DOI: 10.5061/dryad.cz8w9gjj8
title: Intraspecific trait variation shows the predominant influence of functional divergence on species co-occurrence

description: Intraspecific trait variation (ITV) has been recognized as an important
 source of variation in communities. We separated among-population ITV
 (differences in mean trait values among populations) from
 within-population ITV (trait variation within populations) to test three
 theoretical predictions: i) communities should show greater among-species
 trait diversity when among-population ITV is accounted for due to trait
 means shifting away from neighbouring species, ii) the increased
 differences among species should be greatest in species poor communities,
 and iii) within-population trait variation should also be greatest in
 species-poor communities. We tested these predictions in an experimental
 old-field metacommunity, measuring four functional traits known to be
 important for plant function in 1842 individuals across 33 species and 84
 patches that varied in size (area), species diversity, and composition. We
 found that when among-population ITV was accounted for, species diverged
 in their average trait values (nearest neighbour distances and functional
 dispersion), consistent with theory that trait differences among species
 promote coexistence. This divergence was slightly greater in species-poor
 communities. Within-population ITV showed a different pattern than
 predicted, with the highest within-population ITV occurring in large
 patches and in communities where species were more functionally
 differentiated. Overall, among-population ITV revealed the influence of
 ecological interactions on trait divergence among species. Failing to
 incorporate ITV underestimates among-species trait differences and may
 miss opportunities to detect trait-based assembly and coexistence
 mechanisms. Nonetheless, estimates that ignore ITV are strongly correlated
 with those that include ITV, suggesting that the relative differences in
 functional diversity among communities can be estimated without ITV.
 Within-population ITV showed less consistent results, suggesting that
 other factors may have a stronger influence within populations. Synthesis.
 Theory predicts that variation within species may alter species
 coexistence and the functional diversity of communities. We found support
 for the hypothesis that species show higher divergence in their average
 traits when ITV is accounted for. However, we found little support for the
 hypothesis that ITV within populations is greater in patches with few
 species. These results suggest that variation among populations moderates
 species interactions, facilitating species co-occurrence and shaping
 community assembly.
description: # Intraspecific trait variation shows the predominant influence of
 functional divergence on species co-occurrence Dataset DOI:
 [10.5061/dryad.cz8w9gjj8](https://doi.org/10.5061/dryad.cz8w9gjj8) ##
 Description of the data and file structure This data was collected for our
 study examining how the distribution of functional traits within a species
 changes across and within populations in response to neighbouring species.
 We measured four functional traits across thirty-three species in an
 experimental old-field meta-community at the Koffler Scientific Reserve in
 Newmarket, Ontario.  ### Files and variables #### File:
 traits_nonflowering_species.csv **Description:** traits used for species
 found in our study patches but with no reproductive individuals to provide
 traits this year. Trait data taken from Forsyth and Gilbert (Journal of
 Ecology. 2021;109:793ñ805) with transformations done as needed. #####
 Variables * species: species binomial name * log.height: ln height (cm) *
 log.sla: ln sla (cm2/g) * LR_veg_rep_mass: ln (vegetative mass /
 reproductive mass) unitless * sqrt.LDMC: sqrt (leaf_drymass /
 leaf_wet_mass) unitless #### File: species_abundances_by_plot.csv
 **Description:** Counts (population size) of all species in each patch
 used in the experiment. Grass population sizes were estimated using
 conversions of percent cover estimates. Methods following Forsyth and
 Gilbert (Journal of Ecology. 2021;109:793ñ805). ##### Variables *
 block: block in experimental design (Fig. S1) * size: size of one side of
 square patch (equal to square root of area in metres) * plot: patch
 designator. Each block * size * plot is a unique patch within the
 experiment. Note that not all plots (patches) were used - see Methods for
 patch selection. * species: species binomial name * abundance: number of
 individuals in patch * rel.abundance: number of individuals of species /
 number of individuals across all species in patch #### File:
 metadata_and_metacode.csv **Description:** metadata and metacode for raw
 data and code files ##### Variables * metadata and metacode: #### File:
 raw_data.csv **Description:** Individual-level measurements of traits used
 in this study ##### Variables * species: species binomial name *
 block: block in experimental design (Fig. S1) * size: size of one side of
 square patch (equal to square root of area in metres) * plot: patch
 designator. Each block * size * plot is a unique patch within the
 experiment. Note that not all plots (patches) were used - see Methods for
 patch selection. * Individual: individual plant of a given species in a
 single patch * height: plant height along stem in cm * leaf_area: area of
 leaf before drying in cm2 * leaf_mass: leaf wet mass (mass prior to
 drying) in grams * stem_vol: not used in study. We estimated stem volume
 using water displacement, but discarded this trait as we were not
 confident in the accuracy of measurements * plant_mass: dry mass of entire
 plant in grams * leaf_drymass: dry mass of leaf used for leaf_area
 measurement (above), in grams * repro_drymass: drymass of reproductive
 parts including flower heads (grams) * other_drymass: some individuals
 were separated by leaves, stems, etc. before drying. All measures in grams
 * veg_drymass: some individuals were separated by leaves, stems, etc.
 before drying. All measures in grams * stem_drymass: some individuals were
 separated by leaves, stems, etc. before drying. All measures in grams ####
 File: Code_4._trait_differences_among_and_within_species_by_trait_axis.R
 **Description:** Calculating NND, Svar, Fdis, Feve and within-population
 ITV measures for all traits separately and associated statistical tests
 #### File: mean_trait_values_by_species_for_each_trait_axis.csv
 **Description:** description: metapopulation mean trait values following
 PCA. Data file generated from data files above in 'Code 1' #####
 Variables * species: species binomial name * trait_axis: Principal
 components analysis axis * site_PCA_score: metapopulation mean trait value
 (denotes species score on the trait axis identified) #### File:
 Code_2._exploration_of_species_means_and_variances_for_transformations.R
 **Description:** data exploration to determine appropriate transformations
 of traits #### File:
 trait_mean_and_variance_by_plot_for_each_species_and_trait_axis.csv
 **Description:** Patch-level trait means and variances for each species
 and each trait axis. Data file generated from data files above in
 'Code 1' ##### Variables * species: Species binomial name *
 block: block in experimental design (Fig. S1) * size: size of one side of
 square patch (equal to square root of area in metres) * plot: patch
 designator. Each block * size * plot is a unique patch within the
 experiment. Note that not all plots (patches) were used - see Methods for
 patch selection * trait_axis: Principal components analysis axis *
 plot.PCA.score: Patch-level mean * plot.level.variance: Patch-level
 variance * num.ind: number of individuals sampled in the patch #### File:
 Code_1._calculating_multivariate_trait_means_and_variances_at_each_spatial_level.R **Description:** data processing to determine metapopulation means, patch means and patch variances of traits and PCA rotation #### File: Code_3._trait_differences_among_and_within_species_with_figure_saving_code.R **Description:** calculating NND, Svar, Fdis, Feve and within-population ITV measures for all traits simultaneously and associated statistical tests ## Code/software Coding for this project was done in R version 4.2.2 (R Core Team, 2022) and *RStudio* (Posit Team, 2023). These files can be viewed in R, RStudio, or any text editing software. Data files are attached as .csv.