A gridded dataset of belowground autotrophic respiration from 1980 to 2012 in global terrestrial ecosystems upscaling of observations

This data repository contains (1) yearly global autotrophic respiration (RA) dataset from 1980 to 2012 with a spatial resolution of 0.5°; (2) original field observations to develop Random Forest (RF) model; (3) main R codes to produce RA database.Model description:The globally gridded RA database was developed by Random Forest (RF) with 449 field observations (see “dataset.csv” in this repository, updated from Bond-Lamberty and Thomson, 2018) using 11 global variables, including gridded temperature, precipitation, diurnal temperature range, potential evapotranspiration, Palmer Drought Severity Index, nitrogen deposition, downward shortwave radiation, soil carbon content, soil nitrogen density, soil water content, land cover. <br>Dataset information:Dataset name: “Respiration_autotrophic_belowgroud_glob_1980_2012_yr_half_dgree.nc”Which means globally belowground autotrophic respiration from 1980 to 2012 with a spatial resolution of 0.5° at a yearly step.Units: g C m^-2 yr^-1Format: network Common Data Form (netCDF)Spatial coverage: 90S-90N, 180W-180EThe “dataset.csv” file is the field observation from peer review publications combining Global Soil Respiration Database (SRDB v4, Bond-Lamberty and Thomson, 2018), which is publicly available at https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1578. Besides, The database was further updated using observations collected from the China Knowledge Resource Integrated Database (www.cnki.net) up to November 2018 according to the criteria of SRDB. This dataset is provided in format of “.csv”.<br>R codes:10fold_CV_RA.txt: 10-fold CV for RAAnnual_variability_RA.txt: annual variability for global RACMP_RA.txt: comparing RF-RA and Hashimoto2015-RA using CMP approachRa_DD_CC_plot.txt: plotting the comparing results from CMPRA_MAT_MAP_anomaly.txt: plotting and modelling the relationship between temperature/precipitation anomalies and RA RGB_plot.txt: deriving RGB plot to detecting the relative importance of temperature, precipitation and shortwave radiation. <br>

本数据集仓库包含以下三部分内容：(1) 1980年至2012年的全球年度自养呼吸（autotrophic respiration, RA）数据集，空间分辨率为0.5°；(2) 用于构建随机森林（Random Forest, RF）模型的原始野外观测数据；(3) 用于生成自养呼吸数据库的核心R代码。

模型描述：本全球网格化自养呼吸数据库通过随机森林（Random Forest, RF）模型构建，共纳入449组野外观测数据（详见本仓库内的"dataset.csv"，该数据更新自Bond-Lamberty与Thomson于2018年发布的数据集），所用的11个全球变量包括：网格化气温、降水量、昼夜温差、潜在蒸散量、帕尔默干旱严重度指数、氮沉降、下行短波辐射、土壤碳含量、土壤氮密度、土壤含水量以及土地覆盖类型。

数据集信息：
数据集名称："Respiration_autotrophic_belowgroud_glob_1980_2012_yr_half_dgree.nc"，对应1980年至2012年的全球地下自养呼吸数据，以年为时间步长，空间分辨率为0.5°。
单位：g C m⁻² yr⁻¹
格式：网络通用数据格式（network Common Data Form, netCDF）
空间覆盖范围：南纬90°至北纬90°，西经180°至东经180°

本仓库内的"dataset.csv"文件的野外观测数据来自同行评议期刊论文，整合了全球土壤呼吸数据库v4（Global Soil Respiration Database, SRDB v4，Bond-Lamberty与Thomson, 2018），该原始数据库可公开获取于https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1578。此外，本数据集依据SRDB的筛选标准，补充了2018年11月之前从中国知网（China Knowledge Resource Integrated Database, www.cnki.net）收录的观测数据，以".csv"格式提供。

R代码文件说明：
1. 10fold_CV_RA.txt：用于自养呼吸数据的10折交叉验证
2. Annual_variability_RA.txt：用于分析全球自养呼吸的年际变异性
3. CMP_RA.txt：采用CMP方法对比随机森林模拟的自养呼吸数据（RF-RA）与Hashimoto 2015年发布的自养呼吸数据
4. Ra_DD_CC_plot.txt：用于绘制CMP方法得到的对比结果图
5. RA_MAT_MAP_anomaly.txt：用于绘制并建模气温/降水异常与自养呼吸之间的关联关系
6. RGB_plot.txt：用于生成RGB图以量化气温、降水与短波辐射的相对重要性