Data from paper: Large carbon sink potential of Secondary Forests in Brazilian Amazon to mitigate climate change (public) (Q5454)

Title: Large carbon sink potential of Secondary Forests in the Brazilian Amazon to mitigate climate change Contact:Viola Heinrich (viola.heinrich@bristol.ac.uk) This repository contains: Zipped folder: Fig1_data_input.zip - all the files needed to produce Figure 1a-e of the main paper. Set the working directory to folder containing the file and use the script Fig1a_f_plot.R to run(see below). The folder contains the input files of the 6 driving variables used to build regrowth models seen in Figure 1 - these files arein the format driver_assessment_v2.csv. The columns in the files are: A: age of secondary forest; B: 50th percentile (median) ofthe modal Aboveground Biomass (AGB)value for the given age (note, units are in biomass not carbon: Mg/ha/yr); C: The bias-corrected AGB value, calculated by subtractingthe lowest AGB value in column B such that the AGB data starts at or near 0Mg/ha/yr at age 1.D: the number of secondary forest pixels observed to have the given age, E: Threshold : the threshold limits of the given driver e.g. 0 Fires in fire_assessmentv2.csv implies the corresponding secondary forest pixels experienced0 fires throughout the analysis period. The folder also contains the output regrowth models seen in Figure 1 in the format regrowth_model_driver_threshold.RDatawhere driver_threshold refers to the driving variable name and the associated threshold limit for the given driver. Zipped folder: Fig2_regions_outline.zip - contains the boundaries of the 4 regions identified in Figure 2a of the main paper in a shapefile (.shp) format and the corresponding file formats needed to produce and load a shapefile. Zipped folder: Fig1g_2b_e_variable_importance.zip - contains the output files of the random forest analysis assessing the variable importance for the whole Amazon (whole_Amazon subfolder) and for the different regions identified in Figure2a. Files are given as .RDS files that can be loaded in R and the corresponding figures produced using the script Fig1g_2b_e_plot.R. Files start with the region of interest e.g. whole_Amazon or NE_sector. Middle part of the filename -importance_conditionalTrue/False - this determines whether the importance was calculated using the conditional permutation (True) or not (False).The end of the file name - seedNUM - denotes the number of the random seed that was set to extract the sample data. e.g. whole_Amazon_2500_cforest_important_conditionalTrue_seed200.RDS - shows theconditional permutation importance assessment using a sample size of 2500 when the setseed parameter was set to 200 to extract a random sample representing the whole Amazon. The remaining files are therandom forest output - as .RDS file. Please note the code to produce the random forest model and the importance assessment has not been included here - this code takes multiple days to run, so only the input and outputs have been included here. Please contact the corresponding author (see end) for more informationon this. Zipped folder: Fig3_data_input.zip - all the files needed to produce Figure 3a-dof the main paper. Set the working directory to folder containing the file and use the script Fig3_plot.R to run(see below). The folder contains the input files of the 6 driving variables used to build regrowth models seen in Figure 3- these files arein the format REGION-Group.csv. See bullet point 1 for explanations for the columns in the file. Again column E -threshold denotes the code used to identify the the 4 subclasses of regrowth seen in the Figure. Where 11 =No disturbance;12 = Only burning; 21 = Only (multiple) deforestations; 22 = Both burning and multiple deforestations as disturbance. The code takes data in AGB and converts to AGC. The folder also contains the output regrowth models seen in Figure 3in the formatregrowth_model_region_disturbance_type.RDatawhere region_disturbance refers to the region and the type of disturbance experienced. Zipped folder: Fig4_5_carbon_sink_2017.zip- Contains two subfolders: a) Map_aggre_0.1deg -this folder contains .tiff files (and associated files) of the losses, gains and net change in AGC between 2016 - 2017 in secondary forests in Amazonia - this has been aggregated to 0.1 degree grid cells so each cellcontains the total sum of the losses/gains experiencedby secondary forests in that 0.1degree grid cell.b) secondary_forest_by_region_and_disturbance- this folder contains .tiff files (and associated files) of the secondary forest data at the original resolution (30m) for 2016 and 2017split up according to the regions identified in Figure 2, and the type of disturbance(if any). The associated files include a .dbf file which includes additional data [read README.txt file in folder]- upon loading the data in a GIS software - the age of the secondary forest pixel will be displayed - open the attribute table to see more data associated with that given pixel e.g. modelled associated AGB for a given pixel. Files in this folder can be used to make Figure 4d and Figure 5 - see script Fig4_Fig5_plot.R in the code repository (see below). Code:The corresponding code mentioned here can be access here:heinrichTrees/secondary-forest-regrowth-amazon-public (github.com) Data usage:When using any code or data in this repository or another related to this study please cite Heinrich et al.2021 and the original paper as well as the DOI of this repository. If you need anything else, please contact the corresponding author: Viola Heinrich (viola.heinrich@bristol.ac.uk)