#### **Table 2 | Studies included in this analysis.**

*Variables reported: DSi indicates porewater DSi (SiO2) concentrations, BSi indicates aboveground tissue plant BSi concentrations. Productivity indicates biomass per unit area.*

*Sediment values reported as ASi, as measurements include both biogenic and pedogenic Si. Where seasonal differences were observed (aboveground biomass only), we report both seasons separately. Otherwise, values represent average* ± *standard error across both seasons.*

**Table 4 | pH, salinity, and DSi concentrations (average ± standard error) measured in top 30 cm of porewater at each marsh site in this study.**

(except for summer Site 1 sample where 10–20 cm depth had slightly higher concentration) (Table S1). BSi in the roots and rhizomes in *S. patens* ranged from 0.08 to 0.96% and similar to *S. alterniflora*, BSi concentrations of the rhizomes (0*.*13 ± 0*.*02%) were much lower than in the roots (0*.*36 ± 0*.*04%) (Table S1).

Similar to other portions of the marsh budget, porewater concentrations were an order of magnitude higher at Site 1 than at Site 3 on all occasions (**Table 4**, Table S3). Average porewater salinity (30.2 ppt) and pH (7.21) at Site 3 under *S. patens* vegetation was similar to the values measured under *S. alterniflora* (**Table 4**).

#### **BSi ACCUMULATION AS A FUNCTION OF PRODUCTIVITY**

Using all available data from our analysis and the literature, we found a no correlation between aboveground productivity (mass per unit area) and BSi concentrations (*n* = 31, *R* = 0.22, *p* = 0*.*23) (**Figure 2**). We next subdivided the entire data by species

and by location in order to determine if regional or taxonomic differences resulted in distinct relationships between productivity and BSi accumulation in these plants. However, this continued to result in no significant relationships between productivity and BSi concentrations in most situations: *S. patens* (*n* = 9, *R* = 0.14, *p* = 0*.*72) and the non-New England *S. alterniflora* (*n* = 8, *R* = 0.46, *P* = 0.25). In fact, we only found the expected positive relationship between productivity and BSi concentration in New England *S. alterniflora* (*n* = 14, *R* = 0.70, *p <*0.01) (this study, Carey and Fulweiler, 2013) (**Figure 2**). Although the ways in which BSi concentrations vary as a function of productivity is not uniform across sites, we found that all marshes, regardless of location, begin the growing season with a fairly consistent amount of BSi in *S. alterniflora* tissue (0.38 to 0.45% by wt.) (yintercept, **Figure 2**). However, after the initial growing period, BSi accumulation diverges.

#### **BSi ACCUMULATION AS A FUNCTION OF** *IN SITU* **Si AVAILABILITY**

In order to test our hypothesis that *in situ* Si availability impacts BSi accumulation in aboveground plant tissue, we wanted to determine whether elevated sediment ASi concentrations or DSi in the porewater was associated with higher concentrations of aboveground BSi concentrations. Sediment ASi data was only available in conjunction with aboveground BSi concentrations for our original data, and for Carey and Fulweiler (2013). We found a strong correlation (*n* = 22, *R* = 0.60, *p <* 0*.*01) between sediment availability and BSi content (**Table 3**).

We found several studies, in addition to our own original data presented here, where porewater DSi concentrations are presented in conjunction with aboveground BSi concentrations (**Table 2**). Similar to the relationship between aboveground BSi content and productivity, examining all the data together resulted in no relationship between the concentrations of BSi in aboveground biomass and the concentration of DSi in the porewater (*n* = 43, *R* = −0*.*20, *p* = 0*.*21). We then subdivided the data by region and/or species in order to determine if there were differences based on taxonomy or origin. In doing so, different and yet, distinct relationships between porewater DSi and biomass BSi concentrations became apparent.

#### *North American marshes*

A positive correlation between *Spartina* BSi concentrations and porewater DSi concentrations (*n* = 20, *R* = 0.77, *p <* 0*.*01) (**Figure 3A**) was observed when all the data from New England was grouped together [excluding the data from the degraded "high-N" marsh described by Carey and Fulweiler (2013), which is discussed below]. In examining this regional grouping by species, we found a similar positive relationship for both *S. patens* (*n* = 8, *R* = 0.93, *p <* 0*.*01) and *S. alterniflora* (*n* = 12, *R* = 0.72, *p <* 0*.*01). However, data from one New England marsh [*S. alterniflora* at the N-enriched marsh ("high-N" site) presented by Carey and Fulweiler, 2013] showed a distinctly different pattern, as we observed a negative relationship (*n* = 3, *R* = −0*.*98, *p* = 0*.*14) between porewater DSi concentrations and BSi concentrations (**Figure 3C**).

Besides the data from the New England salt marshes, Norris, and Hackney completed a study of net Si accumulation in a mid-Atlantic marsh (North Carolina, USA). This study also observed a negative relationship between porewater DSi concentrations and *S. alterniflora* BSi concentrations (*n* = 3, *R* = −0*.*94, *p* = 0*.*22). However, unlike the pattern observed in the high-N marsh described by Carey and Fulweiler (2013), the data from this North Carolina marsh showed the opposite relationship with time, as over the course of growing season plant BSi concentrations decreased, while porewater concentrations increased (Figure S1).

**FIGURE 3 | BSi concentration in aboveground biomass as a function of porewater DSi concentrations.** *S. patens* (black circles), *S. anglica* (filled gray circles), and *S. alterniflora* (open white circles), *P. australis* (black squares). Dashed line in **(B)** indicates the regression ignoring the two *S. anglica* outliers. Values in **(A,C)** represent average values from triplicate field measurements in top 20 cm of sediment, with spring and summer values plotted individually. Values in **(A)** represent values from five New England salt marshes. Values in **(B)** represent ten marshes in Oosterschelde, and the two marshes in Bay of Brest (Querné et al., 2012). Values in **(C)** represent values from one marsh in New England (*S. alterniflora* data) and one marsh in Belgium [*P. australis* data from Struyf et al. (2005b)].

#### *European marshes*

We observed a weak relationship between plant BSi and porewater DSi concentrations (*n* = 18, *R* = −0*.*45, *p* = 0*.*07) in the data from the European marshes (De Bakker et al., 1999; Querné et al., 2012). This weak negative relationship was primarily driven by two data points of low DSi porewater concentration (**Figure 3B**). Removing these two points (both of which are *S. anglica*) resulted in no relationship between those two variables (*n* = 16, *R* = 0.07, *p* = 0*.*80).

#### **DISCUSSION**

It is not uncommon for a single species of plant to contain different amounts of Si (Hodson et al., 2005), but such variability is typically thought to be due to differences in Si availability in the surrounding environment or growth rates (Norris and Hackney, 1999; Struyf et al., 2005b; Guntzer et al., 2012; Querné et al., 2012; Carey and Fulweiler, 2013). With regard to *Spartina*, productivity does not appear to be a major control over Si accumulation. Despite commencing the growing season with a relatively uniform amount of BSi, the relationship between productivity and aboveground BSi accumulation diverges at higher levels of productivity (**Figure 1**). This divergence indicates that productivity does not control BSi accumulation in the same manner in all *Spartina* species.

Differences in transpiration rates have been shown to be responsible for different levels of Si accumulation in plant leaves (Cornelis et al., 2010b; Guntzer et al., 2012). As such, the lack of relationship between productivity and BSi concentrations may be due to variable transpiration rates among salt marhes and/or water availability across these marshes, supporting the idea that productivity is not a good proxy for water use (Hessini et al., 2009). In addition to potential differences in water availability across sites, our results indicate that variable amounts of bioavailable Si present in the system and different modes of Si accumulation by the plants are the likely drivers of this pattern.

#### **PASSIVE Si ACCUMULATION IN NEW ENGLAND MARSHES**

In the New England marshes, higher ASi availability in the sediments is associated with higher BSi accumulation in the plants. This correlation is likely due to the soluble nature of ASi, which is considered a biologically available form of Si, having dissolution rates orders of magnitudes faster than mineral silicates (Struyf and Conley, 2012). New England salt marshes have some of the highest recorded sediment ASi concentrations (Carey and Fulweiler, 2013), which may explain why the BSi concentrations observed at several of these sites is higher than those found elsewhere (**Figure 1**).

Similar to the relationship observed with sediment ASi, higher porewater DSi concentrations are associated with higher aboveground BSi concentrations in all New England data, except in a highly degraded marsh (high-N marsh, Carey and Fulweiler, 2013) (discussed below) (**Figure 3A**). The positive relationship indicates that in the non-degraded New England marshes, *Spartina* passively accumulates Si, as more Si in the surrounding environment is associated with more Si in aboveground plant tissue. Thus, in this situation of passive accumulation, *in situ* Si availability in both the sediment and porewater are important controls Si accumulation in *Spartina*.

#### **REJECTIVE Si ACCUMULATION IN EUROPEAN MARSHES**

Unlike the strong positive and negative relationships we observed between plant BSi concentrations and porewater DSi concentrations in the New England marsh, we found no relationship between these two variables in the European marshes (**Figure 3B**). The lack of relationship between porewater DSi and plant BSi concentrations points toward *Spartina* in these systems behaving as a Si excluder, particularly at higher Si concentrations. In fact, De Bakker et al. (1999) also came to the same conclusion about their data, and suggested that *S. anglica* may reject Si from its tissue via a barrier on the outer surface of the roots, similar to legumes (Raven, 1983).

The extensive reviews by Jones and Handreck (1967) and Raven (1983) point toward rejector plants accumulating 5–60% of the DSi that is in the transpired water, with the remainder being left in the porewater. Further, at higher soil solution concentrations, plants will reject a larger portion of DSi (Raven, 1983; Cornelis et al., 2010b), which we also find evidence for with our flat regression line between aboveground BSi content and porewater DSi concentrations (**Figure 3B**). The exact mechanisms driving Si rejection in plants are not yet well understood, but it has been suggested that low Si accumulating plants have either a defective or non-existent Si transporter from cortical cells into the xylem (Ma and Yamaji, 2008).

Our designation of a Si excluder to *S. alterniflora* in the French salt marsh disagrees from the original interpretation of the data (Querné et al., 2012). While Querné et al. (2012) do point out the lack of relationship between DSi porewater and plant BSi concentrations, they assign *S. alterniflora* to the passive accumulator category based on the dry weight of BSi in the aboveground tissue alone. While this is a common practice when porewater DSi data is unavailable (Hou et al., 2010; Carey and Fulweiler, 2012), it ignores differences in transpiration or *in situ* Si availability. Thus, only defining Si accumulation by aboveground BSi concentration data may be misleading when passive Si accumulators are exposed to unusually high or low porewater concentrations, as one could incorrectly assign passive accumulators active or rejective status based on dry weight alone (Liang et al., 2005). Based on our analysis of the invasive *Spartina* from Europe, and the range of porewater concentrations observed in salt marshes, we are now skeptical at using the dry weight of BSi alone in quantifying mode of Si accumulation in marsh grasses.

#### **ACTIVE Si ACCUMULATION IN DEGRADED MARSH**

Unlike all other data from New England, we observed a negative relationship between porewater DSi availability and aboveground BSi content in the highly degraded salt marsh described in Carey and Fulweiler (2013) (**Figure 3C**). This negative relationship provides evidence of active Si accumulation, with the plants sequestering Si in high enough proportions to drive down porewater concentrations (Raven, 1983). As described by Raven (1983) and Jones and Handreck (1967), active Si accumulation results in the decline of DSi concentrations in the "bathing medium" as the plant takes up DSi relatively faster than it takes up water. Agricultural studies of active transport in rice, a known active Si accumulator, has identified two ATP-fuelled Si transporters (Ma and Yamaji, 2008), which transports Si through the membranes. Moreover, we consistently observed aboveground BSi concentrations *>*1% by wt., the threshold concentration shown to indicate active accumulation (Ma et al., 2001; Street-Perrott and Barker, 2008; Carey and Fulweiler, 2012; Querné et al., 2012).

In order to provide further support for our interpretation that the negative relationship between porewater DSi concentrations and aboveground BSi concentrations indicates active Si accumulation, we looked to Struyf et al. (2005b), who examined these two variables in a Western European tidal freshwater marsh dominated by *Phragmites australis*. *P. australis* is a known active Si accumulator, allowing us to examine the relationship between plant BSi and porewater DSi concentrations in a marsh experiencing active accumulation. Using the data presented by Struyf et al. (2005b), we found that *P. australis* also exhibits a strong negative relationship between porewater DSi concentrations and aboveground BSi concentrations (*n* = 5, *R* = −0*.*86, *p* = 0*.*06) (**Figure 3C**). The similar relationship between porewater and aboveground BSi concentrations in *P. australis* and the *S. alterniflora* in the degraded high N marsh provides additional evidence of active Si accumulation in the degraded marsh.

This site where evidence of active accumulation is observed is a high-nutrient, degraded salt marsh located downstream of an urban watershed (Wigand et al., 2003; Carey and Fulweiler, 2013). In fact, the N loading here is so high that the marsh is now P-limited, with a summer average molar DIN/DIP ratio in the inundating tidal creek water of 53 (**Table 1**). While it is possible that external factors are resulting in the declining porewater concentrations over time at this marsh, the fact that we do not observe this trend in the four nearby marshes indicates that the degraded, high N nature of the marsh is playing a role in the distinct behavior observed in *Spartina* here.

The results of one study, which focused on Si accumulation in a North Carolina (USA) salt marsh (Norris and Hackney, 1999), did not fit the criteria for any of the three modes of uptake. During our re-analysis of those data we observed a strong negative relationship between porewater DSi concentration and plant BSi concentration. While this trend initially indicates active accumulation, further examination of the change through time reveals that throughout the course of growing season, plant BSi concentrations decreased, while porewater concentrations increased (Figure S1). This is the opposite temporal relationship that one would find with active accumulation and does not fit the expected trend for passive or rejective accumulation either which signals a departure from any of the three traditional modes of uptake. The observations from this marsh call into question whether or not some plants, under certain conditions, can translocate Si.

#### **ENVIRONMENTAL STRESS AND PHENOTYPIC PLASTICITY AS DRIVERS OF Si ACCUMULATION?**

In examining the site characteristics of these marshes, we identify several variables that may drive the different modes of Si accumulation within marsh plants. The marshes studied here span a range of conditions, from nutrient over-enriched to relatively undisturbed, exposing these grasses to variable amounts of stress. Studies of abiotic stress on plant BSi concentrations report mixed results. Querné et al. (2012) found no plant response upon exposure to several types of stress, while Schoelynck et al. (2012)found increased Si accumulation in macrophytes exposed to intense water currents. A recent study of a degraded, "high-N" marsh found significantly more Si accumulation in several components of the marsh budget compared to a lower nutrient marsh (Carey and Fulweiler, 2013), which was hypothesized to be due in part to the stress induced by high air temperatures and low amounts of rainfall. We now propose that this degraded salt marsh is actively accumulating Si, which we suggest is a defense mechanism to ameliorate environmental stress.

In addition to marsh condition, genetic origin represents another variable across sites. *S. alterniflora* is native to the Atlantic and Gulf of Mexico coasts of North America, but invasive in many areas of the world, including the Pacific coast of North America, Europe, and Asia. Similarly, *S. anglica* is invasive in Western Europe. Invasive species in general have been shown to exhibit higher phenotypic plasticity than non-invasive species (Davidson et al., 2011). Phenotypic plasticity refers to the ability of organisms to change their observable traits in response to environmental conditions (Schlichting, 1986; Davidson et al., 2011). This phenomenon may be responsible for the different patterns in Si accumulation by salt marsh plants. Invasive species, particularly *S. alterniflora*, have been shown to exhibit higher phenotypic plasticity than the native plants (Zhao et al., 2010), which may explain the contrasting Si behavior by the same genus of plants. In particular, a recent study in China found the invasive *S. alterniflora* to show a higher degree of morphological growth, and biomass allocation plasticity in association with N availability compared to the native grass (Zhao et al., 2010). Our data suggests that genetic origin is another factor driving the differences in BSi accumulation in *Spartina* across sites. While phenotypic plasticity has been demonstrated for N, to our knowledge this is the first study to suggest a phenoplastic response of *Spartina* to Si.

#### **A CONCEPTUAL MODEL DESCRIBING DRIVERS OF** *Spartina* **Si UPTAKE**

Based upon the available data and our analysis above it is clear that wetland grasses cannot be grouped into one mode of Si accumulation. Rather we hypothesize that different Si accumulation modes are based on site-specific environmental conditions and genetic origin. To demonstrate this hypothesis we developed a conceptual model depicting the different modes of Si uptake by *Spartina* (**Figure 4**), which is based on the different slopes we observed in our linear regressions between porewater DSi availability and aboveground BSi concentrations (**Figure 3**). As illustrated in our model, we propose that *Spartina* passively accumulates Si in non-degraded marshes where the species are native, such as the case in the non-impaired New England marshes included in this study (**Figures 3A**, **4A**). Further, we suggest that *Spartina* behaves as Si excluders/rejectors in situations where the plant is invasive (**Figures 3B**, **4B**). Finally, we hypothesize that active Si accumulation by the native *Spartina* occurs when the plants are exposed to highly stressful, degraded conditions (**Figures 3C**, **4C**).

We present our conceptual model as a hypothesis which must be tested in future salt marsh research. Our hypothesis takes into account all known studies where *Spartina* BSi concentrations are reported alongside either porewater DSi concentrations or sediment ASi concentrations, but other confounding factors (e.g., diatom uptake, interaction with mineral silicates, and transport processes) also play a role in salt marsh Si dynamics. Thus, future work should focus on controlled field observations and laboratory studies which account for confounding variables as a means of testing the conceptual model that we put forth here. The recent recognition that gene expression can control Si accumulation in rice (Ma et al., 2006, 2007) highlights an exciting avenue of potential research for salt marsh grasses, such as *Spartina*.

While this is the first study to provide evidence of variable modes of accumulation in *Spartina*, Liang et al. (2005, 2007) observed both active and passive Si accumulation within several of the same species of plants (e.g., cucumber, rice, maize, sunflower, and wax gourd). Rather than the absolute categorization of "active" accumulator to grasses, the mode of Si accumulation within *Spartina* is variable depending on site-specific conditions. This interpretation aligns with the previous suggestion that plant species should be placed along a spectrum of accumulation, rather than categorized as having only one method of accumulation (Cooke and Leishman, 2011), an idea supported by recent work at the molecular-level of plant Si biochemistry (Ma et al., 2006, 2007; Ma and Yamaji, 2008).

#### **ACTIVE Si ACCUMULATION AND A LOSS OF ECOSYSTEM SERVICE?**

Tidal wetlands are important regulators of Si fluxes to adjacent estuarine systems (Struyf et al., 2005a; Jacobs et al., 2008; Vieillard et al., 2011), often supplying DSi necessary for diatom growth in

coastal systems (Anderson et al., 2002; Danielsson et al., 2008). A recent mass balance of Si fluxes in a New England salt marsh found the marsh to be a "point" source of DSi to the adjacent estuary, primarily due to drainage of Si-rich porewater during the ebbing tide (Vieillard et al., 2011). We observed a 60% decline in marsh porewater concentration over the growing season (spring through fall) in the marsh experiencing active Si accumulation. In turn, we hypothesize that the presence of active Si accumulators in marshes may diminish the export of DSi to downstream coastal systems by reducing DSi porewater concentrations. While the BSi sequestered in the plants will eventually be remineralized, this may occur after the plant has been exported from the marsh. Even in the case that BSi is remineralized *in situ*, it will ultimately shift the timing of DSi availability in the system. A shift to active Si accumulation by marsh grasses exposed to degraded conditions may represent a previously unrecognized way that coastal nutrient enrichment can impact estuarine ecology in North America.

Likewise *P. australis* is an invasive species throughout North American salt marshes (Chambers et al., 1999). We hypothesize that a shift in vegetation type from that of passively accumulating *Spartina* to actively accumulating *P. australis* could result in lower marsh porewater DSi concentrations. Such lower porewater DSi concentrations could reduce the ability for salt marshes to serve as sources of DSi to adjacent estuaries. In turn, we predict that invasion of *P. australis* to North American salt marshes may alter the timing and magnitude of Si exchange in coastal systems, highlighting a potentially unrealized consequence of this invasion to coastal ecosystems.

Tidal wetlands have the ability to control Si availability in coastal systems, which has important consequences for phytoplankton species composition. Here we present evidence that *Spartina* grasses may shift their mode of Si accumulation based on local environmental conditions and genetic origin. Recognition that these wetland grasses accumulate Si differently depending on site-specific characteristics provides new insight regarding the role these grasses play in Si dynamics at this borderland between land and sea.

#### **ACKNOWLEDGMENTS**

We are grateful for field assistance by Jules Opton-Himmel, Kenneth Raposa, Daisy Durant, Amanda Vieillard, Margaret Notopoulos, and Sarah Sargent. In addition, we thank the following people for laboratory assistance: Amanda Vieillard, Elise Greenberg, Ashley Banks, Megan Ware, Suzann Duan, and especially Courtney Zambory. We thank Adrien Finzi for generously allowing us to use his lab and equipment to grind vegetation samples. This research was conducted under an award from the Estuarine Reserves Division, Office of Ocean and Coastal Resource Management, National Ocean Service, National Oceanographic and Atmospheric Association Graduate Research Assistantship and an L. L. Bean Acadia Research Fellowship to Joanna C. Carey. We thank the Department of Earth and Environment at Boston University for partial funding support of Joanna C. Carey. We also thank the Sloan Foundation who provided support for this work to Robinson W. Fulweiler through the Sloan Fellowship.

# **SUPPLEMENTARY MATERIAL**

The Supplementary Material for this article can be found online at: http://www*.*frontiersin*.*org/journal/10*.*3389/fpls*.*2014*.*00186/ abstract

# **REFERENCES**

and water-use efficiency in *Spartina alterniflora*. *Environ. Exp. Bot.* 67, 312–319. doi: 10.1016/j.envexpbot.2009.06.010

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 01 March 2014; accepted: 21 April 2014; published online: 20 May 2014. Citation: Carey JC and Fulweiler RW (2014) Silica uptake by Spartina—evidence of multiple modes of accumulation from salt marshes around the world. Front. Plant Sci. 5:186. doi: 10.3389/fpls.2014.00186*

*This article was submitted to Functional Plant Ecology, a section of the journal Frontiers in Plant Science.*

*Copyright © 2014 Carey and Fulweiler. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Impact of rice cultivar and organ on elemental composition of phytoliths and the release of bio-available silicon

# *Zimin Li 1, Zhaoliang Song1,2\* and Jean-Thomas Cornelis <sup>3</sup>*

*<sup>1</sup> School of Environment and Resources, Zhejiang Agricultural and Forestry University, Lin'an, China*

*<sup>2</sup> State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, China*

*<sup>3</sup> Soil Science and Environment Geochemistry, Earth and Life Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium*

#### *Edited by:*

*Julia Cooke, University of Western Sydney, Australia*

#### *Reviewed by:*

*Jean-Dominique Meunier, Centre National de la Recherche Scientifique, France Wim Clymans, Lund University, Sweden Hongyan Liu, Peking University, China*

#### *\*Correspondence:*

*Zhaoliang Song, School of Environment and Resources, Zhejiang Agricultural and Forestry University, 88 North Huancheng Road, Lin'an, Zhejiang 311300, China e-mail<EMAIL_ADDRESS>
The continental bio-cycling of silicon (Si) plays a key role in global Si cycle and as such partly controls global carbon (C) budget through nutrition of marine and terrestrial biota, accumulation of phytolith-occluded organic carbon (PhytOC) and weathering of silicate minerals. Despite the key role of elemental composition of phytoliths on their solubility in soils, the impact of plant cultivar and organ on the elemental composition of phytoliths in Si high-accumulator plants, such as rice (*Oryza sativa*) is not yet fully understood. Here we show that rice cultivar significantly impacts the elemental composition of phytoliths (Si, Al, Fe, and C) in different organs of the shoot system (grains, sheath, leaf and stem). The amount of occluded OC within phytoliths is affected by contents of Si, Al, and Fe in plants, while independent of the element composition of phytoliths. Our data document, for different cultivars, higher bio-available Si release from phytoliths of leaves and sheaths, which are characterized by higher enrichment with Al and Fe (i.e., lower Si/Al and Si/Fe ratios), compared to grains and stems. We indicate that phytolith solubility in soils may be controlled by rice cultivar and type of organs. Our results highlight that the role of the morphology, the hydration rate and the chemical composition in the solubility of phytoliths and the kinetic release of Si in soil solution needs to be studied further. This is central to a better understanding of the impact of soil amendment with different plant organs and cultivars on soil OC stock and on the delivery of dissolved Si as we show that sheath and leaf rice organs are both characterized by higher content of OC occluded in phytolith and higher phytolith solubility compared to grains and stems. Our study shows the importance of studying the impact of the agro-management on the evolution of sinks and sources of Si and C in soils used for Si-high accumulator plants.

**Keywords: phytolith, rice, silicon solubility, PhytOC, soil-plant systems**

# **INTRODUCTION**

Silicon (Si), the second most abundant element in the continental surface (Wedepohl, 1995), is present in soils mostly as silicates, adsorbed Si onto oxides, biogenic precipitates called phytoliths and microorganisms remains. Dissolved Si (H4SiO4), can be readily taken up by plants and plays an important role as an alleviator of both biotic and abiotic stress (Epstein, 1994; Marschner, 1995; Mecfel et al., 2007). More importantly, Si is usually coupled with carbon (C) in different terrestrial biogeochemical processes (silicate weathering, soil formation, biota nutrition) that occur at different time-scales, which plays a crucial role in the regulation of atmospheric CO2 (Oldenburg et al., 2008; Street-Perrott and Barker, 2008; Li et al., 2011; Song et al., 2012).

Si taken up by roots is mainly deposited in the transpiration sites of plants (e.g., cell walls, cell lumina, and intercellular spaces typically near evaporating surfaces) where polymerization of hydrated amorphous silica occurs to form phytoliths (Piperno, 1988; Ma, 2003). The chemical compositions of phytoliths consists mainly of SiO2 (66–91%), organic carbon OC (1–6%), H2O (0–11%), Al (0.01–4.55%), and Fe (0–2.1%) (Jones and Milne, 1963; Wilding, 1967; Wilding et al., 1967; Wang and Lü, 1993; Wang, 1998; Blecker et al., 2006). The chemical composition of phytoliths is highly dependent on plant species (Kameník et al., 2013). Despite their higher solubility compared to silicate minerals (Fraysse et al., 2009, 2010), phytoliths can be highly resistant to dissolution in specific physico-chemical conditions and can remain for thousands of years in soils (Wilding, 1967; Parr and Sullivan, 2005). Therefore, plant phytoliths play a major role in palaeobotanical, palaeoecological and archeological reconstructions (Clarke, 2003; Piperno, 2006; Cao et al., 2007; Raven and Giordano, 2009). Recent studies report that OC (0.2–5.8%) can be occluded in phytoliths (PhytOC) during plant growth (Parr and Sullivan, 2005; Parr et al., 2010; Li et al., 2013). Si polymerized in plant phytoliths may be more soluble compared to other crystalline mineral phases (Fraysse et al., 2009, 2010), while PhytOC is relatively more stable than other OC fractions in soils (Parr and Sullivan, 2005). For example, Parr and Sullivan (2005) report that the age of phytoliths in volcanic soils and peatland sediments ranges from 0 to 8000 year BP. Moreover, it has been reported that phytoliths in some sediments have a radiocarbon date of 13,300 ± 450 year BP (Wilding, 1967). PhytOC, a crucial component of terrestrial C sink, can represent up to 82% of total C in some soils and sediments after 2000 years of litter fall decomposition, contributing 15–37% in long term terrestrial C sequestration (Alexandre et al., 1997; Parr and Sullivan, 2005).

Cultivated rice (*Oryza sativa*) is the main food source for more than 50% of the global population (Salekdeh et al., 2002) and is currently cultivated on around 1*.*<sup>55</sup> <sup>×</sup> <sup>10</sup><sup>8</sup> ha (i.e., 1.04% of the global terrestrial surface) (IRRI, 2011)1 . Rice, a typical Si high-accumulator, can accumulate more than 10% of SiO2 in dry matter (Alvarez and Datnoff, 2001) and application of Si may improve rice growth both under greenhouse and field conditions (Epstein, 1994, 1999; Liang et al., 2007). Recent studies showed that rice plays a significant role in the coupled terrestrial biogeochemical cycles of C and Si through the production of PhytOC (Parr et al., 2010; Song et al., 2012; Li et al., 2013). However, the impact of rice cultivar and of different rice organs on the phytolith elemental composition and solubility has never been reported (Savant et al., 1997), while solubility studies are important to make correct estimates of PhytOC preservation in soils and Si release in soil solution.

In this study, we investigated elemental compositions of organs and phytoliths, and the release of bio-available Si from rice phytoliths of different cultivars and organs (leaves, sheaths, stems and grains) cultivated in identical pedo-climatic conditions (Hortic Anthrosol in subtropical humid climate), to better understand the role of rice cultivars and organs on elemental composition (Si, Al, Fe, C) of phytolith and the release of bio-available Si (solubility in CaCl2 solution at 0.01 M). Our results offer a research perspective to further study how to improve the phytolith C sequestration and Si fertility in soil-plant ecosystem.

# **MATERIALS AND METHODS**

#### **SAMPLING SITES**

Organ samples (leaves, sheaths, stems and grains) of five rice cultivars (three replicates) were collected during the harvest season in October 2010, from the regional trials of new varieties of crops grown at the experimental site of Zhejiang Soil and Fertilizer Station (30◦56 06.3N and 120◦51 52.9E) in Jiaxing City, Zhejiang Province, southeast China. The experimental site is located in Hangjiahu Plain which experiences a typical subtropical humid monsoon climate, with an average annual precipitation of 1200 mm. The mean annual temperature is 16◦C and the number of frost free days is 230. Soil is classified as the Gleysols (FAO, 1974)2 .

#### **PLANT SAMPLE PREPARATION AND ANALYSIS**

The five rice cultivars planted in the experiment were Jiahua-11, Xianghu-301, Zhejing-37, Ning-81, and Xiushui-09 which have been grown there for 8 years under identical pedo-climatic conditions to eliminate factors that might influence Si uptake and deposition (**Table 1**). We collected 8–10 rice cultivars from each site and their associated surface soil (0–5 cm). Then the stem, leaf, sheath and grains of each rice cultivar plant were separated. The sample material was thoroughly washed with ultrapure water after an ultrasonic bath for 15 min, dried at 75◦C for 48 h. The dried and mixed samples were separated into two subsamples. One subsample was crushed to determine total elemental composition. Total Si, Al and Fe contents in plant samples and in a plant standard GBW 07602 (GSV-1) were determined by ICP-AES after combustion at 950◦C followed by borate fusion (Lu, 2000).

The other subsample was cut into small pieces around 5 mm to extract phytoliths. Using a microwave digestion method (Parr and Sullivan, 2011) and Walkley-Black type digest (Walkley and Black, 1934), we extracted the phytoliths from all rice organs and thoroughly removed extraneous organic materials in the samples (Li et al., 2013). The phytoliths extracted were oven-dried at 75◦C to a constant weight. The organic C released from phytoliths after HF treatment was dried at 45◦C and the C content was determined by classical potassium dichromate method (Lu, 2000; Li et al., 2013). The organic C data were monitored with a standard reference soil of 30 mg (GBW07405). The precision is better than 7%.

Phytoliths samples were dissolved in an alkaline solution (NaOH, 1 M) (Saccone et al., 2006), in which the contents of Si, Al, and Fe were analyzed by ICP-AES.

#### **BIO-AVAILABLE Si ANALYSIS**

The pool of "bio-available Si" was determined by a CaCl2 extraction (0.01 M) (Haysom and Chapman, 1975; Buck et al., 2010;

1Available online at: http://ricestat*.*irri*.*org:8080/wrs2/entrypoint*.*htm.

2Available online at: http://en.wikipedia.org/wiki/FAO\_soil\_classification.

*Means with various letters are significantly different at the p < 0.05 level of confidence according to Duncan's Multiple Range Test.*

Narayanaswamy and Prakash, 2010) on dried phytolith samples. 30 mg of phytoliths was shaken in 50 ml of CaCl2 solution at 20◦C for 5 h, 1–9 days. At the end of each extraction, the concentration of Si was analyzed by ICP-AES. The amount of Si released in the extract over time represents the evolution of the immediately available Si fraction of the readily soluble Si pool (Berthelsen et al., 2001; Sauer et al., 2006; Cornelis et al., 2011). This kinetic extraction (expressed as mg bioavailable Si/g SiO2 in phytoliths) has been designed to study the potential of phytoliths present in rice cultivars to replenish the bio-available Si pool (Houben et al., 2014).

#### **SOIL SAMPLES PREPARATION AND ANALYSIS**

Soil pH was measured in a 1:5 soil: water suspension. Soil organic carbon (SOC) was determined by wet digestion method with 133 mol L−<sup>1</sup> K2Cr2O7 and concentrated H2SO4 at 170–180◦C. Total SiO2, Fe2O3, and Al2O3 in soil were measured by ICP-AES after calcinations at 950◦C followed by borate fusion (Lu, 2000). Soil phytolith extraction methods were slightly modified from methods of Piperno (1988) and Lu et al. (2006) as follows: Na4P2O7 (20%) deflocculating, treatment with H2O2 (30%), and cold HCl (15%), ZnBr2 heavy liquid (2.38 g-cm3) separation. At the end of the soil extraction, the supernatant was separated from the solid residue by centrifugation (3000 g; 5 min) for analyzing phytolith content. All phytoliths extracted were oven-dried at 75◦C and weighed to calculate their contents.

# **STATISTICAL ANALYSIS**

All data are presented as the average of three analytical replicates (soil and plant samples). A One-Way analysis of variation (ANOVA) was carried out on the data obtained from the present study, and means were compared using Duncan's Multiple Range Test (*p <* 0*.*05). The statistical analyses were carried out with SAS software (SAS Institute, 1989).

# **RESULTS**

# **PHYSICO-CHEMICAL SOIL CHARACTERISTICS**

As shown in **Table 1**, the pH value (5.9) was similar in the soil surface of the five different rice species. The total concentration of Fe2O3 and Al2O3 were also identical in the soil surface of the five experimental plots, with mean value at 276 and 146 g/kg, respectively. The total concentration of SiO2 was also identical in the soil surface of the five experimental plots, with mean value at 667 g/kg. The concentration of SOC and phytoliths varied from 15 to 29 g/kg, (mean at 23 g/kg) and from 12 to 19 g/kg (mean at 16 g/kg), respectively. This variation can be explained by the fact that the cultivation of different rice cultivars may cause differences in terms of straw production and residue input in soils, which can influence significantly the content of phytoliths and organic matter in soil.

### **PHYTOLITH CONTENT AND CHEMICAL COMPOSITION OF RICE ORGANS OF DIFFERENT CULTIVARS**

The average content of phytoliths in the five rice cultivars varied significantly from 2.2 to 12.0% between rice organs (**Table 2**). Generally, the phytolith content decreased from 12.0% in sheaths *>*7.0% in leaves *>*3.7% in stems *>*2.2% in grains. The average of Al content for different organs in the five rice cultivars varied from 0.003 to 0.009% (sheaths *>* leaves = stems = grains). The Fe content in rice organs varied between 0.012 and 0.034% and showed the following trend: sheaths *>* stems = leaves = grains. The content of OC occluded in phytoliths (PhytOC) of rice organs varied significantly between 0.06 and 0.23% and showed the following trend: sheaths *>* leaves *>* stems *>* grains.

# **CHEMICAL COMPOSITION OF PHYTOLITHS EXTRACTED FROM DIFFERENT ORGANS**

The mean H2O content in phytoliths ranged from 5.4 to 14.5% and showed the following trend: stems *>* leaves *>* sheaths = grains. As a result of different hydration rates of phytoliths in the different organs, the SiO2 content of phytolith was the highest in the grains (94.71%), then significantly decreased in sheaths (92.50%), leaves (88.47%), and stems (83.04%) (**Table 3**). The average Al content in phytoliths significantly varied from 0.012 to 0.043%: sheaths and leaves *>* grains and stems (**Table 3**; **Figure 1A**). The average Mg content in phytoliths varied from 0.0043 to 0.0082%: sheaths and leaves = grains *>* stems (**Table 3**). The average Fe content in phytoliths ranged from 0.017 to 0.009%: sheaths = leaves = grains = stems (**Table 3**; **Figure 1B**). The average OC content in phytoliths varied from 1.93 to 2.46%, without significant change between plant organs (**Table 3**).

#### **THE RELEASE OF BIO-AVAILABLE Si**

After 7 days, the cumulative release of bio-available Si from phytoliths of different plant organs (mg Si/g SiO2 in phytoliths; **Figure 2A**) significantly varied from 7.8 to 44.9 mg Si/g SiO2 and was the highest in leaves (44.9 mg Si/g of SiO2), then significantly decreased in sheaths (18.1 mg Si/g of SiO2), stems (12.2 mg Si/g of SiO2), and grains (7.8 mg Si/g of SiO2). After 7 days, the release of bio-available Si from phytoliths of stems of different rice cultivars (mg Si/g SiO2 in phytoliths; **Figure 2B**) significantly varied from 6.9 to 15.7 mg Si/g SiO2: Xiushui-09 (15.7 mg Si/g SiO2) *>* Xianghu-301 (13.2 mg Si/g SiO2) and Ning-81 (13.0 mg Si/g SiO2) *>* Zhejiang-37 (7.5 mg Si/g SiO2) and Jiahua11 (6.9 mg Si/g SiO2).

# **DISCUSSION**

#### **IMPACT OF RICE CULTIVAR AND ORGAN ON CONCENTRATION AND ELEMENTAL COMPOSITION OF PHYTOLITHS**

Our results show that a significant correlation exists between the phytolith content in plants and the elemental concentration in plants for the five rice cultivars (Phytolith vs. Si, *<sup>R</sup>*<sup>2</sup> <sup>=</sup> <sup>0</sup>*.*8895; Phytolith vs. Al, *<sup>R</sup>*<sup>2</sup> <sup>=</sup> <sup>0</sup>*.*6494; Phytolith vs. Fe, *<sup>R</sup>*<sup>2</sup> <sup>=</sup> 0*.*572) (**Table 4**). A correlation also exists between the phytolith content in plants and the phytolith elemental content (Phytolith vs. Phytolith-Al, *<sup>R</sup>*<sup>2</sup> <sup>=</sup> <sup>0</sup>*.*6518; Phytolith vs. Phytolith-Fe, *<sup>R</sup>*<sup>2</sup> <sup>=</sup> <sup>0</sup>*.*2973; Phytolith vs. Phytolith-Mg, *<sup>R</sup>*<sup>2</sup> <sup>=</sup> <sup>0</sup>*.*3194) (**Table 5**). This implies that the uptake of Si Al, Fe may significantly affect phytolith production in plant organs. Previous studies already show that climatic (transpiration flow), pedologic conditions (Si availability) and plant species can influence significantly the uptake of Si and the formation of phytoliths in plants (Bartoli and Wilding, 1980; Epstein, 1999; Piperno et al., 2002; Hodson et al., 2005; Henriet et al., 2008; Cornelis et al., 2010, 2011; Kameník et al., 2013; Li et al., 2013). Our study

**Table 2 | Elemental compositions (%) and phytolith content in organs (grains, sheath, stem and leaf) of the different rice cultivars.**

*Means with various letters are significantly different at the p < 0.05 level of confidence according to Duncan's Multiple Range Test.*

*Different lowercase and uppercase letters indicate significant differences among the stands in rice organs and rice cultivars.*

*aPhytOC, OC occluded in phytoliths per 100 g of dry matter for each organs.*

in identical pedo-climatic conditions shows that the precipitation of elements between plant organs of rice cultivars is also controlled by plant physiology, i.e., more transpiration sites in leaves and sheaths. This explains why the elemental composition in organs is related to elemental composition in phytoliths.

Our study also demonstrates that for rice cultivars, a significant negative correlation exits between OC content of phytoliths and the elemental composition in plants (Phytolith-C vs. Phytolith, *<sup>R</sup>*<sup>2</sup> = −0*.*3177, Phytolith-C vs. Si, *<sup>R</sup>*<sup>2</sup> = −0*.*312, Phytolith-C vs. Al, *<sup>R</sup>*<sup>2</sup> = −0*.*2656) (**Table 5**). The higher the elemental content in plants is, the higher the phytolith content will be but the amount of occluded OC within the phytoliths will be lower. The different types of phytolith morphology and specific surface area between plant organs (e.g., between rice stem and rice sheath) may imply different occluded-OC content in phytoliths (Li et al., 2013). However, the impact of this factor on the OC occlusion within phytoliths remains to be examined.

#### **THE PRODUCTION AND STABILITY OF RICE PHYTOLITHS**

In the literature, we find some contradictory results about the control of plant species on the dissolution rate of phytoliths. Fraysse et al. (2009) document similar dissolution rates of phytoliths for four different plant species (horsetail, larch, elm and fern), while Bartoli and Wilding (1980) and Bartoli (1985) show that phytoliths from grass plants and deciduous species are more easily dissolved than that of coniferous species because of physico-chemical differences, i.e., higher Si/Al and Si/Fe ratios and water content. The adsorption of Al, Fe and other bi- and trivalent metals on phytoliths may influence their surface properties and decrease their rate of dissolution in the soil environment (Dove, 1995). In this study, the phytoliths of leaves and sheaths in five rice cultivars are characterized by lower ratio of Si/Fe and Si/Al compared to grains and stem (**Figures 1A,B**), which means that phytolith in leaves and sheaths incorporate more Al and Fe in their structure than in grains and stems. However, we clearly show that the kinetic release of bio-available Si from phytoliths in leaves are much higher relative to phytoliths from sheaths, grains and stems (**Figure 1A**). This is in contradiction with a previous view showing that phytolith solubility decreases with increasing metal content (Bartoli and Wilding, 1980; Bartoli, 1985; van Bennekom et al., 1989), but not with the results of Fraysse et al. (2009) showing similar dissolution rates for phytoliths with different elemental composition. This can be explained by the fact that phytolith solubility of rice cultivars could be controlled more by differences in terms of morphology (i.e., specific surface area) (**Figure 3**) and hydration rate (**Table 3**) than chemical composition. Our data show that the hydration rates of phytoliths (highest H2O content in stem phytoliths) are not related to Si bioavailability which indicates that hydration rate can only explain a small part of the variation in phytolith solubility. This observation requires further investigations for better quantifying the impact of morphology and hydration rate on dissolution rates of phytoliths from different rice cultivars. The **Figure 1B** also shows that the release of bio-available Si from phytoliths in stems among different rice cultivars vary significantly. Thus, besides the impact of rice organs on phytolith solubility, we show that the genetics also partly governs the release of bio-available Si from phytoliths.

 Recent research also indicate that organic matter pyrolyzed from plants (biochar) with high phytolith content can be applied as a

**Table 4 | Correlation analysis of the composition (elemental concentration and phytolith content) of organs in rice cultivars.**

*\*\*p <sup>&</sup>lt; 0.01; (n* <sup>=</sup> *20).*

**Table 3 | Elemental composition (%) of phytoliths extracted from organs of different rice cultivars. Means with various letters are significantly different at the** *p < 0.05* **level of confidence according to Duncan's Multiple Range Test.**

*Different lower case and uppercase letters indicate significant differences among the stands in rice organs and rice cultivars. aAccording to the following equation to estimate the content of H2O in phytoliths. H2O* <sup>=</sup> *100-SiO2-Al2O3-Fe2O3-MgO-OC.*

**Table 5 | The correlation between phytolith elements and plant elements.**

*\*p <sup>&</sup>lt; 0.05; \*\*p <sup>&</sup>lt; 0.01; (n* <sup>=</sup> *20).*

potential source of bio-available Si for crops of Si-accumulator plants (Houben et al., 2014; Liu et al., 2014). Therefore, amendment with biochar made from leaves and sheaths of rice characterized by the highest amount of phytoliths and the highest release rate of Si could be promising for enhancing the bio-availability of Si while increasing OC storage and soil fertility.

The findings of this study suggest that the optimization of utilization of different plant organs as Si amendment could play a key role for more efficient productivity in high Si-accumulating plants. On the other hand, we should increase PhytOC content in soils by increasing return of plant organs characterized by lower phytolith solubility such as grains and stems. We thus suggest further study of the kinetic release of dissolved Si and dissolved OC

**in phytoliths (mg bioavailable Si/g SiO2 in phytoliths) by successive extractions with 0.01 M CaCl2. (A)** Si released from phytoliths extracted from the organs of five rice cultivars (each phytolith sample is the mixture of same organ from five rice cultivars); **(B)** Si released from phytoliths extracted from stems of five rice cultivars. Each point represents the mean of three replicates.

and the evolution of Si and OC stock in soils after amendment with different plant organs.

# **CONCLUSIONS**

The present study mainly focused on the elemental compositions of organs and phytoliths in rice of different cultivars. The

rice cultivar significantly influences the elemental composition of plant organs and phytoliths. Our results show that rice cultivar and Si, Al, Fe uptake may impact production of phytoliths in plants and their quality (chemical composition). The OC content of phytoliths in rice cultivars seems to be significantly affected by the content of Si, Al, and Fe in plants, but not by the elemental concentrations in phytoliths.

In different rice cultivars, the role of the morphology and hydration rate of phytoliths seems to be at least as important as the chemical composition. This documents that rice organs and cultivar can largely influence Si dynamics in soil-plant systems through variable solubility of phytoliths. The soil amendment with plant residues and/or plant biochar should therefore be carried out taking into account the phytolith solubility of different plant organs of Si-high accumulator plants (e.g., leaves and sheaths of rice). On the other hand, phytoliths from grains and stems of rice seem to be more stable in soil and should be used if we aim to increase the soil OC stock through higher PhytOC. A more efficient use of plant residue (type of plant organ) as soil amendment should be considered to improve agronomical productivity of Si-high accumulating plants.

# **ACKNOWLEDGMENTS**

The work was supported by the National Natural Science Foundation of China (41103042), the Field Frontier Project of Institute of Geochemistry, Chinese Academy of Sciences<PHONE_NUMBER>), the Training Program for the Top Young Talents of Zhejiang Agricultural and Forestry University<PHONE_NUMBER>), the Program for the Distinguished Young and middle-aged Academic Leaders of Higher Education Institutions of Zhejiang Province (PD2013240). Jean-Thomas Cornelis is supported by "Fonds National de la Recherché Scientifique" (FNRS) of Belgium.

# **REFERENCES**

Dove, P. M. (1995). Kinetic and thermodynamic controls on silica reactivity in weathering environments. *Rev. Mineral. Geochem.* 31, 235–290.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 09 May 2014; accepted: 17 September 2014; published online: 10 October 2014.*

*Citation: Li Z, Song Z and Cornelis J-T (2014) Impact of rice cultivar and organ on elemental composition of phytoliths and the release of bio-available silicon. Front. Plant Sci. 5:529. doi: 10.3389/fpls.2014.00529*

*This article was submitted to Functional Plant Ecology, a section of the journal Frontiers in Plant Science.*

*Copyright © 2014 Li, Song and Cornelis. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Does elevated CO**<sup>2</sup>** alter silica uptake in trees?

# *Robinson W. Fulweiler 1,2 \*, Timothy J. Maguire2 , Joanna C. Carey3 and Adrien C. Finzi <sup>2</sup>*

<sup>1</sup> Department of Earth and the Environment, Boston University, Boston, MA, USA

<sup>2</sup> Department of Biology, Boston University, Boston, MA, USA

<sup>3</sup> The Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA

#### *Edited by:*

Jane DeGabriel, University of Western Sydney, Australia

#### *Reviewed by:*

Martin Karl-Friedrich Bader, New Zealand Forest Research Institute Ltd (SCION), New Zealand Wim Clymans, Lund University, Sweden

#### *\*Correspondence:*

Robinson W. Fulweiler, Department of Earth and the Environment, Boston University, 685 Commonwealth Avenue, Boston, MA 02215, USA e-mail<EMAIL_ADDRESS>
Human activities have greatly altered global carbon (C) and Nitrogen (N) cycling. In fact, atmospheric concentrations of carbon dioxide (CO2) have increased 40% over the last century and the amount of N cycling in the biosphere has more than doubled. In an effort to understand how plants will respond to continued global CO2 fertilization, longterm free-air CO2 enrichment experiments have been conducted at sites around the globe. Here we examine how atmospheric CO2 enrichment and N fertilization affects the uptake of silicon (Si) in the Duke Forest, North Carolina, a stand dominated by Pinus taeda (loblolly pine), and five hardwood species. Specifically, we measured foliar biogenic silica concentrations in five deciduous and one coniferous species across three treatments: CO2 enrichment, N enrichment, and N and CO2 enrichment. We found no consistent trends in foliar Si concentration under elevated CO2, N fertilization, or combined elevated CO2 and N fertilization. However, two-thirds of the tree species studied here have Si foliar concentrations greater than well-known Si accumulators, such as grasses. Based on net primary production values and aboveground Si concentrations in these trees, we calculated forest Si uptake rates under control and elevated CO2 concentrations. Due largely to increased primary production, elevated CO2 enhanced the magnitude of Si uptake between 20 and 26%, likely intensifying the terrestrial silica pump. This uptake of Si by forests has important implications for Si export from terrestrial systems, with the potential to impact C sequestration and higher trophic levels in downstream ecosystems.

**Keywords: elevated CO2, silicon, forest Si uptake, terrestrial Si pump, active Si accumulation, Si cycling**

# **INTRODUCTION**

We are currently conducting a global experiment by exposing Earth's biosphere to atmospheric carbon dioxide (CO2) concentrations unseen since the early Miocene, some 23 million years ago (Pearson and Palmer, 2000). From the start of the Industrial Revolution we have increased CO2 concentrations by approximately 40% (Pearson and Palmer, 2000) and in the spring of 2014 CO2 levels officially exceeded 400 ppm at the Mauna Loa Observatory (NOAA, 2014). This grand experiment will continue for the foreseeable future, as over the next century CO2 concentrations are expected to increase further (IPCC, 2013).

The impact of increased CO2 concentrations on the terrestrial biosphere has received much research attention over the last several decades. In particular, recent research has focused on how plants have and will respond to rapid CO2 concentration increases in combination with other regional and global climate changes, including warming air temperature and increased N availability (Norby and Luo, 2004;Ainsworth and Long, 2005; Bernhardt et al., 2006; Finzi et al., 2006). Among numerous other impacts, CO2 enrichment can also alter plant stoichiometry (Loladze, 2002). Exposure to elevated CO2 concentrations can cause declines in leaf nutrients, such as N and phosphorus, as well as trace element concentrations (Taub et al., 2008). The mechanism driving this decline is unclear but it has been attributed to nutrient limitation, increased non-structural carbohydrates, lower transpiration rates, or changes in nutrient allocation patterns (Roberntz and Linder, 1999). A compilation of studies on herbaceous and woody plants found that elevated CO2 concentrations decreased foliar element concentrations by up to 15% (Loladze, 2002). Research on rice, a key global crop, found similar declines in essential elements such as N, magnesium, and iron. Such declines in plant elemental concentrations could have serious repercussions for higher trophic levels, including exacerbation of human malnutrition (Loladze, 2002). A meta-analysis by Cotrufo et al. (1998a) found that aboveground N content declined on average by 14% under high CO2 concentrations. Changes in the N content of litter have also been shown to alter rates of decomposition and thus nutrient cycling within terrestrial ecosystems (Cotrufo et al., 1998b). However, changes in foliar elemental composition could also have largescale impacts on the cycling and transport of nutrients from land to the sea.

Silicon (Si) is the seventh-most-abundant element in the universe and the second-most abundant element in soils, the mineral substrate for most of terrestrial plant life (Epstein, 1994; Tréguer and De La Rocha, 2013). In the ocean, Si is a key nutrient required for diatoms and is used by many species of sponges, radiolarians, silicoflagellates, choanoflagellates, and even picocyanobacteria (Baines et al., 2012). Of particular importance are diatoms, as they form the base of many productive marine food webs and they sequester significant amounts of C to the deep ocean. In fact, a recent modeling effort contributes 50% of global ocean productivity to diatoms (Rousseaux and Gregg, 2013). The

primary source of Si to the ocean is the transport of dissolved and biogenic silica (BSi; SiO2) via rivers, which together account for 78% of the net annual Si oceanic inputs (Tréguer and De La Rocha, 2013). The Si transported by rivers ultimately comes from the weathering of the lithosphere, which is dependent on complex interactions between climate, geology, and biology (Bluth and Kump, 1994; Conley, 2002; Derry et al., 2005). Recently there has been emphasis on the role of biology in altering the timing and magnitude of Si export, specifically in terms of biological uptake by terrestrial vegetation (Conley, 2002; Fulweiler and Nixon, 2005; Gérard et al., 2008; Carey and Fulweiler, 2013b) and the role of human activities in directly altering watershed Si export (Clymans et al., 2011; Carey and Fulweiler, 2012a, 2013b; Vandevenne et al., 2012).

Plants readily absorb dissolved silica (DSi), also known as silicic acid (H4SiO4), the dominant form of Si in soil solutions (Epstein, 1994). DSi is taken up with water and carried in the transpiration stream where, with the evaporation of water, it becomes supersaturated and precipitated as BSi or phytoliths (Raven, 2003). Si provides numerous benefits to vegetation including increased resistance to bacteria, fungi, and grazers, as well protection from desiccation and metal toxicity (Hodson and Evans, 1995; Epstein, 1999; Wieczorek et al., 2014). Si is found throughout plants, from their roots to their shoots, but peak concentrations are generally observed at the transpiration termini (Canny, 1990). In fact, Si can compose 10% or more of the dry weight, exceeding those concentrations of well-known macronutrients (i.e., N and potassium; Epstein, 1994). In turn, the accumulation of Si by terrestrial vegetation over the seasonal cycle has the capacity to regulate the watershed export of Si to coastal ecosystems as plants grow and senesce (Fulweiler and Nixon, 2005; Carey and Fulweiler, 2013b). Alternatively, because BSi is 7–20 times more soluble than mineral silicates (Cornelis et al., 2010a), plants may also provide an important source of Si on biological times scales.

Within this context we wanted to determine if trees exposed to elevated CO2 concentrations would exhibit a decline in foliar Si content like those observed for other elements. To do this, we analyzed BSi concentrations of leaf samples from coniferous and deciduous trees from the Duke free-air CO2 enrichment (FACE) experiments in North Carolina. Additionally, we examined Si content under nitrogen (N) enrichment, as well as under the combined impact of CO2 and N enrichment. This is the first study to specifically examine the role of CO2 and N enrichment on Si content in trees.

#### **MATERIALS AND METHODS**

The Duke Face experiment is located in a *Pinus taeda* L. (*P. taeda*, loblolly pine) plantation at Duke University in North Carolina (35◦58 N, 79◦06 W). This plantation was established in 1983 and is characterized as having moderately low-fertility and acidic clay loam (McCarthy et al., 2010). In addition to the dominant pine, deciduous species present include *Acer rubrum* (*A. rubrum*, red maple), *Cercis canadensis* (*C. Canadensis*, red bud), *Cornus florida* (*C. florida*, dogwood), *Liquidambar styraciflua* (*L. styraciflua*, sweet gum), and *Ulmus alata* (*U. alata*, winged Elm). Mean annual precipitation is 1145 mm.

This study was conducted on leaves collected from CO2 and N enrichment experiments that took place between 1996 and 2006. The technical details of these studies have been published previously (e.g., Andrews et al., 2000; Luo et al., 2003; Finzi et al., 2007; McCarthy et al., 2010). Briefly, triplicate 30 m diameter treatment plots were exposed to current +200 ppm of CO2 above ambient during daylight hours in the growing season. Control plots (*n* = 3) were treated in a similar manner but with the addition of ambient air instead of CO2 (McCarthy et al., 2010). In 1998, two of these plots were divided in half and N fertilization began (11.2gNm−<sup>2</sup> y−<sup>1</sup> as urea). For more detailed information on the experimental design see http://face.env.duke.edu.

For this analysis we used dried green leaf samples from *P. taeda* and the five broadleaf species listed above, collected in 2002–2003 and 2006, respectively. *P. taeda* samples (*n* = 31) were separated and ground into a powder using a mortar and pestle. The premilled deciduous samples (*n* = 98) each contained composites of several individuals.

Biogenic Si concentrations were determined using a wet alkaline chemical extraction in a 1% Na2CO3 solution (Demaster, 1981; Conley and Schelske,2001). Duplicate samples were weighed to approximately 30 mg (between 28 and 34 mg) and digested in flat bottomed polyethylene bottles in a shaker bath at 85◦C and 100 rpm for four hours. We used a Seal AA3 flow injection autoanalyzer to colorimetrically determine DSi from the BSi aliquots using the molybdenum blue colorimetric method (Strickland and Parsons, 1972). Standards made of sodium hexafluorosilicate (Na2SiF6) as well as external standards were used throughout the analysis to check accuracy and were always within 4% of the expected value. We report all BSi values as %Si by dry weight.

All statistical analyses were completed using JMP Pro 10.0 and significance was judged with an alpha of 0.05. BSi concentrations across species and treatments exhibited equal variances according to several commonly used unequal variance tests (O'Brien = 0.6385, Brown-Forsythe = 0.3196, Levene = 0.1978). To explore potential drivers of BSi concentrations we used a linear mixed effects model to address if the BSi concentrations were different across species and treatment alone and combined. In this model we treated station as a random effect to assess the potential random station effects of the block design used at the Duke FACE experiment. We used an ANOVA to further explore differences in BSi concentrations across species and followed it by a *post hoc* means comparison with Tukey's test for honestly significant differences (HSD).

#### **RESULTS**

Across all sample types and treatments BSi values ranged from 0.05 to 3.01 %Si dry wt., with a median of 0.82 %Si dry wt. and mean of 0.98 %Si dry wt. *C. florida* exhibited the lowest and least variable BSi concentrations, while *U. alata* had the highest (**Table 1**; **Figure 1**). While some species did exhibit a decline in foliar BSi concentrations under elevated CO2, we found no statistically significant effect of treatment on foliar BSi concentrations (**Table 1**). In fact, our least squared model showed no effect of treatments, station, or treatment by species.

Because of the lack of statistical difference in plant BSi concentrations across all experimental treatments, we averaged

**Table 1 |The mean foliar biogenic silica (BSi) concentrations (%Si by dry wt. ± SE) under the three treatment types and the control for five deciduous and one coniferous species at the Duke FACE experimental forest.**

nm = not measured.

BSi concentrations by species. Clear species differences exist (**Figure 1**), as the majority of species are statistically different from one another (*p* < 0.0001). The exceptions are that *P. taeda*, *A. rubrum*, and *L. styraciflua* are not statistically different from each other, but they are statistically different from *C. florida, C. canadensis*, and *U. alata*. *U. alata* exhibited BSi concentrations statistically higher than all other species (*p* < 0.0001). In all cases, except for *C.* and *C. canadensis*, the mean Si foliar content suggests active accumulation (i.e., %Si above 0.46%; **Figure 1**).

# **DISCUSSION**

In this study we examined foliar BSi concentrations in five deciduous and one coniferous species across three treatments: CO2 enrichment, N enrichment, and N and CO2 enrichment. We expected to see a decrease in Si content as CO2 increased, compared to the control group, as this phenomenon has been observed for a range of other elements such as N, phosphorus, iron, and zinc (Loladze, 2002). In four species (*P. taeda, C. canadensis, A. rubrum, L. styraciflua*) we did observe a decline in BSi concentrations under elevated CO2 but none of them were statistically significant (**Table 1**). The largest decrease of 35% was observed in *C. canadensis* while the others ranged from 7 to 15%. These declines are on par with those reported for essential elements in other plant species and thus, the lack of significance may simply be due to a limited sample number. In one species, *U. alata*, we observed a small, non-significant increase in BSi concentrations under CO2 enrichment (**Table 1**). We know of only one other study that examined the impact of elevated CO2 on plant BSi concentrations. In that study of cotton (*Gossypium hirsutum* L.cv. Deltapine 77), the Si concentrations increased by 26%, although the results were also not significant (Huluka et al., 1994).

We observed a decline in BSi concentrations in N enriched trees compared to the control ranging from 8 to 50%, but none were statistically significant (**Table 1**). Similarly, no significant differences between BSi concentration in CO2 enriched vs. N enriched were found for any of the species. The combined impact of N and CO2 enrichment again exhibited mixed results. For three species (*A. rubrum, L. styraciflua, U. alata*) we observed BSi declines from 12 to 21% and in one species (*C. canadensis*) we observed an increase of 60% (**Table 1**). Previous work at this same site found no significant differences in leaf N, phosphorus, C, lignin, or total non-structural carbohydrates under elevated CO2 (Finzi et al., 2001). This is in contrast to other studies that found decreases in N and increases in C concentrations in other tree species (quaking aspen, *Populus tremuloides* and paper birch, *Betula papyrifera*; Lindroth et al., 2001). Elevated CO2 concentrations also decreased concentrations of N, potassium, phosphorus, and sulfur in Norway spruce (*Picea abies* L. Karst; Roberntz and Linder, 1999). From these and many other studies, foliar chemistry response to elevated CO2 and N appears to be site-specific. Additionally, although we did not observe statistically significant effects, the trends we document may be ecologically important. For example, Si provides defense against herbivory and the 15% decline we observed in *A. rubrum* could impact feeding preferences of vertebrate and invertebrate consumers. The lack of significance may be in part driven by our sample numbers

and thus, a larger study with more data may produce different results.

Silicon uptake by plants is divided into three broad categories (active, passive, or rejective). In active accumulation, plants acquire more Si than they would through water uptake alone. In rejective accumulation, also known as excluder accumulation, Si is taken up at a slower rate than water. Finally, in passive accumulation, water and Si have similar uptake rates (Raven, 1983; Ma et al., 2001b). Plants are assigned one of these categories according to various definitions, a thorough discussion of which is beyond the scope of this paper, but see Carey and Fulweiler (2014) in this Special Issue for a full description. Briefly, previous definitions have been based on Si concentrations in aboveground tissues, on the ratio of Si to calcium, and on the relationship between porewater Si concentration and aboveground tissue Si concentrations (e.g., Jones and Handreck, 1967; Takahashi et al., 1990; Ma et al., 2001a, respectively). More recent work has focused on the presence/absence of Si transporter genes in roots (*Lsi1* and *Lsi2*) and shoots (*Lsi6*) of rice (Ma et al., 2008; Yamaji et al., 2008). Research on accumulation modes in trees is surprisingly lacking. Cornelis et al. (2010b) observed both passive and rejective Si accumulation growth in coniferous tree saplings grown hydroponically. And a decrease in Si concentration with depth was observed in a temperate coniferous forest and designated as active accumulation (Gérard et al., 2008). Adult trees likely rely more heavily on groundwater and thus, in order to precisely determine the mode of Si accumulation, measurements of Si concentrations in groundwater, porewater, and within the tree are needed. Unfortunately, this is beyond the scope of this paper. Therefore, we apply the simplest definition that describes accumulation status as a function of Si concentration in the aboveground tissue alone: active accumulators as >0.46% Si by wt., passive accumulators as between 0.25 and 0.46% Si by wt., and excluders as <0.25% Si by wt. (Ma et al., 2001b; Street-Perrott and Barker, 2008). We acknowledge the limitations of this definition, as aboveground BSi tissue concentrations can be impacted by numerous factors, such as porewater DSi availability and external stressors. However, given our dataset, it is the one most appropriate for us to use. Defining Si accumulation status in trees by linking Si concentrations in aboveground vegetation to changes in porewater and groundwater, and locating Si transporter genes within trees are important areas of future research.

We observed a wide range in foliar BSi concentrations (**Table 1**). The low Si concentrations found in *C. florida* may indicate that these trees excluded H4SiO4. Overall however, the BSi concentrations observed in the Duke forest are 40 to 150% higher than those previously reported for similar species (Hodson et al., 2005). One reason for higher concentrations found in the Duke Forest could be the different soil and climate in North Carolina compared to the majority of studies reported in Hodson et al. (2005), which were dominated by northern temperate field sites. Our samples could also have higher BSi concentrations because of the land use legacy at the Duke Face site. In 1983, just 13 years before these experiments started, the forest was cut, trunks were removed, and the remaining material was burned (Finzi et al., 2001). The impact of land use change and disturbance on Si cycling is an emerging topic. From what we currently know, greater DSi losses have been observed following deforestation (Likens et al., 1970; Conley et al., 2008).

The median and mean BSi concentration (0.81 and 0.98 %Si dry wt., respectively) of the species we studied here is higher than many well-known actively Si accumulating groups, including those found in grasses (*Poaceae*) and sedges (*Cyperaceae*; Jones and Handreck, 1967; Raven, 1983; Ma and Takahashi, 2002). Uptake by forest trees has been hypothesized as a mechanism responsible for both the clear seasonal cycle of Si concentrations in stream water (Fulweiler and Nixon, 2005) and the observation of forested watersheds exporting significantly less Si than watersheds dominated by urban-land uses (Carey and Fulweiler, 2012a, 2013b). Given these data, and the known limitations of Si accumulation definitions, we can only hypothesize that this forest is actively accumulating Si. Regardless, the high Si concentrations we observed support the idea that forests are a critical component in regulating the flux of Si from land to the sea.

#### **DUKE FACE SI UPTAKE**

The impact of elevated CO2, N, and combined elevated CO2 and N led to an approximately 28% increase in net primary production (NPP) at the Duke Face site between 1996 and 2004 (McCarthy et al., 2010). We used the mean NPP over this period to estimate the amount of Si taken up by the Duke forest for the control and elevated CO2 treatments. We focused on the CO2 treatment because we do not have BSi concentrations for the *P. taeda* under N fertilization or the combined elevated CO2 and N fertilization treatments. Additionally, biomass at this site is dominated by *P. taeda*, which comprises ∼98% of the tree basal area (Finzi et al., 2001). We calculated foliar Si:C ratios by dividing the treatment specific median %Si value of either *P. taeda* alone or all the species together by 0.47, as C concentrations in biomass are well constrained between 45 and 50%. We then multiplied this Si:C ratio by the known amount of C in each treatment to get a treatment specific Si foliar uptake value (Conley, 2002; Carey and Fulweiler, 2012b). We estimated woody biomass Si uptake using the mean temperate woody biomass %Si of 0.08 (Fulweiler and Nixon, 2005) and again divided by 0.47. We then prorated the amount of Si by the proportion of leaves (30%) versus woody biomass (70%) in a typical forest to determine a total Si uptake rate (**Figure 2**; Litton et al., 2007). Although we observed a decline in Si concentrations under elevated CO2, the total amount of Si taken up by *P. taeda* was 26% higher at elevated CO2 where NPP was significantly higher compared to ambient CO2 (control: 194 kmol Si km−2, elevated CO2: 251 kmol Si km−2). Together with the hardwood species, Si uptake rate was 20% higher in the elevated compared to ambient CO2 treatment, although absolute rates of uptake were higher than *P. taeda* alone (elevated CO2 = 313 kmol km−<sup>2</sup> <sup>y</sup>−1; ambient CO2 <sup>=</sup> 266 kmol Si km−2, **Figure 2**). These values are on the high end of those reported for forested systems but well within the reported range. For example, Gérard et al. (2008) reported 157 kmol Si km−<sup>2</sup> for a Douglas fir forest in France, while Meunier et al. (1999) reported an uptake of over 3400 kmol Si km−<sup>2</sup> in a bamboo forest.

A review of FACE experiments found that irrespective of ecosystem type, aboveground production increased in the presence of higher CO2 and trees were more responsive than

herbaceous vegetation (Ward et al., 2013). Other studies have found similar increases in global terrestrial production (Melillo et al., 1993; Nemani et al., 2003). In addition, Pan et al. (2013) found that global forest biomass has increased in established forests. Such changes in primary productivity will also alter Si cycling. In fact, Si accumulating vegetation accounts for 55% of terrestrial NPP (33 Gton C y−1) an amount similar to the C sequestered by marine diatoms (Carey and Fulweiler, 2012b). This terrestrial Si pump has important implications for global climate, as Si cycling helps to control atmospheric CO2 concentrations through a variety of mechanisms, including chemical weathering of mineral silicates and C occlusion in soil phytoliths (Berner and Berner, 1997; Parr and Sullivan, 2005). In addition, this vegetation also plays a critical role in modulating the amount and timing of Si export from watersheds to downstream receiving waters (Carey and Fulweiler, 2012a, 2013b), which has direct implications for marine C dynamics. Here, we show that anthropogenically driven enhanced NPP may result in an increase in the terrestrial Si pump as forests take up more Si. In turn, the increased terrestrial Si sink may alter Si availability in aquatic systems. Diatoms require N and Si on a one to one molar basis (Redfield, 1963). Thus, the ratio of N to phosphorus to Si (N:P:Si) helps to control the composition and abundance of phytoplankton species assemblages. Human activities, such as fertilizer use and land use change have increased N and P loading to coastal systems worldwide. Phytoplankton respond to these elevated nutrients by increased productivity. At first, diatoms will bloom until all the Si is consumed at which point other non-Si requiring species will flourish (Anderson et al., 2002). The enhanced Si uptake by forests under elevated CO2 may be another way in which humans are altering nutrient stoichiometry in coastal receiving waters.

Missing from this discussion is the mechanism driving our findings that CO2 and/or N additions have no significant impact on Si accumulation in aboveground biomass. Of course, with more data and different study sites we might observe a significant impact of these factors on Si accumulation rates in forest

or other terrestrial vegetation types. In fact, a recent study found higher Si concentrations in the porewater, sediment, roots, and occasionally the aboveground biomass of a heavily N enriched salt marsh (Carey and Fulweiler, 2013a). Certainly other factors such as changes in water availability and growing season length, as well as warming temperatures, are all factors that might influence foliar BSi accumulation. Here we propose an alternative idea for exploration: we hypothesize that in ecosystems with altered transpiration rates, corresponding changes to leaf Si concentrations will also be observed because Si is delivered to vegetation via water. Higher transpiration rates should, if passive or active accumulation is occurring, result in higher Si concentration in leaves, as Si is typically concentrated at transpiration termini. Conversely, if transpiration rates decline, then less Si will be deposited. Experimental work on Douglas fir saplings found higher Si concentrations that were attributed to greater transpiration in those seedlings (Cornelis et al., 2010b). However, at the Duke FACE experimental site no changes in transpiration were observed and maybe this is why we observed no significant changes in Si concentration (Ward et al., 2013). Complicating these simple ideas is the original hypothesis that motivated this work – enhanced CO2 lowers elemental composition of leaves such as N, phosphorus, and potassium. Thus, quantifying the interplay between structural changes in vegetation and transpiration rates, as well as water availability under future climate change scenarios, will be a critical next step in our understanding of climate change impacts on terrestrial Si cycling.

## **CONCLUSION**

Our data of BSi concentrations in 6 species from the Duke FACE Experiment does not support our initial hypothesis that elevated CO2 concentrations would decrease foliar Si content. In fact, we observed no consistent or significant impact of any of the treatments on foliar Si content. However, according to the simplest definition based on aboveground tissue Si concentrations, we did find evidence that four out of the six tree species we studied may be active Si accumulators. These tree species had Si concentrations higher than some of the most well-known Si accumulators (e.g., grasses and sedges). Further, the higher NPP values observed under elevated CO2 resulted in higher Si uptake rates under elevated CO2 conditions in the Duke forest. Based on this analysis we hypothesize that anthropogenic change, specifically elevated atmospheric CO2 concentrations, may increase biological Si pumping in forests, increasing the magnitude of the terrestrial Si pump.

## **ACKNOWLEDGMENTS**

This research was supported in part by the Sloan Foundation in a fellowship to Robinson W. Fulweiler. The Duke Forest FACE was supported by his study was supported by the US Department of Energy (Grant No. DE-FG02-95ER62083) through the Office of Biological and Environmental Research (BER) and its National Institute for Global Environmental Change (NIGEC), Southeast Regional Center (SERC) at the University of Alabama, and by the US Forest Service through both the Southern Global Climate Change Program and the Southern Research Station. Adrien C. Finzi acknowledges ancillary support from the US NSF

(DEB0236356). Thanks to Jeffrey Pippen for his assistance with the field sampling at Duke. We also thank Ken Czapla for training Timothy J. Maguire on the Seal Autoanalyzer and running many of the Si samples. We thank Hollie Emery for her statistical guidance. We thank our two reviewers who provided helpful suggestions and edits that improved our manuscript.

#### **REFERENCES**

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 06 September 2014; accepted: 19 December 2014; published online: 13 January 2015.*

*Citation: Fulweiler RW, Maguire TJ, Carey JC and Finzi AC (2015) Does elevated CO*<sup>2</sup> *alter silica uptake in trees? Front. Plant Sci. 5:793. doi: 10.3389/fpls.2014.00793 This article was submitted to Functional Plant Ecology, a section of the journal Frontiers in Plant Science.*

*Copyright © 2015 Fulweiler, Maguire, Carey and Finzi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited andthatthe original publication inthis journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*


**William Osterholz 1,\*, Kevin King 1, Mark Williams 2, Brittany Hanrahan 1 and Emily Duncan 3**

Received: 21 August 2020; Accepted: 13 November 2020; Published: 19 November 2020

**Abstract:** Phosphorus (P) stratification in agricultural soils has been proposed to increase the risk of P loss to surface waters. Stratified soil sampling that assesses soil test P (STP) in a shallow soil horizon may improve predictions of P concentrations in surface and subsurface discharge compared to single depth agronomic soil sampling. However, the utility of stratified sampling efforts for enhancing understanding of environmental P losses remains uncertain. In this study, we examined the potential benefit of integrating stratified sampling into existing agronomic soil testing efforts for predicting P concentrations in discharge from 39 crop fields in NW Ohio, USA. Edge-of-field (EoF) dissolved reactive P (DRP) and total P (TP) flow-weighted mean concentrations in surface runoff and tile drainage were positively related to soil test P (STP) measured in both the agronomic sampling depth (0–20 cm) and shallow sampling depth (0–5 cm). Tile and surface DRP and TP were more closely related to shallow depth STP than agronomic STP, as indicated by regression models with greater coefficients of determination (R2) and lesser root-mean square errors (RMSE). A multiple regression model including the agronomic STP and P stratification ratio (Pstrat) provided the best model fit for DRP in surface runoff and tile drainage and TP in tile drainage. Additionally, STP often varied significantly between soil sampling events at individual sites and these differences were only partially explained by management practices, highlighting the challenge of assessing STP at the field scale. Overall, the linkages between shallow STP and P transport persisted over time across agricultural fields and incorporating stratified soil sampling approaches showed potential for improving predictions of P concentrations in surface runoff and tile drainage.

**Keywords:** dissolved reactive phosphorus; total phosphorus; soil test phosphorus; soil stratification; water quality