Introduction

Silicon (Si) influences global biogeochemical processes on long timescales as a result of CO2 neutralization by silicate weathering (Berner 1997) and the essentiality of dissolved silicon (DSi) for phytoplankton CO2 consumers (Conley et al. 1993). On shorter timescales, part of the DSi released by mineral weathering is cycled through vegetation on the earth’s surface (Conley 2002; Derry et al. 2005) before its land-ocean transfer, which contributes to 80% of the ocean’s DSi load (Tréguer et al. 1995). Si is released in soil solutions as monosilicic acid (H4SiO 04 ), which is then translocated to the transpiration sites where polymerization of hydrated amorphous silica occurs to form phytoliths (Jones and Handreck 1965; Casey et al. 2003). Higher plants can accumulate Si, a non-essential but beneficial element, as amorphous biogenic silica (BSi) to a similar degree as some major macronutrients: 0.1–10% (Epstein 1999). In keeping with active, passive or exclusive mechanisms with respect to Si uptake, plant species are classified as high-, intermediate-, or non-accumulators respectively (Takahashi et al. 1990). Hodson et al. (2005) studied phylogenetic variations in the Si composition of plants and demonstrated that gymnosperms and angiosperms accumulate less Si in their shoots than non-vascular plant species and horsetails. In temperate forest ecosystems, previous studies show that the Si uptake varies considerably, ranging between 2 and 44 kg Si ha−1 yr−1 (Bartoli 1983; Markewitz and Richter 1998; Fulweiler and Nixon 2005; Gérard et al. 2008; Cornelis et al. 2010). The major part of the Si uptake returns to the topsoil through litterfall as a reactive BSi pool (Fraysse et al. 2009), this being an ubiquitous and substantial component of forest soil (Drees et al. 1989; Saccone et al. 2007; Conley et al. 2008). In northeast USA at the Hubbard Brook Experimental Forest, the greater DSi leaching to the hydrosphere with deforestation can be attributed to the dissolution of the amorphous biogenic silica which was restored to the topsoil (Conley et al. 2008). Thus, the study of mechanisms controlling the contrasting Si biocycling by tree species is a critical step to improve our knowledge of Si mass-balance in soil-tree systems. The annual Si uptake clearly depends on tree species since a strong difference in Si absorption rates was observed between Douglas fir and Black pine (Cornelis et al. 2010): Pseudotsuga menziesii (30.6 ± 8.0 kg Si ha−1 yr−1) >> Pinus nigra (2.3 ± 0.9 kg Si ha−1 yr−1) in strictly identical climatic and soil conditions. The different accumulation of Si in aerial parts may be due to the varying abilities of Si root-uptake, soil mineralogical composition (Klein and Geis 1978), transpiration rate and availability of silicic acid in the forest soil solution (Jones and Handreck 1967; Hodson and Sangster 1999). Gérard et al. (2008) suggest that Douglas fir on a forest site actively absorbs Si from the soil solution to explain the decrease in DSi concentrations with soil depth and equilibrate mass balance calculations of the Si uptake flux. However, this field study did not consider the impact of pedogenic Si-sinks (i.e. secondary minerals formation and Si adsorption onto Fe oxides), which can also induce a lower DSi concentration in solution. Thus, the mechanisms controlling the effects of tree species on Si biocycling have not yet been elucidated. Furthermore, such a difference of Si concentration in forest vegetation could affect tree seedling growth. Although silicon is not traditionally considered to be an essential plant element (Epstein 1999; Ma and Takahashi 2002; Ma and Yamaji 2006; Liang et al. 2007), many studies have shown its beneficial effect on plant growth and yield (Korndorfer and Lepsch 2001; Ma and Takahashi 2002; Ma 2004), which is more clearly expressed under stress conditions (Epstein 1994; Bélanger et al. 1995). However, besides the study of Emadian and Newton (1989) that demonstrates the beneficial effect of Si supply on pine seedling growth under water-stress conditions, the effect of a wide range of Si supply on the Si uptake and growth of different coniferous tree seedlings in optimal conditions has never been studied.

Here, we set out to (1) understand the contrasting Si uptake between Douglas fir and Black pine and (2) measure the effect of Si on the growth of tree seedlings. Pseudotsuga menziesii and Pinus nigra seedlings were therefore grown for 11 weeks in hydroponics with a wide range of Si concentrations in the nutrient solution (0.2 to 1.6 mM).

Materials and methods

Hydroponic growth conditions

The seeds were collected from Pseudotsuga menziensii Franco stands in Belgium and from Pinus nigra Arn. Ssp laricio Poiret var corsicana stands in France. Tree seeds were surface- sterilized with 5% H2O2 and rinsed five times with demineralized water. The seeds were germinated for 15 days in the dark at day/night temperatures of 20/18°C. They were then weaned for 30 days in nutrient solution tanks before uniform seedlings were selected for the experiments. Batches of six seedlings were grown in separate cylindrical PVC pots containing 2.5 l of nutrient solution and placed on a perforated plate of expanded polystyrene which limits water loss by evaporation. The experiment was conducted over 11 weeks in growth chambers with a 448 µE m−2 s−1 photon density flux for 8 h per day, 75% relative humidity, and day/night temperatures of 20/18°C. The nutrient solution was obtained by mixing salts, boric acid and FeEDTA to reach the following concentrations and match common tree seedling nutrient requirements (Ingestad 1971): Ca(NO3)2 (4.8 mM), CaSO4 (1.6 mM), CaCl2 (1.6 mM), KCl (4.0 mM), K2SO4 (4.0 mM), MgCl2 (0.4 mM), MgSO4 (0.4 mM), NH4Cl (3.2 mM), (NH4)2SO4 (3.2 mM), (0.2 mM), H3BO3 (80 µM), FeEDTA (80 µM), MnCl2 (8 µM), ZnSO4 (0.8 µM), CuSO4 (0.8 µM) and (NH4)6Mo7O24 (5.6 µM). Since the nutrient solution was not renewed, the ion concentrations were calculated to maintain an optimum nutrient status during the experiment. As suggested by Ingestad (1971), we used an optimum NH4–N/NO3–N ratio (40/60). Si was supplied at three different concentrations (0.2, 0.8 and 1.6 mM) for each tree species. Three replicates of six seedlings per pot were repeated for each concentration and for each tree species. As described by Henriet et al. (2006), Si was supplied as H4SiO4 obtained by dissolving sodium metasilicate in demineralized water, followed by leaching on a protonated cation-exchange resin (Amberlite® IR-120). Neither Si precipitation nor H4SiO4 deprotonation was expected because Si concentration was below the solubility limit (<1.79 mM Si) and pH ranged between 5 and 6.5 (Stumm and Morgan 1996).

Sampling and Si analysis

Twice a week, the volumes of the remaining solutions were weighed to estimate water loss, which was immediately balanced by adding demineralized water. Water loss through evaporation, measured in the six control pots, was 6.2 ± 1.9 ml day−1. Cumulative water uptake was calculated as the difference between water loss and evaporation. The potential Si uptake by mass flow (MFU) was defined by the product of water uptake and Si concentration in the nutrient solution. The MFUs were calculated for each sampling period (twice a week) and summed up for the whole period (77 days). For this purpose, two ml of the nutrient solution were sampled twice a week from each pot after mixing and Si concentration was measured by ICP-AES (inductively coupled plasma—atomic emission spectrometry). Moreover, we measured the pH of the nutrient solution at each sampling: initial pH value of nutrient solution was 5.58 ± 0.06 and gradually increased to reach a value of 6.38 ± 0.23 at the end of the experiment. After 11 weeks, seedlings were harvested and the different parts—roots, trunk and leaves—were cut up (Fig. 1). Dry weight was determined after storing at 60°C for one week. The Si leaf concentrations were determined after calcination at 450°C followed by borate fusion (Chao and Sanzolone 1992). Briefly, a crushed sample of 100 mg of the ignition residue was melted at 1000°C for 5 min in a graphite crucible in the presence of 0.4 g Li-tetraborate and 1.6 g Li-metaborate. After dissolution of fusion beads in 10% HNO3, Si content was determined by ICP-AES. Given the negligible Si concentrations in roots and trunk (Cornelis et al. 2010), Si analysis have not been processed in these samples.

Fig. 1
figure 1

Identification of tree seedlings (a. Black pine; b. Douglas fir) parts separated for biomass calculation (roots and leaves) and Si quantification in leaves

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Statistical analysis

Significance levels of tree species (Douglas fir and Black pine) and Si treatments (0.2, 0.8 and 1.6 mM) effects were assessed by ANOVA2 (model : species; treatment; species*treatment). Furthermore, the effect of Si treatments was compared for each species separately with the Fisher’s least significant differences test (LSD, ANOVA1). Statistics were performed with the SAS System (version 9.1, SAS Institute, Cary, NC, USA).

Results

Seedling growth

Whatever the Si treatment, the mean total dry weight of leaves at the end of experiment was 82 mg for each tree species, ranging from 57 to 125 mg. We did not observe significant differences in leaf weight between Si treatments (p-value = 0.16) and tree species (p-value = 0.99) (Table 1). The mean dry weight of roots was lower and ranged from 8.3 to 40.6 mg, with no significant differences between tree species (p-value = 0.09). We observed that root biomass in Black pine was significantly higher for seedlings with the lowest Si concentrations in the nutrient solution.

Table 1 Leaf and root biomass per seedling (in mg of dry matter) for Douglas fir and Black pine grown in nutrient solution with different Si-concentrations; standard deviation associated with the mean (n = 3) is given in parentheses. The interactions between tree species and Si treatments are not significant for leaves and roots biomasses (p-value = 0.39 and 0.84, respectively). Different letters indicate significant differences between Si treatments for the same tree species (p-value < 0.05)
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Water and mass flow Si uptake

Water uptake was significantly greater for Douglas fir seedlings than for Black pine seedlings (Fig. 2). After 11 weeks, the mean cumulative water uptake, equivalent to the transpiration, was 99 ml for Douglas fir and 25 ml for Black pine.

Fig. 2
figure 2

Mean cumulative water uptake per seedling (ml) for the two tree species (white circle = Douglas fir; black circle = Black pine) grown in nutrient solutions with different Si-concentrations. The error bar (n = 3) represents the standard deviation on the mean value calculated in three pots (one per Si treatment) for each species

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After experiments lasting 11 weeks, the potential cumulative mass flow Si uptake (MFU) clearly increased with the Si concentration in the nutrient solution (Fig. 3): from 0.12 to 1.07 mg of Si for Douglas fir and from 0.07 to 0.65 mg of Si for Black pine. At each Si supply and for the first two weeks of the experiments, the MFU was equivalent for Douglas fir and Black pine (i.e ∼0). After 3 weeks, the MFU was markedly higher for Douglas fir than for Black pine for each Si concentration in the nutrient solution.

Fig. 3
figure 3

Cumulative potential mass flow Si uptake per seedling (mg) for the two tree species (white circle = Douglas fir; black circle = Black pine) grown in nutrient solutions with different Si-concentrations: a 0.2 mM Si; b 0.8 mM Si; c 1.6 mM Si. The error bar (n = 3) represents the standard deviation

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Si leaf concentrations

For each tree species, Si leaf concentration clearly increased with the increasing Si concentration in the nutrient solution (Fig. 4 and Table 2): 0.76 to 3.53 mg Si g−1 for Douglas fir and 0.51 to 1.69 mg Si g−1 for Black pine. Douglas fir accumulated significantly more Si in leaves than Black pine (p-value < 0.001), except for the low Si supply where the difference was not significant.

Fig. 4
figure 4

Si concentrations in leaves (mg g−1 of dry matter) for Douglas fir (white) and Black pine (grey) grown in nutrient solutions with different Si-concentrations: 0.2 mM Si, 0.8 mM Si and 1.6 mM Si. The error bar (n = 3) represents the standard deviation associated with the mean

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Table 2 Actual Si concentrations in leaves (mg g−1 of dry matter) for Douglas fir and Black pine grown in nutrient solutions with different Si-concentrations; standard deviation associated with the mean (n = 3) is given in parentheses. The interaction between tree species and Si treatments is not significant (p-value = 0.08). Different letters indicate significant differences between Si treatments for the same tree species (p-value < 0.05)
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Discussion

Si impact on tree seedling growth

The growth of fir and pine seedlings did not increase with increasing Si supply in the nutrient solution (from 0.2 to 1.6 mM): for each tree species, our results did not reveal any positive effect arising from Si supply to the leaf and root dry biomass. In addition, we observed that pine root biomass was significantly larger for seedlings cultivated in the nutrient solution with the lowest Si concentration (0.2 mM), which represents a realistic Si concentration in a temperate forest soil solution (Gérard et al. 2002; Cornelis et al. 2010). These observations contradict previous studies revealing the positive effect of Si on plant growth by improving their resistance to stress, e.g. nutrient imbalance, mineral toxicities, water deficit, diseases and pests (Epstein 1994; Richmond and Sussman 2003; Ma 2004; Liang et al. 2007). In addition, Emadian and Newton (1989) suggest that the relative increase in pine seedling growth accompanied by a higher Si supply is clearly more important under water-stress conditions. Moreover, Henriet et al. (2006) show that Si did not affect the growth of young banana plants since stress was not imposed during the experiment. Thus, the absence, in our study, of a positive Si effect on the growth of tree seedlings could be attributed to the absence of the stress conditions, which can be attenuated by Si.

Mechanisms controlling Si uptake

In Table 3, we show the cumulated potential mass flow Si uptake (MFU) after experiments lasting 11 weeks. We also compute the potential Si concentration in leaves resulting from mass flow absorption, dividing the MFU (mg) by leaf biomass (g), in order to compare this potential Si concentration to the actual Si concentration in leaves (Table 2). At low Si concentration, actual Si leaf concentration was equivalent to potential Si leaf concentration (ratio “actual/potential” ∼1) for the two species, suggesting a passive Si uptake, as for some other dicots (Liang et al. 2006; Nikolic et al. 2007). At intermediate and high Si concentrations in nutrient solutions, we found that the real Si concentration in fir and pine leaves was significantly lower than the potential Si concentrations (ratio “actual/potential” ∼0.2–0.3) for both species, assuming a rejective mode of uptake as for some dicots (Liang et al. 2006; Nikolic et al. 2007). Recent studies demonstrate the existence of active Si transporters in roots (Lsi1 and Lsi2) and shoots (Lsi6), responsible for the high Si uptake capacity of rice (Ma et al. 2006, 2007; Yamaji et al. 2008). Lsi1 is an influx transporter of silicic acid, while Lsi2 is an active efflux transporter of the same chemical compound. These findings imply that the active transport process operates in some places along the Si trajectory from the root to xylem loading sites. For tree seedlings, the likely passive and rejective processes allow us to assume the inhibition of such active Si transporters in roots and shoots at Si concentration used in our hydroponic experiments. However, for realistic Si concentrations observed in forest soil solutions (0.05–0.2 mM Si), we could assume that tree seedling Si uptake could be essentially driven by a combined effect of water flow (passive mode) and active Si uptake. Indeed, in hydroponic experiments, Helianthus annuus and Benincase hispida take up Si passively at high Si concentration in solution (0.85 mM) while the active uptake contributes to the total Si uptake, especially at lower Si concentration in solution (0.085 mM) (Liang et al. 2006). Therefore, we cannot exclude that both active and passive Si uptake co-exist in tree seedlings at lower Si concentrations in rhizospheric solution (0.05–0.2 mM).

Table 3 Potential mass flow Si uptake (MFU) is calculated in mg of Si taken up for each seedling after 11 weeks in hydroponics. The standard deviation associated with the mean (n = 3) is given in parentheses. The estimated Si concentration in leaves is computed through the ratio between MFU and the leaf biomass
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Moreover, the Si rejective process at high concentrations in solution should operate in roots, given the relatively low Si concentration in branches, stembark and stemwood in Douglas fir and Black pine (Cornelis et al. 2010).

Effect of tree species

The higher in-situ Si uptake by Douglas fir as compared with Black pine (Cornelis et al. 2010) is confirmed in this study of hydroponics in relation to tree seedlings. Since the ratios between actual and potential Si concentrations in leaves of both Douglas fir and Black pine are equivalent (Table 3), we conclude that tree species did not affect the Si uptake mechanisms, whatever the Si concentration in nutrient solution. Given the identical Si uptake mechanisms between the two species at realistic Si concentrations (0.2 mM) and the absence of an active Si uptake mode, the much lower accumulation of Si in leaves of Black pine seedlings cannot be directly explained by either a defective or absent transporter to absorb Si from cortical cells to the xylem (Ma and Yamaji 2006) or by a lower density of the Si transporter to absorb Si from the external solution to the cortical cells (Mitani and Ma 2005). The contrasting Si uptake by Douglas fir and Black pine in hydroponics is likely due to the significant difference in transpiration rates. Thus, the in situ contrast in Si uptake in an experimental forest site with identical soil and climatic conditions (Cornelis et al. 2010) could be mainly explained by different transpiration rates. This confirms the following results: (i) the major role of transpiration in Si accumulation in fir leaves (Bartoli and Souchier 1978), (ii) the leaf area index (LAI), that strongly controls the transpiration rates in trees, is 2 times higher for fir species than for pine (Breda et al. 2002), and (iii) Si accumulates preferentially in the plant transpiration termini with greater amounts in the tip and middle of leaves (Sangster et al. 2007).

Note also a greater difference of Si concentration between fir and pine leaves collected on the forest site—5.3 and 0.2 mg Si g−1 dry matter respectively—than the ones measured after our hydroponics experiment—0.7 and 0.5 mg Si g−1 dry matter respectively. This could be explained by tree species impact on other processes that can influence directly or indirectly the Si uptake in the field site: (i) active uptake at Si concentrations lower than 0.2 mM in rhizospheric solution, and/or (ii) Si sinks in soil such as hydroxyaluminosilicates formation, Si sorption onto Fe oxides, opal-A precipitation and clay neoformation which influence the Si activity in rhizospheric solution.

Conclusions

This experimental study using tree seedlings in hydroponic conditions confirms the in-situ observation of higher Si accumulation in Douglas fir leaves as compared with those of Black pine. The mechanisms of Si uptake in hydroponics are identical between tree species: passive (mass-flow driven) uptake at realistic Si concentrations (0.2 mM) and rejective uptake at higher Si concentrations in nutrient solution. The contrasting Si accumulation in the leaves of coniferous tree seedlings could be attributed to the significant difference in the transpiration rates. The higher Si concentrations in nutrient solutions (0.8 and 1.6 mM) do not affect the growth of tree seedlings, probably because they are not subjected to stress conditions. This finding helps us to understand the mechanisms controlling the different Si uptakes by forest vegetations in order to better predict Si pathways in soil-tree systems. Besides the genetic difference controlling the transpiration rate, climatic and pedogenic factors would also influence the coniferous Si biocycling by modifying the water flow in the soil-tree system and Si activity in soil solution. Further study should be carried out in contrasting soil and climate conditions to assess the effect of various transpiration streams and pedogenic processes on Si uptake by forest vegetation and dissolved Si transfers to rivers.