Leaf-scale carbon assimilation simulated by the multi-assumption architecture & testbed for process sensitivity analysis

Raw and processed output from the Multi-Assumption Architecture & Testbed (MAAT, https://github.com/walkeranthonyp/MAAT, tag: v1.2.1_walker2020; Walker et al., 2018). The dataset contains leaf-scale carbon assimilation data from three MAAT simulations and their post-processing and plotting scripts. Simulation 1, labelled "FvC_4proc_proc," is a four-process, process sensitivity analysis (Dai et al., 2017) of carbon assimilation based on the Farquhar et al. (1980) photosynthesis model, and its variant proposed by Collatz et al. (1991). Simulation 2, labelled "FvC_4proc_salt," is a 14 parameter sensitivity analysis (Saltelli et al., 2010) of carbon assimilation based on the Farquhar and Collatz photosynthesis models. Simulation 3, labelled "FvC," is a factorial combination of the alternative process representations and parameter values presented in those original papers across a factorial combination of incident photosynthetically active radiation (50-2000 µmol m-2 s-1, in increments of 50) and atmospheric CO2 concentration (50-1500 µmol m-2 s-1, in increments of 50). Additional scripts/functions for post-processing and plotting are part of the MAAT repository. These data were generated to evaluate and compare the Farquhar and Collatz models of leaf-scale photosynthesis across a range of CO2 and incident light conditions. Analysis of results can be found in Walker et al. (2020). This dataset is comprised of R scripts to process data and produce figures; .RDS files, a binary format specific to R and read with the 'readRDS' function, to store raw MAAT output; R and bash scripts (.bs) that help to run a MAAT simulation, .XML files that are output from MAAT describing a run, and .csv files which contain the calculated sensitivity indexes published in Walker et al. (2020).

本数据集源自多假设架构与测试平台（Multi-Assumption Architecture & Testbed, MAAT，https://github.com/walkeranthonyp/MAAT，标签：v1.2.1_walker2020；Walker等，2018）的原始与经后处理输出结果。数据集包含三项MAAT模拟的叶片尺度碳同化数据，以及各模拟对应的后处理与绘图脚本。
编号为"FvC_4proc_proc"的模拟1为基于法夸尔光合作用模型（Farquhar photosynthesis model，Farquhar等，1980）及其科拉茨等（1991）提出的变体所开展的四过程碳同化敏感性分析（Dai等，2017）。
编号为"FvC_4proc_salt"的模拟2为基于法夸尔与科拉茨光合作用模型开展的14参数碳同化敏感性分析（Saltelli等，2010）。
编号为"FvC"的模拟3为上述原始文献中提出的替代过程表征与参数值的全因子组合，其输入变量为入射光合有效辐射（photosynthetically active radiation，50~2000 μmol·m⁻²·s⁻¹，步长为50）与大气CO₂浓度（50~1500 μmol·m⁻²·s⁻¹，步长为50）的全因子组合。
额外的后处理与绘图脚本及函数已集成于MAAT代码仓库中。本数据集的构建目的为：在一系列CO₂浓度与入射光强条件下，评估并对比叶片尺度光合作用的法夸尔模型与科拉茨模型。相关结果分析可参见Walker等（2020）。
本数据集包含以下内容：用于数据处理与绘图的R脚本；用于存储MAAT原始输出结果的.RDS文件（R语言专属二进制格式，可通过`readRDS`函数读取）；用于运行MAAT模拟的R脚本与Bash脚本（.bs后缀）；MAAT运行时生成的描述单次模拟流程的.XML文件；以及包含Walker等（2020）中发表的计算所得敏感性指数的.CSV文件。