Stress alters the role of silicon in controlling plant water movement
Data files
Sep 22, 2023 version files 111.27 KB
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Conductance_In_Stressed_Plants.csv
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Conductance_In_Unstressed_Plants.csv
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README.md
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Transpiration_In_Stressed_Plants.csv
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Transpiration_In_Unstressed_Plants.csv
Abstract
- One function of plant Si is ameliorating stress, including drought and salinity stress, which can induce active Si uptake in addition to passive uptake via transpiration. However, the interactions and feedbacks between stress, water movement, and Si uptake remain unknown.
- To examine this gap, we compiled papers reporting transpiration and/or stomatal conductance of plants exposed to stresses while varying Si availability.
- Our meta-analysis (34 studies, excluding rice) showed that stress alters the role of Si in controlling water movement across diverse plant groups. Increased Si availability significantly increased water movement in stressed plants, particularly stomatal conductance (p<0.001, k=84) in plants exposed to salinity (p<0.05, k=20) and drought (p<0.05, k=45) stress.
- This signal of increased conductance was most apparent in C4 plants (p<0.001, k=41) and Poales (p<0.001, k=47). These findings have implications for plants under increasing water and salinity stress, particularly for Poales, where survival in affected ecosystems could be mediated by soil Si availability, and in agricultural systems, supplying Si to water-stressed plants could increase productivity.
- Intriguingly, Si addition to unstressed plants had no consistent impact on water movement, with reduction of water movement with Si addition to unstressed plants in 50% of studies, mostly those involving non-Poales species. This is an important first broad-scale Si cost quantification, as the costs of Si for plants have remained stubbornly mysterious, hampering evolutionary and functional understanding of plant Si use.
README: Stress alters the role of silicon in controlling plant water movement
https://doi.org/10.5061/dryad.pzgmsbct6
We asked questions about the impact of silicon supply on water movement in plants, and if stress impacted this relationship. To do this we converted the results of multiple studies into effect sizes that could then be quantitatively combined in a meta-analysis. All effect sizes report a comparison for a given response measure (conductance and transpiration separately) between plants supplied vs not supplied with silicon, and we considered stressed and unstressed plants separately. Our meta-analysis (34 studies) showed that stress alters the role of Si in controlling water movement across diverse plant groups. Increased Si availability significantly increased water movement in stressed plants, particularly stomatal conductance (p<0.001, k=84) in plants exposed to salinity (p<0.05, k=20) and drought (p<0.05, k=45) stress. This signal of increased conductance was most apparent in C4 plants (p<0.001, k=41) and Poales (p<0.001, k=47). The effect sizes extracted from multiple studies, then used to conduct our analyses, are reported here.
Description of the data and file structure
The title of each .csv file indicates whether it contains effect sizes for transpiration or conductance, and for stressed or unstressed plants. Each file reports the effect size (Hedges D and a measure of variance) comparing plants supplied with vs not supplied with silicon in an experiment, collated from published studies. All .csv files have the same headings, which are described in more detail below.
Title: source paper title
REF_ID: a numerical value for each paper that allowed easy identification of data from the same paper to factor into analyses
Authors: source paper authors
Source.Title: source journal name
Publication.Year: source publication year
DOI: source doi, where known
Species: species of plant used in the comparison
Stress: type of stress applied (e.g. drought, salinity) in the study. If these plants are in the unstressed files, the plants are in the control treatment to compare to this stress, but stress has not be applied here
Order: taxonomic order of species of plant
Oder2: Order re-classified as Poales or non-Poales
C3C4: photosynthetic pathway of species (C3 or C4)
Response_Measure: transpiration or conductance
N: number of replicates in the study
Hedges_D: effect size of the experimental outcome of the study comparing plants supplied with silicon vs those not supplied with silicon. Effect sizes are for one response (e.g. conductance or transpiration) which is indicated in the Response_Measure column and file names. Whether stressed or unstressed plant treatments were selected is indicated in file name. This effect size measure compares two means using a pooled standard deviation and bias correction and is a measure of the number of standard deviations by which the means differ (Hedges & Olkin, 1985).
HedgesD_var: The standard deviation value of the above.
Methods
We systematically identified papers testing or reporting the impact of Si availability on plant conductance and transpiration by searching the Web of Science database, for TOPIC: (silicon OR silica) AND TOPIC: (transpiration OR stomatal conductance) AND TOPIC: (plant OR leaf OR leaf OR foliar) and NOT TOPIC (rice) in November 2021. We excluded rice from our analyses. We extracted values for stomatal conductance and transpiration, for experiments in which plants were grown with and without Si addition (+/- Si) and with or without stress (+/- stress) applied to the plants. We converted reported water movement values to stomatal conductance (mmol H2O m2 s-1) and transpiration rate (mol H2O m2 s-1) as appropriate, and all measures of variance to standard deviations.
We used the ‘metafor’ package (Viechtbauer, 2010) in R (R Core Team, 2022) to calculate the effect size (Hedges’ D) of the impact of silicon addition on one response (e.g. conductance or transpiration) at a time for individual studies. This effect size measure compares two means using a pooled standard deviation and bias correction and is a measure of the number of standard deviations by which the means differ (Hedges & Olkin, 1985). We considered stress and unstressed treatments separately. The effect sizes calculated from individual studies were then used to conduct our analyses. The raw effect sizes, prior to analysis, are reported here.
- Viechtbauer, W. (2010). Conducting Meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48.
- R Core Team (2022). R: A language and environment for statistical computing. Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.