Manuscript Dataset - A landscape approach for optimizing the cost-effectiveness of large-scale forest restoration

<p>This is a complete dataset for achieving results of the manuscript "<strong>A landscape approach for optimizing the cost-effectiveness of large-scale forest restoration</strong>". </p> <p> </p> <p><strong>Abstract: </strong></p> <ol> <li>Achieving global targets for forest restoration will require cost-effective strategies to replace agricultural land with forest, while minimizing implementation costs and negative outcomes for agricultural production.</li> <li>Here, we present a landscape approach for optimizing the cost-effectiveness of large-scale forest restoration. Across 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<em>.</em> We compare benefits of our cost-reduction approach to the often-targeted riparian restoration and randomly distributed approaches.</li> <li>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.</li> <li>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.</li> <li><em>Synthesis and applications.</em> Our approach can be parameterized for other regions, to guide forest restoration planning and maximize specific outcomes with minimal costs and reduction of agricultural production.</li>