Soil disturbance and early vegetation response to varying intensity of energy wood harvest

Forest Ecology and Management 348 (2015) 153–163

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Soil disturbance and early vegetation response to varying intensity of energy wood harvest Oili Tarvainen a,⇑, Anne-Maarit Hekkala a,b, Eero Kubin a, Pekka Tamminen c, Tanja Murto a,1, Anne Tolvanen a,b a b c

Natural Resources Institute Finland (Luke), P.O. Box 413, FI-90014 Oulun yliopisto, Finland Thule Institute, P.O. Box 7300, FI-90014 Oulun yliopisto, Finland Natural Resources Institute Finland (Luke), Jokiniemenkuja 1, FI-01370 Vantaa, Finland

a r t i c l e

i n f o

Article history: Received 12 January 2015 Received in revised form 31 March 2015 Accepted 1 April 2015 Available online 20 April 2015 Keywords: Forest soil Logging residue Patch mounding Site preparation Stump removal Understory vegetation

a b s t r a c t Forest biomass plays an important role in the production of renewable energy, particularly in northern Europe. During recent decades, tree stumps have also been increasingly used for energy production. The environmental impacts of stump removal on the functioning of forest ecosystems, for example on soil processes and biodiversity, are still inadequately understood. To investigate the separate impacts of tree stump and logging residue removal on soil and plant variables, we conducted a large-scale replicated experiment in clear-felled stands in three geographical areas. Four energy wood harvesting levels were combined with patch mounding (organic and mineral soil layer turned upside down) as a site preparation method. The harvesting treatments were: (1) no energy wood harvesting, (2) 70% logging residue removal, (3) 25 stumps per hectare left at site and 70% logging residue removal (maximum level in official recommendations), (4) complete stump and 100% logging residue removal. Soil disturbance in terms of mineral and organic soil cover increased with the increasing harvesting level, but complete stump removal did not increase the mineral soil cover more than partial stump removal (on average 95% removed). Despite the increase in soil disturbance, stump removal did not have an overall impact on plant species richness or vegetation composition in the second growing season after harvesting. However, an increasing trend in Betula spp. biomass with increasing harvesting intensity was seen in two of three study areas in four years. Our results underscored the high site-dependency of the effects of stump removal on ecological variables, thus the initial stand structure and vegetation type need to be considered when planning harvesting treatments. Ó 2015 Elsevier B.V. All rights reserved.

1. Introduction The use of renewable energy sources has been promoted to mitigate climate change, which has been one of the main environmental concerns globally during the last decades. For example, in Europe, the target is to increase the share of renewable energy to 20% of all energy sources by 2020 (European Commission, 2009). In northern Europe, the energy consumption is highest during the winter, when the availability of renewable energy sources such as sun, wind and water power is limited. On the contrary, energy wood can be used throughout the year. It is estimated that energy ⇑ Corresponding author. Tel.: +358 50 391 3780. E-mail addresses: Oili.Tarvainen@luke.fi (O. Tarvainen), Anne-Maarit.Hekkala@ luke.fi (A.-M. Hekkala), Eero.Kubin@luke.fi (E. Kubin), Oili.Tarvainen@luke.fi (P. Tamminen), Tanja.murto@metsa.fi (T. Murto), Anne.Tolvanen@luke.fi (A. Tolvanen). 1 Current address: Metsähallitus, P.O. Box 38, FI-39701 Parkano, Finland. http://dx.doi.org/10.1016/j.foreco.2015.04.001 0378-1127/Ó 2015 Elsevier B.V. All rights reserved.

wood may represent 14–18% of the world’s primary energy consumption in 2050, but the geographical distribution of potential energy wood supply vary (Lauri et al., 2014). In addition, the competing alternative uses of forest biomass may affect energy wood production at regional level. The use of small-sized trees and logging residues for energy wood has increased during recent decades in northern Europe, and stumps and lateral roots have also been harvested for energy use (Björheden, 2006; Helmisaari et al., 2014; Torvelainen, 2014). A notable increase in the use of energy wood is still necessary in order to reach national and international targets (Díaz-Yáñez et al., 2013; Lauri et al., 2014). For example, the national targets for renewable energy consumption have been set as high as 38% and 49% in Finland and Sweden, respectively (European Commission, 2009). The increased demand for renewable energy raises questions about the potential risks or advantages of energy wood harvesting (Dahlberg et al., 2011; Bouget et al., 2012; Wall,

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2012), and about the impacts of stump removal on the functioning of forest ecosystems (Walmsley and Godbold, 2010; Persson, 2013). Energy wood harvesting may impact forest ecosystems through at least two mechanisms: the direct disturbance effect on the soil due to the use of heavy machinery, which is expected to trigger vegetation succession relatively quickly, and the removal of organic biomass from the system, which influences the nutrient dynamics and may cause longer-term changes in the ecosystem. The most common energy wood harvesting method, logging residue removal, has been observed to have only a minor or temporary negative impact on stand productivity in clear-felled stands in northern Europe (Saarsalmi et al., 2010; Egnell, 2011; Wall and Hytönen, 2011; Zetterberg et al., 2013). Also, the increase in biomass of understorey vegetation after logging residue removal is short-term (Olsson and Staaf, 1995; Bergquist et al., 1999). The changes are similar to those observed after clear-felling, which only results in a temporary increase in the abundance of pioneer species and decrease in species sensitive to disturbance (Nieppola, 1992; Palviainen et al., 2005). More recently, it has been under debate as to whether stump removal has additional impacts on soil compaction, nutrient leaching and stand productivity (Walmsley and Godbold, 2010; Persson, 2013). According to previous studies, stump removal has been shown to have negative effects on soil properties, but only a minor or short-term effect on tree growth in boreal forest stands (Karlsson and Tamminen, 2013; Egnell et al., 2015). Nevertheless, stump removal may also have long-term impacts on forest ecosystems, as stumps can act as a nitrogen sink during the decomposition process (Palviainen et al., 2010), and decaying stumps offer heterogeneous habitats for many species (e.g. Caruso et al., 2008; Toivanen et al., 2012; Persson et al., 2013). Stump removal affects the decomposer community negatively through exposure of mineral soil cover, and thus may alter nutrient dynamics and promote changes in the understorey vegetation (Kataja-aho et al., 2011). One positive impact of stump removal arises from the prevention of root-rot diseases of forest trees (Cleary et al., 2013). Stump removal has been observed to have an additional disturbance effect on forest soil after site preparation (Kataja-aho et al., 2011; Strömgren and Mjöfors, 2012). Site preparation is commonly used in boreal forests to enhance the survival and early growth of outplanted tree seedlings (Heiskanen et al., 2013). Without site preparation, tree regeneration often fails in stands with the dense ericaceous dwarf shrub cover typical of boreal forests (Mallik, 2003; Hyppönen et al., 2013). The combined impacts of logging residue removal, stump removal and site preparation on soil disturbance and forest vegetation are still inadequately understood. Due to the greater disturbance effect, stump removal may have greater impacts on belowground rhizomes and roots than does logging residue removal. Also, stump removal may decrease the abundance of boreal dwarf shrub-dominated vegetation and increase the dominance of fast-growing species such as grasses and herbs, which may hinder the establishment of tree seedlings. We established an experimental study in 2006 to investigate the impacts of energy wood harvesting and site preparation on ecosystem functioning, biodiversity and stand characteristics (Kubin et al., 2013; Huusko et al., 2015). The present paper explores how the removal of stumps and logging residue affects the proportion of exposed soil surface, vegetation composition and plant biomass. We used four energy wood harvesting levels combined with clear-felling and site preparation. We based our treatment combinations on official recommendations which indicate that 25 stumps per hectare and 30% of logging residues need to be left and evenly distributed on the site (Äijälä et al., 2014). The sequence of the four harvesting treatments was expected to form an increasing soil disturbance gradient. We hypothesised that stump removal

(1) causes additional disturbance to forest soil compared to site preparation alone and site preparation followed by logging residue removal, and (2) increases plant species richness and changes vegetation composition towards fast-growing species more than the other treatments, and that (3) complete stump removal causes the most severe changes in soil and vegetation. To our knowledge, this is the first study to compare energy wood harvesting levels, logging residue removal alone and residue removal combined with partial or complete stump removal, with conventional forest regeneration methods without energy wood harvesting in order to investigate their impact on soil and vegetation. In addition, the effect of stump removal on plant biomass has not been reported earlier. 2. Methods 2.1. Study areas and experimental layout Spruce-dominated managed forest stands in three geographical study areas were chosen in southern and central Finland (Fig. 1, Table 1). The two southern areas belong to the southern boreal vegetation zone, and the northernmost area to the middle boreal vegetation zone (Ahti et al., 1968). Within each study area, three replicate blocks, each consisting of five study sites of ca. 40 m  50 m were established. The size of study sites in the Central area was ca. 30 m  50 m. The blocks of 0.5–1 ha were located at a distance ranging from 0.2 to 15 km from each other. One of five sites in each block was the reference site (reference forest, F) which consisted of managed mature standing forest. The other four were experimental sites with four energy wood harvesting levels combined with clear-felling and site preparation. We based our treatment combinations on official recommendations indicating that 25 stumps per hectare and 30% of logging residues need to be left and evenly distributed on site (Äijälä et al., 2014). The sequence of the four harvesting treatments was expected to form an increasing soil disturbance gradient: (1) no energy wood harvest (No), (2) 70% logging residue removal (L), (3) partial stump and 70% logging residue removal (SL; maximum levels in the official recommendations), and (4) complete stump and 100% logging residue removal (SLc). Patch mounding, turning the organic and mineral soil layer upside down using the machines with the planting unit, was used as the site preparation method in all treatments. The number of stumps left at site in the SL treatment approximates 5% of all stumps 150 mm in diameter in the present study. The total number of study sites was 45 (i.e. 3 geographical areas  3 replicate blocks  5 study sites). Trees were felled from all harvested sites during winter 2007/ 2008 and delimbed at the sites. Logging residues (branches with needles) were collected with a bundler, and stumps with lateral roots up to 5 cm in diameter were dug out of the ground with excavators in June 2008 and left at the sites for six weeks to dry before removal. The stump-uplifting heads were different in each area. In treatment No, where logging residues were not collected, residues were spread evenly on the sites. In treatment SL, the stumps left at site were evenly distributed. In August 2008, Norway spruce nursery seedlings were planted in tandem with patch mounding. The machines used in the patch mounding and planting were ‘Bräcke’, with one planting unit in the South and Central, and ‘M-Planter’ with two planting units in the North area. The seeds were from local origins for each study area, and the seedlings were 1.5 years old at the time of planting. 2.2. Stand characteristics Tree stand characteristics were recorded on two 150 m2 circular sample plots at each study site. The number of stems (d > 45 mm at

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Study site 40 m x 50 m

M Arctic circle

I B

Vegetation survey

North

Soil surface type survey grid Central South

Ground water wells

Fig. 1. Location of the study areas in Finland and a schematic layout of a study site. Soil surface types were surveyed on a grid consisting of 100 points 4 m apart. Vegetation survey plots in 2009 were intact (I) and mound (M), and in 2012 the plant biomass (B) was surveyed from an adjacent plot.

breast height) was calculated by species, and their age, basal area, diameter at breast height and height were measured. Before stump removal in 2008, the number and diameter of the tree stumps (d > 150 mm) were surveyed at the sites with stump removal treatments (SL, SLc). The stumps were counted by species and classified by their pre-felling state: living standing tree, living fallen tree, dead standing tree, dead standing tree broken higher than breast height, old stump, down dead tree with stump. In total, eight species were found, two of which were coniferous. Soil samples were taken during the establishment of a ground water experiment in 2006 (Kubin et al., 2013) and used to determine the soil texture for each area. Soil texture was determined from 234 soil samples using particle size analysis (Elonen, 1971). Other soil characteristics were investigated in 2007. At each study site, two composite samples consisting of 20 pooled subsamples each were systematically collected from the organic layer using a steel borer (d = 60 mm). The thickness of the organic layer was measured at each sampling point. Two composite samples consisting of 10 pooled subsamples each were taken from the upper 0–10 cm mineral soil layer using a steel borer (d = 44 mm). All samples were air dried at 35–40 °C. The milled organic soil samples and sieved mineral soil samples (<2 mm fraction) were used for analysis. Soil pH was determined in a CaCl2-suspension (ratio 10:25). Total C and N concentrations in the air-dried soil samples were determined using a Leco 1000 CHN analyser. 2.3. Soil disturbance We measured the cover of soil surface types formed after treatments at each experimental site. Covers were estimated from 100 point locations in a grid of 10  10 lines. The lines were 4 m apart, 2 m from the site edge and 12 m from the edge where the ground water wells were located (Fig. 1). In the Central area, the grid was 1.5 m from the longer edge and the lines were 3 m  4 m apart from each other. In total, we distinguished seven soil surface types:

intact surface (called intact), track formed by excavator or other machine (excavator track), organic soil clods loosened by machine (organic soil clods), mineral soil exposed by stump removal, patch mound, patch pit, and mineral soil exposed by patch mounding. The exposure of mineral soil by stump removal was measured before patch mounding in order to separate these two types. In order to gain a more general view, the total cover of exposed mineral soil was calculated by pooling the covers of mineral soil exposed by stump removal and patch mounding. 2.4. Vegetation We surveyed the understorey vegetation before and after the clear-felling and site preparation. In 2007, we systematically selected five 1 m  1 m vegetation sampling plots at each study site: one in each of the corners and one in the middle of the study site (225 plots in total). In 2009, the vegetation plots were placed in the corners of the study sites (Fig. 1). In each of the corners, one plot was placed randomly on one patch mound (called mound) and another on the adjacent intact surface (intact). In the reference forest, we had only intact plots. Altogether, 180 intact plots and 144 mound plots were inventoried in 2009. The percentage cover of vegetation was visually estimated using a scale from 0% to 100%. A value of 0.25% represented the presence of a species and a value of 0.5% was given for very small covers, while otherwise only integer values were used. Tree seedlings and shrubs under 0.5 m in height were included in the field layer vegetation, together with dwarf shrubs, herbs, grasses and ferns. The ground layer vegetation consisted of bryophytes, liverworts and lichens. We also inventoried the cover of litter, logging residue, stump, stones, mineral soil, organic soil, down dead wood, living roots and living standing trees. The plant species were organised into plant functional types (PFT) according to their growth form (Appendix A) and finally grouped as follows: (1) tree saplings and shrubs; (2) dwarf shrubs; (3) herbs and grasses including

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Table 1 Climatic and soil characteristics, and stand structure for three study areas in Finland. Mean ± SE are presented for soil and tree variables. Characteristic

South

Central

North

Municipality Location Elevation (m asl)

Kouvola 60°480 N 26°550 E 65–79

Orivesi 61°400 N 24°480 E 117–158

Paltamo 64°270 N 24°480 E 206–214

Climatic variables Annual air temperature (°C)A Annual precipitation (mm)A Temperature sum (>5 °C)A

5.3 716 1539

4.6 658 1367

2.5 690 1113

Soil variables Soil textureB Organic soil thickness (cm) Organic soil C:N Organic soil pHCaCl Mineral soil C:N Mineral soil pHCaCl

Loamy sand 6.8 ± 0.2a 33.9 ± 0.3b 2.99 ± 0.03b 27.6 ± 0.8a 3.57 ± 0.06a

Sandy loam 5.0 ± 0.2b 28.1 ± 1.0c 3.25 ± 0.06a 24.7 ± 0.7b 3.68 ± 0.03a

Sandy loam 6.0 ± 0.4a 36.8 ± 0.8a 3.01 ± 0.03b 22.0 ± 0.5c 3.61 ± 0.05a

Stand structure (DBH > 45 mm) Picea (%)C Pinus (%)C Betula (%)C Stand age in 2007 (years)D Tree density (trees ha1) Basal area (m2 ha1) Diameter at breast height (cm) Average tree height (m)

75 ± 3.8c 22 ± 3.7a 2.8 ± 0.5b 90 ± 2b 814 ± 61a 32.8 ± 0.8a 22.1 ± 0.8a 21.0 ± 0.5a

89 ± 3.1b 0.8 ± 0.3b 6.6 ± 1.3a 79 ± 4c 843 ± 75a 27.5 ± 1.1b 19.0 ± 0.8b 16.9 ± 0.6b

96 ± 0.7a 1.0 ± 0.4b 1.7 ± 0.4b 156 ± 5a 803 ± 39a 30.5 ± 1.3ab 20.1 ± 0.6ab 16.2 ± 0.6b

Stumps of living standing treesE Number (ha1) Diameter (cm)

488 ± 51ab 32.6 ± 0.9a

449 ± 32b 31.0 ± 1.2a

593 ± 45a 33.0 ± 2.5a

Letters a–c indicates significant pairwise differences (p < 0.05) between areas (N = 45; for stumps N = 18). A Average for years 2007–2011 (Venäläinen et al., 2005). B According to USDA classification (Soil Survey Staff, 1999). C Proportion of Picea abies, Pinus sylvestris and Betula spp. from all trees >45 mm in diameter at breast height (DBH). D Measured from 54 Picea abies –trees. E Counted from stump removal sites only and included stumps > 150 mm in diameter.

ferns; (4) bryophytes and lichens. The PFT covers were calculated by pooling the covers of all species belonging to that PFT. Mean cover for each PFT and the field layer and ground layer vegetation was calculated for each site (N = 5 in 2007, N = 4 in 2009). Plant species richness was counted for each area (total number of species at 15 sites) and at site level (total number of species in 4–5 plots). The number of species includes morphospecies groupings such as Poaceae spp. which could not be determined for species level. 2.5. Plant biomass In 2012, four years after harvesting, we clipped the vegetation above the organic layer from 3 to 4 plots per site (in total 120 plots) to measure the biomass of the vegetation. The clipping plots of 1 m  1 m in area were randomly located near the intact and mound plots surveyed in 2009 (Fig. 1). The field layer vegetation (under 0.5 m at height) was clipped from the whole plot, whereas the ground layer vegetation biomass was measured from three pooled subsamples taken along a transect across the clipping plots using a steel borer (d = 100 mm). The number of tree saplings taller than 0.5 m high was counted. The clipped material was separated at species level or at PFT level: Betula spp., Populus tremula, Sorbus aucuparia, Rubus idaeus, Calluna vulgaris, Vaccinium myrtillus, Vaccinium vitis-idaeus, Epilobium angustifolium, herbs and grasses, bryophytes, lichens, unidentified parts. We calculated the biomasses at PFT level by pooling the biomass of all species belonging to the following groups: (1) tree seedlings and shrubs, (2) dwarf shrubs, (3) herbs and grasses, and (4) bryophytes and lichens.

The dry weight was measured after drying at 50 °C for 72 h. The biomass for each species or pooled PFT was scaled up to the per hectare basis. The mean biomass for each site was calculated (N = 3–4). 2.6. Data analysis All statistical analyses were performed using R 2.15.1 (R Core Team, 2014). We used linear (lm) or generalised linear (glm) models to analyse the original differences between the ‘study areas’ (South, Central, North) and the effect of stump number and diameter on the cover of exposed mineral soil. The effects of ‘study area’ and ‘treatment’ (No, L, SL, SLc) on soil surface types were analysed using linear and generalised linear mixed models (lme4 package, Bates et al., 2014). For the plant species richness and covers of ground and field layer vegetation, the fixed factors in the mixed models were ‘study area’, ‘treatment’ (F, No, L, SL, SLc), ‘survey year’ (2007, 2009) and ‘vegetation plot type’ (intact, mound). For the plant biomass variables, the fixed factors in the mixed models were ‘study area’ and ‘treatment’ (F, No, L, SLc) which were chosen after testing the effect of tree saplings on the biomasses at clipping plot level. ‘Block’ was used as a random factor in the mixed models. The random factor takes into account the fact that a set of treatments was located within each block. Also, the pairwise differences between combinations of ‘treatment’ and/or ‘vegetation plot type’ were analysed separately for each area. The figures and tables present the original values. The continuous variables and cover data were analysed using linear models with Gaussian error distribution (lmer with restricted maximum likelihood). The count variables were analysed using generalised linear models with Poisson error distribution (glmer with Laplace approximation). The normality and homogeneity of the model residuals were checked using diagnostic plots. An arcsine square root transformation was used for modelling the cover data, as recommended by Crawley (2007). For the biomass variables, cubic root transformation was best to fulfil the model requirements. An analysis of variance table of type 3 errors was produced for the lmer models using the Satterthwaite approximation for degrees of freedom (lmerTest package, Kuznetsova et al., 2014). Pairwise analyses between the study areas or treatments were conducted by changing the null level of the factor. The estimated difference between two means was considered statistically significant (p < 0.05), when the absolute value of the t- or z-score in the mixed models was P2 (Crawley, 2007). The t- and z-scores were obtained by dividing the model parameter estimates (coefficients) by the model standard errors. We used ordination to visually represent the differences in plant species composition between ‘study areas’, ‘treatments’, ‘vegetation plot types’ and ‘survey years’. Non-metric multidimensional scaling (NMDS) was used to investigate the relationship between the vegetation and stand properties. The Bray-Curtis coefficient was used as a dissimilarity measure in NMDS (metaMDS) and permutational multivariate ANOVA (adonis) in the comparisons of plant species composition in different categories (vegan package, Oksanen et al., 2015). The two-dimensional solution was chosen to minimise stress and to maximise the correlation of the stand structure and vegetation variables in the NMDS ordination. The standard error of ordination scores with 95% confidence limits for each class is illustrated by an ellipsoid. The permutational multivariate ANOVA (PerMANOVA) identifies the relevant centroids of the data and then calculates the squared deviations from these points. Significant differences (p < 0.05) were generated using F-tests based on sequential sums of squares from 999 permutations of the raw data and were considered as significant when the category explained more than 55% of the variation (r2 > 0.3). Stand structure, soil surface type and vegetation related

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variables were fitted to the NMDS ordination in order to explore the relative importance of these variables in structuring plant communities. We used the function envfit from the vegan package (Oksanen et al., 2015) to identify variables that were significantly correlated with plant community composition. The significance of the correlations was assessed by comparing the r2 fit to r2 values generated via 999 random permutations of these variables. Vectors with a correlation r > 0.6 and p < 0.05 were considered to significantly correlate with community data. We also examined the relationships between vegetation and different treatments using indicator species analysis (Dufrêne and Legendre, 1997). We used the multipatt function available in the indicspecies package (De Caceres and Jansen, 2012). The method provides a set of classification groups that best matches the observed species distribution pattern (De Caceres et al., 2010). Therefore, a species might indicate one or several classes. A perfect indicator species (indicator value = 1.00) is always present within that class/classes and never in other class/classes. The statistical significance of the relationship between species and class/classes was achieved using permutation tests (999 permutations). Indicative plant species were detected for different groups if their indicator value was higher than 0.6 and p < 0.01. We classified the harvesting treatments (No, L, SL, SLc) and vegetation survey plots (intact, mound) as well as the reference forest (F) into the following groups: (1) forest before and reference forest after actions (B + F), (2) intact No, (3) intact L, (4) intact SL + SLc, (5) mound No; (6) mound L and (7) mound SL + SLc. 3. Results 3.1. Soil disturbance Both the partial and complete stump and logging residue removal treatments (SL and SLc) affected the soil characteristics more than did the logging residue removal (L) and no energy wood harvesting (No) treatments, but were similar to each other (Fig. 2, Appendix B). Following stump removal, the total cover of exposed mineral soil was up to 10-fold higher and cover of intact surface up to 2.2-fold lower as compared to the No and L treatments. The cover of the intact surface was greater in the South (t = 10.8) and Central (t = 7.60) than in the North area due to the greater cover of excavator tracks in the North (Fig. 2). In addition, the stump removal treatments clearly increased the cover of organic soil clods more in the North than in the South and Central areas (t = 6.15 and 7.08, respectively). Because of the significant interaction between area and treatment factors (p < 0.001), we analysed the differences in intact, organic soil clod and exposed mineral soil covers between the treatments separately for each area (Appendix C). In the South and Central areas, the total cover of exposed mineral soil was 4–10-fold greater after the SL and SLc treatments as compared to other treatments, but in the North, the exposed mineral soil cover varied less between the treatments (range 0.9–1.7-fold). Organic soil clods were found only in the SL and SLc treatments, while the intact cover was similar in all harvesting treatments in the North area. 3.2. Vegetation 3.2.1. Species richness A total of 110 plant species including morphospecies were found during the study period (Appendix A). The species richness was lowest in the South, with 29 plant species, while in the North the richness was higher (39; z = 3.21) and highest in the Central area (55; z = 6.25 and 3.16, respectively). In the second year after harvesting, the total number of plant species increased to 35 in the South, 48 in the North and 88 species in the Central area.

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No overall treatment effect on species richness was found, but area and vegetation plot type affected the number of species (Appendix D). The species richness was similar in the harvesting treatments irrespective of vegetation plot type in the South area, whereas in the intact plots the complete stump and logging residue removal (SLc) treatment resulted in lower species richness in the Central as compared to No and L treatments and higher in the North area as compared to other treatments (Table 2). 3.2.2. Plant species composition The vegetation composition was similar between the harvesting treatments, but differed from the forest reference (Fig. 3d). Within the harvesting treatments, the vegetation composition in the mound plots differed only slightly from the intact plots (Fig. 3c). Prior to harvesting, the study areas differed in plant species composition (F = 11.8, r2 = 0.36, p < 0.01), but in the second year after treatments the differences between areas were no longer that clear (Fig. 3c). In the ordination, the covers of mineral and organic soil increased towards the mound plots in the North and South areas and the number of tree species towards the mound plots in the Central area, while the cover of herbs and number of herb, grass and fern species increased towards the intact plots in the Central area (Fig. 3a, Appendix E). The cover of bryophytes and dwarf shrubs increased towards the forest reference plots. As regards the soil and stand characteristics, the ratio C-to-N and acidity in the organic soil layer decreased while proportion of birch trees before felling increased towards the plots in the Central area (Fig. 3a, Appendix E). 3.2.3. Indicator species analysis None of the plant species indicated stump removal alone, whereas mosses Dicranum polysetum and Hylocomium splendens and herb Melampyrum sylvaticum indicated forest vegetation prior to harvesting, reference sites and intact plots at the harvested sites (Fig. 3b, Appendix F). Herbs E. angustifolium and Luzula pilosa indicated both intact and mound plots at the harvested sites, whereas Pohlia nutans (moss) indicated all harvested sites except the intact plots in the treatment without energy wood harvesting (No). V. vitis-idaea was found in all except the mound plots at the stump removal sites, whereas Picea abies was typical on the mound plots at all harvested sites and also on the intact plots at the stump removal sites. 3.2.4. Vegetation cover All harvesting treatments increased the cover of field layer vegetation in the intact plots but decreased the cover of ground layer vegetation in both types of plot (Table 2, Appendix D). The complete stump and logging residue removal (SLc) treatment resulted in the highest cover of field layer vegetation in the intact plots in the Central area, and the highest cover of ground layer vegetation in the intact plots in the North area as compared to the other harvesting treatments (Table 2). 3.2.5. Plant biomass Four years after harvesting, the total plant biomass was lower at the harvested sites as compared to the reference forest in the South and Central areas, but in the North, the total plant biomass was clearly higher at the harvested sites (Fig. 4). In addition, the direction and extent of the treatment effects on the biomasses of PFTs differed between the study areas (Fig. 4, Appendix G). Ground layer bryophytes and lichens were largely responsible for the difference between areas, as they were negatively affected by harvesting in the South and Central areas, while in the North the ground layer biomass was almost unaffected. The biomass of herbs and grasses was much higher at all harvested sites as compared to the

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Fig. 2. Cover (%) of soil surface types in 2008 at the harvested sites in three study areas. Means of original values are presented (N = 3). MS denotes mineral soil. The harvesting treatments were: No, no energy wood harvest; L, 70% logging residue removal; SL, 25 stump stumps per hectare left at site and 70% logging residue removal (maximum levels in the official recommendations; Äijälä et al., 2014); SLc, complete stump and logging residue removal.

Table 2 The species richness and percentage cover of field layer and ground layer vegetation before harvesting in 2007 (B), and in 2009 in the forest reference (F) and in the intact and mound plots at the harvested (No, L, SL, SLc) sites. Mean and strandard error of original values are presented (N = 3). Significant (p > 0.05) pairwise differences between treatments are presented by letters a–e. The field layer consists of tree seedlings and shrubs under 0.5 m in height, dwarf shrubs, herbs, grasses and ferns. The ground layer vegetation consisted of bryophytes, liverworts and lichens. Mean and standard error of original values are presented (N = 3). The harvesting treatments were: No, no energy wood harvest; L, 70% logging residue removal; SL, 25 stump stumps per hectare left at site and 70% logging residue removal (maximum levels in the official recommendations; Äijälä et al., 2014); SLc, complete stump and logging residue removal. Species richnessA

A B

Field layer coverB

Ground layer coverB

South

Central

North

South

Central

North

South

Central

North

B F

11.8 ± 0.5a 13.0 ± 0.6a

21.2 ± 1.5b 21.4 ± 5.7ab

16.2 ± 1.1a 16.7 ± 5.4a

21.8 ± 5.0b 22.0 ± 7.9b

29.9 ± 2.2c 55.6 ± 7.2b

38.6 ± 4.1b 33.7 ± 11b

76.6 ± 4.0b 81.3 ± 1.7a

65.4 ± 3.2b 83.6 ± 3.2a

68.0 ± 4.8a 73.2 ± 5.6a

Intact No L SL SLc

13.7 ± 3.2a 12.4 ± 2.1a 15.0 ± 1.2a 15.4 ± 1.7a

27.0 ± 3.7a 27.7 ± 3.0a 24.0 ± 5.1ab 20.7 ± 2.4b

11.0 ± 2.1b 11.4 ± 0.9b 11.0 ± 1.6b 19.0 ± 4.1a

43.8 ± 6.9a 49.2 ± 6.5a 49.2 ± 13a 41.3 ± 9.9ab

60.0 ± 12ab 45.7 ± 12b 45.6 ± 8.8b 76.5 ± 8.2a

53.3 ± 13ab 45.2 ± 6.2ab 46.4 ± 13ab 59.2 ± 6.3a

23.3 ± 9.0c 20.2 ± 4.7c 19.5 ± 3.6c 25.3 ± 6.7c

Mound No L SL SLc

12.0 ± 1.6a 12.0 ± 0.6a 12.4 ± 1.8a 13.7 ± 1.4a

22.0 ± 1.8ab 17.0 ± 3.7b 18.4 ± 3.9b 16.7 ± 3.2b

10.4 ± 1.4b 12.4 ± 0.7b 10.4 ± 0.9b 14.7 ± 5.3ab

15.5 ± 3.0b 18.7 ± 3.6b 14.6 ± 6.3b 10.7 ± 3.8b

23.0 ± 13c 22.6 ± 8.4c 25.2 ± 12c 19.8 ± 1.4c

11.4 ± 1.5c 14.9 ± 0.6c 7.00 ± 2.0c 10.7 ± 4.0c

3.70 ± 1.8d 2.70 ± 0.9d 4.50 ± 2.3d 7.40 ± 5.4d

5.90 ± 2.8c 7.60 ± 0.4c 6.80 ± 4.2 cd 9.30 ± 4.5c 3.80 ± 1.7 cd 3.30 ± 0.5 cd 2.60 ± 2.3 cd 0.90 ± 0.3d

19.7 ± 11 cd 21.2 ± 11c 24.7 ± 14bc 37.2 ± 5.7b 6.20 ± 4.5de 4.40 ± 1.9de 1.00 ± 0.4e 5.30 ± 1.8de

Pairwise differences analysed separately for areas using glmer model, Poisson error distribution and block as random factor (N = 42). Pairwise differences analysed separately for areas using lmer model, arcsine square root transformated data and block as random factor (N = 42).

reference forests while the biomass of dwarf shrubs was similar in all treatments, regardless of study area. Tree seedlings and shrubs showed high site-dependency in their responses to harvesting treatments. Their biomass was highest after the complete stump and logging residue removal (SLc) treatment in the South (t = 5.82 and 3.86, respectively for the F and No treatments) and North (t = 4.54 and 2.93, respectively for the F and No treatments) areas, whereas in the Central area the biomass was highest in the treatment without energy wood harvesting (No; t = 5.49, 2.85 and 2.11, respectively for the F, L and SLc treatments). Due to the great variation between and within the areas, no differences in the biomasses of plant species were found between the treatments (Table 3, Appendix G), except in the South, where the complete stump and logging residue removal (SLc) treatment had a higher biomass of Betula spp. seedlings and C. vulgaris as compared with the treatment without energy wood harvesting (No). The biomass of Betula spp. seedlings was also highest in SLc treatment in the North area.

has raised a debate about its ecological effects as compared to more conventional harvesting methods. As we hypothesised, stump removal caused an additional disturbance to the soil. We expected that the complete stump removal would result in the most disturbed soil and hence the highest species richness and greatest changes in species composition. However, the treatment with maximum level of official recommendations (25 stumps per hectare and 30% of logging residue left at site) and complete stump and logging residue removal treatment differed in species richness only in the North study area. Against our second hypothesis, the understorey vegetation composition was similar in all forest harvesting treatments, which indicates that clear-felling alone triggers the greatest changes in the vegetation. The hypothesis was partially supported, however, as an increasing trend in Betula spp. biomass was seen in the South and North areas, thus emphasising the site-dependency of the effects.

4. Discussion

Soil disturbance using heavy machinery for logging residue and stump removal is assumed to cause a long-term decrease in stand productivity because of soil compaction and potential nutrient loss (Walmsley and Godbold, 2010, and references therein; Strömgren

Stump removal following clear-felling is an increasingly common method of energy wood harvesting in northern Europe. This

4.1. Soil disturbance

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(a)

(b)

(c)

(d)

Fig. 3. (a) Two-dimensional NMDS ordination of 126 vegetation plots inventoried before and in a second year after clear-felling and site preparation (stress = 19.8). Fitted vectors (i.e. statistically significant correlations with r > 0.58 and p = 0.001) describing the relationship between stand (soil characteristics, stand structure), plot level (plant functional type, no-plant-related cover) variables and vegetation composition in the plots are presented. The length of each vector indicates the strength of correlation between the vector and the ordination configuration (see Appendix E). (b) Species ordination of the same plots. The indicator species are labelled. (c) Ordination of the plots classified by year, area and vegetation plot type. Survey year is presented using light grey colour for 2007 and black for 2009. (d) Ordination of the plots by treatments. An ellipsoid represents the standard error of ordination scores with 95% confidence limits for each class. For plant species abbreviations, see Appendix A.

et al., 2013). The increase in exposed mineral soil after stump removal was similar to previous results (Kataja-aho et al., 2011; Strömgren and Mjöfors, 2012). In our study, the soil disturbance consisted of various components, of which the exposed mineral soil was the most pronounced. Mineral soil exposure may result in higher soil temperature fluctuation (Ballard, 2000; Devine and Harrington, 2007) which, in turn, may increase the drought stress. However, our results revealed the site-dependency of the ecological consequences of stump removal, as the exposure of mineral soil by stump removal was much higher in the South and Central areas than in the North area where the additional disturbance was caused by organic soil clods. The low exposure of mineral soil in the North was possibly due to the differences in the harvesting machinery. The disturbance of organic soil layer may lead to a risk of nutrient leaching, as has been observed after site preparation (Piirainen et al., 2007). In the long term, these differences in the type of soil disturbance may be seen in the soil carbon and nitrogen pools

(Hyvönen et al., 2012; Strömgren et al., 2013) and in the tree growth. According to our previous results, the early growth of planted spruce seedlings was similar in all areas and harvesting treatments after the fourth growing season (Huusko et al., 2015), whereas logging residue and stump removal has been found to improve the growth of similar age spruce seedlings (Menkis et al., 2010). Also, only a minimal or temporary impact has been noted on tree growth in boreal (Karlsson and Tamminen, 2013; Egnell et al., 2015) and temperate (Hope, 2007) coniferous forest stands in 10–30 years after stump removal. 4.2. Effects of stump removal on vegetation Plant species richness and field layer vegetation cover have been noted to increase after stump removal, especially in the intact soil surface (Kataja-aho et al., 2011), which observations were partially supported in the present study, as complete stump removal resulted in increased species richness in the North. The possible

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Fig. 4. Biomass (mean kg DW ha1) of plant functional types in 2012 at forest reference (F) and harvested (No, L, SLc) sites in three study areas. Mean of original values are presented. The harvesting treatments were: No, no energy wood harvest; L, 70% logging residue removal; SLc, complete stump and logging residue removal.

explanation for the higher species richness in the North may be the low cover of intact soil surface and high cover of excavator track, which enables the establishment of pioneer species such as herbs, grasses and pioneer mosses. On the other hand, the previously observed positive impact of stump removal on Betula spp. (Saksa, 2013) or R. idaeus (Kataja-aho et al., 2011) were only partially supported in the present study. The positive response of Betula spp. to stump removal could be explained by increased germination on disturbed soil (Granström, 1988; Saksa, 2013) and their sprouting ability (Johansson, 2008). R. idaeus was present in all harvesting treatments, but in contrast to Kataja-aho et al. (2011) did not increase in biomass after stump removal. Stump removal has previously been found to negatively affect the typical boreal forest mosses H. splendens and Dicranum spp. and dwarf shrub V. vitis-idaea (Andersson, 2012; Kataja-aho et al., 2011). In the present study, none of the studied species responded more negatively to stump removal than to other harvesting treatments. However, the covers of H. splendens and D. polysetum were lower in the mound plots as compared to the reference forests and intact plots. Even though the biomass of bryophytes and lichens was not affected by stump removal treatments, their species composition might have changed towards more stress-tolerant and fast-growing species. H. splendens is the most sensitive boreal moss species and often greatly decreases after clear-felling due to increased light and drought stress (Nieppola, 1992; Mäkipää, 2000; Palviainen et al., 2005). D. polysetum has a good sprouting ability after disturbance and is expected to recover quickly (Mäkipää, 2000). According to the present results, stump removal did not have strong additional impact on vegetation in the short term, while the responses of different plant species seemed to depend on the soil and stand properties more than on the energy wood harvesting treatment.

E. angustifolium also leads to competition for light (Balandier et al., 2006). E. angustifolium has previously been shown to benefit from the presence of logging residues (Olsson and Staaf, 1995; Bergquist et al., 1999; Palviainen et al., 2005), but in our study it was similarly abundant in all harvesting treatments. However, harvesting logging residues reduces the amount of available nitrogen, which may cause a time-lag in the appearance of E. angustifolium (Bergstedt and Milberg, 2001). The high abundance of herbs and grasses and the low abundance of ground layer bryophytes in all of the harvesting treatments were typical responses to clear-felling and site preparation (Nieppola, 1992; Hannerz and Hånell, 1997; Peltzer et al., 2000; Pykälä, 2004; Palviainen et al., 2005). Clear-felling alone changes the microclimate and soil conditions drastically (Ballard, 2000; Palviainen et al., 2005), which seemed to affect the understorey vegetation more than any harvesting treatment in the present study. National forest inventories carried out in Finland and Sweden show that forest management affect negatively to ericaceous dwarf shrubs (Reinikainen and Salemaa, 2000; Bergstedt and Milberg, 2001). In our study, the biomass of V. myrtillus decreased. According to other studies, dwarf shrub-dominated vegetation is well buffered against light disturbances which do not remove the organic soil layer (e.g. Rydgren et al., 2004; Hautala et al., 2008; Manninen et al., 2009), and, for example, the abundance of V. myrtillus and V. vitis-idaea return to their initial levels within five years of clear-felling (Palviainen et al., 2005). Calluna vulgaris, which seemed to benefit from logging residue removal in the South area, benefits from soil disturbance and it can occupy large areas (Granström, 1988; Nieppola, 1992; Balandier et al., 2006). C. vulgaris can inhibit the root growth of tree species, which has been observed to suppress forest regeneration (Mallik, 2003; Hyppönen et al., 2013).

4.3. Forest regeneration perspective

4.4. Management implications

The establishment of tree seedlings is negatively affected by competition with neighbouring vegetation (Nilsson and Örlander, 1999; Balandier et al., 2006; Pitt et al., 2010; Thiffault et al., 2013). Also, the early growth of planted tree seedlings may be affected by differences in plant secondary succession, since both the timing and duration of competition affect the establishment of tree seedlings (Wagner and Robinson, 2006). Betula spp. can easily overgrow planted conifer seedlings, fast-growing Deschampsia flexuosa competes both at root level for water and nutrients and at shoot level for light, and the aerial growth of

The energy wood harvesting treatments were rather similar in their effects on soil and vegetation, as the most pronounced differences were observed between the study areas. The official recommendations are leaving 25 stumps per hectare and 30% of logging residue at site, but the benefits of leaving some stumps were minor or non-existent on the soil disturbance and vegetation composition. However, potential increase in abundance of Betula spp. after stump removal may lead to an earlier need to tend the stands. Our results underscored the high site-dependency of the effects of stump removal treatments on ecological variables, thus initial

106 ± 105a 182 ± 182a 5.11 ± 4.2a 0 ± 0a

123 ± 66a 80.8 ± 76a 153 ± 55a 152 ± 110a

Central

125 ± 71a 87.3 ± 28a 169 ± 87a 187 ± 123a

North

stand structure and vegetation type need to be considered when planning harvesting treatments. However, because the present results cover only the four first years after treatments, more information is needed in order to understand the long-term consequences of stump removal on vegetation and its competing impact on the regeneration progress. Acknowledgements We thank Reijo Seppänen, Jorma Pasanen, Merjo Laine and Leila Korpela for their invaluable work, and other Metla personnel for participating in establishing the study sites, field and laboratory measurements. The anonymous referees gave invaluable comments in order to improve the paper. Supplementary material

B

Pairwise differences analysed separately for areas using lmer model, cubic root transformed data and block as random factor (N = 12). No pairwise tests. Populus tremula was found only in L treatment in the North area.

References

A

North

474 ± 53a 268 ± 223a 239 ± 117a 165 ± 132a 220 ± 135a 38 ± 38ab 27.2 ± 26ab 0.33 ± 0.3b

Central South

323 ± 53a 154 ± 89ab 92 ± 65b 143 ± 68ab 0.17 ± 0.17a 0.5 ± 0.5a 3.67 ± 3.5a 8.92 ± 7.2a

North Central

0 ± 0a 105 ± 105a 240 ± 233a 159 ± 153a

South

0 ± 0c 22.2 ± 22bc 188 ± 114ab 318 ± 191a

Vaccinium myrtillusA Calluna vulgarisA Treatment

F No L SLc

0 ± 0c 312 ± 109a 69.6 ± 57b 96.9 ± 50ab 0 ± 0b 484 ± 313a 341 ± 49a 444 ± 129a

South

Vaccinium vitis-idaeaA

North Central

0 ± 0b 158 ± 76a 287 ± 154a 79.9 ± 62a 0 ± 0a 15.3 ± 14a 13.5 ± 8.5a 51.4 ± 33a 0 ± 0b 370 ± 239a 43.3 ± 24ab 77.9 ± 59ab

South North Central South

0 ± 0a 5.11 ± 3.4a 91.9 ± 64a 30.6 ± 30.5a 11.7 ± 11.4a 12.2 ± 11.7a 16.6 ± 16.6a 38.9 ± 38.9a

North Central

0 ± 0a 6.33 ± 6.33a 23.6 ± 23.6a 2.00 ± 2.00a 0±0 0±0 0±0 42.7 ± 42.7

South North

161

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.foreco.2015.04. 001.

0.42 ± 0.42b 66.8 ± 61bab 96.4 ± 55ab 224 ± 115a 2.22 ± 1.2b 68.7 ± 46a 10.7 ± 6.6ab 43.7 ± 35ab

Epilobium angustifoliumA Rubus idaeusA

Central South

0 ± 0b 7.00 ± 7.0b 21.8 ± 14ab 62.2 ± 44a F No L SLc

B

Sorbus aucupariaA Betula spp.A Treatment

Table 3 Biomass (mean kg DW ha1) of plant species in 2012 at forest reference (F) and harvested (No, L, SLc) sites. Mean and standard error of original values are presented (N = 3). Significant (p > 0.05) pairwise differences between treatments are presented by letters a-c. The harvesting treatments were: No, no energy wood harvest; L, 70% logging residue removal; SLc, complete stump and logging residue removal.

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