DOI: 10.5061/dryad.5dv41nsd1
title: Data and R code used in: Plant geographic distribution influences chemical defenses in native and introduced Plantago lanceolata populations

description: Plants growing outside their native range may be confronted by new regimes
 of herbivory, but how this affects plant chemical defense profiles has
 rarely been studied. Using Plantago lanceolata as a model species, we
 investigated whether introduced populations show significant differences
 from native populations in several growth and chemical defense traits.
 Plantago lanceolata (ribwort plantain) is an herbaceous plant species
 native to Europe and Western Asia that has been introduced to numerous
 countries worldwide. We sampled seeds from nine native and ten introduced
 populations that covered a broad geographic and environmental range and
 performed a common garden experiment in a greenhouse, in which we infested
 half of the plants in each population with caterpillars of the generalist
 herbivore Spodoptera littoralis. We then measured size-related and
 resource-allocation traits as well as the levels of constitutive and
 induced chemical defense compounds in roots and shoots of P. lanceolata.
 When we considered the environmental characteristics of the site of
 origin, our results revealed that populations from introduced ranges were
 characterized by an increase of chemical defense compounds without
 compromising plant biomass. The concentrations of iridoid glycosides and
 verbascoside, the major anti-herbivore defense compounds of P. lanceolata,
 were higher in introduced populations than in native populations. In
 addition, introduced populations exhibited greater rates of
 herbivore-induced volatile organic compound emission and diversity, and
 similar chemical diversity based on untargeted analyses of leaf methanol
 extracts. In general, the geographic origin of the populations had a
 significant influence on morphological and chemical plant traits,
 suggesting that P. lanceolata populations are not only adapted to
 different environments in their native range but also in their introduced
 range.
description: <strong>Experimental design:
 </strong><em>Plantago lanceolata </em>seeds were
 collected from nine native and ten introduced populations across a wide
 latitudinal and longitudinal gradient throughout the world. Sterilized
 seeds were then germinated in pots filled with a mixture of sand and
 nutrient-poor soil under greenhouse conditions in Jena, Germany. Half of
 the eight-week-old <em>P. lanceolata</em> plants were exposed
 to five 3<sup>rd</sup> instar <em>S.
 littoralis</em> caterpillars for 48 hours, and the other half of the
 plants functioned as undamaged controls (n = 5 per population, per
 treatment). All plants were enclosed in mesh bags that were tightened at
 the bottom and at the top with cable ties. The
 experiment was staggered over five days, and each day a block of 38 plants
 (with two plants per population) was processed. To determine chemical
 defense traits, we first collected volatile organic compounds (VOCs) right
 after the herbivory treatment. After VOC collection, plant tissues
 (leaves, inflorescences, root crown and roots) were harvested separately
 and immediately flash-frozen in liquid nitrogen and then stored at -80 °C
 until further chemical analyses. Leaf and root samples were then
 lyophilized and weighed. Samples were homogenized to a fine powder using a
 ball mill. For chemical analysis, leaf and root powder (10 mg) was
 extracted with 1 mL methanol. <strong>Leaf area
 and leaf damage measurements: </strong>To estimate leaf area and
 experimental leaf damage by <em>S.littoralis
 </em>caterpillars, we took pictures of all leaves of each
 <em>P. lanceolata</em> individual right after harvesting.
 Damage by herbivory was determined by reconstructing the original leaf
 area with Adobe Photoshop CS5 to calculate the proportion of total leaf
 area (cm<sup>2</sup>) and grams consumed (leaf area lost
 divided by specific leaf area).
 <strong>Size-related and resource-acquisition
 traits:</strong><em> </em>Number of leaves, leaf area
 (cm<sup>2</sup>), and<em> </em>plant dry mass
 (g<sub>dw</sub>), including leaves, roots, flower stem, and
 flower biomass, were analyzed as plant size-related traits, taking into
 account only non-infested plants. For analyses of carbon and nitrogen
 concentrations, approximately 10 mg homogenized leaf material were weighed
 into tin capsules and measured with an Elemental Analyzer.
 <strong>Chemical analysis: </strong>Untargeted
 metabolic profiles for <em>P. lanceolata</em> populations
 leaves were obtained by ultra-high-performance liquid chromatography
 coupled via electrospray ionization (ESI) to a qTOF mass spectrometer
 (UHPLC-ESI-HRMS), using both the positive and negative ionization modes.
 Targeted analyses for leaf and root tissues of<em>
 </em>iridoid glycosides, verbascoside, flavonoids, and phytohormones
 were conducted using an HPLC-MS/MS system. Volatile organic compound (VOC)
 emissions of <em>P. lanceolata</em> were identified and
 quantified using a GC-MS and GC-FID.
description: # Data and R code used in: Plant geographic distribution influences
 chemical defenses in native and introduced Plantago lanceolata populations
 ## Description of the data
 and file structure * **00_ReadMe_DescriptonVariables.csv**: A list with
 the description of variables from each file used. *
 **00_Metadata_Coordinates.csv :** A dataset that includes the coordinates
 of each Plantago lanceolata population used. * **00_Metadata_Climate.csv
 :** A dataset that includes coordinates, bioclimatic parameters, and the
 results of PCA. The dataset was created based on the script
 "1_Environmental variables.qmd" *
 **00_Metadata_Individuals.csv:** A dataset that includes general
 information about each plant individual. Information about root traits and
 chemistry is missing in four samples since we lost the samples. *
 **01_Datset_PlantTraits.csv:** Size-related and resource allocation traits
 measured of *Plantago lanceolata* and herbivore damage. *
 **02_Dataset_TargetedCompounds.csv:** Phytohormones, Iridoid glycosides,
 Verbascoside and Flavonoids quantification of the leaves and roots of
 *Plantago lanceolata*. Data generated from HPLC *
 **03_Dataset_Volatiles_Area.csv:** Area of identified volatile compounds.
 Data generated from GC-FID * **03_Dataset_Volatiles_Compounds.csv:**
 Information on identified volatile compounds. Data generated from GC-MS. *
 **04_Dataset_Metabolome_Negative_Metadata.txt:** Metadata for files in
 negative mode * **04_Dataset_Metabolome_Negative_Intensity.xlsx :** File
 with the intensity of the metabolite features in negative mode. The file
 was generated from Metaboscape and adapted as required for the Notame
 package. * **04_Dataset_Metabolome_Negative_Intensity_filtered.xlsx:**
 File generated after preprocessing of features in negative mode. During
 the notadame pacakged preprossesing 0 were converted to na *
 **04_Dataset_Metabolome_Negative.msmsonly.csv:** File with a intensity of
 the the metabolite features in negative mode with ms/ms data. File
 generated from Metaboscape. *
 **04_Results_Metabolome_Negative_canopus_compound_summary.tsv:** Feature
 classification. Results generated from Sirius software. *
 **04_Results_Metabolome_Negative_compound_identifications.tsv:** Feature
 identification. Results generated from Sirius software. *
 **05_Dataset_Metabolome_Positive_Metadata.txt:** Metadata for files in
 positive mode * **05_DatasetMetabolome_Positive_Intensity.xlsx :** File
 with a intensity of the the metabolite features in positive mode. File
 generated from Metaboscape and adapted as required for the Notame package.
 * **05_Dataset_Metabolome_Positive_Intensity_filtered:** File generated
 after preprocessing of features in positive mode.During the notadame
 pacakged preprossesing 0 were converted to na ## ## Code/Software *
 **1_Environmental vairables.qmd:** Rscript to Retrieve bioclimatic
 variables from based on the coordinates
 of each population and then perform a principal components analysis to
 reduce the axes variation and included the first principal component as an
 explanatory variable in our model to estimate trait differences between
 native and introduced populations. Figure 1b and 1d *
 **2_PlantTraits_and_Herbivory:** Rscript for statistical anaylsis of
 size-related traits, resource allocation traits and herbivore damage.
 Figure 2. It needs to source: Model_1_Fucntion.R, Model_2_Fucntion.R,
 Plot_Function.R * **3_Metabolome:** Rscript for statistical anaylsis of
 *Plantago lanceolata* metabolome. Figure 3. It needs to source:
 Metabolome_preprocessing_R, Model_1_Fucntion.R, Model_2_Fucntion.R,
 Plot_Function.R. * **4_TargetedCompounds:** Rscript for statistical
 anaylsis of *Plantago lanceolata* targeted compounds. Figure 4. It needs
 to source: Model_1_Fucntion.R, Model_2_Fucntion.R, Plot_Function.R *
 **5_Volatilome:** Rscript for statistical anaylsis of *Plantago
 lanceolata* metabolome. Figure 5. It needs to source: Model_1_Fucntion.R,
 Model_2_Fucntion.R, Plot_Function.R * **Model_1_Function.R** : Function to
 run statistical models * **Model_2_Function.R** : Function to run
 statistical models * **Plots_Function.R** : Function to run plot graphs *
 **Metabolome_prepocessing.R:** Script to preprocess features