DOI: 10.5061/dryad.hqbzkh1nh
title: Evolution of intraspecific floral variation in a generalist-specialist pollination system

description: Intraspecific processes impact macroevolutionary patterns through
 individual variation, selection, and ecological specialisation.
 According to the niche variation hypothesis, the broader ecological niche
 of generalist species has been proposed to increase in variation among
 individuals, either because they are constituted of diversified
 specialised individuals each exploiting a fraction of the species’ niche,
 or because they are constituted of true generalist individuals that
 experience relaxed selection. To test this hypothesis, we
 surveyed the individual floral morphology of species of Antillean
 Gesneriaceae, a group that has transitioned between
 specialisation for hummingbird pollination and generalisation
 multiple times throughout its evolutionary history. We
 characterised the profiles of corollas using geometric morphometrics and
 compared the intraspecific shape variance of specialists and generalists
 in a phylogenetic context. We used three approaches that differently
 accounted for the high dimensionality of morphological traits, the
 ancestral reconstruction of pollination syndromes over time, and the error
 associated with the estimation of the intraspecific variance. Our
 findings provide partial support for the niche
 variation hypothesis. If considering the whole shape in the
 analysis corroborated this idea, decomposing the shape into
 principal components indicated that not all aspects of the corolla exhibit
 the same pattern of variation. Specifically, pollination generalists tend
 to display greater intraspecific variation than specialists in
 terms of tubularity, but not of curvature. Accounting for the error in the
 estimation of the variance also reduced the support for the
 hypothesis, suggesting that larger sample sizes may be required to reach
 stronger conclusions. This study emphasises the reciprocal influence
 between plants and their pollinators on floral morphology at
 different biodiversity scales, by affecting intraspecific floral variation
 that can result in macroevolutionary patterns.
description: We quantified the corolla shape of species from the Gesneriinae
 subtribe using geometric morphometrics from flower photographs in strict
 lateral view. For each flower photograph, 32 landmarks were placed (6
 landmarks and 26 semi-landmarks). Two landmarks were positioned at the
 tips of the petal lobes, two at the base of the petal lobes, and two at
 the base of the corolla. Pollinator information was
 obtained from field-based information or inferred from flower
 characteristics for species with unstudied pollination biology in the
 field. The phylogeny of the Gesneriinae subtribe
 (Gesneriaceae) species was reconstructed in *BEAST from DNA sequences of 5
 nuclear genes (CYCLOIDEA, CHI, UFR3GT, F3H, and GAPDH ).
description: # Evolution of intraspecific floral variation in a generalist-specialist
 pollination system Access this dataset on Dryad DOI:
 10.5061/dryad.hqbzkh1nh ## Description of the data and file structure Each
 script starts with a brief description of what each does. The main scripts
 are noted from 1 to 7. Phylogenetic trees (spe.tree.txt and
 phylogenetic_tree.tre) are also available. The phylogenetic_tree.tre file
 is a combined tree of 2 *BEAST chains after convergence was verified, and
 spe.tree.txt is the filtered tree (i.e. species in the tree but for which
 we don't have 2D morphometrics). All the filtering is detailed in
 script 4. The folder Photos_of_Gesneriaceae_flowers.zip contains raw
 images used for geometric morphometrics. The Landmarks folder contains the
 raw data of individual floral morphology of species of Antillean
 Gesneriaceae and their pollination syndromes used in downstream analyses:
 * **data.csv** provides the metadata relevant to identifying each image in
 the photos zip folder, the pollination strategy, and a column
 "Confirmed", which defines if the pollination strategy has been
 confirmed by observation (yes) or if it is inferred from floral traits
 (no).  * **matrix_semilandmarks.csv** is used to identify the order of
 landmarks and sliding semi-landmarks. * **numerisation_YYY.MM.DD.txt**
 corresponds to the 2D geometric morphometric quantification of corolla
 shape, their corresponding file names numerisation_YYY.MM.DD_names.txt
 identifies the specimens numerised, and landmarks_YYY.MM.JJ.txt is the
 resulting file using the two precedent ones and the script
 landmarks_protocole_script.R, which is a shorter and generic version of
 the landmarks.R file. It transforms the landmark file obtained from ImageJ
 and pointpicker into a TPS-like file for further geometric morphometrics
 analyses. * **Files_to_remove.csv** identifies the files that were
 discarded. ## Code ### 1 - ImageJ logs to TPS-like.R This script is to
 prepare the landmark files we created using ImageJ/Fiji in the same format
 as if data were retrieved from the software TPS. ### 2 - TPS and
 cleaning.R This script is to use the TPS files and create a landmarks.rds
 file to use in downstream morphometric analyses. Additionally, the script
 landmarks_protocole_script.R is provided in the Landmarks folder as a
 generic and shorter version of the landmarks.R file. It transforms the
 landmark file obtained from ImageJ and PointPicker into a TPS-like file
 for further geometric morphometrics analyses. ### 3 - 2D\_morphometrics on
 specialists and generalists.R Read landmarks. Filter landmarks data per
 syndrome and remove species without enough photos. Procrustes analysis.
 Procrustes ANOVA. Create the objects land.gpa and
 data.sorted_hummingbird.mixed. PCA on individual coordinates, and scree
 plot. Create TPS figures of the mean floral shape and the morphology
 variation along the PCA axes. Same thing with the mean PC coordinates
 (shape) of each syndrome. Visualisation of the PCA and PCA on species
 means, as well as interactive PCA. From this script, you will produce the
 objects data.sorted_hummingbird.mixed and land.pca used in the JIVE
 analysis. ### 4 - Analysis of inter intra specific trait evolution.R This
 is the hierarchical Bayesian Integrative model of Trait evolution analysis
 (JIVE). First, we retrieve the phylogenetic tree and trim it to fit with
 the morphometric data. Prepare the trait matrices used in the joint inter-
 and intraspecific evolution analysis. Stochastic mapping of the
 pollination syndromes along the phylogenetic tree (SIMMAP), and testing of
 the two models of evolution used for the SIMMAPs. Preparation for the JIVE
 analysis. The actual analyses. The ESS estimations. The calcul of marginal
 likelihoods using stepping stone and the Bayes Factors, as well as figures
 related to BF. The plots of the estimated theta values for specialists and
 generalists and finally, the exploration of the SIMMAPs in favor of each
 model or neither. ### 5 - Preparation for calcul on server.R This is an
 example of a JIVE analysis for only a subset of MCMC and one PC axis of
 the floral morphospace. The jive objects are created and tuned for the 3
 PCs and 100 SIMMAPs, but the MCMCs are run for a subset of 10 SIMMAPs and
 only one PC. Each script then accounts for 10 MCMC each. We then have 30
 subsets representing 600 MCMC that were run remotely on the Calcul server.
 ### 6 - PGLS.R From the Procrustes aligned landmark data saved in script
 3, calcul of variances, and PGLS analysis on variances. Figures of
 residuals and barplot of variances that fit the phylogeny. ### 7 -
 mvMORPH.R Calcul of the log variation for each PC axis. Multivariate
 analysis with mvOU and mvOUM on the variances used in the PGLS, the
 log-variance of PC1, PC2, PC3 independently, and PC1+PC2+PC3 jointly, for
 all SIMMAPs. Plot of the theta values resulting from the analyses. Calcul
 of the AICc weights to compare the fit of the models and plot the AICc
 weights. ### utility\_functions.R Additional utility script used for
 geometric morphometrics for thin-plate spline transformation grids. ###
 outlierKD.R Additional utility script used for geometric morphometrics to
 check for outliers in landmarks data.