Achieving global targets for forest restoration will require cost‐effective strategies to return agricultural land to forest, while minimizing implementation costs and negative outcomes for agricultural production. We present a landscape approach for optimizing the cost‐effectiveness of large‐scale forest restoration. Across three different landscapes within Brazil's Atlantic Forest biodiversity hotspot, we modelled landscape scenarios based on spatially explicit data on the probability of natural regeneration, restoration costs, land opportunity costs, and forest restoration outcomes for increasing carbon stocking and landscape connectivity. We compare benefits of our cost‐reduction approach to the legally mandated riparian restoration and randomly distributed approaches. Compared with riparian prioritization and considering both implementation and opportunity costs, our cost‐reduction scenario produced the greatest savings (20.9%) in mechanized agricultural landscapes. When only considering implementation costs, our cost‐reduction scenario led to the highest savings (38.4%) in the landscape with highest forest cover where natural regeneration potential is highest and enables cost‐effective carbon stocking and connectivity. Synthesis and applications. We present a guide for forest restoration planning that maximizes specific outcomes with minimal costs and reduction of agricultural production. Furthermore, we show how policies could encourage prioritization of low‐cost restoration via natural regeneration, increasing cost‐effectiveness. While our study focuses on Brazil's Atlantic Forest, the approach can be parameterized for other regions.

Weak control and monitoring of logging permits put the most commercially valuable Amazonian tree species at risk in Brazil.

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