Unveiling European Biocapacity Trajectories: A Temporal Clustering Analysis Using Dynamic Time Warping

Conventional cross-sectional analyses of biocapacity fail to capture the temporal dynamics and historical pathways that define a nation’s environmental profile, limiting our understanding of the drivers behind sustainability transitions. To address this gap, this study employs a novel methodological framework that combines Dynamic Time Warping with partitional clustering to analyze per capita biocapacity trajectories across 44 European countries from 1970 to 2022. This approach allows for the grouping of countries based on the shape and dynamics of their historical trends, rather than on static snapshots. Our analysis reveals four distinct and statistically significant clusters: (1) Low-Stable (e.g., Germany, the UK, and Italy; characterized by structural constraints and high import dependency), (2) Very High (Finland and Sweden; driven by vast productive forest ecosystems), (3) Medium-Growing (e.g., Austria, Czechia, and Romania; showing a positive trend linked to post-socialist land-use changes and EU integration), and (4) High-Volatile (e.g., Norway, Estonia, and Russia; featuring abundant yet variable resources tied to extractive economies). The findings demonstrate that institutional and historical factors—such as economic transition and policy integration can influence biocapacity trajectories as significantly as geographical endowments. This study provides a new, dynamic framework for comparative sustainability science and offers a robust basis for designing differentiated environmental policies tailored to each cluster’s unique socio-ecological context.