The Global Biodiversity Framework adopted at COP 15 set a target to protect 30% of the world’s land and sea areas by 2030. This paper evaluates the potential contribution of the 30x30 initiative to biodiversity conservation by examining its implications for species that are endemic or occupy very small habitats. Using over 600,000 species occurrence maps derived from GBIF data—substantially expanding representation for plants and invertebrates—the study develops high-resolution, country-specific templates that identify priority-ordered protected areas optimized for cost-effective species coverage. Each iteration expands protection to maximize gains for unprotected species until full coverage is achieved, allowing flexibility to adapt to national economic and political constraints, including the 30% target of 30x30.
Results include priority-ordered terrestrial protected areas for 138 countries and marine protected areas for 160 countries. At the global level, full protection of currently protected species aligns with 30% terrestrial and marine coverage. Expanding global land protection from 14.8% to 18.0% and marine protection from 16.6% to 19.9% would achieve 100% species coverage in the database. However, uneven species distributions make this infeasible for all countries within the 30% territorial limit. Among 242,414 critical species analyzed, 65.5% are currently protected; most of the remainder could be covered within national 30% limits, though some countries would need to exceed them.
The analysis highlights opportunity-cost disparities—particularly for low-income countries—indicating that effective implementation of 30x30 will require international compensation mechanisms. The study underscores that true success lies in species protection rather than territorial extent.
| Repository name | URI |
|---|---|
| Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
Paper exhibits were reproduced on a computer with the following specifications:
• OS: macOS Sequoia
• Processor: Apple M4 Pro
• Memory available: 24 GB
Runtime: 20 minutes
To fully reproduce the findings in this paper, please follow these steps:
.Rproj file.renv::restore() and following the prompts.global_pa_wp_global_libraries.R.global_pa_wp_main.R and executing the code.All datasets used in this project are publicly available, and all data are downloaded directly within the code.
All data sources are publicly available and included in the reproducibility package.
| Author | Affiliation | |
|---|---|---|
| Brian Blankespoor | World Bank | bblankespoor@worldbank.org |
| Susmita Dasgupta | World Bank | sdasgupta@worldbank.org |
| David Wheeler | World Bank | wheelrdr@gmail.com |
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| Location | Code |
|---|---|
| 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.
| Name | URI |
|---|---|
| Modified BSD3 | https://opensource.org/license/bsd-3-clause/ |
| Name | Affiliation | |
|---|---|---|
| Brian Blankespoor | World Bank | bblankespoor@worldbank.org |
| Reproducibility WBG | World Bank | reproducibility@worldbank.org |
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Reproducibility WBG | DECDI | World Bank - Development Impact Department | Verification and preparation of metadata |
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