No rapid soil carbon loss after a windthrow event in the High Tatra

Forest Ecology and Management 276 (2012) 239–246

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No rapid soil carbon loss after a windthrow event in the High Tatra Axel Don a,b,⇑, Manuela Bärwolff c, Karsten Kalbitz d, Rouven Andruschkewitsch e, Hermann F. Jungkunst b,f, Ernst-Detlef Schulze b a

Johann Heinrich von Thünen-Institute, Institute of Agricultural Climate Research, Braunschweig, Germany Max-Planck Institute for Biogeochemistry, Jena, Germany c Thuringian State Institute of Agriculture, Dornburg, Germany d Earth Surface Science, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, The Netherlands e Department of Environmental Chemistry, University of Kassel, Germany f Institute for Environmental Sciences, University of Koblenz-Landau, Germany b

a r t i c l e

i n f o

Article history: Received 10 January 2012 Received in revised form 23 March 2012 Accepted 6 April 2012 Available online 8 May 2012 Keywords: Windthrow Soil organic carbon Disturbance Forest floor Organic layer Minimum detectable difference

a b s t r a c t Windthrows are among the most important disturbances of forest ecosystems in Europe, with expected increasing frequency due to climate change. However, surprisingly little is known about soil carbon dynamics after windthrow mainly due to missing field assessments. After a large windthrow event in the High Tatra Mountains in 2004 three soil monitoring plots were established, one at a non-harvested windthrow left for natural succession, one at a harvested windthrow and one at a reference forest site which remained unaffected by the storm event. No loss in soil organic carbon (SOC) stocks was detected at the two windthrow sites with three inventories over the 3.5 years after the storm event. However, shifts within the organic layers and the mineral soil toward more decomposed organic matter were found. Increasing C/N ratios at the harvested windthrow site indicate that newly established herbaceous vegetation compensated the decline in tree litter input. At the non-harvested windthrow site a flush of needle litter from broken trees helped to sustain SOC stocks. In contrast, SOC stocks at the reference forest increased by 2.2 Mg ha1 year1 with major SOC stock accumulation in the forest floor. An assessment of the sample size required to detect future SOC changes revealed that at the windthrow sites a similar sample size is required as in the undisturbed reference forest. Small scale heterogeneity was at such a level that paired sampling did not significantly reduce the number of required samples. However, the separation of forest floor layers and mineral soil was a major obstacle for efficient forest soil carbon monitoring. The required number of soil samples could be decreased by 45% with a simultaneous sampling of forest floor and upper mineral soil, leading to more reliable SOC inventories. Ó 2012 Elsevier B.V. All rights reserved.

1. Introduction Storm events have caused large windthrows in forests during the last decades and their frequency is expected to increase with future climate change (Usbeck et al., 2010; Seidl et al., 2011). Storms are the most important natural disturbances to affect stand structure in Central Europe, with more than 130 storms significantly having damaged forests in Europe over the last 60 years (http://www.efiatlantic.efi.int/portal/databases/European_storms_ catalogue). Despite some speculation, a clear linkage with forest operations, species selection or site conditions has not yet been established (Gardiner et al., 2010; Van Miegroet and Olsson, 2011). Increased forest damage by windthrows has largely been attributed to increasing stand age and standing stocks throughout ⇑ Corresponding author at: Johann Heinrich von Thünen-Institute, Institute of Agricultural Climate Research, Braunschweig, Germany. Tel.: +49 531 596 2641; fax: +49 531 596 2645. E-mail address: [email protected] (A. Don). 0378-1127/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.foreco.2012.04.010

Europe (Seidl et al., 2011). Living biomass and their carbon sequestration capacity are temporarily lost with windthrows. Thus, the forest carbon sink is threatened not only by increasing maximum gust wind speed but also by increasing mean standing biomass stocks which make forests more susceptible to windthrow. A large storm event in Europe in 1999 reduced the carbon balance by about 16 million tons, which is 30% of the net biome production in Europe (Lindroth et al., 2009). Thus, the carbon sequestration potential of forests maybe overestimated if disturbances are not taken into account (Li et al., 2003). In temperate forests equally high carbon stocks can be found in biomass and soils. Given the importance of windthrows as natural disturbances, quantitative assessments on soil carbon dynamics after windthrow are surprisingly rare. Estimates mostly rely on modelled results and generally assume soil organic carbon (SOC) losses after windthrow (Thürig et al., 2005; Jandl et al., 2007; Lindroth et al., 2009). The famous study by Covington (1981) on a chronosequence after clear cut suggests a rapid 50% SOC loss from the forest floor within 20 years after disturbance, suggesting

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that windthrows may lead to enormous C losses. Forest floor carbon has been found to be most vulnerable, culminating in the hypothesis of ‘‘slow in, rapid out’’ (Körner, 2003; Jandl et al., 2007). However, the Covington study was challenged by Yanai et al. (2003a) indicating some methodological weaknesses and an over-interpretation with the papers reception. Only two out of ten similar clear cut studies found similarly strong SOC losses to Covington’s (Spielvogel et al., 2006). Chronosequence studies can always be confounded by the inter-site variability of soil type, micro climate or changes in harvesting techniques over the long time periods of a forest chronosequence. Real time series help to reduce these confounding factors. Compared to clear cuts, windthrows also include uprootings and can affect areas which are much larger than common clear cuts (Liechty et al., 1997). In order to enhance forest regeneration and due to high costs and risks of wood extractions from windthrows, some windthrow sites have been left for natural succession without any wood harvest (Jonášová et al., 2010). Wood harvest causes additional soil disturbances due to abrupt loss of canopy cover and the use of heavy machinery which may cause some mixing of the forest floor and the mineral soil. Post-windthrow management influences microclimate conditions, water balance and leaching, litter input, re-vegetation dynamics and species composition and subsequently the dynamics of SOC (Fischer et al., 2002; Huber et al., 2004; Kreutzweiser et al., 2008). However, there are no comprehensive studies determining SOC temporal dynamics after windthrow with different post-disturbance management. That might be due to the difficulties in accessing non-harvested windthrow sites, with uprooted trees laying criss-cross several meters high. The storm event Bora in November 2004 damaged more than 40,000 ha forests on the Southern slopes of the High Tatra Mountains in Slovakia. Around 2.5 Mio m3 wood suffered primary damage on a windthrow area of 12,600 ha. Some 100 ha windthrow were left untouched for natural succession whereas in most of the windthrow area wood was extracted. Thus, there was an opportunity to study the influence of windthrow and post-windthrow management on SOC dynamics. Our study aims at quantification of forest floor and upper mineral SOC changes after windthrow, elucidating the underlying processes. Additionally, sampling requirement to detect future SOC changes will be assessed.

2. Materials and methods 2.1. The three Tatra sites Windthrow is a common phenomenon in the High Tatra Mountains with moderate to severe windthrows being reported for

1850, 1915, 1919, 1941 and 1982. At the southern slopes of Tatra National Park (TANAP) a 50 km strip of forest was blown down in November 2004, uprooting most trees. Three research sites have been established which are managed in different ways: (i) windthrow area with all fallen trees and branches being extracted (EXT), (ii) windthrow area left non-harvested for natural succession (NEX) and (iii) an intact spruce forest as a reference site (REF). Each site covers an area of about 1 ha. All three sites are located on gentle slopes of 5–10% at an elevation of 1050–1200 m a.s.l. facing south to southeast. Mean annual temperatures are around 5 °C with 840–970 mm mean annual precipitation. Soils are characterised as Dystric Cambisols on glacial moraine deposits which covers large areas at the hillside toe of the High Tatra Mountains. Soil texture was loamy sand with pH values of around 3 (in KCl) in the upper mineral soil (Table 1). Similar soil type, texture and nutrient status has been found at all three sites except for a higher course fraction at the EXT site with a stone content of up to 75% in deeper soil horizons. This may explain generally lower SOC stocks of the forest floor and the mineral soil at the EXT site as compared to the NEX and REF site (Fig. 1). The forest floor at all three sites was mor type and up to 15 cm thick. The forests are dominated by Picea abies with an admixture of Larix decidua and Pinus sylvestris. Due to their location in the national park they have not been managed during the last decades. The REF site was covered by a 120 year-old stand and was rich in ground vegetation such as Vaccinium myrtillus, Calamagrostis villosa and Pleurozium schreberi. The sample points were covered by 51% with mosses and had a mean ground vegetation cover of 80%. The site was hardly affected by the storm event except for single uprooted trees. At the EXT site extensive herbaceous vegetation established, in particular C. villosa, C. arundinacea and Chamaenerion angustifolium, but the mosses and V. myrtillus almost disappeared. Mean ground vegetation coverage at the sample points was 50% (in 2008) with grasses being dominant (33% coverage). C. villosa abundance developed fast with 3% in the year directly after the windthrow (2005) to 68% (2005) and 86% (2006). C. angustifolium developed 1 year later with 3–4% in 2005 and 2006 and 38% in 2007 (Homolová et al., 2011). C. villosa and C. angustifolium together reached an above ground biomass of 4671 kg ha1, which is almost 100% of total biomass (Krizová et al., 2011). Ground vegetation at the NEX site was more abundant that at the EXT site with 74% average ground coverage (22% grasses, 11% V. myrtillus and 34% mosses; Inventory 2008). C. villosa abundance increased fast (3% in 2005, 68% in 2006), Avenella flexuosa showed peak abundance in 2007 (68% as compared to 8% in 2005 and 38% in 2008) and V. myrtillus only started to decrease in abundance in 2008 (Homolová et al., 2011). Total above ground biomass of C. villosa, V. myrtillus and C. angustifolium was 7244 kg ha1 in

Table 1 Soil characteristics of the three Tatra sites. Horizon [cm] Harvested windthrow (EXT) Ah 0–4 AhBw 4–16 BwAh 16–36 Non-harvested windthrow (NEX) Ah 0–7 AhBw 7–15 Bw 15–33 Reference forest (REF) Ah 0–3 AhBw 3–16 BwAh 16–31

Clay [%]

Silt [%]

Sand [%]

Stone content [%]

pH*

CEC [mmolc kg1]

BS [%]

15 16 13

27 28 28

58 56 59

60 65 70

3.4 3.8 4.1

103 70 40

7 9 14

9 9 4

25 24 26

66 67 70

<5 <5 <5

3.7 4.1 4.3

86 41 26

7 12 20

11 13 12

26 26 26

63 61 62

<5 <5 10–15

2.9 3.7 4.0

87 62 30

7 9 18

CEC, Cation exchange capacity; BS, Base saturation. pH measured in KCl extract.

*

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Micro-sites at the EXT site due to wheel traffic lanes from heavy harvesting machinery were excluded from sampling since they represented only a very minor fraction of the site. 2.2. Soil sampling and analysis Between 33 and 36 sampling points were established and marked at each of the three sites. Sampling points were located every 10 m along three transects which were oriented into East– West, North/North/West–South/South/East and North/North/ East–South/South/West directions, crossing each other at a central point of the plot. At the central point an eddy flux tower was installed. At each sampling point the organic layer (forest floor) and the mineral soil at 0–5 and 5–10 cm depth was sampled in June 2005 (after snow melt of the winter season with the windthrow event), May 2006 and June 2008. Samples of the three inventories were taken within a minimised distance of 20–50 cm from each other. The organic layer was divided into the Oi layer (almost undecomposed litter and detritus with branches and trunks not included), Oe (partially decomposed litter) and Oa layer (humified litter) using a metal frame of 25  25 cm. All samples were collected in plastic bags and dried at 70 °C until weight constant. The total mass of all samples from the organic layers was determined gravimetrically. Samples were chopped up using a cutting mill (SM 2000, Retsch, Germany) in order to homogenise the sample. Mineral soil samples were sieved through 2 mm and all samples were ground before analysis. C and N content was determined via dry combustion at 1100 °C (Vario Max for mineral soil) and 1150 °C (Vario EL for organic layers; both Elementar, Germany). In 2008, the bulk density of the mineral soil 0–5 and 5–10 cm was determined at 15 sampling points per site with three replicates. Cores with a standardised volume of 100 cm3 were used and samples were dried at 105 °C and subsequently weighed. The bulk density was calculated from the sample masses and the volume of the cores. Cold water extracts were prepared from a subset of 423 samples (dried material) covering 15 sample points for each site with the inventories from 2005 and 2008. Organic layer samples were mixed 1:10 (w/v) and mineral soil sample 1:2 (w/v) with distilled water, extracted for 24 h at 5 °C and filtered through a 0.45 lm pre-washed cellulose acetate membrane filter. Dissolved organic carbon (DOC) content was determined (Multi CN, Analytik Jena, Germany). Samples were diluted to 10 mg L1 and fluorescence spectra were recorded (SFM 25, BIO-TEK Kontron Instruments, Germany) to calculate a humification index HIX (Don and Kalbitz, 2005). This index is a measure for the degree of complexity of the organic compounds (McKnight et al., 2001). 2.3. Carbon stock calculations and minimal detectable difference

Fig. 1. SOC stocks of forest floor and upper mineral soil in 2005 (after the windthrow) and in 2006 and 2008. Significant differences in total SOC stocks are marked with different letters (mean ± standard error).

2009 (Krizová et al., 2011). At the NEX site uprooted trees lay criss-cross up to 10 m high, creating a mosaic of covered and noncovered patches. Surprisingly, most uprooted trees survived the windthrow for 2 years. Thus, a flush of needles from the fallen trees only occurred after 2006/2007. The EXT site was harvested during spring 2005 with trunks and branches extracted from the site.

Carbon stocks of the organic layers were calculated as a product from carbon concentration and dry matter mass in Mg ha1. For mineral soil, the carbon concentration was multiplied by the bulk density and the sampling depth to estimate SOC stocks per hectare. For the bulk density the available dataset from 2008 (n = 86) was used to derive a linear pedotransfer function with carbon concentration as input variable to estimate bulk densities for previous inventories in 2005 and 2006. Robustness of this function has been tested against constant bulk densities. The bulk density-soil carbon relation was assumed to remain unchanged for all three inventories. A power analysis was conducted in order to evaluate the sample design and its suitability to detect SOC stock changes. The required sample size n to detect a minimum detectable difference MDD of 15% SOC stock change in each layer and for the total soil has been calculates as

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n¼

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2r MDD2

ðt a;m þ t bð1Þ;m Þ;

with t a;m is the critical t-value of the normal distribution (two sided at a = 0.05:1.96) and t bð1Þ;m is the critical t-value of the normal distribution (two sided at b = 0.2:0.84) (Zar, 1984; Schöning et al., 2006). In order to assess the impact of a paired (same sample locations for each inventory) vs. non-paired (randomly distributed sample locations for each inventory) sampling design on MDD, two types of the variances r were used: (i) r of SOC stocks and (ii) r of the differences in SOC stocks between inventories at each sampling point. Since we did not detect any total SOC stock change, we calculated a mean required sample size using the following inventory pairs: 2005–2006, 2005–2008 and 2006–2008. The required sample size to detect a relative SOC stock change of 15% was calculated for each layer and depth increment and for total organic layer, total mineral soil and whole soil down to 10 cm depth. Semi-variograms have been calculated for total SOC stocks and each layer separately using the gstat package of the R software. Coordinates of each sampling point were estimated using GPS at the NEX site and total station with laser distance measure. Differences between sites (post-windthrow treatments) and the three inventories were assessed using a nested two way ANOVA with inventory year and site as factors followed by a Tukey HSD test using JMP software. 3. Results 3.1. SOC stock changes in the forest floor and mineral soil No significant changes in total SOC stocks were detected down to 10 cm depth of the mineral soil at both windthrow sites within

3.5 years after the windthrow (Fig. 1). However, carbon was transformed and shifted between the different layers of forest floor and between forest floor and mineral soil. At the EXT site, SOC of the Oi and Oe layer (6.3 Mg C ha1) was transformed after the windthrow to more decomposed SOC of the Oa layer and the upper mineral soil (together +6.8 Mg ha1). The largest SOC loss at this site occurred in the litter layer (Oi) with 42% (Fig. 2). In contrast, at the NEX site the litter layer was hardly depleted (1.0 Mg C ha1, 15%). However, SOC at the NEX site was lost from the Oe layer (12.1 Mg C ha1) but was transformed to humified litter of the Oa layer and upper mineral soil 0–5 cm depth (+11.6 Mg C ha1). The REF site was almost unaffected by the storm event in 2004 and served as a control plot for the two windthrow sites. Whereas at the two windthrow sites total SOC stocks remained constant, additional 6.5 ± 4.8 Mg ha1 SOC accumulated at the REF forest within 3 years, which was a significant SOC stock change. This is a sequestration rate of 2.2 Mg C ha1 year1. Thus, 2.0 and 2.8 Mg C ha1 year1 are missing at the EXT and NEX sites respectively, as compared to the reference forest. However, this comparison may be confounded by inter-site variability. Accumulation of SOC at the REF site mainly took place in the litter layer (+2.4 Mg C ha1) which increased by 63%. Similar to the windthrow sites, a transformation of SOC from the Oe layers to the Oa layer was observed (Fig. 2). In the inventory in 2006, Oa SOC stocks seem to be decreased in favour of increased upper mineral SOC stocks at all three sites. These fluctuations might be the result of the well known problem of separating forest floor and mineral soil (Jansen et al., 2005). Sampling in 2006 was conducted under higher soil moisture conditions as compared to 2005 which could influence the classification of different organic layers. No significant changes were detected at any of the three sites in the mineral soil 5–10 cm depth, indicating

Fig. 2. SOC stock changes (left) and C/N ratio changes (right) at two windthrow sites (EXT, NEX) and an undisturbed reference forest (REF) for three organic layers (Oi, Oe, Oa) and the upper mineral soil (Ah 0–5 and Ah 5–10 cm depth) within 3 years after the windthrow event. Significant changes are marked with ⁄ (mean ± standard error).

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relative stability of mineral soil SOC and no sampling bias for this soil depth increment. Thus, sampling down to 10 cm soil depth with two separated mineral soil depth increments insured that sampling errors due to separation of organic layer and mineral soil cancel each other out for the total SOC stocks. There was a significant positive correlation between ground vegetation cover and SOC changes (2005–2008) of the organic layer of the NEX site (R2 = 0.55, p = 0.004). Also the revegetation of certain single plant species and types, such as C. angustifolium and mosses, showed significant positive correlations with changes of SOC of the forest floor or their layers indicating a contribution of the ground vegetation to maintain SOC in the organic layer. However, no such significant correlations were found for the EXT site suggesting that vegetation cover may also be able to enhance decomposition due to shading at the sun exposed EXT site, which was prone to fast drying during summer season.. 3.2. Organic matter quality At all three sites strong gradient of the C/N ratio has been detected with the highest values in the litter layer and the lowest in the mineral soil (Fig 3). The strongest change over time in the C/N ratio occurred in the Oi litter layer of the REF site, indicating a large input of fresh needle litter (Fig. 2). That is in line with the increase in SOC stocks in this layer. In the Oe and Oa layer and the mineral soil of the EXT and REF site a slight increase in the C/N ratio of between +1.1 and +2.1 has been detected indicating enhanced C input in these layers and horizons. At the NEX site no significant changes were detected at any layer or depth increment. Characteristics of soil water extracts are sensitive parameters for quality changes in SOC (Kaiser and Guggenberger, 2000; Kalbitz et al., 2005; Sanderman et al., 2008). The dissolved organic carbon (DOC) concentrations (cold water extract) decreased continuously with depth from 1500 mg L1 in the Oi to 375 mg L1 in the mineral soil at 5–10 cm depth (data not shown). The water extractable carbon fraction comprised on average between 1.1 and 4.0%, with the most soluble carbon in the Oi and the Oa layer (Fig. 3). There was no significant difference in DOC concentrations and water extractable carbon fraction between prior and post windthrow (inventories 2005 and 2008) and between the three sites. The humification index HIX has been determined from fluorescence spectra of water extracts (Don and Kalbitz, 2005). The HIX significantly increased with increasing depth, following an opposite trend as the C/N ratio (Fig. 3). Both variables have been highly correlated (R2 = 0.65) and no significant differences in HIX between the three sites and the inventories 2005 and 2008 could be detected. 3.3. Variability analysis–implications for detecting future soil carbon changes Detecting SOC stock changes is challenging due to the high field variability in particular of the forest floor. In order to quantify the

Fig. 4. Required sample size to detect a relative SOC stock change of 15% in different layers and depth increments and of the sum of forest floor, the sum of mineral soil and the sum of all layers and mineral soil depth increments (‘‘all’’) assuming a paired sampling (above) and a random, non-paired sampling (below) (mean of three inventories ± standard error).

appropriateness of the applied sampling design to detect SOC changes we conducted a power analysis. The number of required samples depends on the specific site variance of SOC stocks and. is expected to decrease with a paired plot design (Yanai et al., 2003b). However, we found slightly decreasing required sample sizes with paired plots only for the total SOC stocks but not for single layers or horizons (Fig. 4). At the windthrow sites, 33 and 25 sample points would be needed at the EXT and NEX site, respectively, to significantly detect a SOC stock change of 15%. Surprisingly, also on the non-disturbed REF site a similarly high sample size of 25 is required to detect a 15% SOC stock change. Thus, our sampling design with 33–36 sample points on each site would allow detection of a change of between 6% and 13% SOC stock change with a repeated inventory. This is equal to a SOC stock change of 7, 14 and 6 Mg ha1 at the EXT, NEX and REF site, respectively. Semi-variograms revealed that there was no spatial correlation between neighbouring sample sites (P10 m distance, Fig. 5). Also for single layers or depth increments, spatial correlations were missing (data not shown), indicating that small scale heterogeneity (<10 m) was equally high as site scale heterogeneity. Therefore, paired sampling did not increase the statistical power as compared to random sampling.

Fig. 3. Profiles of soil C/N ratio, water extractable carbon fraction [%] and humification index HIX from water extracts for the two windthrow sites (EXT, NEX) and the reference forest (REF) (mean ± standard error).

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Fig. 5. Semi-variogram of SOC stocks forest floor plus upper mineral soil for the two windthrow sites (EXT and NEX) and the undisturbed forest (REF).

The highest variability was always found in the Oe and Oa layers of all three sites due to their transitional character between pure organic matter and mineral soil. Between 199 and 349 samples would be required to detect a 15% change separately for an Oe or Oa layer. 65–90% of the variability in the organic layers is derived from differences in accumulated mass and not from variability in carbon concentrations. In the Oi layer, the coefficient of variation (CV) of the carbon concentration was only 4–9% as compared to a 36–47% CV of the litter mass. Additionally, the Oa layer was too thin (<1 cm) at some points to be sampled separately but was sampled together with the Oe layer. This introduced additional variability. Sampling of the forest floor and upper mineral soil at the same sampling point was an efficient way to reduce variability (Fig. 4). The two additional mineral soil samples per sampling point lead to a three times lower required sample size to detect the same total SOC stock change, ending up with 43–48% fewer required soil samples as compared to sampling the organic layer only. 4. Discussion 4.1. Balance of litter input and decomposition determine SOC stock changes Disturbances like clear cuts and windthrows may cause SOC losses, especially in the organic layer (Covington, 1981; Heinsdorf et al., 1986; Brais et al., 1995; Kramer et al., 2004; Pang et al., 2011). However, several studies found also SOC increases (Hendrickson et al., 1989; Mattson and Swank, 1989) or did not detect significant changes after clear cut (Huntington and Ryan, 1990). SOC dynamics on windthrow sites may only be similar to clear cuts if broken trees are harvested and soil disturbances by uprootings are minor. We detected no significant change in SOC stocks including forest floor at the Tatra windthrow sites (Fig. 1). However, we found the upper litter layer (Oi and Oe) transformed by humification and decomposition processes into the humified forest floor layer (Oa) and into mineral soil SOC. The SOC stock changes on windthrow areas could be derived from accelerated decomposition due to changes in micro-climatic conditions when tree cover is removed, or due to changes in litter input and quality from newly sprouting ground vegetation and re-growing trees.

Soil temperature (10 cm depth, continuous measurements) increased by 4 °C at the two windthrow sites as compared to the REF forest during summer season (Mayer, 2008). Increased temperature may stimulate microbial activity and result in higher decomposition rates (Hyvönen et al., 2005). However, soil moisture may become a limiting factor during the summer season in the forest floor, which reduces the decomposition. Decreasing C/N ratios after disturbance have been used as indicators for accelerated decomposition (Spielvogel et al., 2006). However, we did not find such decrease, which underlines the low degree of disruption to the soil SOC balance by the Tatra windthrow. Windthrows are characterised by a sudden large organic C input into the forest floor in the form of coarse woody debris and litter followed by an abrupt decline in tree litter fall (Hagedorn, in press). An estimated 6.8 Mg C ha1 was added as needles to the forest floor at the NEX site after the windthrow, which is around 4–6 times as much as normal annual needle litter input (needle C mass was calculated using the biomass expansion factors by Wirth et al. (2003) based a tree biomass of 248 m3 ha1 measured at the REF site (Seben et al., 2011)). However, this additional carbon was not detected as additional forest floor SOC but was possibly decomposed rapidly. Only a comparison between the windthrow sites and the undisturbed reference forest revealed relative SOC stock losses due to the windthrow, only because of increasing SOC stocks at the reference forest. This divergence between the time series and the paired plot approach can not be solved without better knowledge of the year-to-year fluctuations of forest floor SOC stocks (see REF site SOC stock increases in 2008) and on the impact of small differences in environmental conditions between paired sites on SOC dynamics. Even though the three sites were selected carefully, a higher stone content at the EXT site maybe responsible for in general smaller SOC stocks as compared to REF and NEX site (Fig. 1). 4.2. Soil carbon dynamics on the windthrow with two harvest treatments From the ecosystem scale perspective the carbon balance of windthrow sites is dominated by the decomposition of coarse woody debris (Knohl et al., 2002). Conceptually, fallen trees belong to the organic layer but have not been accounted for in our inventories. We investigated the effects of complete harvest vs. non-harvest of broken trees but did not find any significant difference in SOC dynamics 3.5 years after the windthrow (Fig. 1). At the NEX site the fallen trees were left for natural succession and may contribute to SOC build-up on the long-term. However, most trunks were without soil contact, which significantly hampers decomposition. The incorporation of woody debris into the soil will probably take decades after the windthrow event, with long-term SOC stocks benefiting from non-harvesting. Forest floor SOC has been found to be most vulnerable with fastest SOC loss directly after the disturbance. At two Podzol chronosequences in Eastern Germany, 14–16% SOC loss was detected after clear cut in the forest floor and 0–40 cm mineral soil within 3.5 years – the time range of our study (Heinsdorf et al., 1986). Around 26% forest floor SOC loss within 3.5 years after clear cut and whole tree harvest has been reported from the Southern Appalachian Mountains by Mattson and Swank (1989). A forest floor loss of 42–71% within 3 years after clear cut of northern hardwood forests (Michigan) with different nutrient status underlines the susceptibility of the forest floor to disturbances (Mroz et al., 1985). Significant short term SOC losses (<1 year) were found in tropical forests in Mexico after hurricane Wilma (Vargas et al., 2010). SOC decline was mainly restricted to the Oi and Oe layer with no change in the fine (<2 mm) SOC pool. In contrast, forest floor SOC stocks at the Tatra windthrow sites were not affected by the windthrow. Even

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the complete removal of above ground biomass of fallen trees and needle litter at the EXT site did not significantly reduce forest floor SOC as compared to the NEX site where trees were left for natural succession. Two reasons which may explain these findings are (i) the soil type with low pH values and a high sand content provides sub-optimal living conditions for decomposers (Table 1). Additionally, long winter seasons are succeeded by hot summers which desiccate soils quickly, in particular at the EXT site and in the forest floor, imposing limitations on decomposer activity and detaining a fast SOC loss, and (ii) re-vegetation was fast and dominated by grasses and herbaceous vegetation. C. villosa as most abundant species increased from 3% to 68% abundance from the first to the second year after the windthrow (see material and methods section). Three years after clear cutting 30% increased SOC stock were found in the organic layer at Hubbard Brook experimental forest and attributed to organic-C input from slash residues from harvest (Johnson et al., 1995). SOC stocks at the EXT site may have similarly benefited from harvest residues. Thus, declined organic C-input from needle litter after windthrow was at least partly compensated by root and leaf litter from ground vegetation and some harvest residues at the EXT site. In contrast, mineral soil SOC seems to be hardly affected by disturbance (Fig. 2). A meta-analysis concluded that forest harvesting has little or no effect on mineral soil C and N (Johnson and Curtis, 2001). Only long term effects of disturbances may be significant for mineral soil SOC stocks. Illuviation and mixing of mineral soil and forest floor was found especially relevant for windthrow sites with repeated disturbances (Kramer et al., 2004) and may explain the noticed missing podzolisation at the investigated three Tatra sites (Johnson et al., 1987). 4.3. Implications for forest carbon monitoring Most studies on forest floor dynamics are not able to detect a forest floor SOC change of 20% due to insufficient sampling size (Yanai et al., 2003b). A paired sampling design is proposed to increase the statistical power of repeated inventories. However, at the three Tatra sites this effect was marginal or resulted in opposite effects (Fig. 4). Surprisingly, a spatial correlation between sample points was completely missing at all three sites (Fig. 5). There was also only small temporal correlation (R2: 0.40, 0.03, 0.53 for EXT, NEX and IF site, respectively for 2005 vs. 2008 inventories) underlining the dominance of small scale variability at the decimetre scale of forest floor and mineral soil SOC. Spatial heterogeneity of SOC was hardly affected by windthrow except for pits from uprooted trees and the wheel traffic lanes that have been excluded from sampling. Pits and mounds at the Tatra windthrow EXT site were found to cover only a small surface fraction of 5% (Rojan, 2011). Moreover, at the EXT site the root plates have been moved back into the pits, which further reduced their impact on total SOC dynamics. However, we cannot preclude that higher SOC losses at these partial areas may have occurred that may influence the total SOC balance. Including pits and vehicle tracks as directly disturbed areas in the sampling grid would have drastically increased the sample size demand due to the increased variability. The difficulty in separating forest floor from mineral soil and the distinction of three organic layers additionally increases the variability (Jansen et al., 2005). There is a continuous transition between upper mineral soil and the Oa layer of the forest floor with a steep carbon gradient exactly at the defined border between forest floor and mineral soil at 20% organic carbon concentration (FAO, 1988). Thus, any small deviation from this border may cause large biases in the SOC stocks of forest floor and mineral soil. About 26% of the Oa samples contained less than 20% C. For combined forest floor layers and upper mineral soil sampling (0–10 cm depth), the required sampling size to detect SOC changes could be

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decreased by more than 50%. Moreover, sampling becomes more robust towards changes in staff that conducts the sampling and possible mixing of mineral soil and organic layers due to the disturbance (Huntington and Ryan, 1990; Kramer et al., 2004). The chronosequence study by Covington (1981) reporting large SOC losses after a clear cut had been re-sampled (Yanai et al., 2003a). The reassessments showed that the apparent forest floor loss can be mostly attributed to mixing of forest floor with mineral soil, which is not captured by forest floor sampling only. Thus, forest floor SOC monitoring can be improved with a revised sampling design that includes upper mineral soil sampling for forest floor assessments. 5. Conclusions SOC stocks have remained surprisingly stable after the windthrow event at the High Tatra, indicating low short-term vulnerability of forest floor and upper mineral soil SOC at these sites. Declined tree litter inputs may be compensated by root and leaf litter from the newly established herbaceous vegetation and harvest residues at the EXT site. Thus, SOC losses may be not in line with biomass carbon losses after disturbances, but react more resistantly to disturbances. The failure to detect significant SOC stock changes can not be attributed to an insufficient sampling size. With the high number of sample points per site even small SOC stock changes of 6–13% could have been detected. However, small scale variability of SOC was just as high as site scale variability. Under these conditions paired sampling cannot be recommended, since it does not increase the statistical power and imposes a higher risk of disturbances to the sampling point from previous samplings as compared to non-paired, random sampling. An adequate sampling of mor type forest floor is hampered by its difficult separation from the mineral soil. We propose to combine forest floor sampling with sampling of the upper mineral soil at the same sample point in order to account for the transient character of the Oa layer and upper mineral soil horizon. Forest floor sampling alone may easily become biased particularly at disturbed sites and may result in misleading conclusions. Acknowledgements We are grateful to Peter Fleischer for facilitating the establishment of the research sites at TANAP. We thank Ines Hilke and Birgit Fröhlich for sample analysis and send many thanks to Waldemar Ziegler and all colleagues who helped with the soil inventories in the field. References Brais, S., Camire, C., Pare, D., 1995. Impacts of whole-tree harvesting and winter windrowing on soil-pH and base status of clayey sites of Northwestern Quebec. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 25, 997–1007. Covington, W.W., 1981. Changes in forest floor organic-matter and nutrient content following clear cutting in Northern Hardwoods. Ecology 62, 41–48. Don, A., Kalbitz, K., 2005. Amounts and degradability of dissolved organic carbon from foliar litter at different decomposition stages. Soil Biology & Biochemistry 37, 2171–2179. FAO, 1988. FAO/Unesco soil map of the world revised legend with corrections and updates. In: FAO (Ed.), Wold Soil Resources Report. FAO, Rome. Fischer, A., Lindner, M., Abs, C., Lasch, P., 2002. Vegetation dynamics in central European forest ecosystems (near-natural as well as managed) after storm events. Folia Geobotanica 37, 17–32. Gardiner, B., Blennow, K., Carnus, J.-M., Fleischer, P., Ingemarson, F., Landmann, G., Lindner, M., Marzano, M., Nicoll, B., Orazio, C., Peyron, J.-L., Reviron, M.-P., Schelhaas, M.-J., Schuck, A., Spielmann, M., Usbeck, T., 2010. Destructive storms in European forests: past and forthcoming impacts. In: Final Report to European Commission–DG Environment. EFI, Brusssels. Hagedorn, F., in press. Windthrow effects on soil carbon.

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