A decision support framework for climate-oriented coastal wetland restoration through process-based ecosystem modeling and optimization

Wetland restoration is increasingly recognized as a nature-based climate solution, but effective planning requires balancing nonlinear ecological responses with economic and implementation constraints. We propose a conceptual and computational framework for climate-oriented coastal wetland restoration that embeds processbased ecosystem modeling within restoration optimization. Restoration strategies are represented as portfolios combining discrete choices among restoration measures with continuous decisions on implementation intensity and area allocation. A vertically resolved ecohydrological model simulates soil organic carbon dynamics and decomposition-driven CO2 and CH4 emissions, allowing environmental outcomes to arise from the interaction between restoration decisions and ecosystem processes. These emissions represent decomposition-driven source fluxes and do not constitute a complete net ecosystem greenhouse-gas balance. The optimization is performed using a genetic algorithm with multiple independent runs and provides approximate solutions without a formal guarantee of global optimality. The framework is illustrated through a benchmark analysis and an application to the Ebro Delta. The benchmark shows that alternative objective specifications select distinct interior and corner solutions from the same ecological trade-off. In the Ebro Delta application, imposing a budget constraint reallocates restored area from the deep-rooted vegetation type toward the less expensive shallow-rooted type, while maintaining high vegetation densities and compliance with the methane target, although the CO2 target is exceeded. Global sensitivity analysis identifies the density and area allocation of the deep-rooted vegetation type as the main drivers of restoration performance. The results show that restoration outcomes depend not only on total vegetation cover but also on portfolio composition and implementation intensity. The proposed framework provides a flexible methodology for integrating process-based ecological models into restoration planning under alternative environmental objectives and resource constraints.