Range restriction, climate variability, and human-related risks imperil lizards worldwide
Chen, Chuanwu et al. (2023), Range restriction, climate variability, and human-related risks imperil lizards worldwide, Dryad, Dataset, https://doi.org/10.5061/dryad.rjdfn2zgn
The intrinsic predictors were collected from Meiri, 2018, Skeels et al. (2020), and Caetano et al. (2022). The extrinsic factors were calculated by mapping the environmental raters to the species distribution grids based on the shapefiles of the Global Assessment of Reptile Distributions (GARD; Roll & Meiri, 2022).
1. Meiri, S. (2018). Traits of lizards of the world: Variation around a successful evolutionary design. Global ecology and biogeography, 27, 1168–1172.
2. Skeels, A., Esquerré, D., & Cardillo, M. (2020). Alternative pathways to diversity across ecologically distinct lizard radiations. Global Ecology and Biogeography, 29, 454–469.
3. Roll, U., & Meiri, S. (2022). Data from: GARD 1.7—updated global distributions for all terrestrial reptiles. Dryad Digital Repository.
4. 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, e3001544.
We used R and the packages listed below to carry out the analyses. The phylogenetic linear regression model was performed using the package phylolm (https://github.com/lamho86/phylolm). The model averaging analyses were performed by using the package MuMIn (https://cran.r-project.org/package=MuMIn).
Innovation and Entrepreneurship Program of Jiangsu Province, Award: JSSCBS20210302
Priority Academic Program Development of Jiangsu Higher Education Institutions
National Natural Science Foundation of China, Award: 32001226
National Natural Science Foundation of China, Award: 31971545
National Natural Science Foundation of China, Award: 32271734