Roads are key drivers of economic growth and form a dominant feature in many landscapes. With road infrastructure steadily expanding — and projections indicating significant growth — it is important to ensure that road construction and upgrades do not trigger direct and indirect biodiversity loss, especially in ecologically sensitive areas. For road infrastructure to contribute meaningfully to both economic development and environmental protection, reliable data on location specific species distributions, abundance, and conservation status is essential.
This paper presents a methodology for identifying road corridors where biodiversity conservation should be a priority for infrastructure planning. Using over 600,000 species habitat maps derived from Global Biodiversity Information Facility (GBIF) occurrence records, our approach gives greater attention to plants and invertebrates, often overlooked in standard assessments. Designed for multi-processor cloud computing, the system will allow rapid, frequent updates as GBIF expands. By combining high-resolution species maps with country-specific road corridor maps generated by tailored algorithms, we classify species into four conservation priority groups based on endemism and habitat size — giving highest priority to endemic species with small habitats.
We apply this method to the Philippines and Sub-Saharan Africa. Our results show that biodiversity risk along road corridors varies widely, endemism strongly influences biodiversity-sensitive road location, and critical corridors for endemic species with small habitats are relatively few and geographically clustered. This means that road planners can make significant gains in biodiversity conservation by focusing on these limited priority areas, even in countries with constrained budgets.
| Repository name | URI |
|---|---|
| Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
Paper exhibits were reproduced on a computer with the following specifications:
• OS: Windows 11 Enterprise
• Processor: Processor INTEL(R) XEON(R) PLATINUM 8562Y+, 2800 Mhz, 16 Core(s), 16 Logical Pro-
cessor(s)
• Memory available: 128 GB
Runtime: 10 hours.
To reproduce the findings in this paper, follow the steps below:
.Rproj file included in the package.renv::restore()biod_roads_wp_global_libraries.Rbiod_roads_wp__main.R and run the code.biod_roads_wp__main.R to update the path.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 |
2025-10-06
| 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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