Soil organic carbon projections and climate adaptation strategies across Pacific Rim agro-ecosystems

Abstract

In Pacific Rim regions highly exposed to climate variability, accurate projections of soil organic carbon (SOC) are critical for future effective land management and climate adaptation strategies. This study integrated digital soil mapping with CMIP6-based climate correlative spatial modelling to estimate the spatiotemporal distribution of SOC stocks in subtropical (Zhuoshui River) and tropical (Laonong River) watersheds in Taiwan. We collected 901 soil samples and data on 18 environmental covariates and modeled SOC stocks at a 20 m resolution through the Cubist and random forest algorithms, which were also combined with regression kriging. The Cubist-based kriging model was discovered to achieve the highest performance in SOC stock prediction. Mountainous areas were found to contain >80 % of SOC stocks, and tropical zones were discovered to store substantially less carbon than subtropical zones. The space-for-time estimates derived from future climate analogues indicated considerable spatial heterogeneity in potential steady-state SOC conditions. Under SSP1-2.6, climatic analogues associated with cooler and drier conditions corresponded to lower SOC stocks - up to 20.9 % lower than baseline - particularly in uplands, whereas SSP2-4.5 analogues were associated with SOC states that were 7.9 % higher, especially in mountainous regions. These contrasts reflect spatial associations observed in the contemporary landscape rather than mechanistic predictions of erosion, productivity, or carbon-cycle responses. Partial least squares path modeling revealed a strong climate-topography interaction and explicitly quantified their contributions to SOC stocks, dominated by topography and followed by prolonged dry spells (CDD). This interaction is more pronounced in uplands than in mountainous areas, where topography mitigates temperature extremes and their effects on SOC retention. Extended CDD may decrease organic inputs by reducing vegetation growth and soil moisture, thereby enhancing carbon losses. Examining the interactions between climatic extremes, landscape types, and SOC stocks is essential for enhancing soil resilience and ensuring stable SOC stocks in the future.