4.0 Article

Using prioritisation tools to strategically restore vegetation communities in fragmented agricultural landscapes

Journal

ECOLOGICAL MANAGEMENT & RESTORATION
Volume 18, Issue 1, Pages 45-53

Publisher

WILEY-BLACKWELL
DOI: 10.1111/emr.12224

Keywords

habitat restoration; Marxan; modeling; revegetation; strategic; woodland

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Restoring native habitats in heavily cleared and fragmented areas such as agricultural landscapes is important to maintain and increase remaining native floral and faunal communities. Identifying priority vegetation types for restoration - as well as the parcels of land where this restoration could take place at a landscape scale - may assist in strategically protecting these biodiversity assets. To prioritise the restoration of terrestrial habitats around an ecologically and culturally significant Ramsar-listed wetland in South Australia, we used the spatial prioritisation tool Marxan. Originally designed for prioritising the protection of reserve areas, Marxan can also be used to identify parcels of land for restoration purposes. We tested how Marxan prioritised the restoration of four distinct vegetation types around the Coorong and Lower Lakes region of South Australia using the inverse of habitat remnancy as a cost and soil type and distance to ecologically significant bird species as a conservation feature. By prioritising restoration activities around certain landscape features, such as remnant areas, our results indicate that we would be able to strategically restore parcels of native habitat that would maximise biodiversity outcomes. This study highlights the need for robust input data, such as priority vegetation types and bird species associated with these habitats, to ensure informative modelling outputs. It also suggests that other measures, such as the cost of different land types, should be included in future restoration planning. Finally, we illustrate how prioritisation tools such as Marxan can be used by natural resource managers to restore areas within fragmented agricultural landscapes.

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