five

Sustained climate change drives rapid evolutionary reduction of phenotypic plasticity

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://figshare.com/articles/dataset/Divergent_evolution_of_plasticity_to_drought_under_climate_change_across_a_precipitation_gradient_a_multi_year_resurrection_experiment/30581402
下载链接
链接失效反馈
官方服务:
资源简介:
This repository contains the raw data, metadata, and R code to reproduce all analyses and figures for our manuscript. We ran a five-year resurrection experiment across a strong precipitation (aridity) gradient to test predictions about contemporary evolution in trait means and phenotypic plasticity under ongoing drought. We quantified morphological and physiological traits under moist vs drought, computed RDPI as an index of plasticity, and analysed multivariate structure (PERMANOVA/PCoA), univariate mixed models, and fitness proxies (flower number under drought). Contentsdata/Taraxacum_assimilation_data.csv — Raw trait observations across treatments and years (LA, LFW, Amax, gs/gmax, WUEi, Biomass; plus Population, Latitude, Year, Fam).data/Flowers_drought_only.csv — Flower counts under drought by population, year, and family.metadata/variable_dictionary.csv — Column definitions, units, and notes.R/00_main.R — Driver script: installs dependencies, sets directories, and orchestrates the full workflow.R/01_multivariate_traits.R — PERMANOVA / ordination of scaled traits.R/02_univariate_traits.R — GLMM/GLM per trait (lme4, Type-III tests).R/03_compute_RDPI.R — RDPI computation/checks from raw trait matrices.R/04_RDPI_trait_GLMs.R — GLMs of RDPI per trait: RDPI ~ Year * Latitude (Type-III, LR).R/05_overall_RDPI_analysis.R — Overall/composite RDPI analyses (GLM, emmeans, CLD letters, figures).R/06_RDPI_vs_flowers.R — Links overall plasticity (RDPI) to fitness (flowers under drought) with mixed models and per-year slopes.R/07_figures.R — Publication figures (e.g., Fig. 2 PCoA with trajectories; exports to output/figures/).output/tables/ — Model tables, ANOVAs, emmeans, slopes, etc.output/figures/ — Final figure files (JPEG/PNG/PDF).output/outdata/PI_all_traits.csv — Derived per-individual RDPI by trait and year (≈ 15,000 rows; 2,500 per trait).session_info/ — R session information saved by 00_main.R.README.md — Quick start and run order.How to reproduceOpen R/00_main.R and run it. This will:Install/load required packages (including devtools) and set project paths.Read the raw CSVs in data/.Source scripts 01–07 in order and write outputs to output/.Figures and tables are written to output/figures/ and output/tables/. Derived datasets (e.g., PI_all_traits.csv) are written to output/outdata/.Note on packages: RDPI is computed with the Plasticity package. If needed, install once via: install.packages("devtools") devtools::install_github("ameztegui/Plasticity", upgrade = "never", dependencies = TRUE) Re-useAll data and code are organised for transparent re-use and auditing. See metadata/variable_dictionary.csv for column-level details and units. Please cite the manuscript and this archive if you use these materials.
创建时间:
2025-11-12
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作