Historical demographic dynamics underlying local adaptation in the presence of gene flow

Biome stability predicts population structure of a southern African aridland bird species

Environments are heterogeneous in space and time, and the permeability of landscape and climatic barriers to gene flow may change over time. When barriers are present, they may start populations down the path toward speciation, but if they become permeable before the process of speciation is complete, populations may once more merge. In Southern Africa, aridland biomes play a central role in structuring the organization of biodiversity. These biomes were subject to substantial restructuring during Plio-Pleistocene climatic fluctuations, and the imprint of this changing environment should leave genetic signatures on the species living there. Here, we investigate the role of adjacent aridland biome boundaries in structuring the genetic diversity within a widespread generalist bird, the Cape Robin-chat (Cossypha caffra). We find evidence supporting a central role for aridland biomes in structuring populations across Southern Africa. Our findings support a scenario wherein populations were isolated in different biome refugia, due to separation by the exceptionally arid Nama Karoo biome. This biome barrier may have arisen through a combination of habitat instability and environmental unsuitability, and was highly unstable throughout the Plio-Pleistocene. However, we also recovered a pattern of extensive contemporary gene flow and admixture across the Nama Karoo, potentially driven by the establishment of homesteads over the past 200 years. Thus, the barrier has become permeable, and populations are currently merging. This represents an instance where initial formation of a barrier to gene flow enabled population differentiation, with subsequent gene flow and the merging of populations after the barrier became permeable.

31° South: The physiology of adaptation to arid conditions in a passerine bird

Arid environments provide ideal ground for investigating the mechanisms of adaptive evolution. High temperatures and low water availability are relentless stressors for many endotherms, including birds; yet birds persist in deserts. While physiological adaptation probably involves metabolic phenotypes, the underlying mechanisms (plasticity, genetics) are largely uncharacterized. To explore this, we took an intraspecific approach that focused on a species that is resident over a mesic to arid gradient, the Karoo scrub-robin (Cercotrichas coryphaeus). Specifically, we integrated environmental (climatic and primary productivity), physiological (metabolic rates: a measure of energy expenditure), genotypic (genetic variation underlying the machinery of energy production) and microbiome (involved in processing food from where energy is retrieved) data, to infer the mechanism of physiological adaptation. We that found the variation in energetic physiology phenotypes and gut microbiome composition are associated with environmental features as well as with variation in genes underlying energy metabolic pathways. Specifically, we identified a small list of candidate adaptive genes, some of them with known ties to relevant physiology phenotypes. Together our results suggest that selective pressures on energetic physiology mediated by genes related to energy homeostasis and possibly microbiota composition may facilitate adaptation to local conditions and provide an explanation to the high avian intraspecific divergence observed in harsh environments.

Sensory trait variation in an echolocating bat suggests roles for both selection and plasticity

Background

Across heterogeneous environments selection and gene flow interact to influence the rate and extent of adaptive trait evolution. This complex relationship is further influenced by the rarely considered role of phenotypic plasticity in the evolution of adaptive population variation. Plasticity can be adaptive if it promotes colonization and survival in novel environments and in doing so may increase the potential for future population differentiation via selection. Gene flow between selectively divergent environments may favour the evolution of phenotypic plasticity or conversely, plasticity itself may promote gene flow, leading to a pattern of trait differentiation in the presence of gene flow. Variation in sensory traits is particularly informative in testing the role of environment in trait and population differentiation. Here we test the hypothesis of ‘adaptive differentiation with minimal gene flow’ in resting echolocation frequencies (RF) of Cape horseshoe bats (Rhinolophus capensis) across a gradient of increasingly cluttered habitats.

Results

Our analysis reveals a geographically structured pattern of increasing RF from open to highly cluttered habitats in R. capensis; however genetic drift appears to be a minor player in the processes influencing this pattern. Although Bayesian analysis of population structure uncovered a number of spatially defined mitochondrial groups and coalescent methods revealed regional-scale gene flow, phylogenetic analysis of mitochondrial sequences did not correlate with RF differentiation. Instead, habitat discontinuities between biomes, and not genetic and geographic distances, best explained echolocation variation in this species. We argue that both selection for increased detection distance in relatively less cluttered habitats and adaptive phenotypic plasticity may have influenced the evolution of matched echolocation frequencies and habitats across different populations.

Conclusions

Our study reveals significant sensory trait differentiation in the presence of historical gene flow and suggests roles for both selection and plasticity in the evolution of echolocation variation in R. capensis. These results highlight the importance of population level analyses to i) illuminate the subtle interplay between selection, plasticity and gene flow in the evolution of adaptive traits and ii) demonstrate that evolutionary processes may act simultaneously and that their relative influence may vary across different environments.