Lab meeting: speciation and secondary sympatry

For next week's lab meeting (April 9 @ 10:30), let's read an interesting, new-ish paper by Alex Pigot and Joseph Tobias from Ecology Letters, showing that secondary sympatry of closely related species is limited by divergence time (with more recently separated species less likely to overlap geographically). This paper provides good evidence that competition limits geographic ranges, and should provide some interesting fuel for discussion in light of sympatric damselflies that have been studied in our lab.

Unfortunately, I will not be able to make it to the discussion, as I will be attending Bengt Hansson's landscape genetics course (co-taught by fellow lab members Maren Wellenreuther and Rachel Dudaniec!), but I can still provide fika and some discussion points.

The title/ abstract and link to the article are as follows:

Species interactions constrain geographic range expansion over evolutionary time

Abstract

Whether biotic interactions limit geographic ranges has long been controversial, and traditional analyses of static distribution patterns have made little progress towards resolving this debate. Here, we use a novel phylogenetic approach to test whether biotic interactions constrain the transition to secondary sympatry following speciation. Applying this temporal framework to a diverse clade of passerine birds (Furnariidae), we reject models of geographic range overlap limited purely by dispersal or environmental constraints, and instead show that rates of secondary sympatry are positively associated with both the phylogenetic and morphological distance between species. Thus, transition rates to sympatry increase with time since divergence and accelerate as the ecological differences between species accumulate. Taken together, these results provide strong empirical evidence that biotic interactions – and primarily ecological competition – limit species distributions across large spatial and temporal scales. They also offer phylogenetic and trait-based metrics by which these interactions can be incorporated into ecological forecasting models.