Quantile-based monthly climate extreme variables and predicted plant species distributions (37) across Victoria, southeast Australia

This collection includes each of the climate variables (including quantile-based extremes) and predicted plant species distributions (37) generated as part of the manuscript titled 'Climate extreme variables generated using monthly time-series data improve predicted distributions of plant species' (Stewart et al. 2020a; doi: 10.1111/ecog.05253).\nLineage: Climate variables are generated using 39 years of monthly maximum temperature (Stewart & Nitschke 2017), minimum temperature (Stewart & Nitschke 2018) and precipitation data (Stewart, et al. 2020b). Annual calculations for maximum temperature of the hottest month (BIO5), minimum temperature of the coldest month (BIO6), and precipitation of the driest quarter (BIO17) were used to quantify 'base climate' (long-term means), variability (standard deviations) and extremes of varying return intervals (defined using quantiles) based on historical observations. A tutorial, with R code, for producing these layers is provided in the supporting information to the manuscript (SDMExtremes_AppendixS2.pdf).\n\nSpecies distribution models were fitted and predicted for 37 plant species across Victoria using boosted regression trees, following the procedures detailed in the published manuscript. Images are provided for base climate, variability and extreme (with 1 in 15 year return interval) models. All cross validation results are provided in the supporting information to the manuscript (SDMExtremes_Appendix_S4.xlsx).

本数据集包含题为《利用月时间序列数据生成的气候极端变量提升植物物种预测分布精度》（Stewart等，2020a；doi:10.1111/ecog.05253）的手稿研究中生成的所有气候变量（含基于分位数的极端值（quantile-based extremes））及37种植物物种的预测分布。
谱系：气候变量基于39年的月最高温（Stewart & Nitschke 2017）、月最低温（Stewart & Nitschke 2018）与降水数据（Stewart等，2020b）生成。通过计算最热月最高温（BIO5）、最冷月最低温（BIO6）及最干季降水量（BIO17）的年值，基于历史观测量化"基础气候"（长期均值）、变异性（标准差）及不同重现期的极端值（return intervals，以分位数定义）。生成这些图层的教程（含R代码）见手稿补充材料（SDMExtremes_AppendixS2.pdf）。

遵循已发表手稿详述的流程，采用提升回归树（boosted regression trees）对维多利亚地区37种植物物种进行物种分布模型的拟合与预测。提供了基础气候、变异性及极端（15年一遇重现期）模型的图像。所有交叉验证结果见手稿补充材料（SDMExtremes_Appendix_S4.xlsx）。