Assessment of the ecological role of historic centres based on the relationship between biodiversity and urban composition

Abstract

Historic centres provide their inhabitants with identity and well-being. Although studies focus on the conservation of the built environment, in recent years the environmental component of historic centres has also been analysed. Issues such as ecosystem services and biodiversity have become more pressing due to rapid population growth, development and the climate crisis. Green spaces in historic centres often conserve biodiversity, as they tend to be protected spaces. This article presents two case studies in Castellón de la Plana (Spain) with the aim of analysing the relationship between the built environment and avian biodiversity. The study uses a four-phase process. The first phase incorporates a review of recent literature to select biodiversity indicators, while the second focuses on open data analysis and incorporation into GIS software. The third phase consists of field data collection and the mapping of biodiversity indicators. Finally, phase four involves the preparation of thematic maps, which allows us to visualize behavioural patterns connecting bird colonies with the morphology of the built environment in order to draw relevant conclusions that can help improve biodiversity. The analysis allowed the calculation of eight indicators and the identification of building typologies, the percentage of green areas and the inspection of features promoting avian biodiversity. In total, 31 bird species were detected, 27 in the historic centre of Castellón and 26 in the historic centre of the Grao district. Among them, the mapping distribution of three endangered species demonstrates their dependence on these historic built habitats. Apus apus, Passer domesticus and Delichon urbicum are present in 97, 82 and 56% of grids, respectively, with ANOVA correlation confirming these species densities found. The study is somewhat limited in the use of the line transect method due to the potential structural biases intrinsic to the unique nature of the districts assessed. © 2023 The Authors