Direct Integration of Population Genetics and Dynamic Species Distribution Modelling Improves Predictions of Post-Glacial History of Piper nigrum

Aim

Climate change has a strong impact on species ranges and the genetic structure of populations, yet conclusions are often subject to large uncertainties when both are analysed independently. Here, we develop a novel framework to directly integrate population genetics and dynamic species distribution modelling to reduce such uncertainties when reconstructing the post-glacial history of black pepper.

Location

Western Ghats, India.

Methods

Genetic data of 243 individuals from 14 populations of wild Piper nigrum were derived from six chloroplast and five nuclear DNA simple sequence repeats (SSRs). Dynamic species distribution models (DSDMs) were applied since the Last Glacial Maximum (LGM, 21,000 years BP) based on paleo-climatic suitability at a high resolution (1 km, 100 years) and evaluated for a wide range of estimated migration rates and climate niches of the species. Population genetics and DSDMs were finally combined in a genetically informed DSDM, in which the estimated model parameters were optimised by maximising the correlation between the genetic diversity of the populations and their simulated colonisation history since the LGM.

Results

We observed higher gene diversity, haplotype richness, and allelic richness at lower latitudes, and two major phylogeographic groups belonging to the southern and central Western Ghats. Demographic inference from chloroplast SSRs estimated the split of these groups around the LGM. DSDMs showed a high uncertainty in parameter estimates, which were clearly reduced for the genetically informed DSDM. With this model, the correlation between genetic diversity and colonisation time was stronger than the correlation with latitude, and the simulation showed a northward expansion from low-latitude refugia and a recent fragmentation of the species range.

Main Conclusions

Our integrative approach reduces uncertainty in DSDMs and facilitates the interpretation of the population genetic structure. This added value is not given when population genetics and species distribution modelling are applied independently and merely compared.