A Story About Understory: The Influence of Understory Species on Carbon Storage in Scots Pine Forests Around the Kootwijkerzand.

(1)

A Story About Understory:

The Influence of Understory Species on Carbon Storage

in Scots Pine Forests Around the Kootwijkerzand.

Future Planet Studies: Earth Sciences Bachelor Thesis

Visual impression of the fieldwork trip (Caycedo, 2017)

Sofia Caycedo - 10695311 Primary Supervisor: Boris Jansen Secondary Supervisor: Olaf Brock University of Amsterdam

(2)

2

Abstract

Forests play an important role in the global carbon cycle, sequestering a majority of the carbon stored in terrestrial ecosystems. In the light of increasing atmospheric CO2 concentrations, there is a rising interest among researchers to understand the processes underlying forest soil carbon storage. While research has indicated that tree species significantly influence carbon storage in forest floors and soils through litter fall, the influence of understory vegetation on forest soil carbon storage is not well documented.

The aim of this research was to shed light on the influence of understory vegetation on carbon storage in Dutch Scots Pine (Pinus Sylvestris L.) forests around the Kootwijkerzand. This area was suitable due to the homogeneity in tree species and substrate as well as the variety of understory species evident. The carbon stock of the biomass, forest floor and mineral topsoil for different groups of understory species in the study area were quantified. Additionally, the contribution of understory vegetation to total forest litter fall was estimated. Waivy Hairgrass (Deschamspia Flexuosa), Common Hair Moss (Polytrichium Commune) and Bilberry (Vaccinium

Myrtillus) were selected as dominant understory species. These species were chosen due to their common

occurrence in the area, as well as their physiological differences. Plots without understory vegetation were also selected that could serve as a control group. Plant biomass and forest floor material were weighed and CNS analyses were carried out for the mineral topsoil samples in order to analyze carbon stocks of biomass, forest floor and mineral topsoil for these species. Subsequently, statistical analyses were performed to compare the carbon stocks and the C/N ratios of the different groups. In addition, the contribution of understory litter to total forest plant litter was estimated on the basis of the biomass data and literature.

The results revealed that forest floor carbon stocks, mineral topsoil carbon stocks and C/N ratios were significantly different. The forest floor carbon stock of Waivy Hairgrass was significantly higher than the other groups. Moreover, the mineral topsoil carbon stocks of Waivy Hairgrass and Common Hairmoss were

significantly higher than the mineral topsoil stocks of Bilberry and the group without understory vegetation. Additionally, the C/N ratio of the mineral topsoil under Waivy Hairgrass and Common Hairmoss was significantly larger than under Bilberry and the group without understory vegetation. Lastly, the results indicated that the contribution of understory vegetation to total litter fall is less than 5 %.

The results indicate that understory species –namely Waivy Hairgrass and Common Hairmoss - positively influence carbon stocks in pine forests near the Kootwijkerzand. This implies that these species could potentially be taken into account when determining adequate forest management techniques to maximize carbon storage. However, more research is necessary to further analyze the interactions between understory litter and long-term soil carbon sequestration in the study area, and determine whether the results are applicable on a larger scale. Moreover, the stability of the carbon stocks for the different understory species should be analyzed. Lastly, an empirical analysis is required in order to verify that the contribution of understory vegetation to total litter fall is indeed less than 5 %.

(4)

4

Introduction

Forests play an important role in the global carbon cycle, sequestering a majority of the carbon stored in

terrestrial ecosystems (Pan et al., 2011). Of the carbon stored in forests, it is estimated that approximately 30% is stored in the forest soils (Janssens et al., 2003). In the light of increasing atmospheric CO2 concentrations as a result of fossil fuel combustion, there is a rising interest among researchers in the processes underlying the storage of carbon in forest soils (Lal, 2005). Understanding these processes is necessary to find ways to maximize this storage in order to mitigate increasing CO2 concentrations (De Deyn, Cornelissen & Bardgett, 2008).

Many researchers have studied the influence of tree species on soil carbon storage in forests. Different tree species were found to have a significant but strongly varying influence on the amount of organic carbon stored in forest floors and forest soils (Finzi, Van Breemen & Canham, 1998; Vesterdal et al., 2008; Vesterdal, Clarke, Sigurdsson & Gunderson, 2013; Trum, Titeux, Ranger & Delvaux, 2011). This varying influence can be

attributed to differences in carbon input through the amount and chemical composition of plant litter (Vesterdal et al., 2008; De Deyn, Cornelissen & Bardgett, 2008; Lal, 2005; Lutzow et al., 2005; Kögel-Knaber, 2005). However, other processes such as climate, temperature, soil chemical properties and soil biotic community also heavily affect carbon storage in forest soils (Prescott, 2010; Lal, 2005). Thus, afforestation and other forest management techniques are gaining attention as potentially effective measures for mitigating atmospheric CO2 increases (Vesterdal et al., 2008; Jonard et al., 2017; Jandl et al., 2007).

While researchers have frequently studied the influence of tree species on soil carbon storage in forests, only a few studies focused on the influence of understory vegetation on carbon storage in forest floors and soils, as many researchers assume that understory vegetation does not considerably affect litter input into the soil (Averill, Turner & Finzi, 2014; Kögel-Knaber, 2002). Kögel-Knaber estimated that the contribution of

understory vegetation to litter fall in forests is less than 5 % (Kögel-Knaber, 2002). Subsequently, the influence of understory vegetation on carbon storage in the forest floor and soil is not well documented. However, Nilsson & Wardle (2005) estimated that the productivity of understory vegetation in a boreal forest is similar to that of the forest’s trees, and that a high turnover rate allows understory vegetation to contribute substantially to annual boreal forest litter fall. Additionally some researchers believe that understory vegetation might have a significant influence on forest soil carbon storages through litter fall (Vesterdal, Clarke, Sigurdsson &

Gunderson, 2013; De Deyn, Cornelissen & Bardgett, 2008). In fact, recent research has indicated that under specific circumstances, the presence of understory vegetation under trees can significantly influence the accumulation of litter-derived carbon in the soil (Qiao, Miao, Silva & Horwath, 2014; Liu et al., 2013).

This research aims to shed light on the influence of understory vegetation on carbon storage in Dutch pine forests. To fulfil this aim we will investigate the carbon stock of the aboveground biomass, the forest floor and the first 0-5 cm of the mineral soil (mineral topsoil) in Scots pine (Pinus Sylvestris L.) forests around the

Kootwijkerzand, near the Dutch Veluwe. This area is known to host a diverse variety of understory species under otherwise similar soil and forest conditions (Bijlsma et al., 2014). The first 0-5 cm of the soil is chosen, as this part of the soil is most influenced by the forest floor (Hagen-Thorn et al., 2004).

The detection of a significant influence could imply that understory vegetation should be taken into account in order to improve the accuracy of national forest carbon stock inventories. Moreover, the information could be used in order to improve forest carbon stock inventories as well as aid the design of forest

(5)

5

Research Questions

The main research question of this research project entailed:

“What is the influence of understory vegetation on carbon storage in Dutch pine forests near Kootwijk?” In order to answer the main research question, several sub-questions were identified:

Sq. 1 “What are the aboveground biomass carbon stocks in Dutch pine forests near Kootwijk for different types of understory vegetation and are there significant differences between them?“

Sq. 2 “What are the forest floor carbon stocks in Dutch pine forests near Kootwijk for different types of understory vegetation and are there significant differences between them?“

Sq. 3 “What are the carbon stocks of the mineral topsoil in Dutch pine forests near Kootwijk for different types of understory vegetation and are there significant differences between them?“

Sq. 4 “What is the C/N ratio of the mineral topsoil in Dutch pine forests near Kootwijk for different types of understory vegetation and are there significant differences between them?“

Sq. 5 “Is the relative contribution of three different groups of understory vegetation to plant litter in Dutch pine forests near Kootwijk 5 % or larger?”

The first three questions were formulated in order to detect a possible influence of the understory species on the carbon stocks. The fourth question was chosen with the knowledge that the soil C/N ratio is an indicator of the potential of the soil to sequester carbon (de Vries et al., 2006). The fifth question was formulated in order to investigate whether understory vegetation litter represents a larger part of the forest plant litter than researchers commonly assume. The threshold in this question was based on Kögel-Knaber’s statement that the contribution of understory vegetation to total forest plant litter is less than 5 % (Kögel-Knaber, 2002). If this study shows that understory vegetation represents a significant part of the forest plant litter, this could imply that understory vegetation plays a larger role in forest soil forming processes than currently thought.

(6)

6

Hypotheses

On the basis of the research questions, five hypotheses were formulated:

1. H1

The understory vegetation species Waivy Hairgrass, Common Hair Moss and Bilberry in Scots Pine forests near the Kootwijkerzand have different aboveground biomass carbon stocks.

2. H1

Under homogenous conditions, differences in understory vegetation species in Scots Pine forests near the Kootwijkerzand result in differences in forest floor carbon stocks.

3. H1

Under homogenous conditions, differences in understory vegetation species in Scots Pine forests near the Kootwijkerzand result in differences in mineral topsoil carbon stocks.

4. H1

Under homogenous conditions, differences in understory vegetation species in Scots Pine forests near the Kootwijkerzand result in differences in mineral topsoil C/N ratios.

5. H1

The contribution of understory vegetation to total plant litter fall in Scots Pine forests near the Kootwijkerzand is 5 % or more.

(7)

7

Materials and methods

Study area

The study area is pine forests near the Veluwe, in the area in and around the Kootwijkerzand. Scots Pine (Pinus

Sylvestris) forests were selected, because Scots Pine is one of the trees most widely evident in Dutch forests

(Dirkse, 1987). Until the 1970’s, over half of the Dutch forests consisted of Scots Pine trees (Mohren & Modde, 2006). In 2006, 33,2 % of Dutch forest stands consisted of Scots Pines (Dirkse et al., 2006). Most of the trees were planted at the end of the 19th_{century during afforestation projects aimed at creating wood for mining} (Mohren & Vodde, 2006). A diverse variety of understory species –including herbaceous plants, shrubs and mosses - can be found in the Scots Pine forest around the Kootwijkerzand (Bijlsma et al., 2014).

The area is situated on top of the geological formation of Boxtel (Geologie van Nederland, 2017). In order to control for environmental factors, plots were chosen in which the substrate and soil are similar. The substrate under all of the plots is drift-sand (Geologie van Nederland, 2017). Smit (1996) found that Cambic or Haplic Arenosols on top of the drift-sand are the most important soil types in this area.

Figure 1: (Left) Geographical map of the area. The red marker is placed at Kootwijkrzand, which is the central area where

fieldwork is to be performed. (Google maps, 2017). Figure 2: (Right) Geological map of the area, coinciding with left image. The yellow color corresponds with the geological unit ‘drift-sand’ (Geologie van Nederland, 2017).

Understory vegetation species & study groups

Three dominant types of understory vegetation species were chosen, which are all evident within the Scots Pine forests located in the study area. These species were chosen due to their common occurrence in the area, as well as their physiological differences. The species – Bilberry (Vaccinium myrtillus), Waivy Hair-grass (Deschampsia

flexuosa) and Hairmoss (Polytrichum) - were selected in collaboration with Annemieke Kooijman from the

Institute for Biodiversity and Ecosystem Dynamics (IBED), according to a study by Annemieke Smit (1995) carried out in the study area (pers. Communication Annemieke Kooijman, IBED). The choice for these

understory vegetation species was further justified by the Veluwe vegetation typology by Bijlsma et al. (2014), as well as by a consultation with forester Florian Bijmold (pers. Communication Florian Bijmold, Staatsbosbeheer).

From now on, the different understory vegetation species are referred to as study groups. Besides the groups of understory vegetation species, a fourth study group was selected: this group contains little to no

(8)

8 understory vegetation, and will act as a control group for the other study groups. Thus, four groups were identified:

1. Waivy Hairgrass (Deschampsia flexuosa) as dominant understory species

This type of grass is evident on the forest edges or in the open areas of pine forest on drift-sand. It is

characterized by a dense grass-mat that covers >25% of the forest floor. It is often situated on a humus profile dominated by an F layer (Bijlsma et al., 2014).

Figure 3: Waivy Hairgrass (Deschampsia flexuosa).(Royal Horticultural Society, 2017).

2. Common Hair Moss (Polytrichium) as dominant understory species

This moss species is evident in the open spaces of the Veluwe pine forest and surroundings. It has a co-dominance of >40% together with heather Calluna Vulgaris (Bijlsma et al., 2014).

Figure 4: Common Hair Moss (Polytrichium). Photo taken while exploring the area around Kootwijk, on 21-04-2017 (Caycedo,

2017).

3. Bilberry (Vaccinium myrtillus) as dominant understory species

Bilberry is a low-growing shrub bearing black, edible berries. It is evident in dry meadows in and around the Veluwe, often in co-dominance together with heather (Bijlsma et al., 2014). Bilberry was found while exploring the pine forests around the Kootwijkerzand.

(9)

9

Figure 5: Bilberry (Vaccinium myrtillus). Photo taken while exploring the area around Kootwijk, on 21-04-2017 (Caycedo,

2017).

4. Little to no understory vegetation

This group consists of areas of the pine forest in the study area in which understory vegetation has been entirely or partially removed, for instance for forest management. A consultation with foresters Frank Volkers and Florian Bijmold for the area around the Kootwijkerzand helped to identify suitable areas for this last study group. They advised to look for bare spaces in the pine forest floor between the Kootwijkerzand and the Hoog Buurlose Heide. These bare spaces are evident due to a project that was completed in 2011, in which the moss and herb layers in this area of the pine forest were removed in order to decrease soil nutrient levels and promote ecological succession. Additionally, the foresters informed us that wild pigs often allow bare patches to appear as they remove understory layers throughout the forest (pers. Communication Frank Volkers, Staatsbosbeheer; pers. Communication Florian Bijmold, Staatsbosbeheer).

Figure 6: Study group with little to no understory vegetation. Photo taken during the fieldwork trip, on 03-05-2017 (Caycedo,

(10)

10 Sample categories

Four sample categories were distinguished for this research project. Together, the sample categories represent the forest floor and the top layer of the mineral soil. The categories include:

1. The aboveground biomass plus the L layer. The L layer is the organic horizon consisting of relatively non-decomposed plant material (Krzic et al., 2013).

2. The F layer, which is found under the L layer and consists of partly decomposed plant material (Krzic et al., 2013).

3. The H layer: this layer is situated under the F layer, and consists of decomposed organic matter (Krzic et al., 2013). The H layer is not always evident and thus will not necessarily be sampled

4. The mineral topsoil (0-5 cm), under the L, F and H layers. Actions in the field

For each study group, 10 samples for the sample categories were taken from the fieldwork area. The samples within groups were approximately 50-100 meters distance from each other, in order to prevent pseudo replication. The ideal amount of sample areas per category and per study group for this research project was determined to be 12. This number was based on literature regarding similar studies (Yin et al. 2016; Tolunay, 2009) as well as on the outcome of a power analysis performed with the online power calculator for a one-way independent ANOVA (QFAB Bioinformatics, 2017). However, due to logistical reasons, the decision was made to select 10 sample areas per group. For the Waivy Hairgrass group, 9 samples were used for further analyses as one of the samples from the CNS analysis proved to be unsuitable for further use.

Per study group, tree cover density and understory vegetation cover density were estimated for each of the sample areas, after which soils were classified according to the World Reference Base 2014’ (IUSS Working Group, 2014).

For the aboveground biomass plus L category, material was collected from a 20-cm2 plot for each of the 10 sample areas. The decision to sample the entire aboveground biomass within the 20-cm2 plots was based on the difficulty of sampling understory vegetation litter. Understory vegetation species – especially those closest to the forest floor such as mosses and grasses - do not produce litter in the same manner as trees do. While trees allow leaves and branches to fall onto the forest floor, these species produce litter as their leaves or roots die off (Hilli, Stark & Derome, 2010). For this reason, the aboveground biomass (of the understory species) was sampled together with the L category to use for further analysis in the laboratory.

For the F category, material was collected from a 20-cm2_{plot for each of the sample areas. If an H layer} is evident, H material was also collected from the 20-cm2_plots.

For the mineral topsoil category, a sample was taken within a 20-cm2_{plot for each of the 10 sample} areas using a bulk density ring.

(11)

11

Figure 7: Map showing the sample locations (Caycedo, 2017).

Actions in laboratory

For the L category, the aboveground biomass samples (containing both understory biomass, understory litter and other litter including pine) were dried at 40° Celsius for approximately four days. Subsequently, the understory vegetation biomass was removed from the rest of the material and weighed separately on a two-decimal balance. The samples from the F and H categories were also dried at 40° Celsius for approximately four days, after which they were weighed on a two-decimal balance.

The mineral topsoil samples were first weighed on a two-decimal balance, after which the samples were dried at 40° Celsius for two days. In order to correct for moisture that had potentially remained in the dried samples, a soil moisture test was performed on a smaller part of the samples. Subsequently, the mineral topsoil’s < 2 mm fraction was milled and total carbon concentrations were determined for this fraction, using a Vario EL elemental analyzer (Elementar Analysensysteme, Hanau, Germany).

Calculations

The biomass carbon stocks were estimated using the biomass sample weights and the 50% carbon concentration estimate (Hiraishi et al., 2014). Similarly, the forest floor carbon stocks per sample area were estimated using the weights of the pine litter, the F layer and the potential H layer as well as the 50 % carbon concentration estimate (Hiraishi et al., 2014). Additionally, the mineral topsoil carbon stocks were estimated using the information on carbon concentrations, soil moisture and bulk density.

(12)

12 Moreover, several calculations were made on the basis of literature, in order to estimate the contribution of the understory vegetation to total forest plant litter fall. A study by Vucetich et al. (2000) provided information on the annual production of Scots Pine forest litter. Osipov (2016) used the following ratios to estimate litter fall for different species in a Middle Taiga forest in Russia:

Understory plant growth / Understory plant biomass Understory litter fall / Understory plant growth

The abovementioned ratio method was used to estimate the stock of litter fall for Common Hairmoss, Bilberry and Waivy Hairgrass in kilogram per hectare per year.

Pristova (2008) analyzed the biomass stock; plant growth and annual litter fall of different forest species including mosses, dwarf shrubs and herbaceous plants in a forest in the Middle Taiga. If one takes the annual litter fall as a percentage of the biomass, one arrives at the following percentages:

Annual aboveground herbaceous plant growth/ Aboveground herbaceous plant biomass * 100 = 100 %

Annual aboveground herbaceous plant litter fall / Annual aboveground herbaceous plant growth * 100 = 89.5 % Annual moss growth/ Moss biomass * 100 = 27.9 %

Annual moss litter fall / Annual moss growth * 100 = 75%

Annual aboveground dwarf shrub growth/ Aboveground dwarf shrub biomass * 100 = 27.3 % Annual aboveground dwarf shrub litter fall / Annual aboveground dwarf shrub growth * 100 = 50 %

We used the biomass stocks as measured in the field as well as the above-mentioned ratios from Pristova (2008) (using the dwarf shrub data for Bilberry, the herbaceous plant data for Waivy Hairgrass and the moss data for Common Hairmoss) to calculate the annual litter fall in kilogram per hectare.

Statistical Analyses

Inter- and intra-study group variance was compared using a one-way ANOVA. The non-parametric Kruskal Wallis test (McDonald, 2014) was used as Lilifors testing (Dallal & Wilkinson, 1986) revealed the data was not all normally distributed.

A p-value of 0.05 was chosen as the significance value for all of the performed analyses. This p-value is common in Earth Science and Biology research projects (Quinn & Keough, 2002; Sokal & Rohlf, 1995). Moreover, the critical Chi-Square value for the Kruskal-Wallis One Way ANOVA analyses, at 3 degrees of freedom, was 7.82.

While the Kruskal Wallis One-Way ANOVA analyses allowed us to detect a significant difference between the mean ranks of the different study groups, it did not allow us to compare all of the study groups individually. Therefore, after the Kruskal Wallis One-Way ANOVA analyses were performed, pairwise comparison analyses were performed using the Bonferroni method (Montgomery, 2017).

Literature study

Lastly, a literature study was performed in order to estimate the C/N ratio of the biomass of grasses, mosses and bilberry. This allowed us to compare the understory biomass C/N ratios to the mineral topsoil C/N ratios that were detected in the laboratory.

(13)

13

Results

Biomass Carbon Stocks

The median carbon stocks for Waivy Hairgrass, Common Hair Moss and Bilberry were respectively 3468.8, 3716.9 and 2631.8 kilogram per hectare. Moreover, the mean ranks for Waivy Hairgrass, Common Hair Moss and Bilberry were respectively 17, 17.8 and 10.4. Neither the p-value nor the Chi-Square value for the mean ranks was significant (p-value>0.05 and Chi-Square value<7.82) (Table 1). This indicates that no significant difference could be detected between the biomass carbon stocks of the three study groups.

Because the Kruskal-Wallis One Way ANOVA analysis did not give significant results, it was not necessary to perform a pairwise comparison of the study groups.

Table 1: Biomass Carbon Stock Kruskal-Wallis ANOVA table

Figure 8: Biomass Carbon Stock Kruskal-Wallis ANOVA output Source SS df MS Chi-sq Prob>Chi-sq

---Groups 326 2 163 4.5 0.1056

Error 1704 26 65.5385 Total 2030 28 Biomass Carbon Stock Kruskal-Wallis ANOVA Table

1 2 4

Study Groups: 1 = Waivy Hairgrass, 2 = Common Hair Moss, 3 = No Understory, 4 = Bilberry

1000 1500 2000 2500 3000 3500 4000 4500 5000 5500

Biomass Carbon Stock (kg / hectare)

(14)

14 Forest Floor Carbon Stocks

The median carbon stocks for Waivy Hairgrass, Common Hair Moss, the group without understory and Bilberry were respectively 59046, 31348, 21970 and 30917 kilogram per hectare and the mean ranks were respectively 33.89, 19.6, 9.8 and 18.1. The differences in the mean ranks were statistically significant (Table 2). Thus, there is sufficient evidence that there is a significant difference between some of the study groups.

Table 2: Forest Floor Carbon Stock Kruskal-Wallis ANOVA table

Figure 9: Forest Floor Carbon Stock Kruskal-Wallis ANOVA output

The pairwise comparison analysis (Figure 10) revealed that the only group that was significantly different from the rest was Waivy Hairgrass, which had a significantly higher forest floor carbon stock. The forest floor carbon stocks of the other three study groups (Common Hair Moss, No Understory Vegetation and Bilberry) did not statistically differ from each other.

Source SS df MS Chi-sq Prob>Chi-sq ---Groups 2621.81 3 873.937 20.17 0.0002 Error 2318.19 35 66.234 Total 4940 38

Forest Floor Carbon Kruskal-Wallis ANOVA Table

1 2 3 4

0 1 2 3 4 5 6 7

Forest Floor Carbon Stocks (kg / hectare)

(15)

15

Figure 10: Forest Floor Carbon Stock Kruskal-Wallis ANOVA Bonferroni Multiple Comparison

Mineral Topsoil Carbon Stocks

The median carbon stocks for Waivy Hairgrass, Common Hair Moss, the group without understory and Bilberry were respectively 17017, 17572, 3695.8 and 4445.5 kg per hectare. The mean ranks (27.78 for Waivy Hairgrass, 31.5 for Common Hair Moss, 8.3 for the group without understory and 13.2 for Bilberry) were significantly different (P-value < 0.05 and Chi-Square value > 6.251) (Table 3). Thus, there is sufficient evidence that there is a significant difference between the mineral topsoil carbon stocks of some of the study groups.

Table 3: Mineral Topsoil Carbon Stock Kruskal-Wallis ANOVA table.

0 5 10 15 20 25 30 35 40 45

3 groups have mean ranks significantly different from Group 1 4

3 2 1

Comparison of Waivy Hairgrass and other Study Groups

Source SS df MS Chi-sq Prob>Chi-sq ---Groups 3698.24 3 1232.75 28.45 2.92473e-06 Error 1241.76 35 35.48 Total 4940 38

(16)

16

Figure 11: Mineral Topsoil Carbon Stock Kruskal-Wallis ANOVA Output

The pairwise comparison analyses (Figures 12 to 15) indicated that the mineral topsoil carbon stocks of Waivy Hairgrass and Common Hair Moss did not significantly differ from each other. Moreover, the mineral topsoil carbon stocks of Bilberry and the group absent of understory vegetation also did not significantly differ from each other. However, these two sets of groups (Waivy Hairgrass & Common Hair Moss, and Bilberry & No Understory) did significantly differ from each other: Waivy Hairgrass & Common Hairmoss had significantly higher mineral topsoil carbon stocks than Bilberry and the group absent of understory vegetation.

1 2 3 4

Study Groups: 1 = Waivy Hairgrass, 2 = Common Hair Moss, 3 = No Understory, 4 = Bilberry 0.5 1 1.5 2 2.5 3 3.5 4

Mineral Topsoil Carbon Stock (kg / hectare)

(17)

17

Figures 12 a, b, c, d (from top left to bottom right): Mineral Topsoil Carbon Stock Kruskal-Wallis ANOVA

Bonferroni Multiple Comparison

0 5 10 15 20 25 30 35 40

2 groups have mean ranks significantly different from Group 3

4 3 2 1

Study Groups: 1 = Waivy Hairgrass, 2 = Common Hairmoss, 3 = No Understory, 4 = Bilberry

Comparison of Waivy Hairgrass and other study groups

0 5 10 15 20 25 30 35 40

4 3 2 1

Comparison of Common Hairmoss and other study groups

0 5 10 15 20 25 30 35 40

4 3 2 1

Comparison of No Understory and other study groups

0 5 10 15 20 25 30 35 40

4 3 2 1

(18)

18

Figure 13: Comparison of the median biomass-, forest floor- and mineral topsoil carbon stocks (Caycedo, 2017).

C/N Ratio

The median C/N ratios were 19.9 for Waivy Hairgrass, 19.06 for Common Hair Moss, 9.34 for the group without understory and 12.57 for Bilberry. Moreover, the mean ranks for Waivy Hairgrass, Common Hair Moss; the group without understory and Bilberry were respectively 30.33, 28.5, 6.65 and 15.55. The difference in mean ranks gave a significant p-value and Chi-Square value (Table 4). This indicates that there is a significant difference between the mineral topsoil C/N ratios of the different study groups.

Table 4: C/N Ratio Kruskal-Wallis ANOVA table.

Biomass carbon stock Forest floor carbon stock Mineral topsoil carbon stock Legend

M edian Car bo n St oc ks (kg / he ct ar e)

Source SS df MS Chi-sq Prob>Chi-sq ---Groups 3663.75 3 1221.25 28.19 3.32048e-06 Error 1275.75 35 36.45 Total 4939.5 38

(19)

19

Figure 14: Mineral Topsoil C/N Ratio Kruskal-Wallis ANOVA Output

Moreover, the pairwise test indicated that several study groups were significantly different from each other.

Figure 18 tm 21 visualize how Waivy Hairgrass was significantly different from both Bilberry and the No

Understory group, and Common Hairmoss was significantly different from Bilberry.

1 2 3 4

Study Groups: 1 = Waivy Hairgrass, 2 = Common Hairmoss, 3 = No Understory, 4 = Bilberry 8 10 12 14 16 18 20 22 24 26 28 C/N Ratio

C/N Ratio Kruskal-Wallis ANOVA Output

0 5 10 15 20 25 30 35 40

2 groups have mean ranks significantly different from Group 3 4

3 2 1

Comparison of Waivy Hairgrass and other study groups

0 5 10 15 20 25 30 35 40

The mean ranks of groups 4 and 1 are significantly different 4

3 2 1

(20)

20 Figures 15 a,b,c,d (from top left to bottom right): Mineral Topsoil C/N Ratio Kruskal-Wallis ANOVA Bonferroni

Multiple Comparison

The grass biomass C/N ratio (3.52) was lower than the median C/N ratio of the mineral topsoil under Waivy Haigrass (19.9). The moss biomass C/N ratio was 34.24, which is higher than the median mineral topsoil C/N ratio under Common Hairmoss (namely 19.06). Moreover, the Bilberry biomass C/N ratio (3.33) was lower than Bilberry’s median mineral topsoil C/N ratio (12.57) (Table 5).

Table 5: C/N ratios of the biomass and mineral topsoil

Biomass C % Biomass N % Biomass C/N Mineral Soil C/N

Grass 501 _14.22 _3.52 _19.9

Moss 501 _1.463 _34.24 _19.06

Bilberry 501 ₁₅4 _3.33 _12.57

No Understory - - - 9.34

1 _{Hiraishi et al. (2014)} 2 _{Smit & Kooijman (2001)}

3 _{Harmens, Norris, Cooper & Hall (2008)}

4 _{Nybakken, Selas & Ohlson (2013)}

Contribution of Understory Vegetation to Total Forest Litter Fall

Vucetich et al. (2000) analysed Scots Pine litter fall at different study areas along a latitudinal gradient in

Northern Europe. They found that at the study area in Southern Poland – a site with coordinates N 50°28′38.42′ E 22°59′29.06′′ which most closely corresponded to the coordinates of the Kootwijkerzand – the total annual litter production (including wood, needle and mixed litter) was 8350 kilogram per hectare (Vucetich et al., 2000).

Moreover, the ratio method by Osipov (2016) revealed that the average annual litter fall for Waivy Hairgrass, Common Hairmoss and Bilberry was respectively 25.54, 6.08 and 2.9983 kilogram per hectare. The maximum value observed was 36.51 kilogram per hectare, which was evident within the Waivy Hairgrass group. The fact that this value is negligible compared to the 8350 kg / ha / year of Scots Pine litter as calculated by Vucetich et al. (2000) made it unnecessary to perform statistical tests with the data.

0 5 10 15 20 25 30 35 40

The mean ranks of groups 2 and 3 are significantly different

4 3 2 1

Comparison of No Understory and other study groups

0 5 10 15 20 25 30 35 40

4 3 2 1

(21)

21

Discussion

Plant litter & carbon sequestration

Before discussing the results of this research, it is relevant to note that the links between the chemical characteristics of plant litter, the carbon stock of the forest floor and mineral soil, and long-term soil carbon sequestration are not clear-cut.

Traditional humification theory states that organic material that is being incorporated into the soil is slowly transformed into longer polyaromatic structures. As this happens, the C/N ratio keeps rising. A high C/N ratio thus indicates ‘stabilization’ of carbon taking place (Stevenson, 1994). According to this theory, “lignin-derived aromatics” provide the basis for these humic substances that are formed the soil (Sollins, Swanston & Kramer, 2007). Litter with a high C/N or lignin/N ratio is thus thought by this group of scholars to decay at a slower rate than litter with a lower C/N or lignin/N ratio (Prescott, 1995; Zhang, Hui, Luo & Zhou, 2008; Aber & Melillo, 1980).

However, other researchers suggest that lignin and other ‘recalcitrant’ plant compounds are more easily decomposable that initially thought (Hilli, 2011;Kögel-Knaber, 2002; Schmidt et al., 2011). While the chemical composition of plant litter is seen as a good determinant of the initial decomposition rate, this is not the case at a later stage of decomposition (Schmidt et al., 2011). These scholars state that factors such as temperature,

moisture content, pH value, the soil microbial community and the molecular composition of the soil play a more important role in the long-term decomposition and stabilization of carbon than the chemical composition of organic material (Lehmann & Kleber, 2015; Lutzow et al., 2005; Schmidt et al., 2011). This would imply that the biotic or abiotic environment are more important than plant litter input for determining soil carbon

sequestration and stability. Moreover, it would imply that a high C/N ratio does not necessarily indicate that carbon is being ‘stabilized’ in the soil (Schmidt et al., 2011).

Understory Biomass & Forest Floor Carbon Stocks

After comparing the biomass carbon stocks for Waivy Hairgrass, Common Hair Moss and Bilberry, one could conclude that –in contract to our hypothesis – that there were no significant differences between them. However, as hypothesized, forest floor carbon stocks differed significantly between the various understory species. Waivy Hairgrass was the only study group that significantly differed from the other three groups. In other words, the presence of Waivy Hair grass seemed to result in a larger amount of carbon accumulating in the forest floor compared to the other understory vegetation species.

The forest floor carbon stock results are in line with earlier findings that different species can lead to the accumulation of different forest litter carbon stocks. When investigating the chemical properties of the forest floor under different tree species, Vesterdal & Raulund-Rasmussen (1998) found strong differences in the carbon content of the forest floors. Moreover, a study investigating the forest floor and soil carbon stocks of six tree species on the Veluwe also found significant differences (Schulp, Nabuurs, Verburg & de Waal, 2008).

As mentioned earlier, few studies have been devoted to analyzing the influence of understory vegetation on forest floor and mineral topsoil carbon stocks. However, one study investigating the influence of dwarf shrubs, mosses and pines trees on litter and soil carbon stocks in boreal forests did find that dissimilarities in the species’ litter input led to differences in forest litter carbon stocks (Hilli, Stark and Derome, 2010). Unlike in our study, the plots dominated by moss contained larger forest litter carbon stocks than the plots dominated by dwarf shrubs: in some of the sites, the total litter carbon stock under mosses was almost similar to that of the pine trees (Hilli, Stark and Derome, 2010). The discrepancy between our results and theirs could potentially be due to differences in nutrient availability. The growth of vegetation in boreal forests is limited by nitrogen availability (Nasholm et al., 1998) while the Veluwe is not nitrogen-limited. Vitt (1990) describes how moss decomposes at a quicker rate in nutrient-rich environments. Thus, moss in the Veluwe might decompose relatively quickly compared to moss in boreal forests. Moreover, differences in species and in climatic characteristics could have led to the discrepancies in the results.

The larger forest floor carbon stocks under Waivy Hairgrass were a direct result of the weight of the forest floor material. The carbon concentration of the material could not have played a role, seeing as we used

(22)

22 the 50 % carbon concentration estimate for all of the understory vegetation groups. As mentioned earlier, it proved difficult to sample the litter of Waivy Hairgrass and Common Hairmoss. For this reason, we do not have data available on the exact amount of litter input of the understory species into the soil. However, the results of this research show that Waivy Hairgrass contributes a substantial amount of litter to the forest floor compared to the other study groups. According to Scholes, Powlson & Tian (1997) the amount of litter input from vegetation strongly influences the development of soil organic matter. Moreover, as mentioned earlier, the chemical

composition of plant litter input as well as the biotic and abiotic environment are seen as important controlling factors, but there are divergent theories regarding which factor is of greater importance (Lehmann & Kleber, 2015; Schmidt et al., 2011; Scholes, Powlson & Tian, 1997). Seeing as we tried to control for environmental factors, the chemical quality of the litter might have been more important in this case for determining the size of the forest floor carbon stock.

As many complex factors influence the carbon balance of the forest floor and the soil, one cannot easily imply on the basis of these results that Waivy Hairgrass can increase the long-term storage of carbon in the forest floor or soil as compared to the other understory species. Forest floor carbon stocks are not necessarily ‘stable’ carbon stocks. The forest floor is highly influenced by environmental processes, and forest floor carbon is often quickly lost through respiration – mainly by roots and the microbial population (Franklin, Högberg, Ekblad & Ågren, 2003).The carbon turnover rate is dependent on many factors including the quality of the plant litter (the C/N ratio and nutrient availability) the microbial composition of the soil and the temperature & moisture circumstances (Prescott, 2010; Franklin, Högberg, Ekblad & Ågren, 2003). However, the forest floor’s H layer is more ‘stable’ in terms of carbon storage than the L and the F layers. We found H layers in five of the Waivy Hairgrass plots and in five of the Common Hairmoss plots, while there was only one H layer to be found in the No Understory Group, and two in the Bilberry group. This can indicate that more ‘stable’ carbon is stored under Waivy Hairgrass and Common Hairmoss.

Lastly, a large forest floor carbon stock might actually have a negative influence on the overall soil carbon balance. Researchers revealed that the input of ‘fresh’ carbon from plant litter into the soil stimulated the release of carbon from deeper soil layers (Fontaine et al., 2007). This is due to the fact that as fresh carbon is supplied to the soil, mineralization by soil microbes that were formerly nutrient-limited is activated deeper in the soil

(Fontaine et al., 2007; Fontaine, Bardoux, Abbadie & Mariotti, 2004). Thus, an input of ‘fresh’ carbon does not necessarily result in an increase in soil carbon (Fontaine, Bardoux, Abbadie & Mariotti, 2004).

Mineral topsoil carbon stocks

The results of this study revealed that, as hypothesized, there were significant differences in the mineral topsoil carbon stocks under the different understory species. Waivy Hairgrass & Common Hair Moss had significantly larger mineral topsoil carbon stocks than Bilberry & the plots lacking understory vegetation. These results might imply that the presence of Waivy Hairgrass & Common Hair Moss enhance the storage of carbon in the mineral topsoil. This is interesting in the light of carbon sequestration efforts, seeing as carbon stored in the mineral soil is relatively ‘stable’ compared to carbon stored in the forest floor (Jandl et al., 2007).

The results are in line with earlier research regarding the influence of forest species on mineral soil carbon stocks. A study by Shan, Morris & Hendrick (2001) revealed that the removal of understory vegetation led to a decrease in soil carbon stocks, due to a reduction in root growth and litter input. Bauhus, Vor, Bartsch & Cowling (2004) found that the presence of high quality litter (with a low C/N ratio) from herbaceous vegetation resulted in higher mineral topsoil carbon stocks. They hypothesized that the litter worked as an energy source for earthworms, which promoted organic matter incorporation into the mineral soil (Bauhus, Vor, Bartsch & Cowling, 2004). Hilli, Stark and Derome (2010) revealed that differences in litter input by dwarf shrubs, mosses and trees led to significant differences in both the quantity and the quality of soil organic carbon stocks. Moreover, many studies found significant differences in carbon stocks as a result of different tree species (Vesterdal et al., 2008; Oostra, Majdi & Olsson, 2006; Finzi, Van Breemen & Canham, 1998; Schulp et al., 2008).

The larger carbon stocks under Waivy Hairgrass & Common Hair Moss could be explained by the fact that these species have specific properties that influence soil processes such that the accumulation of carbon in soil stocks is stimulated. For instance, mosses are known to fix carbon from the atmosphere, as well as

influencing the soil climate through moisture enhancement and temperature reduction. Temperate grasslands are known to store relatively high amounts of soil organic carbon as a result of amongst other things specific nutrient-use traits, the attraction ecosystem engineers and interactions with fungi that stimulate carbon

(23)

23

sequestration (De Deyn, Cornelissen & Bardgett, 2008). Moreover, the higher carbon stocks could be a result of differences in litter input and decomposition. Several studies have indicated that moss litter decomposed at a slower rate than other types of plant litter (Lang et al., 2009; Hilli, Stark & Derome, 2010; Liu, Fox & Xu, 2000; Hobbie, 1996; Berg, 1984). Conversely, several researchers have found that Bilberry leaves decomposition at a very quick rate (Hilli, Stark & Jerome, 2010; Hobbie, 1996; Johansson, 1993).

Interestingly, while Waivy Hairgrass had a significantly larger forest floor carbon stock than all of the other groups, its mineral topsoil carbon stock was not significantly larger than Common Hairmoss. Clearly, a high forest floor carbon stock does not necessarily result in a high mineral topsoil carbon stock. This result could be explained by the fact proposed earlier, that the input of ‘fresh’ carbon from plant litter stimulates the

mineralization of carbon from the soil (Fontaine, Bardoux, Abbadie & Mariotti, 2004). The combined forest floor and soil carbon stock is thus ‘levelled off’ as a result of a higher forest floor carbon stock. Studies analysing the forest floor carbon stocks and soil carbon stocks under different tree species confirmed this effect. They indicated that the species with higher forest floor carbon stocks had relatively low soil carbon stocks and in reverse (Vesterdal et al., 2008; Oostra, Majdi & Olsson, 2006). However, a similar study featuring understory vegetation has yet to be performed.

Another reason that a high forest floor carbon stock doesn’t necessarily coincide with a high mineral topsoil stock is the fact that separate processes influence carbon storage in the forest floor and the mineral soil. Berg et al (2008) explained how forest floor carbon storage is mainly influenced by plant litter input, while mineral soil carbon storage is a function of rhizodeposition as well as leakage from organic material in the forest floor. Kögel-Knaber confirms that rhizodeposition is an important carbon source for soils (Kögel-Knaber, 2002). Thus, information on rhizodeposition for the different understory groups would be valuable. C/N Ratios

Our hypothesis regarding differences in the C/N ratio of the mineral topsoil under the various understory species turned out to be correct. Waivy Hairgrass & Common Hair Moss had significantly larger C/N ratios than Bilberry & the plots lacking understory vegetation. The C/N ratios of Waivy Hairgrass & Common Hair Moss were not significantly different; neither were the C/N ratios of Bilberry & the plots lacking understory vegetation.

While as far as we know no other studies have analysed the influence of different understory species on mineral soil C/N ratios, other studies did find divergent C/N ratios as a result of different tree species (Vesterdal et al, 2008; Finzi, Van Breemen & Canham, 1998; Cools et al., 2014).

Interestingly, we estimated that while the C/N ratio of Bilberry and Waivy Hairgrass biomass was lower than the median C/N ratio of the mineral topsoil under these species, the C/N ratio of Common Hairmoss biomass was higher than its median mineral topsoil C/N ratio. Moreover, it is remarkable that the biomass C/N ratio of Waivy Hairgrass and Bilberry is ten times as small as the moss biomass C/N ratio due to the much lower N concentration in moss biomass. For Common Hairmoss, the average percent ‘decrease’ for both the C & N content from biomass to mineral topsoil was smaller relative to the other groups. The significantly stronger ‘decrease’ in N content for Bilberry and Waivy Hairgrass from biomass to mineral topsoil resulted in the higher C/N content. This could imply that - compared to the other species – relatively less C and N is ‘lost’ during the transformation from Common Hairmoss biomass to organic matter in the mineral topsoil.

As mentioned earlier, a high C/N ratio does not necessarily indicate that carbon is being stabilized in the soil. When investigating carbon sequestration in temperature forests, Alberti et al. (2015) found that at a high soil C/N ratio, microbes have low carbon use efficiency, thus they respire more carbon while priming the decay of soil organic matter. Conversely, in soils with a low C/N ratio (<15), the carbon use efficiency is higher and there is a net formation of soil organic matter (Alberti et al., 2015).Other research has indicated that litter with a high C/N ratio that is incorporated into the mineral soil has found to enhance the soil’s C/N ratio for a relatively short period of time, after which the soil returns to a more balanced C/N ratio (Johnson & Curtis, 2001). Fontaine et al. (2014) also found that a nutrient shortage for soil microbes led to decreased carbon accumulation in soils.

Moreover, many researchers propose that in temperate forests, nitrogen deposition can actually enhance the soil organic carbon stock (Lal, 2005; Janssens et al., 2010; Stockmann et al., 2013; Frey et al., 2014). This is due to the fact that the addition of nitrogen inhibits or slows down decomposition processes, subsequently

(24)

24

enhancing the sequestration of carbon (Jansen et al., 2010; Adams et al., 2005; De Marco et al., 2016).Besides this, the addition of nitrogen to nitrogen-limited forests resulted in the enhancement of biomass growth and thus a larger input of carbon into the soil (Janssens et al., 2010; Bonan & Cleve, 1992). However, as the Veluwe are not nitrogen-limited, this would probably not be the case there.

It would be useful to empirically analyse the C/N ratios and other chemical qualities of the understory biomass and litter, seeing as this can help us come to solid conclusions about the relative amounts of carbon that are released during the transformation of plant material into soil organic matter. Moreover, further research regarding the molecular composition and the microbial biomass of the soil, and their interactions with the understory vegetation litter is necessary to understand the processes inherent to the apparent changes in C/N ratio from biomass to mineral topsoil.

Contribution of understory vegetation to total litter fall

When estimating the contribution of understory litter fall to total forest litter fall, we found that – in contrary to our hypothesis - the contribution of understory litter fall was extremely small compared to the rest of the forest litter fall. However, one must mention that the method used to test this hypothesis might not have been entirely reliable, as data was taken from studies performed in forests situated in other geographic locations. Thus, plant biomasses, annual plant growth rates and annual litter fall production of pine trees and understory vegetation in these forests most likely differ from the Kootwijkerzand Scots Pine forests. Therefore, it is possible that we made a Type II error: the null hypothesis was incorrectly retained.

In order to estimate the contribution of understory vegetation to total litter fall, the initial plan was to empirically sample pine litter and the understory litter separately in the field and weigh it in the laboratory. However, we encountered several issues during the course of this research project that made it difficult to achieve this.

Firstly, while it was possible to sample the pine litter, it proved to be difficult to collect understory litter samples for two of the study groups. The study groups in question were Waivy Hairgrass and Common Hair Moss. This had to do with the fact that there was no real plant litter that could be collected from the surface, because these species do not contribute plant material to the forest floor in a similar way that trees or bushes do. These species contribute plant material to the forest floor as their roots or leaves die off while still attached to the living plant, where after the plant material slowly decomposes and is integrated into the forest floor (Hilli, Stark & Derome, 2010). We were not prepared for this during the fieldwork trip. As a result of this we did not have the equipment and expertise to collect the moss and grass litter in a proper manner.

Moreover, the time scale of this research project proved to be unsuitable to perform a bona fide litter fall study. This research project was executed over the course of three months, and within this time period there was only room for one three-day fieldwork trip to the study area in April. This didn’t allow us to take into account local, seasonal and/or annual patterns in litter fall for the species that were analysed. For instance, Scots Pine trees have appeared to exhibit inter-annual changes in litter fall (Portillo-Estrada, 2013). Moreover, Scots Pine litter fall differs per season and per latitude. Berg et al. (1999) stated that at the latitude of Berlin, which is very similar to the latitude of the Kootwijkerzand, Scots Pine litter fall mainly takes place in late October / early November (Berg et al., 1999).

Referring back to the research question: “Is the relative contribution of three different groups of

understory vegetation to plant litter in Dutch pine forests near Kootwijk 5 % or larger?” we can conclude on the basis of the results that this is not the case. Our hypothesis was based on the idea that a contribution larger than 5 % could imply that understory litter plays a larger role in forest soil-forming processes than formerly thought. However, even though the null hypothesis was not rejected, one must mention that understory vegetation can still influence forest soil forming processes in other ways. For instance, several studies have revealed that the presence of understory vegetation leads to the delayed composition of pine litter in forests, as it forms a barrier that tree litter has to pass before it reaches the forest soil (He et al., 2013; Hagvar, 2016). Moreover, understory vegetation, including bilberry, can hamper the seedling regeneration and early growth of Scots Pine trees (Jaderlund et al., 1998). These processes could imply that the influence of pine trees on forest soil forming processes is dampened by the presence of understory vegetation. Processes like this should be taken into

(25)

25 account in future research regarding the interactions between trees, understory vegetation and carbon in forest floors and mineral soils.

Implications of the results

The first implication of this study is of a political nature. The Netherlands has the obligation to report to the UNFCCC on national carbon stock changes in the Agriculture, Forest & Other Land-uses Sector. The Dutch Ministry of Infrastructure and Environment is responsible for this (Arets et al., 2016). Forest floor carbon represents a large part of the Dutch carbon stock (Schulp et al., 2008). When estimating Forest Land carbon stock changes, the UNFCCC encourages countries to use the ‘stock difference method’, which entails a formula that includes the total forest area, the change in forested area, and whether a forest is primary, planted or naturally regenerated. No attention is paid to the spatial distribution of trees or understory vegetation (Tubiello et al., 2014). Researchers already proposed that forest floor carbon stock estimations would benefit from more detailed measurements that take tree species into account (Schulp et al., 2008; Woodall, Perry & Westfall, 2012). This research project shed light on the fact that besides tree species, understory vegetation can significantly influence forest floor carbon stocks. This means that the presence and spatial distribution of understory

vegetation should potentially also be taken into account when estimating national carbon stocks. However, more research is necessary to determine whether the results of this research project are applicable on a national scale.

Secondly, forest management for carbon sequestration has recently been gaining attention as a potentially effective measure for CO2 mitigation. However, there is still discussion among scientists regarding proper management strategies to enhance carbon sequestration in forest soils (Jandl et al., 2007; Lal, 2005; Noormets et al., 2015). This research project proved that more carbon is stored in the forest floor and mineral topsoil under some understory vegetation species than others. This entails that forest understory vegetation species should possibly be taken into account when determining adequate forest management techniques to maximize carbon storage. The planting of specific species such as grasses and mosses might allow carbon storage in pine forests to be maximized, seeing as these species inherit characteristics that are beneficial to carbon sequestration (Lang et al., 2009; Hilli, Stark & Derome, 2010; Liu, Fox & Xu, 2000; Hobbie, 1996; Berg, 1984; De Deyn,

Cornelissen & Bardgett, 2008). However, long-term studies on carbon storage dynamics in the forest floor & soil after the plantation of understory species are necessary to investigate whether this is possible.

Thirdly, as this research sought to control for environmental factors among all plots, one can imply on the basis of the results that understory litter input might be an important determinant of carbon storage in the soil. This does not coincide with the idea among researchers that instead of plant litter input; abiotic and biotic factors are the most important determinants of soil carbon storage (Schmidt et al., 2011; Lehmann & Kleber, 2015). However, this research did not analyse the possible relationship between the understory litter and the stability of the carbon found in forest floor and carbon stocks. Further research should address this ‘stability’ of the carbon pool under the different species.

Recommendations

As this research project was not able to provide a reliable answer to the question whether the contribution of understory litter to total forest litter fall is more than 5 %, we recommend future studies to analyse this further. In order to account for local, seasonal and/or annual patterns in litter fall, a different fieldwork set up is

required. Most empirical litter studies aiming to analyse the litter fall of forest vegetation species were carried out over the course of one or more years in order to estimate a species’ annual litter production. In order to achieve this, litter samples were either collected straight from the forest floor in set areas several times during the research period (Hilli, Stark & Derome, 2010; Vucetich et al., 2000), or litter traps were placed on the forest floor and routinely sampled with intervals (Osipov, 2016; Barlow, Gardner, Ferreira & Peres, 2007; Peichl & Arain, 2006; Richter et al., 1999; Johansson, 1993; Winterbourn, 1976; Berg et al., 1999; Bjorn et al, 1993; Bauhus, Vor, Bartsch & Cowling, 2004). Thus, future research projects should span at least a year, and make use of litter traps in order to routinely collect litter from trees and bushes.

(26)

26 Moreover, future litter studies should take into account the difficulties regarding the collection of moss and grass litter. Hilli, Stark & Derome (2010) sampled moss litter by removing the entire aboveground moss biomass from set areas in the field, and subsequently removing the dead pieces of moss (the necromass) from the living plants in the laboratory to use for further analysis. The necromass is characterized by its brownish/yellowish color (Hilli, Stark & Derome, 2010). Future studies could use a similar method to sample low understory vegetation such as mosses and grasses.

Besides this, it would be valuable to study the complex interactions between trees, understory vegetation and soils in forests. The mentioned delay in tree litter decomposition in the presence of understory vegetation

(He et al., 2013; Hagvar, 2016) could be analyzed for different understory vegetation groups, in order to gain further insight into the manner in which different understory species affect soil forming processes in forests. Moreover, the mentioned influence of understory vegetation on tree growth (Jaderlund et al., 1998) should be investigated.

Several researchers state the importance of roots in the formation of soil organic matter in forest soils

(Clemmensen et al., 2013; Kögel-Knabner, 2002; Schmidt et al., 2011). Thus, it would be valuable to gain more insight into the influence of understory root litter on carbon stocks in the soil. A study sampling root litter and evaluating the chemical composition of this litter in relation to the soil could help achieve this.

Similarly, empirical information is needed regarding the chemical composition – including the C/N ratio - of the biomass and litter for the various understory species. This information could allow us to gain more insight into the ‘carbon balance’ for the different understory species during decomposition.

Moreover, empirical analyses of the soil chemical composition, the soil microbial community and

environmental factors such as the pH value should be undertaken. This information could help us to understand the exact processes at play during the transformation of understory plant litter into soil organic matter. It would also help us to gain insight into the stability of the carbon pools under the different species.

With regard to carbon sequestration efforts, it is necessary to perform more empirical analyses in order to support the idea that certain understory species can be beneficial for carbon sequestration in forests. It would be useful to perform a study in which grasses or mosses are planted in a forest, and the carbon balance is measured over a longer period of time. This could help support our hypothesis that planting specific species can help maximize carbon storage in forests.

Lastly, it would be valuable if similar studies were performed in other Dutch forests and with other soils. Besides validating our results, studies like this could help determine whether the results are applicable on a national scale. This could bolster the idea that understory species should indeed be taken into account when estimating national forest floor carbon stock estimations.

(27)

27

Conclusion

This research project aimed to shed light on the influence of understory species on carbon storage in Dutch pine forests near the Kootwijkerzand by analysing the carbon stocks of the biomass, forest floor and mineral topsoil as well as the C/N ratio for different understory species. Moreover, it analysed the contribution of understory litter to total forest litter fall in order to check the assumption of Kögel-Knaber (2002) that this contribution is less than 5 %.

The results revealed that understory species significantly influence carbon storage in the forest floor and in the mineral topsoil. Waivy Hairgrass had a significantly higher forest floor carbon stock compared to Bilberry, Common Hairmoss and the group without understory vegetation. Additionally, Waivy Hairgrass and Common Hairmoss had significantly higher mineral topsoil carbon stocks than Bilberry and the group without understory vegetation. The biomass carbon stocks of the different understory species did not significantly differ from each other. Moreover, the C/N ratios of Waivy Hairgrass and Common Hairmoss were significantly higher than the C/N ratios of the other two study groups. While the C/N ratio of Common Hairmoss biomass was smaller than the C/N ratio of its mineral topsoil, the C/N ratio of Bilberry and Waivy Hairgrass biomass was larger than their mineral topsoil C/N ratios.

Despite the detected influence of understory species on carbon stocks, we found the contribution of understory litter fall to total litter fall to be less than 5 %. However, we were not able to empirically measure this and the data we used to calculate the contribution might not be entirely reliable.

On the basis of these results, we can imply that Waivy Hairgrass and Common Hairmoss are beneficial for carbon storage in Scots Pine forest soils. This might be due to the fact that they inherent certain characteristics that aid carbon sequestration. Thus, these species could potentially be used to maximize carbon storage in Scots Pine forest soils. However, long-term empirical research is necessary to determine whether the planting of these species can in fact lead to the enhancement (and stabilization) of carbon in the soil. In the light of pressing climate change issues, such research could potentially be of great importance to national and international policy making.

Future research should also focus on studying the chemical composition (including the C/N ratio) of the understory biomass and litter, as well as the soil chemical composition, the soil microbial biomass and other environmental factors such as the soil’s pH value. This information could help gain insight into the stability of the carbon pool under the different species and the carbon balance during the transformation of plant material into soil organic matter. Moreover, long-term empirical research should be carried out to study the contribution of understory litter fall to total litter fall in the study area.

(28)

28

Bibliography

Aber, J. D., & Melillo, J. M. (1980). Litter decomposition: measuring relative contributions of organic matter and nitrogen to forest soils. Canadian Journal of Botany, 58(4), 416-421.

Adams, A. B., Harrison, R. B., Sletten, R. S., Strahm, B. D., Turnblom, E. C., & Jensen, C. M. (2005). Nitrogen-fertilization impacts on carbon sequestration and flux in managed coastal Douglas-fir stands of the Pacific Northwest. Forest Ecology and Management, 220(1), 313-325.

Alberti, G., Vicca, S., Inglima, I., Belelli-Marchesini, L., Genesio, L., Miglietta, F., & Peressotti, A. (2015). Soil C: N stoichiometry controls carbon sink partitioning between above-ground tree biomass and soil organic matter in high fertility forests. iForest-Biogeosciences and Forestry, 8(2), 195.

Algemene Vereniging Inlands Hout BRBS Recycling Branche Vereniging Organische Reststoffen Form International HVC Groep Koninklijke Vereniging van Nederlandse Houtondernemingen Koninklijke Vereniging van Nederlandse Papier- en Kartonfabrieken Nationaal Bossenfonds Nederlandse

Branchevereniging voor de Timmerindustrie Nederlandse Emballage- en Palletindustrievereniging Platform Bio-Energie Staatsbosbeheer Stichting EcoBouw Nederland Stichting Nationale Boomfeestdag Stichting Natuur & Milieu Stichting Probos Trees for All Unie van Bosgroepen Vereniging van Bos- en Natuurterreineigenaren (2017). Actieplan Bos en Hout. Wageningen: Wageningen University.

Averill, C., Turner, B. L., & Finzi, A. C. (2014). Mycorrhiza-mediated competition between plants and decomposers drives soil carbon storage. Nature, 505(7484), 543-545.

Arets, E. J. M. M., van der Kolk, J. W. H., Hengeveld, G. M., Lesschen, J. P., Kramer, H., Kuikman, P. J., & Schelhaas, M. (2015). Greenhouse gas reporting for the LULUCF sector in the Netherlands (No. 52). Statutory Research Tasks Unit for Nature & the Environment (WOT Natuur & Milieu).

Barlow, J., Gardner, T. A., Ferreira, L. V., & Peres, C. A. (2007). Litter fall and decomposition in primary, secondary and plantation forests in the Brazilian Amazon. Forest Ecology and Management, 247(1), 91-97. Bauhus, J., Vor, T., Bartsch, N., & Cowling, A. (2004). The effects of gaps and liming on forest floor

decomposition and soil C and N dynamics in a Fagus sylvatica forest. Canadian Journal of Forest Research, 34(3), 509-518.

Bayat, A. T. (2011). Carbon Stock in an Apennine Beech Forest. Enschede, The Netherlands: University of Twente. Berg, B. (1984). Decomposition of moss litter in a mature Scots pine forest. Pedobiologia , 26, 301–308. Berg, B., Albrektson, A., Berg, M. P., Cortina, J., Johansson, M. B., Gallardo, A. & McClaugherty, C. (1999). Amounts of litter fall in some pine forests in a European transect, in particular Scots pine. Annals of Forest

Science, 56(8), 625-639.

Berg, B.; McClaugherty, C.; De Virzo Santo, A. (2008). Practicalities of estimating carbon sequestration—Boreal coniferous

forests. CAB Rev. Perspect. Agric. Vet. Sci. Nutr. Nat. Resour, 3, 84.

Bijlsma, R. J., Janssen, J. A. M., Weeda, E. J., & Griffioen, A. J. (2015). Vegetatie-, beheer-en habitattypen van Het

A Story About Understory: The Influence of Understory Species on Carbon Storage in Scots Pine Forests Around the Kootwijkerzand.