This study assessed the damage and the potential economic threat of pine wilt disease, which is the most common disease caused by forest-integrated pests in Korea. To estimate the rate of damage by pine wilt disease, a structural damage function was implemented. The nonlinear panel probit model and the generalized estimated equation (GEE) were used for the estimation. The estimated damage function and representative concentration pathways (RCP)8.5 data were used to predict the future damage rate by pests caused by climate change. In the assessment of the economic impact on forests, the dynamic optimization model was introduced. The concept of environmental payment was introduced to consider the economic value of non-timber benefits. For the economic analysis, three scenarios were established, i.e., no pest outbreak (baseline), pest infestation (no control), and pest infestation (prevention and control), and the forest management revenues that included the wood and non-wood materials for each scenario were compared. On the basis of the results of the analysis, a simulation was conducted to investigate the changes in forest management revenues according to changes in timber market prices, environmental payments, and climate change. The prediction results confirmed that the future damage by pine wilt disease and the extent of the damaged areas will increase as a consequence of climate change. In addition, the analysis of the economic impact showed that the increase of pest damage caused by climate change will worsen the forest management revenues. As pest damage brought on by climate change is expected to increase uncertainties and economic losses, there is a marked need to review the policies that so far have been focusing only on post-response tasks. In addition to a proper post-incident management, it is necessary to secure the sense of control and stability over the matter through the reinforcement of pre-incident management.

While a large sum of timber stock in private forests, especially broadleaved forests, has been ignored by their owners, a rising global concern about climate change and ecosystems has led to a renewed interest in natural broadleaved forest management strategies. This study establishes the forest growth model for the natural broadleaved forest of Gangwon-do based on the matrix model developed by Buongiorno and Michie. The matrix model by Buongiorno and Michie has been widely applied to study forest population dynamics, especially for uneven-aged forests. To develop an existing matrix model, our approach applies transitional probabilities of forest stands which are calibrated using National Forest Inventory data. Both long and short-term predicted simulation results show that the predicted average tree density and diameter distribution from our model are very close to the stand density and diameter distribution from observed data. Although the model simplifies reality, the results from our study confirm that our models are valid enough to predict the average stand status of the broadleaved forests in Gangwon-do.

Climate change is expected to affect the occurrence of forest pests. This study depicts a method to measure the impact of damage inflicted by a forest pest like oak wilt as a result of climate change. We determine the damage function considering the factors related to the pest damage and forecast the future damage rate under future climate change. We estimated the damage rate by using the quasi-maximum likelihood estimation (QMLE) and predicted the future damage rate by using representative concentration pathways (RCP) 8.5 data. We assessed the impact of pests on the management income and the rotation age by using a dynamic optimization model. The results show that the damage rate and the affected area from oak wilt would increase under the climate change. In addition, the economic evaluation indicates that altered climate would reduce the management returns and increase uncertainty. However, these outcomes could be alleviated by carrying out the control and prevention measures after the infection occurs.

The southern pine beetle (SPB), Dendroctonus frontalis Zimmermann, is one of the most destructive insects to pine forests in North and Central America. Historical SPB infestations have shown strong cyclical patterns and are attributed to an array of abiotic and biotic factors with climatic conditions being the dominant. Climate change has been projected to increase SPB infestations; however, its impacts on the cyclical patterns of SPB infestations remain unknown. Here, we estimated the statistical relationship between SPB infestations and climatic and other factors using generalized linear regression modeling and historical data, analyzed the cyclical patterns of SPB infestations via periodogram analysis and explored how these patterns would evolve with the projected future climate change in 11 states of the Southern United States. We found that SPB infestations intensified with increases in seasonal average temperatures and minimum winter temperatures and decreases in spring and winter precipitations. Compared to the historical SPB infestation patterns, climate change was estimated to nearly double SPB infestation frequencies although with smaller amplitudes in the region. Our findings advance the understanding of cyclical patterns of SPB infestations, especially climate change impacts on such patterns, aiding in developing and deploying future SPB management practices and strategies.

This study examined optimal harvesting decisions of multiple age-class private forests that maximize private forest owners’ utility. For this analysis, we developed two scenarios. One scenario was to maintain the harvest level currently performed in the Republic of Korea (ROK) (baseline scenario), and the other was to harvest according to the harvest prescription derived from the discrete-time utility model with a multiple age-class forest (optimization scenario). For the baseline scenario, the cohort component approach was applied to predict changes in the forest’s age structure under the given harvest level. For the optimization scenario, we applied a discrete-time utility model that can describe the consumption and cutting behavior of private forest owners who manage a multiple age-class forest. Then, we compared the changes of the timber supply level and forest structure dynamic by scenarios. The results showed that current harvesting in ROK is not at its optimal level. The baseline scenario results showed that if the current level of harvesting is maintained, a total of 1,315,000 m³ of soft wood will be supplied annually. However, the average annual wood supply will increase to 11,522,000 m³ under the maximized utility scenario. In terms of timber self-sufficiency, if all domestic wood produced is supplied as materials, the supply level from the optimization scenario will meet the government’s policy goal of a 30% timber self-sufficiency rate. However, if the baseline scenario is maintained, supply shortages can be expected by 2050.