To achieve regional and international large-scale restoration goals with minimum costs, several restoration commitments rely on natural regeneration, a passive and inexpensive strategy. However, natural regeneration potential may vary within the landscape, mainly due to its historical context. In this work, we use spatially explicit restoration scenarios to explore how and where, within a given region, multiple restoration commitments could be combined to achieve cost-effectiveness outcomes. Our goal is to facilitate the elaboration of forest restoration plans at the regional level, taking into consideration the costs for active and passive restoration methods. The approach includes (1) a statistical analysis to estimate the natural regeneration potential for a given area based on alternative sets of biophysical, land cover, and/or socioeconomic factors and (2) the use of a land change allocation model to explore the cost-effectiveness of combining multiple restoration commitments in a given area through alternative scenarios. We test our approach in a strategic region in the Brazilian Atlantic Forest Biome, the Paraiba Valley in São Paulo State. Using the available data for 2011, calibrated for 2015, we build alternative scenarios for allocating natural regeneration until 2025. Our models indicate that the natural regeneration potential of the region is actually very low, and the cost-effectiveness outcomes are similar for all scenarios. We believe our approach can be used to support the regional-level decision-making about the implementation of multiple commitments aiming at the same target area. It can also be combined with other approaches for more refined analysis (e.g., optimization models).

为了以最低成本实现区域和国际大规模恢复目标，一些恢复承诺依赖于自然再生，这是一种被动且成本低廉的策略。然而，自然再生潜力可能因景观而异，主要是由于其历史背景。在这项工作中，我们使用空间明确的恢复场景来探索在给定区域内如何以及在何处组合多个恢复承诺以实现成本效益结果。我们的目标是促进区域一级森林恢复计划的制定，同时考虑到主动和被动恢复方法的成本。该方法包括 (1) 统计分析，根据生物物理、土地覆盖、和/或社会经济因素以及 (2) 使用土地变化分配模型来探索通过替代方案在给定区域内结合多种恢复承诺的成本效益。我们在巴西大西洋森林生物群落、圣保罗州帕拉伊巴河谷的战略区域测试我们的方法。使用 2011 年的可用数据，针对 2015 年进行校准，我们构建了用于分配到 2025 年的自然再生的替代方案。我们的模型表明该地区的自然再生潜力实际上非常低，并且所有方案的成本效益结果都相似。我们相信我们的方法可用于支持针对同一目标领域的多项承诺的实施的区域层面决策。