Correlation between genetic diversity and environmental suitability: taking uncertainty from ecological niche models into account

• Published in: Molecular ecology resources 2015-09, Vol.15 (5), p.1059-1066
• Main Authors: Diniz-Filho, José Alexandre F., Rodrigues, Hauanny, Telles, Mariana Pires De Campos, Oliveira, Guilherme De, Terribile, Levi Carina, Soares, Thannya Nascimento, Nabout, João Carlos
• Format: Article
• Language: English
• Subjects: Biostatistics; Brazil; Cerrado; Climate; Confidence intervals; Dipteryx - classification; Dipteryx - genetics; Ecosystem; Genetic diversity; Genetic Variation; heterozygosity; Models, Theoretical; niche modelling; Phylogeography; Population Dynamics; suitability; tropical tree; uncertainty
• ISSN: 1755-098X; 1755-0998
• DOI: 10.1111/1755-0998.12374

The hindcast of shifts in the geographical ranges of species as estimated by ecological niche modelling (ENM) has been coupled with phylogeographical patterns, allowing the inference of past processes that drove population differentiation and genetic variability. However, more recently, some studies have suggested that maps of environmental suitability estimated by ENM may be correlated to species' abundance, raising the possibility of using environmental suitability to infer processes related to population demographic dynamics and genetic variability. In both cases, one of the main problems is that there is a wide variation in ENM development methods and climatic models. In this study, we analyse the relationship between heterozygosity (He) and environmental suitability from multiple ENMs for 25 population estimates for Dipteryx alata, a widely distributed, endemic tree species of the Cerrado region of central Brazil. We propose a new approach for generating a statistical distribution of correlations under randomly generated ENM. The confidence intervals from these distributions indicate how model selection with different properties affects the ability to detect a correlation of interest (e.g. the correlation between He and suitability). Additionally, our approach allows us to explore which particular ensemble of ENMs produces the better result for finding an association between environmental suitability and He. Caution is necessary when choosing a method or a climatic data set for modelling geographical distributions, but the new approach proposed here provides a conservative way to evaluate the ability of ensembles to detect patterns of interest.