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.

Thinning is a silvicultural process in which trees are both harvested selectively and systematically removed from a stand to enhance forest management and ecosystem dynamics. However, this practice is challenged by the mechanical damage to residual trees, and the nature of this damage, particularly on stand damage during mechanized row-thinning and manual selective thinning, in South Korea is unknown. Therefore, objectives of this study were to compare stand damage levels and wound characteristics between three different thinning operations: manual selective, manual row-, and mechanized row-thinning. After thinning, 12%, 15%, and 10% of the residual damaged trees were observed in manual selective, manual row-, and mechanized row-thinning, respectively. Both types of row-thinning predominantly demonstrated damages at the stem and butt region, whereas in manual selective thinning, the most of the damages occurred on the roots. Manual selective thinning exhibited a slightly larger average wound size (207 cm²) compared to mechanized row- (181 cm²) and manual row-thinning (165 cm²). The wound sizes on the stem in mechanized row-thinning were significantly higher than manual selective (p < 0.05). These results may be helpful in understanding exposure to damage among different thinning types and in managing its occurrence in future practices.

Changes in canopy structures caused by harvesting and regeneration practices can significantly alter the wind environment. Therefore, it is essential to understand the wind patterns influenced by seed tree arrangements for predicting seed dispersal by winds and ensuring the success of natural regeneration. This study aimed to identify how wind speed responds to seed tree arrangement designs with differing horizontal distances, vertical positions, and free-stream wind speeds. A wind tunnel test was conducted using pine saplings for a scale model of various seed tree arrangements, and the change in wake speed was tracked. The wake’s relative wind speed averaged 71%, ranging from 3.5% to 108.5%, depending on the seed tree arrangement, distance from saplings, and vertical position. It peaked within the patch of three seed trees compared to other arrangements and at the top canopy layer. The empirical function effectively described the wind speed reduction and recovery with distance from saplings. For instance, the minimum wind speed was reached at 0.6–2.2 times the canopy height, and a wind speed reduction of over 20% of the free-stream wind speed was maintained at a 1.6–7.6 canopy height. A negative relationship between the seed tree leaf area and the relative wind speed was observed only at the top canopy layer. This study presents empirical evidence on the patterns of wake winds induced by different types of heterogeneous canopy structures.

Natural forest regeneration offers economic, ecological, and environmental advantages over artificial regeneration; however, its application is often constrained by uncertainties in stand development and management outcomes. Pre-commercial thinning (PCT), a key assisted natural regeneration practice, is widely used to regulate stand density and improve early stand development. Nevertheless, empirical evidence remains limited regarding how post-thinning residual density influences both tree growth and operational performance in high-density naturally regenerated Pinus densiflora stands. This study evaluated three residual density treatments (RD2000, RD3000, and RD5000) following PCT in naturally regenerated pine stands with an initial density of approximately 30,000 stems ha⁻¹. Diameter at breast height, tree height, and crown area were monitored annually over three years, while thinning productivity and operational costs were quantified during treatment implementation. Residual density significantly affected both biological and operational outcomes. The intermediate residual density (RD3000) showed the most consistent growth responses, whereas the lowest residual density (RD2000) resulted in suppressed growth. The highest residual density (RD5000) achieved the highest productivity and lowest operational costs despite moderate growth performance. These results indicate a trade-off between growth performance and operational efficiency and suggest that an intermediate residual density may provide a balanced strategy for managing naturally regenerated pine stands.

This study aimed to develop and compare prognostic models (logistic regression, Cox proportional hazards, and random forest) to assess delayed mortality in pine (Pinus densiflora) following fires in Korea. Data from a 72-month monitoring of 734 trees across four fire areas were used, accounting for 19 variables: tree size, fire severity, multispectral indices, topography, and bioclimatic variables. Key predictors of mortality included diameter at breast height (DBH), bark scorch index (BSI), delta normalized burn ratio (dNBR), slope, topographic wetness index (TWI), precipitation of the warmest quarter, temperature seasonality and isothermality. The key results indicate that the random forest model was the most effective (AUC = 0.924; sensitivity = 0.892) in identifying trees at high risk of mortality. These results suggest that nonlinear approaches are effective for predicting delayed mortality in fire-damaged pines and can support rapid decision-making in post-fire forest management and restoration under increasing wildfire risk.