• MACCs can guide peatland restoration if key challenges are addressed. • MACCs should focus on peatland condition clusters, not single measures. • Consistent assumptions and monitoring improve cost estimates. • Transparent data strengthens abatement reliability and comparability. • Scenario modelling captures uncertainty and wider co-benefits. As countries strive to meet climatic targets, halting peatland degradation is coming to the foreground as a way of reducing emissions. However, restoring these valuable ecosystems entails complex interventions and substantial costs, requiring an understanding of both emissions and cost dynamics. Marginal abatement cost curves (MACCs) offer a framework to assess the cost-effectiveness of GHG mitigation options and could inform restoration planning by identifying the most efficient pathways for halting degradation. Yet the unique characteristics of peatlands and the very nature of long-term land use change involved pose challenges for their application. In this paper, we explore these challenges and suggest ways in which they may be addressed. The high spatial variability of degradation and restoration responses limits generalisation across sites, suggesting that bottom-up MACCs could be built around clusters of peatlands with similar condition and restoration trajectories rather than individual measures. Further complexity arises from uncertain GHG flux dynamics, trade-offs, and from wide variation in restoration costs. These uncertainties highlight the need to account for variable timeframes of carbon accumulation, the duration of monitoring required to verify long-term benefits, and the risk of future emission reversals. Moreover, restoration delivers multiple non-GHG benefits, calling for multidimensional approaches that complement cost-effectiveness analysis. Ultimately, MACCs should be viewed as iterative decision-support tools that evolve with data, practice, and policy learning.
Urban et al. (Sun,) studied this question.