Impact of silvicultural treatment and forest operation on soil and regeneration in Mediterranean Turkey oak (Quercus cerris L.) coppice with standards

Ecological Engineering 95 (2016) 475–484

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Impact of silvicultural treatment and forest operation on soil and regeneration in Mediterranean Turkey oak (Quercus cerris L.) coppice with standards Enrico Marchi a , Rodolfo Picchio b,∗ , Piotr S. Mederski c , Dinko Vusic´ d , Mattia Perugini b , Rachele Venanzi b a

Università degli Studi di Firenze, Department of Agricultural, Food and Forestry Systems, Florence, Italy Department of Agriculture and Forestry Sciences (DAFNE), Tuscia University, Via S. Camillo de Lellis, 01100 Viterbo, Italy c Pozna´ n University of Life Sciences, Department of Forest Utilisation, Pozna´ n, Poland d University of Zagreb, Faculty of Forestry, Zagreb, Croatia b

a r t i c l e

i n f o

Article history: Received 12 April 2016 Received in revised form 10 June 2016 Accepted 20 June 2016 Available online 9 July 2016 Keywords: Logging operation Tree diversity Soil impact Biological soil quality Turkey oak

a b s t r a c t Coppicing is a very traditional method of forest management and is still widespread in many regions worldwide. Until the middle of the 20th century, coppice forests were very common in most parts of Europe and several issues related to coppicing are still considered relevant and important. In Italy the coppice management has still a good economic and social relevance for hilly and mountainous areas. In addition, forest harvesting has a significant impact on regeneration, fauna and soil. The aim of this study was to investigate the impact of the silvicultural treatment and forest operations on species diversity of tree natural regeneration and soil characteristics in a Turkey oak coppice in central Italy. The forest surface strongly impacted by forest operations was on average 3.4 ± 0.9% of the total area for the two treatments. The findings 6 and 16 months after coppicing on areas A and B, respectively. showed that tree species composition of regeneration was not affected by either the forest operation or the silvicultural treatment. The average regeneration composition analyzed was ca 10% of shoots and 90% of seedlings. On the contrary, physical, chemical and biological soil features were strongly impacted by harvesting operation and slightly by the silvicultural treatment. BD was higher in the disturbed areas than in the undisturbed ones in both the A and B treatments (average increase of 0.232 g/cm3 , equal to ca 28%). PR increased an average of 0.1690 MP (147%) when comparing the disturbed and undisturbed areas of the A and B treatments. SR showed a significant increase in disturbed areas of A (+6.23 t/m2 ; 245%) and B (+2.91 t/m2 ; 114%) in comparison with the control. OM content was significantly higher in the control area (ca 6%) than in the other treatments. pH did not seem to have been influenced by silvicultural treatment or logging operations. The results confirm that Turkey oak coppice soils are characterized by a high biodiversity of edaphic fauna, which is typical of stable ecosystems (QBS-ar > 200). The diversity of tree species regeneration was good and similar to those of well-structured forests (Evenness 0.77). © 2016 Elsevier B.V. All rights reserved.

1. Introduction The process of coppicing is regarded as being almost infinitely repeatable, and it has also been suggested as a valuable management practice for nature conservation and the improvement of environmental conditions for wildlife (Espelta et al., 1995; Franklin and Forman, 1987; Johnson and Krinard, 1983). Coppicing is a traditional method of forest management and is still widespread in

∗ Corresponding author. E-mail address: [email protected] (R. Picchio). http://dx.doi.org/10.1016/j.ecoleng.2016.06.084 0925-8574/© 2016 Elsevier B.V. All rights reserved.

many regions worldwide. Until the middle of the 20th century, coppice forests were very common in most parts of Europe and several issues related to coppicing are considered relevant and important (Kneifl et al., 2015; Szabò, 2010). The importance of coppice management is highlighted by the EU projects developed on this topic in the last decade (e.g. European networking project ‘CForSEE (Coppice for SE Europe) – the multi-functional management of coppice forests’ (2007–2013); COST Action FP 1301 – Innovative management and multifunctional utilization of traditional coppice forests – an answer to future ecological, economic and social challenges in the European forestry sector – Eurocoppice).

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Coppice, in particular of the oak species, has for centuries supplied timber for firewood and charcoal production (Picchio et al., 2011b). It has also represented an important source of litter collection and pasture (Gimmi et al., 2008; Glatzel, 1999). This management system can produce woody biomass (high quality fuel wood) rapidly (generally at most one cutting cycle every 25 years, but in average every 12–18 years for the common coppice forests). The biomass derived from Turkey oak (Quercus cerris L.) coppice, is, therefore, a renewable source of energy. After 1950, the management of coppice was affected by a progressive abandonment as a consequence of environmental policies and socio-economic changes (Biˇcík et al., 2001; Bürgi, 1999; Lo Monaco et al., 2014; Lo Monaco et al., 2011). In Italy, the traditional form of management for those forests is coppice with standards, management that consists in a felling of about 80–85% in mass of the total woody biomass, with release of standard (about 70–120 standard/ha). Oak coppice forests are widespread especially in the countries bordering the Mediterranean. The current distribution of this Quercus genus is linked to human activity which has always favored oak forests, to the detriment of other tree species (Timbal and Aussenac, 1996). In Italy, Turkey oak forests extend for over 1,000,000 ha, representing 11.5% of the national woodland, 9.7% of the national forest area and 3.4% of the national land surface (IFNC, 2007). In central Italy, in particular, the surface area of mainly Turkey oak forests is approximately 710,000 ha, 75.5% of which are coppice with standards (IFNC, 2007). Coppice harvesting is a vital operation in forest management, which has important effects on the understory, fauna and, last but not least, soil (Frey et al., 2011; Picchio et al., 2012a, 2012b). Soil characteristics and function may be affected by coppicing due to the modified input of light, heat and water, as also found for a different treatment in another study (Olajuyigbe et al., 2012). Another soil degradation source connected with coppicing is machine trafficking, which may cause soil compaction, soil horizon mixing and topsoil removal (Korb et al., 2007). Compaction reduces soil porosity and the connectivity of pores, thus increasing soil density and shear strength (Klvac et al., 2010; Picchio et al., 2012b; Williamson and Neilsen, 2000). This soil degradation could reduce tree growth (Grigal, 2000), while carbon dioxide efflux from the soil may change significantly (Olajuyigbe et al., 2012). Logging systems may differ depending on silvicultural management and the final products. The technical and economic utilization of coppice forests is dependent on various factors concerning terrain conditions, transportation networks and harvesting technologies, as well as silvicultural treatment and forest operation systems (Cavalli and Grigolato, 2010; Vusic´ et al., 2013). Although in recent times significant innovations have occurred in forest operations (Picchio et al., 2012a, 2011b), both in terms of technology and methodology, the majority of private and public coppice forests in Italy are still harvested using traditional methods, i.e., motormanual felling with chainsaws and using mules and/or agricultural tractors for extraction (Picchio et al., 2011a, 2011b; Laschi et al., 2016). Unfortunately, studies focusing on the effects of utilization on the physical properties of forest soil are rare, and companies are seldom required to take into account the impact of their operations on the land and on forest sustainability, or rather, to consider the real application of sustainable forest management as suggested by Forest Europe. For these reasons, one of the most important problems of the forest sector is to minimize the ground damage caused by forest operations (Edlund et al., 2013). Some studies suggest minimizing the area of soil disturbance and soil compaction by designing a thinner network of strip roads (Mederski, 2006). In general, the effects of harvesting include changes in vegetation, nutrient availability, soil microclimate and structure, as well as litter quantity and qual-

ity (Borchert et al., 2015; Edlund et al., 2013). In particular, forest operations, such as forwarding and skidding, have a high potential for soil compaction (Jamshidi et al., 2008; Cambi et al., 2015, 2016). However, adequately managed forest ecosystems are claimed to be highly resilient in the long-term (Sánchez-Moreno et al., 2006). The impact caused by the silvicultural treatment itself, and the impact caused by both silvicultural treatment and forest operations are still under investigation and need further research. In order to improve silvicultural management and logging methods, a better knowledge of the long-term impact of forest operations is needed (Maesano et al., 2013; Picchio et al., 2011b). A reduction in the negative effects of felling and extraction is one of the main goals of sustainable forest management (Sist and NguyenThé, 2002; Sist et al., 2003; Tavankar, 2015). The present study was designed to analyze the impact of the silvicultural treatment and logging on forest soils, in addition to the usual physical and chemical analysis (pH, organic matter, bulk density, penetrometric and shear resistance) (Cambi et al., 2015), and an innovative arthropod-based Biological Soil Quality index, QBS-ar (Parisi et al., 2005; Venanzi et al., 2016). This index was suggested as a valuable tool in ecosystem restoration programs for monitoring the development of soil functions and biodiversity, and to prevent the negative effects of soil compaction due to logging activities (Blasi et al., 2013). In the coppice management system the period of time between harvests is usually known as the “cutting cycle” (Espelta et al., 1995; Retana et al., 1992). During this time, restocking of the stand is left to two main natural regeneration processes, through seedlings (gamic) and sprouts (agamic). Due to the high sprouting potential of these oaks after coppicing, the dynamics of recruiting new individuals into existing populations has largely been overlooked. Perhaps the present conditions of genetic density and management tend to prevent population renewal. Some authors (Espelta et al., 1995; Retana et al., 1992) have found that in some coppices, the dynamics of the seedling bank reinforce the role of gap formation through small- or large-scale perturbations in population turnover. Biodiversity conservation has long been a goal of European conservation policy (CBD, 2010; CEC, 1998). However, despite the fact that more than 25% of European land is afforded some level of protection for conservation, biodiversity continues to decline (Sebek et al., 2015). One factor contributing to this decline may be unsuitable management practices in protected areas, or more specifically, the insufficient application of evidence-based conservation recommendations (Sebek et al., 2015; Sutherland et al., 2004). For example a lack of diversity of management systems with the total abandonment of the traditional systems, without simply consider the possibilities of their improvement. An old forest traditional management system was coppice, which maintained a cyclical pattern of extreme changes in ground-level light penetration (Buckley, 1992; Joys et al., 2004). Traditionally these managed woodlands were thus open, sunny, heterogeneous mosaics of forest in various stages of succession, which harboured a high richness of animals and vascular plants (Hédl et al., 2010; Benes et al., 2006; Bengtsson et al., 2000; Bugalho et al., 2011; Spitzer et al., 2008; Vodka and Cizek, 2013; Warren and Thomas, 1992). Biodiversity monitoring is essential in order to support management decisions in maintaining multiple forest ecosystem functions (CBD, 2001). A better understanding of the roles of the components of biological diversity to support the provision of multiple forest ecosystem services is necessary (Corona et al., 2011; Mattioli et al., 2015). For these reasons, in this study, in particular with the purpose of the monitoring the tree biodiversity in a simplified forest management system, the quantity and quality characteristics of regeneration were also investigated. The objective of this study was to investigate the impact of silvicultural treatment and forest operations on regeneration and

E. Marchi et al. / Ecological Engineering 95 (2016) 475–484

soil conditions in a Turkey oak coppice located in central Italy. In particular, the aims were: (i) to investigate the impact of silvicultural treatment on regeneration and soil condition; (ii) to find out how both, silvicultural treatment and forest operations influence regeneration and soil characteristics; (iii) to determine the usefulness of the biodiversity index, referring to tree renovation and soil microarthropods (QBS-ar). 2. Material and methods 2.1. Study sites The study was conducted in a Turkey oak coppice with standards in Castel Giorgio, a village close to the regional border between Umbria and Lazio (42◦ 68 36.16 N, 11◦ 97 40.55 E), in Central Italy. From a morphological point of view the surrounding area has the typical hilly landscape of the Vulsina region. The forest stand harvested was ca 20 ha, located at an elevation of 600 m a.s.l., on a slope with an average gradient of 25% (ranging between 5% and 40%). The ground surface was rambling, with ca 7% of the surface showing obstacles to machine traffic, such as rock outcrops and hollows. The climate is mediterranean, characterized by hot summers, mild rainy autumns and early springs. The mean annual precipitation is approximately 840 mm and the mean annual temperature is 15.1 ◦ C. The highest daily temperatures are recorded in July and August (30 ◦ C, average maximum) and the lowest in January (0 ◦ C, average minimum). The area had three rural forest roads, artificially surfaced, dividing the forest into three parcels. The road slope was low (2%) and the average width of the roadway was 4.20 m. The accessibility of the forest can be defined as good, even if the forest road network in the area did not include permanent tracks. A landing area was made along the wider part of the main road. The soil is volcanic in origin, with considerable depth, and belongs to the typological units “Typic Haplustepts fine, mixed, mesic” (USDA classification). Smooth or stony types of materials have conditioned their alterability and therefore the thickness and type of soil. Moreover, the soil of the area is characterized by a remarkable permeability, which favours percolation and the internal circulation of waters. The soil area is non-hydromorph brown soil, with an acidic sub-acidic reaction. 2.2. Treatment and logging methods Three forest areas of coppice with standards were included in the investigation: 1) Area A (ca 10 ha), where harvesting was carried out mainly in the winter of 2014–15. 2) Area B (ca 10 ha), where harvesting was carried out mainly in the winter of 2013–2014. 3) Area C (ca 15 ha) – the control plot, unharvested and not impacted for more than 16 years. In both area A and B, the coppice was clear-cut at the average growth age of 19 years, releasing 95 standards per hectare. The harvesting operation was completed in both areas A and B within approximately 200 days. Pre-harvest stand data (Table 1) were obtained using standard forest measurement techniques on ten circular plots randomly selected of a 20 m radius, each therefore covering an area of 1256 m2 . For the area A and B, loggings were performed by six operators using the Tree Length System (TLS). All the trees were cut motormanually with a Stihl MS 362 chainsaw. Bunching and extraction

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was carried out by winching uphill using a farm tractor equipped with a forest winch, with a pulling force of 60 kN and equipped with 100 m of cable. The 4 wheeled tractor was a SAME 85 kW, weighing 4800 kg. The tires had a medium degree of use, and their sizes were: front tire 380/60 R30; rear tire 420/70 R30. This tractor travelled on the forest soil and a winching operation was conducted a few times from the forest road. This was mainly due to the complete absence of tracks. All the wood extracted was commercialized as firewood. The post harvesting measurements were carried out in the summer of 2015, approximately 6 and 16 months after coppicing on areas A and B, respectively. 2.3. Analytical methods In order to determine the soil particle size distribution for the areas studied, three soil samples in each area (A–C) were taken randomly from the top 30 cm of mineral soil, which is considered crucial indicators of vulnerability to soil compaction (Cambi et al., 2015; Marchi et al., 2014). For particle size distribution, rock fragments (particles with >2 mm diameter) were removed from the air-dried samples by sieving. Afterwards, three sand fractions: 2.00–0.50 mm (coarse), 0.50–0.25 mm (medium), and 0.25–0.05 mm (fine), were separated by wet sieving. Finally, silt and clay were determined using a hydrometer (Cambi et al., 2016; Picchio et al., 2012b). Four linear transects were tracked to estimate the surface area impacted (only on areas A and B) and the tree community composition (on all areas: A–C). A systematic sampling method was applied, in each area, starting from, the southern border, moved with a linear direction in a northerly direction every 50 m a transect straining point was identified. From every starting point a transect was tracked in easterly direction. Each transect, established using a compass and a tape measure, was rectangular in shape (1 m × 50 m). In order to determine the area impacted by the dragged logs and the moving tractor, soil surface portions were differentiated as those affected and unaffected (or disturbed and undisturbed by visual assessment of soil disturbance method). These post-operation analyses were conducted using research methods based on internationally shared protocols, elaborated and adapted to this context of study as proposed in Picchio et al. (2012a, 2011a, 2012b, 2009, 2011b). The different typology of renovation between seeds and sprouts was analyzed, and only individuals less than 1.5 m high and with visible cotyledon scars were considered as seedlings, as suggested by Retana et al. (1992) and Espelta et al. (1995). The tree renovation community composition was analyzed through the Species Importance Value (SIV) index, calculated for each species as reported in the literature (Pourbabaei et al., 2013; Tavankar et al., 2013): SIV = Relative density (RDe) + Relative frequency (RF) + Relative dominance (RDo).

RDe = (Number of individuals of a species × 100)/total number of individuals of all species.

RF = (Number of plots containing a species × 100)/sum of frequencies of all species.

The seedling height was considered for dominancy (this is the only difference of application respect to the cited references, because in this case this parameter is the only that can give a valid indication of the possibility of life and the ability to compete of the seedlings) and the relative dominance (RDo) calculated by: RDo = (sum of the height of a species × 100)/sum of total height of all species.

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Table 1 main dendrometric characteristics of the coppice before cutting (areas A and B) and at the time of the study (area C) (ANOVA test, df 2, 40, p < 0.05; average ± SD; from the Tukey test applied, different letters show statistically significant differences among treatments). Area

A B C

Age [year]

a,b

18 20b 16a

DBH [m]

Height [m]

0.16 ± 0.03 0.17 ± 0.05a 0.14 ± 0.08b a

Density [trees/ha]

14.8 ± 1.1 13.0 ± 1.5a,b 12.5 ± 1.8b a

1520 ± 57 1800 ± 88b 1695 ± 34a a

The regeneration species diversity index was computed using the Shannon-Wiener information function (Hill, 1973; Özc¸elik et al., 2008) as: H = −˙(ni/n)Ln(ni/n) where: ni = denotes the SIV of a species and n = denotes the sum of the total SIV of all the species. The tree species diversity was tested by calculating the structural evenness index (Pielou, 1966; Begehold et al., 2016): J = H /Hmax where H is the number derived from the Shannon diversity index and Hmax is the maximum value of H This index varies between 0 and 1, where a value of 1 symbolizes an exact uniform distribution. The Shannon index is a model measuring species diversity and the degree of homogeneity in the species abundance. One of its applications is to precisely estimate the anthropogenic impact on ecological systems. The impact on soil due to silvicultural treatment and forest operations was assessed on 6 randomly selected sample plots (SP) for each area (A–C). Each SP consisted of a circular area of 12 m in diameter. For the SPs of the two harvested areas (A and B), two different points (PO) were selected based on a visual assessment (e.g. the presence or absence of bent understory, crushed litter, ruts or soil mixing) to represent disturbed and undisturbed soil conditions, respectively. In each PO, the Bulk Density (BD), pH, Organic Matter content (OM), Penetration Resistance (PR), and Shear Resistence (or strength) (SR) were measured. On area C, for each SP, only one PO was randomly selected for BD, pH, OM, PR and SR measurements. For BD determination, a steel cylinder of a known volume, 8.5 cm high and with a 5.0 cm inner diameter, was inserted into the top of the mineral soil. The soil was removed from the cylinder and, once in the lab, oven-dried at 105 ◦ C for 24 h to constant weight (dry weight) and weighed. The dry weight divided by the volume of the sampling cylinder was understood as the bulk density (BD), expressed in Mg m−3 . The PR of the soil was measured using a Pen-P100 penetrometer, while the SR was taken using a Sciss-S100 scissometer. These parameters were measured in the top 5 cm of the soil. The measured values were standardized to the water-holding capacity of the soil, which was determined as 26%, inferred from the particlesize distribution as according to Saxton et al. (1986). The pH value was measured using potentiometric analysis, using soil/saline solution suspensions (soil-KCl 1 mol) in a 1:2.5 proportion. Organic matter measurement was done by incineration in a mitten at 400 ◦ C for 4 h following the thorough elimination of water and pretreatment at 160 ◦ C for 6 h. The QBS-ar is an index measuring soil impact. It is very useful as it is extremely sensitive to environmental variations caused by anthropic disturbance. This index is exclusively qualitative, and evaluates the presence and the complexity of the soil conditions of the sites under study. For the microarthropod extraction and QBSar index application, three soil cores 100 cm2 and 10 cm deep were

Basal area [m2 /ha]

30.5 40.8 26.1

Above-ground biomass stock

Above-ground biomass harvested

[m3 /ha]

[m3 /ha]

239.8 227.1 212.1

201.2 219.7 –

sampled in each soil typology. Microarthropods were extracted using a Berlese-Tüllgren funnel; the specimens were collected in a preserving solution (ethyl alcohol and glycerol, 75 and 25% by volume, respectively) and identified at different taxonomic levels (class for Myriapoda and order for Insecta, Chelicerata and Crustacea) using a stereo microscope. Soil quality was estimated using the QBS-ar index (Gardi et al., 2008; Menta et al., 2010; Parisi et al., 2005; Tabaglio et al., 2009; Venanzi et al., 2016). The QBS-ar index is based on the following concept: the higher the soil quality, the higher the number of microarthropod groups well-adapted to soil habitats. Soil organisms were separated into biological forms according to their morphological adaptation to soil environments; each of these forms was associated with a score called EMI (ecomorphological index), which ranges from 1 to 20 in proportion to the degree of adaptation. The QBS-ar index value was obtained from the sum of the EMI of all the collected groups. The organisms belonging to each biological taxon were counted in order to estimate their density at the sampled depth (0–10 cm) and ratio of the number of individuals (IND) and the sample area to 1 dm2 of the surface (IND dm−2 ).

2.4. Statistics Statistical analyses were carried out using Statistica 7.1 (2007) Software. As a first step, data distribution was plotted and checked for normality (Lilliefors) and homogeneity of variance (Levene test). All the data points then underwent the t-test, ANOVA or MANOVA, to test the effect of the different treatments. In order to determine the relation between the QBS-ar, BD, PR and SR, a nonparametric correlation analysis (Spearman correlation matrix) was applied. The data, which were not normally distributed and with insufficient homogeneity of variance, were statistically processed using the nonparametric ANOVA Kruskal-Wallis test. Principal Non-metric multidimensional scaling, or nMDS, was applied in comparing univariate descriptors of microarthropod communities and the physical characteristics of the soil.

3. Results 3.1. Silvicultural treatment and dendrometric analysis The silvicultural treatment studied and applied (coppice with standards) seems simple and without any particular applicative problem, but in many cases this typology of forest management is considered a source of heavy environmental impact. The silvicultural treatment applied aims to conserve this management system, increasing sustainability compared to the past. The released scattered standards were 95 trees ha−1 , for both areas, A and B. These standards were of three age classes: 19-year-old (60%), ca 38 y.o. (30%), and ca 57 y.o. (10%). In addition, as prescribed by Regional Forestry Regulation, one tree in each hectare was released to indefinite aging. The dendrometric data collected before the harvesting of areas A and B showed average values which were statistically similar for

E. Marchi et al. / Ecological Engineering 95 (2016) 475–484 Table 2 soil area impacted by bunching and extraction activities (t-test analysis, df 1, 13; average ± SD). Area

P-value

Disturbed soil

Undisturbed soil

A B

>0.05

3.3 ± 1.3% 3.8 ± 0.8%

96.7% 96.2%

Table 3 tree species diversity indexes for the tree areas (Kruskall Wallis-test analysis, df 2, 14; p < 0.05; average ± SD; from the Tukey test applied, different letters show groups with statistically significant differences). Area A B C

Shannon Index a

1.77 1.25b 1.73a

Evenness Index 0.77a 0.64a,b 0.89c

trees age, Dbh (Diameter at breast height) and height, although area B had a higher tree density (Table 1). 3.2. Analysis of the impacted surface In this forest coppice, an average level of planned and applied technology in forest utilizations could lower the impact of the operation as suggested by reduced impact logging (RIL) methodologies (Enters et al., 2002; Maesano et al., 2013). On the basis of what is envisaged in RIL and from what has emerged and has been suggested in other studies (Maesano et al., 2013; Picchio et al., 2012a, 2011a, 2012b), the logging operations were carried out with appropriate mechanization. The tractors skidded the trees on the forest floor only occasionally, and in these cases, the impact was not only characterized by the amount of winching but also the frequency of vehicle movements. The forest surface strongly impacted by forest operations (presence of bent understory, crushed litter, ruts or soil disturbance) was on average 3.4 ± 0.9% of the total area, and did not show any statistical difference between treatments A and B (3.3/3.8%, Table 2). These results were notably lower than those obtained in other studies, characterized, however, by a much higher density of trees released after harvesting (Marchi et al., 2014; Picchio et al., 2012a, 2012b; Tavankar et al., 2013). 3.3. Analysis of stand regeneration In all three analysed areas, for each of the ten tree species that were observed (Fig. 1), there were statistically significant differences regarding the presence of a few species. Quercus pubescens was present only in A and C, Fraxinus ornus and Ulmus minor were present only in A and Prunus avium was present in A and B. Among the tree species, Quercus cerris showed the highest number of seedlings and shoots (subsequently abbreviated to SS) density (over 10,000 SS/ha), while Acer campestre L. showed the lowest density (about 100 SS/ha). U. minor Mill. and Fraxinus ornus L. were found only in area A, i.e. in the area where only the released standards were growing (Fig. 1). The average regeneration composition analyzed was ca 10% of shoots and 90% of seedlings, while only for P. avium, U. minor and Cornus mas was the average percentage of distribution ca 35% of shoots and 65% of seedlings. The SIV showed that Q. cerris was the most important species in all the treatments, in particular in area B (Fig. 2). The tree species diversity, tested by the Shannon-Wiener and the Evenness indices, showed different situations. The highest diversity was found in areas A and C (the average value of the Shannon Index was 1.77 ± 0.10 and 1.73 ± 0.12, and the Evenness Index amounted to 0.77 ± 0.08 and 0.89 ± 0.06, respectively, Table 3), while the lowest diversity was found in area B (Shannon Index 1.25 ± 0.09 and Evenness Index 0.64 ± 0.06, Table 3).

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3.4. Physical and chemical analyses of soil The soil texture was characterized by a high content of sand, 55.2%. The presence of silt was at 38.1% while the clay content was low at 6.7%, therefore the soil can be ascribed to the Franco-sandy (FS) soil material class. Along with the granulometric values and through the Soil Water method (K. Saxton), the soil field capacity was calculated (CC) at 26%. Regarding soil moisture during the sampling period, no statistically significant differences were observed among the treatments (average moisture 38 ± 7%). The soil BD, PR and SR showed statistically significant differences among the treatments (Tables 4 and 5). In particular, the BD was higher in the disturbed areas than in the undisturbed ones in both the A and B treatments (average increase of 0.232 g/cm3 , equal to ca 28%). In treatment C, a significantly lower BD was recorded in comparison with A and B, in both the disturbed and undisturbed areas. In comparison with the control, the BD in the undisturbed areas increased by an average of 0.188 g/cm3 , corresponding to 29%. Penetration analyses showed a significant increment of the PR when comparing the control with the undisturbed areas of A and B (an average of 0.048 MPa; 70%). There were also differences between the control (without any silvicultural treatment in the last decade) and the soil portions not disturbed by logging but subjected to silvicultural treatment. At the same time, the PR increased an average of 0.1690 MP (147%) when comparing the disturbed and undisturbed areas of the A and B treatments. The SR showed a significant increase in disturbed areas of A (+6.23 t/m2 ; 245%) and B (+2.91 t/m2 ; 114%) in comparison with the control. An increase was also recorded when comparing the undisturbed area of A (+1.08 t/m2 ; 42%) and the control. A comparison between the control and the undisturbed area of B did not show any statistically significant differences. The silvicultural activities performed within the studied area, significantly affected the OM content of the soil. In fact, the OM content was significantly higher in the control area (ca 6%, Table 6) than in the other treatments. Any statistically significant differences were recorded between the A and B treatments and the disturbed and undisturbed areas. The pH is a very important parameter for the correct functioning of the soil system, due to the fact that its variations influence various soil parameters and processes (Astolfi et al., 2011). However, in this study (Table 6), this parameter did not seem to have been influenced by silvicultural treatment or logging operations. 3.5. Soil biodiversity analysis The QBS-ar index (Table 7) showed significant differences between the A treatment and the control, and within the undisturbed and disturbed sections of the A treatment, thus suggesting an impact on the microarthropod community due to both the silvicultural treatment and forest operations. Although the microarthropod density significantly increased due to the silvicultural treatment, it did not show any significant changes in comparison with the control due to the join actions of the silvicultural treatment and forest operations. Two years after the treatment, the QBS-ar index was lower than the control in all the areas directly involved with logging activities (temporary tracks), and the recovery of the impacted soil was slow but significant, even just two years after felling. The QBS-ar index was also affected by the silvicultural treatment, but in the soil surfaces not impacted by logging activities, recovery for the microarthropods was very quick: even two years after felling. The results showed that the movement of vehicles had a major impact on the soil condition, while the silvicFultural treatment had a clearly defined impact, but one which was quickly recoverable.

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Fig. 1. number of SS per species in the three treatments (MANOVA test, df 10, 30, p < 0.05; average ± SD; the y axe is in logarithmic scale).

Fig. 2. SIV values for the three areas studied.

Table 4 results of the ANOVA and Tukey test for soil moisture and BD (df 3, 24; average ± SD), difference tested between disturbed, undisturbed and control soil. Area

Soil typology

Moisture%

p-value

Bulk density [g/cm3 ]

A

Undisturbed Disturbed Undisturbed Disturbed Control

38.2 ± 7.1

>0.05

0.773 0.982 0.903 1.157 0.650

B C

± ± ± ± ±

0.098 0.080 0.090 0.188 0.101

p-value

Tukey test

<0.01

a b b d e

E. Marchi et al. / Ecological Engineering 95 (2016) 475–484

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Table 5 results of the MANOVA (df 2, 40; average ± SD) and Tukey test for penetrometer and shear resistance data (average ± SD), difference tested between disturbed, undisturbed and control soil. Area

Soil typology

A

Undisturbed Disturbed Undisturbed Disturbed Control

B C

Penetration resistance[MPa] 0.128 0.294 0.103 0.275 0.068

± ± ± ± ±

0.05 0.09 0.04 0.07 0.03

p-value

Tukey test

Shear resistance[t/m2 ]

<0.01

a b a b c

3.622 8.773 2.467 5.456 2.544

± ± ± ± ±

0.88 2.48 0.91 1.26 0.74

p-value

Tukey test

<0.05

a b a,c d c

Table 6 results of the ANOVA and Tukey test for organic matter content and pH (df 2, 18; average ± SD), difference tested between disturbed, undisturbed and control soil. Area

Soil typology

A

Undisturbed Disturbed Undisturbed Disturbed Control

B C

Organic matter [%] 13.5 11.1 12.0 10.5 19.0

± ± ± ± ±

1.85 2.20 1.96 5.43 2.09

p-value

Tukey test

pH

<0.05

a a a a b

6.4 6.6 6.5 6.5 6.7

p-value ± ± ± ± ±

0.1 0.2 0.1 0.3 0.2

>0.05

Table 7 results of the Kruskall Wallis and Tukey test for QBS-ar index and soil microarthropod density data (df 2, 54; median), difference tested between disturbed, undisturbed and control soil. Area

Soil typology

QBS-ar index

p-value

Tukey test

microarthropod density[ind/dm2 ]

p-value

Tukey test

A

Undisturbed Disturbed Undisturbed Disturbed Control

172 93 240 188 251

<0.05

a b c a c

155 75 219 87 88

<0.05

a b c b b

B C

The QBS-ar index showed a very large variation range (93–251), as observed by Blasi et al. (2013) and Rüdisser et al. (2015). Namely, microarthropod communities were probably affected by the bunching and extraction operations because of the negative effect of soil compaction, in turn due to vehicle trafficking and log dragging. As already shown by Blasi et al. (2013) for forest ecosystems, soil compaction leads to the disappearance of specialized groups such as Protura, Coleoptera and Pauropoda. In addition, the microarthropod density was lower in all the areas involved in the impact caused by vehicles and logs (Fig. 3). Moreover, there was a statistically significant difference between the area subject to silvicultural treatment (but not impacted by vehicles) compared to the control site. In this case, however, it seems that the silvicultural treatment had a positive effect.

4. Discussion The findings showed that soil BD, PR and SR were influenced by both the silvicultural treatment and forest operations. In fact, the increase in soil BD, PR and SR, found in the undisturbed soil portions in the coppiced areas (A and B) in comparison with the control area (C) (without silvicultural treatment in the last decade), clearly suggest the direct effect of silvicultural treatments on soil characteristics. The effect of silvicultural treatment on the physical parameters of the soil is likely to be due to the action of atmospheric events, in particular rain, after removal of the protection of the soil guaranteed by the coppice canopy layer. Six months without the protection of the canopy may lead to significant changes in the physical parameters of the soil. Moreover, the abovementioned comparison (undisturbed A vs undisturbed B) suggests that a period of two years is not sufficient to allow the recovery of the BD and PR, although in 16 years these parameters showed a complete recovery. The lack of significant difference in the SR values of the undisturbed B samples and the control highlighted the fast recovery of the SR (two years).

The significant differences between the disturbed and undisturbed soil samples, in both areas A and B, also highlighted the significant effect of forest operations on soil BD, PR and SR (Tables 4 and 5). Changes in the BD, PR and SR may be caused by the compacting action of harvesting operations. Similar values have been observed in other studies where logs were skidded, and vehicles also moved across the forest soil (Picchio et al., 2012b; Cambi et al., 2016). These data provided further evidence that there is a need to limit the passage of vehicles over the same tracks and on the forest soil. The joint effect of silvicultural treatment and forest operations on the BD, PR and SR meant that the soil did not recover within two years (Tables 4 and 5). The results highlighted that the OM content of the soil was affected only by the silvicultural treatments, while logging activities did not show any significant modification of this parameter, because no changes were recorded between the disturbed and undisturbed samples in both the A and B treatments. The decrease in OM content in the treated areas may be linked to canopy removal, which means a lack of leaves from the canopy contributing to litter layer formation and an increase in the respiratory activity of soil microorganisms. Even two years after harvesting, recovery of the organic matter content had not significantly started. The results concerning stand regeneration indicated a similar taxonomic composition of the forest community among the areas studied, in particular in the harvested areas (A and B), the observed species were the same. The felling produced a greater abundance of heliophilous species due to the increase in light, but probably with little chance of settlement due to strong competition from stump resprouting. Among the three areas studied, there was no difference in the richness of the seedling species, as indicated by other authors (Tehrani et al., 2015; Watkins et al., 2003). However, the tree communities of the areas not only showed different densities of tree species, but different SIV, due to the high level of competition between the sprouts. The silvicultural treatment studied did not

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Fig. 3. nMDS analysis of the EMI-by-sites matrix, bulk density, penetration and shear resistance, difference tested between disturbed, undisturbed and control soil (polygon in the upper right with light blue line: area A undisturbed; polygon in the top center with blue line: area A disturbed; polygon in the bottom center with light green line: area B undisturbed; polygon in the left with green line: area B disturbed; polygon in bottom right with purple line: control). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

affect the species diversity and these results are also supported by another index which was applied, the Evenness index, which showed a very similar value to those of more complex silvicultural treatments, such as high forest. As found also in Blasi et al. (2013), the QBS-ar values showed a significant correlation with soil compaction. Most of the observed variation in the sample was explained by the different degree of soil compaction rather than by physical habitat heterogeneity. Namely, microarthropod communities are probably affected by bunching and extraction operations because of the negative effect of soil compaction, in turn due to vehicle traffic, as already shown by Blasi et al. (2013). In this study, soil compaction led to the disappearance of specialized groups such as Protura, Coleoptera and Pauropoda (Fig. 3). In addition to the QBS-ar index, the population density was evaluated during sampling in terms of individuals per dm2 , intending that this soil unit was specifically sampled at a pre-established depth of 10 cm. As can be observed from the data gathered, the microarthropod density was inferior in all the areas involved in the impact caused by the movement of vehicles and loads, while there was a significant statistical difference only between area A, subject to harvesting for 6 months (but not impacted by vehicles), and the control site (Table 7). It seems that the silvicultural treatment only had a negative effect in this area, though a minimum one. The movement of mechanical vehicles and loads had a negative influence on the index as observed for many other parameters. The nMDS of the EMI-by-sites matrix (Fig. 3) showed a negative relationship between the degree of arthropod complexity and soil compaction: the most impacted (and thus most compacted) sites featured an over-simplification of the species of fauna, losing the taxonomic and functional groups specifically adapted to soil habitats. As this study also showed, forest soil is extremely fragile in physical as well as chemical and biological terms and its balances are highly complex. Forest soil characteristics make it extremely vulnerable to natural or anthropic disturbance, for example, logging

operations (Vossbrink and Horn, 2004). Therefore, impact evaluation is extremely important in terms of forest management, and as a result, the design and application of low impact logging methods. The overall consequences of soil compaction are a decrease in soil permeability, and in the growth and nutrient supply of the root systems. These consequences are clear and definitely not positive as also shown by various authors (Alakukku, 2000; Heinonen et al., 2002). Moreover, from a phytopathological viewpoint, the increase in water runoff facilitates the expansion and transmission of pathogens in the form of spores and rhizoids (Vannini et al., 2009). 5. Conclusions A more complete census of the impact of forest coppice management is needed for a better understanding of the biological phenomena that are enabled and maintained by these systems. This study allowed the assessment of the impact of silvicultural treatment and harvesting operations on tree renovation composition and soil characteristics. Physical, chemical and biological soil properties are often significantly impacted by active forest management, in particular by silvicultural treatments and by harvesting operations, which may result in soil compaction and subsequent restrictions to tree growth and natural regeneration. The findings in this study demonstrate that tree species composition of regeneration was not impacted by silvicultural treatment or harvesting operations. On the other hand, physical, chemical and biological soil features were only marginally impacted by the silvicultural treatment applied, but were strongly impacted by harvesting operations. Heavy soil compaction, in the two areas (A and B), affected less than 4% of the forest surface, where bulk density increased (+28% for both areas), and microarthropod density decreased (−46%, 6 months after the harvest in area A, and −22%, 24 months after the harvest in area B). In this case, where winching was unavoidable and convenient, careful supervision and appropriate worker training could minimize logging impact, or rather limit this impact to small surfaces. In general, the impact caused

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by vehicle movement on forest soils (off the track) is evident by elaborating the data of the physical-mechanical soil components. Therefore, when future forest operations will be planned, a careful design of skid roads which limits any negative impact on the soil is recommended. It is also possible that the appropriate design of strip roads and forwarder use could be a way to lower the area of soil disturbance. In future research, it would be interesting to evaluate the capacity for recovery from these types of stress on the soil in the range still not studied of 2–16 years. Furthermore, it would be desirable to create designated skid trails that could be used to limit such an impact, hence preserving the rest of the area. For this specific study and other similar forest situations, if silvicultural treatment and logging activities were well planned and the sustainable forest management guide lines were followed, none particular post harvesting operation will be necessary. In some cases, there could be the need of a cleaning up the profile of tracks and if necessary a carryover of aggregates on main forest roads. These operations allow a sustainable forest management also for the future. In addition, a forest road network viable and functional will ensure a limited impact on forest soil (impacted soil surfaces <5–10%). The importance of studies such as these also lies in the possibility of deploying and updating the guidelines, criteria and indicators for sustainable forest management, as proposed by Forest Europe. Acknowledgements This contribution fits within COST Action FP 1301 ‘EuroCoppice’ of the EC’s Seventh Framework Program. References Özc¸elik, R., Diamantopoulou, M.J., Wiant Jr., H.V., Brooks, J.R., 2008. Comparative study of standard and modern methods for estimating tree bole volume of three species in Turkey. For. Prod. J. 58 (6), 73–81. Alakukku, L., 2000. Response of annual crops to subsoil compaction in a field experiment on clay soil lasting 17 years. In: Horn, R., Van den Akker, J.J.H., Arvidsson, J. (Eds.), Subsoil Compaction: Distribution, Processes and Consequences. Advances in Geoecology, vol. 32. Catena Verlag, Reiskirchen, pp. 205–208. Astolfi, S., Zuchi, F., De Cesare, L., Badalucco, S., Grego, S., 2011. Cadmium-induced changes in soil biochemical characteristics of oat (Avena sativa L.) rhizosphere during early growth stages. Soil Res. 49 (7), 642–651. Bürgi, M., 1999. A case study of forest change in the Swiss lowlands. Landsc. Ecol. 14 (6), 567–575. Begehold, H., Rzanny, M., Winter, S., 2016. Patch patterns of lowland beech forests in a gradient of management intensity. For. Ecol. Manage. 360, 69–79. Benes, J., Cizek, O., Dovala, J., Konvicka, M., 2006. Intensive game keeping, coppicing and butterflies: the story of Milovicky Wood Czech Republic. For. Ecol. Manage. 237, 353–365. Bengtsson, J., Nilsson, S.G., Franc, A., Menozzi, P., 2000. Biodiversity, disturbances, ecosystem function and management of European forests. For. Ecol. Manage. 132, 39–50. ˇ epánek, V., 2001. Land-use changes and their social driving Biˇcík, I., Jeleˇcek, L., Stˇ forces in Czechia in the 19th and 20th centuries. Land Use Policy 18 (1), 65–73. Blasi, S., Menta, C., Balducci, L., Conti, D.F., Petrini, E., Piovesan, G., 2013. Soil microarthropod communities from Mediterranean forest ecosystems in Central Italy under different disturbances. Environ. Monit. A 185, 1637–1655. Borchert, H., Huber, C., Göttlein, A., Kremer, J., 2015. Nutrient concentration on Skid trails under Brush-Mats – Is a redistribution of nutrients possible? Croat. J. For. Eng. 36 (2), 243–252. Buckley, G., 1992. Ecology and Management of Coppiced Woodlands. Chapman & Hall, London. Bugalho, M.N., Caldeira, M.C., Pereira, J.S., Aronson, J., Pausas, J.G., 2011. Mediterranean cork oak savannas require human use to sustain biodiversityand ecosystem services. Front. Ecol. Environ. 9, 278–286. CBD, 2001. Sustainable management of non-timber forest resources. Montreal: convention on biological diversity; Technical Series No. 6. CBD, 2010. COP 10 Decision X/2 Strategic Plan for Biodiversity 2011–2020, (accessed 12.12.15). CEC, 1998. European Community Biodiversity Strategy., (accessed 12.12.15). Cambi, M., Certini, G., Neri, F., Marchi, E., 2015. The impact of heavy traffic on forest soils: a review. For. Ecol. Manage. 338, 124–138. Cambi, M., Certini, G., Fabiano, F., Foderi, C., Laschi, A., Picchio, R., 2016. Impact of wheeled and tracked tractors on soil physical properties in a mixed conifer stand. IForest 9, 89–94.

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