An introduction to decision science for conservation

Abstract

Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms: decision science, decision theory, decision analysis, structured decision-making, and decision-support tools. Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems.

From Climate Change to Pandemics: Decision Science Can Help Scientists Have Impact

“…We begin by explaining the fundamentals of decision science, with an overview of structured decision making (Gregory et al, 2012). As decision science methods have been covered in detail elsewhere (e.g., Hemming et al, 2021), we only provide the necessary background to understand our vision. We then describe our vision for decision science and explain why we believe it's important to include an awareness of the broader context of decisions when framing scientific questions.…”

Incorporating management action suitability in conservation plans

“…Our approach provides a framework to assist in formulating management alternatives for conservation planners (and hence contributes to existing planning paradigms, such as dynamic adaptive policy pathways; Haasnoot et al, 2013). Alternate implementation pathways are a cornerstone of structured decision making but developing them can be challenging – especially when cognitive biases, differing value judgements, and/or competing interests are present (Hemming et al, 2022). We suggest that our framework can assist in overcoming such challenges by querying commonly held – and often fallacious – beliefs that an existing or current action remains the only option suitable to meet an objective (i.e.…”

“…The conservation of biodiversity is fraught with complexity and uncertainty (Hemming et al, 2022). To deliver on conservation objectives, decision makers must navigate challenging social and technical contexts while contending with escalating threats (Maxwell et al, 2016).…”

Planning for people and nature: Comparing quality‐of‐life outcomes across environmental systems to inform conservation planning

“…Our teams invested time and resources into this process, but in some ways, these initial indicator rankings and comparison could be considered a rapid prototype (Garrard et al, 2017; Nicolson et al, 2002). Prototyping builds an initial framing of the decision problem and produces the elements of the decision relatively quickly, which can help the group identify aspects of the decision that may warrant addition investments of resources (Garrard et al, 2017; Hemming et al, 2022). Decision emphasis during this first iteration focused on developing a thorough list of alternatives that aligned with quality‐of‐life domains.…”