A Threat-Scoring Framework Using Crowdsourced Data Indicates High Threat Levels In Fossorial Shieldtail Snakes

Data and code (R programming language) for Shinde et al. (2026) A Threat-Scoring Framework Using Crowdsourced Data Indicates High Threat Levels In Fossorial Shieldtail Snakes. Animal Conservation This repository contains all data files and code used to conduct the analyses reported in Shinde et al. (2026) Anim. Cons. The code can be used to calculate threat metrics and reproduce figures from the article. Please refer to the main text while using the repository and the code. Data sources: GARD 1.7 Shieldtail range maps [9 species] are a subset from Roll, U., & Meiri, S. (2022). GARD 1.7-Updated Global Distributions for all Terrestrial Reptiles [Dataset]. Dryad. published in Caetano, G. H. D. O., Chapple, D. G., Grenyer, R., Raz, T., Rosenblatt, J., Tingley, R., ... & Roll, U. (2022). Automated assessment reveals that the extinction risk of reptiles is widely underestimated across space and phylogeny. PLoS Biology, 20(5), e3001544. IUCN Shieldtail range maps [9 species] were downloaded from the IUCN website. IUCN (2025). The IUCN Red List of Threatened Species. Version 2024-1. https://www.iucnredlist.org. Accessed on [22 March 2025]. Global Tree Cover data was sourced from Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. (2013). High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342 (15 November): 850-53. Data available online from: https://glad.earthengine.app/view/global-forest-change. Global Built-up land data was sourced from Potapov, P., Hansen, M. C., Pickens, A., Hernandez-Serna, A., Tyukavina, A., Turubanova, S., ... & Kommareddy, A. (2022). The global 2000-2020 land cover and land use change dataset derived from the Landsat archive: first results. Frontiers in Remote Sensing, 3, 856903. https://doi.org/10.3389/frsen.2022.856903