Next Article in Journal
Using Virtual Reality to Assess Landscape: A Comparative Study Between On-Site Survey and Virtual Reality of Aesthetic Preference and Landscape Cognition
Next Article in Special Issue
Soil Disturbance and Recovery after Coppicing a Mediterranean Oak Stand: The Effects of Silviculture and Technology
Previous Article in Journal
A Publicly Available Cost Simulation of Sustainable Construction Options for Residential Houses
Previous Article in Special Issue
Experimental Study Based on Game Theory on the Private, Voluntary Supply Mechanisms of Goods for Forestry Infrastructure from the Perspective of Quasi-Public Goods
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 12
Issue 7
10.3390/su12072874
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Soil Recovery Assessment after Timber Harvesting Based on the Sustainable Forest Operation (SFO) Perspective in Iranian Temperate Forests

by
Hadi Sohrabi
1,
Meghdad Jourgholami
1,
Mohammad Jafari
2,
Naghi Shabanian
3,
Rachele Venanzi
4,5,*,
Farzam Tavankar
6 and
Rodolfo Picchio
4
1
Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj 999067, Alborz, Iran
2
Department of Reclamation of Arid and Mountainous Regions, Faculty of Natural Resources, University of Tehran, Karaj 999067, Alborz, Iran
3
Department of Forestry, Faculty of Natural Resources, University of Kurdistan, Khanagah Campus, Sanandaj 66177-1-5175, Iran
4
Department of Agricultural and Forest Sciences, University of Tuscia, 01100 Viterbo, Italy
5
Department of Land, Environment, Agriculture and Forestry, Università degli Studi di Padova, 35020 Legnaro, Padova, Italy
6
Department of Forestry, Khalkhal Branch, Islamic Azad University, Khalkhal 56817-31367, Iran
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(7), 2874; https://doi.org/10.3390/su12072874
Submission received: 12 March 2020 / Revised: 31 March 2020 / Accepted: 1 April 2020 / Published: 3 April 2020
(This article belongs to the Special Issue Technologies, Applications and Assessments for Proper Sustainable Forest Operations (SFO))
Browse Figures
Versions Notes

Abstract

:
Minimizing the impact of timber harvesting on forest stands and soils is one of the main goals of sustainable forest operation (SFO). Thus, it is necessary to make an accurate assessment of forest operations on soil that is based on the SFO perspective. The present study was conducted according to SFO principles to investigate the time required for the natural recovery of soil after disturbance by skidding operations in some Iranian forests. The physical, chemical, and biological properties of soil found in abandoned skid trails from different time periods were compared with undisturbed forest soils. The soil bulk density, the penetration resistance, and the microporosity of a 25-year-old skid trail were 8.4–27.4% and 50.4% greater, and the total porosity, macroporosity, and soil moisture were 1.9–17.1% and 4.6% lower than the undisturbed area. In a 25-year-old skid trail, the values of pH, Electrical conductivity (EC), C, N, available P, K, Ca, and Mg, earthworm density, and biomass were lower than in the undisturbed area, and the C/N ratio value was higher than in the undisturbed area. High traffic intensity and slope classes of 20–30% in a three-year-old skid trail had the greatest impact on soil properties. In order to have sustainable timber production, SFO should be developed and soil recovery time should be reduced through post-harvest management operation.

1. Introduction

One of the main goals of sustainable forest operation (SFO) is to comply with the forest operations ecology [1,2,3]. Environmental issues and concerns have been increasing as quickly as the development of the mechanization of forest operations across most of the world over the last 50 years [4]. From an SFO perspective, forest operational planning must consider all possible factors affecting environmental impacts, as well as their interactions. Soil plays a vital role in forest ecosystems by providing nutrients, water, and energy flow, which leads to forest productivity and biodiversity conservation [5,6,7]. Due to their specific characteristics, forest soils are highly susceptible to disturbances caused by skidding operations, the effects of which may persist for years after skidding [8,9,10]. Log skidding in forest stands impacts the soil that, at the same time, is used as a growth substrate. However, due to soil disturbance, skidding operations lead to soil compaction, soil layer displacement, and the deformation of soil structure and texture [11,12,13]. Skidding operations generally require a wide and dense network of skid trails for proper access at the forest stand level. Also, finding the optimum space between the forest road to minimize the total cost of timber extraction and road construction plays a key role in planning sustainable forest operations [14]. In this case, a large area of forest soil is affected by the machinery traffic, with possible related changes or disturbances. In general, it may be possible to note an increasing trend in soil bulk density (BD) values [10,15,16,17,18], as well as shear and penetration resistance (PR) values [7,8,11,19,20]. At the same time, it may be possible to note a decreasing trend for the presence of macropores [21], hydraulic conductivity of water, air permeability, air–water and gas exchange [22], organic matter [5,20,23], the presence and quality of soil microorganisms [24,25], and carbon sequestration capacity [26]. The lack of recovery of soil properties, especially bulk density and penetration resistance, can also impact the regeneration and decrease of growth seedlings, as reported by Picchio et al. [9] and Sohrabi et al. [27].
Machinery traffic could also lead to variations in some soil features, but without a clear trend, including soil pH [20,28]; microbial biomass, due to inadequate respiration [29,30,31]; and nutrient availability, due to changes in mineralization process [20,29]. Variations in these soil features, depending on their degree and intensity, can influence plant growth [23,32,33,34].
The influence of important factors on soil property changes after skidding operation are traffic intensity (the number of passes), slope gradients, and skidding direction. Numerous studies have shown that high traffic intensity (more than 15 passes) and high slope gradient (more than 20%) in mountainous areas cause soil disturbance to a greater extent and with greater intensity [35,36,37].
The recovery of physical, chemical, and biological soil properties is a topic that has been extensively discussed but has not always been clearly stated due to the difficulties in assessing multiple complex variables. The processes of soil swelling and shrinkage, freezing and thawing, wetness and drought [38,39], root–soil interaction [40,41], fauna activities [39,41,42], precipitation, and the height of the stands are the main factors that can accelerate the recovery process of disturbed soils [43,44]. In addition, soil properties (structure, texture, thickness, and depth), soil moisture and litter layer, terrain slope, soil initial compaction, harvesting systems, and the type of machinery used in skidding operations also affect the soil recovery rate [8,45,46,47,48].
The recovery of the physical, chemical, and biological properties of compacted soils can take years and even decades without the use of improvement treatments [12,17,49,50,51]. Ezzati et al. [50] and Jaafari et al. [36] have shown that soil properties did not recover during a long-term period (20 years) after skidding operation. Von Wilpert and Schäffer [52] reached a similar conclusion; whereas Mohieddinne et al. [48] found that sandy neutral soils recovered in less than 20 years due to soil biological activities. According to some studies, the time required to recover the biological properties of soil is less than that of the physical and chemical properties [5,11]. For example, Mariani et al. [53] showed that soil biomass recovered on the forest floor between three and seven years after harvesting in Canada. Furthermore, Macedo et al. [54] reported that soil C and N were significantly recovered 13 years after harvesting. Picchio et al. [8] and Venanzi et al. [20] have shown that soil recovery after reduced impact logging activities can occur within 6–10 years, and this can be considered fairly fast. Accordingly, Hope [55] has shown that many of the changes that were visible in the first year after the harvesting operation disappeared in the 10 years following the operation, and the effects of machinery traffic on the chemical properties of the soil were significantly recovered, while the shortest time to recover physical properties such as bulk density was reported to be five years.
Three especially prominent approaches in the sustainability of forest operations are: environmentally sound forest harvesting, reduced-impact logging, and forest operations ecology [3]. Forest operations ecology applies the principles of industrial ecology to forest operations systems. It aims to develop and deploy environmentally sound forest operations technologies, to use resources efficiently, to minimize the overall production of waste and emissions, and to minimize the impacts on the structures and functions of environmental spheres (atmosphere, biosphere, hydrosphere, and lithosphere) [1]. Characterizing the effects of skidding operations on the physical, chemical, and biological properties of soil is one important step in protecting the forest ecosystem and forest soil fertility [56]. The aeration status and soil porosity, the quality and quantity of organic matter, the microbial biomass, and the soil nutrients are considered criteria for the evaluation of soil health and biological and chemical activity. Therefore, there is a need to investigate the changes in the physical, chemical, and biological properties of soil. Awareness of the time required for the recovery of disturbed soils is essential to sustainable forest management. We hypothesize that soil properties could not be recovered after skidding operations over a long-term period (20 years) under natural conditions. The main aim of this study is (1) to evaluate the time required for the recovery of the physical, chemical, and biological properties of soil; and (2) to assess the long-term effect of the slope of the skid trail, machine traffic, and soil depth on the recovery process of the soil environment after ground-based skidding operations in the Hyrcanian forests of Iran.

2. Materials and Methods

2.1. Site Description

This study was conducted in seven different forest compartments located in the Namkhaneh and Gorazbon districts of the Kheyrud forest, part of the Hyrcanian forest in northern Iran. The research area lies between 51°36′50″ E and 51°38′21″ E longitude and 36°34′21″ N and 36°33′34 5″ N latitude, at altitude of 1000–1232 m above sea level. The study area has no dry season and has a humid climate with an average annual rainfall of 1146 mm and an average annual temperature of 8.55 °C. The soil texture of the study site ranges from silt loam to loamy (Table 1). The soils are mainly brown forest (Alfisols) with good drainage and, in terms of geology, belong to the Jurassic period. This area is predominantly covered by deciduous trees such as oriental beech (Fagus orientalis Lipsky), hornbeam (Carpinus betulus L.), velvet maple (Acer velutinum Boiss.), Cappadocian maple (Acer cappadocicum Gled), large-leaved lime tree (Tilia platyphyllos Scop.), chestnut-leaved oak (Quercus castaneifolia C.A.M.), mountain elm (Ulmus glabra Huds.), and Caucasian alder (Alnus subcordata C.A. Mey). The silvicultural treatment applied in the study area was a combination of single-tree selection and group selection, resulting in uneven-aged stands. More general information of the experiments is given in Table 1. Motor-manual felling and processing (i.e., using chainsaws) were carried out at the felling site. The skidding machinery (Timberjack 450 C) was equipped with winch cables and was used to extract logs with a length of 5–15 m from the forest area to the landings. The Timberjack skidder is an articulated four-wheel drive vehicle with a weight of 10.3 tons (total weight with equipment) and an engine power of 177 hp. The front and rear axles in this machine are equipped with 775 × 813 mm tires with an average ground pressure of 220 kPa and a ground clearance of approximately 0.6 m, with an overall width of 3.1 m.

2.2. Experimental Design

In this study, the long-term natural recovery of soil physical parameters (dry bulk density, total porosity, macroporosity, microporosity, penetration resistance, and soil moisture), chemical parameters (soil pH and Electrical conductivity (EC), C (%), N (%), C/N ratio, available P, K, Ca, and Mg), and biological parameters (earthworm density and biomass) on the surface soil layer of the skid trail was quantified at different levels of slope, traffic intensity, and soil depth and compared to the undisturbed area. Four abandoned skid trails with a downslope skidding direction that encompassed a wide range of longitudinal slope gradients (regardless of the lateral slope, area height, and soil texture and structure) in three replications at the forest level were selected for the study. The trails ranged from three years, through 10 years and 20 years, to 25 years since forest harvesting (Figure 1). A three-year-old skid trail instead of one-year-old skid trail was chosen because the study was conducted after the introduction of a prohibition of forest harvesting in the Hyrcanian forest, and the last trail on which the skidding operation was conducted was three years old. The average load volume and number of logs for each skidding cycle by the Timberjack skidder were 3.8 m3 and 2, respectively. The motivation behind this research was to gain a retrospective view of the research conducted by Ezzati et al. [50] and Sohrabi et al. [27] in the Hyrcanian forest, who claimed that the recovery of soil physical properties can be lengthy. However, this research did not investigate the recovery of the chemical and biological properties of the soil in responses to soil compaction over the time, which is one of the most interesting ideas developed in the current research. On all the studied skid trails, the skidder only traveled on the skid trails at the time of skidding, and these skid trails were not used for timber extraction in later years. The entrances of skid trails were blocked by embankments after the timber extraction was completed. Felled trees were thick and high (dbh > 60 cm; height > 20 m), and were scattered around the skid trails (selection cutting silviculture), the logs from the bole of each felled tree formed a complete machine load (the logs of each felled tree were individually extracted in one skidding cycle). Due to the above conditions, the farther away from the landings the traffic intensity decreases (Figure 2A). The average length of skid trails in the study area was about 150 m, with the first 50 m (0–50 m) from the forest road considered as high traffic intensity (HST), the second 50 m (50–100 m) as medium traffic intensity (MST), and the third of 50 m (100–150 m) or subsidiary of the skid trail as low traffic intensity (LST) [35,36,50]. In the skid trails, three slope classes (0–10%, 10–20%, and 20–30%) were considered with regard to variations and maximum slope. Therefore, the research plots included three traffic-intensity classes and three slope-gradient classes, thus forming nine combinations of traffic frequency and trail gradients; each treatment combination was replicated three times at the forest level, totaling 27 treatment plots (N = 27 in each recovery period). On the skid trails, in each treatment (e.g., a combination of slope and traffic), sampling plots with the dimensions of 40 m2 were designed. In each sampling plot, five sampling lines were designed at a distance of 2 m from each other and perpendicular to the skid trail, of which three lines were randomly selected for sampling. Soil samples were taken from a depth interval of 0–10 and 10–20 cm at three locations in each plot: (LW) the left wheel track, (BW) between the tracks, and (RW) the right wheel track (Figure 2B). To compare the soil properties between the skid trail and the undisturbed area, soil samples were taken inside the forest at least 20–30 m (the size of the average height of the dominant trees in the area) away from the skid trail, where the effects of the skidding operations on the soil completely disappeared (n = 81 in each recovery period). Ruts were measured on the skid trails at the site of the compaction measurement line, and ruts with a depth of 5 cm and a length of at least 2 m were considered to be caused by soil disturbance [57]. In each rut, at 25 mm horizontal intervals, depth was measured, and the mean was considered to be caused by soil disturbance. Obviously, the distance between the compaction and the rut sampling lines was not less than 2 m [58].

2.3. Measurements and Laboratory Analysis

A steel ring (5 cm in diameter and 10 cm in height; 196.25 cm3) was used to collect soil samples from depths of 0–10 and 10–20 cm. The soil samples were stored and coded in plastic bags. On the same sampling day, the wet weight of all samples was measured before transfer to the laboratory. In the laboratory, the soil samples were dried at 105 °C for 24 h to calculate the soil moisture content, dry bulk density, and porosity.
The bulk density and total porosity were calculated using Equations (1) and (2).
B D = W D V C
where BD is the dry bulk density (g cm−3), WD is the weight of the dry soil (g), and VC is the volume of the cylinder (cm3).
TP = 1 − ( B D 2.65 ) × 100
where TP is the apparent total porosity (%), BD is the bulk density (g cm−3), and 2.65 g cm−3 is the soil particle density [59].
Macroporosity and microporosity were calculated using Equations (3) and (4).
MIP = θ m × B D
where MIP is the microporosity (%), BD is the dry bulk density (g cm−3), and θm is the water content on a mass basis (%).
MP = TP − MIP  
where MP is the macroporosity (%), TP is the total porosity (%), and MIP is the microporosity (%).
The hydrometric method was used to determine the soil texture, whereas the determination of soil penetration resistance was made with a hand-held soil penetrometer (Eijkelkamp 06.01.SA penetrometer with a 60° cone and a 1 m maximum measuring depth) that was inserted vertically into the soil with equal pressure at the location of each sample. Since soil moisture influences the measurement of penetration resistance, all measurements were performed under similar conditions.
In order to measure the soil chemical properties, samples were taken from the mineral soil layer. Therefore, soil samples were air-dried and soil particles <2 mm were used for the experiments. The Orion Ionalyzer (Model 901, Cambridge, MA, USA) pH meter was used to measure soil pH in a soil/water ratio of 1:2.5. Electrical conductivity (EC) was determined using an Orion Ionalyzer EC meter in a 1:2.5 soil/water solution. The Walkley–Black procedure [60] was used to determine the organic carbon (OC) content in percentage, and the Kjeldahl method was used to measure total N [61]. The Olsen method was used by utilizing a spectrophotometer to determine the available phosphorus (P) of the soil, and an atomic absorption spectrophotometer (by ammonium acetate extraction at pH 9) was used to determine available potassium (K), calcium (Ca), and magnesium (Mg) of the soil [62]. To determine the earthworm density and biomass, sample plots of 25 × 25 cm were designed on the sampling lines and the number of earthworms were counted at soil depths of 0–10 and 10–20 cm. After collection, the earthworms were washed and weighed, and then to determine the dry weight, earthworms were dried for 24 h at 60 °C [62].

2.4. Statistical Analyses

Statistical analyses were performed using SPSS version 17 (Chicago, IL, USA) software. As a first step, data distribution was plotted and checked for normality (Kolmogorov–Smirnov) and homogeneity of variance (Levene test). One-way and two-way ANOVAs were used to assess the significance of the observed mean differences in the physical, chemical, and biological properties of the soil under different skidder traffic levels, trail gradients, wheel track locations, soil depths, and their interactions. The comparison between the physical, chemical, and biological properties of the soil was made by using one-way ANOVA (p-level α ≤ 0.05) and Duncan’s multiple range tests. The relationships between soil properties were determined using Pearson correlation. Significant relationships between variables and principal components were determined by using principal component analysis (PCA) via the PC-ORD (Version 4, WILD BLUEBERRY MEDIA LLC, Corvallis, OR, USA) software.

3. Results

3.1. Physical Properties of the Soil

The age of a skid trail and the sampling depth treatments had a significant effect on all the physical properties of the soil. Different traffic intensities had a significant effect on BD, PR, and total porosity (TP), while having no significant effect on the other properties. Different slopes had no significant effect on the physical properties (except PR and TP), nor did wheel track location (except PR) or the interaction of treatments (Table 2).
Changes in the physical properties of the soil showed that soil properties recover within different years of skidding activities (Table 3). From the three-year-old skid trail to the 25-year-old skid trail, the BD, PR, and MIP decreased. In contrast, the TP, MP, and SM increased and differed significantly from the undisturbed area. Three years after the skidding operation, the BD, PR, and MIP were 12.6%, 107%, and 69.51% higher than the undisturbed area, respectively. Meanwhile, 25 years after the skidding operations, they were 8.4%, 27.4%, and 50.44% higher than the undisturbed area, respectively. Furthermore, three years after the skidding operation, the TP, MP, and SM were 2.47%, 23.3%, and 10.23% lower than the undisturbed area, respectively. Meanwhile, 25 years after the logging operations, they were 1.96%, 17.1%, and 4.58% lower than the undisturbed area, respectively (Table 3).
The investigation of the rut depth under different traffic intensities showed an increasing trend with the increase of traffic intensity in the skid trails (Figure 3). The rut depth in all the skid trails (except the 25-year-old skid trail) was significantly different for all three traffic intensities. The rut depth improved over the years following the skidding operation, so that by 25 years after the skidding operation, low and medium traffic intensity was fully recovered. The highest rut depth was observed in the three-year-old skid trail under high traffic intensity, with the amount of 20.1 cm, while the lowest was observed in the 25-year-old skid trail under high traffic intensity, with the amount of 5.3 cm (Figure 3). The results of this study show that the rut depth recovered in less time than other physical properties of the soil.

3.2. The Chemical and Biological Properties of the Soil

The effect of the age of the skid trail and traffic intensity on all chemical properties was significant, while it was not significant on biological properties (Table 4). The slope of the skid trail had a significant effect on chemical properties (except C), while it had no significant effect on biological properties. The wheel track location had a significant effect on the pH and EC of the chemical properties. It also had a significant effect on biological properties at the 0.01% level. Furthermore, the soil depth has a significant effect on the chemical (except C) and biological properties. However, the interaction effects of treatments on the chemical (except EC and C/N ratio) and biological properties were not significant (Table 4).
Over the years following the skidding operation, the chemical and biological soil properties improved from the three-year-old skid trail to the 25-year-old skid trail (Table 5). Twenty-five years after the skidding operation, the values of pH, EC, C%, N%, available P, K, Ca, and Mg, earthworm density, and biomass soil were 6.4%, 20%, 22.77%, 38.8%, 11.2%, 14.2%, 10.3%, 15.1%, 28.3%, and 30.5% lower than the control area, respectively, and value of the C/N ratio was 26.2% higher than the control area (Table 5). The chemical and biological properties of the soil were significantly different from the control area 25 years after the skidding operation (Table 5).
Changes in the earthworm number and biomass under different traffic intensities and soil depths were lower at depths of 10–20 cm than depths of 0–10 cm, and lower under high rather than medium and low traffic intensities (Figure 4). The lowest earthworm number and biomass were obtained under high traffic intensity at soil depths of 10–20 cm. The earthworm number and biomass under different traffic intensities in both depths of soil were lower than the undisturbed area and were significantly different (Figure 4).

3.3. Principal Component Analysis (PCA)

The different traffic intensities (high, medium, and low) and different slopes (0–10%, 10–20%, and 20–30%) in the skid trails and the physical, chemical, and biological properties of the PCA analysis are presented in Figure 5 and Figure 6. The PCA results show the relation between traffic intensity in the skid trails and the soil properties and reveal that the first and second axes explain 76.98% and 14.63% of the total variance, respectively (Figure 5). The PCA analysis results for the relationship between the different slopes in the skid trails and the soil properties show that the first and second axes explain 74.34% and 13.91% of the total variance, respectively (Figure 6). The analysis of the traffic intensity and the slope of the skid trails three and 25 years after the skidding operation show that as these two treatments increase, the effect on the soil increases. The results also show that high traffic intensity (H3) and slope classes of 20–30% (C3) in three-year-old skid trails had the greatest impact on soil properties (according to maximum distance from the coordinate center and proximity to axis 1) (Figure 5 and Figure 6). The PCA analysis shows that 25-year-old skid trails under different traffic intensities and slopes had the least impact on soil properties (according to proximity to the coordinate center and away from the axis 1). The TP, MP, MIP, SM, and pH were close to the center axis, indicating that the effect of traffic and slope treatments was lower on these properties. However, the effects of these treatments on other physical, chemical, and biological properties were greater due to the distance from the coordinate center. The location of treatments affecting soil variables indicates that the undisturbed area is on the left side of the graph (Figure 5 and Figure 6). The undisturbed area is slightly different, with older trails in low traffic and slope classes, whereas younger trails have high traffic and slope classes.
The traffic intensity of three-year-old skid trails (H3) was positively correlated with BD (r = 0.92), PR (r = 0.95), and C/N ratio (r = 0.84), while it was negatively correlated with the other soil properties (Table 6). Also, the slope classes of three-year-old skid trails was positively correlated with BD (r = 0.83), PR (r = 0.93), and C/N ratio (r = 0.67), while it was negatively correlated with the other soil properties (Table 6).

4. Discussion

A comprehensive review of the natural recovery of the physical, chemical, and biological properties of the soil after skidding operations can complement the previous research chain and can be a guide to reducing the detrimental effects of skidding operations on forest soil and acquiring new knowledge on the sustainability of forest operations. In the past, there have been many studies conducted on the effects of skidding operations on soil of skid trails in controlled conditions. It is important to specify that the present research is retrospective, and the statistics and information obtained from the skidding operation were descriptive. Further experiments and sampling were performed on the desired trails and compared with the control area to evaluate the soil recovery process after skidding operations and to validate the descriptive data. Our study confirms that the effects of the age of the skid trail, traffic intensity, and sampling depth are more than those of other treatments. In this study, the slope of the skid trail changed the physical properties of the soil but had no significant effect due to the slope being divided into classes with less variation range (0–10%, 10–20%, and 20–30%). There appears to be a threshold to the slope gradient that has to be surpassed, however, before slope effects become visible [36]. Similarly, Najafi et al. [35] observed that the disturbance in soil physical properties was not significant in the slope classes of 0–10% and 10–20%, whereas for slopes of more than 20%, soil disturbance was significantly increased.
The change in the physical properties of the soil under the influence of skidding has been confirmed by other researchers, including Tavankar et al. [63], Ezzati et al. [50], Jourgholami at al. [32], Picchio et al. [9], and Sohrabi et al. [27]. The highest soil changes were obtained for high traffic intensity and slope, three years after the skidding operation. Further soil changes under high traffic intensity may be due to the high soil moisture during the skidding operation, the output timber volume of the area, and the number of passes. Skidding operations on steep terrain cause severe wheel slips of the machine, resulting in more puddling and dragging of the soil [44,64]. In addition, the slower speed of a machine on steeper terrain, especially upward skidding, causes more vibration of the surface soil and is disturbed more severely than compared to flat terrain [65]. With an increasing number of passes on steep terrain, the proportion of microporosity to macroporosity increases, and previous studies have confirmed this result [44,66]. During the skidding operation, the pores in the soil surface layer are compressed, which increases the soil strength, thereby reducing and changing the soil pores. The Soil moisture content decreases with the increasing traffic intensity and slope of the skid trail, so that the lowest moisture content is obtained under high traffic intensity and for a slope of 20–30%. The decrease in soil moisture is mainly due to a decrease in total porosity and macroporosity and an increase in the bulk density at the surface and in the soil profile [10,35,50].
Over the years after the skidding operation, the soil physical properties improve from the three-year-old trail to the 25-year-old trail, although there are significant differences with the control area. The results show that 25 years after the skidding operations, the BD, PR, and MIP were 8.4%, 27.4%, and 50.44% greater, respectively, and the TP, MP, and SM, which were 1.96%, 17.1%, and 4.58% lower than the undisturbed area, respectively. The results of this study are consistent with the results of the study by Ezzati et al. [50], which reported that, 20 years after skidding operations, under high traffic intensity and gentle slope class (<20%), the bulk density was 35–42% higher and the total porosity and macroporosity were 18–24% and 19–28% lower than the undisturbed area, respectively. After 25 years of skidding, the BD was lower than the threshold value of 1.40–1.55 g/cm−3 [38], indicating a recovery process for this feature. According to the findings of Ampoorter et al. [67], increasing the PR to more than 2 MPa limits the infiltration and growth of root trees in soil types. In this study, 25 years after skidding, the PR was less than 2 MPa, which indicates its recovery over time. One important effect of soil compaction is a decrease in total porosity by a decrease in macroporosity and an increase in microporosity [50]. The increase in the proportion of TP and MP over 25 years after the skidding operation is not unexpected. The MP in this study exceeded the threshold value of 10% [22], which is a prerequisite for airflow, microbial activity, and rooting. The soil moisture content increased in different years after skidding operation from the three-year-old trail to 25-year-old trail, which may be due to the reduced soil compaction and increased litter layer of the soil surface for water infiltration, as well as the reduced surface runoff through more pores in the soil [67].
The creation of soil ruts contributed to the increase in traffic intensity in this study, which was also reported by Botta [68], Eliasson [69], and Ezzati et al. [50]. When the soil moisture is saturated and soil cavities are filled with water, the skidding operation removes the surface layers of the soil and thus creates deep ruts in the soil. Soil ruts are more specified in the immediate years after skidding and high traffic intensity, leading to the disruption of natural drainage structures and reduced stability and soil aggregation. The tire size and average pressure on the soil are other effective factors in creating a rut in the soil during the skidding operation [50]. The rut depth improves in different years after the skidding operation, so that 25 years after the skidding operation, under low and medium traffic intensity, the soil is fully recovered. Consistent with the current study, Hatchel et al. [70] stated that rut recovery created after skidding operations requires a period of 18–19 years. The results of this study show that rut depth recovery requires less time than other physical properties of the soil.
Our study indicates that the effects of the treatments on the chemical properties were more intense than on the physical properties, which may be due to the mixing of the surface soil with the lower layers, the removal of soil, and soil sampling from the deep layers when compared to the undisturbed area [36]. On the other hand, the puddling and dragging of the soil of the skid trail after the skidding operation causes erosion and the loss of soil nutrients, which ultimately results in prolonged recovery for soil chemical properties. Changes in soil chemical properties under the influence of skidding operations have also been confirmed in previous studies [17,36,71].
In this study, the changes (decrease) in organic matter content and in different slopes and under different traffic intensities of the skidding trails compared to the control area are due to low levels of litter layer at the soil surface. Cutting down trees along the skidding trails for easier logging operation results in reduced tree density and, consequently, in reduced the litter layer of the forest floor [10,28,35,70]. C and N in soil have a close relationship with each other, in which, in this study, the trend changes were similar. A decrease in C and N levels after the skidding operations can be due to the displacement and mixing of organic and mineral soils, as well as the appearance of deep soil layers following the skidding operations [36]. The skidding operations reduce soil acidity on different slopes and under different traffic intensities of the skid trails compared to the undisturbed area. Consistent with the results of the current study, Hosseini et al. [71] reported that soil acidity on skid trails was lower than in undisturbed areas in the Hyrcanian forest. Soil compaction, disturbance, surface runoff, and soil erosion caused by skidder traffic are the main reasons for these changes [51]. Therefore, based on this hypothesis, the soil C, N, P, K, and pH concentrations in skid trails are significantly lower than in control areas [17,36]. The decrease in soil organic matter content and available P, K, Ca, and Mg, in soil after the skidding operations was reported in this study and in other studies [17,36,72,73].
The results show that soil chemical properties are not fully recovered after 25 years following skidding operations; thus, the difference compared to the undisturbed area is significant. The chemical soil properties improved over the years following the skidding operations. Accordingly, Hosseini et al. [69] reported that seven years after skidding operations in the Hyrcanian forest, the chemical properties of the soil were recovered and had no significant difference compared to the undisturbed area. The improvement of soil chemical properties can be due to climatic conditions, a decrease in bulk density over time, the litter layer thickness, the type and quality of the litter layer, and the activity of soil organisms. Since there is a direct relationship between the chemical properties of the soil and the vegetation type and density and the amount of litter, changes in the forest floor cover and the soil organic layer have direct effects on the chemical properties. In line with the current results, Jourgholami et al. [74] reported that, by adding a litter layer to the soil surface, the chemical properties can be partially recovered.
The results show that the earthworm number and biomass under different traffic intensities of the skid trails was lower than in the undisturbed area; thus, these changes were higher under a high traffic intensity. The soil habitat had a lower quality in terms of coarse porosity, temperature and moisture, organic matter content, and vegetation under different traffic intensities compared to the undisturbed area. In addition, the earthworm number and biomass at a soil depth of 10–20 cm was lower than at a depth of 0–10 cm. Earthworm immobilization plays an important role in the reduction of earthworm number and biomass due to the increase in penetration resistance and the reduction of coarse pores at a depth of 10–20 cm. The soil habitat quality and earthworm mobility are two effective factors in the recovery of earthworm communities after skidding operations [24]. Twenty-five years after a skidding operation, soil biological properties in skid trails will be improved, and will be significantly different from the undisturbed area. The earthworm density (0.48 n m−2) and biomass (2.05 mg m−2) were higher in the 25-year-old skid trail than the 20- > 10- > 3-year-old skid trails. Furthermore, Jourgholami et al. [74] reported that by adding a litter layer of different trees (beech + hornbeam + velvet maple) to the skid trail soil, 5 years after skidding operations, an increase in earthworm density (1.02 n m−2) and biomass (13.26 mg m−2) can be observed, but this differs significantly from the undisturbed area. The lack of full recovery of earthworm number and biomass after 25 years may be due to unfavorable soil properties and a low litter layer. The litter layer increases the organic matter content and the decomposition rate of organic matter at the soil surface, which increases soil respiration by positively impacting the microbial communities of the soil [51,74,75,76]. Previous studies have shown that increasing organic matter decomposition rate, decreasing C/N ratio in organic layers, and fine soil texture all have a significant relationship with earthworm biomass [17,77,78].

5. Conclusions

From a sustainable forest operation perspective, forest operational planning must consider all possible factors affecting environmental impacts, as well as their interactions. The evaluation of the time required for soil recovery is essential for managing forests on the basis of SFO, particularly in ground-based logging systems. This study was designed to determine the effects of different levels of traffic intensity, slope gradient, soil depth, and wheel track on the physical, chemical, and biological properties of the soil on the soil recovery assessment after timber harvesting. We found increased BD, PR and MIP and decreased TP, MP, SM, in the chemical and biological properties of the soil following ground-based skidding compared to the undisturbed areas, particularly on steep slopes with high traffic intensity and a sampling depth greater than 0.1 m. Twenty-five years after the skidding operations, the physical, chemical, and biological properties of the soil were somewhat recovered in the skid trails, but remained significantly different to the undisturbed area. The outcomes of this study indicate that the recovery time of the chemical properties of the soil is longer than that of the biological and physical properties, and that the complete recovery of these properties takes more than 25 years. Accordingly, forest managers need to consider the potential impacts of skidding operations on soil disturbance. Therefore, due to the long recovery process of compacted soils, reducing the area covered by skidding trails, avoiding or limiting skidding trails on steep slopes, using appropriate machinery, designing exact and specified skidding trails, and cutting down trees in the correct direction are all essential to avoiding unnecessary traffic. On the other hand, the use of improvement treatments (different foliage mulch and tree planting(, and comparing their performance in terms of the recovery of the soil properties of skid trails, are essential in order to accelerate biological activities and natural regeneration, prevent soil water erosion, and regulate the water cycle. A careful use of machines and tools, a mindful choice of operating season and meteorological conditions, well thought out logging planning and practices, and the training and skill development of forest operators can mitigate the negative environmental impacts of forest operations. The “reevaluation of logging practices” and “logging development programs” should be developed as the main aims of SFO to reduce soil compaction during timber skidding and extraction.

Author Contributions

Conceptualization, H.S., M.J. (Meghdad Jourgholami), M.J. (Mohammad Jafari), and N.S.; methodology, H.S., M.J. (Meghdad Jourgholami), M.J. (Mohammad Jafari), N.S., R.V., F.T., and R.P.; software, H.S., M.J. (Meghdad Jourgholami), M.J. (Mohammad Jafari), and N.S.; validation, H.S., M.J. (Meghdad Jourgholami), M.J. (Mohammad Jafari), N.S., R.V., F.T., and R.P.; formal analysis, H.S., M.J. (Meghdad Jourgholami), M.J. (Mohammad Jafari), and N.S.; investigation, H.S., M.J. (Meghdad Jourgholami), M.J. (Mohammad Jafari), and N.S.; data curation, H.S., M.J. (Meghdad Jourgholami), M.J. (Mohammad Jafari), N.S., R.V., F.T., and R.P.; writing—original draft preparation, H.S., M.J. (Meghdad Jourgholami), M.J. (Mohammad Jafari), N.S., and R.V.; writing—review and editing, H.S., M.J. (Meghdad Jourgholami), M.J. (Mohammad Jafari), N.S., R.V., F.T., and R.P.; supervision, M.J. (Meghdad Jourgholami), F.T., and R.P. All authors read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

This work was supported by the Italian Ministry for education, University and Research (MIUR) for financial support (Law 232/2016, Italian University Departments of excellence)—UNITUS-DAFNE WP3.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Heinimann, H.R. Forest operations engineering and management—The ways behind and ahead of a scientific discipline. Croat. J. For. Eng. 2007, 28, 107–121. [Google Scholar]
  2. Marchi, E.; Picchio, R.; Spinelli, R.; Verani, S.; Venanzi, R.; Certini, G. Environmental impact assessment of different logging methods in pine forests thinning. Ecol. Eng. 2014, 70, 429–436. [Google Scholar] [CrossRef]
  3. Marchi, E.; Chung, W.; Visser, R.; Abbas, D.; Nordfjell, T.; Mederski, P.S.; McEwan, A.; Brink, M.; Laschi, A. Sustainable Forest Operations (SFO): A new paradigm in a changing world and climate. Sci. Total Environ. 2018, 634, 1385–1397. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Riala, M.; Athanassiadis, D.; la Hera, P.; Rodriguez, J. Development Potential of Inventions in Forest Biomass Harvesting. D 6.3. INFRES Project Report. 2015. Available online: http://www.forestenergy.org/observer:get_page/observer/action/details/itemid/706 (accessed on 28 March 2018).
  5. Venanzi, R.; Picchio, R.; Piovesan, G. Silvicultural and logging impact on soil characteristics in Chestnut (Castanea sativa Mill.) Mediterranean coppice. Ecol. Eng. 2016, 92, 82–89. [Google Scholar] [CrossRef]
  6. Dominati, E.; Patterson, M.; Mackay, A. A framework for classifying and quantifying the natural capital and ecosystem services of soils. Ecol. Econ. 2010, 69, 1858–1868. [Google Scholar] [CrossRef]
  7. Picchio, R.; Tavankar, F.; Nikooy, M.; Pignatti, G.; Venanzi, R.; Lo Monaco, A. Morphology, growth and architecture response of beech (Fagus orientalis Lipsky) and maple tree (Acer velutinum Boiss.) seedlings to soil compaction stress caused by mechanized logging operations. Forests 2019, 10, 771. [Google Scholar] [CrossRef] [Green Version]
  8. Picchio, R.; Mercurio, R.; Venanzi, R.; Gratani, L.; Giallonardo, T.; Lo Monaco, A.; Frattaroli, A.R. Strip clear-cutting application and logging typologies for renaturalization of pine afforestation—A case study. Forests 2018, 9, 366. [Google Scholar] [CrossRef] [Green Version]
  9. Picchio, R.; Venanzi, R.; Tavankar, F.; Luchenti, I.; Iranparast Bodaghi, A.; Latterini, F.; Nikooy, M.; Di Marzio, N.; Naghdi, R. Changes in soil parameters of forests after windstorms and timber extraction. Eur. J. For. Res. 2019, 138, 875–888. [Google Scholar] [CrossRef]
  10. Jourgholami, M.; Ghassemi, T.; Labelle, E.R. Soil physio-chemical and biological indicators to evaluate the restoration of compacted soil following reforestation. Ecol. Indic. 2019, 101, 102–110. [Google Scholar] [CrossRef]
  11. Marchi, E.; Picchio, R.; Mederski, P.S.; Vusić, D.; Perugini, M.; Venanzi, R. Impact of silvicultural treatment and forest operation on soil and regeneration in Mediterranean Turkey oak (Quercus cerris L.) coppice with standards. Ecol. Eng. 2016, 95, 475–484. [Google Scholar] [CrossRef]
  12. Klaes, B.; Struck, J.; Schneider, R.; Schüler, G. Middle-term effects after timber harvesting with heavy machinery on a fine-textured forest soil. Eur. J. For. Res. 2016, 135, 1083–1095. [Google Scholar] [CrossRef]
  13. Tavankar, F.; Bonyad, A.E.; Nikooy, M.; Picchio, R.; Venanzi, R.; Calienno, L. Damages to soil and tree species by cable-skidding in Caspian forests of Iran. For. Syst. 2017, 26, 1–9. [Google Scholar] [CrossRef] [Green Version]
  14. Matthews, D.M. Cost Control in the Logging Industry; McGraw-Hill: New York, NY, USA, 1942; p. 374. [Google Scholar]
  15. Poltorak, B.J.; Labelle, E.R.; Jaeger, D. Soil displacement during ground-based mechanized forest operations using mixed-wood brush mats. Soil Till. Res. 2018, 179, 96–104. [Google Scholar] [CrossRef]
  16. Flores Fernández, J.L.; Rubin, L.; Hartmann, P.; Puhlmann, H.; von Wilpert, K. Initial recovery of soil structure of a compacted forest soil can be enhanced by technical treatments and planting. For. Ecol. Manag. 2019, 431, 54–62. [Google Scholar] [CrossRef]
  17. Jourgholami, M.; Labelle, E.R.; Feghhi, J. Efficacy of leaf litter mulch to mitigate runoff and sediment yield following mechanized operations in the Hyrcanian mixed forests. J. Soils Sediments 2019, 19, 2076–2088. [Google Scholar] [CrossRef]
  18. Cambi, M.; Grigolato, S.; Neri, F.; Picchio, R.; Marchi, E. Effects of forwarder operation on soil physical characteristics: A case study in the Italian Alps. Croat. J. For. Eng. 2016, 37, 233–239. [Google Scholar]
  19. Picchio, R.; Spina, R.; Calienno, L.; Venanzi, R.; Lo Monaco, A. Forest operations for implementing silvicultural treatments for multiple purposes. Ital. J. Agron. 2016, 11, 156–161. [Google Scholar]
  20. Venanzi, R.; Picchio, R.; Grigolato, S.; Latterini, F. Soil and forest regeneration after different extraction methods in coppice forests. For. Ecol. Manag. 2019, 454, 117666. [Google Scholar] [CrossRef]
  21. Flores Fernández, J.L.; Hartmann, P.; Schäffer, J.; Puhlmann, H.; von Wilpert, K. Initial recovery of compacted soil planting and technical treatments decrease CO2 concentrations in soil and promote root growth. Ann. For. Sci. 2017, 74, 73. [Google Scholar] [CrossRef] [Green Version]
  22. Ampoorter, E.; Goris, R.; Cornelis, W.M.; Verheyen, K. Impact of mechanized logging on compaction status of sandy forest soils. For. Ecol. Manag. 2007, 241, 162–174. [Google Scholar] [CrossRef]
  23. Makineci, E.; Demir, M.; Comez, A.; Yilmaz, E. Chemical characteristics of the surface soil, herbaceous cover and organic layer of a compacted skid road in a fir (Abies bornmulleriana Mattf.) forest. Transport. Res. Part D 2007, 12, 453–459. [Google Scholar] [CrossRef]
  24. Bottinelli, N.; Capowiez, Y.; Ranger, J. Slow recovery of earthworm populations after heavy traffic in two forest soils in northern France. Appl. Soil Ecol. 2014, 73, 130–133. [Google Scholar] [CrossRef]
  25. Schweier, J.; Blagojević, B.; Venanzi, R.; Latterini, F.; Picchio, R. Sustainability assessment of alternative strip clear cutting operations for wood chip production in renaturalization management of pine stands. Energies 2019, 12, 3306. [Google Scholar] [CrossRef] [Green Version]
  26. Brevik, E.; Fenton, T.; Moran, L. Effect of soil compaction on organic carbon amounts and distribution, South-Central Iowa. Environ. Pollut. 2002, 116, S137–S141. [Google Scholar] [CrossRef]
  27. Sohrabi, H.; Jourgholami, M.; Tavankar, F.; Venanzi, R.; Picchio, R. Post-harvest evaluation of soil physical properties and natural regeneration growth in steep-slope terrains. Forests 2019, 10, 1034. [Google Scholar] [CrossRef] [Green Version]
  28. Makineci, E.; Demir, M.; Comez, A.; Yilmaz, E. Effects of timber skidding on chemical characteristics of herbaceous cover, forest floor and topsoil on skidroad in an oak (Quercus petrea L.) forest. J. Terramech. 2007, 44, 423–428. [Google Scholar] [CrossRef]
  29. Goutal, N.; Renault, P.; Ranger, J. Forwarder traffic impacted over at least four years soil air composition of two forest soils in northeast France. Geoderma 2013, 193, 29–40. [Google Scholar] [CrossRef]
  30. Hartmann, M.; Niklaus, P.A.; Zimmermann, S.; Schmutz, S.; Kremer, J.; Abarenkov, K.; Lüscher, P.; Widmer, F.; Frey, B. Resistance and resilience of the forest soil microbiome to logging-associated compaction. ISME J. 2014, 8, 226. [Google Scholar] [CrossRef]
  31. Epron, D.; Plain, C.; Ndiaye, F.K.; Bonnaud, P.; Pasquier, C.; Ranger, J. Effects of compaction by heavy machine traffic on soil fluxes of methane and carbon dioxide in a temperate broadleaved forest. For. Ecol. Manag. 2016, 382, 1–9. [Google Scholar] [CrossRef]
  32. Jourgholami, M.; Soltanpour, S.; Etehadi Abari, M.; Zenner, E.K. Influence of slope on physical soil disturbance due to farm tractor forwarding in a Hyrcanian forest of northern Iran. iForest 2014, 7, 342–348. [Google Scholar] [CrossRef] [Green Version]
  33. Cambi, M.; Hoshika, Y.; Mariotti, B.; Paoletti, E.; Picchio, R.; Venanzi, R.; Marchi, E. Compaction by a forest machine affects soil quality and Quercus robur L. seedling performance in an experimental field. For. Ecol. Manag. 2017, 384, 406–414. [Google Scholar] [CrossRef]
  34. Picchio, R.; Latterini, F.; Mederski, P.S.; Venanzi, R.; Karaszewski, Z.; Bembenek, M.; Croce, M. Comparing accuracy of three methods based on the gis environment for determining winching areas. Electronics 2019, 8, 53. [Google Scholar] [CrossRef] [Green Version]
  35. Najafi, A.; Solgi, A.; Sadeghi, S.H. Soil disturbance following four wheel rubber skidder logging on the steep trail in the north mountainous forest of Iran. Soil Till. Res. 2009, 103, 165–169. [Google Scholar] [CrossRef]
  36. Jaafari, A.; Najafi, A.; Zenner, E.K. Ground-based skidder traffic changes chemical soil properties in a mountainous Oriental beech (Fagus orientalis Lipsky) forest in Iran. J. Terramech. 2014, 55, 39–46. [Google Scholar] [CrossRef]
  37. Jourgholami, M.; Labelle, E.R.; Feghhi, J. Response of Runoff and Sediment on Skid Trails of Varying Gradient and Traffic Intensity over a Two-Year Period. Forests 2017, 8, 472. [Google Scholar] [CrossRef] [Green Version]
  38. Kozlowski, T.T. Soil compaction and growth of woody plants. Scand. J. For. Res. 1999, 14, 596–619. [Google Scholar] [CrossRef]
  39. DeArmond, D.; Emmert, F.; Lima, A.J.N.; Higuchi, N. Impacts of soil compaction persist 30 years after logging operations in the Amazon Basin. Soil Till. Res. 2019, 189, 207–216. [Google Scholar] [CrossRef]
  40. Dexter, A.R. Amelioration of soil by natural processes. Soil Till. Res. 1991, 20, 87–100. [Google Scholar] [CrossRef]
  41. Meyer, C.; Lüscher, P.; Schulin, R. Recovery of forest soil from compaction in skid tracks planted with black alder (Alnus glutinosa (L.) Gaertn.). Soil Till. Res. 2014, 143, 7–16. [Google Scholar] [CrossRef]
  42. Lal, R. Effects of macrofauna on soil properties in tropical ecosystems. Agric. Ecosyst. Environ. 1988, 24, 101–116. [Google Scholar] [CrossRef]
  43. Fründ, H.C.; Averdiek, A. Soil aeration and soil water tension in skidding trails during three years after trafficking. For. Ecol. Manag. 2016, 380, 224–231. [Google Scholar] [CrossRef]
  44. Jourgholami, M.; Etehadi Abari, M. Effectiveness of sawdust and straw mulching on postharvest runoff and soil erosion of a skid trail in a mixed forest. Ecol. Eng. 2017, 109, 1–9. [Google Scholar] [CrossRef]
  45. Mace, A.C., Jr. Recovery of Forest Soils from Compaction by Rubber-Tired Skidders; School of Forestry, University of Minnesota: St. Paul, MN, USA, 1971; Volume 226, p. 7688. [Google Scholar]
  46. Reisinger, T.W.; Pope, P.E.; Hammond, S.C. Natural recovery of compacted soils in an upland hardwood forest in Indiana. North. J. Appl. For. 1992, 9, 138–141. [Google Scholar] [CrossRef]
  47. Zenner, E.K.; Fauskee, J.T.; Berger, A.L.; Puettmann, K.J. Impacts of skidding traffic intensity on soil disturbance, soil recovery, and aspen regeneration in north central Minnesota. North. J. Appl. For. 2007, 24, 177–183. [Google Scholar] [CrossRef] [Green Version]
  48. Mohieddinne, H.; Brasseur, B.; Spicher, F.; Gallet-Moron, E.; Buridant, J.; Kobaissi, A.; Horen, H. Physical recovery of forest soil after compaction by heavy machines, revealed by penetration resistance over multiple decades. For. Ecol. Manag. 2019, 449, 117472. [Google Scholar] [CrossRef]
  49. Rab, M.A. Recovery of soil physical properties from compaction and soil profile disturbance caused by logging of native forest in Victorian Central Highlands, Australia. For. Ecol. Manag. 2004, 191, 329–340. [Google Scholar] [CrossRef]
  50. Ezzati, S.; Najafi, A.; Rab, M.A.; Zenner, E.K. Recovery of soil bulk density, porosity and rutting from ground skidding over a 20-year period after timber harvesting in Iran. Silva Fenni. 2012, 46, 521–538. [Google Scholar] [CrossRef] [Green Version]
  51. Jourgholami, M.; Khajavi, S.; Labelle, E.R. Mulching and water diversion structures on skid trails: Response of soil physical properties six years after harvesting. Ecol. Eng. 2018, 123, 1–9. [Google Scholar] [CrossRef]
  52. Von Wilpert, K.; Schäffer, J. Ecological effects of soil compaction and initial recovery dynamics: A preliminary study. Eur. J. For. Res. 2006, 125, 129–138. [Google Scholar] [CrossRef]
  53. Mariani, L.; Chang, S.X.; Kabzems, R. Effects of tree harvesting, forest floor removal, and compaction on soil microbial biomass, microbial respiration, and N availability in a boreal aspen forest in British Columbia. Soil Biol. Biochem. 2006, 38, 1734–1744. [Google Scholar] [CrossRef]
  54. Macedo, M.O.; Resende, A.S.; Garcia, P.C.; Boddey, R.M.; Jantalia, C.P.; Urquiaga, S.; Campello, E.F.C.; Franco, A.A. Changes in soil C and N stocks and nutrient dynamics 13 years after recovery of degraded land using leguminous nitrogen-fixing trees. For. Ecol. Manag. 2008, 255, 1516–1524. [Google Scholar] [CrossRef]
  55. Hope, G.D. Changes in soil properties, tree growth, and nutrition over a period of 10 years after stump removal and scarification on moderately coarse soils in interior British Columbia. For. Ecol. Manag. 2007, 242, 625–635. [Google Scholar] [CrossRef]
  56. Li, Q.; Allen, H.L.; Wollum II, A.G. Microbial biomass and bacterial functional diversity in forest soils: Effects of organic matter removal, compaction, and vegetation control. Soil Biol. Biochem. 2004, 36, 571–579. [Google Scholar] [CrossRef]
  57. Curran, M.; Dubé, S.; Bulmer, C.; Berch, S.; Chapman, B.; Hope, G.; Currie, S.; Courtin, P.; Kranabetter, M. Forest and Range Evaluation Program, Ministry of Forests and Range and Ministry of the Environment; Protocol for Soil Resource Stewardship Monitoring: Victoria, BC, Canada, 2009. [Google Scholar]
  58. Nugent, C.; Kanali, C.; Owende, P.M.; Nieuwenhuis, M.; Ward, S. Characteristic site disturbance due to harvesting and extraction machinery traffic on sensitive forest sites with peat soils. For. Ecol. Manag. 2003, 180, 85–98. [Google Scholar] [CrossRef]
  59. Picchio, R.; Neri, F.; Petrini, E.; Verani, S.; Marchi, E.; Certini, G. Machinery-induced soil compaction in thinning two pine stands in central Italy. For. Ecol. Manag. 2012, 285, 38–43. [Google Scholar] [CrossRef]
  60. Walkley, A.; Black, I.A. An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci. 1934, 37, 29–38. [Google Scholar] [CrossRef]
  61. Salehi, A.; Ghorbanzadeh, N.; Kahneh, E. Earthworm biomass and abundance, soil chemical and physical properties under different poplar plantations in the north of Iran. J. For. Sci. 2013, 59, 223–229. [Google Scholar] [CrossRef] [Green Version]
  62. Kooch, Y.; Zaccone, C.; Lamersdorf, N.P.; Tonon, G. Pit and mound influence on soil features in an Oriental Beech (Fagus orientalis Lipsky) forest. Eur. J. For. Res. 2014, 133, 347–354. [Google Scholar] [CrossRef]
  63. Tavankar, F.; Majnounian, B.; Bonyad, A.E. Logging damages on forest regeneration and soil compaction using ground-based system (case study: Asalem forest area, Guilan). Water Soil Sci. 2009, 13, 449–456. [Google Scholar]
  64. Gayoso, J.; Iroume, A. Compaction and soil disturbances from logging in Southern Chile. Ann. Forest Sci. 1991, 48, 63–71. [Google Scholar] [CrossRef] [Green Version]
  65. Majnounian, B.; Jourgholami, M. Effect of rubber-tired cable skidder on soil compaction in Hyrcanian forest. Croat. J. For. Eng. 2013, 34, 123–135. [Google Scholar]
  66. Greacen, E.L.; Sands, R. Compaction of forest soils. A review. Soil Res. 1980, 18, 163–189. [Google Scholar] [CrossRef]
  67. Ampoorter, E.; De Schrijver, A.; Van Nevel, L.; Hermy, M.; Verheyen, K. Impact of mechanized harvesting on compaction of sandy and clayey forest soils: Results of a meta-analysis. Ann. For. Sci. 2012, 69, 533–542. [Google Scholar] [CrossRef] [Green Version]
  68. Botta, G.F.; Jorajuria, D.; Rosatto, H.; Ferrero, C. Light tractor traffic frequency on soil compaction in the Rolling Pampa region of Argentina. Soil Till. Res. 2006, 86, 9–14. [Google Scholar] [CrossRef]
  69. Eliasson, L. Effects of forwarder tyre pressure on rut formation and soil compaction. Silva Fenn. 2005, 39, 549. [Google Scholar] [CrossRef] [Green Version]
  70. Hatchell, G.E.; Ralston, C.W.; Foil, R.R. Soil disturbance in logging. J. For. 1970, 68, 772–775. [Google Scholar]
  71. Hosseini, S.A.O.; Nasiri, M.; Akbarimehr, M. Skidders traffic assessment on forest soil properties. Int. J. Civ. Eng. 2015, 13, 372–377. [Google Scholar]
  72. Demir, M.; Makineci, E.; Yilmaz, E. Investigation of timber harvesting impacts on herbaceous cover, forest floor and surface soil properties on skid road in an oak (Quercus petrea L.) stand. Build. Environ. 2007, 42, 1194–1199. [Google Scholar] [CrossRef]
  73. Demir, M.; Makineci, E.; Comez, A.; Yilmaz, E. Impacts of repeated timber skidding on the chemical properties of topsoil, herbaceous cover and forest floor in an eastern beech (Fagus orientalis Lipsky) stand. J. Environ. Biol. 2010, 31, 477–482. [Google Scholar]
  74. Jourgholami, M.; Nasirian, A.; Labelle, E. Ecological restoration of compacted soil following the application of different leaf litter mulches on the skid trail over a five-year period. Sustainability 2018, 10, 2148. [Google Scholar] [CrossRef] [Green Version]
  75. Prescott, C.E.; Grayston, S.J. Tree species influence on microbial communities in litter and soil: Current knowledge and research needs. For. Ecol. Manag. 2013, 309, 19–27. [Google Scholar] [CrossRef]
  76. Jourgholami, M.; Labelle, E.R. Effects of plot length and soil texture on runoff and sediment yield occurring on machine-trafficked soils in a mixed deciduous forest. Ann. For. Sci. 2020, 77, 19. [Google Scholar] [CrossRef]
  77. Jourgholami, M.; Fathi, K.; Labelle, E.R. Effects of litter and straw mulch amendments on compacted soil properties and Caucasian alder (Alnus subcordata) growth. New For. 2020, 51, 349–365. [Google Scholar] [CrossRef]
  78. Ampoorter, E.; De Schrijver, A.; De Frenne, P.; Hermy, M.; Verheyen, K. Experimental assessment of ecological restoration options for compacted forest soils. Ecol. Eng. 2011, 37, 1734–1746. [Google Scholar] [CrossRef]
Sustainability 12 02874 g001 550
Figure 1. The study area in the Namkhaneh and Gorazbon districts in the Hyrcanian forests and the skid trails in different years after skidding operation (3, 10, 20, and 25 years).
Figure 1. The study area in the Namkhaneh and Gorazbon districts in the Hyrcanian forests and the skid trails in different years after skidding operation (3, 10, 20, and 25 years).
Sustainability 12 02874 g001
Sustainability 12 02874 g002 550
Figure 2. A sketch of the sampling design in the skid trails and the undisturbed area. (A): Each skid trail was divided into three traffic intensities (high, medium, and low traffic intensity), and in each traffic class three slope classes were considered (0–10%, 10–20%, and 20–30%). The sampling plots were designed with dimensions of 40 m2 in each of the skid trail treatments, along with the sampling plots in the undisturbed area and the soil sampling point at depth intervals of 0–10 and 10–20 cm at the three locations in each plot (B): the left wheel track (LW), between the tracks (BW), and the right wheel track (RW).
Figure 2. A sketch of the sampling design in the skid trails and the undisturbed area. (A): Each skid trail was divided into three traffic intensities (high, medium, and low traffic intensity), and in each traffic class three slope classes were considered (0–10%, 10–20%, and 20–30%). The sampling plots were designed with dimensions of 40 m2 in each of the skid trail treatments, along with the sampling plots in the undisturbed area and the soil sampling point at depth intervals of 0–10 and 10–20 cm at the three locations in each plot (B): the left wheel track (LW), between the tracks (BW), and the right wheel track (RW).
Sustainability 12 02874 g002
Sustainability 12 02874 g003 550
Figure 3. Average rut depth under different traffic intensities in different skid trail age classes, and results of the Duncan’s multiple range tests.
Figure 3. Average rut depth under different traffic intensities in different skid trail age classes, and results of the Duncan’s multiple range tests.
Sustainability 12 02874 g003
Sustainability 12 02874 g004 550
Figure 4. Changes in earthworm density (left) and biomass (right) under different traffic intensities in the two soil depths.
Figure 4. Changes in earthworm density (left) and biomass (right) under different traffic intensities in the two soil depths.
Sustainability 12 02874 g004
Sustainability 12 02874 g005 550
Figure 5. Principal component analysis (PCA) ordination of the traffic intensity in skid trails (3, 10, 20, and 25, age of the skid trails; H, M, L, and Un, high, medium, and low traffic intensity and undisturbed area, respectively), and soil physical (BD, bulk density; TP, total porosity; MP, macroporosity; MIP, microporosity; PR, penetration resistance; SM, soil moisture), chemical (pH; EC, electrical conductivity; C, organic C; N, nitrogen content; C/N, C/N ratio; P, available phosphorous; K, available potassium; Ca, available calcium; Mg, available magnesium), and biological (Ew D, earthworm density; Ew B, earthworm biomass) properties.
Figure 5. Principal component analysis (PCA) ordination of the traffic intensity in skid trails (3, 10, 20, and 25, age of the skid trails; H, M, L, and Un, high, medium, and low traffic intensity and undisturbed area, respectively), and soil physical (BD, bulk density; TP, total porosity; MP, macroporosity; MIP, microporosity; PR, penetration resistance; SM, soil moisture), chemical (pH; EC, electrical conductivity; C, organic C; N, nitrogen content; C/N, C/N ratio; P, available phosphorous; K, available potassium; Ca, available calcium; Mg, available magnesium), and biological (Ew D, earthworm density; Ew B, earthworm biomass) properties.
Sustainability 12 02874 g005
Sustainability 12 02874 g006 550
Figure 6. PCA ordination of the slope classes in the skid trails (3, 10, 20, and 25, age of the skid trails; A, B, C, and Un, 0–10%, 10–20%, and 20–30% slope classes and undisturbed area, respectively), and soil physical (BD, bulk density; TP, total porosity; MP, macroporosity; MIP, microporosity; PR, penetration resistance; SM, soil moisture), chemical (pH; EC, electrical conductivity; C, organic C; N, nitrogen content; C/N, C/N ratio; P, available phosphorous; K, available potassium; Ca, available calcium; Mg, available magnesium), and biological (Ew D, earthworm density; Ew B, earthworm biomass) properties.
Figure 6. PCA ordination of the slope classes in the skid trails (3, 10, 20, and 25, age of the skid trails; A, B, C, and Un, 0–10%, 10–20%, and 20–30% slope classes and undisturbed area, respectively), and soil physical (BD, bulk density; TP, total porosity; MP, macroporosity; MIP, microporosity; PR, penetration resistance; SM, soil moisture), chemical (pH; EC, electrical conductivity; C, organic C; N, nitrogen content; C/N, C/N ratio; P, available phosphorous; K, available potassium; Ca, available calcium; Mg, available magnesium), and biological (Ew D, earthworm density; Ew B, earthworm biomass) properties.
Sustainability 12 02874 g006
Table
Table 1. Location and specifications of the study area.
Table 1. Location and specifications of the study area.
Age of Skid Trail (years)ReplicationDistrict (No. of Compartments)Skid Trail Length (m)Skid Trail Density
(m ha−1)		Elevation (m)Soil Texture
31stGorazbon (C. 315)85078.61186Clay
2ndGorazbon (C. 316)100071.31214Clay
3rdGorazbon (C. 316)90071.31191Silty clay loam
101stGorazbon (C. 318)93065.81186Clay loam
2ndGorazbon (C. 317)105084.81200Silty clay loam
3rdGorazbon (C. 317)86084.81090Clay loam
201stNamkhaneh (C. 221)100053.81120Silt loam
2ndNamkhaneh (C. 220)98551.31010Clay loam
3rdNamkhaneh (C. 220)80051.31117Clay
251stNamkhaneh (C. 218)104074.51050Clay
2ndNamkhaneh (C. 218)98074.51140Silty clay loam
3rdNamkhaneh (C. 221)95053.81020Clay
Table
Table 2. Analysis of variance (p-values) of the effect of abandoned skid trails, traffic intensity, slope, wheel track location, soil sampling depth, and their interactions on the physical properties of the soil.
Table 2. Analysis of variance (p-values) of the effect of abandoned skid trails, traffic intensity, slope, wheel track location, soil sampling depth, and their interactions on the physical properties of the soil.
Source of VarianceAge of Skid TrailTraffic IntensitySlopeWheel TrackDepthInteraction
d.f.p-Valued.f.p-Valued.f.p-Valued.f.p-Valued.f.p-Valued.f.p-Value
BD (g cm−3)30.000 **20.000 **20.418 ns20.254 ns10.000 **240.63 ns
PR (MPa)30.000 **20.000 **20.000 **20.000 **10.000 **240.998 ns
TP (%)30.000 **20.000 **20.041 *20.224 ns10.005 **240.993 ns
MP (%)30.000 **20.546 ns20.305 ns20.350 ns10.000 **240.998 ns
MIP (%)30.000 **20.549 ns20.481 ns20.783 ns10.000 **240.999 ns
SM (%)30.000 **20.549 ns20.481 ns20.783 ns10.000 **240.999 ns
Note: * p < 0.05; ** p < 0.01; ns not significant; BD, bulk density, PR, penetration resistance; TP, total porosity; MP, macroporosity; MIP, microporosity; SM, soil moisture; df, degrees of freedom.
Table
Table 3. Changes in the physical properties of the soil (mean ± standard error) in different years after the skidding operation.
Table 3. Changes in the physical properties of the soil (mean ± standard error) in different years after the skidding operation.
Different Years After the Skidding Operation (Years)
Soil Physical Properties3102025Un
BD (g cm−3)1.07 ± 0.01 a1.12 ± 0.01 b1.05 ± 0.01 a1.03 ± 0.01 a0.95 ± 0.03 c
PR (MPa)3.25 ± 0.06 a3.04 ± 0.04 b2.90 ± 0.04 b2.0 ± 0.04 c1.57 ± 0.12 d
TP (%)84.03 ± 0.23 b83.0 ± 0.15 c84.04 ± 0.15 b84.47 ± 0.15 ab86.16 ± 0.48 a
MP (%)51.23 ± 0.57 c52.66 ± 0.38 c53.14 ± 0.38 b55.36 ± 0.38 b66.78 ± 0.19 a
MIP (%)32.8 ± 0.63 a30.34 ± 0.42 a30.9 ± 0.42 b29.11 ± 0.42 b19.38 ± 1.3 c
SM (%)40.2 ± 1.24 c41.2 ± 0.82 b41.76 ± 0.82 b42.73 ± 0.82 b44.78 ± 2.58 a
Note: Different letters in a row indicate significant differences among the intensities of the physical properties of the soil (p < 0.05), based on the Duncan’s multiple range tests. The values 3, 10, 20, and 25 denote the age of the skid trails; Un, undisturbed area; BD, bulk density; PR, penetration resistance; TP, total porosity; MP, macroporosity; MIP, microporosity; SM, soil moisture.
Table
Table 4. Analysis of variance (p-values) of the effect of abandoned skid trail, traffic intensity, slope, wheel track location, soil sampling depth, and their interaction on the chemical and biological properties of the soil.
Table 4. Analysis of variance (p-values) of the effect of abandoned skid trail, traffic intensity, slope, wheel track location, soil sampling depth, and their interaction on the chemical and biological properties of the soil.
Source of VarianceAge of Skid TrailTraffic IntensitySlopeWheel TrackDepthInteraction
d.f.p-Valued.f.p-Valued.f.p-Valued.f.p-Valued.f.p-Valued.f.p-Value
pH (1:2.5 H2O)30.000 **20.000 **20.000 **20.000 **10.000 **240.690 ns
EC (ds/m)30.000 **20.000 **20.000 **20.000 **10.000 **240.000 **
C (%)30.000 **20.000 **20.107 ns20.999 ns10.722 ns241.000 ns
N (%)30.000 **20.000 **20.000 **20.361 ns10.000 **241.000 ns
C/N ratio30.000 **20.000 **20.000 **20.302 ns10.000 **240.035 *
Available P (mg kg−1)30.000 **20.000 **20.000 **20.513 ns10.006 **241.000 ns
Available K (mg kg−1)30.000 **20.000 **20.000 **20.694 ns10.020 *241.000 ns
Available Ca (mg kg−1)30.000 **20.000 **20.000 **20.256 ns10.000 **241.000 ns
Available Mg (mg kg−1)30.000 **20.000 **20.001 **20.813 ns10.050 *241.000 ns
Earthworm density (n m−2)30.199 ns20.422 ns20.090 ns20.001 **10.019 *240.652 ns
Earthworm biomass (mg m−2)30.215 ns20.429 ns20.115 ns20.002 **10.030 *240.687 ns
Note: * p < 0.05; ** p < 0.01; ns not significant.
Table
Table 5. Changes in the chemical and biological properties of the soil (mean ± standard error) in different years after the skidding operation.
Table 5. Changes in the chemical and biological properties of the soil (mean ± standard error) in different years after the skidding operation.
Different Years after the Skidding Operation (Years)
Soil Chemical and Biological Properties3102025Un
pH (1:2.5 H2O)5.96 ± 0.04 c6.07 ± 0.04 c6.32 ± 0.04 b6.59 ± 0.04 b7.04 ± 0.07 a
EC (ds/m)0.26 ± 0.19 c0.26 ± 0.19 c0.29 ± 0.19 b0.32 ± 0.19 b0.4 ± 0.35 a
C (%)2.31 ± 0.05 d2.78 ± 0.05 c2.9 ± 0.05 c3.12 ± 0.05 b4.04 ± 0.09 a
N (%)0.2 ± 0.05 d0.27 ± 0.05 c0.36 ± 0.05 b0.41 ± 0.05 b0.67 ± 0.01 a
C/N ratio11.55 ± 0.07 a10.29 ± 0.07 b8.05 ± 0.07 c7.61 ± 0.07 d6.03 ± 0.13 d
Available P (mg kg−1)9.59 ± 0.05 d12.01 ± 0.05 c14.49 ± 0.05 bc17.11 ± 0.05 b19.28 ± 0.09 a
Available K (mg kg−1)138.1 ± 1.08 d187.8 ± 1.08 cd238.4 ± 1.08 c275.7 ± 1.08 b321.49 ± 2.03 a
Available Ca (mg kg−1)105.7 ± 0.39 d137.1 ± 0.39 c176.6 ± 0.39 c214.3 ± 0.39 b239.05 ± 0.75 a
Available Mg (mg kg−1)28.85 ± 0.23 d37.23 ± 0.23 c44.27 ± 0.23 bc51.94 ± 0.23 b61.18 ± 0.43 a
Earthworm density (n m−2)0.22 ± 0.07 d0.33 ± 0.07 c0.41 ± 0.07 b0.48 ± 0.07 b0.67 ± 0.14 a
Earthworm biomass (mg m−2)0.94 ± 0.31 d1.41 ± 0.31 c1.71 ± 0.31 bc2.05 ± 0.31 b2.95 ± 0.59 a
Note: Different letters in a row indicate significant differences among the intensities of the physical properties of the soil (p < 0.05), based on Duncan’s multiple range tests. The values 3, 10, 20, and 25, denote the age of the skid trails; Un, undisturbed area.
Table
Table 6. Pearson correlation coefficients between the soil properties and the effective treatments on soil (traffic intensity and slope classes of three-year-old skid trails).
Table 6. Pearson correlation coefficients between the soil properties and the effective treatments on soil (traffic intensity and slope classes of three-year-old skid trails).
Variable Traffic IntensitySlope Classes
Pearson Correlation (R)p-ValuePearson Correlation (R)p-Value
Soil physical propertiesBD0.92 **0.0000.83 **0.000
PR0.95 **0.0000.93 **0.000
TP–0.76 **0.000–0.91 **0.000
MP–0.52 *0.021–0.99 **0.000
MIP–0.51 *0.015–0.58 *0.020
SM–0.52 *0.015–0.58 *0.020
Soil chemical propertiespH–0.98 **0.000–0.98 **0.000
EC–0.94 **0.000–0.95 **0.000
C–0.97 **0.000–0.98 **0.000
N–0.98 **0.000–0.98 **0.000
C/N0.84 **0.0000.67 **0.000
Available P–0.98 **0.000–0.98 **0.000
Available K–0.98 **0.000–0.98 **0.000
Available Ca–0.98 **0.000–0.97 **0.000
Available Mg–0.99 **0.000–0.98 **0.000
Soil biological propertiesEw D–0.96 **0.000–0.88 **0.000
Ew B–0.96 **0.000–0.90 **0.000
** A significant difference at the 0.01% level. * A significant difference at the 0.05% level. BD, bulk density; TP, total porosity; MP, macroporosity; MIP, microporosity; PR, penetration resistance; SM, soil moisture; EC, electrical conductivity; C, organic C; N, nitrogen content; C/N, C/N ratio; P, available phosphorous; K, available potassium; Ca, available calcium; Mg, available magnesium; Ew D, earthworm density; Ew B, earthworm biomass.

Share and Cite

MDPI and ACS Style

Sohrabi, H.; Jourgholami, M.; Jafari, M.; Shabanian, N.; Venanzi, R.; Tavankar, F.; Picchio, R. Soil Recovery Assessment after Timber Harvesting Based on the Sustainable Forest Operation (SFO) Perspective in Iranian Temperate Forests. Sustainability 2020, 12, 2874. https://doi.org/10.3390/su12072874

AMA Style

Sohrabi H, Jourgholami M, Jafari M, Shabanian N, Venanzi R, Tavankar F, Picchio R. Soil Recovery Assessment after Timber Harvesting Based on the Sustainable Forest Operation (SFO) Perspective in Iranian Temperate Forests. Sustainability. 2020; 12(7):2874. https://doi.org/10.3390/su12072874

Chicago/Turabian Style

Sohrabi, Hadi, Meghdad Jourgholami, Mohammad Jafari, Naghi Shabanian, Rachele Venanzi, Farzam Tavankar, and Rodolfo Picchio. 2020. "Soil Recovery Assessment after Timber Harvesting Based on the Sustainable Forest Operation (SFO) Perspective in Iranian Temperate Forests" Sustainability 12, no. 7: 2874. https://doi.org/10.3390/su12072874

APA Style

Sohrabi, H., Jourgholami, M., Jafari, M., Shabanian, N., Venanzi, R., Tavankar, F., & Picchio, R. (2020). Soil Recovery Assessment after Timber Harvesting Based on the Sustainable Forest Operation (SFO) Perspective in Iranian Temperate Forests. Sustainability, 12(7), 2874. https://doi.org/10.3390/su12072874

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop