Post-processing workflow for ED2 simulations for the Brazilian Amazon, initialised with airborne lidar (Part 2)
DOI10.5281/zenodo.14775867Zenodo14775867MaRDI QIDQ6691133
Dataset published at Zenodo repository.
Michael Keller, Liang Xu, Eric Bastos Görgens, Ovidiu Csillik, Elsa M. Ordway, Lara Kueppers, Britaldo Silveira Soares Filho, Erik Larson, Xiangtao Xu, Francisca Rocha de Souza Pereira, Antonio Ferraz, Jean P. Ometto, Marcos Longo, Paul Moorcroft, Ekena Rangel Pinagé, Luciane Sato, Mauro Lúcio Rodrigues Assis, Jessica Needham, Kevin Bowman, Sassan Saatchi
Publication date: 30 January 2025
Copyright license: Creative Commons Attribution 4.0 International
These scripts uses the RData objects produced by the first set of post-processing workflows (available inthis archive) to generate most figures presented in the following manuscript: Longo, M., M. Keller, L. M. Kueppers, K. Bowman, O. Csillik, A. Ferraz, P. R. Moorcroft, J. P. Ometto, B. S. Soares-Filho, X. Xu, M. L. F. de Assis, E. B. Grgens, E. J. L. Larson, J. F. Needham, E. M. Ordway, F. R. S. Pereira, E. Rangel Pinag, L. Sato, L. Xu and S. Saatchi. Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes. In review.This data set contains the following scripts, each in its own compressed directory. All directories for plots and summaries require setting the path to RUtils, which is also provided in this data set too. 01+04+S14_PlotGMeanCompare.tgz. This script combines individual plots of global averages into Figure 1, Figure 4 and Figure S14. 02+S10_PlotDYDX.tgz. This script combines individual plots of sensitivities to environmental drivers into Figure 2 and Figure S10. 03_PlotXYSummary.tgz. This script combines plots of ET and GPP responses to environmental drivers by patch AGB classes into Figure 3. 05_PlotXYSimSumm.tgz.This script combines plots of ET and GPP responses to environmental drivers by simulation to into Figure 5. S06_PlotGMeanEval_AGB+LAI.tgz. This script combines plots of global averages of AGB and LAI from ED2 and benchmarks into Figure S06. S08_PlotEMeanCorr_GPP+ET+SH.tgz. This script combines plots of correlations of GPP, ET and SH between ED2 and select benchmarks into Figure S08. S09_PlotGMeanFixed.tgz. This script combines global averages of edaphic conditions and mean annual precipitation into Figure S09. S11+S12_PlotXYbyPAGB.tgz. This script plots the ET and GPP response to environmental drivers by patch AGB classes and by Amazonian region into Figures S11 and S12. S13_PlotGStateCompare.tgz. This script plots the global averages of AGB and LAI, and the differences between simulations Recovery and Degradation and Control. S15+S16+S17_PlotXYbySimul.tgz. This script plots the plots of ET and GPP responses to environmental drivers by simulation and by Amazonian region into Figures S15, S16 and S17. SummCompGMean.tgz. Summaries of the global mean analyses by variable of interest and simulation. SummDYDXbyPAGB.tgz. Summaries of the sensitivities of ET and GPP to environmental drivers by patch AGB (simulation Control). SummDYDXbySimul.tgz. Summaries of the sensitivities of ET and GPP to environmental drivers by simulation. SummResponseByPAGB.tgz.Summaries of the responses of ET and GPP to environmental drivers by patch AGB (simulation Control). SummResponseBySimul.tgz. Summaries of the responses of ET and GPP to environmental drivers by simulation. RUtils.tgz. Folder containing additional R scripts that may be used for running all scripts above. Additional figures not listed here were either generated with QGIS (Figures S1 and Figure S3), by manually combining panels from existing output from the first set of post-processing workflows(Figure S2, Figure S5, Figure S7), or because they are generated directly by the first set of post-processing workflows (Figure S4).
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