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<p><i>Calotropis procera</i> (Aiton) W.T.Aiton is a perennial xerophytic shrub widely distributed in arid and semi-arid regions of Iran. Understanding the spatial and phenotypic variation of morphological and anatomical traits is crucial for evaluating adaptive capacity under environmental gradients. We investigated leaf morphological and anatomical variation across 12 populations of <i>C. procera</i>, integrating multivariate analyses, spatial modeling, reaction norm mixed models (RRMM), and landscape adaptive indices (LAI). Morphological and anatomical traits exhibited significant population differentiation and phenotypic plasticity. Spatial principal component analysis (sPCA) revealed strong spatial structuring of traits along climatic and geographic gradients. Redundancy analysis (RDA) and canonical correspondence analysis (CCA) showed significant associations between traits and environmental variables. Kriging of LAI highlighted heterogeneous adaptive potential, with high-LAI populations serving as genetic and adaptive reservoirs, while low-LAI populations were vulnerable. Our findings provide a comprehensive framework for assessing phenotypic adaptation and guiding conservation of xerophytic species in arid landscapes.</p>

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Morphological, anatomical, and spatial adaptation of Calotropis procera populations across climatic and geographic gradients in Iran

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月23日

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  • Mohamad Reza Kordasti,
  • Masoud Sheidai,
  • Fahimeh Koohdar

摘要

Calotropis procera (Aiton) W.T.Aiton is a perennial xerophytic shrub widely distributed in arid and semi-arid regions of Iran. Understanding the spatial and phenotypic variation of morphological and anatomical traits is crucial for evaluating adaptive capacity under environmental gradients. We investigated leaf morphological and anatomical variation across 12 populations of C. procera, integrating multivariate analyses, spatial modeling, reaction norm mixed models (RRMM), and landscape adaptive indices (LAI). Morphological and anatomical traits exhibited significant population differentiation and phenotypic plasticity. Spatial principal component analysis (sPCA) revealed strong spatial structuring of traits along climatic and geographic gradients. Redundancy analysis (RDA) and canonical correspondence analysis (CCA) showed significant associations between traits and environmental variables. Kriging of LAI highlighted heterogeneous adaptive potential, with high-LAI populations serving as genetic and adaptive reservoirs, while low-LAI populations were vulnerable. Our findings provide a comprehensive framework for assessing phenotypic adaptation and guiding conservation of xerophytic species in arid landscapes.