making tools and frameworks whenever assumptions (or reframed claims and hypotheses) are made, which could greatly facilitate and improve the weighing of diverse evidence to make decisions in a range of situations.

Date: 2023-06-22
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:ujk6n

DOI: 10.31219/osf.io/ujk6n

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