Data and code share for NGS

Code and data for the paper “Global crop production increase by soil organic carbon”Code authors: Dominic Woolf ([e-mail]) and Yuqing Ma ([e-mail])Data contact by Mingsheng Fan ([e-mail])Description: 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”.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.