During forest operations, canopy removal results in the soil surface being vulnerable to deformation, negatively impacting soil fertility and water quality. This study utilized unmanned aerial vehicle (UAV) photogrammetry to accurately detect soil surface deformation (SSD). Two-dimensional images were safely collected on a steep slope without real-time kinematics by conducting vertically parallel flights (VPFs). A high-resolution digital surface model (DSM) with a <3 cm resolution was acquired for precise SSD detection. Using DSM of difference (DoD), SSDs were calculated from DSMs acquired in June, July, September, and October 2022. By checking spatial distances at ground control points, errors of DSM alignments were confirmed as only 3 cm, 11.1 cm, and 4 cm from July to June, September to June, and October to June, respectively. From the first month of monitoring, erosion and deposition of approximately 7 cm and 9 cm, respectively, were detected at validation points (VPs). However, from total monitoring, cumulative SSD was assessed as having deposition tendencies at all VPs, even compared to ground truths. Although UAV photogrammetry can detect SSDs, spatial distortion may occur during UAV surveys. For vegetation growth issues, UAV photogrammetry may be unable to capture data on the soil surface itself.

Machine traffic during timber harvesting operations induces soil compaction, which is particularly evident in the formation of ruts. Visual inspection of rut formation is labor-intensive and limits the volume of data that can be collected. This study aims to contribute to the limited knowledge base regarding the extent of soil physical disturbance caused by machine traffic on steep slopes and to evaluate the utility of LiDAR and UAV photogrammetry techniques. The selected traffic trails included single-pass uphill, single-pass downhill, three-pass round trip, and five-pass round trip trails, with an average slope of 70.7%. Traditional methods were employed to measure rut depth using a pin board and to assess soil bulk density (BD) and soil porosity (SP) from soil samples. The results revealed that the average rut depth was 19.3 cm, while the deepest ruts were observed after a single pass (uphill: 20.0 cm; downhill: 22.7 cm), where BD and SP showed the most significant changes. This study provides a rare quantitative evaluation of the applicability of remote sensing methods in forestry by comparing surface height data collected via a pin board with that derived from a Mobile LiDAR System (MLS) and UAV photogrammetry using structure-from-motion (SfM). When compared to pin board measurements, the MLS data showed an R² value of 0.74 and an RMSE of 4.25 cm, whereas the SfM data had an R² value of 0.62 and an RMSE of 5.27 cm. For rut depth estimation, SfM (16.0 cm) significantly underestimated values compared to the pin board (19.3 cm) and MLS (19.9 cm). These findings not only highlight the potential and limitations of remote sensing methods for assessing soil disturbance in steep forest environments but also contribute to addressing the knowledge gaps surrounding the effects of soil compaction in steep terrain.

Pollutants can exist in the soil for a long time and alter the bacterial community. Using lubricants to prevent the wear of chainsaw blades is necessary for thinning activities and wood harvesting. We investigated the influences of soil contamination with chainsaw lubricants on soil bacterial communities. Bio-oil, mineral oil, and recycled oil were scattered on each treatment to investigate variations in soil bacterial structure during treated periods using the Illumina MiSeq sequencing platform. The results obtained were 5943 ASVs, 5112 ASVs, and 6136 ASVs after treatment at one month, six months, and twelve months, respectively. There was a significant difference in Shannon and Simpson indices between treatments and controls. A total of 46 bacterial genera with an average relative abundance of more than 1.0% were detected in all soil samples. Massilia was the most common genus detected in control at one month, with an average relative abundance of 14.99%, while Chthoniobacter was the most abundant genus detected in bio-oil, mineral oil, and recycled oil treatments at one month, with an average relative abundance of 13.39%, 14.32%, and 10.47%, respectively. Among the three chainsaw lubricants, bio-oil and mineral oil had fewer impacts than recycled oil. The abundances of several functional bacteria groups in the bio-oil treatment were higher than in other treatments and controls. Our results indicated that different chainsaw lubricants and their time of application affected the soil bacterial community composition.

Mechanized timber harvesting is cost efficient and highly productive. However, mechanized harvesting operations are often associated with several environmental problems, including soil compaction and disturbance. Soil compaction impedes air circulation between the soil and atmosphere, which in turn results in increased concentrations of CO₂ within soil pores. In this study, we investigated the impact of forest machine traffic on soil conditions to determine soil CO₂ efflux (F_c), and soil CO₂ concentrations (S_c). Field measurements included soil bulk density (BD), soil temperature (ST), soil water content (SWC), F_c, and S_c over a 3-year period at a specific thinning operation site (Hwacheon-gun) in the Gangwon Province of Korea. To assess the soil impacts associated with machine traffic, we established four machine-treatment plots (MT) characterized by different geographical and traffic conditions. The results revealed that BD, S_c, and SWC increased significantly on the disturbed track areas (p < 0.05). Furthermore, reduced soil F_c values were measured on the soil-compacted (machine disturbed) tracks in comparison with undisturbed (control) areas. Variations in BD, SWC, and S_c were significantly different among the four MT plots. Additionally, in comparison with undisturbed areas, lower F_c and higher S_c values were obtained in compacted areas with high soil temperatures.

Severe droughts and changing precipitation patterns could alter the biogeochemical properties of the soil, affecting soil carbon cycles in forest ecosystems. A throughfall exclusion (TFE) experiment was conducted in a continental climate coniferous stand in Gangwon Province, Korea, to examine the effects of excluding rainfall on total soil respiration (SR), heterotrophic soil respiration (HR), autotrophic soil respiration (AR), sapling diameter growth, and soil bacterial communities from July 2016 to October 2017. The soil water content (SWC) was significantly decreased by the exclusion of the throughfall, resulting in changes in the bacterial communities, and subsequently a decrease in HR. Although AR did not present significant differences between the control and TFE plots, the rate of sapling growth was significantly lower in the TFE plots compared with that in the control plots. An exponential function relating SR to soil temperature accounted for 0.61% and 0.82% of the variance in SR in the control and TFE plots, respectively (Q₁₀ = 2.48 and 2.86, respectively). Furthermore, a multivariate nonlinear model based on soil temperature and SWC explained 0.89% and 0.88% of the variance in SR in the control and TFE plots, respectively. When soil temperature was high, SR showed high fluctuations due to SWC variation. However, when SWC was low, we detected relatively small fluctuations in SR due to soil temperature. The results of this study show that the activity of soil microbial and root respiration during the growing season may be lower under future drought conditions.