Abstract: This study aimed to explore the differences in morphology and nutrient distribution of Quercus mongolica seedlings from two regeneration types (i.e., seed regeneration and sprout regeneration) by comparing the growth characteristics of 1-year-old seedlings and sprouts in a montane region of eastern Liaoning Province, China. The results showed that there were significant differences in biomass between seedlings and sprouts. Specifically, the leaf weight, stem weight,  and stem weight to aboveground biomass ratio of sprouts were significantly greater than those of seedlings (P<0.05). leaf weight to above ground biomass ratio, Photosynthetic tissuetononphotosynthetic tissue ratio of seedlings were significantly higher than those of sprouts (P<0.05). The growth traits of sprouts were characterized by short and thick stems while the seedlings exhibited tall and small stems with thick and long roots. There were no significant differences in specific leaf area, nitrogen content and δ¹³C in leaf between seedlings and sprouts (P>0.05). The water content of sprouts was significantly greater than that of seedlings (P<0.05). There were no significant differences in the contents of structural carbon and nonstructural carbon between seedlings and sprouts (P>0.05). However, the sprouts had significantly less soluble sugar contents in leaf and stem, and a significantly greater starch pool in leaf than the seedlings (P<0.05). It can be concluded that there are different growth strategies to acclimating the local environments for seedlings of Q. mongolica from two regeneration types. Sprouts of Q. mongolica sustain their growth relying on the nutrients and water supplied by parent plants, meanwhile, much more starch produced by photosynthesis is stored in their leaves. However, the seedlings of Q. mongolica tend to raise the growth of stem and the biomass of photosynthetic tissue to most utilize light resources, meanwhile, much more soluble sugar is stored in leaves and stems to maintain their growth.

Key words: grey correlation analysis, Liaoning Province, energy consumption, economic growth