The effects of global climate change on forest carbon sequestration potential in vegetation: source data and reproducible code

This repository contains the processed source data and reproducible Python code used to generate all figures in the manuscript The effects of global climate change on forest carbon sequestration potential in vegetation. The study combines 3.77 billion spaceborne lidar measurements from NASA's Global Ecosystem Dynamics Investigation (GEDI) and Ice, Cloud, and land Elevation Satellite-2 (ICESat-2), optical remote-sensing land-cover data, and the Ecosystem Demography (ED) model to estimate contemporary vegetation carbon stocks at 1-km spatial resolution. Starting from these observation-constrained forest conditions, the model projects transient annual biomass dynamics through 2100 under a reference scenario and 64 alternative scenarios spanning future climate, disturbance, and atmospheric CO₂ conditions. These simulations are used to quantify the forest carbon sequestration potential gap, defined as the difference between potential biomass in 2100 and contemporary biomass. The repository is organized by figure. Each figure has a dedicated folder (e.g., Figure_1, Figure_2, and Figure_S2) containing the processed source data required to reproduce the corresponding figure, together with publication-quality exported figure files. A single Jupyter notebook, Figures.ipynb, located in the repository root reproduces all main-text and supplementary figures from the corresponding processed data. Each section of the notebook is clearly labeled by figure number (e.g., Figure 1, and Figure 2) and generates the associated figure directly from the source data provided in this repository. The repository contains only the processed data required to reproduce the published figures. Detailed descriptions of the datasets, modeling framework, and analytical methods are available in the accompanying manuscript.