Assessing Potential Changes in the Distribution of Major Warm–Temperate Tree Species in South Korea Under Climate Change Scenarios
Abstract
Climate change drives shifts in forest vegetation zones, and the major tree species of warm–temperate evergreen broad-leaved forests in South Korea are also expected to undergo changes in their potential distributions under future climate conditions. This study applied a Committee Averaging (CA) ensemble species distribution model to Quercus acuta, Machilus thunbergii, Quercus glauca, and Castanopsis sieboldii to project changes in their potential distributions under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) across two future periods (2050s and 2090s). To compare interspecific differences in response more clearly, we applied a two-tier threshold scheme that distinguished potential habitat (agreement ≥0.6) from highly suitable habitat (>0.8), and we concurrently conducted a Multivariate Environmental Similarity Surface (MESS) analysis to assess predictive uncertainty arising from extrapolation into future climates. The CA ensemble models showed excellent predictive performance (AUC 0.947–0.989; TSS 0.837–0.943). For Q. acuta, M. thunbergii, and Q. glauca, potential habitat expanded consistently across all SSP scenarios, and highly suitable habitat shifted northward into parts of the central and Gangwon regions. In contrast, both the potential habitat and the highly suitable habitat of C. sieboldii contracted under most future scenarios. These results demonstrate that even species belonging to the same warm–temperate evergreen broad-leaved forest community can respond differently to future climate. The two-tier threshold scheme applied in this study was effective not only for assessing whether distributions expand but also for delineating and evaluating climatically stable core habitats. Although our findings need to be interpreted in light of the uncertainty associated with extrapolation into future climates, they can serve as useful baseline data for establishing climate-change-adaptive forest conservation and species-specific management strategies.