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. 2020 Mar 17;10:4884. doi: 10.1038/s41598-020-61880-9

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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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A set of maps showing three different scales of potential animal occurrence data and subsequent models for an endangered animal species case study in California. From left-to-right, the first panel shows California within an inset denoting the regional sampling focus specific to this study. Data can be sampled throughout the entire range of a species depending on its distribution and extent and are typically modeled with Maxent. The middle inset maps the estimated home ranges using 95% minimum convex polygon models for the lizard species Gambelia sila within Carrizo National Monument, California, USA from 2016 to 2018. The inset on right shows the fine-grain telemetry relocation data collected as points. A total of 3553 instances were sampled for a total of 80 unique individual animals. Shrub and open designations describe whether the individual animal in each was instance was within 5 m of a shrub (dark green points) or in the relative open not near the canopy of a shrub (light green points). In this study, we use resource selection functions to infer predicted likelihoods of habitat use patterns at this scale. Base map credits ESRI.