Litter decomposition involves multiple complex processes, including interactions between the physicochemical characteristics of litter species and various environmental factors. We selected four representative pine species in South Korea (Pinus densiflora Siebold & Zucc., Pinus thunbergii Parl., Pinus koraiensis Siebold & Zucc., and Pinus rigida Miller) to investigate the decay rate and effects of the physicochemical properties on decomposition. Needle litters were incubated in microcosms at 23 °C for 280 days and retrieved four times in about 70-day intervals. The mass loss showed significant differences among the species and was higher in the order of P. densiflora (30.5%), P. koraiensis (27.8%), P. rigida (26.5%), and P. thunbergii (23.6%). The needle litter decomposition showed a negative relationship with the initial surface area, volume, density, cellulose content, and lignin/nitrogen of the litter, and a positive relationship with the initial specific leaf area (SLA), surface-area-to-volume ratio (SA/V), and water- and ethanol-soluble substances. The decomposition rate was highly affected by the physical properties of litter when compared with the initial chemical litter quality, and it was strongly influenced by SLA and SA/V. Accordingly, the physical properties of pine needle litter, especially SLA and SA/V, may be the key factors, and they could be used as predictive indices for the decomposition rate of pine tree litters.

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The purpose of this study was to investigate the objective impact in accuracy and reliability with tendency depend on training samples by using the high-resolution images. Supervised classification was performed based on multi-spectral images which made by each satellite and aerial images for considering all of bands' characteristics. The highest accuracy was 84.7% with satellite image(3*3) and 83% with aerial image(5*5) at the accuracy verification phase. Also, the overall accuracy with the consideration of Kappa coefficient were 0.84 for satellite images and 0.82 for aerial images. In all of the images, the smaller training sample was, the higher accuracy showed. Therefore, tree species classification accuracy was tended to rely on training sample size.

This study was proposed to adaptable species according to climate change using warmth index(WI) in Cheonan-Si. RCP 8.5 was used to estimate change of warmth index(WI) depending on climate change in Cheonan-Si. Climatic change of Cheonan-Si was estimated to change from cool temperate forest central zone to warm temperate forest zone. The following plant species will survive within WI change of Cheonan-Si from 2010 to 2050：18 species in the tree layer including Quercus serrata, Q. variabilis, Pinus densiflora, Q. acutissima etc.; 28 species in the shrub layer including Rhus trichocarpa, Lindera obtusiloba, Zanthoxylum schinifolium etc.; 24 species in the herb layer including Oplismenus undulatifolius, Carex lanceolata, etc.; 12 species in the vine plants including Smilax china, Cocculus trilobus, etc. Key Words：Cool temperate forest central zone, Warm temperate forest zone.