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Article

Post-Harvest Evaluation of Logging-Induced Compacted Soils and the Role of Caucasian Alder (Alnus subcordata C.A.Mey) Fine-Root Growth in Soil Recovery

by
Zahra Rahmani Haftkhani
1,
Mehrdad Nikooy
1,*,
Ali Salehi
1,
Farzam Tavankar
2 and
Petros A. Tsioras
3,*
1
Department of Forest Science and Engineering, Faculty of Natural Resources, University of Guilan, Sowmeh Sara 41996-13776, Iran
2
Department of Forestry, Khalkhal Branch, Islamic Azad University, Khalkhal 56817-31367, Iran
3
Lab of Forest Utilization, School of Forestry and Natural Environment, Aristotle University of Thessaloniki, P.O. Box 227, 541 24 Thessaloniki, Greece
*
Authors to whom correspondence should be addressed.
Forests 2025, 16(7), 1044; https://doi.org/10.3390/f16071044
Submission received: 17 April 2025 / Revised: 18 June 2025 / Accepted: 19 June 2025 / Published: 21 June 2025
(This article belongs to the Section Forest Soil)
Browse Figures
Versions Notes

Abstract

Accelerating the recovery of compacted soils caused by logging machinery using bioengineering techniques is a key goal of Sustainable Forest Management. This research was conducted on an abandoned skid trail with a uniform 15% slope and a history of heavy traffic, located in the Nav forest compartment of northern Iran. The main objectives were to assess (a) soil physical properties 35 years after skidding by a tracked bulldozer, (b) the impact of natural alder regeneration on soil recovery, and (c) the contribution of alder fine-root development to the restoration of compacted soils in beech stands. Soil physical properties and fine root biomass were analyzed across three depth classes (0–10 cm, 10–20 cm, 20–30 cm) and five locations (left wheel track (LT), between wheel tracks (BT), right wheel track (RT)) all with alder trees, and additionally control points inside the trail without alder trees (CPWA), as well as outside control points with alder trees (CPA). Sampling points near alder trees (RT, LT, BT) were compared to CPWA and CPA. CPA had the lowest soil bulk density, followed by LT, BT, RT, and CPWA. Bulk density was highest (1.35 ± 0.07 g cm−3) at the 0–10 cm depth and lowest (1.08 ± 0.4 g cm−3) at 20–30 cm. The fine root biomass at 0–10 cm depth (0.23 ± 0.21 g dm−3) was significantly higher than at deeper levels. Skid trail sampling points showed higher fine root biomass than CPWA but lower than CPA, by several orders of magnitude. Alder tree growth significantly reduced soil bulk density, aiding soil recovery in the study area. However, achieving optimal conditions will require additional time.

1. Introduction

Forest soil compaction is one of the most important effects of ground-based skidding operations. The compaction of forest soils caused by the traffic of logging machines leads to reductions in soil pores, porosity, and soil aeration [1,2]. Undisturbed forest soil usually has high porosity and low bulk density, which makes it prone to being compacted by logging equipment/machinery. Soil compaction reduces soil characteristics such as porosity, hydraulic conductivity, permeability, ventilation, gas exchange and root growth, and overall may lead to impaired soil function [3,4]. Twum and Nii-Annang [5] reported that forest machinery considerably increased bulk density and penetration resistance, which rarely exceeded growth limits for optimal root elongation. According to Ampoorter et al. [6], logging machine traffic affects the growth of the remaining forest trees; however, its greatest impact is on the soil of the forest, especially the soil of the logging roads [7]. As a result of soil compaction, the growth and penetration of roots decreases, which causes less absorption of nutrients and water, and eventually, to decreased tree growth [8]. The recovery of disturbed forest soils under unfavorable climatic conditions and a lack of optimal management practices, as in the case of skidding during rainy days, can be very slow. Depending on various factors such as soil texture, weather conditions, the severity and extent of damages and soil fauna and flora activity, soil recovery can vary from 1 year, referring to the soil surface, up to 100 years for deeper soil layers [9]. The destruction and displacement of the layer of surface litter on the logging roads is another effect of ground-based skidding [10,11]. This mixing and removal of the litter layer with the surface soil causes changes in the physical, chemical, and biological properties of the soil and the availability of nutrients [12]. In order to speed up the recovery of the compacted soil of skid trails, the implementation of best management techniques that include the use of water diverters and plant mulches is strongly suggested [13,14].
The use of biological tillage is one of the ways to accelerate soil recovery on skid trails. In recent years, there has been a strong emphasis on enhancing the soil conditions of skid trails by planting trees. It is well known that alder species (Alnus spp.) are useful for soil amendment and can tolerate the challenging conditions of skid trails [15,16]. Furthermore, alder species develop a symbiotic relationship with Frankia spp. bacteria., enabling biological nitrogen fixation and stimulating microbial activity [17,18]. These traits contribute to improved soil structure and fertility, thereby enhancing ecosystem recovery. Beyond nitrogen fixation, alder species have been associated with increased soil enzyme activities and nutrient content, particularly carbon and nitrogen, in the upper soil layers [19].
The morphology and spatial distribution of fine roots are also important. Rapid fine root growth and high root turnover production has been reported to contribute to soil aggregation at the physical and biochemical level [20,21]. Physically, fine roots penetrate compacted soil layers, increasing porosity, soil aeriation and water infiltration, and reducing bulk density [22]. Biochemically, root exudates release extracellular polymeric substances such as polysaccharides, proteins, and lipids, which act as binding agents that facilitate the formation and stabilization of soil aggregates [23,24].
Recent studies continue to demonstrate this recovery potential in skid trails, where the growth of alder trees on skid trails has led to the recovery of the bulk density, coarse porosity, and total porosity of the soil at a depth of 1–6 cm [25]. In Switzerland, an evaluation of the effects of alder planting on logging roads found no obstacles to root penetration in the soil [26]. Fernández et al. [1] observed the positive effect of planting alder species on improving the soil microporosity in skid trails. They also showed that due to the planting of alder species, the bulk density of skid trails has decreased compared to the control area. In addition, in a soil compaction test, the rooting ability of alder species compared to other broad-leaved species has been proven [27], which possibly contributes to their effectiveness in restoring soil structure. The recovery of the physical properties of the soil in skid trails under different treatments was investigated in the forests of the Bern region in Switzerland [28]. This study showed that the development of the root system of black alder trees (Alnus glutinosa (L.) Gaertn.) can accelerate the restoration of damaged soils. Despite the strong and deep compaction of the studied soil, signs of recovery were observed even at a depth of 0.7 m in a period of only seven years. Warlo et al. [25], by investigating the characteristics of the soil in a ten-year skid trail with and without planting black alder, showed that ten years after soil compaction, the bulk density in the left and right tracks was still higher than in the control area. The highest values were found at a depth of 20–30 cm and decreased at higher depths. However, except for the depth of 40–50 cm, no significant difference in bulk density was evident between the planted skid trails and unplanted skid trails.
However, the soil amendment of the skid trail is not limited to alder species. In Iran, 25 years after logging, earthworm density and soil biomass were higher in the soils of skid trails planted with maple (Acer velutinum Boisis) and Caucasian alder (Alnus subcordata C.A.Mey) than in the control area [29]. Also, Jourgholami et al. [30] tested the soil recovery potential of skid trails with different combinations of Japanese maple (Acer palmatum Thunb.), Oriental beech (Fagus orientalis Lipsky) and European hornbeam (Carpinus betulus L.) leaf litter. The results of their study show that a combination of the litter of these three species had the greatest effect on restoring the physical, chemical and biological properties of the skid trail soil.
Despite several studies exploring soil recovery, few have addressed long-term changes (>30 years) or quantified the role of fine roots in natural regeneration contexts. This study addresses this gap by evaluating the long-term recovery of skid trail soils influenced by naturally regenerated Alnus subcordata. Caucasian alder was considered as an ideal candidate, as it is a fast-growing species with natural occurrence in the study area, and has been studied in various regions in Europe and Asia. We hypothesize that (a) compacted soils recover fully over 35 years, and (b) the natural growth of alder trees accelerates this recovery.

2. Materials and Methods

2.1. Study Area

The study site was in the Nav forest (37°38′21″ N 48°46′30″ E, 1550 m above sea level) in northern Iran (Figure 1). The mean annual temperature at the closest meteorological station is −5 °C in the winter and 26 °C in the summer, and the mean annual precipitation is 1050 mm. The study area has a north–northwest aspect and is relatively uneven, with an average slope of 35%. The soil has a sandy loam texture and belongs to the Luvisols. The forest is a pure oriental beech stand (Fagus orientalis Lipsky), with individual trees of European hornbeam (Carpinus betulus L.), Caucasian alder (Alnus subcordata C.A.Mey), and Cappadocian maple (Acer cappadocicum Gled.). The stand density and the standing volume were measured at 230 trees Ha−1 and 226 m3 Ha−1, respectively.
Marked trees were felled in a semi-mechanized way, whereby the shelterwood method was used, resulting in a harvesting volume of 3200 m3 log felled by chainsaw. Skidding operation was carried out in the summer of 1989 by a tracked bulldozer along a 950-meter-long skid trail. No specific instructions were given to the logging and skidding crews at the time of operations. The slope of the studied skid trail was 15% and the traffic intensity was severe, with more than 15 skidding cycles performed on it. The tracked bulldozer carried, on average, about three logs that corresponded to a volume of 2.35 m3 per skidding cycle. After the end of the skidding operations, the study area was fenced with barbed wire and no operations have been carried out in the studied parcel for the last 35 years.

2.2. Sampling Design

Nine rectangular plots measuring 20 m long and 4 m wide located on similar slope gradients were randomly established along the examined skid trail. Micro-environmental variables such as light availability and rainfall interception were not individually measured or controlled. Each plot had naturally grown alder trees (Figure 2), and three alder trees were selected as follows: (i) one on the left wheel track (LT), (ii) one on the right wheel track (RT) and (iii) one on the space between the two wheel tracks (BT). Additionally, two control points were selected in each plot, the first located 20 m outside the skid trail in an area with alder trees (CPA), and the second positioned inside the skid trail in an area without alder trees (CPWA) (Figure 3). All selected trees had nearly identical diameters (25–30 cm) and heights (12–15 m). At a distance of 1 m from the alder tree stems, soil samples were collected in three depth classes (0–10 cm, 10–20 cm and 20–30 cm) [31]. Steel cylinders, measuring 100 mm long and 56 mm in diameter, were used to collect the samples, which were later transported in plastic bags to the laboratory. In each of the nine plots, one unique sampling point was designated for LT, BT, RT, CPA and CPWA, resulting in a total of 45 soil samples that were collected and analyzed.
Samples were weighed on the day of collection and were oven-dried at 105 °C until a constant mass was achieved to gravimetrically determine bulk density [32,33]. Particle size distribution was determined using the Bouyoucos hydrometer method [34]. Following the removal of organic matter, calcium carbonate (CaCO3) and iron oxides, 30 mL of a 1% w/v sodium hexametaphosphate (Na6P6O18) solution (10 g/L) was added to 50 g of soil. This dispersing agent facilitated the chemical separation of the soil particles, whereas mechanical separation was possible using a mechanical stirrer (mixer) for 15 min.
To determine fine root biomass, samples measuring 10 cm × 10 cm × 10 cm were collected at a depth of 30 cm. Fine roots, with a diameter of less than 2 mm, were separated from the soil samples and washed using a 2 mm sieve. The sieved samples were oven-dried at 70 °C for 24 h. The masses of the dried samples were used to calculate their density per square meter for each sample.

2.3. Analysis of Data

The normality of the data was checked using the Kolmogorov–Smirnov test and the homogeneity of variances was evaluated using the Levene test.
One-way analyses of variance were used to identify statistically significant differences among treatment means. Post hoc comparisons of the treatment group means were performed using the Duncan test with significance determined at p ≤ 0.05.
Two-way analyses of variance were applied to relate soil property responses across the examined soil depths, treatments, and their interactions. Treatment effects were considered statistically significant at p ≤ 0.05. The data were analyzed using the SPSS statistical package, version 23 (Chicago, IL, USA).

3. Results

3.1. Soil Moisture

No statistically significant differences were found in terms of the effects of treatment, depth, or their interaction on soil moisture (Table 1). Soil moisture ranged from 23.85% to 30.55% (Table 2). The lowest moisture percentage value was related to LT at a depth of 20–30 cm (23.85 ± 1.13%) and the highest moisture percentage value was related to the CPA region at the depth of 0–10 cm (30.55 ± 1.24%) (Table 1). The analysis shows that the effect of treatment, soil depth, and their interaction on soil moisture was not statistically significant (p ≥ 0.05).

3.2. Soil Texture

The texture of all studied samples was sandy loam, with sand constituting, in most cases, more than 60% of the sample mass (range: 56.41%–66.25%) and silt more than 30% of it (range: 24.36%–33.42%) (Table 3).

3.3. Soil Bulk Density

The two-factor analysis of variance (ANOVA), considering treatments and soil depths, revealed a significant effect of both factors on average bulk density (Table 4). However, this was not the case for their interaction. The average bulk density in CPWA was significantly higher than at all examined depths. On the contrary, no significant differences were observed among the other treatments, although the CPA treatment exhibited the lowest average bulk density (Figure 4).
At all soil depths, CPA exhibited the lowest bulk density values, ranging from 1.02 to 1.35 g cm−3, whereas the highest were found in CPWA, ranging from 1.13 to 1.41 g cm−3 (Table 5). LT, BT and RT bulk density values are in most cases closer to CPA, as a comparison of average bulk density values across the examined treatments shows (Figure 4).
The average bulk density values across the examined treatments ranged from 1.09 to 1.24 g dm−3 in CPA, LT, BT and RT, and differed significantly to CPWA’s average value of 1.30 g dm−3 (F = 7.370, df = 4, p < 0.001) (Figure 4). Regarding soil depth, the comparison of average bulk density values across depth classes indicated that the highest bulk density occurred at a depth of 20–30 cm (1.35 g cm−3), while the lowest was observed at 0–10 cm (1.08 g cm−3). Significant differences were found between the average bulk density values of the three depth classes (F = 91.263, df = 2, p < 0.001) (Figure 5).

3.4. Fine Root Mass

The analysis of variance of two factors (treatments and soil depths) showed that there is a significant difference between the average values of fine root mass between treatments and soil depths, and for the interactions between them (Table 6).
Overall, the fine root mass values were the highest in CPA at all examined soil depths (Table 7). The highest amount of fine root mass belonged to CPA at a depth of 0–10 cm (1.18 ± 0.778 g dm−3) and was significantly higher compared to the other treatments, whereas the lowest amount belonged to CWPA at a depth of 20–30 cm (0.009 ± 0.002 g dm−3). RT, BT and LT seem to follow the same fine root mass distribution pattern across the various soil depths, and statistically significant differences were found among them at the same depths. RT and LT exhibited almost identical fine root mass quantities, whereas this was slightly increased in BT at a depth of 0–10 cm (0.250 vs. 0.152 g dm−3), but its value was still not statistically significant. The lowest amount of fine root mass at all examined soil depths belonged to CPWA, ranging from 0.009 to 0.002 g dm−3, and were many times lower compared to the other treatments.

4. Discussion

In forestry, modern logging machines operate throughout the year, primarily for economic reasons and regardless of weather and soil interactions, causing soil structure changes and soil compaction [35]. Factors such as climatic conditions, degree of compaction, moisture level, soil type, vegetation, the expansion and contraction of soil, period of the freezing and melting of ice, the rooting of plants, the amount of organic matter, the amount of rainfall and physiographic factors (height above sea level, the slope of the area and the direction) have effects on the process of soil recovery [36]. Different methods can be used in order to accelerate the soil recovery process after the completion of forest operations, with biological tillage being one of them. In this study, we investigated the effect of naturally grown Caucasian alder (Alnus subcordata C.A.Mey) trees on the soil recovery of heavily compacted skid trails impacted by skidding operations 35 years ago.

4.1. Soil Bulk Density

The results of the study show that the soil bulk density in all treatments where alder trees were present (RT, BT, LT and CPA) was significantly lower than where trees were missing (CPWA) (Table 5 and Figure 4). The presented values for soil bulk density measured on the wheel tracks (LT and RT) and between tracks (BT) are comparable to those for CPA and distinctly different to those for CPWA. When monitoring the recovery of a compacted forest soil structure, treated with a combination of regeneration techniques and mulching, liming, planting of grey alder trees or a combination of those, we observed improvement in terms of the soil aeration status and acceleration of its recovery [1]. Warlo et al. [37], after examining soil recovery on skid trails planted with black alder and untreated skid trails in northeastern Switzerland, reported that a decrease in bulk density to 1.23 g cm−3 and an increase in soil porosity to 57% in the treated skid trails indicated their partial structural recovery. Meyer et al. [28] examined planting black alders into the ruts of skid lanes, with and without the application of compost, and its effects on the regeneration of soil structure in a gleyic Cambisol on the Swiss Plateau. Their results indicate that the planting of black alder combined with compost application resulted in a significant regeneration of structure, although recovery was still far from complete compared to the untrafficked reference soil. However, without compost, there was no significant treatment effect compared to the unplanted skid lanes. Meyer et al. [26] examined the potential of accelerating soil regeneration by planting black alder trees (A. glutinosa (L.) Gaertn.) in skid lane tracks. The tree growth was exceptionally strong on the skid lanes. Furthermore, total and coarse soil porosity showed significant increases in the planted skid lanes as compared to untreated control subplots, approaching the values found for untrafficked soil in the immediate vicinity.
Skid trails created during logging operations can adversely impact soil structure and rooting conditions, often leading to long-term compaction and degradation. Previous studies have investigated the roles of various natural and anthropogenic measures in mitigating these effects and accelerating soil recovery. Schäffer et al. [38], during the analysis of fine rooting below skid trails, reported that fine root density was higher in the topsoil than in the deeper soil horizons. According to their results, rooting was almost non-existent on the right-hand track, but the left-hand track was in comparatively better condition. Only on the edge closest to the track was the rooting condition normal, where it could be considered similar to the control area. The rooting condition was also moderate in the middle section of the track, which had not been subjected to traffic. In addition to the protective effect of the branches and crowns of alder trees on the soil of the skid trails, the development of the root system of the alder tree can restore the compacted soil of the skid trails and improve the physical parameters of the soil, such as bulk density. Also, the positive role of organic materials such as litter [30], saw dust [39,40], leaves [40], agricultural straw [40], wood fiber [41], and hydro-mulch [42] in speeding up the recovery of the physical characteristics of the soil on logging roads has been reported. Jourgholami et al. [42] reported an increase in bulk density on skid trail soil following the implementation of saw dust and water diversion structures. However, their final results indicate that despite their implementation, these treatments did not result in the full recovery of the soil. According to Jourgholami et al. [30], the application of leaf litter mulches was very beneficial to the compacted soil, significally improving its properties across all examined treatments. Despite the improvements within a 5-year long period, the examined soil properties still fell behind compared to the control treatment values. Khoramizadeh et al. [40] highlighted the role of litter mulch, straw mulch, and sawdust in enhancing soil quality on skid trails. Similarly, Jourgholami et al. [43] demonstrated the effectiveness of harvesting residues and organic mulch in restoring compacted soil, as well as mitigating surface runoff and rill and interrill erosion. Additionally, the construction of water bars had positive effects within a period of 7 to 11 years, particularly in skid trails with low slope and low traffic, by promoting the recovery of soil properties and soil moisture [44,45].

4.2. Soil Moisture

The results of the average moisture percentage of the studied treatments show that the lowest moisture percentage was related to the left wheel track area at a depth of 20–30 cm, and the highest moisture percentage was related to the control area at a depth of 0–10 cm. In these areas, after 35 years, there were no significant differences between the levels of soil moisture between the control areas and logging routes, suggesting an improvement in soil conditions for water retention. Our findings are in line with those of previous studies reporting that the growth of alder trees on skid roads increases the soil moisture and water retention, and leads to the restoration of soil’s physical properties [46,47].

4.3. Fine Roots

In the present study, the effects of the natural growth of alder species on the distribution of fine root biomass in different treatments (CPA, RT, BT, LT, and CPWA) across three depth classes of 0–10, 10–20 and 20–30 cm were studied. Fine root biomass was highest in CPA, followed by BT, which correlates with lower bulk density values. This suggests that the fine roots of Alnus subcordata contribute to loosening compacted soils by increasing porosity. Their role is both physical—via soil penetration—and biochemical—via root exudates that facilitate aggregation. Although the results related to RT and LT showed a significant difference compared to the CPWA, they still remained lower than those observed in CPA. Fernández-Méndez et al. [48] studied the planting of alder trees on the edges of skid trails, and reported the highest amount of fine root mass in BT. Warlo et al. [37], after studying the characteristics of soil structure in a ten-year old skid trail with and without black alder treatments in Switzerland, reported the highest root biomass in the control areas and the lowest in the untreated areas. A similar finding has been reported by Malo and Messier [49] for the root growth of Acer saccharum Marsh. in Quebec, Canada.
According to our findings, the largest amount of fine roots was present at a depth of 0–10 cm, and the amount of fine roots decreased with increasing depth, which is in line with the results of previous studies [49,50]. Flores Fernández et al. [13] also reported the highest amount of fine roots biomass at a depth of 0–10, although in their study, they reported a lack of significant differences across soil depths.
These patterns are consistent with the known ecological behaviors of fine roots, which tend to concentrate in upper soil layers where water, nutrients, and gas exchange are more available [1]. Fine roots are responsible for resource uptake, carbon cycling, and the formation of soil aggregates through root exudates and microbial interactions [51,52,53,54]. It has been documented that the carbon and nutrients released to the soil through root micro decomposition can exceed those from leaves’ decomposition [55], a pattern observed across various forest soils with different physical characteristics [56,57]. The development of fine roots is often limited by soil compaction, an adverse condition commonly induced by ground-based logging machinery [40,58,59]. Compacted soils restrict rooting by reducing pore space and oxygen availability, directly impacting fine root growth and turnover.
However, our results suggest that alder species—especially in CPA and BT—contribute to overcoming these constraints. Alders are known for their high tolerance to degraded soils [60] and their ability to improve soil structure through vigorous rooting and nitrogen fixation. Previous research has demonstrated that alder root systems can help restore compacted soil conditions. For example, Flores Fernández [13] found that grey alder outperformed willow and black alder in terms of both survival and growth in compacted skid trails. Similarly, black and grey alder showed greater success than Salix caprea and Rhamnus frangula, further supporting our observations.

4.4. Study Limitations, Outcome Interpretations and Future Research Directions

Despite our efforts to ensure a robust study design, with all plots randomly established along the same skid trail under similar slope gradients and stand conditions, measurements of light availability or rainfall interception were not conducted. We acknowledge that spatial variation in these environmental factors may have influenced soil recovery dynamics and fine root development. Future studies should incorporate such variables in order to improve the accuracy and generalizability findings.
Notwithstanding these limitations, our results provide partial support for our hypothesis (a), which suggests that the compacted soils underwent substantial recovery over the 35-year period, particularly in upper layers and in the presence of alder. However, soil parameters in the CPWA indicate that full recovery has not yet been achieved across all treatments. In contrast, hypothesis (b), which asserts that the natural growth of alder trees accelerates soil recovery, is strongly supported by the observed improvements in bulk density and fine root biomass in the LT, BT, and RT.
One potential explanation for discrepancies among similar studies might be that most studies have focused on isolated aspects of fine root growth and their individual impacts on soil recovery. Moreover, many of these studies followed short-term experimental designs, failing to fully capture the long-term complexity of soil recovery processes. Future research should adopt a more comprehensive approach to provide meaningful insights for forest managers. In this regard, the application of advanced analytical techniques—such as structural equation modeling (SEM) and time-series analyses—is highly recommended, offering enhanced inferential power and facilitating a better understanding of the multifaceted interactions among soil properties, vegetation dynamics and anthropogenic influences.

5. Conclusions

The results of this study show that the growth of alder trees effectively contributed to the recovery of bulk density and fine root mass in logging-induced compacted soils, particularly in the upper soil layer (0–10 cm) and the between-tracks (BT) area. Compared to control plots without alder trees (CPWA), bulk density was reduced by approximately 9% in plots with alder trees (CPA), and fine root biomass increased by up to 450%. However, the bulk density in CPWA still remained 5%–10% higher than in CPA, indicating that full recovery had not yet occurred 35 years after the skidding operations and failing to confirm our first hypothesis. Based on these findings, we recommend integrating alder planting on compacted sites as a bioengineering strategy, supported by soil amendments where feasible. Furthermore, our results of partial soil recovery, as in the upper soil layers, indicate that the natural growth of Alnus subcordata significantly accelerated recovery processes, affirming our second hypothesis.
Since machinery-induced soil compaction is a major factor in reducing fine roots in skid trails, the use of best management practices and the smarter planning of skid roads to limit soil compaction should be prioritized during both the planning phase and the practical implementation of logging activities. Based on our results, planting alder tree saplings will be effective in speeding up the recovery of compacted forest soils during logging operations. Moreover, the fine root development of alder trees is expected to be effective in restoring the chemical and biological functions of the soil and minimize soil water erosion, especially if combined with organic soil amendments and water bar construction, where necessary.
To fully understand the mechanisms and long-term potential of encouraging fine root growth for soil recovery, future research should examine a broader range of environmental and management variables over extended monitoring periods. In this context, it would be valuable to investigate the restoration potential of additional species—such as maple and some conifers—that have been used in the study area to rehabilitate soil properties on skid trails.

Author Contributions

Conceptualization, M.N.; methodology, M.N.; formal analysis, M.N. and P.A.T.; investigation, M.N., Z.R.H., A.S. and F.T.; resources, M.N., Z.R.H., A.S. and F.T.; data curation, M.N., P.A.T., Z.R.H. and F.T.; writing—original draft preparation, M.N., P.A.T., Z.R.H. and F.T.; writing—review and editing, M.N. and P.A.T.; visualization, M.N., P.A.T. and F.T.; supervision, M.N. and F.T.; project administration, M.N. and F.T.; funding acquisition, M.N. and A.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data presented in this study will be made available upon request from the corresponding author.

Acknowledgments

We thank all the individuals involved in the project for their expertise and assistance in all aspects of our study, and for their help in developing and reviewing the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Location of study area in a map of Iran (left), and in a map of the Nav forests (right).
Figure 1. Location of study area in a map of Iran (left), and in a map of the Nav forests (right).
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Figure 2. Alder trees growing on abandoned skid trails in the study area.
Figure 2. Alder trees growing on abandoned skid trails in the study area.
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Figure 3. Graphical presentation of the sampling points selection method at the plot level: CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees).
Figure 3. Graphical presentation of the sampling points selection method at the plot level: CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees).
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Figure 4. Comparison of the average soil bulk density across the examined treatments: CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees). Different letters indicate statistically significant differences among treatments based on Duncan’s post hoc test (p < 0.05).
Figure 4. Comparison of the average soil bulk density across the examined treatments: CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees). Different letters indicate statistically significant differences among treatments based on Duncan’s post hoc test (p < 0.05).
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Figure 5. Comparison of the bulk density mean values across the examined soil depths. Different letters indicate statistically significant differences among soil depths based on Duncan’s post hoc test (p < 0.05).
Figure 5. Comparison of the bulk density mean values across the examined soil depths. Different letters indicate statistically significant differences among soil depths based on Duncan’s post hoc test (p < 0.05).
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Table 1. Results of two-way analysis of variance (ANOVA) for the effects of treatment, depth and their interaction (treatment × depth) on soil moisture.
Table 1. Results of two-way analysis of variance (ANOVA) for the effects of treatment, depth and their interaction (treatment × depth) on soil moisture.
SourceSum-of-SquaresDegrees of FreedomMean SquaresF Ratiop-Value
Treatment57.86414.472.480.066
Depth22.68211.341.940.161
Depth × Treatment53.2786.661.140.367
Error175.37305.852.48
Total34,532.654514.47
Table 2. Average soil moisture (mean ± standard error) by treatment: CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees).
Table 2. Average soil moisture (mean ± standard error) by treatment: CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees).
Depth (cm)Treatment
CPA (%)LT (%)BT (%)RT (%)CPWA (%)
0–10 cm30.55 ± 1.2426.05 ± 4.2629.14 ± 1.1428.00 ± 3.7228.66 ± 2.27
10–20 cm27.34 ± 3.7226.36 ± 1.6426.59 ± 0.9029.76 ± 1.6927.48 ± 2.27
20–30 cm27.47 ± 3.8923.85 ± 1.1327.44 ± 1.7425.43 ± 2.2129.54 ± 2.76
Table 3. Particle size distribution (%) of soil samples, showing the mean ± standard error for clay (<2 μm), silt (2–50 μm), and sand (50–2000 μm) fractions across different treatments in the research area: CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees).
Table 3. Particle size distribution (%) of soil samples, showing the mean ± standard error for clay (<2 μm), silt (2–50 μm), and sand (50–2000 μm) fractions across different treatments in the research area: CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees).
Soil Depth (cm)Sampling PointParticle Size Distribution
Clay (%)Silt (%)Sand (%)
0–10CPA13.23 ± 3.3424.36 ± 1.0562.41 ± 2.81
RT11.87 ± 2.0325.27 ± 0.9562.87 ± 1.21
BT9.27 ± 0.5930.50 ± 1.5760.23 ± 2.00
LT7.27 ± 1.2928.47 ± 2.9064.27 ± 1.94
CPWA8.20 ± 4.8031.10 ± 2.4560.70 ± 4.07
10–20CPA11.00 ± 2.2625.93 ± 2.6763.07 ± 1.80
RT10.42 ± 0.1123.34 ± 2.7566.25 ± 2.71
BT9.67 ± 1.6130.90 ± 2.4659.43 ± 1.00
LT10.57 ± 1.3933.42 ± 2.1656.01 ± 3.52
CPWA9.53 ± 2.2432.03 ± 0.6058.43 ± 2.31
20–30CPA11.43 ± 3.7525.57 ± 3.3763.00 ± 2.45
RT12.26 ± 1.2831.33 ± 2.0856.41 ± 2.81
BT7.37 ± 0.2331.07 ± 2.0461.57 ± 1.81
LT9.17 ± 3.7832.63 ± 2.7958.20 ± 2.55
CPWA6.05 ± 1.4733.17 ± 2.9560.79 ± 4.06
Table 4. Results of two-way analysis of variance (ANOVA) for the effects of treatment, depth and their interaction (treatment × depth) on bulk density.
Table 4. Results of two-way analysis of variance (ANOVA) for the effects of treatment, depth and their interaction (treatment × depth) on bulk density.
SourceSum-of-SquaresDegrees of FreedomMean SquaresF Ratiop-Value
Treatments0.0640.027.420.000
Depth0.5920.29143.100.000
Depth × Treatment0.0180.000.830.586
Error0.06300.00
Total69.2245
Table 5. Bulk density values (mean ± SD, g cm−3) across different soil depth classes and the examined treatments: CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees). Different letters indicate significant differences among treatments according to Duncan post hoc test (p < 0.05).
Table 5. Bulk density values (mean ± SD, g cm−3) across different soil depth classes and the examined treatments: CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees). Different letters indicate significant differences among treatments according to Duncan post hoc test (p < 0.05).
Depth (cm)Treatment
CPA (g cm−3)LT (g cm−3)BT (g cm−3)RT (g cm−3)CPWA (g cm−3)
0–101.02 ± 0.04 e1.07 ± 0.03 de1.08 ± 0.02 de1.07 ± 0.05 de1.13 ± 0.05 d
10–201.22 ± 0.03 c1.24 ± 0.04 c1.23 ± 0.03 c1.29 ± 0.02 bc1.35 ± 0.03 ab
20–301.35 ± 0.02 ab1.35 ± 0.02 ab1.29 ± 0.04 bc1.35 ± 0.04 ab1.41 ± 0.04 a
Table 6. Results of two-way analysis of variance (ANOVA) for the effects of treatment, depth and their interaction (treatment × depth) on average fine root biomass.
Table 6. Results of two-way analysis of variance (ANOVA) for the effects of treatment, depth and their interaction (treatment × depth) on average fine root biomass.
SourceSum-of-SquaresDegrees of FreedomMean SquaresF Ratiop-Value
Treatment2.1140.5312.580.000
Depth0.6420.327.570.002
Depth × Treatment0.9780.122.890.016
Error1.26300.04
Total6.5745
Table 7. Average fine root mass (g dm−3) across different treatments in the research area CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees). Different letters indicate statistically significant differences among treatments based on Duncan’s post hoc test (p < 0.05).
Table 7. Average fine root mass (g dm−3) across different treatments in the research area CPA (outside the skid trail, with alder trees), LT (left wheel track, with alder trees), BT (between wheel tracks, with alder trees), RT (right wheel track, with alder trees), and CPWA (inside the skid trail, no alder trees). Different letters indicate statistically significant differences among treatments based on Duncan’s post hoc test (p < 0.05).
Depth (cm)Treatment
CPA (g dm−3)LT (g dm−3)BT (g dm−3)RT (g dm−3)CPWA (g dm−3)
0–101.177 ± 0.778 a0.152 ± 0.053 bc0.250 ± 0.026 bc0.148 ± 0.037 bc0.026 ± 0.004 c
10–200.445 ± 0.115 b0.092 ± 0.024 bc0.087 ± 0.058 bc0.091 ± 0.008 bc0.018 ± 0.003 c
20–300.226 ± 0.023 bc0.039 ± 0.009 c0.025 ± 0.004 c0.045 ± 0.008 c0.009 ± 0.002 c
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Rahmani Haftkhani, Z.; Nikooy, M.; Salehi, A.; Tavankar, F.; Tsioras, P.A. Post-Harvest Evaluation of Logging-Induced Compacted Soils and the Role of Caucasian Alder (Alnus subcordata C.A.Mey) Fine-Root Growth in Soil Recovery. Forests 2025, 16, 1044. https://doi.org/10.3390/f16071044

AMA Style

Rahmani Haftkhani Z, Nikooy M, Salehi A, Tavankar F, Tsioras PA. Post-Harvest Evaluation of Logging-Induced Compacted Soils and the Role of Caucasian Alder (Alnus subcordata C.A.Mey) Fine-Root Growth in Soil Recovery. Forests. 2025; 16(7):1044. https://doi.org/10.3390/f16071044

Chicago/Turabian Style

Rahmani Haftkhani, Zahra, Mehrdad Nikooy, Ali Salehi, Farzam Tavankar, and Petros A. Tsioras. 2025. "Post-Harvest Evaluation of Logging-Induced Compacted Soils and the Role of Caucasian Alder (Alnus subcordata C.A.Mey) Fine-Root Growth in Soil Recovery" Forests 16, no. 7: 1044. https://doi.org/10.3390/f16071044

APA Style

Rahmani Haftkhani, Z., Nikooy, M., Salehi, A., Tavankar, F., & Tsioras, P. A. (2025). Post-Harvest Evaluation of Logging-Induced Compacted Soils and the Role of Caucasian Alder (Alnus subcordata C.A.Mey) Fine-Root Growth in Soil Recovery. Forests, 16(7), 1044. https://doi.org/10.3390/f16071044

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