Environmental policies that impose restrictions within one location may be undermined or reinforced by ‘spillover effects,’ the movement of actors, processes, or knowledge to other locations. Such spillovers are an important consideration in the design of interventions seeking to reduce commodity driven deforestation. In these settings, global markets and mobile actors can move deforestation and conservation behaviors over large distances, complicating efforts to measure and manage spillovers. Here we quantify forest loss and conservation spillovers from the Roundtable on Sustainable Palm Oil (RSPO) certification system in Indonesian Borneo (Kalimantan). We examine whether spillovers from certification are transmitted through corporate groups (i.e. to non-certified, RSPO member-held plantations) or local agricultural markets (i.e. to lands near certified mills). We find that, from 2009 to 2016, spillovers from RSPO certification reduced deforestation within Indonesia’s forest estate, but increased deforestation in areas zoned for agricultural use. The private RSPO certification system has complemented public conservation by aligning de facto land cover with central government land zoning policy. Despite these benefits, aggregate avoided deforestation attributed to direct and spillover effects was statistically and substantively insignificant when compared to the total deforestation occurring inside all of Kalimantan’s oil palm concessions. While certification has reduced illegal deforestation, stronger sector-wide action appears necessary to ensure that oil palm production is no longer a driver of forest loss.

A growing number of companies have announced zero-deforestation commitments (ZDCs) to eliminate commodities produced at the expense of forests from their supply chains. Translating these aspirational goals into forest conservation requires forest mapping and monitoring (M&M) systems that are technically adequate and therefore credible, salient so that they address the needs of decision makers, legitimate in that they are fair and unbiased, and scalable over space and time. We identify 12 attributes of M&M that contribute to these goals and assess how two prominent ZDC programs, the Amazon Soy Moratorium and the High Carbon Stock Approach, integrate these attributes into their M&M systems. These programs prioritize different attributes, highlighting fundamental trade-offs in M&M design. Rather than prescribe a one-size-fits-all solution, we provide policymakers and practitioners with guidance on the design of ZDC M&M systems that fit their specific use case and that may contribute to more effective implementation of ZDCs.