PS 94-60 - Development of forest’s distribution model in South Korea using IPCC A1B scenario

Friday, August 6, 2010
Exhibit Hall A, David L Lawrence Convention Center
Dongkun Lee and Jaeuk Kim, Landscape Architecture and Rural System Engineering, Seoul National University, Seoul, Korea, Republic of (South)
Background/Question/Methods

The earth’s temperature rose about 0.6±0.2°C during the twentieth century. In Korea’s case, analysis from meteorological station from 1904 to 2000 shows that the mean temperature rose by 1.5°C as CO2 concentration in the atmosphere increased due to rapid industrialization. Even though it is essential to evaluate the influence of climate changes on the ecosystem, specific studies on how global warming has changed and damaged the biosphere have not been performed in Korea. Thus, the aim of this research is to study the effects of global warming on the biosphere in Korea and to propose a way to cope with these changes. Using the present (1971~2000) climate data from the Korea Meteorological Administration (KMA), a multinomial logit model was performed on the estimated current climate and information about inhabitation conditions of coniferous forests, deciduous forests and mixed forests on the actual vegetation map. The IPCC SRES A1B scenario by KMA was applied for the distribution of four future time periods (2026~2035, 2046~2055, 2066~2075, 2096~2100) on this model.

Results/Conclusions

Average temperature (April), maximum temperature (January) and minimum temperature (September) were selected by this model. The distribution model of forest vegetation for the greatest natural area has 56.8% prediction accuracy. This model considered a limited range of forest type to improve prediction accuracy because of a difference between statistical formulas and the real world. Prediction accuracy increased to 76.1% using limited range. After this model was applied on a nationwide scale, prediction accuracy decreased to 65.6%. The sample area conserved, on the other hand, showed most forests were affected by human actions. The coniferous forests decreased by about half of present area and deciduous forests decreased some by 2030. Mixed forests, however, increased. When the distribution of forests in 2050 and 2070 was compared to the distribution in 2030, coniferous forests and mixed forests decreased continuously while deciduous forests increased. The forest pattern showed some change by 2100, deciduous forests downturned but coniferous forests and mixed forests upturned. This research is very significant in that it evaluates the future vulnerability of vegetation in the mountains and the forests utilizing various climate models. It would be possible to use results from this study as drafting material to prepare administrative plans for any plant communities that exhibit any vulnerable characteristics.

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