Biodiversity and Conservation

, Volume 21, Issue 7, pp 1627–1650 | Cite as

Combining community-level spatial modelling and expert knowledge to inform climate adaptation in temperate grassy eucalypt woodlands and related grasslands

  • Suzanne M. Prober
  • D. W. Hilbert
  • S. Ferrier
  • M. Dunlop
  • D. Gobbett
Original Paper


Many studies predict effects of future climate scenarios on species distributions, but few predict impacts on landscapes or ecological communities, the scales most relevant to conservation management. We combined expert knowledge with community-level spatial modelling (using artificial neural networks, ANN, and generalised dissimilarity modelling, GDM) to inform climate adaptation management in widespread but highly threatened temperate grassy ecosystems (TGE) of Australian agricultural landscapes. GDM predicted high levels of ‘biotically-scaled environmental stress’ (scaled in terms of potential change in species composition of communities) for plants, reptiles and snails within the TGE under medium, and especially high, 2070 climate scenarios. Predicted stress was lower for birds, mammals and frogs, possibly owing to generally wider species distributions, but these models do not account for changing habitat characteristics. ANN predicted environments within the current TGE biome will become increasingly favourable for formations such as chenopod shrublands, Casuarina L. forests and Callitris Vent. forests by 2070, although classification error for eucalypt woodland in current climates was high. Expert knowledge and GDM suggest these predictions may be mediated by attributes such as environmental heterogeneity that confer resilience, but GDM confirms that widespread degradation has greatly compromised the capacity of TGE to adapt to change. Based on model predictions and expert knowledge we discuss five potential climate change outcomes for TGE: decreasing fire frequency, structural change, altered functional composition, exotic invasion, and cascading changes in ecological interactions. Although significant ecological change in TGE is likely, it is feasible to ameliorate non-climatic limits to adaptation and promote reassembly by native rather than exotic species. Current conservation efforts already target similar goals, and reinforcing and adjusting these approaches offer the highest priority, lowest risk climate adaptation options. We conclude that despite high uncertainties, combining community-level modelling with expert knowledge can guide climate adaptation management.


Artificial neural networks Climate change Community-level modelling Global warming Generalized dissimilarity modelling Savannah 



Artificial neural network


Generalised dissimilarity modelling


Major vegetation sub-group (DEWR 2007)


Major vegetation group (DEWR 2007)


National Vegetation Information System (DEWR 2007)


Temperate grassy ecosystems; pertaining to eucalypt woodlands and related grasslands in south-eastern Australia


Atmospheric CO2



We thank Cameron Fletcher, Tom Harwood, Kristin Williams and Georg Wiehl (CSIRO) for modelling and GIS support, Janet Stein (Australian National University) for providing environmental data for modelling, and Alan House, Adam Liedloff, Anita Smyth, Tara Martin and Helen Murphy (CSIRO) for comments and discussion. Financial support was provided by the Department of Environment, Water, Heritage and Arts, and the CSIRO Climate Adaptation Flagship. We are grateful for the valuable input provided by workshop attendees: Greg Baines (Department of Territory and Municipal Services, ACT), Justin Billings (Department of Environment, Water, Heritage and Arts), Ross Bradstock (University of Wollongong), Kerry Bridle (CSIRO/University of Tasmania), Sue Briggs (Department of Environment and Climate Change, NSW), Don Butler (Macquarie University, Environment Protection Authority, Qld), Oberon Carter (Department of Primary Industries, Parks, Water and Environment, Tasmania), Saul Cunningham (CSIRO), Liz Dovey (Department of Climate Change), Angela Duffy (Department of Environment and Heritage, SA), Louise Gilfedder (Department of Primary Industries, Parks, Water and Environment, Tasmania), David Keith (Department of Environment and Climate Change, NSW), Ian Lunt (Charles Sturt University), Sue McIntyre (CSIRO), Tim Milne (Nature Conservation Society, SA), Karel Mokany (CSIRO), Jim Radford (Australian Bush Heritage), Rainer Rehwinkel (National Parks and Wildlife Service, NSW), Vivienne Turner (Arthur Rylah Institute for Environmental Research), Kristen Williams (CSIRO).

Supplementary material

10531_2012_268_MOESM1_ESM.pdf (62 kb)
Supplementary material 1 (PDF 63 kb)


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Copyright information

© © CSIRO 2012 2012

Authors and Affiliations

  • Suzanne M. Prober
    • 1
  • D. W. Hilbert
    • 2
  • S. Ferrier
    • 3
  • M. Dunlop
    • 3
  • D. Gobbett
    • 4
  1. 1.CSIRO Ecosystem SciencesWembleyAustralia
  2. 2.CSIRO Ecosystem SciencesAthertonAustralia
  3. 3.CSIRO Ecosystem SciencesCanberraAustralia
  4. 4.CSIRO Ecosystem SciencesGlen OsmondAustralia

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