DOI: 10.5061/dryad.j3tx95xsc
title: Data and code from: Temperature affects the relative importance of phenotypic plasticity and natural selection contributing to the niche breadth of invasive plants

description: 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.
description: We selected nine field sites in the Hainan, Guangdong, Fujian,
 Zhejiang, Shanghai, Jiangsu, and Shandong provinces spanning the
 latitudinal gradient (19–38° N) of <em>S</em>.
 <em>alterniflora</em> 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 &gt; 30 m to avoid repeated
 collection of the same clone belongs to the same lineage with
 <em>S</em>. <em>alterniflora</em> 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 <em>S. alterniflora</em> 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 8<sup>th</sup>, 2019;
 Mid-latitude common garden: November 15<sup>th</sup>, 2019;
 Low-latitude common garden: November 13<sup>th</sup>, 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
 15<sup>th</sup>, 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
 30<sup>th</sup>, 2020 for a total of 197 days and the seedling
 survival rate was determined at the end of the germination common garden
 experiment.
description: # Temperature affects the relative importance of phenotypic plasticity and
 natural selection contributing to the niche breadth of invasive plants
 **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.