Structured Counterfactual Selection in Conservation Impact Evaluations

Counterfactuals fundamentally shape what impact evaluations estimate, yet documentation of how they are chosen is rare in conservation. We present a practical framework to make counterfactual choice systematic and transparent. First, we identify common evaluation goals and map these to four broad counterfactual types - no-intervention, program-level variation, attribute-level variation, and alternative implementation contexts. Second, we propose a four-step, iterative process for selecting counterfactuals that foregrounds decision context, conceptual counterfactuals, feasibility constraints (programme feasibility, ethical, observability of outcomes), and the final choice with limitations. We offer a concise minimum reporting set (the “counterfactual reporting standards” or CREST) to standardize documentation and illustrate the approach with a worked example comparing MPA expansion versus enhanced enforcement. Adopting structured counterfactual selection will increase the policy relevance and comparability of conservation evaluations, reduce misinterpretation of effect sizes across studies, and strengthen meta-analysis. We call on authors, reviewers, and journals to require transparent counterfactual reporting to accelerate accumulation of usable evidence and improve decision-making globally also.