
This repository provides all scripts and data necessary to reproduce the analyses and figures presented in our manuscript, Zhang et al. (2026). Unexpected expansion and regrowth in Earth’s mangrove forests over the past four decades, accepted for publication in Science. Code_Figures.zip contains Jupyter Notebook scripts written in Python to reproduce all analyses, data processing workflows, and figures described in the paper. Code_Data.zip includes the datasets required to run the notebooks. All codes were developed using Python (version 3.11.7) with standard geospatial and scientific libraries (e.g., numpy, pandas, geopandas, rasterio, matplotlib, cartopy, geemap). The notebooks are organized by figure number for easy replication and modification. Update note: Version 1.0.1 adds the Code_Data.zip file that was inadvertently omitted from the initial release (v1.0). All previously released scripts remain unchanged.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
