Improving optimal forest management model to account for climate change

Moonil Kim of Korea University, Republic of Korea, aimed to improve the existing forest growth model and research algorithms of the G4M model so that it could be adapted to South Korea.

Moonil Kim

Moonil Kim


More than 63% of South Korea is covered with forest. Recently, most (69.5%) of the forests in South Korea between 20 and 40 years old have become very dense and competitive for trees [1]. An optimal forest management plan is thus needed to address these problems. To establish a forest management plan, a forest growth model is needed that considers future climate change and also a model to predict changes in the forest carried out under the forest management plan. The aim of this research was to try to improve the existing forest growth model and research algorithms of the G4M model so that it could be adapted to South Korea.


1. Improvement of forest growth model to cover possible effects of climate change

A radial growth model (equation 1) was developed to include topographic and climatic factors. The model was developed using growth data obtained from 43,532 individual trees at 3,357 National Forest Inventory (NFI) plots in South Korea.

2. G4M model study and simulation

Some of the coefficients of tree growth equations in G4M were revised using yield tables produced by the Korea Forest Service. The forest area was also classified using two criteria: radial growth patterns for each tree species and climatic factors.


The growth model developed in this study successfully described the relationship between radial growth patterns of each tree species and climatic factors (Figure d).

The growth model reflects the actual growth distribution of pine trees with a high accuracy and even estimated regions where the growth rate of pine tree is low or there are as yet no pine trees (Figures a, b, c).

The G4M model results are reasonable considering the current status of forest area in South Korea (Figure e).

Figure 1. (a) Current eSG of P. densiflora from previous growth model [2]; (b) from our model and (c) actual distribution of P. densiflora; (d) correlation between tree growth and annual mean temperature; (e) estimated stocking stem carbon using G4M ore abundant forest than South Korea until 1970s (click on the image to enlarge).


[1] Korea Forest Service (2011). Statistical Yearbook of Forestry. Daejeon, Korea: KFS

[2] Byun et al. (2013), Radial growth response of Pinus densiflora and Quercus spp. to topographic and climatic factors in South Korea. Journal of Plant Ecology 6(5), 380-392.


Nicklas Forsell and Georg Kindermann, Ecosystems Services and Management, IIASA


Moonil Kim of Korea University, Republic of Korea, is a citizen of the Republic of Korea. He was funded by IIASA and worked in the Ecosystems Services and Management (ESM) Program during the YSSP.

Please note these Proceedings have received limited or no review from supervisors and IIASA program directors, and the views and results expressed therein do not necessarily represent IIASA, its National Member Organizations, or other organizations supporting the work.

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Last edited: 29 September 2015


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