Razieh  Ebadati Esfahani 2020. Applying Ellenberg's indicator values to the study of green roofs installed with native plants. Master Thesis. The University of Lisbon -  School of Agriculture.

Supervisors: 

Prof. Maria Teresa Gomes Afonso do Paço

Prof. Ana Paula Ferreira Ramos

 Abstract
Horizon 2020 policies and objectives for urban management, including energy conservation and increase of biodiversity, growing interest, and cities need to build sustainable green roofs in urban spaces, have led to advanced scientific research in this area. This has also induced a more specific choice of plant species and nature-based solutions to be used. In North Europe, North America, and Asia, extensive green roofs are generally part of the new building design, while they are still uncommon in the Mediterranean area. Environmental conditions can be limiting for the expansion of green roofs in those areas. The use of native species, given their high diversity and adaptations to environmental stresses, can be a sustainable solution, both in terms of biodiversity and economics. This study seeks to examine the native plant survival rate results, flowering duration and intensity, and green cover areas of three green roof projects NativeScapeGR, apiWall, and apiMat conducted separately from 2016 to 2020 at the University of Lisbon. Furthermore, we used Ellenberg's indicator values for the plants chosen to propose a list of suitable natives for green roofs.
Among all species evaluated, only Antirrhinum linkianum, Brachypodium phoenicoides, Briza maxima, Capsella bursa-pastoris, Chrysanthemum coronarium, Foeniculum vulgare, Lavandula stoechas, Rosmarinus officinalis, and Sedum sediforme showed favorable results, based on the results of NativeScapeGR, apiWall, and apiMat projects and Ellenberg's indicator.
This research presents a reliable method for selecting wild plant species (non or less irrigated than the species more commonly available commercially) and design patterns for extensive green roofs based on ecological and nature-based characteristics.
Keywords:

Edition: 7th Edition: 2018/2020
University: University of Lisbon, Portugal
Section: Thesis
Author: Razieh  Ebadati Esfahani