Data from: Higher-order species interactions cause time-dependent niche and fitness differences: experimental evidence in plant-feeding arthropods

trajectories.csv (the raw data) id: replicate identifiervariant: co-existence status ("competition" or "monoculture")day: day of experimentspecies: mite species ("CRM" or "WCM")n: population density model.R The R script with the GAMM fitted to the trajectory data; also produces simulations from this model (saved as sim.csv). sim.csv (simulations from the GAMM) day: day of experimentspec_var: combination of co-existence status ("competition" or "monoculture") and species ("CRM" or "WCM")X1:X1000: population densities simulated from the fitted GAMM (on the log scale) reg.RData The GAMM for growth rates. NFD_over_time_monte_carlo_gam.py Python script to compute niche and fitness differences. Takes sim.csv (densities over time for different instantiations) and reg.RData ( stores the GAMM from R for the growth rates) as input and generates the file Data_NFD_monte_carlo_multi_c.csv which stores the niche and fitness differences computed for these communities. figures.R The R script that produces Figures 2-4. plot_biotic_model.py Python code to generate the figures S3 and S4 showing the simulations of a biotic resource competition model. plot_abiotic_model.py Python code to generate the figures S1 and S2 showing simulations of an abiotic resource competition model.trajectories.csv（原始数据） id: 重复样本标识符（replicate identifier） variant: 共存状态，取值为“竞争”或“单种培养” day: 实验天数 species: 螨类物种，取值为“CRM”或“WCM” n: 种群密度 model.R 用于将广义加性混合模型（GAMM）拟合至轨迹数据的R脚本，同时可基于该模型生成模拟数据（保存为sim.csv）。 sim.csv（基于GAMM生成的模拟数据） day: 实验天数 spec_var: 共存状态（“竞争”或“单种培养”）与物种（“CRM”或“WCM”）的组合 X1:X1000: 基于拟合的GAMM模拟得到的种群密度（以对数尺度表示） reg.RData 存储了用于增长率拟合的广义加性混合模型（GAMM）的文件。 NFD_over_time_monte_carlo_gam.py 用于计算生态位与适合度差异的Python脚本。该脚本以sim.csv（不同实例下的时序种群密度数据）和reg.RData（存储了R语言中用于增长率拟合的GAMM）作为输入，最终生成Data_NFD_monte_carlo_multi_c.csv文件，该文件存储了针对这些群落计算得到的生态位与适合度差异。 figures.R 用于生成图2至图4的R脚本。 plot_biotic_model.py 用于生成补充图S3与S4的Python代码，该组图表展示了生物资源竞争模型的模拟结果。 plot_abiotic_model.py 用于生成补充图S1与S2的Python代码，该组图表展示了非生物资源竞争模型的模拟结果。