Search

Loss of canopy cover by forest harvesting generally increases the average surface runoff volume and sediment. Selective cutting (single and group selection method) is the most usual forest harvesting method in the Hyrcanian forests in the north of Iran. The purpose of this study is to find the effect of selective logging technique on the hydrological behavior of runoff and sediment in the Kheyrud forests located in northern Iran over 1 year. Four treatments were implemented: natural forest without harvesting (C), forest with selective harvesting (H) and area without canopy cover (WC) and skid trail (S). Three types of data were measured in each plot including soil chemical and physical properties, runoff and sediment load after each rainfall. The results indicate significant differences ( P ≤ 0.05) in runoff generation and sediment production with respect to the treatments cover. The runoff in all treatments showed relatively similar response to rainfall, while the highest runoff and sediment were observed in skid trails, and the area without canopy cover (1.13 and 0.62 mm, and 1.2 and 0.51 g m), averagely. In contrast, the natural forest without harvesting and the forest with selective harvesting treatments exhibited the lowest amounts of runoff (0.2 and 0.44 mm) and sediment (0.1 and 0.17 g m), averagely. Implementation of low logging technique was useful to control the effects of logging on the runoff and sediment yield. [ABSTRACT FROM AUTHOR]

Forest roads are important for adequate management of natural resources, but they are also a dominant contributor of sediment to forest streams and water pollution. This study measured road sediment concentration from forest roads to determine the impact of rainfall intensity and cutslope types on sediment concentration in the Patom district of northern Iran. Two 110 m road segments with variable soil and rock fragment cover exposed at the cutslopes were studied. Seven rainfall and corresponding runoff events were measured in 1-liter bottle samplers every 10 minutes at the outlet of cross sectional culverts, and from two 3 m² plots on the roadbeds adjacent to each cutslope. A statistically significant difference at the 95% confidence level between two cutslope types and rainfall intensity on sediment concentration was determined from the field data based on nonparametric tests, though no statistically significant difference in the concentration of sediment between the two roadbeds plots were found. The average of sediment concentration of soil trench and the rock fragment cover cutslopes were 60.3 and 46.8 g/l, respectively. The results reported here should help forest road managements to improve the understanding of cutslopes erosion and sediment production from forest roads and to employ suitable methods to reduce sediment production. [ABSTRACT FROM AUTHOR]

Forest roads are important for adequate management of natural resources, but they are also a dominant contributor of sediment to forest streams and water pollution. This study measured road sediment concentration from forest roads to determine the impact of rainfall intensity and cutslope types on sediment concentration in the Patom district of northern Iran. Two 110 m road segments with variable soil and rock fragment cover exposed at the cutslopes were studied. Seven rainfall and corresponding runoff events were measured in 1-liter bottle samplers every 10 minutes at the outlet of cross sectional culverts, and from two 3 m² plots on the roadbeds adjacent to each cutslope. A statistically significant difference at the 95% confidence level between two cutslope types and rainfall intensity on sediment concentration was determined from the field data based on nonparametric tests, though no statistically significant difference in the concentration of sediment between the two roadbeds plots were found. The average of sediment concentration of soil trench and the rock fragment cover cutslopes were 60.3 and 46.8 g/l, respectively. The results reported here should help forest road managements to improve the understanding of cutslopes erosion and sediment production from forest roads and to employ suitable methods to reduce sediment production. [ABSTRACT FROM AUTHOR]

An efficient and low-cost transportation network is necessary for sustainable management. Roading and log skidding are the most expensive and destructive operations in forest environment, unless carefully planned and evaluated. A transportation network has to be assessed and optimized to minimize the total cost of road construction and its environmental impact. The aim of this study was determining the optimum forest road network density, and evaluating the quantity and quality of the existing forest road network. In order to determine the optimum forest road network density, skidding cost, road construction and maintenance costs, and harvesting volume in each compartment were considered. Then optimum skidding distance was calculated with regard to optimum road density and total correction factors. The relative openness and efficiency coefficient of the existing forest road network were determined for the calculated optimum skidding distance, using ArcGIS. The results showed that the optimum road density, relative openness and road network efficiency coefficient were 21.5 m ha-1, 90% and 32%, respectively. As a result, when the quality of a forest road network has to be evaluated, road network efficiency coefficient is more efficient than relative openness, that per se cannot be considered as an appropriate indicator. [ABSTRACT FROM AUTHOR]

Abstract: Forest vegetation is known to enhance the stability of slopes by reinforcing soil and increasing its shear resistance through root system. The effects of root reinforcement depend on the morphological characteristics of the root system, the tensile strength of single roots, and the spatial distribution of the roots in soil. In the present study the results of research carried out in order to evaluate the biotechnical characteristics of the root system of Persian Ironwood (Parrotia persica), in northern Iran are presented. Profile trenching method was used to obtain root area ratio (RAR) values for uphill and downhill sides of the individual trees. For each species, single root specimens were sampled and tested for their tensile strength. It was found that root density generally decreases with depth according to an exponential law. Maximum RAR values were located within the first 0.1m, with maximum rooting depth at about 0.65m. RAR values ranged from 0.001% at lower depths to 1.39% near the surface, at upper 0.1m depth. Significant differences of RAR values, rooting depth and root cohesion between uphill and downhill were observed, however, the differences were not significant for number of roots (ANCOVA). Downhill profiles had higher RAR values, rooting depth and root cohesion. In general, root tensile strength tends to decrease with diameter according to a power law, as observed by other researchers. Downhill roots were significantly stronger in tensile strength than uphill ones. Inter-species variation of tensile strength in downhill roots was also observed. The resulting data were used to evaluate the reinforcing effects in terms of increased shear strength of the soil, using Wu/Waldron Model. The root reinforcement provided by Persian Ironwood is about 46.0kPa in the upper layers and 0.3kPa in the deeper horizons. The results of Spearman test revealed a significant correlation between RAR and c r and that best followed by a power law. The results presented in this paper contribute to expanding the knowledge on biotechnical characteristics of Persian Ironwood on slope reinforcement. [Copyright &y& Elsevier]

Forest road planning with the available tools, e.g. PEGGER and GIS, still requires a lot of time of an expert, and the designed roads are not guaranteed to be efficient in terms of the cost or suitability of the road. In this article, we propose a novel Genetic Algorithm (GA) based method for forest road planning. To do so, each road is represented as a sequence of fixed and variable (control) points. A novel objective (fitness) function is defined based on the length, gradient, and suitability of the roads (individuals). The proposed algorithm is applied to the Arasbaran forest area and the resulted roads are compared with PEGGER-designed roads regarding length, Bachmund index, accessibility, and suitability. The results clearly show the power of the proposed GA algorithm in reducing computation time, road construction costs, and environmental impacts compared to the common road planning approaches. [ABSTRACT FROM AUTHOR]

Purpose: Root reinforcement is a key parameter in slope stability analysis, but is difficult to be effectively included at the hillslope-scale due to the complexity of root systems. As a result, hillslope-scale analysis of root reinforcement still requires high levels of field validation to account for variability in root properties as a function of topography, ecology, and soil properties. This study investigated root distributions and estimated root reinforcement at an unprecedent scale of field and laboratory measurement, using this to understand differences among species (Carpinus betulus and Fagus orientalis), diameter at breast height (DBH), slope position, altitude, vertical and horizontal distances from trees in Hyrcanian temperate forests, Iran. Method: We excavated 1080 profile trenches 0.5 m wide, 1.0 m length, and 1.0 m deep upslope and downslope from trunks of C. betulus and F. orientalis with a range of DBH (7.5–82.5 cm) at three different altitudes (400, 950, and 1300 m a.s.l.). We assessed the effects of different forest coverage on slope stability via a 3-D limit equilibrium-based slope stability model where parameter uncertainties are explicitly accounted for using Monte Carlo Simulation. Results: The Root Area Ratio (RAR) of C. betulus is always higher than F. orientalis. RAR of F. orientalis is higher in upslope, whereas RAR of C. betulus is similar in both positions. Higher RAR contributed to higher root reinforcements for C. betulus when comparted with F. orientalis. Additionally, after accounting for DBH influences, altitude significantly affects the root reinforcement of C. betulus. The results of slope stability analysis showed that the most stabilizing species is C. betulus in a mature growth condition, maintaining an instability probability of ~ 18.3%. Conclusion: C. betulus is preferable to F. orientalis for increasing slope stability. Forest managers should consider this outcome when developing strategies for silvicultural treatment and reforestation projects in mountainous areas of temperate regions. [ABSTRACT FROM AUTHOR]

Although selection cutting has many advantages, its potential for damage to residual trees is a major challenge of forest management. The present study evaluated damage to residual trees during manual felling and cable-skidder logging operations in 18 instances of selection cutting in the Caspian forests of Iran. Data was collected from 100 m × 100 m systematic sample plots (0.1 ha) at each logging site. Harvest intensity ranged from 3.8 to 11 trees ha −1 and it averaged 7.3 trees ha −1 . Damage to residual trees was 10.5–23.6% with an average of 16.9%. There was a positive and significant correlation between amount of damage and harvest intensity ( R 2 = 0.65, P < 0.01). The multiple regression analyses also indicated that there were statistically significant relation ( R 2 = 0.77, P < 0.01) between amounts of trees damage and independent variables (harvest intensity, ground slope and stand density). Injury to the bottoms of tree boles 100–200 cm 2 in size was the most common types of damage. Damage was concentrated in small diameter trees (DBH < 40 cm). Most logging damage occurred during winching. Results suggest adherence to two silvicultural practices: (1) limit harvest intensity to 6 trees ha −1 , (2) limit selection cutting in slopes, less than 50%. Additional operational suggestions are implementation of felling direction and avoid log extraction through dense stands. [ABSTRACT FROM AUTHOR]

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 R2 values 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. Core Ideas: 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. [ABSTRACT FROM AUTHOR]

Understanding the physical and especially mechanical properties of forest soils is very important in forest engineering operations including road construction and exploitation. Unconfined compressive strength (UCS) is one of the most important mechanical properties for evaluating the strength of adhesive soils in many engineering projects including forest roads. Measuring the USC of soil in the laboratory and in situ is difficult, time-consuming, and costly, so it is essential to explore a rapid, low-cost, and non-destructive method. The aim of this study was to estimate the UCS of forest roads using spectroscopy. The applied support vector machine (SVM) method determined the soil moisture classes (i.e., 14%, 25%, 31%, and 36%) with R2 of 0.98. Two methods of partial least squares regression (PLSR) and the normal difference index (NDI) were used to estimate the UCS at different moisture classes. The results showed that the NDI performed better than the PLSR to estimate the USC at four different moisture classes of 14% (R2 = 0.8, RMSE = 19.36, RPD = 2.61), 25% (R2 = 0.78, RMSE = 16.06, RPD = 1.64), 31% (R2 = 0.82, RMSE = 11.2, RPD = 2.28), and 36% (R2 = 0.83, RMSE = 7.49, RPD = 2.41). Also, a sampling interval method was applied to reduce spectral dimensionality and processing time. The sampling interval of 16 nm was selected using a genetic algorithm. Finally, the UCS was estimated at maximum soil moisture using the simple regression model (SRM) based on the results of NDI. Based on this current study, it has been found that using spectroscopy to estimate the UCS of soil could be considered an alternative method for developmental operations in identifying the UCS of soil due to the costly and time-consuming conventional laboratory methods. [ABSTRACT FROM AUTHOR]

• The potential of previous spectral indices to predict Atterberg limits was confirmed. • Spectral indices were linked to the soil parameters with PLS and PLS-BPNN. • A range of R2 (0.62–0.99) found between Atterberg limits and spectral reflectance. • We tested non-linear neural net vs. linear PLSR to link spectra to soil properties. Conventional methods for the determination of Atterberg limits based on laboratory tests are time-consuming. Reflectance spectroscopy which is fast and cost-effective has been reported as an alternative method for estimating Atterberg limits. To assess the efficiency of the method, 60 forest soil samples were measured by visible-near infrared reflectance spectroscopy (VNIR) within the range of 350–2500 nm. The Savitzky-Golay (SG) smoothing method for spectral data was used to reduce signal noise and the first derivative reflectance (DR) was applied to accentuate the features and assemble the data for use in the modeling process. In this study, raw reflectance (R) and first derivative reflectance (DR) data were used to estimate Atterberg limits. All two-band combinations of three types of spectra (ratio index, normalized difference index and difference index) as well as PLS and PLS-BPNN were calculated to extract optimum waveband combination and calibrations between Atterberg limits and reflectance spectra. The correlation coefficients between Atterberg limits and reflectance spectra indicated both positive and negative correlation at various wavelengths across the spectrum. The highest correlation for liquid limit (r = −0.86), plastic limit (r = −0.76) and plasticity index (r = −0.7) was found at 1921, 1938 and 1913 nm, respectively. In addition, the results showed the spectral indices technique as a good method for estimating soil plasticity and improving the prediction accuracy of Atterberg limits. In the current study, PLS and PLS–BPNN were also used to develop the calibration models for estimating Atterberg limits using R and DR. The results demonstrated that the prediction accuracy of PLS-BPNN for both R and DR was higher than that of PLS. Correlation coefficients between shrinkage limit (SL) and reflectance spectra showed weak correlation, and overall reflectance had the same correlation. The results represented that this method could be used to estimate soil plasticity properties quickly, non-destructively, and with minimal sample preparation and high accuracy. These advantages may be more important, especially when a huge number of samples should be tested and analyzed within a short period of time. [ABSTRACT FROM AUTHOR]