• Ocean and Polar Research
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• v.24 no.2
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• pp.153-166
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• 2002

Particle fluxes were measured by using time-series sediment traps in the Bransfield Strait from December 27th, 1999 to December 26th, 2000. Total mass fluxes showed distinct seasonal variations with high fluxes in the austral summer and low fluxes in the austral winter at a 678m water depth in the eastern Bransfield Strait, while they were high only in January and fairly low in other months at a 960m water depth in the central Bransfield Strait. The reason that total mass fluxes occurred only in January at a 960m water depth in the central Bransfield Strait seems to be the strong current in the surface waters, which leads to a substantial amount of terrestrial materials and locally produced organic matter being advected away from the mooring site. Total mass fluxes were very high from January to October at a 1678m water depth in the eastern Bransfield Strait, while they were high only in January and February at a 1860m water depth in the central Bransfield Strait. The fact that total mass fluxes were higher at the deep water in the both sites than at the intermediate water depth may reflect that a substantial amount of terrestrial and organic materials are laterally transported by strong tidal current from the shallow environments to the deep basins.

• 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.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.228-240
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• 2023

Growing complexity in ecosystem structure and functions, under impacts of climate and land-use changes, requires interdisciplinary understandings of processes and the whole-system, and accurate estimates of the changing functions. In the last three decades, observation networks for biodiversity, ecosystems, and ecosystem functions under climate change, have been developed by interested scientists, research institutions and universities. In this paper we will review (1) the development and on-going activities of those observation networks, (2) some outcomes from forest carbon cycle studies at our super-site "Takayama site" in Japan, and (3) a few ideas how we connect in-situ and satellite observations as well as fill observation gaps in the Asia-Oceania region. There have been many intensive research and networking efforts to promote investigations for ecosystem change and functions (e.g., Long-Term Ecological Research Network), measurements of greenhouse gas, heat, and water fluxes (flux network), and biodiversity from genetic to ecosystem level (Biodiversity Observation Network). Combining those in-situ field research data with modeling analysis and satellite remote sensing allows the research communities to up-scale spatially from local to global, and temporally from the past to future. These observation networks oftern use different methodologies and target different scientific disciplines. However growing needs for comprehensive observations to understand the response of biodiversity and ecosystem functions to climate and societal changes at local, national, regional, and global scales are providing opportunities and expectations to network these networks. Among the challenges to produce and share integrated knowledge on climate, ecosystem functions and biodiversity, filling scale-gaps in space and time among the phenomena is crucial. To showcase such efforts, interdisciplinary research at 'Takayama super-site' was reviewed by focusing on studies on forest carbon cycle and phenology. A key approach to respond to multidisciplinary questions is to integrate in-situ field research, ecosystem modeling, and satellite remote sensing by developing cross-scale methodologies at long-term observation field sites called "super-sites". The research approach at 'Takayama site' in Japan showcases this response to the needs of multidisciplinary questions and further development of terrestrial ecosystem research to address environmental change issues from local to national, regional and global scales.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.272-281
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• 2023

Ecosystem observatories are burgeoning globally in an endeavour to detect national and global scale trends in the state of biodiversity and ecosystems in an era of rapid environmental change. In this paper we highlight the additional importance of regional scale outcomes of such infrastructure, through an introduction to the Great Western Woodlands TERN (Terrestrial Ecosystem Research Network) SuperSite, and key findings from three gradient plot networks that are part of this infrastructure. The SuperSite was established in 2012 in the 160,000 km² Great Western Woodlands region, in a collaboration involving 12 organisations. This region is globally significant for its largely intact, diverse landscapes, including the world's largest Mediterranean-climate woodlands and highly diverse sandplain shrublands. The dominant woodland eucalypts are fire-sensitive, requiring hundreds of years to regrow after fire. Old-growth woodlands are highly valued by Indigenous and non-Indigenous communities, and managing impacts of climate change and the increasing extent of intense fires are key regional management challenges. Like other TERN SuperSites, the Great Western Woodlands TERN SuperSite includes a core eddy-covariance flux tower measuring exchanges of carbon, water and energy between the vegetation and atmosphere, along with additional environmental and biodiversity monitoring around the tower. The broader SuperSite incorporates three gradient plot networks. Two of these represent aridity gradients, in sandplains and woodlands, informing regional climate adaptation and biodiversity management by characterising biodiversity turnover along spatial climate gradients and acting as sentinels for ecosystem change over time. For example, the sandplains transect has demonstrated extremely high spatial turnover rates in plant species, that challenge traditional approaches to biodiversity conservation. The third gradient plot network represents a 400-year fire-age gradient in Eucalyptus salubris woodlands. It has enabled characterisation of post-fire recovery of vegetation, birds and invertebrates over multi-century timeframes, and provided tools that are directly informing management to reduce stand-replacing fires in eucalypt woodlands. By building regional partnerships and applying globally or nationally consistent methodologies to regional scale questions, ecological observatories have the power not only to detect national and global scale trends in biodiversity and ecosystems, but to directly inform environmental decisions that are critical at regional scales.

• Ocean and Polar Research
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• v.25 no.1
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• pp.41-52
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• 2003

Sediment trap samples were collected to find out characteristic behaviors of metals in the settling particles by using time-series sediment traps at 678m and 1678m water depths in the Bransfield Strait from December 27th, 1999 to December 26th, 2000. Total mass fluxes at the intermediate water depth (678m water depth) were high in the austral summer and low in the austral winter, whereas at the deep water depth (1678m water depth) they showed high values in both the summer and winter. Total mass fluxes were generally higher in the deep water depth than in the intermediate water depth, which indicates that a substantial amount of sediments are laterally transported by strong currents into the deep basin from the shallow water depths. Aluminium contents also showed large seasonal variations with high values in the winter and low values in the summer. On the contrary, organic carbon contents were high in the summer and low in the winter. Al contents were negatively correlated with organic carbon contents, which may be ascribed that detrital particles are diluted by organic matter produced by phytoplankton in the surface waters. Metals measured in this study exhibited three characteristic behaviors; 1) a positive correlation with Al-Ti, Fe, Mn, V, Co, and Ba, 2) a negative correlation with Al-Cd and Zn, 3) no relationship with Al-Sr, Cu, Cr, Ni. Terrestrial materials may act as a major source fer metals that are positively correlated with Al, and organic matter may be a major source for metals that are negatively correlated with Al. Enrichment factor (EF) of Fe, Mn, Ba, Vi Co, Sr, Cr, and Ni ranged from 0.5 to 1.5, whereas EF of Zn, Cu, and Cd showed much higher values than 1.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.2
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• pp.242-251
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• 2010

In comparison with other terrestrial ecosystems, rice paddies are unique because they provide the primary food source for over 50% of the world's population, and act as major sources of global methane. The present paper summerizes a long-term field study that combine carbon isotopes, and canopy-scale flux measurements in an irrigated rice paddy, in conjugation with continuous monitoring of environmental, and vegetational factors. Both $CO_2$, and methane fluxes were largely influenced by soil temperature, and moisture conditions, especially across drainage events. Soil-entrapped $CO_2$, and methane showed a gradually increasing trend throughout growing season, but rapidly decreased upon flood water drainage. These variations in flux were well correlated with changes in concentration, and isotope ratio of soil $CO_2$, and methane, and of atmospheric $CO_2$, and methane within, and above the canopy. The isotopic signature of the gas exchange process varied markedly in response to change in contribution of soil respiration, belowground storage, fraction of $CO_2$ recycled, magnitude, and direction of $CO_2$ exchange, transport mechanism, and fraction of methane oxidized. Our results clearly demonstrate that stable isotope analysis can be a useful tool to study underlying mechanisms of gas exchange processes under natural conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1117-1132
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• 2019

Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.

• 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 Remote Sensing
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• v.27 no.4
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• pp.481-494
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• 2011

Investigation of the $CO_2$ exchange between biosphere and atmosphere at regional, continental, and global scales can be directed to combining remote sensing with carbon cycle process to estimate vegetation productivity. NASA Earth Observing System (EOS) currently produces a regular global estimate of gross primary productivity (GPP) and annual net primary productivity (NPP) of the entire terrestrial earth surface at 1 km spatial resolution. While the MODIS GPP algorithm uses meteorological data provided by the NASA Data Assimilation Office (DAO), the sub-pixel heterogeneity or complex terrain are generally reflected due to coarse spatial resolutions of the DAO data (a resolution of $1{\circ}\;{\times}\;1.25{\circ}$). In this study, we estimated inputs retrieved from MODIS products of the AQUA and TERRA satellites with 5 km spatial resolution for the purpose of finer GPP and/or NPP determinations. The derivatives included temperature, VPD, and solar radiation. Seven AmeriFlux data located in the Corn Belt region were obtained to use for evaluation of the input data from MODIS. MODIS-derived air temperature values showed a good agreement with ground-based observations. The mean error (ME) and coefficient of correlation (R) ranged from $-0.9^{\circ}C$ to $+5.2^{\circ}C$ and from 0.83 to 0.98, respectively. VPD somewhat coarsely agreed with tower observations (ME = -183.8 Pa ~ +382.1 Pa; R = 0.51 ~ 0.92). While MODIS-derived shortwave radiation showed a good correlation with observations, it was slightly overestimated (ME = -0.4 MJ $day^{-1}$ ~ +7.9 MJ $day^{-1}$; R = 0.67 ~ 0.97). Our results indicate that the use of inputs derived MODIS atmosphere and land products can provide a useful tool for estimating crop GPP.