J. Martínez Minaya, D. Conesa, M. J. Fortin, C. Alonso-Blanco, F. X. Picó, A. Marcer
Global climate change (GCC) is seriously affecting the distribution of many organisms. At present, multiple efforts are focused on the development of models to predict changes in distribution ranges due to GCC. In this study, we analyse the effect of GCC on the distribution range of the plant Arabidopsis thaliana. We use a collection of 301 natural A. thaliana populations occurring in the Iberian Peninsula and we compare three approaches: SDMs (species distribution models) excluding SAC (spatial autocorrelation) based on binary presence-only data from thresholded genetic cluster membership proportions; and non-spatial and spatial HBBMs (hierarchical Bayesian Beta regression models) based on continuous genetic cluster membership proportions data. We conclude that spatial HBBMs are a useful tool to avoid the loss of information due to the transformation of a continuous variable into a binary variable and to take into account the SAC.
Palabras clave / Keywords: climate change, geographic genetic structure, spatial autocorrelation, hierarchical Bayesian models, Arabidopsis thaliana
Programado
Sesión GT08-2 Inferencia Bayesiana-2: Genomics and Spatial statistics under a Bayesian perspective (BAYES-2). Organizador: Stefano Cabras
29 de mayo de 2018 17:00
Sala 1
