This study investigates 15 populations of an alpine shrub Rhododendron intricatum in the Mt. Gongga region of the eastern Hengduan Mountains and reveals coordinated genomic and phenotypic responses to shared environmental gradients.
Abstract
Understanding how plants adapt to elevational niches is essential for uncovering mechanisms of natural selection and diversity patterns in mountain systems. Integrating genomic and ecological approaches is therefore important for advancing our knowledge of plant adaptation and informing conservation under climate change. In this study, we investigate 15 populations of an alpine shrub Rhododendron intricatum in the Mt. Gongga region of the eastern Hengduan Mountains, focusing on genomic and phenotypic responses across elevations. Genotype‐environment association analyses identified multiple outlier genomic regions associated with elevation, consistent with polygenic responses to environmental gradients, and candidate genes were broadly linked to functions such as signalling, stress responses, metabolism and reproductive regulation. Distinct allele turnover patterns along precipitation seasonality and mean annual temperature further indicate the combined effects of climatic heterogeneity in shaping genomic responses. Concurrently, systematic trends were detected in phenotypic traits along elevation, including increased leaf spectral reflectance, shifts in vegetative dimensions and changes in floral morphology. Predictive models under future climate scenarios reveal increasing genetic offset through time, and projected mismatch becomes uniformly severe across the entire elevational gradient by the end of the century. Together, multiple lines of evidence reveal coordinated genomic and phenotypic responses to shared environmental gradients. Our findings demonstrate generalized ecological strategies in mountain systems and highlight the extreme vulnerability of alpine endemics to ongoing climate change.
How biotic and abiotic selective pressures shape adaptive genomic variation is revealed and a framework for forecasting evolutionary responses to future global change is provided.
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