• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• Korean Journal of Agricultural Science
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• v.43 no.4
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• pp.537-546
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• 2016

The development of models for agriculture systems, especially for crop production, has supported the prediction of crop yields under various environmental change scenarios and the selection of better crop species or cultivar. Crop models could be used as tools for supporting reasonable nutrient management approaches for agricultural land. This paper outlines the simplified structure of main crop models (crop growth model, crop-soil model, and crop-soil-environment model) frequently used in agricultural systems and shows diverse application of their simulated results. Crop growth models such as LINTUL, SUCROS, could provide simulated data for daily growth, potential production, and photosynthesis assimilate partitioning to various organs with different physiological stages, and for evaluating crop nutrient demand. Crop-Soil models (DSSAT, APSIM, WOFOST, QUEFTS) simulate growth, development, and yields of crops; soil processes describing nutrient uptake from root zone; and soil nutrient supply capability, e.g., mineralization/decomposition of soil organic matter. The crop model built for the DSSAT family software has limitations in spatial variability due to its simulation mechanism based on a single homogeneous field unit. To introduce well-performing crop models, the potential applications for crop-soil-environment models such as DSSAT, APSIM, or even a newly designed model, should first be compared. The parameterization of various crops under different cultivation conditions like those of intensive farming systems common in Korea, shortened crop growth period, should be considered as well as various resource inputs.