Nature-Based Solutions for Climate Mitigation, Resilience, and Environmental Management: A Review of Algorithmic and Equity-Focused Prioritization under Uncertainty

Nature-based solutions (NbS) leverage ecological processes to address climate change while providing biodiversity conservation and human well-being benefits. This review synthesizes the conceptual foundations of NbS, evaluates their climate mitigation and resilience potential, and examines governance, equity, and research priorities for operationalization at scale. Evidence for carbon sequestration across forests, wetlands, peatlands, mangroves, and soils highlights NbS as cost-effective contributors to near-term mitigation with co-benefits including habitat restoration, water regulation, disaster risk reduction, urban heat mitigation, and livelihood support. Key challenges such as scalability, monitoring gaps, policy misalignments, and risks from single-metric prioritization are identified. Decision-support methods including multi-criteria analysis, GIS-based spatial optimization, multi-objective evolutionary algorithms, and machine learning enable scenario simulation and tradeoff quantification among carbon, biodiversity, and adaptation outcomes. Integrating uncertainty through ensemble analysis, sensitivity testing, and robust decision-making is crucial for risk-aware planning. Equity and justice considerations emphasize inclusive governance, indigenous stewardship, free prior informed consent, and targeted finance mechanisms. The review concludes by proposing a research and practice roadmap that promotes algorithmic fairness, co-optimization of social and ecological objectives, sustainable finance innovation, and transdisciplinary collaboration to ensure NbS deliver effective, equitable, and resilient outcomes.