Introduction Mountain habitats feature steep environmental gradients that shape specific vegetation diversity and soil heterogeneity. However, how plants coordinated aboveground and belowground reproductive strategies under varying resource availability remained poorly understood. Methods We quantified the belowground bud bank, functional traits, and phylogenetic structures to elucidate plant resource allocation strategies governing community assembly in mountain grasslands of northern China. Six habitat types (SubAlpine Meadow, Forest-Edge Meadow, Floodplain Meadow, Hillside Steppe, Dry Steppe and Sandy Steppe) were selected based on resource availability along the elevation. Results 1) Subalpine Meadow exhibited the highest density and diversity. Floodplain Meadow and Dry Steppe had higher ramet density but lower diversity. Bud densities and diversities in the Subalpine, Floodplain and Hillside Steppe were higher than those in other low-elevation habitats; 2) None of the bud bank density, plant height and abundance showed strongly phylogenetic signals. The NTI, NRI were positively related with B/V density, while they were negatively correlated with height and B/V diversity indices; 3) Soil resources distinctly regulated aboveground and belowground populations: Total nitrogen, porosity and soil moisture were negatively correlated with diversities but positively with densities, acting as constraints on the density-diversity trade-off. Importantly, soil organic carbon specifically promoted belowground bud diversity, while total potassium drove aboveground ramet diversity. Conclusion Our results revealed that deterministic processes (niche theory) governed community assembly in the Saihanwula mountain grassland. The aboveground and belowground populations in mountain grasslands were governed by distinct ecological processes and soil resources. Interspecific competition and environmental filtering drove aboveground community assembly, whereas resource availability constrained the belowground bud bank. Our findings provided significant insights for predicting the renewal and recovery potential of plants under global changes.
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Ma et al. (2026) studied this question.
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