As most of the forest fires in South Korea are related to human activity, socio-economic factors are critical in estimating their probability. To estimate and analyze how human activity is influencing forest fire probability, this study considered not only environmental factors such as precipitation, elevation, topographic wetness index, and forest type, but also socio-economic factors such as population density and distance from urban area. The machine learning Maximum Entropy (Maxent) and Random Forest models were used to predict and analyze the spatial distribution of forest fire probability in South Korea. The model performance was evaluated using the receiver operating characteristic (ROC) curve method, and models’ outputs were compared based on the area under the ROC curve (AUC). In addition, a multi-temporal analysis was conducted to determine the relationships between forest fire probability and socio-economic or environmental changes from the 1980s to the 2000s. The analysis revealed that the spatial distribution was concentrated in or around cities, and the probability had a strong correlation with variables related to human activity and accessibility over the decades. The AUC values for validation were higher in the Random Forest result compared to the Maxent result throughout the decades. Our findings can be useful for developing preventive measures for forest fire risk reduction considering socio-economic development and environmental conditions.

Microbial biomass and enzyme activity are essential for ecosystem function in managed forests; however, uncertainty remains because microbial biomass and enzymatic responses to thinning highly differ with case studies. This study addressed the drivers for the site-specific responses of microbial biomass and enzyme activity to thinning. Study sites included two oak and three larch forests; each had un-thinned control, intermediate thinning (15-23% basal area reduction), and heavy thinning treatments (30-44% basal area reduction). Soil properties (temperature, water content, pH, total and inorganic nitrogen, and total carbon/nitrogen ratio), microbial biomass, enzyme (β-glucosidase, N-acetylglucosaminidase, leucyl aminopeptidase, acid phosphatase, and phenol oxidase) activity, and soil carbon storage were determined 6 years after thinning. Compared to the control, microbial biomass carbon and nitrogen were higher under the intermediate and the heavy thinning by 13.9 and 24.4% and 11.5 and 29.9% at one oak forests, respectively, and higher under the intermediate thinning by 53.7 and 70.7% at one larch forests. There were the post-thinning changes in leucyl aminopeptidase activity by -46.9% and by 150.0-210.0% at an oak and larch forest, respectively, acid phosphatase activity by 60.0% at one oak forest, and phenol oxidase activity by 355.0% at one oak forest. The effect sizes of thinning for soil properties explained 94% and 77% of variance of the effect sizes for microbial biomass and enzyme activity. Especially, the effect sizes for soil water content, NH4+, total carbon/nitrogen ratio, and temperature were the most influential. Furthermore, the effect size for soil carbon storage was parabolically related to the effect size for microbial biomass carbon (R2 = 0.66). These findings highlight that inconsistent thinning effects on soil properties varied microbial biomass and enzymatic responses to thinning, which differentiated the change in soil carbon storage across sites. Future studies should consider such inconsistencies when examining the effects of forest management.

Purpose: The purpose of this study is to synthesize the impacts of climate change on agriculture and assess the status of policies, programs and strategies to adapt small farm holders to climate change in South Asia. Design/methodology/approach: The authors collected secondary information through a desktop review of policy documents, action plans and published reports. Face-to-face interviews with policy makers, agriculture and climate experts representing the government, non-governmental organizations, international development agencies and the private sector were also conducted to validate the secondary information. Findings: The results revealed that agriculture is the dominant economic mainstay providing livelihood to over 70 per cent, employing 60 per cent of the labor force and contributing about 22 per cent of the regional gross domestic product. Climate impacts, such as floods, sea level rise and salt intrusion, increased frequency and intensity of storms, and pests combined with increasing water scarcity continue to reduce arable land, reduce yield of crops and threaten the food security of farmers. Adaptation efforts include using improved varieties of crop; changing cropping patterns and planting seasons; and water conservation techniques. However, progress remains low because of a lack of adequate technical knowledge and financial resources. Originality/value: The amount of published literature on climate change and its impact on agriculture is increasing, but there is little effort to analyze and document impacts and strategies to adapt small farm holders to climate change at a landscape level, particularly in South Asia. This study fills in this gap and will serve as a valuable source of information for those wishing to conduct research or develop adaptation strategies for any of the four countries of Bangladesh, Bhutan, India and Nepal.