Relation between the age of managed heathland communities and C and N mineralization at different soil depths

(1)

Relation between the age of managed heathland

communities and C and N mineralization at different soil

depths

Bsc Thesis Earth Sciences

Marleen van Dusseldorp Student number: 10069534

University of Amsterdam Supervisor: Albert Tietema

June 2015

Abstract

The Dutch heathlands originate from traditional agriculture practices that include forest cutting, stock grazing, sod-cutting and harvesting vegetation in a 3-5 years cycle to yield winter fodder for the cattle. Cutting the vegetation and grazing prevented the establishment of forests. As traditional land

management is very labor intensive, cutting and burning of heathland is nowadays performed with in irregular time intervals. This research will study C and N mineralization in managed heathland

communities in Oldebroek. This specific heathland area is mowed in a series of different time intervals creating an area with heathland plots of four different ages: 3, 15, 22 and 31 years. This

(2)

Samples from different soil depths are analyzed to examine whether the different mowing cycles influences the vertical distribution of C and N mineralization rates. To achieve this, soil samples were taken to the lab where NH4 and NO3 content and mineralization rates were determined from these soil samples. Additionally, CO2 accumulation was measured to obtain mineralization rates. Significant differences in carbon mineralization rates were found in various depths between the four age communities. For the nitrogen mineralization, only significant differences between the age

communities were found at 5-10 cm depth. No significant differences between the age communities were found in nitrification rates.

Keywords: mineralization, heathland, nitrogen cycle, respiration

Table of Content

Introduction p. 3

Methods p. 5

Sampling p. 5

Lab analysis p. 6

Calculations & Statistical analysis p. 7

Results p. 8 Carbon p. 8 Nitrogen p. 12 Discussion p. 15 Conclusions p. 16 Acknowledgements p. 17 References p. 17 Appendices p. 20

A. Kruskal-Wallis per community p. 20 B. Kruskal-Wallis per layer p. 23 C. NH4 + NO3 before/after incubation p. 32 D. Raw data Auto Analyzer p. 38 E. Raw data Gas Chromatograph p. 43

(3)

Introduction

The origin of most European heathlands, including those in the Netherlands, is dominated by forest cutting followed by stock grazing, sod cutting, and harvesting of vegetation in a 3-5 years cycle to yield winter fodder for the cattle. The obtained sods were used to create arable land. The remainder soils after nutrient rich sods removal transformed into nutrient poor areas with heathland shrubs as the main vegetation. The repetitive cutting and grazing of vegetation prevented the development of forests (Webb, 1998).

Between 1990 and 2006 the surface area in Europe covered by Calluna and Scelerophyllous vegetation has declined by 2682 km2_{(European Environment Agency, 2010). As the traditional} management practices have stopped, intensive land management is required to preserve the

heathland areas that are left and prevent the development of forests. Other factors that can influence the loss of heathland areas are the anthropogenic impacts: climate change, agricultural policies and nitrogen pollution (Vandewalle et al., 2010).

As the heathland flora and fauna is threatened, extensive research is conducted on conservation and management of the heathland areas. One example is the research done by Kopittke et al. (2012) on the effects of anthropogenic disturbances on carbon (C) and nitrogen (N) cycles. That study focused on cyclical vegetation removal, elevated N deposition and a drought treatment (simulating predicted consequences of climate change). The emphasis of the subsequent research by Kopitke et al. (2012) was on the overall changes in these cycles due to climate change and cutting cycles. Kopittke et al. (2012) looked at the effects of different aged heathland communities on biomass and carbon stocks based on three heathland plots that were aged 12 (‘Young’), 18 (‘Middle’) and 28 (‘Old’) years. The results of that study showed that above ground biomass differed significantly between the Young, the Middle and the Old community. This is explained by the growth cycle of Calluna plants (figure 1).

Figure 1: Above-gound Calluna Biomass (kg/m2_{) for the different aged communities from year 1998 to 2011.The middle} community is measured over time, the young and old community in 2011, with the dotted line reflected back in time to compare with the development ages of the old community. From: (Kopittke et al. 2012).

Results of the same study show that the mean thickness of the organic layer of the Middle

community was lower than that of the Young and Old community. This was suggested to be the result of ploughing, causing soil layers to mix. A non-linear relationship between the bulk density and carbon concentrations was found. The organic layer had the lowest bulk density and the highest soil organic carbon (SOC) concentration. With depth, bulk density increased and SOC concentration decreased (figure 2). The bulk density of the organic layer at 0-5 cm depth was measured to be significantly lower at the Middle community compared to the Young and Old community. The study suggested that this lower density in the organic layer of the Middle community indicated that the

(4)

deposition of the material was more recent and, therefore, less decomposed. However, a comparison of total C stocks for both the organic layer and the mineral layers up to 10 cm, did not yield a

significant difference between the different age communities.

Figure 2: Bulk density in g/cm3_{indicated with the black lines, and C % per soil depth indicated with the grey lines. From} Kopittke et al. (2012).

Where this previous study by Kopittke et al. (2012) examined the total carbon stocks, others have studied the effect of nitrogen transformations along a successional gradient from heathland to forest (Kristensen and Hendriksen, 1998) or nitrogen mineralization and organic matter (OM) accumulation for different heathland ages (Berendse, 1990). A study on the effects of both the heathland age and vertical mineralization rates of carbon and nitrogen has not been performed yet. The purpose of this research is to provide more detail on how the respiration and mineralization rates differ both per layer and per age community. More examination is done on the vertical distribution of C and N mineralization rates of regions subjected to heathland cutting in different cycles. Samples will be taken at the same heathland area in Oldebroek as used in research of Kopittke et al. (2012), where the main vegetation is Calluna vulgaris. Regions of this heathland area are cut in different time intervals causing a chronosequence of 3, 15, 22, and 31 years respectively. This provides an opportunity to study the following research question:

“How does the age of managed heathland communities influence the vertical distribution of nitrogen and carbon mineralization?”

Given the study by Kopittke et al. (2012) it is hypothesized in this research that the carbon and nitrogen mineralization will be maximal in the organic layer at 0-2 cm and 2-5 cm depth where C and OM content is highest and significantly smaller in the 5-10 cm mineral layer. Additionally, the OM of the upper 0-2 cm and 2-5 cm layer is expected be of a different quality that may result in a faster or slower decomposition by microbial biomass. As part of the topsoil, these upper layers are expected to have been deposited more recently and decompose more easily. Because more lignin content was found in the OM of the ‘Old’ community in the previous study of Kopittke et al. (2012),

decomposition rates are hypothesized to be slower here and thus lower mineralization rates are expected. Lastly, it is hypothesized that the Middle community will not have significant differences in mineralization rates between the upper two layers (0-2 and 2-5 cm) because the material is expected to be homogenized due to ploughing (Kopittke et al., 2012).

(5)

Soil sampling

Soil samples are collected from the four different age communities in Oldebroek (figure 3). Six soil cores from 10cm depth are taken from every age community at randomly chosen locations within the communities. To sample the cores, a PVC pipe with a diameter of 4.3 cm was hammered in the ground to obtain an intact soil core. Hereafter, these soil cores were cut into three slices at

respectively 0-2 cm depth, 2-5 cm, and 5-10 cm depth. This resulted in a total of 4 (age communities) x 6 (sample locations) x 3 (depths) = 72 soil samples.

Figure 3: a) The site at Oldebroek with the four age communities: three large plots for the Young, Middle, and Old community and 6 smaller plots for the youngest plots of 3 years old. The red dots indicate soil sample cores sites. Long-term manipulation plots are indicated with a squared polygon: no samples were taken inside these plots. b) Sample location within an age community, each red dot represents a soil core. c) Profile of a soil core, sliced in three separate samples. Figure modified from Kopittke et al. (2012).

The sample analyses requires approximately 14 grams of the organic material and 40 grams of mineral material. For this reason, several sample cores per location were required to obtain sufficient material for analysis. These cores were taken from a very small area to minimize spatial variability and the samples were mixed per depth layer. Because the 0-2 cm layer consists mostly of organic material and litter and the 2-5 cm and 5-10 cm mostly of mineral soil, there is a difference in bulk density and weight. For the mineral layer, 8 samples per location were required to provide sufficient material. Thus, for the mineral layers 6 locations x 8 samples = 48 soil cores per age community were required. Due to the low bulk density of the upper 0-2 cm, 20 samples per location were needed for this layer. Thus, 6 locations x 20 samples = 120 samples from the upper 0-2 cm layer were required per age community (figure 3).

Lab analysis of the data

After the soil samples are collected, analyses on NO3 and NH4 content were conducted in the lab at the Faculty of Science, University of Amsterdam. To determine the mineralization rate, halve of the samples were analyzed right after sampling, while the other half after 7 days of incubation.

Additionally some samples were used for moisture content and carbon mineralization analyses.

Nitrate transformation

The source of organic N is organic matter such as plant litter, dead animal remains or excrements. This is converted by microorganisms to ammonium (Alef & Kleiner, 1986):

RNH2 + H2O + H+ ↔ ROH + NH4+

NH4 can be converted to NO2 and NO3 by oxidation, which is called nitritation and nitratation respectively (Buday et al., 2000). This conversion to is done through mineralization:

(6)

NH4 + 2O2 → NO3 + H2O + 2H+

Mineralization depends on microbial respiration, microbial biomass, temperature, water content, oxygen availability and C/N ratio, amongst other factors (Bengtsson et al., 2003). Effects of the nitritation process on mineralization will be neglected based on the assumption that the conversion of nitrite to nitrate is so fast that the process of nitritation is inefficient, and only NO3 will be measured.

As described above, the nitrogen cycle consist of several steps. Because nitrogen mineralization to ammonium coincides with nitrification, where ammonium is converted nitrate, all these compounds will be measured at the same time.

Nitrogen extraction

Nitrogen measurement will be done similar as by Tietema et al. (1992a). After sampling, samples were stored at a low temperature (2 ˚C) to stop the microbial activity. To re-initiate the microbial activity, the samples were subjected to room temperature for two days. To investigate the rate of carbon and nitrogen mineralization, NH4 and NO3 were measured before and after an incubation period of 7 days with a flow-injection Auto Analyzer (AA). The net mineralization is determined after sieving (remove gravel and roots by hand), mixing to homogeneity, and extracting the soil samples in 0.05 M L-1_K

2SO4 solution for analysis of NH4 and NO3 contents. This extraction is done with 3 grams of the organic layer (0-2 cm). For the samples from the mineral layer (the lower 2-5 cm and 5-10cm), 10 grams of the samples is used. To these samples 40 ml of the 0.05 M L-1_K

2SO4 solution is added giving the soil to liquid ratios of approximately 1:13 and 1:4. Thereafter the filtrate is filtered through a membrane (Whatman, poresize: 0.45 µm) through a vacuum system, to get a filtered extraction for analysis on the Auto Analyzer.

Carbon measurements

Organic matter is decomposed and converted to CO2 again by micro organisms (heterotrophic respiration): C6H12O6 + 6O2 ---> 6H2O + 6CO2 + energy

This heterotrophic respiration is also called carbon mineralization and will be determined by measuring the amount of CO2 at the first day and at day three using the Gas Chromatograph (GC). This analysis is performed by placing 3 grams of organic samples and 10 grams of mineral samples in a 20ml glass jar and adding demi-water to equalize moisture content for the different layers. After closing the jars, 6 ml of lab air was injected in these jars to a sufficient pressure for the GC to perform two measurements.

In absence of oxygen, anaerobic processes by micro-organisms will transform organic matter in CO2 and methane CH4 by: C6H12O6 ---> 3CH4 + 3CO2. In analogue to nitrogen, the assumption will be made that there is enough oxygen available in the jars to assume that the amount of CH4 is negligible. Methane is measured with the GC to validate this assumption.

Calculations and statistical analysis

The amount of NH4 and NO3 measured before and after incubation will provide insight in the net N

mineralization and nitrification rate in mg N kg-1_{over the time span of the incubation. These rates are}

calculated by the formula

Net N mineralization = (NH4 (t7)-NH4 (t0)) + (NO3 (t7) -NO3 (t0))

and

Nitrification = (NO3 (t7) -NO3 (t0)),

(7)

For carbon, the change in the amount of CO2 will be measured over the time span of three days. This

will tell us about the decomposition of carbon over time, as CO2 is the indicator of respiration by

microbes. The amount of C in mg C kg-1 _day-1_{converted to CO}

2 over time is calculated.

As a first step in the statistical analysis, the data is checked for outliers. This is done by measuring the 1st and 3rd Quartile and IQR and thereby measuring the upper and lower boundary for values. All values outside these boundaries are removed from the dataset.

The Kruskal-Wallis test (as an integral function in Matlab 2011b) is used to test the significance of the different outcomes between the age communities. A P-value of less than 0.05 is considered a

significant difference (Tietema et al., 1992a). A first reason to apply the Kruskal-Wallis test is that the variability in measurements is very high. The second reason for using the Kruskal-Wallis test is that the data size varies between the populations after outlier removal: in some groups no outlier had to be removed, in others two or more. After the Kruskal-Wallis test, a multi-comparison test is used to determine which groups differ significantly from each other.

Results

In this section, the data obtained by the Gas Chromatograph and Auto Analyzer are presented graphically. The raw data can be find in the appendices D and E. The results considering carbon and nitrogen are presented separately. For both substances, first the mineralization rates for the different age communities per layer are provided, followed by a trend analysis with the outcomes of the Kruskal-Wallis tests and, finally, the mineralization rates per m2_{to determine if there is spatial} variability between the age communities.

Carbon

Figure 4: The trend line of the measured CO2 values with the Gas Chromatograph (GC) from the 6 sample locations per age community. The first point is the atmospheric concentration when the jars with soil samples were closed. The first cluster of points is the GC measurement during day 1, the second cluster during day 3.

Figure 4 shows the distribution of the carbon over time. From r2, it can be seen that the variability in measurements differs per age community and per layer. For points that seem inconsistent with the linear trend, the Inter Quartile Range (IQR) is calculated to determine if they should be classified as outliers. Only two outliers were found and have been removed from the dataset (highlighted with the red circle in figure 4). The remaining data is used to calculate the net carbon mineralization over the three day measurement period (figure 5).

(8)

Figure 5: Measured carbon mineralization in mg C kg-1_{OM over a three day period for the different age communities at} three soil layer depths: 0-2 cm, 2-5 cm and 5-10 cm.

Figure 5 displays the carbon mineralization rate over a 3 day period. This rate is calculated by

subtracting the concentration on day 1 from the concentration on day 3 for the four age communities at the three layer depths. Per depth a Kruskal-Wallis test is used to determine whether the

communities differ significantly from each other.

Test Layer Depth Significant differences

between communities P-value Carbon mineralization 0-2 cm Pioneer - Middle

Young - Middle 0.0032

Carbon mineralization 2-5 cm Young - Old 0.0006

Carbon mineralization 5-10 cm Pioneer - Middle

Young - Middle 0.0011 Carbon mineralization per m2 0-2 cm Pioneer - Middle Young - Middle 0.0028 Carbon mineralization

per m2 2-5 cm Young - Old 0.0012

Carbon mineralization per m2 5-10 cm Pioneer - Middle Young - Middle 0.0019 NH4 content before incubation 0-2 cm Pioneer - Middle Young - Middle 0.0042 NH4 content before incubation 2-5 cm Pioneer - Middle Young - Middle 0.0018 NH4 content before incubation 5-10 cm Pioneer - Middle Young - Middle 0.0021

NH4 content after incubation 0-2 cm Pioneer - Middle 0.0133

NH4 content after incubation 2-5 cm Pioneer - Middle

NH4 content after incubation 5-10 cm

Pioneer - Middle

Nitrogen mineralization 0-2 cm No 0.0357

Nitrogen mineralization 2-5 cm No 0.0841

Nitrogen mineralization 5-10 cm Young - Middle

Young - Old 0.0016

(9)

m2

Nitrogen mineralization per

m2 2-5 cm No 0.1008

Nitrogen mineralization per

m2 5-10 cm Young - Middle 0.0006 NO3 content before incubation 0-2 cm Pioneer - Middle Young - Middle 0.0102 NO3 content before incubation 2-5 cm No 0.0747 NO3 content before incubation 5-10 cm No 0.1492 NO3 content after incubation 0-2 cm Pioneer - Middle Young - Middle 0.0047 NO3 content after

incubation 2-5 cm Pioneer - Old 0.0263 NO3 content after

incubation 5-10 cm Young - Old 0.0326

Nitrification 0-2 cm No 0.3203 Nitrification 2-5 cm No 0.2227 Nitrification 5-10 cm No 0.3909 Nitrification per m2 0-2 cm No 0.2976 Nitrification per m2 2-5 cm No 0.2228 Nitrification per m2 5-10 cm No 0.3647

Table 1: Outcomes Kruskal-Wallis test to determine significant differences between the age communities per layer. For more details on the calculations, see appendix B and appendix C.

In the layer of 0-2 cm depth, the carbon mineralization rates of the Middle community is significantly lower than in the Pioneer and Young community. In the layer of 2-5 cm depth the Young has a significantly higher mineralization rate than the Old community. In the layer of 5-10 cm the significant differences are similar to the first layer.

Within the age communities, it is calculated whether mineralization rates in the layers differed significantly from each other. For both the ‘Pioneer’, the ‘Young’ and the ‘Middle’ community, the rates in the upper (0-2 cm) layer are significantly higher than in the third (5-10 cm) layer (appendix A).

All the previous calculations are done in mg C kg-1_{OM. To examine the spatial variability of the} different age communities, the net mineralization rate is additionally calculated per m2_{(figure 9).}

(10)

Figure 9: Measured carbon mineralization in mg C kg-1_{OM m}-2 _{over a three day period for the different age communities} at three soil layer depths: 0-2 cm, 2-5 cm and 5-10 cm.

The significant differences per age community in the net carbon mineralization rate per m2_{does not} differ from the rate per kg OM (table 1). The rates per m2_{are lower than the rates per kg OM as there} is less than a kilogram OM per m2_.

Nitrogen

Table 2: NH4 and NO3 concentration in mg kg OM-1_{before (T0) and after (T7) an incubation period of seven days and the} percentage NO3 before and after incubation.

(11)

At the start of the incubation, the average N contents were 254 mg NH4 kg OM-1 and 35 mg NO3 kg

OM-1_{. After incubation, this average was 405,5 mg NH}

4 kg OM-1 and 56 mg NO3 kg OM-1. The NH4 content (table 2) of the Middle community is significantly higher than in the Pioneer and Young communities before the incubation in all layers. After the incubation it was still significantly higher in the second and third layer (table 1).

For the NO3, the content (table 2) in the 0-2 cm layer was significantly higher in the Middle

community than in the Pioneer and Young community before the incubation. After incubation the NO3 content in the Middle community was also significantly higher than in the Pioneer and Young

community at 0-2 cm depth. In the 2-5 cm layer the content was significantly higher in the Old community than in the Young (table 1).

Figure 10: Measured nitrogen mineralization in mg NH4+NO3 kg OM-1_{over a seven day incubation for the different age} communities at different soil depths.

The net nitrogen mineralization over an incubation period of seven days is seen in figure 10. Here also a Kruskal-Wallis test is performed to determine significant differences.

For the first and second layer (0-2 cm and 2-5 cm respectively), no significant difference was found. A remarkable outcome is that for the first layer a p-value of 0.0357 is found (< 0.05) but no significant difference between any communities is given in the multi-comparison test.

In the third layer (5-10 cm) the nitrogen mineralization rates for the Young community were significantly lower than in the Middle and Old community (table 1).

Calculating significance in mineralization rates for the different layers per age community from the Young community, the 2-5 cm layer mineralization rate is significantly higher than at the 5-10 cm layer. From the Middle community the first layer is significantly higher than the second and third layer (appendix A).

(12)

Figure 14: Measured nitrogen mineralization in mg NH4 + NO3 kg OM-1 m2 over a seven day incubation for the age communities at different soil depths.

To provide insight in the spatial variability of the different age communities, the net nitrogen

mineralization rate is also calculated per m2_{(figure 14). The trends are different from the calculations} in NH4+NO3 kg OM-1 in figure 10: the Young community is now significantly lower than the Middle

community in the first layer (0-2 cm) similar to the third layer (5-10 cm). However in the third layer the Young and Old community do not significantly differ any more. There are still no significant differences in the second layer (2-5 cm).

Figure 15: Measured nitrogen mineralization in mg NO3 kg OM-1_{over a seven day incubation for the different age} communities at different soil depths.

Figure 15 shows the net nitrification rate over the incubation period. Although in the first layer (0-2 cm) there is a peak in the Middle age community and in the second layer (2-5 cm) a peak in the Old community, there is no significant difference between these communities and the others (table 1). Reason is the great variability in the measurements as seen in the standard deviation.

Calculating significance per age community, only from the Pioneer community the nitrification rates at 2-5 cm were significantly lower than at 5-10 cm (appendix A).

(13)

Figure 19: Measured nitrification in mg NO3 kg OM-1_m2_{over a seven day incubation for the age communities at different} soil depths.

For the nitrification also a calculation is done per m2_{. The peaks in the first layer of the Middle} community and the second layer of the Old community are still there but the rates are lower per m2 as the OM content is less than a kilogram. Also, the peaks per m2_{are still not significantly higher than} the rates in other age communities (table 1).

Discussion

The question now is whether these measurements on carbon and nitrogen mineralization can provide more information the effect of the different cutting cycles. Plants need both NO3 and NH4 to

grow. However, de Graaf et al. (1998) showed that C. vulgaris can also grow solely on NH4 as this is

the most available form of nitrogen in acid soils. Another (Van Den Berg, 2005) shows that the highest shoot biomass for C. vulgaris was at 500 µmol L−1_NH

4. In this research a maximum of 377 µmol L−1

NH4 was measured in the second layer (2-5 cm) of the Middle community indicating that an higher

content would still be favorable.

The results in table 1 show that not a lot of NH4 is converted to NO3 but mainly organic material is

converted to NH4.

In table 1 it is also seen that the NH4 content is significantly higher in the Middle age community than

in the younger Pioneer and Young communities. This might be a result of the ploughing of this age community as has been stated by Kopittke et al. (2012). However, this difference is not seen in the net N mineralization rates per kg OM, due to the great variance in measurements. For this reason, we cannot draw definitive conclusions on the effect of ploughing on mineralization. However, considering the calculations per m2_{, there is a significant difference between the Middle and Young community in}

the first (0-2 cm) layer and third (5-10) layer. Still, there is no significant difference for the Middle community in the second layer, and no significant difference between the Middle and Pioneer and Middle and Old community is found.

For the C mineralization rates a significant difference can be found in both the first (0-2 cm) and third layer (5-10 cm) layer between the Middle and the Pioneer community and between the Middle and Young community. This could be due to the ploughing, however this difference was not found in the second (2-5 cm) layer. When looking at the calculations per m2_{, significant differences are found for}

the same communities in the same layers, so still no significant differences in the second layer. One of the reasons that not all trends are significant might be due to the methods used which will be further discussed.

Sampling

(14)

three depths similar for all communities. However in the previous study by Kopittke et al. (2012) it was found that the chemical soil horizons differ significantly in depth per age communities. This means that the chemical properties of these soil horizons also differed in the soil core slices made in this research. This might have caused a different trend than expected per depth and age community. Preparation

Other improvements that could be made are in the preparation of the samples:

1) The samples were homogenized and sieved by hand. Because of that small gravels might have been overlooked and included in the weight measurements;

2) Moisture content was homogenized per layer for the different age communities. However to be able to compare the first layer of all the age communities, the moisture content of all the age communities should be the same per layer. This might have influenced the CO2 measurements but

not the nitrogen measurements as 40ml of 0.05 M L-1_K

2SO4 was added for extraction which makes

the effect of moisture content negligible.

A study by Tietema et al. (1992b) shows that for CO2 respiration, the moisture content has the most

effect when it is lower than 75%. The effect of moisture content lower than 75% can influence the measurements by a maximum of 0.5 gram CO2 kg-1 soil day-1, which is 0,13 gram C kg-1 soil day-1 or 130

mg C kg-1_{soil day}-1_{. Only the measurements of the first layer (0-2 cm) in the Middle community and}

the second layer (2-5 cm) in the Young community were influenced by this mistake as they had a divergent moisture content to the same layers of other age communities: either less than 75% in comparison to the others (Middle), or more than 75% compared to the others (Young).

Future research

For future research the soil cores could be divided in smaller parts, for example slices per 1,5 cm so the chemical properties of the different soil horizons are less of an influence. In this research, the significant difference within the age community per depth is also calculated. Future research should take into account that the different depth layers differ in moisture content and other chemical properties, so that a proper comparison may require a correction factor for these chemical factors. Lastly, more samples could be taken from the Middle age community to further examine the effect of ploughing. In this study some exceptional values were found in this community, but no conclusions can be drawn on the effect of ploughing on mineralization rates due to the large variability in obtained data. Taking more samples for all communities in future research could smoothen these variations and confirm some of the exceptional trends found in this research.

Conclusion

In conclusion, significant differences in carbon mineralization rates have been found in the first (0-2 cm) and third (5-10 cm) layer for the Middle community compared to the Pioneer and Young

community. In the first layer, the rates in the Middle community were significantly lower, in the third significantly higher. Because these differences were not found in the second layer no overall

conclusion can be drawn on the effect of ploughing in the Middle community. In the second layer (2-5 cm) the Young community had a significantly higher rate than the Old community. However, because we only found this result in one layer, and only between two communities, no conclusive statements can be made on the effect of different ages. The trends on m2_{scale were similar to those on mg kg}-1

OM scale, so no different conclusions can be drawn on this different scale.

For the nitrogen mineralization rates, significant differences have been found only in the third layer (5-10 cm) between the Young and Middle and between the Young and Old community. No significant differences are found between the Young and Pioneer community. This indicates that that the nitrogen mineralization rates in the younger age communities up to 15 years are significantly lower than in the older communities up to 31 years, at 5-10 cm depth.

(15)

community for the 0-2 cm depth and the 5-10 cm depth layers, where both the rates in the Middle community were significantly higher. Al though more significant differences were found when looking at a larger scale still, no significant differences for the Middle community were found in the second layer (2-5 cm). Also between the Middle and Old or Middle and Pioneer community no significant differences were found. For this reason, no overall conclusions can be made on the effect of ploughing on the Middle layer on a m3_{scale either.}

Lastly, for the nitrification rates two extraordinary peaks were found in the first (0-2 cm) layer of the Middle community and the second (2-5 cm) layer of the Old community. However, these peaks were not significant in both the ' NO3 kg-1 OM ' calculations and the ' NO3 kg-1 OM m-2' calculations.

Therefore also no conclusions can be drawn on the nitrification rates.

Acknowledgements

Thanks goes to dhr.dr. A. Tietema and H.P. Sterk for all their help and advice during the field work, the lab work, the data analysis and for the useful comments on the report.

Also thanks to J.W. Westerveld for all her help and patience at the lab, the carbon measurements and analysis.

Thanks to P. Serné and L. de Lange for preparing the Gas Chromatograph and Auto Analyzer and doing the nitrogen measurements.

Lastly, thanks to F. Vlaar and J. Schaap for their company at the field work and especially F. Vlaar for all the help with the practical work in the lab.

References

Alef, K., & Kleiner, D. (1986). Arginine ammonification, a simple method to estimate microbial activity potentials in soils. Soil Biology and Biochemistry,18(2), 233-235.

Bengtsson, G., Bengtson, P., & Månsson, K. F. (2003). Gross nitrogen mineralization-, immobilization-, and nitrification rates as a function of soil C/N ratio and microbial activity. Soil Biology and

Biochemistry, 35(1), 143-154.

Berendse, F. (1990). Organic matter accumulation and nitrogen mineralization during secondary succession in heathland ecosystems. The Journal of Ecology, 413-427.

Buday, J., Drtil, M., Hutnan, M., & Derco, J. (2000). Substrate and product inhibition of nitrification. CHEMICAL PAPERS-SLOVAK ACADEMY OF SCIENCES, 53(6), 379-383.

Canfield, D. E., Glazer, A. N., & Falkowski, P. G. (2010). The evolution and future of Earth’s nitrogen cycle. science, 330(6001), 192-196.

European Environment Agency (2010). EU 2010 Biodiversity Baseline; Post-2010 EU biodiversity policy.

Galloway, J. N., Townsend, A. R., Erisman, J. W., Bekunda, M., Cai, Z., Freney, J. R., ... & Sutton, M. A. (2008). Transformation of the nitrogen cycle: recent trends, questions, and potential solutions. Science, 320(5878), 889-892.

Golubyatnikov, L. L., Mokhov, I. I., & Eliseev, A. V. (2013). Nitrogen cycle in the Earth climatic system and its modeling. Izvestiya, Atmospheric and Oceanic Physics, 49(3), 229-243.

de Graaf, M. C., Bobbink, R., Roelofs, J. G., & Verbeek, P. J. (1998). Differential effects of ammonium and nitrate on three heathland species. Plant Ecology, 135(2), 185-196.

Kristensen, H. L., & Henriksen, K. (1998). Soil nitrogen transformations along a successional gradient from Calluna heathland to Quercus forest at intermediate atmospheric nitrogen deposition. Applied Soil Ecology, 8(1), 95-109.

Kraal, P., Nierop, K. G., Kaal, J., & Tietema, A. (2009). Carbon respiration and nitrogen dynamics in Corsican pine litter amended with aluminium and tannins. Soil Biology and Biochemistry, 41(11), 2318-2327.

(16)

Kopittke, G. R., Tietema, A., van Loon, E. E., & Kalbitz, K. (2012). The age of managed heathland communities: implications for carbon storage?. Plant and soil, 369(1-2), 219-230.

Philips, S., Wyffels, S., Sprengers, R., & Verstraete, W. (2002). Oxygen-limited autotrophic

nitrification/denitrification by ammonia oxidizers enables upward motion towards more favorable conditions. Applied microbiology and biotechnology, 59(4-5), 557-566.

Tietema, A., De Boer, W., Riemer, L., & Verstraten, J. M. (1992a). Nitrate production in nitrogen-saturated acid forest soils: vertical distribution and characteristics. Soil biology and Biochemistry, 24(3), 235-240.

Tietema, A., Warmerdam, B., Lenting, E., & Riemer, L. (1992b). Abiotic factors regulating nitrogen transformations in the organic layer of acid forest soils: moisture and pH. Plant and Soil, 147(1), 69-78.

Van Den Berg, L. J., Dorland, E., Vergeer, P., Hart, M. A., Bobbink, R., & Roelofs, J. G. (2005). Decline of acid sensitive plant species in heathland can be attributed to ammonium toxicity in combination with‐ low pH. New Phytologist,166(2), 551-564.

Vandewalle et al. (2010). Review paper on concepts of dynamic ecosystems and their services, The RUBICODE project - Rationalising Biodiversity Conservation in Dynamic Ecosystems (Funded under the European Commission Sixth Framework Programme). Website accessed June 2015.

www.rubidcode.net/RUBICODE_Review_on_Ecosystem_Services.pdf

Webb, N. R. (1998). The traditional management of European heathlands. Journal of Applied Ecology, 35(6), 987-990.

Appendices

(17)

Nitrogen Mineralization

%Nitrogen Mineralization: significant difference between the different layers for the same age community

%Pioneer [p,tbl,stats] = kruskalwallis(PioneerM,GroupPM) multcompare(stats) %% No significant differences %Young [p,tbl,stats] = kruskalwallis(YoungM,GroupYM) multcompare(stats)

%% Layer 2 and 3 are significantly different %Middle

[p,tbl,stats] = kruskalwallis(MiddleM,GroupMM) multcompare(stats)

%% Layer 1 is significantly different from layer 2 and 3 %Old

[p,tbl,stats] = kruskalwallis(OldM,GroupOM) multcompare(stats)

%% No significant differences

Figure 20: Example of Kruskal-Wallis test outcomes in Matlab 2011b. Upper tables include the p-values. The multiple comparison test shows which groups differ significantly from each other.

(18)

Figure 22: p-values for the Middle (left) and Old (right) community

Nitrification

%Nitrification: significant difference between the different layers for the same age

%community %Pioneer

[p,tbl,stats] = kruskalwallis(PioneerN,GroupPN) multcompare(stats)

%% Layer 2 and 3 are significantly different %Young [p,tbl,stats] = kruskalwallis(YoungN,GroupYN) multcompare(stats) %% No significant differences %Middle [p,tbl,stats] = kruskalwallis(MiddleN,GroupMN) multcompare(stats) %% No significant differences %Old [p,tbl,stats] = kruskalwallis(OldN,GroupON) multcompare(stats) %% No significant differences

Figure 23: p-values for the Pioneer (left) and Young (right) community

Carbon Mineralization

%Carbon Mineralization: significant difference between the different layers for the same age

%community %Pioneer

[p,tbl,stats] = kruskalwallis(PioneerC,GroupPC) multcompare(stats)

(19)

%% Layer 1 and 3 are significantly different %Young

[p,tbl,stats] = kruskalwallis(YoungC,GroupYC) multcompare(stats)

%% Layer 1 and 3 are significantly different %Middle

[p,tbl,stats] = kruskalwallis(MiddleC,GroupMC) multcompare(stats)

%% Layer 1 and 3 are significantly different %Old

[p,tbl,stats] = kruskalwallis(OldC,GroupOC) multcompare(stats)

%% No significant differences

Figure 25: p-values for the Pioneer (left) and Young (right) community

B. Kruskal-Wallis calculations in Matlab 2011b per layer (differences in age communities) % Nitrogen Mineralization: significant difference between the different ages for the same layer for Mineralization

% Layer 1

[p,tbl,stats] = kruskalwallis(Layer1M,Group_Min1) multcompare(stats)

(20)

% Layer 2 [p,tbl,stats] = kruskalwallis(Layer2M,Group_Min2) multcompare(stats) %% no significant differences % Layer 3 [p,tbl,stats] = kruskalwallis(Layer3M,Group_Min3) multcompare(stats)

(21)

% Nitrification: significant difference for Nitrification % Layer 1

[p,tbl,stats] = kruskalwallis(Layer1N,Group_Nit1) multcompare(stats)

%% geen significante verschillen

% Layer 2

(22)

% Layer 3

%% geen significante verschillen

% Carbon Mineralization: significant difference for CARBON mineralization % Layer 1

[p,tbl,stats] = kruskalwallis(Layer1C,GroupC1) multcompare(stats)

(23)

% Layer 2

%% group 2-4 are significantly different

% Layer 3

(24)

% Nitrogen Mineralization PER M2: significant differences % Layer 1

[p,tbl,stats] = kruskalwallis(Layer1_m2M,Group1_m2M) multcompare(stats)

%% group 2-3 are significantly different from each other

% Layer 2

(25)

% Layer 3

%% group 2-3 are significantly different from each other

% Nitrification PER M2: significant differences % Layer 1

[p,tbl,stats] = kruskalwallis(Layer1_m2N,Group1_m2N) multcompare(stats)

(26)

% Layer 2 [p,tbl,stats] = kruskalwallis(Layer2_m2N,Group2_m2N) multcompare(stats) %% no significant differences % Layer 3 [p,tbl,stats] = kruskalwallis(Layer3_m2N,Group3_m2N) multcompare(stats) %% no significant differences

(27)

% Carbon Mineralization PER M2: significant differences % Layer 1

[p,tbl,stats] = kruskalwallis(Layer1_m2C,Group1_m2C) multcompare(stats)

%% group 1-3 and 2-3 are significantly different

% Layer 2

(28)

% Layer 3

(29)

Figure 27: NH4 and NO3 in mg kg-1_{OM before and after incubation}

% NH4 content BEFORE incubation: significant differences % Layer 1

[p,tbl,stats] = kruskalwallis(Layer1B,Group1B) multcompare(stats)

% Layer 2

(30)

% Layer 3

% NH4 content AFTER incubation: significant differences % Layer 1

[p,tbl,stats] = kruskalwallis(Layer1A,Group1A) multcompare(stats)

(31)

% Layer 2

% Layer 3

(32)

% NO3 content BEFORE incubation: significant differences % Layer 1

[p,tbl,stats] = kruskalwallis(Layer1BN,Group1BN) multcompare(stats)

% Layer 2

(33)

% Layer 3

%% no significant differences

% NO3 content AFTER incubation: significant differences % Layer 1

[p,tbl,stats] = kruskalwallis(Layer1AN,Group1AN) multcompare(stats)

(34)

% Layer 2

% Layer 3

(35)

D. Raw data Auto Analyzer

Auto Analyzer - before Incubation

Identity1 Sample NH4 µmol/l NO3+NO2 µmol/l N-t µmol/l DON µmol/l

2015 F&M 1 P1 50 12 98 37 2015 F&M 2 P1 <10 4 61 57 2015 F&M 3 P1 <10 <3 32 32 2015 F&M 4 P1 96 14 161 51 2015 F&M 5 P1 21 12 63 31 2015 F&M 6 P1 <10 4 39 35 2015 F&M 7 P2 35 4 76 37 2015 F&M 8 P2 <10 7 63 56 2015 F&M 9 P2 <10 4 38 35 2015 F&M 10 P2 156 7 211 48 2015 F&M 11 P2 76 4 126 46 2015 F&M 12 P2 <10 11 66 55 2015 F&M 13 P3 <10 3 41 38 2015 F&M 14 P3 <10 3 32 30 2015 F&M 15 P3 <10 6 33 27 2015 F&M 16 P3 82 6 145 56 2015 F&M 17 P3 34 4 62 24 2015 F&M 18 P3 <10 4 34 30 2015 F&M 19 Y1 <10 4 61 56 2015 F&M 20 Y1 117 6 193 71 2015 F&M 21 Y1 14 9 103 80 2015 F&M 22 Y1 <10 4 69 65 2015 F&M 23 Y1 16 4 79 59

(36)

2015 F&M 24 Y1 <10 3 70 67 2015 F&M 25 Y2 <10 11 103 92 2015 F&M 26 Y2 82 5 177 90 2015 F&M 27 Y2 19 11 128 98 2015 F&M 28 Y2 <10 4 72 68 2015 F&M 29 Y2 10 7 112 95 2015 F&M 30 Y2 <10 6 89 83 2015 F&M 31 Y3 <10 4 69 65 2015 F&M 32 Y3 19 7 99 73 2015 F&M 33 Y3 <10 <3 55 55 2015 F&M 34 Y3 <10 3 63 60 2015 F&M 35 Y3 <10 27 107 80 2015 F&M 36 Y3 <10 6 74 68 2015 F&M 37 M1 92 53 190 45 2015 F&M 38 M1 119 16 178 44 2015 F&M 39 M1 154 5 199 40 2015 F&M 40 M1 98 8 152 45 2015 F&M 41 M1 143 10 185 32 2015 F&M 42 M1 108 31 201 62 2015 F&M 43 M2 316 15 418 87 2015 F&M 44 M2 278 6 338 54 2015 F&M 45 M2 213 10 295 72 2015 F&M 46 M2 226 7 309 77 2015 F&M 47 M2 293 10 383 80 2015 F&M 48 M2 256 14 339 69 2015 F&M 49 M3 154 8 220 58 2015 F&M 50 M3 147 6 214 61 2015 F&M 51 M3 129 5 153 19 2015 F&M 52 M3 85 5 107 16 2015 F&M 53 M3 237 8 264 20 2015 F&M 54 M3 240 8 267 19 2015 F&M 55 O1 10 5 32 18 2015 F&M 56 O1 45 8 65 12 2015 F&M 57 O1 194 12 246 41 2015 F&M 58 O1 62 12 95 21 2015 F&M 59 O1 50 24 144 70 2015 F&M 60 O1 26 7 92 58 2015 F&M 61 O2 21 6 97 70 2015 F&M 62 O2 13 5 32 14 2015 F&M 63 O2 118 15 209 76 2015 F&M 64 O2 58 6 108 44 2015 F&M 65 O2 35 11 96 50 2015 F&M 66 O2 29 5 93 60 2015 F&M 67 O3 12 4 27 12

(37)

2015 F&M 68 O3 <10 5 72 67

2015 F&M 69 O3 58 10 128 61

2015 F&M 70 O3 18 6 82 59

2015 F&M 71 O3 20 12 45 12

2015 F&M 72 O3 <10 3 49 46

Auto Analyzer - after Incubation

Identity1 Sample NH4 µmol/l NO3+NO2 µmol/l N-t µmol/l DON µmol/l

2015 M 1 P1 135 19 222 68 2015 M 2 P1 87 7 179 85 2015 M 3 P1 56 7 137 74 2015 M 4 P1 228 14 326 84 2015 M 5 P1 157 5 248 86 2015 M 6 P1 20 4 85 61 2015 M 7 Y1 37 6 116 73 2015 M 8 Y1 280 4 387 103 2015 M 9 Y1 103 6 189 80 2015 M 10 Y1 71 6 145 68 2015 M 11 Y1 2256 6 2457 195 2015 M 12 Y1 55 6 129 68 2015 M 13 M1 103 131 314 80 2015 M 14 M1 208 24 300 68 2015 M 15 M1 225 5 296 66 2015 M 16 M1 211 8 283 64 2015 M 17 M1 203 18 288 67 2015 M 18 M1 96 91 258 71 2015 M 19 O1 118 12 210 80 2015 M 20 O1 177 9 300 114 2015 M 21 O1 343 20 447 84 2015 M 22 O1 162 32 283 89 2015 M 23 O1 79 128 291 84 2015 M 24 O1 95 5 193 93 2015 M 25 P2 81 4 158 73 2015 M 26 P2 48 5 114 61 2015 M 27 P2 22 7 100 71 2015 M 28 P2 240 5 337 92 2015 M 29 P2 190 6 279 83 2015 M 30 P2 <10 5 75 70 2015 M 31 Y2 67 5 153 81 2015 M 32 Y2 232 10 349 107 2015 M 33 Y2 128 7 257 122 2015 M 34 Y2 68 6 171 97

(38)

2015 M 35 Y2 90 9 206 107 2015 M 36 Y2 82 10 301 209 2015 M 37 M2 377 18 475 80 2015 M 38 M2 352 9 455 94 2015 M 39 M2 288 5 369 76 2015 M 40 M2 290 5 376 81 2015 M 41 M2 333 6 414 75 2015 M 42 M2 325 21 414 68 2015 M 43 O2 79 9 151 63 2015 M 44 O2 63 4 97 30 2015 M 45 O2 152 58 262 52 2015 M 46 O2 88 17 149 44 2015 M 47 O2 53 33 113 27 2015 M 48 O2 78 5 135 52 2015 M 49 P3 14 7 38 17 2015 M 50 P3 <10 5 43 38 2015 M 51 P3 <10 8 65 57 2015 M 52 P3 108 10 209 91 2015 M 53 P3 55 4 106 47 2015 M 54 P3 17 5 61 39 2015 M 55 Y3 <10 6 60 54 2015 M 56 Y3 17 5 47 25 2015 M 57 Y3 <10 5 61 56 2015 M 58 Y3 <10 4 55 51 2015 M 59 Y3 12 10 81 59 2015 M 60 Y3 <10 5 53 48 2015 M 61 M3 182 10 247 55 2015 M 62 M3 206 7 255 42 2015 M 63 M3 176 5 230 49 2015 M 64 M3 125 6 172 41 2015 M 65 M3 288 7 357 62 2015 M 66 M3 260 10 310 40 2015 M 67 O3 12 6 71 53 2015 M 68 O3 16 9 82 57 2015 M 69 O3 80 20 146 46 2015 M 70 O3 21 6 78 51 2015 M 71 O3 35 10 67 22 2015 M 72 O3 18 11 70 41

Blancs - before incubation

2015 F&M 73 <10 5 42 37

2015 F&M 74 <10 3 47 44

(39)

2015 F&M 76 <10 6 64 58

2015 F&M 77 <10 4 39 35

2015 F&M 78 <10 <3 38 38

2015 F&M 79 <10 <3 37 37

2015 F&M 80 <10 3 29 25

Blancs - after incubation

2015 M 77 <10 6 43 37

2015 M 78 <10 5 23 18

2015 M 79 <10 4 26 22

2015 M 80 <10 8 35 27

E. Raw data - Gas Chromatograph

Measurements day 1 Summar y Sequence Details Name: Directory: Data Vault: No. of Injections: By Component software No. Injection Name Area Amount

mV*min FID FID

CO2 CO2

1 SA01 n.a. n.a.

2 standard_01 n.a. n.a. 3 standard_02 4,35 399,32 4 standard_03 8,85 964,61 5 standard_04 17,34 2028,94 6 standard_05 43,75 5342,46

(40)

7 standard_06 84,07 10401,2 2 8 standard_07 165,3 20590,4 5 9 77 3,89 342,38 10 1 154,48 19233,7 8 11 2 196,36 24487,8 3 12 3 156,07 19433,6 5 13 4 172,33 21473,2 3 14 5 147,07 18304,2 6 15 6 179,06 22317,3 6 16 7 186,17 23209,5 7 17 8 206,76 25791,8 2 18 9 203,6 25395,8 2 19 check01 3,06 237,62 20 74 4,01 357,8 21 10 183,44 22866,3 7 22 11 214,33 26741,8 2 23 12 187 23313,4 5 24 13 125,52 15601,1 2 25 14 136,88 17025,3 4 26 15 133,51 16602,7 6 27 16 153,13 19064,7 9 28 17 125,84 15640,9 29 18 96,5 11959,8 5 30 check02 3,09 242,11 31 78 3,95 350,11 32 19 252,4 31518,2 33 20 108,06 13410,3 34 21 244,01 30465,1 1 35 22 224,03 27958,4

(41)

8 36 23 110,74 27491,8 7 37 24 46,15 11287,2 2 38 25 128,52 31952,8 4 11591,6 6 40 26 163,32 40685,7 2 41 27 137,73 34265,2 1 42 check03 3,1 242,5 43 75 4,05 362,3 44 28 113,35 28148,7 9 45 29 172,58 43009,1 6 46 30 126,76 31513,3 8 47 31 159,37 39694,7 1 48 32 181,77 45315,6 1 49 33 227,41 56764,5 8 50 34 42,46 10360,7 5 51 35 211,35 52735,4 9 52 36 117,71 29241,2 8 53 SA01 n.a. n.a. 54 standard_01_0 2 1,98 102,96 55 standard_02_0 2 4,34 398,22 56 standard_03_0 2 8,69 944,27 57 standard_04_0 2 17,28 2021,35 58 standard_05_0 2 42,56 5193,39 59 standard_06_0 2 82,9 10254,4 2 60 standard_07_0 2 158,28 19710,3 7 61 73 3,9 343,64

(42)

62 37 161,98 40350,0 1 63 38 140,89 35057,8 7 64 39 169,43 42218,8 2 65 40 163,73 40787,3 66 41 122,53 30451,1 67 42 130,87 32544,4 8 68 43 174,4 43464,8 6 69 44 158,97 39592,8 4 70 45 121,91 30296,6 5 71 check04 3,11 244,17 72 76 3,77 327,58 73 46 133,32 33157,9 2 74 47 94,91 23521,9 6 75 48 53,83 13215,1 1 76 49 73,46 18138,8 1 77 50 69,2 17071,1 1 78 51 50,45 12367,2 8 79 52 72,08 17792,9 80 53 83,34 20618,1 2 81 54 58,04 14271,2 6 82 check05 3,09 241,38 83 80 4,04 361,39 84 55 82,33 20365,2 8 85 56 75,92 18756,7 4 86 57 88,23 21844,3 3 87 58 57,59 14157,3 2 88 59 97,38 24141,3 1 89 60 98,61 24449,2 90 61 76,36 18866,2

(43)

3 91 62 93,98 23289,0 3 92 63 137,75 34270,2 93 check06 3,07 239,82 94 79 3,49 291,93 95 64 74,81 18478,4 9 96 65 97,45 24157,6 8 97 66 91,22 22595,6 1 98 67 59,66 14675,8 1 99 68 132,83 33036,2 9 100 69 60,03 14769,8 101 70 49,27 12070,4 102 71 52,42 12861,0 3 103 72 44,22 10804,3 2 Measurements day 3 No. of Injections: By Component software No. Injection Name Area Amount

mV*min FID FID

CO2 CO2

1 SA01 n.a. n.a.

2 standard_01 1,95 105,8 3 standard_02 4,29 405,96 4 standard_03 8,58 957,65 5 standard_04 16,66 1995,31 6 standard_05 41,69 5211,02 7 standard_06 79,77 10103,1 1 8 standard_07 157,78 20125,7 9 9 77 3,81 344,57 10 1 63,16 63752,5

(44)

8 11 2 75,89 76842,3 1 12 3 57,65 58085,8 5 13 4 65,2 65845,2 6 14 5 55,59 55972,6 9 15 6 62,83 63415,4 3 16 7 63,16 63749,7 2 17 8 74,27 75167,9 5 18 9 69,96 70740,4 7 19 check01 3,13 257,09 20 74 3,93 359,45 21 10 63,79 64395,9 8 22 11 72,88 73746,4 9 23 12 60,81 61337,9 6 24 13 38,35 38249,6 6 25 14 43,59 43644,5 26 15 44,13 44196,1 7 27 16 48,87 49066,5 9 28 17 39,5 39439,3 29 18 28,23 27850,8 30 check02 3,26 272,91 31 78 3,89 354,66 32 19 75,54 76481,7 4 33 20 34,59 34391,1 34 21 72,89 73752,9 7 35 22 66,34 67019,9 7 36 23 59,34 59828,5 37 24 25,77 25328,1 4 38 25 69,49 70254,7 39 26 87,93 89213,8

(45)

3 40 27 72,17 73013,0 6 41 check03 3,26 272,96 42 75 4,06 375,77 43 28 60,46 60974,9 4 44 29 90,03 91374,6 8 45 30 64,86 65503,7 3 46 31 83,91 85076,7 4 47 32 94,59 96055,9 2 48 33 123,34 125611, 3 49 34 25,77 25319,0 1 50 35 112,6 114571, 7 51 36 60,58 61103,4 3

52 SA01 n.a. n.a.

53 standard_01_02 1,98 109,7 54 standard_02_02 4,35 413,82 55 standard_03_02 8,65 966,33 56 standard_04_02 17,18 2061,66 57 standard_05_02 42,94 5371,59 58 standard_06_02 81,87 10373,0 2 59 standard_07_02 156,54 19966,2 6 60 73 3,88 353,56 61 37 77,33 78321,9 1 62 38 68,91 69663,5 63 39 82,93 84076,1 6 64 40 77,56 78553,8 1 65 41 59,41 59902,7 6 66 42 61,74 62297,8 67 43 80,01 81076,1 6 68 44 73,75 74636,8 2

(46)

69 45 55,53 55916,3 7 70 check04 3,26 273,78 71 76 3,76 338,11 72 46 60,33 60842,6 2 73 47 41,12 41096,1 5 74 48 23,82 23317,7 5 75 49 31,73 31450,3 6 76 50 29,25 28895,9 77 51 21,03 20450,2 2 78 52 30,87 30567,2 1 79 53 34,96 34768,7 5 80 54 24,22 23734,4 1 81 check05 3,25 272,27 82 80 4,03 373,1 83 55 40,77 40736,0 7 84 56 39,68 39622,4 8 85 57 45,02 45113,8 6 86 58 28,56 28196,2 5 87 59 48,65 48840,4 7 88 60 47,91 48081,7 1 89 61 41,26 41248,7 9 90 62 48,68 48870,9 3 91 63 71,09 71907,6 7 92 check06 3,27 275,06 93 79 3,58 314,3 94 64 37,82 37706,0 2 95 65 52,17 52455,2 2 96 66 47,48 47641,4 8

(47)

97 67 28,84 28475,9 1 98 68 63,78 64390,6 1 99 69 28,77 28410,0 7 100 70 22,95 22427,5 7 101 71 24,83 24362,3 9 102 72 20,63 20037,6 5

103 SA01 n.a. n.a.

104 standard_01_03 2 111,03 105 standard_02_03 4,38 417,4 106 standard_03_03 8,67 968,59 107 standard_04_03 17,24 2069,19 108 standard_05_03 42,89 5364,83 109 standard_06_03 82,04 10395,4 2 110 standard_07_03 159,71 20373,5 2