A simulation study of landscape scale forest succession in northeastern China

Changbai Natural Reserve in northeastern China provides an excellent opportunity to explore how temperate and boreal forest ecosystems in northeastern China will evolve and recover over large spatial and temporal scales. Such studies are increasingly needed to design scientifically sound forest management and restoration plans in this region. Long-term (300 years) successional trajectories of the dominant tree species are simulated on the heterogeneous, undisturbed area (within the reserve) using a spatially explicit landscape model. We also examine the spatial and temporal constrains of landscape recovery on the human disturbed areas (surrounding the reserve). Simulation results suggest that an equilibrium in landscape structure and composition is approached on the large landtypes dominated by shade tolerant species, but not on landtypes altered by humans. Such equilibrium can be observed in spruce-fir, mountain birch, and larch forests and not in aspen-birch forests. Our results suggest that direct and indirect human impact may produce long-term alterations to forest landscape patch structure that persist for decades to centuries. For example, even with complete natural succession over 300 years, Korean pine only recovers on 1/3 of the areas in the landtypes it can dominate. We estimate a full recovery would take another 200-300 years without human disturbance. Our results also indicate that landscape-scale recovery is often limited by the available seed sources and this is particularly true for Korean pines in this region. Comparison of simulation results for the entire study area with land types (two scales) reveals the greatest variations at the land type scale. This discrepancy indicates that the 'space-for-time' substitutions can be flawed as species composition and age class at a given site and time may represent only the specific successional history of that site. This is particularly true for human disturbed forest landscapes where higher variations are observed.