In the context of increasingly frequent extreme weather events and escalating geopolitical conflicts, the timber supply chain is confronted with growing systemic risks. This study develops a comprehensive resilience evaluation framework for timber supply chains across five dimensions: resource production base, supply and distribution capacity, risk resistance capability, economic environment support, and industrial organization efficiency. This resilience indicator aims to quantify the supply chain system's ability to maintain core functions, absorb shocks, and recover rapidly when facing external disturbances. This study evaluates the dynamic evolution and regional disparities of China's timber supply chain resilience between 2013 and 2022, through constructing a comprehensive evaluation system and applying spatial analysis methods. The results reveal that national resilience exhibits three discernible cycles of growth and decline, driven alternately by policy adjustments and external shocks, while multidimensional coordination efficiency shows a marked decline. A four-tier gradient structure emerged—Eastern China leading, Northeast China declining, Central China stabilizing, and Western China lagging—where interprovincial interactions further reinforced regional disparities. Spatial clustering produced distinct patterns: “East-hot, West-cold; coastal-strong, inland-weak.” This study offers a scientific basis for regional collaborative governance and differentiated policy design in timber supply chains, thereby contributing to the optimization of China's national timber security system. • Developed a five-dimensional framework for timber supply chain resilience. • Applied CRITIC-EWM, coupling, Gini, and spatial autocorrelation models. • Identified three cycles of growth and decline in the resilience of China's timber supply chain from 2013 to 2022. • Revealed an East–West gradient and intensifying regional disparities. • Spatial correlation derives from cross-regional interactions, whose shaping extent is defined by super-variable density.
Ma et al. (Sat,) studied this question.