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A thorough quantification of soil chemical properties is essential for assessing the engineering properties of forest soils for road design, construction, and maintenance. Here, we investigate the applicability of visible–near‐infrared (Vis–NIR) spectroscopy in conjunction with advanced statistical analysis for estimation of soil chemical properties. Sixty forest soil samples were collected and analyzed for pH, electrical conductivity (EC), CaCO3, organic matter (OM), and cation exchange capacity (CEC) with established laboratory methods. The spectral measurements were performed with a Vis–NIR spectrometer within a range of 350–2,500 nm. To estimate abovementioned soil properties from reflectance spectra, advanced statistical techniques including partial least squares regression (PLSR), hybrid partial least squares and artificial neural networks (PLS–DI–ANN) models, hybrid partial least squares and adaptive neural fuzzy inference system (PLS–DI–ANFIS) models, as well as narrow band spectral indices were applied. The obtained results ​​indicate that the PLS–DI–ANFIS models show great potential for the estimation of pH, EC, OM, and CEC from reflectance spectra and their first derivatives, exhibiting higher R2values and lower RMSE than the other investigated models. The estimation accuracy for CaCO3, however, was low for all applied methods. The results confirm that Vis–NIR spectroscopy may be applied as a rapid and cost‐efficient alternative to standard chemical soil analysis techniques, aiding forest road design, construction, and maintenance. Vis–NIR spectroscopy and machine learning improve soil chemical property estimation.The combined PLS–DI–ANFIS analysis provides the most robust estimation model.Vis–NIR spectroscopy aids the design, construction, and maintenance of forest roads.

ABSTRACTForest workers encounter many health-related problems due to their harsh working conditions. This study focused on the evaluation of the physical workload of tree fellers during clearcut operations in a pine plantation forest in northern Iran by means of heart rate measurements. Anthropometric and personal data of the subjects such as age, body mass index (BMI), work experience, and health problems were also collected. The subjects were also asked to assess their perceived level of fatigue by means of the Swedish Occupational Fatigue Inventory. Activity sampling was used to record the physical workload of 13 subjects during a working day of 8 h for each one of them by means of a Polar Electro H10 heart rate sensor. The collected data were used for the calculation of heart rate indices that determine the strain of the subjects. The results showed that the mean level of physical workload was 43.54% of the relative heart rate (HRR) which corresponds to heavy work. The workers assigned most of the effective work time to tree processing (39.78%), back cut (18.6%), and undercut (12.07%). The highest mean heart rates (HRwork) were measured during the work elements of tree processing (117.7 bpm), back cut (115.6 bpm), and undercut (114.8 bpm). The study results also showed that the number of harvested trees and the average tree diameter at breast height exerted a significant impact on HRR and the BMI class on HRwork. Furthermore, age class was negatively correlated to net productivity.

Although the effects of different vegetation cover on soil reinforcement due to their roots have been addressed in the literature, there remains a lack of assessment and comparison of root biomechanical properties of hardwood and softwood plantations for similar site conditions. To address this gap, two adjacent hillslopes with similar site conditions but different forest plantations, a Picea abies (softwood) and a Fraxinus excelsior (hardwood), were selected to assess and compare their effectiveness in protecting sloping soils. The profile trench method was used to obtain root distribution from both upslope and downslope sides of tree samples and on each side at two horizontal distances from the tree stems. Root tensile strength of live root samples was measured using a standard Instron Universal Testing Machine. A modified Wu and Waldron root reinforcement model was used to calculate root cohesion for the two plantations. The root tensile strength for was significantly greater for softwood than for hardwood trees (19.31 ± 2.64 vs 16.98 ± 1.01 MPa). Interestingly, the number of roots, root area ratio values, and the root tensile strength of the two species did not significantly differ between the upslope and downslope sides of trees. The results also showed a higher root cohesion for the softwood than the hardwood species (1.56 ± 0.34 vs 1.03 ± 0.21 kPa). In addition, softwood trees extended their contribution to soil protection to a larger horizontal distance compared with hardwood. However, our findings generally revealed that the values of root cohesion of both studied plantations were surprisingly lower than those found in earlier reports.

Forest roads are an essential infrastructure and prerequisite in the management of forested areas. Sustainable management of roads depends on regular and timely forest road maintenance. A road inventory is the first step of forest road management, control of construction standards, and maintenance operation; and GIS can be a powerful tool for acquirement, analysis, and management of data in road management. The purpose of this study was to obtain the required information to assess existing road standards by way of a road inventory and use the results to schedule maintenance operations. To achieve this goal, a part of the road network from Kaleibarchay watershed in Arasbaran forest was inventoried, and cross sectional components were measured and compared to standard ones. Culverts along the road were also investigated. Road components, problems of surfacing, and slope stability were analyzed in ArcGIS9.3software. The results showed significant differences between existing parameters and standard ones, and the exceptions were side ditch depth and roadbed. The results of culvert assessment showed that the road segment only had one culvert. According to the results, cross-slope has the highest consistency with standard values. Around a quarter (25.19%) of the road length had no signs of surfacing problems. Among surfacing problems, rutting had the highest abundance and cut slope had more stability problems than fill slope. In order to have better management of drainage systems, we suggested some places for installing new cross drains including culverts and fords. The results of this research can be used in developing effective maintenance operations for the road in this study, and also as a model to study and collect required inventory data and in applying GIS to forest roads management.

Abstract: Slope is a complex environmental factor that can subject plants to a number of mechanical stresses. The anchorage of roots and improvement of slope stability mainly depend on specific properties of root systems, such as root distribution. In the present study, 24 trees (from three species) growing on gentle slopes (10–20°) were randomly chosen for root distribution analysis. The profile trenching method was used to obtain root characteristics. The findings indicated that root area ratio (RAR) decreased with depth and that maximum RAR values were observed in the upper layers; RAR values were between 0.0004% and 6.6444%. Average RAR values were not statistically different in upslope and downslope layers except in one case. The dot grid method (100 × 150 mm) usually overestimated the RAR values. The amount of roots decreased with depth following a power law. About 50% and 90% of roots were located in the first 30 and 60 cm depths, respectively. Results of analysis of covariance (ANCOVA) showed a significant effect of diameter at breast height (DBH) on total RAR but not on the total number of roots. About 70% of roots had diameter of less than 10 mm. Spearman’s correlation showed significant negative correlation between the total number of roots and the amount of N, P, and K elements, and a positive correlation between DBH and RAR. The results serve to develop understanding of the biotechnical characteristics of root systems of Caspian species.

AbstractSlope is a complex environmental factor that can subject plants to a number of mechanical stresses. The anchorage of roots and improvement of slope stability mainly depend on specific properties of root systems, such as root distribution. In the present study, 24 trees (from three species) growing on gentle slopes (10–20°) were randomly chosen for root distribution analysis. The profile trenching method was used to obtain root characteristics. The findings indicated that root area ratio (RAR) decreased with depth and that maximum RAR values were observed in the upper layers; RAR values were between 0.0004% and 6.6444%. Average RAR values were not statistically different in upslope and downslope layers except in one case. The dot grid method (100 × 150 mm) usually overestimated the RAR values. The amount of roots decreased with depth following a power law. About 50% and 90% of roots were located in the first 30 and 60 cm depths, respectively. Results of analysis of covariance (ANCOVA) showed a significant effect of diameter at breast height (DBH) on total RAR but not on the total number of roots. About 70% of roots had diameter of less than 10 mm. Spearman's correlation showed significant negative correlation between the total number of roots and the amount of N, P, and K elements, and a positive correlation between DBH and RAR. The results serve to develop understanding of the biotechnical characteristics of root systems of Caspian species.