• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.554-568
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• 2021

Forests are the largest carbon (C) sinks in terrestrial ecosystems. Recently, as enhancing forest C sequestration capacity has been proposed as a basic direction of the Republic of Korea's "2050 Carbon Neutral Strategy," accurate estimation of forest C sequestration has been emphasized. According to the Intergovernmental Panel on Climate Change guidelines, sequestration quantity is calculated from changes in C stocks in forest C pools, such as biomass, deadwood, litter and soil layer, and harvested wood products. However, in Korea, only the overstory biomass increase is now considered the amount of sequestration quantity, so there can be a significant difference from the actual forest C sequestration. In this study, we quantified forest C exchange through C flux measurement using an eddy covariance system and an automated soil chamber system in a 57-year-old Korean pine plantation located in Mt. Taehwa, Gwangju-si, Gyeonggi-do. Then, the net amount of C sequestration was compared with the amount of the overstory biomass increase. We estimated the annual C stock change in the remaining C pools by comparing the net sequestration amount from the C flux measurement with the overstory biomass increase and C stock change in the litter layer. Therefore, the net C sequestration of the Korean pine plantation estimated from the flux measurement was 5.96 MgC ha^-1, which was about 2.2 times greater than 2.77 MgC ha^-1 of the overstory biomass increase. The annual C stock increase in the litter layer was estimated to be 0.75 MgC ha^-1, resulting in a total annual C stock increase of 2.45 MgC ha^-1 in the remaining C pools. Our results indicate that the domestic forest is a larger C sink than the current methods, implying that more accurate calculations of the C sequestration capacity are necessary to quantify C stock changes in C pools along with the C flux measurement.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.1
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• pp.45-50
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• 2005

This study was conducted to measure and understand the exchange of CO₂ and water in a rice canopy. Eddy covariance system was installed on a 10m tower along with other meteorological instruments. CO₂ flux and surface energy balance were measured throughout the whole growing season in 2003 over a typical paddy field in Icheon, Korea. During the early growth stage in May and June, most of net radiation was partitioned to latent heat flux with daytime Bowen ratio of 0.3 to 0.7. Evapotranspiration (i.e., daily integrated latent heat flux) typically ranged from 3 to 4 mm d/sup -1/, with even higher rates on sunny days. Daily integrated net ecosystem exchange (NEE) of CO₂ increased with increasing solar radiation and leaf area index (LAI). The NEE was especially high during the stages of young panicle formation and heading. On 1 June 2003, when the rice field was flooded, it was a weak sink of atmospheric CO₂ with an uptake rate of 9.1 gm/sup -2/d/sup -1/. Despite frequent rainy and cloudy conditions in summer, maximum NEE of 36.2 gm/sup -2/d/sup -1/ occurred on 31 July prior to heading stage. As rice crop senesced after early September, the NEE decreased.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.1
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• pp.107-114
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• 2005

Soil CO₂ emission is one of the primary components in carbon balance of terrestrial ecosystems. In soil CO₂ flux measurements, chamber method is currently the most common technique. Prior to compare or synthesize the data collected from different chamber methods, potential biases must be quantified for each measurement system. We have conducted an intercomparison experiment among four closed dynamic chamber systems and an automatic open-closed chamber system in a temperature-controlled phytotron. Due to the disturbed CO₂ concentrations inside the phytotron during the measurements with closed dynamic chambers and the changes in soil water content, the interpretation of the data was difficult to quantify the biases of individual methods. However, the experiment provided not only valuable information on the performance characteristics of the five instruments to varying soil temperature and CO₂ concentration but also useful insights for better designs and strategy for future intercomparison in a controlled environment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.307-316
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• 2019

In the agricultural sector, greenhouse gas emissions vary depending on the interaction of all ecosystem changes such as soil environment, weather environment, crop growth, and anthropogenic farming activities. Agricultural sector greenhouse gas emissions resulting from many of these interactions are highly variable. Uncertainty-based evaluation that defines the interval with confidence level of greenhouse gas emission and absorption is necessary to take account of the variance characteristics of individual emissions, but research on uncertainty evaluation method is insufficient. This study aims to decide on the effect of reducing N₂O emissions from upland soils using an uncertainty-based approach. An uncertainty-based approach confirmed whether there was a difference between confidence intervals in the 5 different fertilizer treatment groups to reduce greenhouse gas emissions. Unlike the statistically significant test with three repetition averages, the uncertainty-based approach method estimated in this study is able to estimate the confidence interval considering the distribution characteristics of the emissions, such as the dispersion characteristics of individual emissions. Therefore, it is considered that the reliability of emissions can be improved by statistically testing the variance characteristics of emissions such as the uncertainty-based approach. It is hoped that the direction of the uncertainty-based approach for the effect of reducing greenhouse gas emissions in agriculture will be helpful in the future development of agricultural greenhouse gas emission reduction technology, adaptation to climate change, and further development of sustainable eco-social system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.2
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• pp.138-149
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• 2003

Korean regional network of tower flux sites, KoFlux, has been initiated to better understand $CO_2$, water and energy exchange between ecosystems and the atmosphere, and to contribute to regional, continental, and global observation networks such as FLUXNET and CEOP. Due to heterogeneous surface characteristics, most of KoFlux towers are located in non-ideal sites. In order to quantify carbon and energy exchange and to scale them up from plot scales to a region scale, applications of various methods combining measurement and modeling are needed. In an attempt to infer regional-scale flux, four methods (i.e., tower flux, convective boundary layer (CBL) budget method, MM5 mesoscale model, and NCAR/NCEP reanalysis data) were employed to estimate sensible heat flux representing different surface areas. Our preliminary results showed that (1) sensible heat flux from the tower in Haenam farmland revealed heterogeneous surface characteristics of the site; (2) sensible heat flux from CBL method was sensitive to the estimation of advection; and (3) MM5 mesoscale model produced regional fluxes that were comparable to tower fluxes. In view of the spatial heterogeneity of the site and inherent differences in spatial scale between the methods, however, the spatial representativeness of tower flux need to be quantified based on footprint climatology, geographic information system, and the patch scale analysis of satellite images of the study site.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.96-104
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• 2001

Usage of ecosystem models has been extended to landscape scales for understanding the effects of environmental factors on natural and agro-ecosystems and for serving as their management decision tools. Accurate prediction of spatial variation in daily temperature is required for most ecosystem models to be applied to landscape scales. There are relatively few empirical evaluations of landscape-scale temperature prediction techniques in mountainous terrain such as Korean Peninsula. We derived a periodic function of seasonal lapse rate fluctuation from analysis of elevation effects on daily temperatures. Observed daily maximum and minimum temperature data at 63 standard stations in 1999 were regressed to the latitude, longitude, distance from the nearest coastline and altitude of the stations, and the optimum models with $r^2$ of 0.65 and above were selected. Partial regression coefficients for the altitude variable were plotted against day of year, and a numerical formula was determined for simulating the seasonal trend of daily lapse rate, i.e., partial regression coefficients. The formula in conjunction with an inverse distance weighted interpolation scheme was applied to predict daily temperatures at 267 sites, where observation data are available, on randomly selected dates for winter, spring and summer in 2000. The estimation errors were smaller and more consistent than the inverse distance weighting plus mean annual lapse rate scheme. We conclude that this method is simple and accurate enough to be used as an operational temperature interpolation scheme at landscape scale in Korea and should be applicable to elsewhere.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.1
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• pp.16-29
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• 2016

The total area of paddy field was estimated to be 55 % of the cultivated lands in South Korea, which is approximately 1 million hectares. Organisms inhabiting paddy fields if they are sensitive to environmental changes can be environmental indicator of paddy fields. Biological indicators such as phenology and distributional range are evaluated as intuitive and quantitative method to analyze the impact of climate change. This study aims to estimate flight time change of Hydrophilidae species' based on the RCP 8.5 climate change scenario. Unmanned monitoring systems were installed in Haenam, Buan, Dangjin and Cheorwon relative to the latitudinal gradient. In the three regions excepting Cheorwon, it was able to measure the abundance of flying Hydrochara affinis and Sternolophus rufipes. Degree-day for the flight time was determined based either on field measurement values and estimates of 2020s, 2050s and 2080s from KMA climate change scenario data. As a result, it is found that date of both species of initial flight becomes 15 days earlier, that of peak flight becomes 22 days earlier and that of final flight does 27 days earlier in 2080s compared to 2020s. The climate change impact on flight time is greater in coastal area, rural area and valley than inland area, urban area and plan. H. affinis and S. rufipes can be used as climate change indicator species.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.2
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• pp.101-108
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• 2011

Climate change could have a pronounced impact on natural and agricultural ecosystems. To assess the impact of climate change, projected climate data have been used as inputs to models. Because such studies are conducted occasionally, it would be useful to employ Cloud computing, which provides multiple instances of operating systems in a virtual environment to do processing on demand without building or maintaining physical computing resources. Furthermore, it would be advantageous to use open source geospatial applications in order to avoid the limitations of proprietary software when Cloud computing is used. As a pilot study, Amazon Web Service ? Elastic Compute Cloud (EC2) was used to calculate the number of days with rain in a given month. Daily sets of climate projection data, which were about 70 gigabytes in total, were processed using virtual machines with a customized database transaction application. The application was linked against open source libraries for the climate data and database access. In this approach, it took about 32 hours to process 17 billion rows of record in order to calculate the rain day on a global scale over the next 100 years using ten clients and one server instances. Here I demonstrate that Cloud computing could provide the high level of performance for impact assessment studies of climate change that require considerable amount of data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.3
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• pp.227-232
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• 2014

Ageratina altissima is an invasive plant species known to threaten native plant communities in Korea. A. altissima is thought to invade shady forests from disturbed open areas; however, uncertainty remains as to how shade and litter depth might affect establishment. A study of A. altissima distribution characteristics in areas adjacent to trails was undertaken at Mt. Umyeon in Seoul, Korea. Increasing densities of A. altissima were found to correlate with greater light availability and decreasing litter depth (p < 0.001) within 10 m distance from trail locations and on ridges rather than further within forests and valleys. The effects of soil moisture content, soil gravel content and soil pH on distribution were not found to be significant, suggesting that A. altissima is adaptable to a broad range of soil conditions. Results indicate that forest areas close to trails may be particularly susceptible place to A. altissima invasion, demonstrating the need to carefully consider implications for A. altissima expansion in trail management.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.242-252
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• 2016

A process-based ecosystem model, BIOME-BGC, was applied to simulate seasonal and inter-annual dynamics of carbon and water processes for potential evergreen needleleaf forest (ENF) biome in Korea. Two simulation sites, Milyang and Unljin, were selected to reflect warm-and-dry and cool-and-wet climate regimes, where massive diebacks of pines including Pinus densiflora, P. koraiensis and P thunbergii, were observed in 2009 and 2014, respectively. Standard Precipitation Index (SPI) showed periodic drought occurrence at every 5 years or so for both sites. Since mid-2000s, droughts occurred with hotter climate condition. Among many model variables, Cpool (i.e., a temporary carbon pool reserving photosynthetic compounds before allocations for new tissue production) was identified as a useful proxy variable of tree carbon starvation caused by reduction of gross primary production (GPP) and/or increase of maintenance respiration (Rm). Temporal Cpool variation agreed well with timings of pine tree diebacks for both sites. Though water stress was important, winter- and spring-time warmer temperature also played critical roles in reduction of Cpool, especially for the cool-and-wet Uljin. Shallow soil depth intensified the drought effect, which was, however, marginal for soil depth shallower than 0.5 m. Our modeling analysis implicates seasonal drought and warmer climate can intensify vulnerability of ENF dieback in Korea, especially for shallower soils, in which multi-year continued stress is of concern more than short-term episodic stress.