Data from: A global synthesis of how plants respond to climate warming from traits to fitness
Data files
Mar 26, 2025 version files 2.27 MB
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README.md
2.74 KB
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WarmingPlants_Data.zip
2.26 MB
Abstract
Despite intensive research, our understanding of how plants respond to warming by coordinating their full arsenal of traits to adjust fitness is lacking. To fill this gap, we applied a trait-based framework with three clusters (two functional clusters: “carbon-fixation rate” and “carbon-fixation area”; a third cluster: “total carbon fixation”) to a global dataset compiled from 572 studies of warming experiments with 677 species and a comprehensive list of traits and fitness components. The pairwise correlation analysis complemented with SEM and PCA showed that plants increased biomass (the core variable in the third cluster) under warming by coordinating satellite traits in two functional clusters to adjust their core traits, net photosynthesis rate, and total leaf area, respectively. In particular, the trait coordination was characterized by the maintenance of net photosynthesis rate and the increase of total leaf area, which was robust across ecological contexts although warming responses of the variables per se displayed context-dependences. Moreover, the trade-offs between biomass and reproduction (itself bearing mass vs. number trade-offs) in their warming responses scaled the coordination to enhance fitness except in the contexts where reproduction was reduced. These findings could help explain and predict plant form and function in a warming world.
Dataset DOI: 10.5061/dryad.4j0zpc8pq
Pengyan Jia1†, Rong Zhang1†, Bernhard Schmid2, Han Wang3, Jin-Sheng He1,4, Jiaxi Liu1, Sijie Liu1, Sipeng Jian1, Yanhao Feng1*
1State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China
2Remote Sensing Laboratories, Department of Geography, University of Zurich, Zurich 8057, Switzerland
3Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
4Institute of Ecology, College of Urban and Environmental Sciences, Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China
*Author of correspondence: Yanhao Feng (Email: fengyh@lzu.edu.cn)
Description of the data and file structure
1. WarmingPlants_Data.zip:
(1) WarmingPlants_Data.xlsx: An Excel file containing raw data used in our study, along with variable abbreviations for the 45 variables included in the raw data. For detailed information on how the raw data was generated, please see the data compilation in Materials and Methods.
(2) Metadata.csv: A file that interprets all the 31 columns in the raw data (WarmingPlants_Data.xlsx).
2. WarmingPlants_Code.R (Zenodo)
The codes for generating results of Figures and Tables in the main text and supplementary information in our analysis.
3. Supplementary information.zip (Zenodo)
(1) Estimate: This folder contains four CSV files with calculated effect sizes overall and separately for growth forms, warming objects, and warming facilities (the calculation of effect sizes might take a few minutes, but you can directly read these data tables for the visualization of figures)
(2) Main: This folder contains all the figures and tables in the main text generated by running the R code (WarmingPlants_Code.R).
(3) Supplementary: This folder contains all the figures and tables in supplementary information generated by running the R code (WarmingPlants_Code.R).
(4) R_functions: This folder contains customized R scripts for specific statistical tasks:
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get_sig_letter.R: Assigns significance marker letters based on p-values.
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InDaPCA.R: Performs Principal Component Analysis (PCA) on incomplete data.
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corstarsl.R: Generates correlation matrices with significance stars.
Code/software
The codes of R for generating results of Figures and Tables in the main text and supplementary information in our analysis are in the Software related works.