Integrating high-resolution data and species-level traits for enhanced ecosystem projections using a dynamic...

Accurate quantification of carbon dynamics is critical for developing effective climate mitigation strategies. In this study, we employed the CARAIB dynamic vegetation model (DVM) to analyze carbon fluxes and stocks (biomass and total soil carbon) in Wallonia, Belgium (1980-2070), integrating species-level traits, high-resolution land use/land cover (LULC) data, climate data, and type-1 fuzzy logic for uncertainty quantification. We provide insights into ecosystem resilience and carbon sequestration under Representative Concentration Pathways (RCPs) 2.6 and 8.5. Historical results (1980-2020) demonstrated strong model performance, with gross primary production (GPP) validation achieving R² > 0.85 against MODIS and GOSIF datasets, and aboveground biomass correlating well with GEDI (R² = 0.77) and ESA-CCI (R² = 0.91) datasets. Grasslands emerged as critical carbon sinks, exhibiting the highest mean GPP (2480 g C m^-2 yr^-1), surpassing forests due to rapid growth and belowground carbon storage. Future projections (2021-2070) identified afforestation as a robust mitigation strategy, increasing forest GPP by 18% and total biomass by 60-110 Mt C under RCP 8.5. Under RCP 2.6, total biomass was more stable due to the milder emissions trajectory, emphasizing its potential for long-term ecosystem resilience. Interestingly, total soil carbon showed similar levels across both RCPs, indicating belowground carbon resilience despite emissions differences. Sensitivity analyses of LULC scenarios highlighted grassland resilience, with grasslands sustaining a high GPP (2604-2728 g C m^-2 yr^-1) and contributing significantly to soil carbon storage, while deforestation caused substantial carbon losses. These findings underscore the need for nuanced land management, integrating afforestation and grassland conservation, to enhance resilience and sustainable carbon sequestration under climate change.