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Field sampling
The sampling took place in mid-March 2018 (at the very beginning of spring season) when roots are growing slowly or not at all, and that allowed us to minimize soil core losses (soil not too dry neither too wet). We harvested litter and soil cores (90 cm deep) from four sampling points within each plot, with each sampling point located at the centre of square with four alive trees (see Table 3.1 for number of live trees per plot). Firstly, we collected the forest floor litter within a rectangular frame of 10 × 20 cm. Then, the top 0–15 cm of soil was collected manually with a soil corer (8 cm Ø). The bottom 15–90 cm of soil was collected with a mechanical drill, attached onto a gouge (4 cm Ø). We aimed at drilling and collecting soil cores down to 120 cm, but we could not always sample the 90–120 cm layer. The soil from the lower part of the soil column fell out at the lower side of the gouge in many cases, rendering our sampling incomplete. The few samples from 90–120 cm layer that we managed to collect, did not have any roots and roots were rarely found in the lower part of the 60–90 cm layer. Hence, we chose to analyse only samples down to 90 cm, assuming this depth permits to sample all fine roots under our site conditions. The hardpan was discontinuous and not encountered at all the sampling points (51 out of 96 sampling points), but when occurring it was detected at an average depth of about 50 cm below the surface, and it varied from friable to very dense with an average thickness of 17 cm (Table 3.1). After collection, the soil cores were carefully separated into five layers (0–5; 5–15; 15–30; 30–60; 60–90 cm), and together with the forest floor samples stored at 4°C before further analysis.
A full inventory of stem diameters for all alive trees per plot was performed at the end of 2017 (10 years-old trees since plantation). In June-July 2018, we recorded soil cover of understory vegetation around each sample point (four for each plot) and made inside plot measurements of stem diameters and canopy dimensions of the four bordering trees around each sampling point. For measurements on understory, we used standardized patterns of cover and recordings were done by the same experienced operators. For measurement on trees, their diameters and the longest canopy branches in four directions (two perpendicular to the tree line, two in the direction of the tree) were measured. The canopy extension (in m2) of each tree was computed by using the four largest branches and assuming a vertical projection on the forest floor. The canopy ratio was then defined as the canopy extension divided by 4 m2 (the theoretical space of each tree in the design). Values higher than 1 mean that the tree occupies more than this space (see Table 3.1 for summary descriptors of the stand density, diameter, basal area, and canopy dimension), which is the case here, as pine extended its canopy (average canopy ratio: 1.46 under control conditions, and 1.46 under irrigation) into birch (average canopy ratio: 0.88 under control conditions, and 0.83 under irrigation) and directly competes for light (canopy closure) (Table 3.1).
Table 3. 1 Overview table of stand characteristics at 10 years-old. Values are means (± standard deviations) of 36 centre trees per plot (alive and measurable trees at breast height 130 cm) repeated across 8 blocks (4 blocks are irrigated and 4 blocks are not).
a Daily irrigation from May to October equivalent to about 3 mm day -1
b Mean values based on plot averages for four blocks (max = 36 in pure stand, 18 in mixed stands)
c Using quadratic means for mean DBH at 130 cm
d Mean values based on the sum of alive and measurable trees at the plot level
e Measurements performed on the 4 bordering trees for each sampling point
f Depth of hardpan encountered at the sampling date
g Hardpan thickness at the sampling date
Root sorting
The soil cores were passed briefly on a 2 mm mesh size sieve, in order to separate roots from bulk soil by hand, which is adequate for our sandy soils. The roots retrieved this way were then soaked in water, and fine roots (≤ 2 mm Ø) were separated into the different target species (birch, pine) and understory species (Bracken, Purple moor-grass, Common Gorse, Bell heather, Common heather, Alder buckthorn, European honeysuckle). Fine roots (≤ 2 mm Ø) are essential for water and nutrient uptake (Jackson et al. 1997) and are the ones most affected by change in environmental conditions (Ostonen et al. 2007b). Root fractions greater than 2 mm in diameter were not common in our samples and were not considered here. This is also because small cores are not appropriate to investigate medium root and coarse root distributions. We removed dead roots, which we identified by the presence of dark discoloration of the central cylinder and decreased flexibility of root segments (Bauhus and Messier 1999). Birch and pine roots were identified visually according to root colour, epidermis texture, root tip ectomycorrhizal colonization, and root tip ramifications. Both birch and pine are associated with ectomycorrhizal fungi; birch is very ramified, with reddish colour, and smooth epidermis, while pine is much less ramified, with characteristic dichotomous root tips, and rougher epidermis. To recognize between the understory species, we uprooted whole plants of each species and kept them as reference material. In addition, distinctive descriptions were already available from Bakker et al. (2006).
Additionally, after separating roots from soil, we assessed soil moisture for each sample by comparing the fresh soil weight to the dry soil weighed after 72 h at 105°C. Composites of the four cores were made for each soil layer per plot, and these samples were then air-dried for chemical analysis (3 species treat. × 2 water treat. × 4 blocks × 5 depths = 120 samples) (see Table B3.2 in Appendix B).
Data collection and computation of root morphology variables
Birch and pine fine roots were scanned using the WinRhizo Software (version 2005a, Regents Instruments Inc. Canada). To measure the fine root morphology, we selected two or three largely intact fine roots (< 2 mm Ø) as a subsample for scans. The roots were placed in a transparent water filled tray (20 × 30 cm), and roots were spread as much as possible, while trying to keep complete roots intact. The root density was kept at approximatively 0.5 mm root per mm2 surface (Bouma et al. 2000), and the image resolution was 800 dpi. The roots were not stained. After scanning, the scanned roots were oven-dried for four days at 40°C and weighed. This analysis provided data on fine root length, fine root surface area, root tip abundance, which were used to calculate: Specific Root Length (SRL) (fine root length/ dry root weight), Specific Root Area (SRA) (fine root area/ dry root weight), and Specific Root Tip Density (SRTD) (number of root tips / dry root weight). The root morphology indicators were calculated based on existing indicators (Comas and Eissenstat 2009; Godbold et al. 2003; Jagodziński and Kałucka 2011). We further used the scans to extract data on the distribution of fine root length per diameter class (0.0 – 0.5 mm; 0.5 – 1.0 mm; 1.0 – 1.5 mm; 1.5 – 2.0 mm) (see Fig. B3.5 in Appendix B), with a particular interest in the very fine root fraction (diameter class of 0.0 – 0.5 mm Ø). The very fine root fraction is usually occupied by 1st and 2nd root orders (most distal parts of the root system), which have been observed to be more sensitive to environmental factors and to soil depth than higher root orders (Makita et al. 2011; Ostonen et al. 2007b). Hence, we calculated fine root fraction (fine root length per diameter class), as a percentage of the total fine root length; all diameter classes (≤ 2 mm Ø summed). The remaining root fragments (not subsampled for the scans), were also dried and weighed to compute total root parameters for each soil layer. With the dried fine root biomass, we calculated Fine root mass density (FRMD) (dry root weight / soil volume) which we used to investigate how fine root mass density changed with soil depth.
Table of contents :
Chapter 1 | Introduction
1.1 Changes in climate and biodiversity
1.2 Importance of roots for nutrient cycling
1.3 General aspects of biodiversity belowground
1.4 Fine root dynamics
1.4.1 Environmental effects on fine root dynamics
1.4.2 Biodiversity effects and resource availability
1.5 Decomposition
1.5.1 Climate and trait control on the decomposition of leaves and roots
1.5.2 Direct and indirect effects of tree diversity on decomposition
1.6 Rationale and research questions
References
Chapter 2 | Materials and Methods
2.1 Study design
2.2 Site description
2.3 Methods
2.3.1 Tree species studied and tree inventory
2.3.2 Belowground productivity and turnover
2.3.3 Vertical root profiles
2.3.4 Decomposition
2.3.5 Soil analyses
2.4 Data treatment
2.5 Organization of the Result chapters
References
Chapter 3 | Effect of tree mixtures and water availability on belowground complementarity of fine roots of birch and pine planted on sandy podzol
3.1 Introduction
3.2 Materials and Methods
3.2.1 Study site
3.2.2 Field sampling
3.2.3 Root sorting
3.2.4 Data collection and computation of root morphology variables
3.2.5 Calculation of vertical root distribution index
3.2.6 Calculation of diversity metrics
3.2.7 Data analysis
3.3 Results
3.3.1 Overall treatment effects on fine root biomass and morphology
3.3.2 Vertical root patterns
3.3.3 Relative fine root attributes
3.4 Discussion
3.4.1 General considerations
3.4.2 Effect of mixing tree species on vertical root segregation and belowground overyielding
3.4.3 Pronounced vertical root segregation and belowground overyielding under ambient water supply
3.4.4 Depth-specific effects on relative yield
3.5 Conclusion
Acknowledgements
References
Chapter 4 | Fine root dynamics in response to tree species mixing, stand density, and water availability
Abstract
4.1 Introduction
4.2 Materials and Methods
4.2.1 Study site and experimental design
4.2.2 Fine root production and turnover
4.2.3 Fine root decomposition
4.2.4 Chemical analysis of roots
4.2.5 Root litter input and C, N, P fluxes in the soil
4.2.6 Data analysis
4.3 Results
4.3.1 Differences in fine root morphology and chemistry between species, and between ingrowth cores and root standing biomass cores
4.3.2 Fine root production and turnover
4.3.3 Fine root decomposition
4.4 Discussion
4.4.1 General considerations
4.4.2 Effect of tree species mixing
4.4.3 Effect of stand density
4.4.4 Effect of irrigation
4.4.5 Implications for carbon and nutrient cycling
4.5 Conclusion
