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Ecological connectivity as a planning tool for the conservation of wildlife in cities

journal contribution
posted on 2024-11-02, 23:14 authored by Holly Kirk, Kylie Soanes, Marco AmatiMarco Amati, Sarah BekessySarah Bekessy, Lee Harrison, Kirsten Parris, Cristina Ramalho, Rodney Van de Ree, Caragh Threlfall
The application of ecological theory in urban planning is becoming more important as land managers focus on increasing biodiversity to improve human welfare in cities. 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. Measuring the contribution of green infrastructure to landscape connectivity can maximise the successful return and conservation of urban nature. By using ecological connectivity theory as a planning tool, the effect of different interventions (both positive and negative) on the ease with which wildlife can move across the landscape can be compared. 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 extensions which improve the application of this method as a planning tool: • 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). • An approach 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. • Guidance for using the method to compare different urban planning scenarios.

History

Journal

MethodsX

Volume

10

Number

101989

Start page

1

End page

12

Total pages

12

Publisher

Elsevier

Place published

Netherlands

Language

English

Copyright

© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Former Identifier

2006120828

Esploro creation date

2023-04-06

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