Latitudinal variation in climate-associated genes imperils range-edge populations
Smith, Steve et al. (2020), Latitudinal variation in climate-associated genes imperils range-edge populations, Dryad, Dataset, https://doi.org/10.5061/dryad.73n5tb2v2
The ecological impacts of increasing global temperatures are evident in most ecosystems on Earth, but our understanding of how climatic variation influences natural selection and adaptive resilience across latitudes is still largely unknown. Latitudinal gradients allow testing general ecosystem-level theories relevant to climatic adaptation. We assessed differences in adaptive diversity of populations along a latitudinal region spanning highly variable temperate to subtropical climates. We generated and integrated large-scale information from environmental mapping, phenotypic variation and genome-wide data for 21 populations of rainbowfish (Melanotaenia duboulayi), an emerging aquatic system for studies of climate change. We detected, after controlling for spatial population structure, strong interactions between genotypes and environment associated to variation in stream flow and temperature. Some of these hydroclimate-associated genes were found to interact within functional protein networks that contain genes of adaptive significance for projected future climates in rainbowfish. Hydroclimatic selection was also associated with variation in phenotypic traits, including traits known to affect fitness of rainbowfish exposed to different flow environments. Consistent with predictions from the ‘climatic variability hypothesis’, populations exposed to extremes of important environmental variables showed stronger adaptive divergence and less variation in climate-associated genes compared to populations at the center of the environmental gradient. This suggests that populations that evolved at environmental range margins may be more vulnerable to changing climates, a finding with implications for predicting adaptive resilience and managing biodiversity under climate change.
Australian Research Council, Award: DP110101207
Australian Research Council, Award: FT130101068