Phytolith Assemblages and Opal Concentrations from Modern Soils

Quaternary International 287 (2013) 101e113

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Phytolith assemblages and opal concentrations from modern soils differentiate temperate grasslands of controlled composition on experimental plots at Cedar Creek, Minnesota

Mikhail S. Blinnikov a,*, Chelsey M. Bagent a, Paul E. Reyerson b a Department of Geography, St. Cloud State University, St. Cloud, MN 56301, USA b Department of Geography, University of Wisconsin-Madison, Madison, WI 53706, USA article info abstract

Article history: Researchers frequently assume that phytolith assemblages in modern soils reflect composition of recent Available online 29 December 2011 vegetation because of the direct deposition of silica into the soil, once plants decay. This paper tests this assumption and determines whether temperate grasslands of different composition can be reliably detected based on their silica record in topsoil in a controlled experiment. The differences in total biogenic opal concentration (TBOC) and diversity of morphotypes were assessed in the Biodiversity II experiment (E120) at Cedar Creek Ecosystem Science Reserve, Minnesota, USA, where controlled mixtures of C3 grasses, C4 grasses, legumes, non-legume forbs, and woody shrubs (Quercus) were grown for a period of eight years. The plots have been manually maintained to contain the target species, and thus provide an opportunity to test numerous hypotheses regarding phytolith production patterns under diverse mixtures of plants. Soil samples were obtained from plots representing a variety of functional group mixtures. Pinch soil samples of 20 g from 10 random locations inside each plot were obtained. Phytoliths were extracted from each sample by chemically removing organics and carbonates and using heavy liquid flotation. A chemical dissolution method was used to obtain estimates of TBOC. Morphotypes were counted under a microscope. Morpho- types were analyzed on all plots against each other and against the morphotypes expected in the plants that grow on each plot using ANOVAs, linear regression, PCA and cluster analysis. Average above-ground biomass of expected phytolith producers was weakly but positively correlated with the TBOC values (R2 ¼ 0.42). The morphotype analysis showed that species’ composition was most accurately reflected in the phytolith assemblages on grass-dominated plots. For example, it was possible to distinguish C3,C4, or mixed grass- dominated plots from each other. Although the majority of phytoliths were from Poaceae, large shares were also from forbs and woody plants. Plots without any grasses still had some presence of grass phytoliths suggesting limited horizontal translocation and/or inheritance. Ó 2011 Elsevier Ltd and INQUA. All rights reserved.

1. Introduction reconstructions makes their modern depositional patterns essential to study. Phytoliths are silica (opal) microfossils produced in tissues of Although species of many families produce phytoliths (Piperno, higher plants. Monosilicic acid (H4SiO4) is absorbed from soils by roots 1989), in the temperate regions of North America and Eurasia only and is deposited as hydrogenated non-crystalline SiO2 in the plant a few families are responsible for over 95% of all phytoliths (Voronkov tissues, inside specialized cells, in cell walls of non-specialized cells, et al., 1978; Piperno, 2006). Speciﬁcally, these are Poaceae (grasses), and in intercellular spaces (Raven, 1983; Perry et al., 1984; Piperno, Cyperaceae, Asteraceae (Lanning and Eleuterius, 1989; Piperno, 2006). Phytoliths provide dual function of structural support 2006), ferns, horsetails, conifers (Klein and Geis, 1978), and some (increased rigidity and strength) and protection from herbivores and deciduous trees (Geis, 1973; Bozarth, 1992). Dicot forbs produce few pathogens in plants, although their exact role is unclear (Piperno, diagnostic shapes of silica (Morris et al., 2009a), but contribute some 2006). Their utility in paleoenvironmental and archeological amorphous biogenic silica to the soils. A few families common in the temperate regions do not appear to accumulate silica at all (e.g., Fabaceae and Brassicaceae) and are silent in the soil phytolith * Corresponding author. record. Poaceae (grass) phytoliths have been the most studied (Twiss E-mail address: [email protected] (M.S. Blinnikov). et al., 1969; Blackman, 1971; Brown, 1984; Mulholland, 1989;

Fredlund and Tieszen, 1994; Blinnikov, 2005), particularly at the not from a controlled experiment. More recently, Fishkis et al. (2010) subfamily and tribe level (Watson and Dallwitz, 1994). demonstrated that vertical translocation of common reed phytoliths Analysis of soil assemblages of phytoliths has emerged as in intact soil cores is relatively minimal even with vigorous watering a powerful method of paleoreconstructions, especially for the semi- and introduced earthworms, ranging from 10 to 20 mm, with higher arid areas, such as grasslands, where pollen or macrofossils are range observed in sandy, as compared to silty, soil. Their study did not scarce (Jones, 1969; Lu and Liu, 2003; Gallego and Distel, 2004 address the question of horizontal translocation. Clearly, empirical Blinnikov, 2005; Boyd, 2005; Lu et al., 2005; Osterrieth et al., 2009; testing of the hypothesis of local deposition in an experimental Morris et al., 2009a,b). Much of the reconstructions involving phy- setting is required. toliths assume direct in situ deposition underneath the parent plant driven by gravity. Once embedded in the soil profile, phytoliths may 2. Regional setting translocate downward, upward, or sideways with water, burrowing animals, cryoturbation or fire, but little empirical evidence exists to The study area is located at the Cedar Creek Ecosystem Science suggest the spatial and temporal scale of such translocations (Barboni Preserve (CCESP) of the University of Minnesota, which is located et al., 1999; Bremond et al., 2004; Boyd, 2005). In any case, it is ex- 50 km north of Minneapolis, Minnesota (Fig. 1). Established in 1940, pected that the vast majority of the soil phytolith record represents the preserve comprises 2200 ha in Anoka and Isanti Counties. The highly localized signals, as plants do not actively disperse phytoliths preserve is part of the Anoka Sand Plain, a large subsection of the far away, unlike pollen (Piperno, 2006). However, Fredlund and Minnesota and northeast Iowa morainal section of the Eastern Tieszen (1994, 1997) found out that only about half of phytoliths in Broadleaf Forest Province (MN DNR, 2009). Anoka Sand Plain is an the modern soils of the North American Great Plains could be outwash plain of the Wisconsin glacial origin. The main source of attributed to the local sources. Many came from extralocal sources, glacial meltwater came from the Superior and Rainy lobes of the defined as a few meters to a few hundred meters away. However, Laurentide Ice sheet before 12,000 years ago. The sand plain is their study relied on observational evidence from native prairies and homogenous laterally and extends for 20e30 km north to south and

Fig. 1. Location of Cedar Creek Ecosystem Science Preserve in Minnesota, USA. M.S. Blinnikov et al. / Quaternary International 287 (2013) 101e113 103

40e50 km east to west north of the Mississippi River. Moraines in 3.2. Soil sample processing adjacent subsections surround the outwash plain and the Superior Lobe ground moraine forms the northern border. The Anoka Sand Pinch soil samples were taken in the summer of 2001 from ten Plain stretches across the northern Twin Cities metropolitan area, random places on each plot to obtain about 20 g of aggregate which includes St. Cloud to the west and North Branch to the east (topsoil) for each plot. The samples were substantially litter free (MN DNR, 2009). and represent direct subsurface samples (<1 cm of topsoil). The soil The Anoka Sand Plain is underlain by the bedrock of Cambrian and samples were processed using traditional acid digestion and heavy Ordovician dolomite, sandstone, and shale. Above the bedrock, the flotation techniques (Pearsall, 2000; Blinnikov, 2005). About 10 g of surface glacial deposits are usually less than 60 m thick (MN DNR, soil for each sample were dried and weighed (sand was previously 2009). Soils are primarily derived from the sand of the outwash removed through sieving). Carbonates were removed by heating plain and most of these sandy soils are dry upland soils (Psamments), samples in HCl (10%) solution heated for 1 h. Next, organics were except for some organic soils (Hemists) found throughout the removed by heating in 70% nitric acid with a pinch of potassium outwash plain in the ice block depressions and tunnel valleys, and perchlorate added for 3 h. The sediment was then neutralized by some prairie soils (Aquolls) along the Mississippi River (MN DNR, light solution of KOH, washed twice, and deflocculated by adding 2009). 5% sodium pyrophosphate, then washed again. Heavy liquid CCESP lies at an ecotone between prairie to the west and forest flotation involved adding ZnI2 solution to the specific gravity of to the east. Its uplands are covered by a fire-dependent mosaic of 2.3 g/cm3 to each sample, shaking vigorously, and centrifuging at oak savanna, prairie, hardwood forest, pine forest, and abandoned 3000 rpm for 10 min. Floating phytoliths were then siphoned off fields. The lowlands are comprised of ash and cedar swamps, bogs, the top and put in a new tube. This procedure was repeated until no marshes, and sedge meadows. Large tracts of the pre-agricultural new material was observed near the surface. The obtained phyto- ecosystems of the region are preserved within its boundaries as liths were dried in a drying oven and weighed. a successional chronosequence of more than 80 old fields of known history (Hodson, 1984). 3.3. Estimating biogenic silica

3. Materials and methods The dry original soil weights and dry phytolith weights were compared to get an estimate of the percentage of total biogenic opal 3.1. Soil sample collection content in the soil (TBOC). While commonly used, this method for measuring weights that relies on gravity separation and heavy Soil samples were obtained from the experimental plots at liquid flotation technique may result in an error for two reasons. CCESP that were used in the Experiment 120 (E120) also known as Some phytoliths may remain lodged in the residue and not float to Biodiversity II experiment. E120 started in 1994 to test some the top. Also, based on experience, it is likely that some phytoliths fundamental assumptions in biodiversity and competition theory may get lost during the transfer process from vial to vial. For this (Tilman et al., 1997, 2006; Siemann et al., 1998; Lambers et al., reason, an alternative method of TBOC estimation that uses full 2004) and provided a convenient site to study modern phytolith dissolution of silica (DeMaster, 1981) was tried. Twenty samples production and deposition patterns. E120 is located in an aban- (10 from the heaviest, and 10 e lightest weights based on total doned brome (Bromus inermis Leyss.) field that was prepared with biomass on the plots) were chosen for a more reliable independent herbicide and fire with subsequent removal of the top 6e8cmof measure of the total biogenic opal concentration. This method has soil, with the remaining soil having been plowed and disked. Such been used successfully on a wide variety of sediments, ranging from treatment should have removed most pre-existing phytoliths terrestrial (Saccone et al., 2006, 2007), marine (DeMaster, 1981) from the plots. This study area consists of 340 nine by nine m plots and lacustrine (Flower, 1993) and utilizes an alkali solvent to impart separated by three m buffers. E120 used 168 plots within the silica dissolution, and the resulting solution concentration can be study area (www.cedarcreek.umn.edu/research/data/All_ measured. However, alkali solutions impart dissolution in all silica Experiment_Methods.php?input¼e120). These 168 plots were forms; the rates of which are determined by individual solubilities. seeded to have 1, 2, 4, 8, or 16 species of plants in different func- Sequential leaching is able to differentiate labile silica from mineral tional group mixtures. Five functional groups (FG) include Festu- forms (crystalline primary and secondary minerals) by focusing on coid C3 grasses, Panicoid C4 grasses, Forbs, Legumes, Woody the rate of silica dissolution through time (Follett et al., 1965; (Quercus), and various mixtures of them. These plots have been Segalen, 1968; McKyes et al., 1974; DeMaster, 1981). A critical manually weeded in the subsequent summer months and main- assumption is that higher solubility forms of silica (labile silica) will tained regularly throughout the years (Siemann et al., 1998; be quickly depleted, while low-solubility, crystalline forms will Lambers et al., 2004). Control over the specific plants and amount dissolve slowly and steadily. The resulting silica concentration of time for deposition make conclusions about in situ deposition through time (dissolution curve, Fig. 4) can then be broken into more reliable, because the exact composition of plants on the plots non-linear (labile) and linear (mineral) silica fractions through the are known (Fig. 2). use of linear regression. Labile silica content is estimated by fitting A subset of 51 plots of various combinations of functional a least-squares regression line using data points from the linear groups was used (Table 1, Fig. 3). It was not practical to sample all portion of the dissolution curve. This line is then extrapolated back 168 plots, and the design of E120 is not perfectly balanced across to time 0, which yields the true, corrected amount (Fig. 4). In all possible combinations of functional groups. This is reflected in essence, the y-intercept represents the offset of the mineral silica this study, with exact groups on the plots used shown in Table 1. curve generated by labile silica content. Although not all labile silica From the perspective of phytoliths, addition of legumes should not is necessarily biogenic, if the underlying soil is uniform, as is the make any difference, because this functional group does not case at the study site, any differences in its concentrations are likely produce any phytoliths (Voronkov et al., 1978; Piperno, 2006). to be due to the production of biogenic silica by vegetation on the Therefore, any plots with only legumes should only have phyto- plots. liths coming from outside the plots, assuming no inheritance of As an alkali solvent, 0.5 M NaOH is able to fully solubilize amor- phytoliths from the original vegetation before the start of the phous silica, as well as forms which are products of weathering, such experiment. as dissolved, adsorbed, and short-order clays (Follett et al., 1965). 104 M.S. Blinnikov et al. / Quaternary International 287 (2013) 101e113

Fig. 2. Visual appearance of selected combinations of the functional groups of plants growing on the E120 experimental plots at Cedar Creek. Each plot is 9 9 m in size. Plot 153 e C3 Grass (Agropyron smithii); Plot 31 e C4 Grass (Schizachyrium scoparium); Plot 165 e C3 and C4 Grass (Poa pratensis, Sorghum nutans); Plot 14 e Forb (Asclepias tuberosa, Liatris aspera); Plot 94 e Legume (Lespedeza capitata); Plot 151 e Woody (Quercus ellipsoidalis); Plot 126 e Bare Ground; Plot 130 e C3 and C4 Grass, Forb, Legume, and Woody (Achillea millefolium, Asclepias tuberosa, Elymus canadensis, Liatris aspera, Panicum virgatum, Petalostemon purpureus, Quercus macrocarpa, Schizachyrium scoparium).

However, given the mineral nature of the sample soils (sandy method of Jones and Dreher (1996).Briefly, aliquots were acidified outwash) as well as the short duration of soil formation, pedogenic with 5 ml 0.5 M H2SO4 in 25-ml class A volumetric flasks. After silica formation would be expected to be minimal. Given that only the acidification, 5 ml 0.0437 M ammonium molybdate tetrahydrate upper 6e8 cm of topsoil was removed, it is entirely possible that was added, mixed, and allowed to sit for approximately 2 min. pedogenic labile silica was inherited from the previous soil. This Consequently, 2.5 ml 1.33 M tartaric acid and 1 ml reducing solution effect was expected to be minimal due to downward mobilization of were added. Reducing solution consisted of 25 g sodium bisulfite, 2 g these forms. Saccone et al. (2007) documented losses of pedogenic sodium sulfite, and 0.4 g 1-amino-2-naphtol-4-sulfonic acid dis- labile silica due to downward movement following disturbance in solved into 250 ml H2O. Flasks were then brought to the 25-ml mark Spodosols. Likewise for these soils, any residual, inherited pedogenic using DI water and mixed thoroughly. Color was measured after 0.5 h labile silica would be lost from the current surface. Hence, the pres- using a Milton Roy Spectronic D spectrophotometer at 810 nm. ence of labile silica on the soil surface should be controlled by current Standard curves were generated daily. Following data point acquisi- vegetation (Bartoli, 1983; Alexandre et al., 1997; Alexandre and tion, outliers were identified using Cook’sDistance,Di (Cook, 1982). Meunier, 1999; Blecker et al., 2006; Borba-Roschel et al., 2006; Data point Di values which were greater than 20% of an F-distribution Conley et al., 2008; Cornelis et al., 2010). (a ¼ 0.05) where considered outliers and removed (Kutner et al., Samples were air-dried and crushed using a mortar and rubber 2004). Bootstrapping (500 iterations) was then performed using pestle. Approximately 0.1 g of sample was then immersed in 100 ml the remaining points, whereby the mean of the outcomes was 0.5 M NaOH at 85 C. Sample bottles were then placed in a recipro- considered the most likely labile silica estimate. cating water bath for up to 5.3 h. Aliquots were then drawn off using Experiments conducted with samples containing a known amount a digital pipettor at 0.5 h intervals, beginning 2 h after immersion. of silica gel have shown that the sequential leaching method is able to Aliquot size was typically 0.5 ml, although 0.25 ml was occasionally recover >90% of all labile silica (Koning et al., 2002; P. Reyerson, used for samples containing more silica than expected. Silica unpublished data). Likewise, sample reproducibility experiments concentration was then measured using a modified molybdate blue conducted by P. Reyerson yielded imprecision of less than 10%. M.S. Blinnikov et al. / Quaternary International 287 (2013) 101e113 105

Table 1 Soil samples processed for morphotype analysis from Cedar Creek E120 experiment.

Plot Functional groupsa Planted speciesb Above-ground biomass (g/m2)c Cover (%)d 2 L Lesca 122.48 22.90 6 4 Panvi, Schsc 98.02 25.93 11 F Achmi 126.46 35.59 14 F Asctu, Liaas 51.72 22.81 16 F Asctu 55.78 23.25 20 L Amopet 45.02 43.99 24 34F Asctu, Elyca, Panvi, Schsc 78.89 27.90 26 34L Agrsm, Elyca, Petpu, Somu 113.74 26.27 29 L Lesca 195.58 30.57 35 34FLW Agrsm, Amopet, Andge, Asctu, Elyca, Koecr, Lesca, Liaas, Luppe, 197.57 46.90 Monsol, Panvi, Petpu, Queel, Quema, Schsc, Somu 48 3L Koerc, Lesca 230.53 49.63 69 F Achmi 112.28 31.80 83 L Luppe 376.74 70.47 94 L Lesca 261.94 42.96 110 34L Elyca, Lesca, Luppe, Panvi 259.60 57.79 129 F Liaas 118.24 26.82 130 34FLW Achmi, Asctu, Elyca, Liaas, Panvi, Petpu, Quema, Schsc 269.14 48.68 135 4 Schsc 151.51 41.12 136 34FLW Achmi, Agrsm, Amopet, Andge, Asctu, Elyca, Lesca, Liaas, Luppe, 339.17 57.99 Monsol, Panvi, Petpu, Queel, Quema, Schsc, Somu 139 3L Agrsm, Elyca, Koecr, Lesca 352.13 54.01 151 W Queel 25.50 18.37 153 3 Agrsm 57.66 33.34 156 34FLW Achmi, Agrsm, Amopet, Andge, Asctu, Elyca, Koecr, Lesca, Liaas, 103.49 29.16 Monsol, Panvi, Petpu, Queel, Quema, Schsc, Somu 157 3 Agrsm 34.87 26.52 160 34FLW Achmi, Agrsm, Amopet, Andge, Asctu, Koecr, Lesca, Liaas, Luppe, 120.92 37.22 Monsol, Panvi, Petpu, Queel, Quema, Schsc, Somu, Schsc, Somu 161 W Quema 14.81 15.68 165 34 Poapr, Somu 130.18 37.12 171 3L Amopet, Asclu, Elyca, Koecr, Monsol, Petpul, Queel 252.60 71.74 174 34FLW Achmi, Agrsm, Amopet, Asctu, Elyca, Koecr, Lesca, Liaas, Luppe, 343.98 56.66 Monsol, Panvi, Petpu, Queel, Quema, Schsc, Somu, Schsc, Somu 176 34F Agrsm, Liaas, Panvi, Poapr 202.80 31.05 177 34FLW Amopet, Andge, Asctu, Koecr, Liaas, Quema, Schsc, Somu 246.25 60.76 178 34F Achmi, Agrsm, Elyca, Koecr, Lias, Monsol, Panvi, Schsc 524.43 72.90 193 4L Andge, Luppe 346.13 57.64 221 W Quema, Queel 15.50 17.20 229 34L Andge, Petpu, Poapr, Schsc 102.62 43.95 232 34FLW Amopet, Koecr, Luppe, Monsol, Panvi, Queel, Schsc, Somu 339.10 65.77 234 3L Elyca, Luppe 266.47 62.99 236 4L Lesca, Panvi 291.65 42.71 255 W Queel 32.18 15.81 256 3 Agrsm 47.51 30.80 259 4L Lesca, Schsc 295.64 66.47 266 34FLW Achmi, Agrsm, Amopet, Andge, Petpu, Quema, Schsc, Somu 140.50 39.16 280 4 Schsc 101.54 24.14 282 4 Somu 144.06 38.59 286 34L Lesca, Poapr, Schsc, Somu 224.34 48.34 292 34L Amopet, Andge, Elyca, Koecr, Lesca, Luppe, Poapr, Somu 281.00 68.10 296 W Quema 33.16 23.85 304 3 Agrsm 118.70 48.49 311 34 Koecr, Panvi 211.92 38.50 324 3 Elyca, Poapr 89.48 35.75 334 34 Elyca, Somu 96.88 33.04

a 3 e C3 grasses (Festucoids), 4 e C4 grasses (Panicoids), F e forbs (Asteraceae, other), L e legumes (Fabaceae), W e woody (2 species of Quercus). b These were target species of E120 experiment that were deliberately planted. Despite weedings, a few plots contained very small proportion, <1% by biomass, of additional species (not shown), for example, Bouteloua spp. which could have impact on phytolith soil record (see Discussion). Achmi: Achillea millefolium L. (Forb, Asteraceae); Agrsm:

Agropyron smithii Rydb. (C3 festucoid Poaceae); Amoca: Amorpha canescens Pursh (Legume, Fabaceae); Andge: Andropogon gerardii Vitman (C4 panicoid Poaceae); Asctu: Asclepias tuberosa L. (Forb, Asclepiadaceae); Elyca: Elymus canadensis L. (C3 festucoid Poaceae); Koecr: Koeleria cristata Pers. (C3 festucoid Poaceae); Lesca: Lespedeza capitata Michx. (Legume, Fabaceae); Liaas: Liatris aspera Michx. (Forb, Asteraceae); Luppe: Lupinus perennis L. (Legume, Fabaceae); Monﬁ: Monarda ﬁstulosa L. (Forb, Lamiaceae); Panvi: Panicum virgatum L.

(C4 panicoid Poaceae); Petpu: Petalostemon purpureus (Vent.) Rydb. (Legume, Fabaceae); Poapr: Poa pratensis L. (C3 festucoid Poaceae); Queel: Quercus ellipsoidalis E.J.Hill (woody); Quema: Quercus macrocarpa Michx. (woody); Schsc: Schizachyrium scoparium (Michx.) Nash (C4 panicoid Poaceae); Sornu: Sorghastrum nutans (L.) Nash. c Average value of biomass clipping done by E120 researchers in 1994, 1995 and 1996 as reported in E120 datasheet. Our soil samples were collected in 2001. d Average value of percent cover on plots in 1994, 1995, 1996 as reported in E120 datasheet. Our soil samples were collected in 2001.

3.4. Morphotype analysis them to be rotated to evaluate true 3D shapes), then using an optical Leica microscope at 400 magnification to count them The heavy liquid flotation method leaves phytoliths available (Yost and Blinnikov, 2011). For each sample about 300 phytoliths for counting. The counting was done by mounting phytoliths on were counted and classified. After counting 150, the counting was a slide suspended in immersion oil under a cover slip (allowing continued on the opposite side of the slide to get a better 106 M.S. Blinnikov et al. / Quaternary International 287 (2013) 101e113

Fig. 3. Map of all plots of the E120 experiment showing planted functional groups and proportions of C3 grass vs. C4 grass vs. non-grass phytoliths. sampling of phytoliths from that sample and as a form of inde- 4. Results pendent control (Alexandre and Bremond, 2009). The morphotype classification system used is that of Fredlund and Tieszen 4.1. Total biogenic opal accumulation (1994) for short cells, and Blinnikov (2005) for other morphotypes (Figs. 5 and 6). The International Code of Phytolith Fifty-three samples processed with the traditional method of Nomenclature (Madella et al., 2005) is used for standard mor- heavy liquid flotation and weighing the dry floated fraction yielded photype names. biogenic opal (silica) concentrations varying from a low of 0.0083% to M.S. Blinnikov et al. / Quaternary International 287 (2013) 101e113 107

a linear regression (Fig. 8 shows above-ground biomass results only). Three-year average biomass values (based on measurements in 1994, 1995 and 1996) account for the interannual variability on plots. Although below-ground biomass measurements were also available, the focus was on the above-ground biomass only, because previous phytolith research (Voronkov et al., 1978; Piperno, 2006)suggests that below-ground parts accumulate little silica, and also because in most field studies worldwide only above-ground biomass values for vegetation are usually available. Both unadjusted mean biomass value averaged over three years and an adjusted mean biomass value were used. Values on biomass production were weighted to accom- modate presumed difference in silicification rates in different functional groups. Specifically, values of 0.01 were used for legumes (almost no silicification based on many published sources, e.g., see literature reviews on silicification rates in various taxa in Voronkov et al. (1978) and Hodson et al. (2005)), 0.1 for forbs and woody plants (light silicification, about 10% of what is expected in grasses) and 1.0 for grasses (heavy silicification). For example, for a hypo- thetical mixed plot with equal proportion of legume, forb and grass presence in the biomass, the total biomass value was adjusted as following:

¼ : : þ : : þ : Madj 0 33 0 01MLegume 0 33 0 1MForb 0 33MGrass (1) Such adjustment would lower biomass value in plots, where plants other than grasses were planted. Plots with only grasses (C3,C4 or mixtures) would have the same biomass value as in the unadjusted case. Although some literature on variable rates of silicification in C3 vs. C4 grasses exists (Johnston et al.,1967; Fredlund and Tieszen,1994; Hodson et al., 2005), it was assumed that all grass species silicified equally. Fig. 4. Dissolution curves used in DeMaster’s method of estimation of total biogenic Linear regression with unadjusted biomass and DeMaster disso- opal concentration (TBOC) showing linear and non-linear portions (a) and linear lution data yielded a low positive R-squared value of 0.274. For extrapolation (b). adjusted biomass and DeMaster dissolution data the R-squared value was 0.418, indicating a stronger dependence of the TBOC on above- a high of 4.2317% of dry soil weight. Nineteen samples have been also ground biomass (Fig. 8). If traditional weighting data was used processed with the dissolution (DeMaster’s) method yielding values instead of DeMaster’s, the R-squared values were slightly above 0, from a low of 0.3299% to a high of 1.8%. In all but two cases, suggesting no relationship between the two. It is likely the error in DeMaster’s method yielded higher values, about 3e20 times greater the weight estimates by this imprecise technique that is causing this. on average (Table 2). This was expected, because DeMaster’s method This study indicates that weighing the extracted phytolith fraction measures all labile silica in the soil, including the smallest particles of should not be relied upon at all, and the dissolution technique should the clay fraction, while the standard method generally floats only the be used instead when estimating TBOC. silt fraction sized phytoliths. In the two exceptions, the DeMaster’s method yielded only a third of the yield in the traditional method. 4.2. Morphotype analysis Interestingly, both exceptions came from plots with legumes (which should contribute no silica) and C4 Panicoid grass (heavy silica A total of 13 morphotypes were used in this study. Three were production expected). Because the experimental pre-treatment of non-grass forms (blocky/globular, epidermal polygonal, epidermal soil was done uniformly across all plots, it was assumed that any anticlinal), nine were grass forms (plates, wavy/crenates, rondels, difference in TBOC on plots after 8 years of growing mixtures should bilobates, saddles, crosses, bilobates Stipa-type, elongate long cells be due to the difference in (re)deposition of biogenic silica by plants and bulliforms) and one (trichomes) was a mixed class with some grown on the plots during the experiment. Additional sources of contributed by grasses and others by dicots, e.g., Asteraceae. While biogenic silica include diatoms and sponges, which were observed in more individual morphotypes were distinguished during counts small numbers in many samples. The null hypothesis is that all plots (e.g., three kinds of rondels and four of crenates), the aggregate have the same TBOC after 8 years. scheme for reporting results is used here to make them comparable A one-way ANOVA with DeMaster’s dissolution data was done to other studies, especially Fredlund and Tieszen (1994), and to comparing the total biogenic opal concentration of grass-containing reduce counting error possible when distinguishing fine details plots and non-grass plots (those would be plots with legumes only, under the microscope. Fig. 5 shows common morphotypes used in with forbs only, or with woody species only). There is a distinct this study as they were observed in ashed plant material. Fig. 6 difference between them, although it is not significant with only shows same morphotypes as observed in soils from the Cedar nineteen samples used (Fig. 7). The mean value for grass-dominated Creek plots. Fig. 9 presents all counts from all plots in one graph. plots was 1.04 0.37%, while the mean value for non-grass plots was The first two axes of the PCA ordination results are shown on Fig. 10 0.78 0.26% (N ¼ 19, p ¼ 0.103). Thus, after only eight years of the and cluster analysis dendrogram is shown on Fig. 11. experiment, grass added about 0.25% of biogenic opal to the soils. Overall, the samples are not dramatically different from each Above-ground biomass per m2 and percent cover on plots were other (Fig. 9). Most morphotypes are observed on all plots, albeit in used as the independent variable with TBOC as dependent variable in different proportions. This is not surprising given the relatively crude 108 M.S. Blinnikov et al. / Quaternary International 287 (2013) 101e113

Fig. 5. Morphotypes found in ashed samples of the plant species growing on the E120 experimental plots at Cedar Creek: A e Rondels in Agropyron smithii; B e Rondels in Elymus canadenisis; C e Plates in Koeleria cristata; D e Plates and Rondels in Poa pratensis; E e Bilobates, crosses, and rondels in Andropogon gerardii; F e Bilobates in Panicum virgatum; G e Bilobates and Crosses in Schizachyrium scoparium; H e Bilobates, Saddles, and Crosses in Sorgastrum nutans; I e Blocky forms in Achillea millefolium; J e Blocky, Epidermis, and Trichomes in Asclepias tuberosa; K e Epidermis and Segmented Hairs in Liatris aspera; L e Blocky forms in Monarda ﬁstulosa; M e Epidermis and Segmented Hairs in Solidago rigida; N e Epidermal and Blocky forms in Quercus macrocarpa. M.S. Blinnikov et al. / Quaternary International 287 (2013) 101e113 109

Fig. 6. Morphotypes found in the soil samples from the E120 experimental plots at Cedar Creek (abbreviations in parentheses): A e Plate (pr), B e Short wavy plate (ws)/short lobed plate (ls), C e Long wavy plate (wl)/long lobed plate (ll), D e Long cell smooth straight (lr), E e Long cell deep spikes (ld), F e Rondel oval (ro), G e Rondel pyramidal (rp), H e Rondel keeled (rk), I - Bilobate Stipa-type (bs), J e True bilobate (bb), K - Cross (cs), L e Saddle (sa), M e Trichomes (ht), N e Bulliforms, O e Blocky/Other, P e Epidermal.

Table 2 Samples processed for TBOC by both traditional dry-weight and dissolution method of DeMaster’s (1981).

Plot TBOC, weight (%) TBOC, dissolution Functional groups 3-yr. above-ground 3-yr. cover Grass (G)/Non-grass (N) method (%) biomass average (g/m2) average (%) 2 0.2792 0.9437 L 122.475 22.90 N 20 0.1033 0.3299 L 45.025 43.99 N 56 1.2892 0.4388 4L 164.692 45.16 G 94 0.0647 0.8042 L 261.939 42.96 N 125 4.2317 1.313 4L 181.478 44.38 G 129 0.1425 1.0317 F 118.236 26.82 N 136 0.105 1.0467 34FLW 339.172 57.99 G 157 0.1964 0.892 3 34.872 26.52 G 161 0.2439 0.8701 W 14.805 15.68 N 168 1.497 0.955 34 94.600 54.33 G 177 0.0465 0.7648 34FLW 246.250 60.76 G 178 0.0428 1.8009 34F 524.433 72.90 G 221 0.0521 0.5569 W 15.500 17.20 N 255 0.095 0.6316 W 32.183 15.81 N 280 0.0923 0.656 4 101.539 24.14 G 296 0.1439 1.0823 W 33.161 23.85 N 311 0.2386 1.1221 34 211.922 38.50 G 324 0.2573 1.2283 3 89.484 35.75 G 334 0.0424 1.2625 34 96.878 33.04 G 110 M.S. Blinnikov et al. / Quaternary International 287 (2013) 101e113

With respect to PCA, squared-root transformed values were used instead of raw percentages to emphasize rarer morphotypes. The overall scatter plot actually looks similar even if raw values are used. The first two axes account for about 48% of the total variability of the data. The lower left corner is populated by samples from non-grass covered plots with assemblages dominated by blocky morphotypes. The lower right corner is populated by samples from mixed plots with significant presence of C4 grasses, with assemblages dominated by bilobates, crosses and insignificant number of saddles. The upper right corner is populated by samples with C3 grasses dominated by wavy/crenate morphotypes and rondels. The upper left corner is populated by a variety of samples, primarily by mixtures, with most prominent morphotype distinguishing this group being the trichomes and long cells. Very few Stipa-type morphotypes were found, which is not surprising given the absence of Stipa from the target species. Such morphotypes are more common in the native Minnesota prairie (Fredlund and Tieszen, 1997; Blinnikov, unpublished). Also, a few saddles were found in some samples, which were not expected at all, because no Chloridoid species of grass were planted. However, a few plots did have unintended weedy Bouteloua, a Chloridoid and a copious saddle producer, which evidently escaped annual weedings. The cluster analysis in MINITAB revealed the same broad three groupings as the PCA, namely non-grass plots dominated by blocky and epidermal morphotypes, mixed grass plots and pure C3 (wavy/ crenate and rondels) or C4 (bilobates, saddles and crosses) plots. Overall results seem to confirm to the expectations that modern vegetation is reflected in the upper soil phytolith assemblage, even after only eight years of growing the controlled mixtures.

5. Discussion Fig. 7. One-way ANOVA results for total biogenic opal concentrations on grass and non-grass dominated plots from Cedar Creek. TBOCW is estimated with the traditional heavy liquid flotation method with subsequent weighing of the extracted opal. TBOCD Study of phytolith taphonomy is required to improve accuracy of is estimated with DeMaster’s dissolution method. paleoenvironmental reconstructions (Rovner, 1986; Bowdery, 1999). In this study, experiment that lasted for only 8 years already level of morphotype distinction. For example, rondels were all produced marginally significant difference in total opal concentra- counted as a sum, although in reality some variation of keeled, tions on grass-vs. non-grass dominated plots as measured by two pyramidal and oblong rondels was observed in samples during alternative methods. Furthermore, plots covered with different microscopy. Nevertheless, even with this aggregated form of analysis, functional mixtures of plants could be distinguished based on mor- most samples are falling into three large clusters (Fig. 3): samples photype analysis by both PCA and cluster analysis. Specifically, as expected, phytolith records from C (Festucoid) grass plots were with a large proportion of non-grass forms, samples with either C3 or 3 reliably different from those of C (Panicoid) grass plots, from mixed C4 grass morphotypes and mixed C3eC4 samples. On non-grass plots, 4 the share of non-grass phytoliths was 40e75% of the total. On grass C3 C4 plots, and from plots dominated by either Asteraceae forbs or plots, the share of non-grass phytoliths was 5e15% (Figs. 3 and 10). woody (Quercus) shrubs. Also, as expected plots with only legumes had very low TBOC values and few morphotypes of phytoliths available for counts. Those phytoliths were primarily from grasses produced on the surrounding plots, across 3 m wide buffer, although the possibility that some may have been inherited from the pre- existent “brome field” cannot be excluded. This finding suggests that phytolith record in modern soils does reflect to a high degree the prevalent modern vegetation as most researchers assume, but that some local translocation sideways is possible. In an early study from Ohio, Wilding and Drees (1971) found that topsoil under native prairie contained 3e10 times as much biogenic opal per unit of volume as soils under deciduous forest. The prairie soils had about 0.1% of the weight in biogenic opal. Verma and Rust (1969) found 0.5% opal concentrations in Minnesota prairie soils. Using similar traditional floating and weighting method, the mean value for the grass plots was 0.33%. Using more precise DeMaster’s method, the mean value for the grass plots was 1.04%. Overall, the highest TBOC values were observed on plots with pure mixtures of C3 and C4 grasses and plots growing all functional Fig. 8. Linear regression of total biogenic opal concentration on grass vs. non-grass groups together (C and C grasses, forbs, legumes, and woody). This covered plots in E120 experiment with TBOC (‘Opal % Dis’) measured with the disso- 3 4 lution DeMaster’s method against above-ground adjusted biomass (‘AbvBioAdj, g/m2’). is not surprising, given that grasses are heavy phytolith producers Adjustment is explained in Formula 1. and a major conclusion of the E120 biodiversity experiment was that M.S. Blinnikov et al. / Quaternary International 287 (2013) 101e113 111

Fig. 9. All morphotype counts from E120 experimental plots used in this study. The values are square-root adjusted percentage values to emphasize more rare morphotypes for PCA and cluster analysis. Samples 1001e1006 are reference samples from a native mixed C3eC4 prairie in Minnesota.

more species grown together produce significantly higher overall biomass (Tilman et al., 1997). In contrast, plots with the lowest TBOC were pure legume, forb and woody plots. Phytoliths from grasses (Poaceae) dominated morphotype assemblages on all plots (80e95% of all morphotypes in the silt fraction; not including diatoms or sponge spicules). Grass phytoliths were also found on plots where no grass was planted, for example, on plots with only forbs or legumes. In a few cases, these were plots where grasses grew as non-intended weeds (e.g., Bouteloua grass was noted as <1% of cover on some plots, and it produced well- identifiable saddles). In other cases, phytoliths of grasses could come from the neighboring plots (Fig. 3) or inherited from the pre- existing “brome field.” With respect to the latter, there was no evidence for any of the phytoliths belonging unequivocally to B. inermis, the species that had been presumably grown at Cedar Creek site prior to the start of the experiment (typically, those would be flat, slightly undulating crenate forms). The experimental set-up

Fig. 11. Dendrogram of a cluster analysis of all samples (Ward’s method, Euclidean Fig. 10. Ordination of all morphotypes and plots by the principal components analysis distance, performed in MINITAB 15) showing distance between all Cedar Creek plots (first two axes shown, performed in MINITAB 15). The matrix of morphotype percent used in this study. Clusters 1 and 2 include primarily mixed plots (34FLW, 34F, 34L), values was squared-root transformed prior to the analysis: a) loadings of different cluster 3 includes primarily pure grass plots (3 and 4), and cluster 4 includes pure Forb, morphotypes’ plot, b) samples’ plot. Woody, and Legume dominated plots. 112 M.S. Blinnikov et al. / Quaternary International 287 (2013) 101e113 involved removal of 8e10 cm of topsoil, which should have removed Alexandre, A., Meunier, J.-D., 1999. Late Holocene phytolith and carbon-isotope most available phytoliths accumulated over the past century. record from a latisol at Salitre, south-central Brazil. Quaternary Research 51, 187e194. However, the possibility of some morphotypes being inherited Alexandre, A., Meunier, J.-D., Farbice, C., Koud, J.-M., 1997. Plant impact on the cannot be completely excluded, but the significant difference in biogeochemical cycle of silicon and related weathering processes. Geochimica e morphotype composition on plots (Figs. 8, 10 and 11) seems to argue et Cosmochimica Acta 61, 677 682. Barboni, B., Bonnefille, R., Alexandre, A., Meunier, J.-D., 1999. Phytoliths as paleo- against the strong inheritance signal. environmental indicators, west side Middle Awash valley, Ethiopia. Fredlund and Tieszen (1994) estimated that in the native grass- Palaeogeography, Palaeoclimatology, Palaeoecology 152, 87e100. land sites in the Great Plains, only about 50% of all phytoliths in Bartoli, F., 1983. The biochemical cycle of silicon in two temperate forest ecosystems. Environmental Biogeochemistry 35, 469e476. modern soils are truly local, with the rest brought in because of Blackman, E., 1971. Opaline silica bodies in the range grasses of southern Alberta. translocations with wind, fire and herbivores. How far the phytoliths Canadian Journal of Botany 49, 769e781. can travel is not clear from their study, but their “extra-local” phy- Blecker, S.W., McCulley, R.L., Chadwick, O.A., Kelly, E.F., 2006. Biologic cycling of silica across a grassland bioclimosequence. Global Biogeochemical Cycles 20, toliths seem to have come from 10s to 100s of meters away, while GB3023. doi:10.1029/2006GB002690. “regional” forms come from distances of many kilometres away. No Blinnikov, M.S., 2005. Phytoliths in plants and soils of the interior Pacific Northwest, such truly long-distance transported forms were found in this study, USA. Review of Palaeobotany and Palynology 135, 71e98. but a few phytoliths found on some plots could have come from Borba-Roschel, M., Alexandre, A., Varajao, A.F.D.C., Meunier, J.-D., Varajao, C.A.C., Colin, F., 2006. Phytoliths as indicators of pedogenesis and paleoenvironmental across a short buffer (<3 m) around the plots. This is similar to the changes in the Brazilian Cerrado. Journal of Geochemical Exploration 88, findings in Bremond et al. (2005), who found that, “the very short 172e176. distance between two plots (30 m) may induce an artifact because Bowdery, D., 1999. Taphonomy, phytoliths and the African Dust Plume. In: Mountain, M.-J., Bowdery, D. (Eds.), Taphonomy: The Analysis of Processes from phytolith assemblages from open sites represent vegetation from Phytoliths to Megafauna. ANH Publications, The Australian National University, a wider surrounding area than in forest where wind transportation is Canberra, pp. 3e8. fi weak.” Boyd, M., 2005. Phytoliths as paleoenvironmental indicators in a dune eld on the northern Great Plains. Journal of Arid Environments 61, 357e375. Bozarth, S.R., 1992. Classification of opal phytoliths formed in selected dicotyledons 6. Conclusions native to the Great Plains. In: Rapp Jr., G., Mulholland, S.C. (Eds.), 1992. Phytolith Systematics. Emerging Issues, Advances in Archeological and Museum Science, vol. 1, pp. 193e214. This study shows that even a short-term (8 years) controlled Bremond, L., Alexandre, A., Errol, V., Guiot, J., 2004. Advantages and disadvantages mixtures experiment results in significant differences both in the of phytolith analysis for the reconstruction of Mediterranean vegetation: an assessment based on modern phytolith, pollen and botanical data (Luberon, overall level of biogenic silica concentration and in morphotype France). Review of Palaeobotany and Palynology 129, 213e228. composition on plots, generally reflective of the vegetation above- Bremond, L., Alexandre, A., Hely, C., Guiot, J., 2005. A phytolith index as a proxy of ground biomass and species’ composition. While individual species tree cover density in tropical areas: calibration with leaf area index along cannot be detected, phytolith analysis can reliably identify festu- a forest-savanna transect in southeastern Cameroon. Global and Planetary Change 45, 277e293. coid vs. panicoid vegetation, as well as vegetation with a significant Brown, D.A., 1984. Prospects and limits of a phytolith key for grasses in the central component of Asteraceae (segmented hairs) or Quercus (epidermal United States. Journal of Archeological Science 11, 345e368. cells). Some sideways translocation of morphotypes is probably Conley, D.J., Likens, G.E., Buso, D.C., Saccone, L., Bailey, S.W., Johnson, C.E., 2008. Deforestation causes increased dissolved silicate losses in the Hubbard Brook occurring even on short time scales resulting in a small fraction of Experimental Forest. Global Change Biology 14, 2548e2554. the morphotypes coming from outside the 9 9 m plots, across at Cook, R.D., 1982. Residuals and Influence in Regression. Chapman and Hall, least a 3 m wide buffer. However, the proportion of such mor- New York, NY. Cornelis, J., Ranger, J., Iserentant, A., Delvaux, B., 2010. Tree species impact the photypes in this study was substantially lower than 50% or more as terrestrial cycle of silicon through various uptakes. Biogeochemistry 97, discussed in Fredlund and Tieszen (1994). The authors are currently 231e245. working on two additional lines of analysis: spatial assessment of DeMaster, D.J., 1981. The supply and accumulation of silica in the marine environ- e fi ment. Geochimica et Cosmochimica Acta 45, 1715 1732. hot spots associated with speci c plots as shown in Fig. 3 to Fishkis, O., Ingwersen, J., Lamers, M., Denysenko, D., Streck, T., 2010. Phytolith quantify the level of neighboring plot influences and a more transport in soil: a laboratory study on intact soil cores. European Journal of Soil detailed analysis of specific morphotypes, such as individual rondel Science 61, 445e455. Flower, R.J., 1993. Diatom preservation: experiments and observations on disso- and crenate forms, lumped together in this report. Even with this lution and breakage in modern and fossil material. Hydrologia 269/270, aggregated study, phytoliths can reliably identify extant prairie 473e484. vegetation on modern plots at least with respect to woody/forbs, Follett, E.A.C., McHardy, W.J., Mitchell, B.D., Smith, B.F.L., 1965. Chemical dissolution e Festucoid (C ) and Panicoid (C ) grasses. techniques in the study of soil clays: Part I. 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