Height–diameter allometry for the management of city trees in the tropics. (16th October 2020) - Song, Xiao Ping; Lai, Hao Ran; Wijedasa, Lahiru S; Tan, Puay Yok; Edwards, Peter J; Richards, Daniel R
Abstract: Trees are important components of urban greenery because of their large stature and longevity, and their ability to enhance the environmental quality of city landscapes. However, benefits and hazards associated with trees depend on their size, which changes over time and varies among species. While urban trees are often measured during routine management, the full value of these data is rarely realised. Our study uses nation-wide inspection records from Singapore to develop allometric models for 54 species grown in the urban tropics ( n = 345 794), a region that is poorly represented in allometric literature. We use the height–diameter relationship to demonstrate how analyses of existing datasets can be used to support decisions on tree inspection and maintenance. The accuracy of models developed separately for each species (single-species models) and using the pooled data for all species (mixed-effects model) was compared. Model outputs and derived metrics were used to detect height outliers and priority regions that may require greater inspection effort, which we summarise using spatial visualisations and an online web application. Model parameters also varied according to each species' pruning intensity and maximum height, and can thus provide a useful heuristic when selecting species to plant. Such data-driven approaches have the potential to support both management and research, though changes to workflows may be needed to take advantage of new sources of data. Integrating multiple datasets into decision-making will require expertise across multiple disciplines, and coordinated action among stakeholders. By sharing the code used to develop the allometric models in a new open-source R package ' allometree ', we hope to promote reproducibility and facilitate the application of allometric equations to other tree parameters, study regions and management objectives.