Jun 05, 2013
EEB graduate student Qixin He’s paper was selected as EEB’s Outstanding Paper of the Year. Published online June 5, 2013 in the journal Evolution, the paper is titled "Integrative testing of how environments from the past to the present shape genetic structure across landscapes."
He's coauthors are her advisor Professor L. Lacey Knowles and a former postdoctoral fellow in the Knowles lab, Danielle Edwards. They have been studying a southwestern Australian lizard species, Lerista lineopunctulata, which has highly reduced limbs and lives on sand plains or dunes. The genetic diversity of the species is not even – it’s highest in peninsulas near Shark Bay and lowest in the northern and southern extremes of their distribution, He explained.
“Several mechanisms could potentially explain this pattern,” said He. “Climatic factors might make the peninsulas more suitable habitats for the lizards, or the peninsulas might have been their refuge in the glacial time, and current distribution is a recolonization process from the past, or both of these mechanisms may be important. We performed ecological niche modeling using climatic data of their current distribution and predicted their potential occurrence in the past. During glaciations, coastline extended towards the ocean as sea level decreased. We found that in the last glacial maximum (LGM, a time in Earth’s climate history when ice sheets were at their maximum extension, about 20,000 years ago), suitable areas for the species shifted significantly, and only the Shark Bay area remained suitable from LGM until the present.
“Our spatially explicit demographic modeling confirmed that the model which considered recolonization from refugia and tracked the suitability of changes through time had the highest support, compared to ones that only considered current distributions or suitabilities. This finding emphasized the importance of linking historical processes with patterns we observe in the present. As landscapes are changing, so are species. Our paper also presented a scenario testing approach by integrating distributional, demographic and coalescent models to generate species-specific predictions of genetic variation, which can be readily applied in many different questions or systems.”
EEB postdoctoral fellows Joseph Coolon and Joseph Brown were the reviewers. “Beyond simply identifying the problem, Qixin et al. go on to supply a solution,” the committee wrote. They also noted that the authors performed post-analysis model adequacy tests, “something that is far too rarely performed in evolutionary biology.”
“Qixin's paper is rigorous in analysis, yet pedagogically presented; for these reasons, it is sure to be of great interest to the field,” they concluded.