Urban Trees and Hydrological Ecosystem Service: A Novel Approach to Analyzing the Relationship Between Landscape Structure and Runoff Reduction.

Autor: Amini Parsa V; Social-Ecological Systems Analysis Lab, Faculty of Economics and Sociology, University of Lodz, Lodz, Poland. vahid.parsa@uni.lodz.pl., Istanbuly MN; Department of Natural Resources and Environment, University of Aleppo, Aleppo, Syria., Kronenberg J; Social-Ecological Systems Analysis Lab, Faculty of Economics and Sociology, University of Lodz, Lodz, Poland., Russo A; School of Arts, University of Gloucestershire, Cheltenham, UK., Jabbarian Amiri B; Department of Regional Economics and the Environment, Faculty of Economics and Sociology, University of Lodz, Lodz, Poland.
Jazyk: angličtina
Zdroj: Environmental management [Environ Manage] 2024 Jan; Vol. 73 (1), pp. 243-258. Date of Electronic Publication: 2023 Aug 26.
DOI: 10.1007/s00267-023-01868-z
Abstrakt: Urban stormwater runoff has posed significant challenges in the face of urbanization and climate change, emphasizing the importance of trees in providing runoff reduction ecosystem services (RRES). However, the sustainability of RRES can be disturbed by urban landscape modification. Understanding the impact of landscape structure on RRES is crucial to manage urban landscapes effectively to sustain supply of RRES. So, this study developed a new approach that analyzes the relationship between the landscape structural pattern and the RRES in Tabriz, Iran. The provision of RRES was estimated using the i-Tree Eco model. Landscape structure-related metrics of land use and cover (LULC) were derived using FRAGSTATS to quantify the landscape structure. Stepwise regression analysis was used to assess the relationship between landscape structure metrics and the provision of RRES. The results indicated that throughout the city, the trees prevented 196854.15 m 3 of runoff annually. Regression models (p ≤ 0.05) suggested that the provision of RRES could be predicted using the measures of the related circumscribing circle metric (0.889 ≤ r 2  ≤ 0.954) and the shape index (r 2  = 0.983) of LULC patches. The findings also revealed that the regularity or regularity of the given LULC patches' shape could impact the patches' functions, which, in turn, affects the provision of RRES. The landscape metrics can serve as proxies to predict the capacity of trees for potential RRES using the obtained regression models. This helps to allocate suitable LULC through optimizing landscape metrics and management guidance to sustain RRES.
(© 2023. The Author(s).)
Databáze: MEDLINE
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