Can Plant Functional Traits Be Used as Integrators of Environmental Stressors in Urban Areas?

This study investigates the environmental differences and tree leaf structure and morphology in urban and suburban sites in the Chicago Metropolitan region. The leaf functional traits of Norway Maple and Littleleaved Linden were studied in three locations in the summer of 2023: an urban park (University of Illinois Chicago, Chicago, IL), a suburban park (Morton Arboretum in Lisle, IL), and a suburban residential site (Lombard, IL). Our urban site had higher daytime and nighttime air and land surface temperatures compared to suburban sites, with significant fluctuations observed across the sites. Cumulative growing degree days, a measure of potential photosynthetic active days, were higher in the urban site than in the suburban sites during March and August. Norway Maple trees growing in the urban site had higher specific leaf area (SLA) and lower leaf dry matter content (LDMC) than in suburban sites, resulting in bigger and thinner leaves than in suburban sites. Similarly, Little−leaved Linden trees in suburban residential sites displayed higher SLA and lower LDMC than trees of the same species in suburban park and residential sites. Gas exchange traits, namely photosynthetic assimilation, transpiration rates, and stomatal conductance, decreased between the urban and two suburban sites as temperatures increased throughout the summer. The influence of species and site on gas exchange traits was significant during the summer but not during the fall. Norway Maple gas exchange values decreased as the growing season progressed, as expected by ontogeny. In contrast, Little−leaved Linden maintained similar leaf gas exchange values throughout the growing season. Comparisons with existing global trait databases emphasize the need for localized data to capture site−specific responses accurately because although some traits aligned well with database values, others deviated significantly, underscoring the importance of comprehensive datasets for robust ecosystem modeling and management strategies.