DOI: 10.5061/dryad.pzgmsbd0t
title: Data from: Interactive effects of warming and competition do not limit the adaptive plastic response to drought in populations of a Mediterranean plant

description: This dataset contains the phenotypic data measured during the experiment
 and the R code employed in the statistical analyses of the paper
 "Interactive effects of warming and competition do not limit the
 adaptive plastic response to drought in populations of a Mediterranean
 plant", published in Global Change Biology. Water scarcity is the
 main selective pressure determining the performance of Mediterranean plant
 populations, with climate change predicted to increase the intensity and
 duration of droughts. However, drought rarely acts in isolation. Climate
 change also involves substantial warming in this region and may disrupt
 natural processes, including biotic interactions. Phenotypic plasticity
 allows plants to cope with rapid and multifaceted environmental changes.
 Although our knowledge of plastic responses to drought in Mediterranean
 plants has increased in recent years, how co-occurring simultaneous
 stressors interact to produce additive, synergistic, or antagonistic
 effects that enhance or constrain adaptive plastic responses to drought is
 still unknown. Using a factorial experimental approach based on a
 multivariate common garden, we assessed whether adaptive phenotypic
 plasticity to drought and population differentiation in traits related to
 drought response were affected by the occurrence of other key simultaneous
 stressors, warming and intraspecific competition, in a Mediterranean
 gypsum endemic shrub. In response to drought, plants expressed adaptive
 plastic responses associated with a mixed resource-use strategy, combining
 conservative (sclerophyllous leaves with higher water use efficiency) and
 acquisitive (advanced phenology) phenotypic responses. Although the
 response to drought was modified by synergistic and antagonistic
 interactions with warming and competition, these interactions did not
 change the direction or reduce the extent of adaptive plasticity to
 drought. This suggests that plastic responses to drought may also provide
 benefits against warming and competition. Finally, we detected significant
 population differentiation in all functional traits, but phenotypic
 differences in reproductive biomass were significantly reduced under
 combined drought and warming. Our results emphasize the robustness of
 adaptive plasticity to drought under complex stress scenarios and
 underscore the importance of realistic, multifactorial experimental
 approaches to predict whether adaptive responses of plant populations will
 remain effective in a climate change context and influence their future
 ecological and evolutionary dynamics.
description: # Data from: Interactive effects of warming and competition do not limit
 the adaptive plastic response to drought in populations of a Mediterranean
 plant Dataset DOI: [10.5061/dryad.pzgmsbd0t](10.5061/dryad.pzgmsbd0t) ##
 Description of the data and file structure The dataset contains the
 phenotypic data generated from the experiment and the R code used for data
 analysis. If you have any questions about the datasets, please contact
 [marina.ramosm@urjc.es](mailto:marina.ramosm@urjc.es) ### Files and
 variables #### File: Code_analysis_Ramos-Muñoz_et_al._2025_GCB.R
 **Description:** All analyses were performed using R v 4.3.1 (R Core Team,
 2023). If you have any questions about any specific analysis, please
 contact [marina.ramosm@urjc.es](mailto:marina.ramosm@urjc.es) #### File:
 README_Ramos-Muñoz_2025_GCB.docx **Description:** This README file
 contains all the information needed to understand the data, and it is very
 similar to the information contained here #### File:
 Matrix_phenotypic_data_GCB_Ramos-Muñoz_et_al_2025.xlsx
 **Description:** Phenotypic data generated during the experiment. The
 dataset (Excel file) includes a sheet called “README”, which describes all
 the traits and variables included in the dataset. Trait abbreviations
 match with those in Table 1 and are precisely explained in the “README”
 sheet. Missing data are coded as NA. ##### Variables: See variable sheet
 in file. ## Code/software All analyses were performed using R v 4.3.1 (R
 Core Team, 2023). The code employed in these analyses can be also found as
 an attached file to this submission. If you have any questions about any
 specific analysis, please contact
 [marina.ramosm@urjc.es](mailto:marina.ramosm@urjc.es)