Abstract
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.
| Original language | English |
|---|---|
| Article number | 101989 |
| Pages (from-to) | 1-12 |
| Number of pages | 12 |
| Journal | MethodsX |
| Volume | 10 |
| Early online date | 4 Jan 2023 |
| DOIs | |
| Publication status | Published - 2023 |
| Externally published | Yes |
Bibliographical note
Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- Applied ecology
- Biodiversity conservation
- Nature in the city
- Urban planning
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