An examination was undertaken of the literature and restoration cases for 4 major Australian vegetation types (sclerophyll; rainforest; grassland; and wetland) to explore the proposition that ecological resilience may govern recovery after anthropogenic damage, and/or provide a fundamental guide and measure of success for ecological restoration. Also, primary data were collected from highly degraded sites (5 sclerophyll, 3 rainforest, and 4 grassy sites) to assess recovery after restoration treatment. These were supplemented with questionnaire data from practitioners working at a wider range of rainforest and sclerophyll sites, and reports from practitioners working on grassland and wetland sites. In all 4 vegetation types, species generally fell into two main groups : longer-lived 'resprouters' and shorter-lived 'obligate seeders'. But different resilience models were identified for the 4 vegetation types. The sclerophyll type exhibited higher in situ resilience but lower migratory resilience than the rainforest type, which was facilitated by flying frugivore dispersal to perch trees. Self-perpetuation was more tightly coupled with disturbance in the sclerophyll, grassland and wetland types than rainforest; and therefore 'designed disturbance' played a more obvious role in enhancing recovery within these types, than in rainforest. Results suggest that resilience (as both an ecosystem property and a theoretical concept) is fundamental to the practice of ecological restoration. Some prediction of resilience potential of particular degraded sites (and prediction of the degree and type of restoration subsidy needed) can be based on knowledge of : individual species' recovery mechanisms; resilience models for individual vegetation-types; and the site's colonisation potential and impact history / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:ADTP/235691 |
| Date | January 1996 |
| Creators | McDonald, M. Christine, University of Western Sydney, Hawkesbury, Faculty of Agriculture and Horticulture |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Source | THESIS_FAH_HOR_McDonald_M.xml |
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