Unravelling Adaptive Resilience, Tolerance Mechanisms and Mitigation Potential of Roadside Tree Species to Vehicular Emissions across Urban Habitats
Urban roadside trees (URTs) are crucial in mitigating air pollution and enhancing city ecosystem services. However, vehicular emissions and human activities in urban areas poses significant physiological, and biochemical challenges to their resilience. This study elucidates the adaptive resilience and tolerance mechanisms of URTs subjected to vehicular emissions across various urban habitats. A plant functional trait-based approach was employed to assess seasonal modulations in physiological responses, biochemical adaptations, and air pollution tolerance of five roadside tree species in habitats dominated by industrial, vehicular, and societal activities, as well as control sites. We evaluated adaptive resilience by assessing functional traits such as stomatal conductance, transpiration, water use efficiency, nitrogen use efficiency, leaf thickness, proline accumulation, and total sugars. Air pollution tolerance was determined using the air pollution tolerance index (APTI), calculated based on antioxidant levels, chlorophyll content, relative water content, and leaf pH. The mitigation efficiency of tree species was evaluated by examining carbon assimilation, dust load capacity, and cooling effects of trees across studied habitats. All functional traits varied significantly across species and environmental conditions. The findings revealed that tree species with higher adaptive resilience and air pollution tolerance exhibited greater mitigation efficiency toward urban climate conditions and vehicular emissions. Furthermore, this study provides essential scientific insights into tree species adaptive resilience, tolerance, and mitigation efficiency in response to vehicular pollution. This approach may assist urban planners and policymakers in selecting appropriate species for green belts and urban green spaces to adapt to and mitigate urban climate challenges and vehicular emissions.
Institutions
- Forest Research Institute (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-06-05
- DOI
- https://doi.org/10.5281/zenodo.15789437
- Primary Topic
- Complex Network Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00