Conservation has never lacked ideas. Protected areas, payments for ecosystem services, community management, certification schemes, and public campaigns have all been promoted as solutions to biodiversity loss. What has often been missing is reliable knowledge about how well these interventions work, for whom, and under what conditions. A growing body of recent research argues that answering those questions requires moving beyond counting activities to establishing causal impact — determining whether observed outcomes can truly be attributed to conservation actions. Two recent commentaries underscore this shift. One, published on Mongabay by Oxford researcher Tanya O’Garra, warns that conservation risks spending scarce funds on “well-intentioned but ineffective efforts” without stronger causal evidence. Another, published in Nature, argues that biodiversity policy suffers from an “evidence problem,” with many interventions not grounded in robust research. Together with recent methodological papers, they reflect a field attempting to move from persuasion to proof. From monitoring to impact evaluation Traditional conservation monitoring focuses on trends: forest cover, species abundance, or compliance indicators. These metrics are valuable but insufficient. A forest might remain intact because of protection, or because it lies far from roads, markets, or settlements. Distinguishing between these possibilities requires impact evaluation — assessing changes that can be causally attributed to an intervention. Impact evaluation centers on a deceptively simple question: what would have happened without the intervention? Because this counterfactual world cannot be observed, researchers approximate it using comparison groups or statistical techniques. The aim is to rule out alternative explanations for observed outcomes. The…This article was originally published on Mongabay

From Conservation news via This RSS Feed.