Contrasting spatio-temporal variation of fine root dynamics in nearby evergreen korean pine and deciduous oak forests - Woojin Huh; Minsu Lee; Seohyun Kim; Siyeon Byeon; Tae Kyung Kim; Jeonghyun Hong; Chanoh Park; Gayoung Won; Eunsook Kim; Hyun Seok Kim (Plant and Soil, 2025)
Background and aims Although fine roots play a key role in belowground carbon and nutrient cycling, our understanding of species-specific differences in their phenology, morphology, and turnover remains limited – especially across contrasting tree functional types such as evergreen conifers and deciduous broadleaved species. Improved insight into fine root dynamics is essential for understanding how different forest types shape ecosystem functioning, including potential contributions to soil carbon inputs. Methods The dynamics of fine roots (< 2 mm in diameter) were investigated in adjacent evergreen pine (TCK: Taehwa coniferous forest of Korea) and deciduous oak (TBK: Taehwa broadleaf forest of Korea) forests. Minirhizotron images were taken over two years to analyze root production, mortality, turnover, and longevity. Sequential coring was used to assess root biomass and morphological characteristics, along with soil chemical properties across depths (0-30 cm). Results Although TCK roots had larger diameters compared to TBK, TCK unexpectedly exhibited higher turnover rates. Additionally, TCK exhibited a bimodal phenological pattern while TBK exhibited a unimodal pattern. TBK had higher specific root length and faster turnover, as well as more carbon at 0-10 cm soil depths. In contrast, TCK had more uniform root and soil carbon distributions across depths. Conclusion Our findings reveal clear species-specific differences in fine root phenology, morphology, and turnover between adjacent evergreen and deciduous forests. These differences likely reflect distinct belowground strategies for resource acquisition and may influence the timing and magnitude of root-derived carbon inputs to soil. Understanding such variation is critical for improving forest ecosystem models and guiding adaptive management.