Data and code shared for NGS

Code and data for the paper “Global crop production increase by soil organic carbon”Code authors: Dominic Woolf and Yuqing MaCode contact by [e-mail] or [e-mail] authors: Mingsheng Fan, Yuqing Ma, Rong Li, Lei QiaoData contact by [e-mail]: R scripts and data to quantify the causal effect of soil organic carbon (SOC) on crop yield of the three major crops (maize, wheat and rice). The R script and data aim to achieve three contents: (1) quantify the causal effect of SOC on crop yield; (2) analyze the major drivers of soil organic carbon yield gap; (3) make global extrapolation of SOC yield gap for the three studied crops.***Please install the necessary packages using the R script “Load Packages.R”.<br>1. Causal effect of SOC on crop yield(1) “Causal effect of SOC on crop yield by Random Forest.R”: R script used to establish the causal effect of SOC on crop yield by partial dependence using Random Forest.(2) “Causal effect of SOC on crop yield by Causal Forest.R”: R script used to estimate the effect size of SOC on crop yield by casual forest.(3) “Causal effect of SOC on crop yield under different N levels.R”: R script used to establish the casual effect of SOC on crop yield under different nitrogen input levels.(4) “Causal effect of SOC on crop yield under climate zones”: R script used to establish the casual effect of SOC on crop yield under global climate zones.(5) “data.csv”: CSV data used in this section.<br>2. Drivers of SOC yield gap(1) “Calculating SOC yield gap.R”: R script used to estimate SOC yield gap for each field trial.(2) “Determination of drivers for the SOC yield gaps.R”: R script used to quantify the driver of SOC yield gap based on field trial data by Random Forest.(3) “data.csv”: CSV data used in this section.<br>3. Global extrapolation of SOC yield gap(1) “Determination of coefficient and index of agreement for global extrapolation model.R”: R script used to analyze the model performance for global extrapolation(2) “Leave one out cross-validation to estimate prediction uncertainty for global extrapolation.R”: R script used to estimate the standard errors of predicted SOC yield gaps derived from global extrapolation models.(3) “Technical potential for global extrapolation.R”: R script used to estimate global yield increase under technical potential to increase SOC.(4) ”10.Unconstrained increase for global extrapolation.R”: R script used to estimate global yield increase under unconstrained increase in SOC.(5) “data.csv”: CSV data used in this section.(6) “Maize global data.csv”: The distribution of global maize cropping area used to estimate global maize yield increase derived from SOC.(7) “Wheat global data.csv”: The distribution of global wheat cropping area used to estimate global wheat yield increase derived from SOC.(8) “Rice global data.csv”: The distribution of global rice cropping area used to estimate global rice yield increase derived from SOC.

本数据集配套论文《土壤有机碳驱动的全球作物产量提升》（原文标题：Global crop production increase by soil organic carbon），代码作者为Dominic Woolf与Yuqing Ma，代码联系邮箱为[e-mail]或[e-mail]；数据作者为Mingsheng Fan、Yuqing Ma、Rong Li与Lei Qiao，数据联系邮箱为[e-mail]。

数据集说明：本资源包含用于量化土壤有机碳（soil organic carbon, SOC）对三大主粮作物（玉米、小麦、水稻）产量的因果效应的R脚本与配套数据，旨在完成三项核心任务：(1) 量化土壤有机碳对作物产量的因果效应；(2) 解析土壤有机碳产量缺口的主要驱动因子；(3) 针对上述三大作物实现土壤有机碳产量缺口的全球外推。

请通过R脚本"Load Packages.R"安装必要的依赖包。

1. 土壤有机碳对作物产量的因果效应
(1) "Causal effect of SOC on crop yield by Random Forest.R"：采用随机森林（Random Forest）通过偏依赖分析构建土壤有机碳对作物产量因果效应的R脚本。
(2) "Causal effect of SOC on crop yield by Causal Forest.R"：采用因果森林（Causal Forest）估算土壤有机碳对作物产量效应量的R脚本。
(3) "Causal effect of SOC on crop yield under different N levels.R"：分析不同氮素输入水平下土壤有机碳对作物产量因果效应的R脚本。
(4) "Causal effect of SOC on crop yield under climate zones.R"：分析全球气候分区下土壤有机碳对作物产量因果效应的R脚本。
(5) "data.csv"：本部分所用的CSV格式数据文件。

2. 土壤有机碳产量缺口的驱动因子
(1) "Calculating SOC yield gap.R"：估算各田间试验土壤有机碳产量缺口的R脚本。
(2) "Determination of drivers for the SOC yield gaps.R"：基于田间试验数据，通过随机森林量化土壤有机碳产量缺口驱动因子的R脚本。
(3) "data.csv"：本部分所用的CSV格式数据文件。

3. 土壤有机碳产量缺口的全球外推
(1) "Determination of coefficient and index of agreement for global extrapolation model.R"：分析全球外推模型性能的R脚本，用于确定模型系数与一致性指标。
(2) "Leave one out cross-validation to estimate prediction uncertainty for global extrapolation.R"：采用留一交叉验证（Leave one out cross-validation）估算全球外推模型预测的SOC产量缺口标准误的R脚本。
(3) "Technical potential for global extrapolation.R"：估算通过提升土壤有机碳水平的技术潜力实现全球作物产量提升的R脚本。
(4) "10.Unconstrained increase for global extrapolation.R"：估算土壤有机碳无约束提升情景下全球作物产量提升的R脚本。
(5) "data.csv"：本部分所用的CSV格式数据文件。
(6) "Maize global data.csv"：用于估算土壤有机碳驱动的全球玉米产量提升的全球玉米种植面积分布数据文件。
(7) "Wheat global data.csv"：用于估算土壤有机碳驱动的全球小麦产量提升的全球小麦种植面积分布数据文件。
(8) "Rice global data.csv"：用于估算土壤有机碳驱动的全球水稻产量提升的全球水稻种植面积分布数据文件。