• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2015.08a
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• pp.117-120
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• 2015

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.270-271
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• 2019

• Journal of Forest and Environmental Science
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• v.33 no.4
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• pp.305-314
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• 2017

This study aimed to predict changes in forest area using a probability density function, in order to promote effective forest management in the area north of the civilian control line (known as the Minbuk area) in Korea. Time series analysis (2010 and 2016) of forest area using land cover maps and accessibility expressed by distance covariates (distance from buildings, roads, and civilian control line) was applied to a probability density function. In order to estimate the probability density function, mean and variance were calculated using three methods: area weight (AW), area rate weight (ARW), and sample area change rate weight (SRW). Forest area increases in regions with lower accessibility (i.e., greater distance) from buildings and roads, but no relationship with accessibility from the civilian control line was found. Estimation of forest area change using different distance covariates shows that SRW using distance from buildings provides the most accurate estimation, with around 0.98-fold difference from actual forest area change, and performs well in a Chi-Square test. Furthermore, estimation of forest area until 2028 using SRW and distance from buildings most closely replicates patterns of actual forest area changes, suggesting that estimation of future change could be possible using this method. The method allows investigation of the current status of land cover in the Minbuk area, as well as predictions of future changes in forest area that could be utilized in forest management planning and policymaking in the northern area.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.385-391
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• 2017

This study was conducted to estimate litter carbon stock change from the National Forest Inventory (NFI) data for national greenhouse gas inventory report. Litter carbon stocks were calculated from the NFI dataset in NFI5 (2008) and NFI6 (2013) in Gangwon province. Total carbon stock change of litter was $0.68{\pm}0.71\;t\;C/ha$ from NFI5 (2008) to NFI6 (2013), however, there was no significant difference between the both dataset at 2008 and 2013 year. Litter carbon stock of coniferous stands was higher than deciduous stands in NFI5 (2008) and NFI6 (2013) (P<0.05). This study was limited to pilot study, so we will assess litter carbon stock using more complete data from NFI systems. It can be used as data sources for national greenhouse gas inventory report on forest sector.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2015.08a
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• pp.121-125
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• 2015

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.274-274
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• 2019

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2015.08a
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• pp.113-116
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• 2015

• Journal of Korean Society of Forest Science
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• v.95 no.5
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• pp.539-542
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• 2006

This study confirmed econometrically the causality of forest inventory and roundwood supply using Korean data. In general, forest inventory is included as explanatory variable in roundwood supply function. We checked whether each series is stationary or not before using it in the model, and determined whether the combination of the series is comtegrated. The relationship between forest inventory and roundwood supply was represented by bivariate vector autoregressive model. The causality of forest evidence of the causal relationship between change in forest inventory and change in roundwood supply in Korea. That is, change in forest inventory does not cause change in roundwood supply in Korea. It seems reasonable not to include forest inventory as explanatory variable in roundwood supply function in Korea.

• Journal of Forest and Environmental Science
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• v.30 no.2
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• pp.189-200
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• 2014

The tropical wet evergreen, tropical semi evergreen and moist deciduous forest types are projected to be impacted by climate change. In the Western Ghats region, a biodiversity hotspot, evergreen forests including semi evergreen account for 30% of the forest area and according to climate change impact model projections, nearly a third of these forest types are likely to undergo vegetation type change. Similarly, tropical moist deciduous forests which account for about 28% of the forest area are likely to experience change in about 20% of the area. Thus climate change could adversely impact forest biodiversity and product flow to the forest dependent households and communities in Uttara Kannada district of the Western Ghats. This study analyses the distribution of non-timber forest product yielding tree species through a network of twelve 1-ha permanent plots established in the district. Further, the extent of dependence of communities on forests is ascertained through questionnaire surveys. On an average 21% and 28% of the tree species in evergreen and deciduous forest types, respectively are, non-timber forest product yielding tree species, indicating potential high levels of supply of products to communities. Community dependence on non-timber forest products is significant, and it contributes to Rs. 1199 and Rs. 3561/household in the evergreen and deciduous zones, respectively. Given that the bulk of the forest grids in Uttara Kannada district are projected to undergo change, bulk of the species which provide multiple forest products are projected to experience die back and even mortality. Incorporation of climate change projections and impacts in forest planning and management is necessary to enable forest ecosystems to enhance resilience.

• Journal of Forest and Environmental Science
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• v.33 no.1
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• pp.1-7
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• 2017

In the present exploration we identified perception of forest dependent communities in relation to impact of climate change on forest ecosystem in and around Chilapatta reserve forest in northern part of West Bengal, India. Purposive sampling method was used for selection of area and random sampling method was used for selection of respondent. The data collection in this study was through questionnaire based personal in-depth interviews. Almost all the respondents (94%) were farmers and rest had occupation other than farming. Almost all the respondents perceived negative impact of climate change on forest though the level of perception varies from very low to medium (0.23-0.52) based on average perception score after assigning score to individual statements. The level of perception on impact of climate change on forest ecology and forest flora of the community is low and very low as the average perception score is 0.39 and 0.23, respectively while, it is medium (0.52) for forest fauna. Alternately their perception on decreased stream/river flow and quick drying of seasonal streams or water bodies is based on their livelihood experience as they depend on these for their domestic and irrigation water use and fish catch for family diet.