The publication of nearly 600,000 new species occurrence maps using Global Biodiversity Information Facility data provides an opportunity to reassess international species protection with broader representation for plants, invertebrates, and other species. This development aligns with the global 30x30 initiative, where 188 governments have committed to expanding terrestrial and marine protection to cover 30 percent of the planet by 2030. This study leverages Global Biodiversity Information Facility occurrence maps to identify new opportunities for species protection in 10 countries in Latin America (Brazil, Costa Rica, and Ecuador), Africa (Cameroon, South Africa, and Madagascar), and the Asia-Pacific region (Papua New Guinea, the Philippines, India, and China). By focusing on individual countries, the paper emphasizes the importance of local conservation stewardship. Both terrestrial and marine cases are analyzed, with particular attention to endemic species. Unlike previous efforts, this approach assigns equal weight to all vertebrates, invertebrates, plants, and other species mapped in the database. A spatially efficient algorithm identifies priority localities for establishing new protected areas to safeguard unprotected species. The findings reveal that initial conditions, such as existing protection levels and the spatial clustering of unprotected species, greatly influence outcomes. Unprotected species are shown to be spatially clustered in some countries but not in others, and the representation of different taxa among unprotected species is found to vary significantly across countries. Some countries can achieve full protection within the 30 percent territorial limit, while others may need to exceed it. However, in all cases, spatial clustering enables significant protection gains through modest expansions of protected areas, demonstrating a path forward for enhancing biodiversity conservation within global commitments.
Repository name | URI |
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Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
Paper exhibits were reproduced in a computer with the following specifications:
• OS: Windows 11 Enterprise, version 21H2
• Processor: Intel(R) Xeon(R) Gold 6226R CPU @ 2.90GHz, 16 Core(s)
• Memory available: 15.7 GB
• Software version: R 4.4.1, Stata 18.
~20 minutes runtime
To successfully replicate this package, new users should follow these steps:
.Rproj
file). renv
package by running:renv::restore()
biod_pa_wp__main.R
).biod_pa_wp__main.R
file to execute the full replication process.Some data is restricted and has not been included in the reproducibility package. For more details, please refer to the README file.
Author | Affiliation | |
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Brian Blankespoor | World Bank | bblankespoor@worldbank.org |
Susmita Dasgupta | World Bank | sdasgupta@worldbank.org |
David Wheeler | World Bank | wheelrdr@gmail.com |
2025-02-20
Location | Code |
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World | WLD |
The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.
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Modified BSD3 | https://opensource.org/license/bsd-3-clause/ |
Name | Affiliation | |
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Brian Blankespoor | World Bank | bblankespoor@worldbank.org |
Reproducibility WBG | World Bank | reproducibility@worldbank.org |
Name | Abbreviation | Affiliation | Role |
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Reproducibility WBG | DIME | World Bank - Development Impact Department | Verification and preparation of metadata |
2025-02-20
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