{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DIME","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2025-02-20","version":"1"},"project_desc":{"authoring_entity":[{"name":"Brian Blankespoor","affiliation":"World Bank","email":"bblankespoor@worldbank.org"},{"name":"Susmita Dasgupta","affiliation":"World Bank","email":"sdasgupta@worldbank.org"},{"name":"David Wheeler","email":"wheelrdr@gmail.com","affiliation":"World Bank"}],"title_statement":{"title":"Reproducibility package for Implementing 30x30: Lessons from Country Case Studies","idno":"RR_WLD_2025_277"},"data_statement":" Some data is restricted and has not been included in the reproducibility package. For more details, please refer to the README file.","software":[{"name":"R","version":"4.4.1"},{"name":"Stata","version":"18"}],"scripts":[{"title":"Reproducibility package for Implementing 30x30: Lessons from Country Case Studies","date":"2025-02-20","notes":"Computational reproducibility verified by Development Impact (DIME) Analytics team, World Bank.","notes.1":"Computational reproducibility verified by Development Impact (DIME) Analytics team, World Bank.","file_name":"RR_WLD_2025_277.zip","zip_package":"RR_WLD_2025_277.zip","dependencies":"All dependencies are stored in the renv environment in this reproducibility package."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2025-02-20","abstract":"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.","geographic_units":[{"name":"World","code":"WLD","type":"Region"}],"keywords":[{"name":"Biodiversity Conservation"},{"name":"Protected Areas"},{"name":"Endemic Species"},{"name":"Kunming-Montreal\nGlobal Biodiversity Framework"}],"topics":[{"id":"Q57","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Ecological Economics: Ecosystem Services \u2022 Biodiversity Conservation \u2022 Bioeconomics \u2022 Industrial Ecology","parent_id":"Q5"}],"output":[{"type":"Working Paper","description":"Policy Research Working Papers (PRWP) 11045","title":"Implementing 30x30 : Lessons from Country Case Studies","authors":"Susmita Dasgupta, Brian Blankespoor, David Wheeler","doi":"https:\/\/doi.org\/10.1596\/1813-9450-11045","uri":"http:\/\/documents.worldbank.org\/curated\/en\/099643201242514265"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"~20 minutes runtime","disclaimer":"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.","license":[{"name":"Modified BSD3","uri":"https:\/\/opensource.org\/license\/bsd-3-clause\/"}],"contacts":[{"name":"Brian Blankespoor","affiliation":"World Bank","email":"bblankespoor@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"reproduction_instructions":"To successfully replicate this package, new users should follow these steps:  \n1. **Download** the package.  \n2. **Open** the R project (`.Rproj` file).  \n3. **Recreate** the R environment using the `renv` package by running:  \n `renv::restore()`\n4. Add the Stata path in the main R script (`biod_pa_wp__main.R`).\n5. **Run** the `biod_pa_wp__main.R` file to execute the full replication process.\n- Note: There are two figures (Figures 20 and 22) that the user will not be able to reproduce, as the data used to create them are restricted. However, these figures are included in the outputs folder so that users can visually review their reproducibility. All the other data needed to run this package is already included. \n","technology_environment":"Paper exhibits were reproduced in a computer with the following specifications:\n\u2022 OS: Windows 11 Enterprise, version 21H2\n\u2022 Processor: Intel(R) Xeon(R) Gold 6226R CPU @ 2.90GHz, 16 Core(s)\n\u2022 Memory available: 15.7 GB\n\u2022 Software version: R 4.4.1, Stata 18.","datasets":[{"name":"Critical Species by Country","note":"Source: Elaborated by the authors.\nCritical Species for Brazil, Cameroon, China, Costa Rica, India, Madagascar, Papua New Guinea, Philippines, South Africa, Ecuador. Data is included in the reproducibility package, it will also be published in the Development Data Hub. \nLocation: local\/geo_data\/ folders: Brazil_full_protection, Brazil_top4, Cameroon_full_protection, Cameroon_top4, China Files, Costa_Rica_top3, India Files, Madagascar_top4, Philippines_top4, South_Africa_top3, species.","access_type":"Included in the reproducibility package","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066734\/Implementing-30x30--Lessons-From-Country-Case-Studies---replication-data-files","license":"Creative Commons NonCommercial License","license_uri":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/deed.en"},{"name":"Protected Areas by Country","note":"Source: Elaborated by the authors.\nProtected Areas for Brazil, Cameroon, China, Costa Rica, India, Madagascar, Papua New Guinea, Philippines, South Africa, Ecuador. Data is included in the reproducibility package, it will also be published in the Development Data Hub. \nLocation: local\/geo_data\/ folders: Brazil_PA, Cameroon_PA, China Files, Costa_Rica_PA, India Files, Papua_New_Guinea_PA, South_Africa_PA, Ecuador_PA.","access_type":"Included in the reproducibility package","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066734\/Implementing-30x30--Lessons-From-Country-Case-Studies---replication-data-files","license":"Creative Commons NonCommercial License","license_uri":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/deed.en"},{"name":"World Database of Protected Areas - Restricted","note":"Source: World Bank. \nLocation: Boundary_Data_10mil\/WB_Admin0_boundary_lines_10m.shp; Boundary_Data_10mil\/WB_Admin0_boundary_lines_disputed_areas_10m.shp; Boundary_Data_10mil\/WB_Admin0_Disputed_areas_10m.shp; Boundary_Data_10mil\/WB_Coastlines_10m.shp. \nThe non-inclusion of these files only limits the user to produce figures 20 and 22, which are included in the outputs folder for comparison. \n","access_type":"There is no documented way to access the data, and it is not included in the reproducibility package."},{"name":"World Database of Protected Areas Boundary Lines - Public","note":"Source: World Bank API. Code to query this data is already included in the reproducibility package (biod_pa_wp_load_ddh_boundary_data.R). \nLocation: wbbnd_ddh\/WB_countries_Admin0_10m\/WB_countries_Admin0_10m.shp.","access_type":"Included in the reproducibility package","license":"Creative Commons NonCommercial License","license_uri":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/deed.en","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066734\/Implementing-30x30--Lessons-From-Country-Case-Studies---replication-data-files"}]},"tags":[{"tag":"DOI"},{"tag":"Open code"},{"tag":"Open data"}],"schematype":"script"}