Data-driven optimisation of national botanical garden systems for ex situ conservation

Plant diversity loss driven by human activities and climate change underscores the urgent need for effective ex situ conservation through botanical gardens. Yet many national botanical garden (NBG) systems remain fragmented due to the lack of objective spatial planning. Here we present a data-driven framework to optimise the size and configuration of NBG systems by integrating species coverage, distinctiveness, and complementarity. As a case study, we combine 49,308 living collection records from 29 botanical gardens with 1.56 million native plant distribution records across China. Similarity-based clustering analysis reveals six geographically coherent groups, and a complementarity ranking maximises taxonomic coverage while minimising avoidable duplication across institutional collections. This analysis prioritises 16 existing gardens and identifies 5 additional regions for new NBGs, together potentially safeguarding 73.2% of China's vascular flora. Our framework improves the efficiency, representativeness, and resilience of ex situ conservation, providing a transferable model for strengthening botanical garden systems in biodiversity-rich countries. • A data-driven framework for optimising national ex situ conservation networks • A prioritisation scheme integrating distinctiveness and complementarity to reduce redundancy • An optimised national botanic garden network for China safeguarding 73.2% of the vascular flora • A transferable model for strengthening botanic garden systems in biodiversity-rich countries