Data from: Silicon mediates geographic variation of herbivory-related traits in a widespread plant invader

Lu, Jinan1 ; Guo, Yaolin1; Zhao, Yu-Jie1; Wu, Jihua2; Li, Bo3; Richards, Christina4; Ju, Rui-Ting 1

Published Sep 11, 2025 on Dryad. https://doi.org/10.5061/dryad.w6m905r0j

Data files

Sep 11, 2025 version files 29.60 KB

Raw_data.xlsx

27.08 KB
README.md

2.52 KB

Abstract

Silicon, the Earth’s second most abundant element, affects plant defenses across large geographic scales, which is an interesting yet mostly unexplored issue for non-native species. We investigated silicon-mediated variation in defensive/nutritional traits and palatability to generalist herbivores in 16 geographic populations of the invasive grass Spartina alterniflora collected from native and introduced ranges. We found that silicon supplementation generally increased leaf silicon content, which then enhanced plant physical/chemical defenses and reduced nutrition, ultimately impeding the growth of generalists. Yet, the pathways of silicon accumulation affecting generalists differed between plant provenances: enhancing quantitative and qualitative chemical defenses in native populations, but improving quantitative chemical and structural defenses in introduced ones. This suggests a silicon-mediated shift in Spartina’s defense strategy following introduction. Our findings provide insights into how non-native plants utilize silicon to enhance defenses, emphasizing the importance of metalloid defenses in invasion success.

https://doi.org/10.5061/dryad.w6m905r0j

Description of the data and file structure

we examined 16 native and introduced populations of Spartina to investigate the geographic variation in its palatability to generalist herbivores and the associated traits in response to silicon supplementation.

Files and variables

File: Raw_data.xlsx

Description: Raw_data.xlsx contains only one sheet: Plant traits & herbivore growth

Variables

Column 1: Si treatment — Si+/Si−
Column 2: Range — The original range of plant populations: native range, high-latitude introduced range and low-latitude introduced range
Column 3: Population — The abbreviation of plant populations:
- MC: Morehead City, North Carolina
- SI: Sapelo Island, Georgia
- TB: Tampa Bay, Florida
- TS: Tangshan, Hebei
- DY: Dongying, Shandong
- LYG: Lianyungang, Jiangsu
- YC: Yancheng, Jiangsu
- SH: Chongming, Shanghai
- CX: Cixi, Zhejiang
- TZ: Taizhou, Zhejiang
- WZ: Wenzhou, Zhejiang
- FZ: Fuzhou, Fujian
- QZ: Quanzhou, Fujian
- ZZ: Zhangzhou, Fujian
- BH: Beihai, Guangxi
- LZ: Leizhou, Guangdong
Column 4: Family — The propagule source
Column 5: Sqrt_Si (mg/g) — The square-root transformed leaf silicon content
Column 6: Ln_SLA (cm2/g) — The natural-log transformed specific leaf area
Column 7: Toughness (N) — The leaf toughness
Column 8: Sqrt_JA (mg/g) — The square-root transformed jasmonic acid content
Column 9: Tannins (mg/g) — The leaf tannin content
Column 10: Flavonoids (mg/g) — The leaf flavonoid content
Column 11: Carbon (mg/g) — The carbon content
Column 12: C: N ratio — The carbon-to-nitrogen ratio
Column 13: Sqrt_myth_Growth (mg) — The square-root transformed weight gain in fresh biomass of Mythimna separata
Column 14: Loc_growth (mg) — The weight gain in fresh biomass of Locusta migratoria

Code/software

All analyses were performed with R version 4.1.2 software. We used the lme4 package for linear mixed models (LMMs) to analyze differences in dependent variables as affected by silicon treatments and population ranges. To understand the relationships among silicon treatments, leaf traits, and generalist performance in each plant population range, we employed the lavaan package to construct three structural equation models (SEMs).