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. 2020 Jul 10;10:11473. doi: 10.1038/s41598-020-68167-z

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Multi-colinearity among the predictor variables used in the final random forest modelling of tiger and leopard. The multi-colinearity was tested at (r > 0.50) using the R package “rfUtilities” and correlogram was produced using the R package “ENMTools”. The road density is represented at two spatial scales (1 km and 4 km) as shown in the top right corner of the correlogram as rd1km and rd4km, and moistdec, drydec represent the moist and dry deciduous forests respectively and hump denotes the human population density defined as the number of persons per square km.