Balancing ecological benefits and feasibility in large-scale restoration planning: A multi-objective optimization decision-support framework

Large-scale ecosystem restoration requires spatial planning tools that identify where limited resources are most likely to deliver durable ecological benefits. Yet ecological feasibility is often treated as an exclusion filter or screening criterion; here, we optimize it alongside biodiversity and other ecological criteria. We developed a multi-objective optimization decision-support framework that integrates ecological feasibility with extinction risk reduction, carbon stock priority, and riparian restoration priority. The framework is grounded in systematic conservation planning and formulated as a mixed-integer linear programming model. Single-objective optimizations define benchmark performance for each criterion, and normalized goal programming identifies compromise portfolios under fixed restoration budget and land suitability constraints. Ecological feasibility is represented as a spatial indicator of relative favorability for restoration persistence under recurrent pressures, based on recurrent fire exposure, anthropogenic pressure, and invasive species richness. Applied to continental Chile at 1 km2 resolution (812,910 planning units), including ecological feasibility as an optimization objective resulted in a 16.52% spatial reallocation of the feasibility-excluded portfolio, with an equivalent proportion entering the feasibility-inclusive portfolio, under an illustrative 30% national restoration planning scenario. This reallocation increased feasibility performance by 11.07 percentage points and extinction risk reduction by 1.20 percentage points, with moderate reductions in carbon stock priority (-4.17) and riparian restoration priority (-2.47). Selection frequency diagnostics showed that compromise solutions were anchored in a shared backbone of multipurpose areas, complemented by specialized units that resolved local trade-offs. The framework provides a transparent and adaptable basis for balancing ecological value with favorability for restoration persistence in spatial prioritization.