Conservation data infrastructures: from carbon accounting to multiple biodiversity and social measures.
Abstract
Environmental big data and analytical models are increasingly informing conservation efforts to address global climate and biodiversity crises. Yet, the growing reliance on data-driven approaches raises concerns regarding biases, uncertainties, and injustices in environmental decision-making processes. This article presents 'conservation data infrastructures' as socio-technical processes of conceiving, producing, and distributing conservation data that affect multifaceted decisions and practices. Drawing on major carbon conservation programs in Australia and Brazil, we assess how data-driven investment planning and project assessments set what is valued, how it is measured, and whose interests are accounted for. Both case studies reveal how technological innovations expand carbon accounting methods by integrating ecological and social data with advanced analytical models to encompass a wide range of place-based impacts. However, data-driven solutions alone may not lead to transformative changes that fully address existing disparities in environmental priorities and benefit distribution across scales. We conclude that the proposed notion of data infrastructures not only reveals socio-technical limitations but also elevates multiple perspectives and local realities to reimagine and rework conservation measures.