Data and Code for 'Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle'

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Main Author: Zhao, Ruiying
Format: Recurso digital
Published: Zenodo 2025
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author Zhao, Ruiying
author_facet Zhao, Ruiying
contents <p>This dataset includes code and data for the manuscript of 'Zhao, R., Luo, X., Walker, A. P., Hoffman, F. M., Koh, L.P. (2025). Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle'.</p> <p><strong>Update (Nov 2025): </strong>we have released the <em>version 2</em> to include the raw data (Source_Data_Fig1.xlsx, Source_Data_Fig2.xlsx, Source_Data_Fig3.nc) and code (master_figure_clean.m, sup_code.zip) used for analysis and figure generation.</p> <p><strong>Update (Jun 2025): </strong>we have released the <em>version 1</em> to include the input, code and output for creating machine learning emulators for PFT GPP of each DGVM in TRENDY v9. </p> <p>The file 'input.zip' includes the predictor variables (i.e., annual precipitation, temperature, solar radition, pressure and wind speed during 2001-2019 from CRU JRA v2.1 datasets) and response (i.e., pixel PFT GPP rate) for each PFT of each DGVM.</p> <p>The file 'code4emulators.mlx' includes the code for training machine learning emulators (i.e., Random Forest models) for each PFT of each DGVM.</p> <p>The file 'model_emulators.zip' includes all trained emulators.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_17718653
institution Zenodo
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publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Data and Code for 'Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle'
Zhao, Ruiying
<p>This dataset includes code and data for the manuscript of 'Zhao, R., Luo, X., Walker, A. P., Hoffman, F. M., Koh, L.P. (2025). Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle'.</p> <p><strong>Update (Nov 2025): </strong>we have released the <em>version 2</em> to include the raw data (Source_Data_Fig1.xlsx, Source_Data_Fig2.xlsx, Source_Data_Fig3.nc) and code (master_figure_clean.m, sup_code.zip) used for analysis and figure generation.</p> <p><strong>Update (Jun 2025): </strong>we have released the <em>version 1</em> to include the input, code and output for creating machine learning emulators for PFT GPP of each DGVM in TRENDY v9. </p> <p>The file 'input.zip' includes the predictor variables (i.e., annual precipitation, temperature, solar radition, pressure and wind speed during 2001-2019 from CRU JRA v2.1 datasets) and response (i.e., pixel PFT GPP rate) for each PFT of each DGVM.</p> <p>The file 'code4emulators.mlx' includes the code for training machine learning emulators (i.e., Random Forest models) for each PFT of each DGVM.</p> <p>The file 'model_emulators.zip' includes all trained emulators.</p>
title Data and Code for 'Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle'
url https://doi.org/10.5281/zenodo.17718653