Effects of Korean Pine Basal Area in Mixed Broadleaved–Korean Pine Forest Stands on Its Natural Regeneration in Northeast China

Author:

Ge Xiaowen1,Zhu Jiaojun21,Lu Deliang21,Zhu Chunyu213,Gao Pingzhen213,Yang Xiaoyan4

Affiliation:

1. CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Shenyang, China

2. Qingyuan Forest CERN, Chinese Academy of Sciences, Shenyang, China

3. University of Chinese Academy of Sciences, Beijing, China

4. College of Forestry, Shenyang Agricultural University, Shenyang, China

Abstract

Abstract Understanding the natural regeneration of Korean pine (Pinus koraiensis Sieb. et Zucc.) in mixed broadleaved–Korean pine (MBK) forests is crucial for MBK forest conservation and secondary deciduous broadleaved forest restoration. We hypothesized the ratio of Korean pine basal area (RKp) in MBK stands affected its natural regeneration. Regeneration censuses, including the height, root collar diameter, age, and growth stages (younger seedling, older seedling, smaller sapling, and taller sapling) of Korean pine, were conducted in northeast China. Results indicated the stem density and age composition of younger seedlings were positively correlated with RKp, whereas those of the saplings were negatively correlated with RKp. In the stands with lower RKp (<80% in Lesser Khingan Mountains [LKM]; <40% in Lushuihe Forestry Bureau [LFB]), individuals in all growth stages regenerated well with an age span of 65 yr. However, the regeneration of taller saplings was severely inhibited with increasing RKp (LKM: RKp ≥ 80%; LFB: RKp ≥ 40%). In summary, RKp significantly affected the natural regeneration of Korean pine in MBK forests. The basal-area thresholds limiting regeneration were found to be 80% in LKM stands and 40% in LFB stands. These basal-area thresholds provided evidence of why the zonal climax was MBK forests rather than pure Korean pine forests.

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Ecological Modelling,Ecology,Forestry

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