Data from: Interactive effects of warming and competition do not limit the adaptive plastic response to drought in populations of a Mediterranean plant
Data files
Jul 30, 2025 version files 167.91 KB
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Code_analysis_Ramos-Muñoz_et_al._2025_GCB.R
14.58 KB
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Matrix_phenotypic_data_GCB_Ramos-Muñoz_et_al_2025.xlsx
135.41 KB
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README_Ramos-Muñoz_2025_GCB.docx
16.19 KB
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README.md
1.73 KB
Abstract
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.
Dataset DOI: 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
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
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