Data and code from: Temperature affects the relative importance of phenotypic plasticity and natural selection contributing to the niche breadth of invasive plants
Data files
Apr 21, 2025 version files 142.10 KB
Abstract
Plant species adapt to changing climates through phenotypic plasticity and natural selection, affecting invasive plants’ niche breadth. However, our limited understanding of how temperature affects the relative importance of phenotypic plasticity and natural selection contributes to invasive plants' niche breadth across latitudes. Here, we used a model system, the salt marsh grass Spartina alterniflora, native to the United States but was introduced into China in 1979, spreading over 20° latitude. We collected seeds of S. alterniflora from nine locations across different latitudes in China, measured phenotypic plasticity, natural selection, and niche breadth of germination and post-germination traits in three greenhouse common garden experiments (low-latitude: 20.9° N, mid-latitude: 28.3° N, and high-latitude: 37.4° N) spread across the latitude in China. We found that germination time, germination percentage, germination index, and seedling survival all increased with latitude within the common gardens. Germination time showed a lower slope at the high-latitude common garden sites, but the other variables had higher slopes at the high-latitude common garden sites. The phenotypic plasticity of germination and post-germination traits across latitudes decreased with increasing latitude of origin, similar to germination niche breadth. Furthermore, temperature negatively affected the natural selection but positively affected the phenotypic plasticity. These results indicated that climate-driven selection favors sexual reproduction at higher latitudes and higher phenotypic plasticity at lower latitudes. Our findings highlight that phenotypic plasticity and natural selection could drive the niche breadth across latitudes. This is critical for predicting the niche breadths of invasive species and the potential management of biological invasions in future climate conditions.
1.Germination traits raw data: Cumulative germination, Germination index, Germination num, Germination rate, T50, Survival rate, GI plasticity, GR plasticity, GS plasticity, T50 Plasticity, Niche breadth.
- Garden_location: garden site name
- Provenance: field seed collection site name
- Garden_latitude: garden site latitude (N)
- Block_NO: block number
- Provenance_Latitude: field seed collection site latitude (N)
- Cumulative_per: germination rate per observation day
- Germination_day: day of observation
- T50: mean germiantion time (days)
- Germination_rate: germination percentage
- Germination_index: germination index
- Survival_rate: survival percentage
- Survival_num_mean: mean seeding survival number per provenance
- GI plasticity: germination index plasticity
- GR plasticity: germination rate plasticity
- GS plasticity: Germination survival plasticity
- T50 plasticity: mean germination time plasticity
2.Germination traits and provenance climate factors raw data: Germination index-T4C, Germination index-Tmax, Germination index-Tmean, Germination index-Tmin, Germination rate-T4C, Germination rate-Tmax, Germination rate-Tmean, Germination rate-Tmin, T50-T4C, T50-Tmax, T50-Tmean, T50-Tmin, Survival-T4C, Survival-Tmax, Survival-Tmean, Survival-Tmin, GI.Plasticity-T4C, GI.Plasticity-Tmax, GI.Plasticity-Tmean, GI.Plasticity-Tmin, GR.Plasticity-T4C, GR.Plasticity-Tmax, GR.Plasticity-Tmean, GR.Plasticity-Tmin, T50.Plasticity-T4C, T50.Plasticity-Tmax, T50.Plasticity-Tmean, T50.Plasticity-Tmin, GS.Plasticity-T4C, GS.Plasticity-Tmax, GS.Plasticity-Tmean, GS.Plasticity-Tmin.
- Garden_location: garden site name
- Provenance: field seed collection site name
- Garden_latitude: garden site latitude (N)
- Block_NO: block number
- Provenance_Latitude: field seed collection site latitude (N)
- Cumulative_per: germination rate per observation day
- Germination_day: day of observation
- T50: mean germiantion time (days)
- Germination_rate: germination percentage
- Germination_index: germination index
- Survival_rate: survival percentage
- Survival_num_mean: mean seeding survival number per provenance
- GI plasticity: germination index plasticity
- GR plasticity: germination rate plasticity
- GS plasticity: Germination survival plasticity
- T4C: total number of days less than 4 ℃ (days)
- Tmax: average daily maximum temperature (℃)
- Tmean: annual mean daily temperature (℃)
- Tmin: average daily minimum temperature (℃)
3.Germination traits and garden location climate factors raw data: Germination index-T4C(Garden), Germination index-Tmax(Garden), Germination index-Tmean(Garden), Germination index-Tmin(Garden), Germination rate-T4C(Garden), Germination rate-Tmax(Garden), Germination rate-Tmean(Garden), Germination rate-Tmin(Garden), T50-T4C(Garden), T50-Tmax(Garden), T50-Tmean(Garden), T50-Tmin(Garden), Survival-T4C(Garden), Survival-Tmax(Garden), Survival-Tmean(Garden), Survival-Tmin(Garden)
- Garden_location: garden site name
- Provenance: field seed collection site name
- Garden_latitude: garden site latitude (N)
- Block_NO: block number
- Provenance_Latitude: field seed collection site latitude (N)
- Cumulative_per: germination rate per observation day
- Germination_day: day of observation
- T50: mean germiantion time (days)
- Germination_rate: germination percentage
- Germination_index: germination index
- Survival_rate: survival percentage
- Survival_num_mean: mean seeding survival number per provenance
- GI plasticity: germination index plasticity
- GR plasticity: germination rate plasticity
- GS plasticity: Germination survival plasticity
- T4C: number of days less than 4℃ (days)
- Tmax: average daily maximum temperature (℃)
- Tmean: annual mean daily temperature (℃)
- Tmin: annual mean daily temperature (℃)
4.Germination data analysis code:
- R_Code_for_Germination_MS(Figure 2.3.4): This R code is used to calculate or analyze the Germination data and the results of this analysis are displayed in Figure 2.3.4.
- R_Code_for_Cor_between_Trait_and_Field_weather(Figure 5): The R code used to calculate the correlation (Cor) between a specific trait (such as plant height, yield, etc.) and field weather data (like temperature, rainfall, humidity), with the results shown in Figure 5 of the related paper.
- R_Code_for_Cor_between_Plasticity_and_Field_weather(Figure 6): R code used to calculate the correlation between plasticity and field weather data, which is visualized or summarized in Figure 6 of the related paper
- R_Code_for_Cor_between_Trait_and_Garden_weather(Figure S): This R code calculates the relationship between a specific trait and the weather data collected from a garden environment, and the results are presented in Figure S.
- Repeated_Measures_Analysis: This code is analyzing germination data using two different statistical methods: Repeated Measures ANOVA (RMANOVA) and a Linear Mixed Model.
- Summary of AVOVAs: The code evaluates relationships between various factors, such as Garden_location, Pro.latitude, Provenance_Latitude.
The script was created using version 4.3.2
5.Data Description
Categorical Variables
This dataset includes categorical variables representing field seed collection sites (provenance) and common garden location. Below is a detailed description of the site codes:
Provenance Codes
DZ: Seeds collected from Danzhou, Hainan Province, China
LZ: Seeds collected from Leizhou, Guangdong Province, China
YX: Seeds collected from Yunxiao, Fujian Province, China
LY: Seeds collected from Luoyuan, Fujian Province, China
YQ: Seeds collected from Yueqing, Zhejiang Province, China
HZW: Seeds collected from Hangzhouwan, Zhejiang Province, China
CM: Seeds collected from Chongming, Shanghai, China.
GY: Seeds collected from Ganyu, Jiangsu Province, China
DY: Seeds collected from Dongying, Shandong Province, China
Garden location Codes
Zhanjiang: garden located in Zhanjiang, Guangdong Province, China
Taizhou: garden located in Taizhou, Zhejiang Province, China
Dongying: garden located in Dongying, Shandong Province, China
Missing Data
Some cells in the dataset are intentionally left empty (blank) and NA to indicate no data available or unrecorded information. These values are not errors but reflect limitations in data collection.
We selected nine field sites in the Hainan, Guangdong, Fujian, Zhejiang, Shanghai, Jiangsu, and Shandong provinces spanning the latitudinal gradient (19–38° N) of S. alterniflora in China. Seeds were collected from nine field sites along a latitudinal gradient from south to north at maturity between September and November 2019 . At each site, we sampled 10 quadrats (0.5 × 0.5 m) that were separated by > 30 m to avoid repeated collection of the same clone belongs to the same lineage with S. alterniflora occurred in monospecific stands. The filled seeds from each quadrate were placed into separate zip-lock bags and stored in 10 PSU seawater at 4 ºC. To standard the local climate and document the mechanisms of seed germination and seedling establishment in S. alterniflora at different latitudes, we established three greenhouse common gardens across the latitudinal gradient of the species in Dongying (37.46° N, 121.39° E), Taizhou (28.65° N, 121.41° E), and Zhanjiang (21.27° N, 110.35° E), in November 2019. Each common garden comprised 10 rectangular plastic pools as blocks (length: 1.10 m, width: 0.82 m, depth: 0.26 m). Each pool contained nine plastic pots as provenance (18 cm diameter and 24 cm depth) grouped into three rows and three columns. Each bucket was filled with a mixture of 50% Jiffy peat substrate (Jiffy Products International BV, Moerdijk, Netherlands) and 50% vermiculite (v/v). In November 2019 (High-latitude common garden: November 8th, 2019; Mid-latitude common garden: November 15th, 2019; Low-latitude common garden: November 13th, 2019), 20 filled seeds were randomly selected from each quadrat for sowing, and 1800 seeds were sown in a single garden (20 seeds/quadrat × 10 quadrants × 9 sampling sites). Seeds from each quadrat were randomly sown on a 4 × 5-hole grid plate placed at the center of each plastic pot to accurately record the germination time of each seed. The locations of sampling sites varied haphazardly within each pool. The seeds were covered with a thin layer of soil of approximately 0.2 cm after sowing. Fresh water was sprayed on the soil surface above the seeds daily to keep them wet. Germinated seeds were counted daily beginning on November 15th, 2019 (when all seeds were sown in the three common gardens), and the germination time of each seed was recorded. Seed germination was assessed when the seed germ was exposed to the soil surface. The germination experiment ended when no new germinations occurred in a consecutive week (7 days). Seedlings were observed until May 30th, 2020 for a total of 197 days and the seedling survival rate was determined at the end of the germination common garden experiment.