This repository archives and shares datasets, code, and resources associated with the research "Collaborative research networks as a strategy to synthesize knowledge of Amazonian biodiversity", by Resende et al., (2025), conducted under the INCT-SinBiAm (National Institute of Science and Technology in Synthesis of Amazonian Biodiversity) initiative. SinBiAm is a collaborative research network integrating 45 academic and non-academic institutions from Brazil and abroad, dedicated to synthesizing biodiversity data in Amazonian ecosystems. We aim to:
- Provide open access to biodiversity datasets from forest and freshwater ecosystems.
- Share analytical scripts and models used in biodiversity research and synthesis.
- Facilitate collaboration among researchers, policymakers, and educators.
- Support the training of scientists and decision-makers committed to Amazon conservation.
Below is an overview of the repository’s folder structure:
├── datasets
│ └── csv # Contains CSV data files used in the study.
│ ├── bolsistas_incts.csv # Lists fellows affiliated with the INCTs, including identifiers and affiliations.
│ ├── gbif_data.csv # Dataset extracted from GBIF containing species distribution data.
│ ├── gbif_macrophyte.csv # Data on macrophyte species collected from GBIF.
│ ├── incts.csv # Data on spatial distribution of INCTs across Brazil.
│ ├── neo_sex.csv # Lists fellows affiliated with the INCTs and their sex.
│ └── taoca_data.csv # Dataset extracted from TAOCA containing species data.
│ └── pdf # Contains PDF files used in the study.
│ └── res_2022.pdf # Document with results on the 2022 call for INCT proposals.
│ └── spatial # Contains spatial files for geographic analysis.
│ ├── BR_Regioes_2023.shp # Shapefile with Brazilian regions for spatial analysis.
│ ├── BR_UF_2022.shp # Shapefile with Brazilian states for spatial analysis.
│ └── brazilian_legal_amazon.shp # Shapefile defining the Brazilian Legal Amazon boundaries.
│
├── figures
│ ├── 2022_proposals.tif # Barplot showing proposals submitted in 2022 by Brazilian regions.
│ ├── all_maps.tif # Compilation of various maps used in the study.
│ ├── map_biodiversity.tif # Map illustrating biodiversity INCTs distribution.
│ ├── map_coords&students.tif # Map showing the distribution of coordinators and students og INCTs across Brazil.
│ └── proportion_taxa.tif # Visualization of taxa proportions in the GBIF vs. TAOCA datasets.
│
├── figures_edit
│ ├── all_maps_edit.tif # Edited version of all_maps.tif.
│ ├── map_biodiversity_edit.tif # Edited version of map_biodiversity.tif.
│ ├── map_coords&students_edit.tif # Edited version of map_coords&students.tif.
│ └── proportion_taxa_edit.tif # Edited version of proportion_taxa.tif.
│
├── old_packages
│ ├── tabulizer_0.2.2.tar.gz # R package for extracting tables from PDFs.
│ └── tabulizerjars_1.0.1.tar.gz # Java dependency required for the tabulizer package.
│
├── scripts
│ ├── 00. setup.R # Script for setting up the R environment and loading dependencies.
│ ├── 01. sex survey.R # Script to scrap data on sex of coordinators and students of INCTs.
│ └── 02. data analysis.R # Main R script for data processing, statistical analysis, and visualization.
│
├── INCT.Rproj # RStudio project file for organizing and managing the analysis environment.
│
├── LICENSE # License file specifying the terms of use and distribution of the repository.
│
└── README.md # Documentation file providing an overview of the project and instructions for use.
- Clone the repository:
git clone https://github.com/lucas-colares/INCTs.git
- Open
INCT.Rprojin RStudio. - Run
00. setup.Rto set up the analysis environment. - Use the remaining scripts to explore and analyze the data.
If you use or modify any part of this repository in your work, please cite the original paper:
Resende, B., Colares, L.F., et al. (2025). Collaborative research networks as a strategy to synthesize knowledge of Amazonian biodiversity. Submitted to Proceedings of the Royal Society B: Biological Sciences.
This repository is released under the MIT license. You are free to use, modify, and distribute the code with proper attribution.