Natural regeneration in forest management, which relies on artificial planting, is considered a desirable alternative to reforestation. However, there are large uncertainties regarding the natural regeneration processes, such as seed production, seed dispersal, and seedling establishment. Among these processes, seed dispersal by wind must be modeled accurately to minimize the risks of natural regeneration. This study aimed to (1) review the main mechanisms of seed dispersal models, their characteristics, and their applications and (2) suggest prospects for seed dispersal models to increase the predictability of natural regeneration. With improving computing and observation systems, the modeling technique for seed dispersal by wind has continued to progress steadily from a simple empirical model to the Eulerian-Lagrangian model. Mechanistic modeling approaches with a dispersal kernel have been widely used and have attempted to be directly incorporated into spatial models. Despite the rapid development of various wind-dispersal models, only a few studies have considered their application in natural regeneration. We identified the potential attributes of seed dispersal modeling that cause high uncertainties and poor simulation results in natural regeneration scenarios: topography, pre-processing of wind data, and various inherent complexities in seed dispersal processes. We suggest that seed dispersal models can be further improved by incorporating (1) seed abscission mechanisms by wind, (2) spatiotemporally complex wind environments, (3) collisions with the canopy or ground during seed flight, and (4) secondary dispersal, long-distance dispersal, and seed predation. Interdisciplinary research linking climatology, biophysics, and forestry would help improve the prediction of seed dispersal and its impact on natural regeneration.

High temperatures and droughts following winter dormancy can negatively affect seedling growth and mortality. An open-field experiment was conducted to study the growth and mortality of Larix kaempferi seedlings in response to spring warming and drought treatments and to determine whether seedlings could regain their growth capability once the treatments were discontinued. In May 2020, 1-year-old seedlings were exposed to four treatments: control, warming-only, drought-only, and the combined warming and drought. Drought treatment reduced the seedling height and root collar diameter and increased the mortality rate. The combined warming and drought treatments had the highest mortality rates, followed by the drought, control, and warming treatments. However, after the cessation of the treatments, the combined warming and drought treatments increased seedling height, root collar diameter, and individual seedling biomass because the high mortality rate relaxed competition among seedlings. This suggests that the effects of low competition on the surviving seedlings may mitigate the negative effects of warming and drought on seedling growth. Our study demonstrates that despite the high mortality and decreased growth during the treatment period, seedlings subjected to combined high temperature and drought stress showed short-term high levels of growth compared to seedlings subjected to a single stress.

Biogeochemical models use estimates of carbon (C) and nitrogen (N) turnover times for the future projection of global forest C and N stocks, but unexplained variation in the C and N turnover times is causing considerable uncertainty. This study aimed to estimate C and N turnover times of South Korean forests and explain their variation with forest type, temperature, precipitation, stand age, and ecosystem C:N ratio. We used the balance method and data‐model fusion to estimate the C and N turnover times. Data‐model fusion was used to integrate the National Forest Inventory data (2011–2020) with a biogeochemical model, Forest Biomass and Dead organic matter Carbon and Nitrogen (FBD‐CAN). The N turnover time (376–499 years) was ∼45 times longer than the C turnover time (9–10 years). Forest type had no substantial effects on the C and N turnover times. However, the C and N turnover times were positively correlated with stand age and ecosystem C:N ratio, and negatively correlated with temperature. Overall, ecosystem C:N ratio, stand age, temperature, and precipitation explained 45%, 15%, 12%, and 3%, respectively, of the total variation of the C and N turnover times. These results contribute to the understanding and prediction of forest C and N changes in a changing world and highlight the importance of considering C:N ratio for reliable estimation of the C and N turnover times.

Forests mitigate climate change by absorbing CO₂. However, N₂O emissions in forests, which has 298 times larger global warming potential than CO₂, can diminish the climate mitigation role of forests. Thus, it is crucial to project not only CO₂ absorption but also N₂O emissions in forests to provide a scientific basis for the 1.5 °C Paris Agreement goal. This study used a biogeochemical model, called FBD-CAN, to project CO₂ absorption and N₂O emissions of South Korean forests from 2021 to 2080 under three climate scenarios, including the current climate, Representative Concentration Pathway (RCP) 4.5, and RCP 8.5. From 2021 to 2080, CO₂ absorption decreased from 5.0 to 1.4 Mg CO₂ ha^—1 year^—1 under the current climate with the aging of forests, while N₂O emissions increased from 0.25 to 0.33 Mg CO₂ eq. ha^—1 year^—1. Climate change accelerated the decreasing trend in CO₂ absorption and the increasing trend in N₂O emissions. The subalpine region had a faster decreasing trend in CO₂ absorption than the central and southern regions due to its older stand age. These findings provide scientific references for future greenhouse gas reduction plans and broaden our knowledge of the impacts of climate change on the climate mitigation role of forests.

Urban trees grow in diverse environments where site conditions and human management may influence their growth patterns. However, few allometric equations (AEs) have been developed for urban trees, and the effects of environmental variations across urban land use categories on tree biomass remain largely unexplored. Therefore, this study developed urban land-use-specific AEs for major urban tree species in South Korea. We selected eight major urban tree species groups (at genus level), harvested 201 trees, and non-destructively measured the stem volumes of 1995 trees using a laser dendrometer. Species-specific and generalized AEs to estimate stem volume were developed under three urban land use categories: street trees, urban parks, and others. The results indicated that differences in stem volume across urban land use categories varied by species, with street trees generally showing smaller stem volumes. Furthermore, due to the high variation in stem volume within species, sampling designs that encompass diverse size distributions are necessary when developing AEs for urban trees. Our findings indicate that various factors in urban environments influence tree volume and considering these differences is essential for improving biomass estimation accuracy.

Humans have affected the carbon (C) and nitrogen (N) cycles in forests; however, the quantification of the responses of forest C and N balances to human activities is limited. In this study, we have quantified the impacts of the long-term national forest rehabilitation plan and the contribution of the increase in air temperature, CO₂ concentration, and N deposition on the C and N balances of the South Korean forests during 1973–2020 by using a biogeochemical model. During the simulation period, the C balance increased from 0.2 to 4.3 Mg C ha⁻¹ year⁻¹, and the N balance increased from 0.2 to 17.4 kg N ha⁻¹ year⁻¹. This resulted in the storage of 825 Tg C and 3.04 Tg N by the whole South Korean forests after the national forest rehabilitation plan. The increase in air temperature, CO₂ concentration, and N deposition contributed −11.5, 17.4, and 177 Tg C to the stored C stock, respectively, and −25.4, 8.90, and 1807 Mg N to the stored N stock, respectively. This study provides references for future forest rehabilitation efforts and broadens our knowledge on the impacts of human-induced environmental changes on the C and N balances of forests.