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Silicon Dynamics During 2 Million Years of Soil Development in a Coastal Dune Chronosequence Under a Mediterranean Climate

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Abstract

Silicon (Si) in plants confers a number of benefits, including resistance to herbivores and water or nutrient stress. However, the dynamics of Si during long-term ecosystem development remain poorly documented, especially the changes in soils in terms of plant availability. We studied a 2-million-year soil chronosequence to examine how long-term changes in soil properties influence soil Si pools. The chronosequence exhibits extreme mineralogical changes—from carbonate-rich to quartz-rich soils—where a carbonate weathering domain is succeeded by a silicate weathering domain. Plant-available Si concentrations were lowest in young soils (Holocene, < 6.5 ka), increased in intermediate soils (Middle Pleistocene, 120 ka), and finally decreased toward the oldest, quartz-rich soil (Early Pleistocene, 2 Ma). Silicon availability is likely low and relatively constant in the young soils because (1) carbonate weathering consumes protons and therefore reduces weathering of silicate minerals and (2) Si adsorption by secondary minerals is high in alkaline soils. In the middle-aged sites, Si availability rises with the loss of carbonates and the formation of kaolinite that appears to drive its concentration, and then falls in the oldest sites with quartz enrichment. The increasing accumulation of biogenic silica following carbonate depletion indicates stronger soil–plant Si cycling as ecosystem development proceeds. A literature analysis confirms the shift in processes controlling Si availability between the carbonate and silicate weathering domains. Overall, our results show a nonlinear response of plant-available Si to long-term pedogenesis, with likely important implications for the Si-related functioning of terrestrial ecosystems.

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Adapted from Cornelis and others (2011b).

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Acknowledgements

All the authors would like to thank the Western Australian Department of Biodiversity, Conservation and Attractions for letting us sample soils along the Guilderton chronosequence and for the access to these rare, biodiverse and outstanding ecosystems. This work would not have been possible without the invaluable analytical advice and help of Jean-Charles Bergen, Francois Fontaine and François Fontaine (ULiège) as well as Anne Iserentant (UCLouvain) whom we sincerely thank. We also thank the “Laboratoire d’Analyses des Sols INRA” (Arras, France). J-T.C and F.dT were supported by “Fonds National de la Recherche Scientifique” of Belgium (FNRS; Research Credit Grant for the project SiCliNG CDR J.0117.18). Finally, we thank the two referees for their valuable and thoughtful inputs during the review process.

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Correspondence to Felix de Tombeur.

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Author’s contribution

FdT and J-TC elaborated the research question, and all the authors designed the field approach. FdT and J-TC collected samples. FdT performed the analyses. FdT and J-TC interpreted the data. FdT wrote the first version of the manuscript, and all authors contributed to the text.

Electronic supplementary material

Below is the link to the electronic supplementary material.

10021_2020_493_MOESM1_ESM.pdf

Figure S1 – Soil profiles and pedogenic horizons of the Guilderton dune chronosequence. Photos were found in Turner and others (2018) (PDF 10002 kb)

10021_2020_493_MOESM2_ESM.pdf

Figure S2 – XRD diffraction patterns of the studied bulk soils. The number represents the chronosequence stage. The dotted bars in different colors represent different minerals: red for kaolinite, black for quartz, yellow for K-feldspar and plagioclase, and blue for carbonate minerals (calcite, calcite-Mg, aragonite) (PDF 330 kb)

10021_2020_493_MOESM3_ESM.pdf

Figure S3 – SiCC concentrations versus SiAA concentrations (mg kg−1) along the Guilderton chronosequence. Black lines indicate the regression line between both variables. Shaded areas represent 95% confidence interval of the regression. Equation regression, coefficients of determination (R2) and p-values are shown. The filling color of the points indicates the clay concentration of the sample (PDF 206 kb)

10021_2020_493_MOESM4_ESM.pdf

Table S1 – Soil total elemental composition of the studied soil horizons. Detection limits (dl) were 0.2 g kg−1 for Mg, K, Na, Al and Fe and 10 mg kg−1 for Mn. Standard errors are indicated in parentheses (n = 3). Table S2 – Si extracted with CaCl2, acetic acid, Na2CO3 and oxalate and ratio of SiCC to Sitot. Detection limits (dl) were 0.04 g kg−1 for Siox; 0.5 mg kg−1 for SiCC and SiAA. Standard errors are indicated in parentheses (n = 3). Table S3 – Literature data used for soil pH and SiCC concentrations found in Figure 6. Soil types have been translated into descriptions to harmonize between the different classifications systems (PDF 481 kb)

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de Tombeur, F., Turner, B.L., Laliberté, E. et al. Silicon Dynamics During 2 Million Years of Soil Development in a Coastal Dune Chronosequence Under a Mediterranean Climate. Ecosystems 23, 1614–1630 (2020). https://doi.org/10.1007/s10021-020-00493-9

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