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Article

Soil Compaction and Productivity Evolution in a Harvested and Grazed Mediterranean Scots Pine (Pinus sylvestris L.) Forest

by
María José Aroca-Fernández
1,*,
José Alfredo Bravo-Fernández
1,
Juan Ignacio García-Viñas
1,* and
Rafael Serrada
2
1
ECOGESFOR, Universidad Politécnica de Madrid, C/José Antonio Nováis 10, 28040 Madrid, Spain
2
Independent Researcher, Pza. Pablo Iglesias 1, 19001 Guadalajara, Spain
*
Authors to whom correspondence should be addressed.
Forests 2024, 15(3), 451; https://doi.org/10.3390/f15030451
Submission received: 6 February 2024 / Revised: 22 February 2024 / Accepted: 22 February 2024 / Published: 28 February 2024
(This article belongs to the Section Forest Soil)
Browse Figures
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Abstract

:
The effects of machinery and livestock on forest soil compaction have mostly been studied at short-term and local scales. A better understanding of the long-term effects of compaction in mature stands at the management scale is needed, especially in hot and dry climates. This study aims to analyze (1) soil compaction in a Mediterranean Scots pine (Pinus sylvestris L.) forest subjected to mechanized logging and grazing for more than 50 years and (2) forest productivity trends during these 50 years of disturbance. Soil penetration resistance (0–10 cm and 10–20 cm) and soil moisture (0–12 cm) were measured in 181 randomly selected points affected by “high machinery traffic”, “high cattle traffic” or “low traffic”. Decennial forest inventory data on density, timber volume, and recruitment were collected and analyzed over the five decades preceding soil measurements. Soil penetration resistance exceeded 2500 kPa at a significant portion of the sampled points, although the highest levels of compaction tended to be concentrated in the subsurface layer of the high-traffic areas. Cattle and machinery caused significant compaction in these areas and increased penetration resistance in the range of 350–450 kPa. However, despite the long period of disturbance and the increase in penetration resistance observed, no signs of productivity decline were detected in the forest.

1. Introduction

Soil compaction and its related effects have been widely reported in the literature as major causes of soil degradation that can affect soil productivity and, consequently, vegetation development [1]. Soil compaction reduces porosity (especially the large pore fraction) and leads to a rearrangement and closer packing of soil particles, increasing the cohesive forces between them and reducing the connectivity of the pore network [2]. All of these processes affect four soil physical parameters that ultimately determine vegetation development and root growth [3]: aeration, temperature, water availability, and mechanical resistance to root elongation [4]. Changes in these parameters beyond certain thresholds, which depend on the species [5,6] and climate [7], can lead to limitations in root structure and function such as root elongation, water and nutrient uptake, or respiration. If the limitations are too severe or long-lasting, aerial growth and site productivity may also be negatively affected [1].
Most of the detrimental effects of soil compaction on vegetation were initially studied and characterized in agricultural systems where machinery impacts are high in intensity, frequency, and density [8,9,10]. Since the 1950s, this concern about the detrimental effects of compaction has been extended to forestry [1,11,12,13,14,15]. Abundant research on forest soil compaction over the years has shown that (1) both machinery and livestock are capable of compacting forest soils and (2) the areal extent, intensity, and depth of impacted soil depend on both site (soil texture, structure, organic matter and moisture, topography, weather, and climate) and forest use characteristics (frequency of perturbation, spatial distribution, or load size) [11,15,16,17,18]. However, most of the literature has focused on assessing compaction in areas with heavy traffic, mainly machinery, in scenarios where compaction has a higher risk of negative effects (mainly intensively managed wet and cold forests) [19,20,21,22,23,24,25]. Regarding the effects of compaction on vegetation development, only the effect on seedling rooting has been clearly demonstrated in the literature [26,27,28,29,30]. In contrast, research on aerial part growth, particularly within mature stands, is much more scarce and inconclusive [13,31], especially at long-term and landscape scales [32,33]. In the case of livestock compaction, concerns about the effect on vegetation have mostly focused on the effect on pasture productivity particularly on farm areas with high stocking rates [34,35].
Moving from local effects on soils and seedling roots to stand-scale effects on growth and site quality is not trivial. This requires, among other things, consideration of (i) the overall compacted area as well as its spatial pattern at the forest scale, together with its expected long-term evolution resulting from cumulative effects (balance between impact recurrence and system resilience), and (ii) the resilience of plant communities according to species composition and stand characteristics (age, structure, density, etc.).
The complexity and long timeframes of forest systems result in a wide variety of potential scenarios that are not easy to assess, but, as noted by [33,36], the ultimate effects of compaction on vegetation at the stand scale need to be assessed in order to provide sound management advice to forest owners and managers. Building up a sufficient body of long-term studies in the literature on the effects of soil compaction on forest productivity under a wide range of scenarios, together with accurate descriptions of sites, vegetation, and forest uses, would be a crucial step towards real progress in the analysis of forest soil compaction [12,37]. In this regard, there are very few examples in the literature where scenarios involving both machinery and livestock are analyzed, and they are mostly related to farming [38,39]. Nevertheless, the combination of forest with mechanized harvesting and extensively managed livestock (along with wild ungulates) is quite common in Spain. Thus, more than 55% of the Spanish territory is classified as nonagricultural and nonurban, and almost 70% of this is forest or woodland [40]. Most of this area is managed extensively with rotations of more than 80 years and mechanized harvesting every 10–15 years. Extensive free-grazing cattle, traditionally present in Spanish forests, explain a large part of the landscape characteristics [41]. Therefore, it is particularly important to evaluate the effects of machinery and livestock compaction in extensively managed forests in Spain. Furthermore, it should be considered that warmer and drier Mediterranean climatic conditions can mitigate many of the negative consequences [42] commonly associated with compaction in cold and wet climates [1].
The aim of this research was to analyze soil compaction and forest productivity in one of these cattle-machinery scenarios: a Mediterranean mountain forest that has been extensively managed for more than 100 years, mainly for timber and livestock production. The specific objectives of this study were (i) to provide reference values for the levels of compaction reached in this context; (ii) to determine whether livestock and mechanized harvesting were increasing soil compaction in the forest; and (iii) to assess the evolution of forest productivity in the presence of both compacting agents.
The long period of mechanized full-tree logging with hand-felling, winching, and skidder yarding, combined with extensive cattle grazing in the studied forest, resulted in local soil penetration resistance values that are likely to limit the root growth of Scots pine (Pinus sylvestris L.) growing on sandy loam soils in a Mediterranean climate. However, despite the observed long-period disturbance and increases in penetration resistance, no signs of forest productivity decline were detected, indicating that high local compaction levels do not necessarily imply significant effects on vegetation growth at the forest scale.

2. Materials and Methods

2.1. Study Site

The studied forest is located on the southeastern slopes of the Sistema Central mountain range (40°50′ N, 3°55′ W), about 45 km north of Madrid, Spain. Its elevation ranges from 1260 to 2000 m.a.s.l. Mean annual precipitation is 1115.8 mm, with 95.3 mm in summer. Monthly air temperature averages from 0.3 °C to 16.1 °C (24.1 °C was the mean of the maximum air temperatures in August; −4.6 °C was the mean of the minimum air temperatures in January). Soils are sandy loams [43] mostly derived from gneiss [44].
“Cabeza de Hierro” has an extension of 2016 ha (94% wooded) and is mainly dominated by Scots pine (Pinus sylvestris L.). The forest is unevenly aged and is managed by a group selection system. In the lower areas, the main stratum is interspersed with various-sized clumps of Spanish Oak (Quercus pyrenaica Willd.) coppice with standards, which results in a mixed stand structure. The most common species found in the understory are Cytisus oromediterraneus Rivas Mart. et al. (higher areas), Juniperus communis L., Genista florida L., and Pteridium aquilinum L. (lower areas). Other tree species, such as Sorbus aucuparia L., Ilex aquifolium L., or Betula pubescens Ehrh., are also scattered throughout the forest. “Cabeza de Hierro” is managed cost-effectively to sustain multiple services, including timber production as the main objective and livestock, recreational use, and wildlife and environmental conservation as secondary objectives, among others. Treatments were carried out by mechanized logging for 50 years prior to sampling. Ground-based full-tree logging was performed employing hand-felling, winching, and skidder yarding. Mechanical logging equipment consisted mainly of a rubber-tired Timberjack 240E skidder, the main characteristics of which are shown in Table 1. The mean frequency of harvesting entries to each stand was about once every 15 years. The forest has a permanent network of forest roads as well as primary and secondary skid trails and landings.
Free grazing has been allowed in the forest for local livestock since before 1840. Until the 1960s, livestock included goats, sheep, horses, and cows; however, for the last few decades, it has consisted mostly of cows of Negra Avileña, Charolais, and Limusine breeds, whose main features are summarized in Table 2. About two hundred cows graze continuously in the forest, 8–9 months a year (April to November). Wild ungulates (roe deer, Capreolus capreolus L.) are also abundant in the forest.

2.2. Data Collection

2.2.1. Sampling Areas, Sampling Points, and Measured Variables

A total of 192 points were sampled and distributed across four 100 × 100 m plots encompassing average topographical and stand conditions in the forest (Table 3, Figure 1). Consequently, 48 points were randomly sampled within each plot (approximately 1 point every 15 × 15 m) to collectively provide a representative depiction of the overall state of soil compaction of the area (Section 3.2 of the results details the observed distribution between points affected by high and low machine and livestock traffic). At each point, soil penetration resistance (PR) was measured with a Rimik CP20 recording cone penetrometer (Agridry Rimik PTY Ltd., Towoomba, QLD, Australia) [47] with a diameter of 1.27 cm and a cone angle of 30°. Readings in kilopascals (kPa) were automatically recorded in 1.5 cm increments as the penetrometer was manually inserted to a depth of 20 cm. Soil water content (10–12 cm depth) was assessed by a TDR moisture probe (DeltaT Devices Ltd., Cambridge, UK). Aborted probe insertions caused by big-sized stoniness, parental rock, or big roots in the subsurface were excluded from the input data prior to the analyses (11 points out of 192). Analyses were therefore performed over the remaining 181 points (approx. 45 points per experimental block). The sampling was conducted in the second week of May (in the middle of the growing season). Penetration resistance has been commonly employed for indirectly assessing soil compaction [2,4]. Although this method entails some limitations, the aims of this research and the site conditions enable its use in the current study (see Supplementary Material).

2.2.2. Assessment of the Effect of Compaction Agents

Each sampled point among the 181 randomly selected samples was classified as “high traffic” or “low traffic” according to the logging and grazing history of their respective locations. Only two levels of traffic were considered given that retrospective analyses do not allow a detailed characterization of cattle and machinery traffic intensities [48].
The “high machinery traffic” subset comprised all the sampled points located on skid trails and landings within the experimental blocks. The mean frequency of use of the track network in the studied forest is about once every 2–3 years with a high number of passes per operation. In contrast, the area out of the trails is trafficked only when its respective stand receives silvicultural treatments, which take place, on average, once every 15 years. In particular, according to the harvesting plans of the forest, no mechanized silvicultural treatments had been carried out in any of the selected blocks for the ten years prior to the study, whereas skid trails and landings inside them had been trafficked during logging operations in the surrounding stands within two years of the sampling. Machinery traffic characteristics in the considered categories are summarized in Table 4.
Levels of cattle traffic were set based on grass coverture. The zones with a higher grass cover tend to be much preferred for grazing (and therefore much more trampled) than those mainly covered by shrubs or litter [49,50]. In the studied forest, cattle also tend to concentrate in pasture areas, especially nearby forest roads and/or water and supplementary feeding points [51]. The four experimental blocks were located within the livestock roaming range. Inside them, there were grass surfaces where grazing and trampling were expected to concentrate. Hence, the percentage of grass coverture within 1.5 × 1.5 m plots around sampling points was evaluated and plots showing grass cover ≥ 90% were classified as “high cattle traffic” points. It is worth noting that there were no bare soil areas at the time of sampling due to a high livestock stocking rate. Therefore, bare soil areas were not a problem for the proposed classification rule.

2.2.3. Assessment of Site Productivity Evolution

A forest inventory for management purposes was carried out every decade for 50 years prior to the sampling period. In these inventories, the main dendrometric variables were measured for trees with a diameter at breast height greater than 10 cm. These variables encompassed tree density, diameter at breast height (and consequently basal area), and tree top height. The initial five inventories employed a full-tree method, while the last one used regular grid sampling through 745 multiple-radius plots. This methodological transition was made subsequent to confirming that the accuracy levels remained consistent across both approaches [52]. Diameters were measured with calipers and heights with a Bitterlich relascope or Haglof hypsometer.
Ideally, changes in site productivity should have been assessed on the basis of site-dependent parameters such as site index. However, due to the uneven-aged structure of the forest, data on trees’ ages were not available nor were data on top heights in the first 3 inventories. Therefore, the analysis was based on the long-term evolution of stand density, timber volume, and recruitment. Consequently, the variables analyzed during the study period were the number of stems with a diameter at breast height (DBH) higher than 20 cm per ha, the number of stems with 10 cm < DBH < 20 cm per hectare, standing wood volume per ha, extracted timber volume per ha, and volume growth. Considering that management-dependent stand variables will be employed for site quality evaluation instead of those exclusively linked to site conditions, conclusions will be carefully drawn as observable changes could be produced either by site quality alterations or by forest management itself.

2.3. Data Analysis

The cone penetration resistance measurements taken every 1.5 cm were averaged for each sampling point in two depth ranges: PR0–10cm = mean PR values for 0–10 cm depth and PR10–20cm = mean PR values for 10–20 cm depth. Data analysis on these two variables was performed in three steps: (1) first, the overall observed soil strength values were described to give an overview of the compaction status of the forest after decades of multi-purpose management; the overall correlation between PR and soil moisture was also assessed; (2) then, the influence of machinery and cattle activity on the observed soil strength values, if any, was assessed; and (3) finally, the evolution of forest’s timber stocking during 50 years of exploitation was analyzed to somehow evaluate the stand productivity in relation to the effects of the compaction agents previously described.
Overall PR values for 0–10 cm and 10–20 cm depths were represented by the mean values ± standard deviation. The normality distribution and homogeneity of variance of PR0–10cm, PR10–20cm, and soil moisture were assessed using the Kolmogorov–Smirnov test and the Levene test, respectively. Since the data met the normality requirement, the correlation between PR and soil moisture was examined using Pearson’s correlation coefficient. The 95% confidence intervals for the mean soil moisture (0–12 cm) at the time of PR were also plotted, categorizing the points into three groups: low, medium, and high, with each category corresponding to one-third of the range of PR0–10cm values found in the studied area. The PR values at 0–10 cm were chosen for the analysis to use the same depth to sample moisture. ANOVA and post hoc Tukey tests were employed to assess the significance of mean differences between categories. General linear modeling (two-way analysis of variance) was used to explore the influence of high traffic of machinery and cattle on the soil penetration resistance values. Both disturbances were considered as two fixed factors with two levels: high and low traffic. The main effects and their two-way interaction were analyzed. The entire sample was considered together (no random factor for sampling areas) because the unbalanced design did not allow for robust estimation of the error terms. Frequency distributions of PR for high- and low-traffic areas were presented with histograms and summarized in contingency tables. All analyses were performed with SPSS 15.0 software (SPSS Inc., Chicago, IL, USA).

3. Results

3.1. Overall Values of Soil Penetration Resistance: Relationship with Soil Moisture

Penetration resistance (PR) measurements in the 0–10 and 10–20 cm top layers of the soil (sampling size = 181) averaged (mean ± sd) 927 ± 372 kPa and 1804 ± 482 kPa, respectively. The frequencies of measured PR values exceeding threshold values commonly reported in the literature for the initiation of issues in the root growth of conifers in sandy or sandy loam soils are summarized in Table 5. These thresholds range from 2000 kPa for a reduction in root elongation rate to 2500–3000 kPa for root elongation stop [53,54].
None of the observations within the upper soil layer (0–10 cm) exceeded any of those values. However, contingent upon the selected PR threshold—be it 2000, 2500, or 3000 kPa—between 0% and 37.8% of the sampled points were found to be beyond the specified bounds within the subsurface soil layer (10–20 cm). PR thresholds influencing aboveground growth and survival were not evaluated as they are not clear for either saplings [13] or mature trees [55].
The mean surface (0–12 cm) soil water content during the sampling period (mean ± sd) was 12.2 ± 6.4%. Soil moisture levels at the time of PR sampling showed a significant and positive linear correlation with PR at that depth (Pearson correlation coef. = 0.30, p-value = 0.000). As depicted in Figure 2, the points showing the 1/3 lowest PR values in the surface layer (PR0–10cm ∈ [200–700 kPa]) maintained moisture levels significantly lower than the 2/3 more compacted ones (PR0–10cm ∈ [700–1200 kPa] and PR0–10cm ∈ [1200–1700 kPa]) according to ANOVA and Tukey’s post hoc test (Figure 1).
Furthermore, despite the samples being collected in the middle of the growing season, it was observed that over 60% of the points with PR0–10cm < 700 kPa exhibited soil moisture levels below 10%—the usual reference value for the wilting point in sandy loam soils. This percentage decreased to 30% and 25% for points with 700 kPa< PR0–10cm < 1200 kPa and PR0–10cm > 1200 kPa, respectively.

3.2. Impact of Soil Compacting Agents: Cattle Trampling and Mechanized Harvesting

In the random sampling, 135 points were found to be affected by low traffic, 34 by high cattle traffic, and 19 by high machinery traffic; of the latter two, seven corresponded to points affected by both high machinery and cattle traffic. The average soil penetration resistance values (mean ± sd), categorized by the type of disturbance were as follows: (1) for the upper layer (0–10 cm): 830 ± 341 kPa, 1261 ± 297 kPa, and 1176 ± 324 kPa for low traffic, high cattle traffic, and high machinery traffic, respectively; and (2) for the subsurface layer (10–20 cm): 1694 ± 453 kPa, 2142 ± 420 kPa, and 2171 ± 369 kPa for low traffic, high cattle traffic, and high machinery traffic, respectively. The two-way analysis of variance revealed a significant influence of the main effects of both fixed factors (machinery traffic [high/low] and cattle traffic [high/low]) on PR values (p-value < 0.001). The effect of interaction (cattle x machinery: PR0–10cm = 1388 ± 245 kPa and PR10–20cm = 2270 ± 285 kPa, and 1176) was not significant, so it was not considered in further analyses.
The measured values indicate that areas with high traffic from cattle and machinery exhibited PR increments with respect to low-traffic areas comparable in magnitude. These increments were approximately 400 kPa and 450 kPa for the surface and subsurface layer, respectively, translating to relative increases of around 45% and 30% concerning the average PR levels in low-traffic conditions. Confidence intervals for mean PR values across depths and perturbations are shown in Figure 3.
With regard to threshold values (Table 6), it has to be stressed that, although the mean values did not exceed 3000 kPa, the percentages of points with PR10–20cm above 2000 or 2500 kPa were significantly lower in low-traffic areas than in high-traffic areas (χsquare p-value < 0.001). Thus, low-traffic areas showed 28% of points where the PR was higher than 2000 kPa compared to 65% in high-traffic areas, and they rarely exceeded 2500 kPa (3% of sampled points compared to 23% in high-traffic areas).
Histograms of PR relative frequencies are plotted in Figure 4 for three subsets according to perturbations: (i) high machinery traffic; (ii) high cattle traffic; and (iii) low traffic. The histograms for cattle and machinery high-traffic subsets were very similar for both 0–10 and 10–20 cm soil depth. Both, however, differ significantly from the histograms of the low-traffic areas.

3.3. Changes in Site Productivity?

The stocking information provided by the six decadal management inventories carried out in the 50 years prior to the compaction sampling is summarized in Table 7. No machinery was employed for logging before that moment, whereas grazing has been taking place in the forest since ancient times (see Section 2.2.2).
As can be observed in Table 7, standing total volume remained fairly constant through the set period even though harvested timber volume slightly raised over that time. Big stem density (ØBreastHeigth ≥ 20 cm) remained almost steady apart from a slight decrease between years 10 and 20 due to the logging of the oldest stems during that period. Small stem density (10 cm ≤ Ø ≤ 20 cm) fluctuated much more than big stem density, and it increased noticeably, roughly doubling throughout the period analyzed. All these stand variables showed stability even though over 85% of the initial timber stock was extracted during the analyzed period.

4. Discussion

4.1. Penetration Resistance Overall Values in the Forest: Potentially Harmful?

Determining whether the observed PR levels should be considered harmful or not is not a trivial matter. Both PR critical limits and their expected effects show high variability in the literature. Thus, we can find threshold values from 800 to 5000 kPa with related harmful effects that range from slowing down root elongation to stopping vegetation growth completely [15,56].
The evaluation of the PR levels found in the forest with respect to the most common reference values (Table 5) would indicate that a significant part of the study area might show certain restrictions to root growth, although these limitations would not be strong enough to halt it completely. However, it should be noted that PR measurements were made only once during the growing season, so conclusions on these values can only be reliably related to the timing and conditions of measurement. There is much more uncertainty about the net effect of soil compaction over the whole growing season. In this sense, considering the higher soil moisture found in the more compacted areas, it could be expected that moderate levels of soil compaction may allow a longer growing season in these areas due to the effect on water availability. Moreover, we observed lower compaction in the top soil level (0–10 cm) where most of the root biomass is located (Figure 2).
This trend was already observed by Gómez et al., 2012 [57] who encountered that, for sandy and sandy loam soils in a Mediterranean climate, soil compaction extended the period of plant-available water for 86 and 48 days in the 1 to 15 and 15 to 30 cm soil depth, respectively. Thus, improvements in soil water balance could be buffering the soil-strength constraints for plant development: root systems would grow slower within compacted areas but they may do so for a longer period because of their higher water content. In this regard, Brais (2001) [58] found that growth in the early establishment period was positively affected by increased microporosity values on coarse-textured soils.
In summary, the obtained PR levels were not alarming but moderately high within the subsurface soil layer (10–20 cm) for more than 1/3 of the sampled points. Despite this, there is notable uncertainty about the PR net effect on roots throughout the whole year because of the observed compaction offsetting effects (soil strength vs. moisture availability).

4.2. Cattle and Machinery Effects

Both mean values and differences between PR levels of high- and low-traffic areas are within the range of values reported in the literature for sandy and sandy loam soils [59,60,61]. Nevertheless, it is more common to find higher values when soils have been affected by machinery and lower ones when affected by cattle [62].
Frequency distributions of PR values within the high and low machinery and cattle traffic areas (Table 6, Figure 2) showed that the impact of compacting agents on topsoil was mainly concentrated in the high-traffic areas. The addition of occasional impacts within the low-traffic areas has not been high enough to equalize both populations, despite the long period of exposure to both uses. In this regard, several authors support that compaction agents’ traffic should be concentrated on permanent trails and grazing areas to reduce the overall and long-term detrimental effects at the forest level [59,63,64,65,66,67]. They argue that soil recovery rates are slow and mostly ineffective in counteracting the impact of compaction agents; hence, spreading traffic equally over the entire surface only increases the permanently compacted surface rather than decreasing the overall intensity of impact. On the contrary, other authors consider that it is certainly better not to concentrate the impacts on specific areas but to spread the damage as far as possible so that soils can recover between successive uses [21,68].
In the study area, machinery moves mostly along permanent skid trails, although a smaller proportion of traffic is also unevenly distributed over the rest of the area. With regard to livestock, despite free grazing, cattle trampling tends to be concentrated around grazing areas and both water and feeding points (Bravo et al., 2010 [51]), while decreasing with distance from these areas. This distribution of traffic appears to have succeeded in clustering damage on tracks and grazing areas. This could be either because the accumulation of impact in low-traffic areas has not yet been sufficient to reach the compaction levels of high-traffic areas or because recovery processes are effective in these areas.
In any case, the period of impact accumulation (>50 years) is expected to have lasted long enough to allow some equilibrium between soil conditions and disturbance regime, at least in highly trafficked areas [62,69]. It is therefore essential to assess whether the site quality of the forest has been negatively affected by the evolution of compaction levels to date. This assessment will determine whether a change in the current management system is needed or whether long-term monitoring of soil status would be sufficient. Periodic monitoring of soil compaction trends may be particularly important in low-impact areas, where the equilibrium between soil and disturbances is unlikely to have been reached.

4.3. Forest Productivity

Forest uses (including livestock and mechanized logging) have not prevented the forest from maintaining sustained yield, standing volume, and an adequate recruitment of saplings. In addition, the forest currently has a balanced age-class distribution and good health and is performing its ecological and protective functions well [70]. So far, no signs of decline have been detected either in the productivity of the forest’s main species or in its overall condition and functionality. Nevertheless, based on the available information, we cannot categorically rule out a decline in site quality as a result of mechanized logging and cattle practices, since stocks and density evolution are affected by both site quality changes, climate, and management.
There is no consensus in the literature on the effects of compaction on productivity [13,37]: most reviews warn of the risk posed by the long compaction recovery periods (particularly of subsurface soil) [71] and the subsequent impact accumulation that inevitably leads to yield reductions [1]. However, all kinds of results can be found in specific experiments [32,72,73,74]. In this context, Curran et al. (2005) [55] point out that results from existing long- and short-term studies have shown a full range of possible productivity outcomes, and the net effect depends on which growth-limiting factors were affected by the disturbance.
The apparent absence of site quality decline in the study area is consistent with the above facts: (1) the encountered compaction levels are not extremely high considering the feasible range; and (2) the sandy loam soil texture of the study area, together with the Mediterranean climate type, are expected to buffer the potential impact of compaction levels on root growth and plant development [7,57]. In addition, this study was focused on a mature forest composed mainly of trees with already-developed root systems. These conditions are expected to differ greatly from those of saplings, which have typically been evaluated when assessing the effects of soil compaction on vegetation growth [6,12,75,76,77,78]. Saplings still have developing root systems and therefore show much greater dependence on their continued expansion than adults [79]. Adult trees within a mature forest such as “Cabeza de Hierro” tend to have well-developed root systems over a broad soil volume, which increases their resilience. Moreover, the main impact of soil compaction on adult trees does not concern the expansion of their root systems but the renewal rate of fine roots or the availability of water in the surrounding soil. Busse et al. (2017) [80] found no differences in rooting patterns or in fine or lateral root numbers between compacted and noncompacted areas in conifer forests 20 years after compacting treatments, suggesting a long-term tolerance of conifer roots to soil compaction.
Finally, it should be noted that the highest levels of compaction were largely concentrated in high-traffic areas, meaning that their spatial distribution could be contributing to the low impact on forest productivity. For instance, high machinery traffic areas are essentially linear, so are expected to be less harmful (given that lateral growth around them is not impeded) to the arrangement of root systems than the same area concentrated in a continuous surface.

5. Conclusions

Fifty years of mechanized full-tree logging with hand-felling, winching, and skidder yarding, combined with over a century of extensive cattle grazing, may result in soil penetration resistance levels that are likely to limit root growth of Scots pine (Pinus sylvestris L.) growing on sandy loam soils in a Mediterranean climate. However, high local compaction levels do not necessarily imply productivity losses at the forest scale. Under these site conditions, appropriate forest planning along with diligently performed forest uses can reconcile long exploitation periods with forest sustainability.
The results obtained further underline that the impact of forest uses cannot be thoroughly assessed on the basis of the level and depth of induced soil compaction: it is paramount to also consider the overall percentage of the compacted area and its spatial distribution at the forest scale. Climatic conditions are also relevant, as soil water conditions may improve with compaction, especially in sandy soils in arid climates such as the Mediterranean.
With regard to the studied forest, given its compaction status, it would be advisable to concentrate machinery and cattle traffic on landings, tracks, and pastures and to carry out long-term monitoring of the evolution of compaction extent in less trafficked areas.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f15030451/s1, Section S1: Soil penetration resistance as compaction index: terms and conditions of use. References [2,4,7,81,82,83,84,85,86,87,88,89,90,91] are cited in the Supplementary Materials.

Author Contributions

Conceptualization, M.J.A.-F., J.A.B.-F. and R.S.; methodology, M.J.A.-F.; software, M.J.A.-F.; formal analysis, M.J.A.-F.; investigation, M.J.A.-F., J.A.B.-F. and R.S.; resources, J.A.B.-F., J.I.G.-V. and R.S.; data curation, M.J.A.-F., original draft preparation, M.J.A.-F.; writing—review and editing, M.J.A.-F., J.A.B.-F. and R.S.; supervision, J.A.B.-F., J.I.G.-V. and R.S.; project administration, J.I.G.-V. and R.S.; funding acquisition, J.I.G.-V. and R.S. All authors have read and agreed to the published version of the manuscript.

Funding

Universidad Politécnica de Madrid (Programa Propio).

Data Availability Statement

Data will be available with free access at a public repository once the manuscript is accepted with a permanent DOI.

Acknowledgments

We would like to thank J.A. Fernández-Yuste for his invaluable support and assistance in the development of this work and J. Fernández and M. Venturas for their help in the final drafting of the paper.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Kozlowski, T.T. Soil Compaction and Growth of Woody Plants. Scand. J. For. Res. 1999, 14, 596–619. [Google Scholar] [CrossRef]
  2. Lipiec, J.; Hatano, R. Quantification of Compaction Effects on Soil Physical Properties and Crop Growth. Geoderma 2003, 116, 107–136. [Google Scholar] [CrossRef]
  3. Letey, J. Relationship between Soil Physical Properties and Crop Production. In Advances in Soil Science SE—8; Stewart, B.A., Ed.; Advances in Soil Science; Springer: New York, NY, USA, 1985; Volume 1, pp. 277–294. ISBN 978-1-4612-9539-6. [Google Scholar]
  4. Miller, R.E.; Colbert, S.R.; Morris, L.A. Effects of Heavy Equipment on Physical Properties of Soils and on Long-Term Productivity: A Review of Literature and Current Research; Nactional Council for Air and Stream Improvement: Cary, NC, USA, 2004. [Google Scholar]
  5. Materechera, S.A.; Dexter, A.R.; Alston, A.M. Penetration of Very Strong Soils by Seedling Roots of Different Plant Species. Plant Soil 1991, 135, 31–41. [Google Scholar] [CrossRef]
  6. Alameda, D.; Villar, R. Moderate Soil Compaction: Implications on Growth and Architecture in Seedlings of 17 Woody Plant Species. Soil Tillage Res. 2009, 103, 325–331. [Google Scholar] [CrossRef]
  7. Gomez, A.; Powers, R.F.; Singer, M.J.; Horwath, W.R. Soil Compaction Effects on Growth of Young Ponderosa Pine Following Litter Removal in California’s Sierra Nevada. Soil Sci. Soc. Am. J. 2002, 66, 1334–1343. [Google Scholar] [CrossRef]
  8. Moon, J.W. Some Field Observations of the Agronomic Significance of Compact Subsoils. Soil Sci. Soc. Am. Proc. 1938, 3, 237–241. [Google Scholar] [CrossRef]
  9. Huberty, M.R. Compaction in Cultivated Soils. Am. Geophys. Union Trans. 1945, 25, 896–899. [Google Scholar]
  10. Veihmeyer, F.J.; Hendrickson, A.H. Soil Density and Root Penetration. Soil Sci. 1945, 65, 487–495. [Google Scholar] [CrossRef]
  11. Cambi, M.; Certini, G.; Neri, F.; Marchi, E. The Impact of Heavy Traffic on Forest Soils: A Review. For. Ecol. Manag. 2015, 338, 124–138. [Google Scholar] [CrossRef]
  12. Mariotti, B.; Hoshika, Y.; Cambi, M.; Marra, E.; Feng, Z.; Paoletti, E.; Marchi, E. Vehicle-Induced Compaction of Forest Soil Affects Plant Morphological and Physiological Attributes: A Meta-Analysis. For. Ecol. Manag. 2020, 462, 118004. [Google Scholar] [CrossRef]
  13. Ampoorter, E.; De Frenne, P.; Hermy, M.; Verheyen, K. Effects of Soil Compaction on Growth and Survival of Tree Saplings: A Meta-Analysis. Basic Appl. Ecol. 2011, 12, 394–402. [Google Scholar] [CrossRef]
  14. 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]
  15. Greacen, E.L.; Sands, R. Compaction of Forest Soils. A Review. Soil Res. 1980, 18, 163–189. [Google Scholar] [CrossRef]
  16. Jones, A. Effects of Cattle Grazing on North American Arid Ecosystems: A Quantitative Review. West. N. Am. Nat. 2000, 60, 155–164. [Google Scholar]
  17. Nazari, M.; Eteghadipour, M.; Zarebanadkouki, M.; Ghorbani, M.; Dippold, M.A.; Bilyera, N.; Zamanian, K. Impacts of Logging-Associated Compaction on Forest Soils: A Meta-Analysis. Front. For. Glob. Chang. 2021, 4, 780074. [Google Scholar] [CrossRef]
  18. Nazari, M.; Arthur, E.; Lamandé, M.; Keller, T.; Bilyera, N.; Bickel, S. A Meta-Analysis of Soil Susceptibility to Machinery-Induced Compaction in Forest Ecosystems across Global Climatic Zones. Curr. For. Rep. 2023, 9, 370–381. [Google Scholar] [CrossRef]
  19. Jakobsen, B.F.; Greacen, E.L. Compaction of Sandy Forest Soils by Forwarder Operations. Soil Tillage Res. 1985, 5, 55–70. [Google Scholar] [CrossRef]
  20. Miller, R.E.; Scott, W.; Hazard, J.W. Soil Compaction and Conifer Growth after Tractor Yarding at Three Coastal Washington Locations. Can. J. For. Res. 1996, 26, 225–236. [Google Scholar] [CrossRef]
  21. Brais, S.; Camiré, C. Soil Compaction Induced by Careful Logging in the Claybelt Region of Northwestern Quebec (Canada). Can. J. Soil Sci. 1998, 78, 197–206. [Google Scholar] [CrossRef]
  22. Claverie, J.; Balbuena, R.; Terminiello, A.; Casado, J.; Manghi, E.; Jorajuría, D. Compactación Inducida Por El Tráfico de Máquinas En Suelo Forestal. Rev. Bras. Eng. Agríc. Ambient. 2000, 4, 286–289. [Google Scholar] [CrossRef]
  23. Goutal, N.; Keller, T.; Défossez, P.; Ranger, J. Soil Compaction due to Heavy Forest Traffic: Measurements and Simulations Using an Analytical Soil Compaction Model. Ann. For. Sci. 2013, 70, 545–556. [Google Scholar] [CrossRef]
  24. Blouin, V.M.; Schmidt, M.G.; Bulmer, C.E.; Krzic, M. Mechanical Disturbance Impacts on Soil Properties and Lodgepole Pine Growth in British Columbia’s Central Interior. Can. J. Soil Sci. 2005, 85, 681–691. [Google Scholar] [CrossRef]
  25. 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]
  26. Bengough, A.G.; Bransby, M.F.; Hans, J.; Mckenna, S.J.; Roberts, T.J.; Valentine, T.A. Root Responses to Soil Physical Conditions: Growth Dynamics from Field to Cell. J. Exp. Bot. 2006, 57, 437–447. [Google Scholar] [CrossRef] [PubMed]
  27. Chapman, N.; Miller, A.J.; Lindsey, K.; Whalley, W.R. Roots, Water, and Nutrient Acquisition: Let’s Get Physical. Trends Plant Sci. 2012, 17, 701–710. [Google Scholar] [CrossRef] [PubMed]
  28. Naghdi, R.; Solgi, A.; Labelle, E.R.; Zenner, E.K. Influence of Ground-Based Skidding on Physical and Chemical Properties of Forest Soils and Their Effects on Maple Seedling Growth. Eur. J. For. Res. 2016, 135, 949–962. [Google Scholar] [CrossRef]
  29. Cambi, M.; Mariotti, B.; Fabiano, F.; Maltoni, A.; Tani, A.; Foderi, C.; Laschi, A.; Marchi, E. Early Response of Quercus Robur Seedlings to Soil Compaction Following Germination. Land Degrad. Dev. 2018, 29, 916–925. [Google Scholar] [CrossRef]
  30. Jourgholami, M.; Khoramizadeh, A.; Zenner, E.K. Effects of Soil Compaction on Seedling Morphology, Growth, and Architecture of Chestnut-Leaved Oak (Quercus castaneifolia). iForest 2017, 10, 145–153. [Google Scholar] [CrossRef]
  31. Bulmer, C.; Venner, K.; Prescott, C. Forest Soil Rehabilitation with Tillage and Wood Waste Enhances Seedling Establishment but Not Height after 8 Years. Can. J. For. Res. 2007, 37, 1894–1906. [Google Scholar] [CrossRef]
  32. Grigal, D.F. Effects of Extensive Forest Management on Soil Productivity. For. Ecol. Manag. 2000, 138, 167–185. [Google Scholar] [CrossRef]
  33. Kirby, M. Whither Soil Compaction Research? Soil Tillage Res. 2007, 93, 472–475. [Google Scholar] [CrossRef]
  34. Drewry, J.J.; Cameron, K.C.; Buchan, G.D. Pasture Yield and Soil Physical Property Responses to Soil Compaction from Treading and Grazing—A Review. Soil Res. 2008, 46, 237–256. [Google Scholar] [CrossRef]
  35. Drewry, J.J.; Paton, R.J.; Monaghan, R.M. Soil Compaction and Recovery Cycle on a Southland Dairy Farm: Implications for Soil Monitoring. Soil Res. 2004, 42, 851–856. [Google Scholar] [CrossRef]
  36. Worrell, R.; Hampson, A. The Influence of Some Forest Operations on the Sustainable Management of Forest Soils—A Review. Forestry 1997, 70, 61–85. [Google Scholar] [CrossRef]
  37. Tarpey, R.A.; Jurgensen, M.F.; Palik, B.J.; Kolka, R.K. The Long-Term Effects of Silvicultural Thinning and Partial Cutting on Soil Compaction in Red Pine (Pinus resinosa Ait.) and Northern Hardwood Stands in the Northern Great Lakes Region of the United States. Can. J. Soil Sci. 2008, 88, 849–857. [Google Scholar] [CrossRef]
  38. Botta, G.F.; Antille, D.L.; Bienvenido, F.; Rivero, D.; Avila-Pedraza, E.A.; Contessotto, E.E.; Ghelfi, D.G.; Nistal, A.I.; Pelizzari, F.M.; Rocha-Meneses, L. Effect of Cattle Trampling and Farm Machinery Traffic on Soil Compaction of an Entic Haplustoll in a Semiarid Region of Argentina. Agron. Res. 2020, 18, 1163–1176. [Google Scholar] [CrossRef]
  39. Chyba, J.; Kroulík, M.; Krištof, K.; Misiewicz, P.A.; Chaney, K. Influence of Soil Compaction by Farm Machinery and Livestock on Water Infiltration Rate on Grassland. Agron. Res. 2014, 12, 59–64. [Google Scholar]
  40. Montero, G.; Serrada, R. La Situación de los Bosques y el Sector Forestal en España—ISFE 2013; Sociedad Española de Ciencias Forestales: Pontevedra, Spain, 2013. [Google Scholar]
  41. AGRESTA; INCA. Criteria and Indicators for Sustainable Forest Management, in Spanish Forests 2012; Medio, A.I., Ed.; Ministerio de Agricultura, Alimentación y Medio Ambiente: Madrid, Spain, 2012.
  42. Powers, R.F.; Andrew Scott, D.; Sanchez, F.G.; Voldseth, R.A.; Page-Dumroese, D.; Elioff, J.D.; Stone, D.M. The North American Long-Term Soil Productivity Experiment: Findings from the First Decade of Research. For. Ecol. Manag. 2005, 220, 31–50. [Google Scholar] [CrossRef]
  43. Roig Gómez, S. Caracterización Edáfica de los Principales Pastizales Naturales del Valle del Paular (Madrid). Ph.D. Thesis, Universidad Polictecnica de Madrid, Madrid, Spain, 1999. [Google Scholar]
  44. Ministerio de Agricultura Pesca y Alimentación (MAPA). Mapa 1:200.000 de Cultivos y Aprovechamientos de la Provincia de Madrid y Memoria; Ministerio de Agricultura Pesca y Alimentación: Madrid, Spain, 1985.
  45. Deschênes, C. Pression Exerceé sur le Sol par la Machinerie Forestiere: Repertoire; Ministere de l’Energie et des Ressources, Canada: Quebec, Canada, 1989.
  46. Greenwood, K.L.; McKenzie, B.M. Grazing Effects on Soil Physical Properties and the Consequences for Pastures: A Review. Aust. J. Exp. Agric. 2001, 41, 1231–1250. [Google Scholar] [CrossRef]
  47. Rimik Agricultural Electronics. CP20 Cone Penetrometer Hardware Instructions Manual; Agridry Rimick PTY LT: Toowoomba, Australia, 1995; Volume 31. [Google Scholar]
  48. Ezzati, S.; Najafi, A.; Rab, M.; Zenner, E. Recovery of Soil Bulk Density, Porosity and Rutting from Ground Skidding over a 20-Year Period after Timber Harvesting in Iran. Silva Fenn. 2012, 46, 521–538. [Google Scholar] [CrossRef]
  49. Sigua, G.C.; Coleman, S.W. Long-Term Effect of Cow Congregation Zone on Soil Penetrometer Resistance: Implications for Soils and Forage Quality. Agron. Sustain. Dev. 2009, 29, 517–523. [Google Scholar] [CrossRef]
  50. Tate, K.W.; Dudley, D.M.; Mcdougald, N.K.; Melvin, R.G. Effect of Canopy and Grazing on Soil Bulk Density. Rangel. Ecol. Manag. 2004, 57, 411–417. [Google Scholar] [CrossRef]
  51. Bravo, J.A.; Rubio, A.; Aroca-Fernández, M.J.; Serrada, R.; Roig, S. Diagnosis Y Distribución Espacial Del Sobrepastoreo Mediante Sig. Caso Del Monte ‘Cabeza de Hierro’ (Rascafría, Madrid). In Proceedings of the IV Reunión Ibérica de Pastos y Forrajes, Zamora, Spain and Miranda do Douro, Portugal, 3–6 May 2010; pp. 537–542. [Google Scholar]
  52. Martínez-Osorio, M. Comparación de un Conteo Pie a Pie Frente a un Inventario por Muestreo, en el Monte ‘Cabeza de Hierro’ (Rascafría, Madrid). Estudio de la Relación ‘Variabilidad—Tamaño de Parcela’, Mediante Modelización; ETSI Montes Forestal y Medio Natural: Madrid, Spain, 2004. [Google Scholar]
  53. Bulmer, C.E. Forest Soil Rehabilitation in British Columbia: A Problem Analysis; Research Branch B.C. Ministry of Forest: Victoria, BC, Canda, 1998. [Google Scholar]
  54. Sinnett, D.; Morgan, G.; Williams, M.; Hutchings, T.R. Soil Penetration Resistance and Tree Root Development. Soil Use Manag. 2008, 24, 273–280. [Google Scholar] [CrossRef]
  55. Curran, M.P.; Heninger, R.L.; Maynard, D.G.; Powers, R.F. Harvesting Effects on Soils, Tree Growth, and Long-Term Productivity. In Productivity of Western Forests: A Forest Products Focus; Harrington, C.A., Schoenholtz, H.S., Eds.; DIANE Publishing: Darby, PA, USA, 2005; pp. 3–15. [Google Scholar]
  56. Gebauer, R.; Martinková, M. Effects of Pressure on the Root Systems of Norway Spruce Plants (Picea abies [L.] Karst.). J. For. Sci. 2012, 51, 268–275. [Google Scholar] [CrossRef]
  57. Gomez, G.A.; Singer, M.J.; Powers, R.F.; Horwath, W.R. Soil Compaction Effects on Water Status of Ponderosa Pine Assessed through 13C/12C Composition. Tree Physiol. 2002, 22, 459–467. [Google Scholar] [CrossRef] [PubMed]
  58. Brais, S. Persistence of Soil Compaction and Effects on Seedling Growth in Northwestern Quebec. Soil Sci. Soc. Am. J. 2001, 65, 1263–1271. [Google Scholar] [CrossRef]
  59. 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]
  60. Bulmer, C.; Krzic, M. Soil Properties and Lodgepole Pine Growth on Rehabilitated Landings in Northeastern British Columbia. Can. J. Soil Sci. 2003, 83, 465–474. [Google Scholar] [CrossRef]
  61. Mulholland, B.; Fullen, M.A. Cattle Trampling and Soil Compaction on Loamy Sands. Soil Use Manag. 1991, 7, 189–193. [Google Scholar] [CrossRef]
  62. Aroca-Fernández, M.J.; Bravo-Fernández, J.A.; García-Viñas, J.I.; Fernández-Yuste, J.A.; Serrada, R. Forest Soils Compaction: Better Hoofs or Rubber-Tired? Cuad. Soc. Esp. Cienc. 2019, 45, 37–58. [Google Scholar]
  63. Horn, R.; Vossbrink, J.; Becker, S. Modern Forestry Vehicles and Their Impacts on Soil Physical Properties. Soil Tillage Res. 2004, 79, 207–219. [Google Scholar] [CrossRef]
  64. Horn, R.; Vossbrink, J.; Peth, S.; Becker, S. Impact of Modern Forest Vehicles on Soil Physical Properties. For. Ecol. Manag. 2007, 248, 56–63. [Google Scholar] [CrossRef]
  65. Ampoorter, E.; Van Nevel, L.; De Vos, B.; Hermy, M.; Verheyen, K. Assessing the Effects of Initial Soil Characteristics, Machine Mass and Traffic Intensity on Forest Soil Compaction. For. Ecol. Manage. 2010, 260, 1664–1676. [Google Scholar] [CrossRef]
  66. Page-Dumroese, D.S.; Jurgensen, M.; Terry, T. Maintaining Soil Productivity during Forest or Biomass-to-Energy Thinning Harvests in the Western United States. West. J. Appl. For. 2010, 25, 5–11. [Google Scholar] [CrossRef]
  67. von Wilpert, K.; Shäffer, J. Ecological Effects of Soil Compaction and Initial Recovery Dynamics: A Preliminary Study. Eur. J. For. Res. 2006, 125, 129–138. [Google Scholar] [CrossRef]
  68. Serrano, J.; Marques, J.; Shahidian, S.; Carreira, E.; Marques da Silva, J.; Paixão, L.; Paniagua, L.L.; Moral, F.; Ferraz de Oliveira, I.; Sales-Baptista, E. Sensing and Mapping the Effects of Cow Trampling on the Soil Compaction of the Montado Mediterranean Ecosystem. Sensors 2023, 23, 888. [Google Scholar] [CrossRef] [PubMed]
  69. Lei, S.A. Soil Compaction from Human Trampling, Biking, and off-Road Motor Vehicle Activity in a Blackbrush (Coleogyne ramosissima) Shrubland. West. N. Am. Nat. 2004, 64, 125–130. [Google Scholar]
  70. Bravo-Fernández, J.A.; Serrada, R. Tercera Revisión del Proyecto de Ordenación del Monte ‘Cabeza de Hierro’ (Rascafría, Madrid); SECF: Ávila, Spain, 2007. [Google Scholar]
  71. 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]
  72. Alameda, D.; Villar, R.; Iriondo, J.M. Spatial Pattern of Soil Compaction: Trees’ Footprint on Soil Physical Properties. For. Ecol. Manag. 2012, 283, 128–137. [Google Scholar] [CrossRef]
  73. Blanco, J. a Forests May Need Centuries to Recover Their Original Productivity after Continuous Intensive Management: An Example from Douglas-Fir Stands. Sci. Total Environ. 2012, 437, 91–103. [Google Scholar] [CrossRef] [PubMed]
  74. Fox, T.R. Sustained Productivity in Intensively Managed Forest Plantations. For. Ecol. Manag. 2000, 138, 187–202. [Google Scholar] [CrossRef]
  75. Misra, R.K.; Gibbons, A.K. Growth and Morphology of Eucalypt Seedling-Roots, in Relation to Soil Strength Arising from Compaction. Plant Soil 1996, 182, 1–11. [Google Scholar] [CrossRef]
  76. Bulmer, C.E.; Simpson, D.G. Soil Compaction and Water Content as Factors Affecting the Growth of Lodgepole Pine Seedlings on Sandy Clay Loam Soil. Can. J. Soil Sci. 2005, 85, 667–679. [Google Scholar] [CrossRef]
  77. 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]
  78. Labelle, E.R.; Kammermeier, M. Above- and Belowground Growth Response of Picea abies Seedlings Exposed to Varying Levels of Soil Relative Bulk Density. Eur. J. For. Res. 2019, 138, 705–722. [Google Scholar] [CrossRef]
  79. Puhe, J. Growth and Development of the Root System of Norway Spruce (Picea abies) in Forest Stands—A Review. For. Ecol. Manag. 2003, 175, 253–273. [Google Scholar] [CrossRef]
  80. Busse, M.D.; Fiddler, G.O.; Shestak, C.J. Conifer Root Proliferation after 20 Years of Soil Compaction. For. Sci. 2017, 63, 147–150. [Google Scholar] [CrossRef]
  81. Bengough, A.; Mullins, C. Mechanical impedance to root growth: A review of experimental techniques and root growth responses. J. Soil Sci. 1990, 41, 341–358. [Google Scholar] [CrossRef]
  82. Bengough, A.G.; McKenzie, B.M. Sloughing of root cap cells decreases the frictional resistance to maize (Zea mays L.) root growth. J. Exp. Bot. 1997, 48, 885–893. [Google Scholar] [CrossRef]
  83. Dec, D.; Dörner, J.; Balocchi, O. Temporal and spatial variability of structure dependent properties of a volcanic ash soil under pasture in southern Chile. Chil. J. Agric. Res. 2011, 71, 293–303. [Google Scholar] [CrossRef]
  84. Manoel, C.; Vaz, P.; Hopmans, J.W. Simultaneous measurement of soil penetration resistance and water content with a combined penetrometer—TDR moisture probe. Soil Sci. Soc. Am. J. 2001, 65, 4–12. [Google Scholar]
  85. Mckenzie, B.M.; Mullins, C.E.; Tisdall, J.M.; Bengough, A.G. Root–soil friction: Quantification provides evidence for measurable benefits for manipulation of root-tip traits. Plant. Cell Environ. 2013, 36, 1085–1092. [Google Scholar] [CrossRef] [PubMed]
  86. Miller, R.E.; Hazard, J.; Howes, S. Precision, Accuracy, and Efficiency of Four Tools for Measuring Soil Bulk Density or Strength; U.S. Department of Agriculture Forest Service: Portland, OR, USA, 2001.
  87. Schmalz, H.J.; Taylor, R.V.; Johnson, T.N.; Kennedy, P.L.; Sandra, J.; Newingham, B.A.; Mcdaniel, P.A. Soil morphologic properties and cattle stocking rate affect dynamic soil properties. Rangel. Ecol. Manag. 2013, 66, 445–453. [Google Scholar] [CrossRef]
  88. Smith, C.W. The effect of soil compaction and soil physical properties on the mechanical resistance of South African forestry soils. Geoderma 1997, 78, 93–111. [Google Scholar] [CrossRef]
  89. Steber, A.; Brooks, K.; Perry, C.H.; Kolka, R. Surface compaction estimates and soil sensitivity in Aspen stands of the Great Lakes States. N. J. Appl. For. 2007, 24, 276–281. [Google Scholar] [CrossRef]
  90. Whiteley, G.M.; Utomo, W.H.; Dexter, A.R. A comparison of penetrometer pressures and the pressures exerted by roots. Plant Soil 1981, 61, 351–364. [Google Scholar] [CrossRef]
  91. Zou, C.; Penfold, C.; Sands, R.; Misra, R.; Hudson, I. Effects of soil air-filled porosity, soil matric potential and soil strength on primary root growth of radiata pine seedlings. Plant Soil 2001, 236, 105–115. [Google Scholar] [CrossRef]
Forests 15 00451 g001
Figure 1. Location of the “Cabeza de Hierro” forest in Spain (top left corner of the figure) and locations of sampling areas (blue dots) within the forest perimeter (red line) (coordinate system: ETRS89 UTM 30N; contour lines every 20 m).
Figure 1. Location of the “Cabeza de Hierro” forest in Spain (top left corner of the figure) and locations of sampling areas (blue dots) within the forest perimeter (red line) (coordinate system: ETRS89 UTM 30N; contour lines every 20 m).
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Forests 15 00451 g002
Figure 2. Confidence intervals for the mean soil moisture at PR sampling time. The values are categorized into three groups: low, medium, and high, with each category corresponding to one-third of the range of PR0–10cm values encountered in the studied area. Tukey homogeneous subsets are indicated by a letter above the interval bar.
Figure 2. Confidence intervals for the mean soil moisture at PR sampling time. The values are categorized into three groups: low, medium, and high, with each category corresponding to one-third of the range of PR0–10cm values encountered in the studied area. Tukey homogeneous subsets are indicated by a letter above the interval bar.
Forests 15 00451 g002
Forests 15 00451 g003
Figure 3. Confidence intervals for the mean PR values as influenced by machinery traffic and cattle trampling. (A) Average values for 0–10 cm soil depth; (B) average values for 10–20 cm soil depth. Sample size in each level is indicated above the interval.
Figure 3. Confidence intervals for the mean PR values as influenced by machinery traffic and cattle trampling. (A) Average values for 0–10 cm soil depth; (B) average values for 10–20 cm soil depth. Sample size in each level is indicated above the interval.
Forests 15 00451 g003
Forests 15 00451 g004
Figure 4. Histograms of relative frequencies for PR values for Forests 15 00451 i001 low traffic points, Forests 15 00451 i002 high machinery traffic points, and Forests 15 00451 i003 high cattle traffic points, within (A) surface layer (0–10 cm) and (B) subsurface layer (10–20 cm).
Figure 4. Histograms of relative frequencies for PR values for Forests 15 00451 i001 low traffic points, Forests 15 00451 i002 high machinery traffic points, and Forests 15 00451 i003 high cattle traffic points, within (A) surface layer (0–10 cm) and (B) subsurface layer (10–20 cm).
Forests 15 00451 g004
Table 1. Technical specifications of the machinery operated in the study area [45].
Table 1. Technical specifications of the machinery operated in the study area [45].
Brand/ModelWeight (kg) (Unladed)TiresGround Pressure (kPa)
UnladedLaded
TimberJack Cable Skidder 240A744123.1–2647 (Front)
30 (Rear)		59 (Rear)
Table 2. Features of grazing livestock in the study area.
Table 2. Features of grazing livestock in the study area.
BreedAdult Female Weight (kg) *Mean Hook Area (cm2) **Ground Pressure (kPa)
Negra Avileña500–600388.2141.7
Limousin650–850474.5158.1
Charolés700–950504.9162.8
* Source: Federación Española de Asociaciones de Ganado Selecto (FEAGAS) http://feagas.com/ (accessed on 10 January 2023). ** The mean area of the hooks was estimated based on weight-hook area data provided by Greenwood and McKenzie (2001) [46].
Table 3. Topographical conditions and stand mean characteristics within the experimental blocks.
Table 3. Topographical conditions and stand mean characteristics within the experimental blocks.
Sampling Areas
ABCD
Slope (%)15.618.68.89.9
Elevation (m)1526.71517.41441.41338.6
Aspect (°)174.8142.2268.376.4
N (trees/ha)Psyl10–20cm15.091.362.0120.2
Psyl>20cm173.6169.0156.5257.2
Qpyr202.8498.547.960.8
G (m2/ha)Psyl10–20cm0.31.51.22.3
Psyl>20cm38.826.321.526.5
Qpyr3.911.42.21.5
Dg (cm)Psyl10–20cm14.914.315.215.2
Psyl>20cm53.344.541.836.2
Qpyr15.617.124.517.7
Mean height (m)Psyl20.015.613.916.4
Qpyr10.210.711.910.2
Aspect: aspect measured in clockwise degrees from north. N: tree density; G: basal area at breast height per hectare (m2/ha); Dg: mean diameter at breast height (cm); Psyl10–20cm: Scots pine (Pinus sylvestris L.) trees with 10 cm < Dg < 20 cm; Psyl>20cm: Scots pine trees with Dg > 20 cm; Qpyr: all Spanish oak trees with Dg > 10 cm.
Table 4. Machinery traffic features for highly and non-highly trafficked areas within the experimental blocks.
Table 4. Machinery traffic features for highly and non-highly trafficked areas within the experimental blocks.
Level of Machinery Traffic
HighLow
Frequency of operations2–3 years15 years
Intensity of passes per operationHighSporadic
Last use1–2 years before sampling>10 years before sampling
Table 5. Percentage of observations within 0–10 and 10–20 cm soil layers exceeding threshold values commonly reported in the literature for the initiation of issues in the root growth of conifers in sandy or sandy loam soils values.
Table 5. Percentage of observations within 0–10 and 10–20 cm soil layers exceeding threshold values commonly reported in the literature for the initiation of issues in the root growth of conifers in sandy or sandy loam soils values.
Soil DepthPenetration Resistance (kPa) 1
>2000>2500>3000
0–10 cm0%0%0%
10–20 cm37.8%7.2%0%
1 Considered PR thresholds [53,54]: 2000 kPa: reduction in root elongation; 2500 to 3000 kPa: root elongation stop.
Table 6. Relative frequency (%) of sampling points with penetration resistance above the given limits (2000, 2500, and 3000 kPa) within the subsurface layer (10–20 cm) depending on disturbance source.
Table 6. Relative frequency (%) of sampling points with penetration resistance above the given limits (2000, 2500, and 3000 kPa) within the subsurface layer (10–20 cm) depending on disturbance source.
SourceNPR10–20cm (kPa)
>2000>2500>3000
High cattle traffic3468%24%0%
High machinery traffic1963%21%0%
Low traffic13428%3%0%
All18038%7%0%
N: sampling size; PR10–20 cm: average soil penetration resistance (kPa) for 10–20 cm depth.
Table 7. Stand density and wood production evolution since the start of mechanized logging in “Cabeza de Hierro” forest.
Table 7. Stand density and wood production evolution since the start of mechanized logging in “Cabeza de Hierro” forest.
Years of Mechanized LoggingDensity [stems·ha−1] *1Volume [m3·ha−1] *2
Small Stems
[10 cm ≤ Ø ≥ 20 cm]		Big Stems
[Ø ≥ 20 cm]		TotalVharvVtotGrowth
090.7230.0320.617.7158.7
10131.2237.4368.622.1158.7
2087.6214.9302.536.5158.637.4
30163.0211.8374.831.0150.436.6
40218.7215.5434.330.3165.037.4
50178.8209.4388.2 156.737.7
*1 Ø: breast height diameter. *2 Vharv: wood volume per ha (m3/ha) harvested from the forest during the indicated period; Vtot: total wood volume per ha (m3/ha) existing in the forest during the period indicated; Growth: m3 of wood per ha that the forest has grown in the indicated period.
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Aroca-Fernández, M.J.; Bravo-Fernández, J.A.; García-Viñas, J.I.; Serrada, R. Soil Compaction and Productivity Evolution in a Harvested and Grazed Mediterranean Scots Pine (Pinus sylvestris L.) Forest. Forests 2024, 15, 451. https://doi.org/10.3390/f15030451

AMA Style

Aroca-Fernández MJ, Bravo-Fernández JA, García-Viñas JI, Serrada R. Soil Compaction and Productivity Evolution in a Harvested and Grazed Mediterranean Scots Pine (Pinus sylvestris L.) Forest. Forests. 2024; 15(3):451. https://doi.org/10.3390/f15030451

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Aroca-Fernández, María José, José Alfredo Bravo-Fernández, Juan Ignacio García-Viñas, and Rafael Serrada. 2024. "Soil Compaction and Productivity Evolution in a Harvested and Grazed Mediterranean Scots Pine (Pinus sylvestris L.) Forest" Forests 15, no. 3: 451. https://doi.org/10.3390/f15030451

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