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. 2019 Mar 12;9:4229. doi: 10.1038/s41598-019-40450-8

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© The Author(s) 2019

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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Presence and significance and coefficient values for random and fixed effects present in the top set models of each category. The left hand plots indicate whether predictors are absent (yellow), present but non-significant (green), or present and significant (blue) in each top model. The right hand plots indicates the coefficient values for predictors when present in each top model. In each panel, models are numbered along the x-axis, ranked in order of model performance, from low DIC (“best”, left-hand side) to high DIC (“worst”, right-hand side). The Intercept term was present with significant negative impacts in all models and is not shown. The fixed effect predictors are ordered by the number of times they appeared in the top model set from most (top) to least (bottom) and their names are abbreviated as in Table 1. The spatial random effects are precision (Prec_ID) and the phi parameter, (Phi_ID).