Impact of different parts of skid trails on runoff and soil erosion in the Hyrcanian forest (northern Iran)

Geoderma 263 (2016) 161–167

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Impact of different parts of skid trails on runoff and soil erosion in the Hyrcanian forest (northern Iran) Atta Safari a, Ataollah Kavian a, Aidin Parsakhoo b, Iman Saleh a, Antonio Jordán c,⁎ a Department of Watershed Management Engineering, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University (SANRU), Mazandaran Province, P. O. Box: 737, Sari, Islamic Republic of Iran b Department of Forestry, Faculty of Natural Resources, Gorgan Agricultural Sciences and Natural Resources University, Golestan Province, Gorgan, Islamic Republic of Iran c MED_Soil Research Group, Department of Crystallography, Mineralogy and Agricultural Chemistry, University of Seville, Sevilla, Spain

a r t i c l e

i n f o

Article history: Received 26 July 2014 Received in revised form 2 September 2015 Accepted 16 September 2015 Available online xxxx Keywords: Forest roads Rainfall simulation Runoff rate Soil loss Wheel tracks

a b s t r a c t Mechanical logging and skid trail construction in mountainous areas are associated with soil compaction and erosion risks. In this research, surface runoff and soil loss were studied at plot scale in different parts of skid trails in the Darab Kola mountain forests (northern Iran) using rainfall simulation experiments (20 min at intensity of 54 mm h−1). Rainfall simulations were carried on different parts of skid trails: [i] in the wheel tracks, [ii] in the central part between tracks, and [iii] in adjacent undisturbed forest floor as control. At each plot, 30 soil samples (0–20 cm deep) were collected for physical and chemical characterizations. Although forest floor showed a relatively low response to simulated rainfall, results show that skid trails in the study area have a deep impact in the hydrological and erosional response of slopes at plot scale. Significant differences in runoff rates and soil erosion rates between wheel tracks/central parts of skid trails and undisturbed forest floor have been found. Although sediment concentration in runoff of skid trail parts was, on average, not different from that of forest soils, higher runoff rates in skid trail parts contribute to increase soil erosion risk. Soil texture and decreased bulk density, soil organic matter content and stability of aggregates are the main soil characteristics contributing to enhanced runoff generation and soil erosion risk in skid trails. Skid trails in the Darab Kola mountain forests are a source of sediments and runoff, which can cause in- and offsite impacts. Proper planning of forestry activities in the area should consider using erosion control measures in unpaved forest roads, especially in sensible forest areas and steep road segments. Insloping should help undisturbed forest soil areas to capture most of runoff flow and detached sediments, decreasing the severity of impacts in the study area. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Forest systems constitute valuable economic resources that provide consumer products (construction materials, paper, fuel wood and others) and services (outdoor recreation and environmental services) (Zhang and Pearse, 2011). Forests play a key role in the nutrient cycle, hydrology and ecosystem functioning, and any interference may cause great impacts (Hosseini et al., 2012). Human-induced changes to vegetation cover, soils, and topography may cause important changes on the hydrologic and erosional response of disturbed surfaces (Dunne, 1979; Walling and Fang, 2003) and induce a number of adverse on-site and off-site effects including diminished soil productivity (Eswaran et al., 2001; Lal, 1998), degraded water quality (Lal and Stewart, 1994), and increased sedimentation on both ⁎ Corresponding author at: Dpto. de Cristalografía, Mineralogía y Química Agrícola, Facultad de Química (Universidad de Sevilla), C/Profesor García González, 1, 41012 Sevilla, Spain. E-mail address: [email protected] (A. Jordán).

http://dx.doi.org/10.1016/j.geoderma.2015.09.010 0016-7061/© 2015 Elsevier B.V. All rights reserved.

man-made and natural water bodies (Syvitski et al., 2005; Walling and Fang, 2003). Skid trails are temporary vehicle pathways usually used for timber transportation to access roads or a concentration area. Forest roads and skid trails play an important role in rural development, providing wood transportation networks and recreational activities (Parsakhoo et al., 2009), but they can also have negative impacts on ecosystems (Dong et al., 2012). The construction and use of roads can lead to soil losses from the road bed and nearby slopes as well as sediment accumulation in forest basins (Aruga et al., 2005; Jones et al., 2000). A better understanding of road-sediment production rates is required to guide future development and erosion control efforts (Jordán-López et al., 2009). The recent development of forest road networks and the construction of skid trails bring out the role of roads as runoff and sediment sources, which has not been sufficiently considered in many areas. The assessment of soil erosion is particularly important in forested areas, because natural erosion rates tend to be very low (RamosScharrón and MacDonald, 2005), but small changes may cause great impacts. It is well known that forest roads may cause many local

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impacts on soil properties, increasing soil erosion and mass movements after heavy storms or prolonged rainy periods (Gresswell et al., 1979; Gucinski et al., 2001; Jordán-López et al., 2009; LaMarche and Lettenmaier, 2001; Larsen and Parks, 1997; Sidle et al., 1985; Wemple et al., 1996; Ziegler and Giambelluca, 1997) or as a consequence of the raindrop impacts and surface runoff (Froehlich, 1995; Ziegler et al., 2000a). In addition, overland flow from forest roads and skid trails may contribute to transport eroded sediments (Montgomery, 1994; Wemple, 1994) so that increased sedimentation and peak flows are often reported in watersheds with dense road networks. Skid trails and forest roads may cause considerable local changes to soil properties and to the geomorphologic and hydrologic behaviour of hill slopes, increasing soil erosion and mass movements after extreme rainstorms (Bochet et al., 2005; Demir et al., 2007; James and McNeil, 2006; Mahmoudzadeh, 2007; Sui et al., 2008). Road construction removes forest vegetation, disturbs the forest floor, and damages soil structure, which impressively increases soil loss (Parsakhoo et al., 2009). The severity of impacts is related to slope gradient (Dyrness, 1965; Qinsen and Shuren, 1994), vegetation cover (Cerdà, 2007; Lee et al., 2013), mechanical pressure (Battiato et al., 2013), seasonality and rainfall intensity (Martínez-Zavala et al., 2008), soil texture and moisture content at the time of construction (Croke et al., 2001; Gokturk et al., 2006; Pinard et al., 2000; Swift, 1984). Compaction of the roadbed largely explains the variety and intensity of erosion processes (Arnáez et al., 2004). High rates of sediment production are often reported after the construction of forest roads when they are used for frequent transport of logs (Megahan et al., 2001; Reid and Dunne, 1984), or when no conservation measures are carried out (Arnáez et al., 2004). Most efforts to reduce soil erosion and off-site sedimentation have traditionally focused on the improvement of agricultural practises and soil conservation techniques (Englisch et al., 2000; Giordano et al., 2000), but the importance of forest roads as sources of runoff and sediments has not been sufficiently considered (Martínez-Zavala et al., 2008). It is known that unpaved roads may cause important local changes to soil properties, interception of surface and subsurface water flows, generation of surface flow in areas far from established channels, and are a major source of sediments in forested watersheds (Luce and Wemple, 2001; Megahan et al., 1983), but these processes are rarely quantified (Martínez-Zavala et al., 2008). The measurement of soil erosion rates under natural rainfall conditions is costly and time consuming. Rainfall simulation has been used extensively as a cost effective method for soil erosion prediction under a wide range of systems including cultivated soils (Elliot et al., 1989; Loch et al., 1989; Meyer and Harmon, 1984), forest soils (Croke et al., 1999; Martínez-Zavala and Jordán, 2008), unpaved roads (Croke et al., 1999, 2006; Ziegler et al., 2000b; Jordán-López et al., 2009) and mining reclamation areas (Loch, 2000; Sheridan et al., 2000). The advantages of rainfall simulation are the relatively low cost, rapid data collection and the ability to investigate many processes and treatments efficiently (Sheridan et al., 2008). Although the accuracy of this method at different scales is largely untested, especially in the case of unpaved forest roads (Sheridan et al., 2008), simulated rainfall experiments allow the researcher to control rainfall amount, intensity and time, so that they are suitable for the study of hydrological soil processes at detailed scales (Martínez-Murillo et al., 2013; Martínez-Zavala et al., 2008; Meyer, 1994). In the last decades, the road network has considerably increased in the Hyrcanian forests, northern Iran (Parsakhoo et al., 2011). In previous investigations, deep rills on the surface of skid trails in the Darab Kola forest area have been reported, causing canalization of runoff flow and enhancing water erosion on steep slopes (Lotfalian et al., 2013). Reduced traffic safety, slope failure and risk for economic activities are some of the impacts of soil erosion risk associated to forest roads cited by Lotfalian et al. (2013). Forest roads, wheel tracks and transport of logged wood are among the causes of accelerated erosion and sediment

production in the Hyrcanian broad-leaved forests. Because of its sensitivity to impacts, it is necessary to collect new and accurate data about erosion and sediment yield from skid trails in this area for comprehensive management of watersheds (Fu et al., 2010). Few studies have focused on the impact of different parts of skid trails separately. So, the main objective of this paper is to study the impacts of wheel tracks and the middle part of roadbeds (the central area between wheel tracks) on runoff and sediment yield from forest skid trails using simulated rainfall experiments. 2. Materials and methods 2.1. Study area The study area (57 km2) is located in the Darab Kola forest, 15 km east of Sari city, in Mazandaran Province (northern Iran), approximately at 36°31′20″ N/53°17′20″ E and 120–800 m asl. The main soil types are Rendzic Leptosols (according to FAO, 1988), 110–120 cm deep, developed from marl, calcareous sandstone and limestone (Department of Forests and Rangelands, 2003). Most of slopes are facing North/ Northeast and average gradient is 40%. The main woody species in Darab Kola forest are oriental beech (Fagus orientalis), Wych elm (Ulmus glabra), Persian maple (Acer velutinum), European hornbeam (Carpinus betulus), Persian ironwood (Parrotia persica) and black alder (Alnus glutinosa). Herbaceous vegetation in the forest includes sweet bedstraw (Gallium odoratum), spurge (Euphorbia spp.), tutsan (Hypericum androsaemum) and fern (Polystichum spp.). The climate is very wet with mean monthly temperature ranging from 26.1 °C in August to 7.5 °C in February, 16.7 °C on average. Mean annual rainfall is 984 mm, with minimum and maximum monthly values in July (36 mm) and November (120 mm). 2.2. Soil sampling and analysis Skid trails are temporary constructions and the network varies in function of the location of new logging areas. For this research, three groups of 10 soil points (30 plots) were selected randomly for this study in wheel tracks (WT), skid trail central areas (CA) and the forest floor (FF). We have considered skid trail areas as those between the two wheel tracks left by the wheeled skidder (Beaudet et al., 2014). Although varying according to vehicles and charge, on average, width and separation between parallel skid trails were 20–25 cm and 2 m, respectively. At each one of the 30 plots, a 0.5 × 2 m area was established for rainfall simulation experiments. Previously to rainfall simulations, 10 soil samples (0–20 cm deep) were collected by hand at each plot in an area of 1 m2 located 1 m down slope, using a steel cylinder (20 cm inner diameter, 1.5 cm long and 484 cm3 in volume) for physical (soil texture, bulk density and moisture content) and chemical (CaCO3 content, organic matter content, pH and electrical conductivity of soil extracts) analyses. Soil samples were oven-dried at 105 °C for 24 h and weighted. For textural analysis, air-dried soil subsamples were pre-treated with H2O2 (6%) to remove organic matter and sodium acetate/acetic acid (pH 5) to remove carbonates, dried in the oven to obtain the initial weight and dispersed with a sodium hexametaphosphate solution, mechanically shaken overnight. The sand fraction (0.05–2 mm) was removed from the suspension by wet sieving; the clay fraction (b 0.002 mm) was determined by the Bouyoucos hydrometer method (Gee and Bauder, 1986) and the silt fraction (0.002–0.05 mm) was calculated as the difference between 100% and the sum of the sand and clay percentages. Soil CaCO3 content was measured using the NaOH titration method (Rowell, 1994). Soil organic C was determined using the Walkley–Black method (Walkley and Black, 1934). The organic matter content was also calculated multiplying the organic carbon content by 1.724. Soil bulk density was measured by triplicate using the core method (Blake and Hartge, 1986).

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The soil erosionability factor (K) was calculated according to Wischmeier and Smith (1978), using the Eq. (1):
 0:00021 M1:14 ð12−OMÞ þ 3:25ðC soilstr −2Þ þ 2:25 C perm −3 K¼ 100

ð1Þ

ð2Þ

where msilt is silt content, mvfsand is very fine sand content and mc is clay content. The Mean Weight Diameter (MWD) of soil aggregates was used to study aggregate stability. MWD was calculated using a wet sieving method and according to Eq. (3): MWD ¼

n X xi wi

3. Results 3.1. Soil properties

where K is the soil erodibility factor; OM is the organic matter content (%), Cperm is the soil permeability class according to saturated hydraulic conductivity (1, N 60 mm/h; 2, 10–60 mm/h; 3, 5–10 mm/h; 4, 2–5 mm/h; 5, 1–2 mm/h; 6,b1 mm/h), Csoilstr is the soil structure class (1, friable; 2, fine polyhedral; 3 medium to coarse polyhedral; 4, solid) and M is particle size parameter and can be calculated as in Eq. (2):
 M ¼ msilt þ mvfsand  ð100−mc Þ

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ð3Þ

Most of studied soil properties (texture, bulk density, soil moisture, organic matter content, CaCO3 content, pH, and electrical conductivity) did not show significant differences between WT and CA plots (Table 1). In contrast, values from WT and CA plots were significantly different from FF plots (Table 1). Soil texture varied between clay loam in WT and CA plots and sandy loam in FF plots, and no significant differences were found between textural fractions from WT and CA plots. Mean bulk density increased from 1.58 g cm−3 in control plots (FF) to 1.71 and 1.73 g cm−3 (WT and CA, respectively). Soil moisture was significantly higher in FF (46.8%, on average) than in WT (34.8%) or CA plots (35.7%). Organic matter content did not showed significant differences between WT and CA plots (1.88%, on average), but increased more than 3.5 times in FF plots (6.76%). Carbonate content varied slightly between 0.60 (FF) and 3.40% (mean value in WT and CA plots). Soil acidity (pH) and salinity (electrical conductivity) showed significant differences, but did not show qualitative changes. The K factor varied significantly between 0.13 (FF) and 0.23 (WT), although these values may be considered moderate or low for the corresponding textural classes (Wischmeier and Smith, 1978). Finally, mean MWD increased from 0.58 (WT) to 2.60 (FF).

i¼1

Where xi is the mean diameter of remained aggregate on a sieve, wi is the ratio between the dry weights of remained aggregates on each sieve to total dry weight of the sample and n is the number of sieve fractions. 2.3. Rainfall simulation experiments Rainfall simulation dates were selected after a period of several dry days, when soil moisture content was close to the permanent wilting point, around 10% in FF plots and 20% in WR and CA plots (permanent wilting points were estimated using soil texture and organic matter content, according to Saxton and Rawls, 2006). Rainfall simulations were carried out during a 20-days period in June 2013, using a portable single nozzle rainfall simulator. The simulator was supported by telescopic metal legs and a BEX 1:4 S 6.5 spraying system nozzle was used (U.S. Patent No. 4,142,682). The nozzle was placed 3 m from the ground and was connected through a rubber pipe to a mobile pump. The opening angle of the spray cone of this nozzle is generally in the range of 15–100°. At each experiment, simulated rain lasted for 20 min at 54 mm h−1 intensity, dropping from the nozzle onto a rectangular area (0.5 × 2 m2) limited by a steel frame. Although the depth and width of WT and CA varied, these dimensions were calculated so that the experimental area was uniform in all cases, avoiding mixed zones (as WT/CA or WT/FF surfaces). Thirty rainfall simulations were carried out on skid trails in the study area, including WT (10 plots), CA (10 plots) and adjacent FF as control (10 plots). Time to runoff was recorded at each plot. Runoff water and sediment samples were collected using gauges every 5 min and runoff volumes and coefficients were calculated. At each case, sediments were oven-dried at 105 °C for at least 2 h and weighted. 2.4. Statistical analysis The normal distribution of data was checked using the Shapiro-Wilk test. Factorial design was used to analyse quantitative factors of runoff and soil loss. Differences between mean values from different groups of samples were studied ANOVA test. When the ANOVA null hypotheses were rejected, the Duncan test was used to compare the means among groups. All computations were carried out using SPSS v. 18 (SPSS Inc., 2009).

3.2. Rainfall simulation Runoff initiated relatively quickly at WT and CA plots (2.41 min, on average), but delayed until 11.31 min in FF (Table 2). On average, runoff fate from WT plots generally increased quickly during the first 10 min and increased slightly until the end of the 20-min period (Fig. 1). In CA plots, mean runoff rate increased during the first 15 min and then remained steady until the end of the experiment. In contrast, runoff rate from FF plots reached the steady state after some minutes after runoff initiation and stayed below 2%. On average, runoff rates increased significantly from FF (0.49%) to CA and WT plots (7.64 and 9.63%, respectively) (Table 2). Although no significant differences were found among WT, CA and FF plots (values ranging between 9.07 and 11.22 g L−1), sediment yield and soil erosion rates increased largely between FF and WT/CA plots (Table 2). Soil erosion rates behaved in a very similar way to runoff rates, with higher erosion rates in WT and CA plots than in FF plots (Fig. 2). Mean soil erosion rates were 21.83 (FF), 262.44 (CA) and 3101.65 g m−2 h−1 (WT) (Table 2). Sediment concentration in runoff from WT and CA plots increased linearly during the first 5 and 10 min of experiments (respectively) and, then, decreased (Fig. 3). On the other hand, sediment yield from FF plots

Table 1 Mean values (±standard deviation) of soil properties (0–20 cm) in different parts of skid trails and ANOVA p-value. Within-a-row means followed by the same letter in the same row are not significantly different (p ≥ 0.05). WT: wheel tracks; CA: skid trail central areas between wheel tracks; FF: forest floor. Measured variables

WT

CA

FF

ANOVA p-value

Clay (%) Silt (%) Sand (%) Bulk density (g cm−3) Soil moisture content (%) Organic matter content (%) CaCO3 content (%) pH Electrical conductivity (dS m−1) K factor MWD

36.3 ± 1.2 b 31.6 ± 2.4 b 32.1 ± 1.2 a 1.73 ± 0.01 b 34.8 ± 1.1 a 1.86 ± 0.02 a 3.42 ± 0.08 b 6.49 ± 0.12 a 0.18 ± 0.00 a

36.8 ± 0.7 b 31.4 ± 0.6 b 31.9 ± 1.0 a 1.71 ± 0.02 b 35.7 ± 1.5 a 1.90 ± 0.07 a 3.37 ± 0.16 b 6.56 ± 0.06 a 0.18 ± 0.00 a

10.2 ± 0.1 a 25.3 ± 2.0 a 64.5 ± 1.9 b 1.58 ± 0.01 a 46.8 ± 1.8 b 6.72 ± 0.07 b 0.60 ± 0.02 a 6.76 ± 0.03 b 0.31 ± 0.00 b

0.000 0.009 0.000 0.000 0.000 0.000 0.000 0.015 0.000

0.23 ± 0.01 c 0.58 ± 0.15 a

0.19 ± 0.00 b 0.13 ± 0.01 a 0.000 1.61 ± 0.06 b 2.60 ± 0.02 c 0.000

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Table 2 Results (mean values ± standard deviation) of rainfall simulation experiments in different parts of skid trails. Within-a-row means followed by the same letter in the same row are not significantly different (p ≥ 0.05). The post-hoc test was not applied when significant differences among groups were not found (ANOVA p-value ≥ 0.05). WT: wheel tracks; CA: skid trail central areas between wheel tracks; FF: forest floor. Variable

WT

CA

FF

ANOVA p-value

Time to runoff (min) Runoff rate (%) Sediment yield (g) Sediment concentration in runoff (g L−1) Soil erosion rate (g m−2 h−1)

2.28 ± 0.59 b 9.63 ± 5.39 a 25.14 ± 19.75 a 9.07 ± 7.03 301.65 ± 236.97 b

2.53 ± 1.66 b 7.64 ± 5.79 a 21.87 ± 15.41 a 11.22 ± 11.42 262.44 ± 184.95 b

11.31 ± 5.44 a 0.49 ± 0.43 b 3.64 ± 5.52 b 9.71 ± 14.05 21.83 ± 33.13 a

0.000 0.000 0.002 ≥0.05 0.001

increased since runoff initiation and remained stable during the last 5 min of the experiments, with values between 15 and 20 g L−1. Correlation coefficients between rainfall simulation variables are shown in Table 3. Time to runoff was negatively correlated with runoff rate (r = −0.618, p = 0.01), sediment yield (r = − 0.609, p = 0.01) and soil loss rate (r = − 0.617, p = 0.01). Positive correlation coefficients were determined for runoff rate and sediment yield (r = 0.848, p = 0.01), runoff rate and soil loss rate (r = 0.860, p = 0.01) and soil loss rate and sediment yield (r = 0.995, p = 0.01). 3.3. Analysis of variance of simulated rainfall experiments The results of the ANOVA test (Table 2) showed that runoff flow started faster in WT and CA (2.41 min, on average) than in FF plots (11.31 min). Non-significant differences were found between time to runoff from WT and CA plots. Runoff rates were significantly enhanced in WT and CA plots (8.64%, on average) with respect to FF plots (0.49%). Although sediment concentration in runoff did not show significant differences among different types of plots, sediment yield and soil erosion rates were largely enhanced in WT and CA plots with respect to FF plots. On average, sediment yield and soil erosion rate were respectively 6.44 and 12.90 times higher in WT and CA than in FF plots.

yield and soil erosion rates were positively correlated with silt content, bulk density and K factor. Although sediment yield and soil erosion rates showed no significant correlation with CaCO3 content, negative correlations were found with pH (−0828 and −0.851, respectively; p = 0.01). 4. Discussion The hydrological and erosional response of wheel tracks and skid trail central areas between tracks of skid trails in the Darab Kola forest (northern Iran) have been studied in this research. Our results show that skid trails play a major role in forest erosion processes at plot scale. 4.1. Runoff and soil loss from skid trails

Correlation coefficients among soil properties and rainfall simulation experiments are shown in Table 3. Time to runoff initiation is positively correlated with sand content (r = 0.862; p = 0.01) and inversely with silt and clay contents (correlation coefficients −0.868 and −0.837, respectively; p = 0.01). Soil moisture, organic matter content, carbonate content and aggregate stability (MWD) were also positively correlated with time to runoff initiation. Runoff rate was positively correlated with silt and clay contents, bulk density and K factor, and negatively correlated with sand, organic matter content and pH. Finally, sediment

Rainfall simulation experiments have shown significant variations for runoff generation and soil loss in WT and CA of skid trails with respect to FF control plots. Although not always (Jordán-López et al., 2009), higher runoff rates in unpaved surfaces of forest roads have been generally reported by authors (Arnáez et al., 2004; Cao et al., 2013; Jordán and Martínez-Zavala, 2008 and Lotfalian et al., 2013) than in cut slopes, sidecast fill slopes or forest soils. Runoff was considerably accelerated in WT and CA plots. Time to runoff is used as an index of time required for the topsoil pore system to become saturated with water during rainfall (Cerdá, 2001; Martínez-Zavala and Jordán, 2008). According to Jordán and MartínezZavala (2008), accelerated time to runoff in unpaved forest roads occurs because of sealing, aggregate destruction and pore clogging with fine particles. In our study area, soil sealing was observed (but not quantified) in WT and CA, which also showed finer texture and higher compaction. Soil compaction in the roadbed, but especially in WT, is related to width and inflation pressure of tyres, as well to the intensity of traffic, as shown by Botta et al. (2006). In contrast, well aggregated soil and a developed pore system under vegetation cover in FF plots

Fig. 1. Variation of runoff rate from wheel tracks (WT), skid trail central areas between wheel tracks (CA) and forest floor (FF) plots with time during rainfall simulation experiments.

Fig. 2. Variation of sediment concentration in runoff water from wheel tracks (WT), skid trail central areas between wheel tracks (CA) and forest floor (FF) plots with time during rainfall simulation experiments.

3.4. Correlation among soil and rainfall simulation variables

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Fig. 3. Variation of soil erosion rates in runoff water from wheel tracks (WT), skid trail central areas between wheel tracks (CA) and forest floor (FF) plots with time during rainfall simulation experiments.

contribute to delay runoff generation in adjacent areas of roads (Cerdà, 1998; Parsakhoo et al., 2014). Significant differences among runoff production from different parts of skid trails have been found. The increased runoff rate in WT and CA with respect to control FF plots is in agreement with previous results reported by many researchers who have investigated the impact of wheel tracks, traffic of heavy skidding machines and skid trail construction on runoff. Arnáez et al. (2012), for example, reported that tractor wheel tracks contributed to runoff generation more than other areas. Although the roadbed is a major source of runoff flow in unpaved forest roads (Arnáez et al., 2004; Jordán-López et al., 2009), traffic and disturbance by anthropic activities (e.g., timber harvesting; Sowa and Kulak, 2008) may cause irregularities on its surface, channelling water and contributing to accelerated flow (Dobiáš, 2005). Although no differences have been found among sediment concentration in runoff from WT, CA and FF plots, soil erosion rates from WT and CA plots were considerably higher than in FF plots. This is in agreement with results reported by Arnáez et al. (2012) in agricultural soils, where they observed that wheel tracks showed limited sediment concentrations in runoff during rainfall simulations. They explained this as a consequence of low particle detachment in compacted soil surfaces. Under the rainfall intensity used in our experiment (54 mm h−1 during 20 min), similar sediment concentrations in runoff were observed in WT, CA and FF plots. Nevertheless, increased runoff flow in WT and CA plots contributed to trigger sediment yields and soil loss. Table 3 Correlation coefficients between soil properties and variables determined during rainfall simulation. Marked coefficients (a) are significant at the 0.01 level (2-tailed). Non-marked coefficients are significant at the 0.05 level (2-tailed). Non-significant coefficients are not displayed. Variables

Time to runoff

Rainfall Runoff rate simulation Sediment yield Soil loss rate Soil Clay Silt Sand Bulk density Soil moisture Organic matter content CaCO3 content pH Electrical conductivity K factor MWD

−0.618a −0.609a −0.617a −0.837a −0.868a 0.862a −0.889a 0.730 0.847a −0.837a 0.725 0.830a −0.794 0.736

Runoff rate

0.848a 0.860a 0.683 0.834a −0.730 0.725 −0.713 0.676 −0.784 −0.719 0.765

Sediment Soil loss yield rate

0.995a 0.797 0.687

−0.828a 0.694

0.811a −0.679 0.715

−0.851a 0.718

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Triggered soil erosion rates in WT and CA plots are related with heavy traffic on skid trails, in contrast to undisturbed forest floor. In the case of bare roadbeds, tyre depressions are incised immediately by runoff flow during rainfall events on the wet roadbed, accelerating sediment transport (Ziegler et al., 2004) and triggering soil erosion rates. Although concentrated flow running through wheel ruts should favour particle detachment compared to other sections of the roadbed (CA), rainfall simulation experiments have not shown significant differences in runoff production and soil loss between WT and CA plots (although yes FF in respect of plots). Soil properties related with runoff (texture, bulk density, organic matter and CaCO3 contents and electrical conductivity) and soil erosion rates (texture, bulk density and acidity) are not significantly different in WT and CA plots (with K factor varying only between 0.23 ± 0.01, WT, and 0.19 ± 0.00, CA). Despite the possible off-site implications, differences between runoff and erosion rates in WT and AC seem to be controlled by soil properties. This is in agreement with Burroughs et al. (1991), who observed that differences between sediment production from wheel ruts and unrutted road sections are a function of relative soil erodibility, as it occurs in bare soils (Cerdà, 1997, 2002). Erosion control treatments should include gravelling the roadbed, as suggested by Sheridan and Noske (2007), who observed that, under light vehicle traffic, soil erosion rates decrease significantly when the roadbed is gravelled. 4.2. Effect of soil properties on the hydrological and erosive response of skid trails Finer texture, increased bulk density and degradation of soil structure in the 0–20 cm layer of WT and CA plots contributed to increased runoff rates. FF plots, in contrast, showed a sandy loam texture and higher aggregation. Reduced aggregate stability and increased soil erodibility (K factor) have been cited as key factors for soil erosion from forest roads (Parsakhoo et al., 2014). Our research shows that changes in the topsoil may be explained by low organic matter content, soil sealing and mechanical pressure in the roadbed. Soil organic matter and clay content are the main cementing agents in the study area, so that topsoil removing during construction leads to a significant decrease in both properties at the surface (0–20 cm) and, consequently, to a decrease of aggregation and increased soil erodibility, as shown by Jordán-López et al. (2009) and Martínez-Zavala et al. (2008). In other cases, CaCO3 content has been reported as a significant factor for reduction of soil erodibility (Parsakhoo et al., 2014). Our results are consistent with findings by Foltz et al. (2009); Kolka and Smidt (2004); Matangaran and Kobayashi (1999); Sakai et al. (2008) and Sowa and Kulak (2008), who have observed that traffic of skidding machines on forest skid trails compacts the topsoil and contributed to decreased soil infiltration rates, so enhancing ponding and runoff flow generation. 4.3. Consequences for planning and erosion control Forest roads are constructed for rural economic activities and exploitation of forest resources. In steep areas, this often results in dense forest road networks, because they are most often located perpendicularly or obliquely to line of maximum slope. Consequently, the design of forest road systems is optimized for easy transport, traffic flow and accessibility, but other impacts are often ignored (Dabek et al., 2014). The assessment of risks associated to forest roads is necessary for adequate management of forest resources (Lotfalian et al., 2013). Great differences between soil physical characteristics in WT/CA plots and the undisturbed forest soil have led to different hydrological and erosional responses. Skid trails work as a source of sediments and runoff, which can, in turn, cause large in- and off-site impacts. Shi et al. (2008), for example, showed that intensity of soil erosion processes decreased with increasing distance from skid trails, and Jimenez et al. (2013)

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highlighted the role played by roadsides. Undesired effects can be increased depending also on traffic density and the type of vehicles running (Sowa and Kulak, 2008). Intense vehicle flow may completely remove plant cover in CAs of unpaved roads, triggering soil physical degradation processes (Jordán and Martínez-Zavala, 2008). In addition, forest activities such as transport of wood and other forest products may cause intense degradation of forest soils in different ways. Sowa and Kulak (2008) and Naghdi et al. (2009) reported that soil degradation by forest roads is affected by intensity of timber harvesting. Soil compaction, decreased soil infiltration rates and soil erosion strongly depend on harvesting methods and intensity. Consequently, concerned politics, land planning and management programmes must be considered for soil erosion control. 5. Conclusions Although the assessment of soil erosion risks and impacts of forest roads are necessary for suitable management of forest resources, very scarce information is available in forest areas of northern Iran. Our results show that the hydrological behaviour and erosional response of the Darab Kola forest slopes may be intensely impacted by skid trails at plot scale. Generally, results of this research show significant differences in time to runoff, runoff volume, runoff coefficient, sediment yield and soil erosion rates among different parts of the skid trails (WT and CA) and control soils (FF). Although forest floor shows a low erosion risk, unpaved surfaces play a main role as runoff and sediment sources in the study area. Soil compaction, coarsely textured surface layer, low organic matter content and degradation of soil structure in skid trails are some of the causes of enhanced runoff and soil erosion rates in skid trails. WT and CA plots of skid trails showed high runoff rates. Although the sediment concentration in runoff observed in WT and CA plots is not very different from that observed in control forest soil plots (FF) at plot scale, higher runoff rates help to increase soil loss in these areas. Larger scale experiments are necessary for the interpretation of hillslope and catchment processes. Adequate policies and forest planning should consider the implementation of road erosion control measures (cross drains, gravelling or reduced tyre pressure), especially in sensible forest areas and steeper road sections. Insloping should help forest soil areas (with higher infiltration rates) to capture most of runoff flow and detached sediments. Acknowledgments The authors are thankful to Cristine Morgan, editor-in-chief of Geoderma and two anonymous referees, who have contributed significantly to improve the quality of the paper. Appendix A. Supplementary data Supplementary data associated with this article can be found in the online version, at doi: http://dx.doi.org/10.1016/j.geoderma.2015.09. 010. These data include Google maps of the most important areas described in this article. References Arnáez, J., Larrea, V., Ortigosa, L., 2004. Surface runoff and soil erosion on unpaved forest roads from rainfall simulation tests in northeastern Spain. Catena 57, 1–14. Arnáez, J., Ruiz-Flaño, P., Lasanta, T., Ortigosa, L., Llorente, J.A., Pascual, N., Lana-Renault, N., 2012. Efectos de las rodadas de tractores en la escorrentía y erosión de suelos en laderas cultivadas con viñedos. Cuad. Investig. Geogr. 38, 115–130. Aruga, K., Sessions, J., Miyata, E.S., 2005. Forest road design with soil sediment evaluation using a high-resolution DEM. J. For. Res. 10, 471–479. Battiato, A., Diserens, E., Laloui, L., Sartori, L., 2013. A mechanistic approach to topsoil damage due to slip of tractor tyres. J. Agric. Sci. Appl. 2, 160–168.

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