Doctoral Thesis
Integrating species pools, dark diversity and functional trait frameworks to assess vegetation recovery
Doctor of Philosophy (PhD), Murdoch University
DOI:
https://doi.org/10.60867/00000144
Abstract
The species pool concept offers a way to quantify diversity beyond observed species by considering those that could occur in a focal area (the species pool), those absent despite suitable conditions (dark diversity), and how far sites are from their potential diversity (community completeness). Combining this with trait-based approaches can reveal why suitable species tend to be absent (dark diversity affinity; DDA) and the processes shaping communities. Such frameworks can improve restoration outcomes, but their use in practice remains limited and few applicable case studies are available.
This thesis applies species pool- and trait-based methods to evaluate taxonomic and functional recovery in post-mining vegetation to demonstrate how they can inform restoration. Long-term monitoring datasets from three distinct ecosystems are assessed to showcase applicability across different ecological and management contexts.
In recovering jarrah forest, species and functional richness declined over 25 years while dark diversity increased, and community completeness decreased. Topsoil handling, fertilisation and seeding emerged as key site-level drivers of DDA, alongside several life history and nutrient acquisition traits. In recovering kwongan shrublands, multiple processes were found to operate simultaneously across different trait axes to generate fine-scale heterogeneous community patterns, with management practices influencing the composition of available traits. In recovering Nullarbor shrublands and woodlands, taxonomic and functional recovery toward reference targets varied among community types. No measured site characteristics explained DDA, though several traits emerged as drivers of species absences.
Together, these discrete case studies demonstrate how integrating species pool- and trait-based frameworks provide practical indicators of recovery and actionable insights for adaptive restoration, with relevance extending across different ecosystems and management contexts. This work represents one of the first comprehensive applications of taxonomic and functional dark diversity methods in large-scale restoration, highlighting how conceptual ecological tools can advance restoration science and inform evidence-based environmental management.
Details
- Title
- Integrating species pools, dark diversity and functional trait frameworks to assess vegetation recovery
- Authors/Creators
- Johan De Wet Wasserman
- Contributors
- Ladislav Mucina (Supervisor) - Murdoch University, Centre for Terrestrial Ecosystem Science and SustainabilityJames Tsakalos (Supervisor) - Murdoch University, Centre for Terrestrial Ecosystem Science and SustainabilityAlethea Rea (Supervisor) - Murdoch University, School of Mathematics, Statistics, Chemistry and PhysicsMark Dobrowolski (Supervisor) - Murdoch University, Centre for Terrestrial Ecosystem Science and Sustainability
- Awarding Institution
- Murdoch University; Doctor of Philosophy (PhD)
- Identifiers
- 991005904174007891
- Murdoch Affiliation
- Centre for Terrestrial Ecosystem Science and Sustainability; School of Environmental and Conservation Sciences
- Resource Type
- Doctoral Thesis
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