This project addresses the Industrial Strategy Grand Challenge theme of Artificial Intelligence and Data Driven Economy, specifically the latter element. It aims to build the evidence and data base for environmental benefits of urban trees and enhance the use of these data in wider society by developing and expanding an existing citizen science tool.
Trees in urban environments provide multiple benefits (pollution reduction, water regulation, carbon sequestration, amenity value etc.) which are increasingly well understood. Tools for assessing and valuing these benefits have been developed and their use in small and large-scale ecosystem-services evaluations is increasing. A key challenge is building understanding and acceptance of the value of urban trees among wider society. Citizen science provides an opportunity to actively engage individuals and organisations in data collection, information generation and understanding. In the context of urban trees in the UK, Treezilla – the Monster Map of Trees (www.treezilla.org), a collaboration between the Open University, Forest Research and Treeconomics (a social enterprise specializing in this area), engages citizens in these data collection efforts. It is also a platform to make tree data from local authorities and other organisations available to a wider public, adding value to it by incorporating ecosystem services calculations. At present the site is the largest open tree map that we are aware of anywhere, with over 800,000 records.
Treezilla uses models of the way ecosystem services vary with tree size and species to estimate their value. These models, developed in the USA, have been translated to be UK-relevant, but there is scope for them to be refined. This project will aim to collect data on UK urban trees to refine existing ecosystem service models. In parallel it will continue the collation and curation of large, local authority held tree datasets and carry out and evaluate a programme of citizen engagement in order to assess the use of Treezilla by citizens. Ultimately it will use data within Treezilla and models of ecosystem services provision to model the environmental benefits of urban trees at small and large scales and provide an open data-rich tool to allow others to do the same.
The project will investigate tree ecosystem services at individual and UK-wide scales. A sample of urban trees will be identified for detailed individual monitoring through the course of the PhD. Tree growth and physiology will be assessed using standard tools such as dendrometers, PAR sensors and LAI assessments. Large-scale ecosystem services provision from urban trees will be assessed at town/city scale UK-wide from data collated from local authorities and through the Treezilla app. The Treezilla app and database will form the primary means of citizen engagement. Spatial modelling of ecosystem services provision will use existing urban forest effects models in combination with a range of existing environmental datasets.
The outcomes will be improved models of ecosystem services provision from urban trees in the UK and an enhanced understanding of how data generated from these models can be used to inform citizens and organisations of the benefits of urban trees.
Partners and collaboration (including CASE)
This project will continue a long-running collaboration between OU and Forest Research (FR) on citizen science tools for ecosystem services valuation of trees which has resulted in the development of Treezilla and a NERC Green Infrastructure Innovation award: Project VITAL. The proposed CASE studentship would use the tools developed in VITAL. There is ongoing and active collaboration with FR’s Urban Forest Research Group supported by formal collaboration agreements. The project would continue and enhance the collaboration with the CASE placement carried out in FR’s Urban Forest Research Group.
Engaging society in driving change in environmental management is an essential element of delivering on this ambition. Key to ecosystem services delivery by trees are their ability to mitigate extremes of temperature, reducing energy consumption for domestic and commercial temperature regulation, sequestering carbon and perhaps most importantly improving air quality through removal of particulate and gaseous pollutants. This project will develop the tools from citizen science data to provide evidence and engage individuals and organisations in environmental management practices which support clean growth.