Journal of Korean Society of Forest Science (한국산림과학회지)

Korean Society of Forest Science (한국산림과학회)
권호 표지
DOI QR코드

DOI QR Code

Development of Stand Yield Table Based on Current Growth Characteristics of Chamaecyparis obtusa Stands

현실임분 생장특성에 의한 편백 임분수확표 개발

  • Jung, Su Young (Warm Temperate and Subtropical Forest Research Center, National Institute of Forest Science) ;
  • Lee, Kwang Soo (Warm Temperate and Subtropical Forest Research Center, National Institute of Forest Science) ;
  • Lee, Ho Sang (Warm Temperate and Subtropical Forest Research Center, National Institute of Forest Science) ;
  • Ji Bae, Eun (Forest Biomaterials Research Center, National Institute of Forest Science) ;
  • Park, Jun Hyung (Forest Technology and Management Research Center, National Institute of Forest Science) ;
  • Ko, Chi-Ung (Division of Forest Industry Research, National Institute of Forest Science)
  • 정수영 (국립산림과학학원 난대.아열대산림연구소) ;
  • 이광수 (국립산림과학학원 난대.아열대산림연구소) ;
  • 이호상 (국립산림과학학원 난대.아열대산림연구소) ;
  • 배은지 (국립산림과학원 산림바이오소재연구소) ;
  • 박준형 (국립산림과학원 산림기술경영연구소) ;
  • 고치웅 (국립산림과학원 산림산업연구과)
  • Received : 2020.08.25
  • Accepted : 2020.11.13
  • Published : 2020.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

We constructed a stand yield table for Chamaecyparis obtusa based on data from an actual forest. The previous stand yield table had a number of disadvantages because it was based on actual forest information. In the present study we used data from more than 200 sampling plots in a stand of Chamaecyparis obtusa. The analysis included theestimation, recovery and prediction of the distribution of values for diameter at breast height (DBH), and the result is a valuable process for the preparation ofstand yield tables. The DBH distribution model uses a Weibull function, and the site index (base age: 30 years), the standard for assessing forest productivity, was derived using the Chapman-Richards formula. Several estimation formulas for the preparation of the stand yield table were considered for the fitness index, and the optimal formula was chosen. The analysis shows that the site index is in the range of 10 to 18 in the Chamaecyparis obtusa stand. The estimated stand volume of each sample plot was found to have an accuracy of 62%. According to the residuals analysis, the stands showed even distribution around zero, which indicates that the results are useful in the field. Comparing the table constructed in this study to the existing stand yield table, we found that our table yielded comparatively higher values for growth. This is probably because the existing analysis data used a small amount of research data that did not properly reflect. We hope that the stand yield table of Chamaecyparis obtusa, a representative species of southern regions, will be widely used for forest management. As these forests stabilize and growth progresses, we plan to construct an additional yield table applicable to the production of developed stands.

본 연구는 남부지방 대표수종인 편백 현실림의 생장 특성을 반영한 수확표를 작성하기 위하여 수행되었다. 200개소 이상의 편백의 표준지 생장조사 자료를 분석에 이용하였다. 기존의 임분수확표 작성 절차인 직경분포의 추정, 적합, 예측의 단계를 거쳤으며, 직경분포모델은 Weibull 함수를 이용하였다. 임지생산력을 평가하기 위한 기준인 지위지수(기준임령 30년)는 Chapman-Richards식을 이용하여 추정하였다. 임분수확표 작성을 위한 평균직경 등 여러 추정식은 적합도를 고려하여 최적의식을 선정하고 이용한 결과, 조사된 편백 현실임분의 지위지수는 10~18 범위에 있음이 밝혀졌다. 추정된 임분재적 모델은 편백림의 임분재적에 대해 62%의 설명력을 가지는 것으로 나타났다. 실재적과 추정재적 간의 잔차도분석 결과 '0'을 중심으로 모두 고른 잔차를 보여 본 추정 결과를 이용함은 문제가 없을 것으로 판단되었다. 이번 남부지방을 대표하는 침엽수인 편백에 대한 임분수확표 작성 결과가 현실의 산림경영에 폭넓게 사용되기를 바라며, 향후 편백 임분 생장이 더욱 안정화되고 생육발달로 장벌기 대경재 생산지가 많이 확보되면 더욱 개선된 수확표의 작성도 가능할 것으로 기대된다.

Keywords

References

  1. Cao, Q.V. 1997. A method to distribute mortality in diameter distribution models. Forest Science 43(3): 435-442.
  2. Clutter, J.L., Fortson, J.C., Pienaar, L.V., Brister, G. H. and Bailey., R.L. 1983. Timber management: A quantitative approach. John Wiley & Sons. pp. 333.
  3. Gadow, K.V. and Bredenkamp, B. 1992. Forest management. Academia. pp. 151.
  4. Garcia, O. 1981. Simplified method-of-moments estimation for the Weibull distribution. New Zealand Journal of Forest Science 11(3): 304-306.
  5. Korea Forest Service. 2019. Statistical yearbook of forestry. vol. 49. pp. 444.
  6. Korea Rural Economic Institute. 2019. A study on the realization of forest resource recycling type forestry for a sustainable low-carbon society. PCAFRP (Presidential committee on agriculture, fisheries and rural policy). pp. 52.
  7. Laar, A.V. and Akca, A. 1997. Forest mensuration. Cuvillier Verlag Gottingen. pp. 418.
  8. Lee, K.H., Son, Y.M. and Bae, S.W. 2009. Tree volume, weight and stand yield table. National Institute of Forest Science. pp. 271.
  9. Lee, K.H., Son, Y.M., Yim, J.S., Kim, R.H., Lee, S.J. and Koo, C.U. 2018. Guideline of forest measurement and survey. National Institute of Forest Science, Research Book, No. 113. pp. 191.
  10. National Institute of Forest Science. 1987. Yield tables and site index tables. pp. 49.
  11. National Institute of Forest Science. 2019. Development of treatment regime for forest management in Cryptomeria japonica and Chamaecyparis obtusa stands. Program II, Research Report. pp. 301-334.
  12. National Institute of Forest Science. 2020. Analysis data of stem taper in Cryptomeria japonica and Chamaecyparis obtusa stand. Inner data (without printed).
  13. Park, T.S., Kim, D.C., Kwon, O.B., Lee, M.W., Lee, S.S., Lee, R.H., Cho, Y.H., Kang, S.Y., Chung, Y.K., Byun, W.H. and Woo, J.C. 1992. Forest Management. Hwangmunsa. pp. 426.
  14. Schumacher, F.X. 1939. A new growth curve and its application to timber yield studies. Journal of Forestry 37: 819-820.
  15. Son, Y.M., Kim, S.W., Lee, S.J. and Lim, J.S. 2014. Estimation of stand yield and carbon stock for Robinia pseudoacacia stands in Korea. Journal of Korean Forest Society 103(2): 264-269. https://doi.org/10.14578/JKFS.2014.103.2.264
  16. Son, Y.M., Lee, K.H., Chung, S.K., Kim, S.H. and Lee, W.K. 2004. Analysis of forest resources. National Institute of Forest Science, Research Book, No. 4. pp. 128.
  17. Shiver, B.D. 1988. Sample sizes and estimation methods for the Weibull distribution for unthinned slash pine plantation diameter distributions. Forest Science 34(3): 809-814.
  18. Weibull, W. 1951. Applied Linear Regression, 2nd. ed. Wiley, N.Y., pp. 324.
  19. Yim, K.B. et al.. 1997. Silviculture. Hwangmunsa. pp. 349.