Intraspecific morphological variation and environmental drivers in

Introduction: Methods: We analyzed 15 quantitative traits in 200 individuals from four populations located in the Azuay and Cañar provinces to identify morphological groups and assess their environmental drivers. Hierarchical clustering and Random Forest classification were employed to detect distinct morphological groups. Additionally, generalized linear models were used to evaluate the influence of climatic seasonality and spatial autocorrelation on the most relevant traits. Results: We identified two distinct morphological groups, primarily differentiated by seed number per fruit, fruit humidity, fruit length and width, and petiole length traits that together explained over 75% of the observed variation. Climatic seasonality and spatial autocorrelation significantly influenced these key traits. Notably, seed number and fruit length responded strongly to variations in temperature and precipitation, while traits such as fruit humidity and petiole length showed moderate sensitivity to environmental gradients. A Random Forest classification model, based on the most relevant traits, achieved 99.5% accuracy, enabling robust assignment of new individuals into morphological groups. Discussion: Our findings highlight the influence of environmental heterogeneity on intraspecific differentiation in