An effective strategy to resolve conservation conflicts on lands outside of nature reserves is to consider the spatial arrangement of agricultural and native vegetation parcels such that the ecological value of the landscape is improved without reducing the amount of land used for agricultural production. Global optimization methods have been used to identify the best spatial arrangement of land parcels for a given project goal, but these methods are not designed to provide pathways to reach the optimum from the initial landscape. Here we describe how local search algorithms can be used to develop land parcel rearrangement pathways to obtain a landscape that sustains greater species richness than the initial landscape without changing the amount of land used for agricultural production. To demonstrate how the local optimization framework can be applied, an ecological setting based on a forest-grassland mosaic ecosystem in Rio Grande do Sul, Brazil was constructed. Plant samples collected from this region were used to construct species area curves. Multiple locally optimal solutions that improved the modeled species richness of the landscape almost to globally optimal levels were identified. To support the results, the algorithm was also applied to a 306,250 ha forest-grassland region of Rio Grande do Sul. The case study results suggested that conservation polices solely based on landowners satisfying a legal reserve percentage on their property should be revised to consider landscape-level connectivity. Providing multiple possible solutions for landscape configurations using local optimization methods may improve managerial flexibility for decision-makers, compared to global optimization approaches providing a single solution. Furthermore, the algorithm details the parcel exchange pathways that are required to reach the optimal land state. We conclude that local and global optimization approaches can be used in combination to improve land use decision-making for conservation, in mosaic ecosystems as well as other terrestrial ecosystems.