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Urban ecological connectivity as a planning tool for different animal species

Authors :
Holly Kirk
Kylie Soanes
Marco Amati
Sarah Bekessy
Lee Harrison
Kirsten Parris
Cristina Ramalho
Rodney van der Ree
Caragh Threlfall
Publication Year :
2022
Publisher :
Cold Spring Harbor Laboratory, 2022.

Abstract

The application of ecological theory to urban planning is becoming more important as land managers focus on increasing urban biodiversity as a way to improve human welfare. City authorities must decide not only what types of biodiversity-focused infrastructure should be prioritized, but also where new resources should be positioned and existing resources protected or enhanced. Careful spatial planning can contribute to the successful return and conservation of urban nature by maximizing the contribution of green infrastructure to landscape connectivity. By using ecological connectivity theory as a planning tool, governments can quantify the effect of different interventions on the ease with which wildlife can move across the landscape. Here we outline an approach to a) quantify ecological connectivity for different urban wildlife species and b) use this to test different urban planning scenarios using QGIS. We demonstrate four extensions to the work by Deslaurier et al. (2018) and Spanowicz & Jaeger (2019) which improve the application of this method as a planning tool for local government:A step-by-step method for calculating effective mesh size using the open-source software QGIS.Conversion of the effective mesh size value (meff) to a “probability of connectedness” (Pc, for easier interpretation by local government and comparisons between planning scenarios).Guidance for measuring species-specific connectivity, including how to decide what spatial information should be included and which types of species might be most responsive to connectivity planning.Advice for using the method to measure the outcome of different urban planning scenarios on ecological connectivity.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........5dc010bddeca23af64935a7c6de187c7