Reconstructing pre-impact vegetation cover in modified landscapes using environmental modelling, historical surveys and remnant vegetation data: a case study in the Fleurieu Peninsula, South Australia
Article first published online: 14 APR 2004
Journal of Biogeography
Volume 31, Issue 5, pages 787–805, May 2004
How to Cite
Bickford, S. and Mackey, B. (2004), Reconstructing pre-impact vegetation cover in modified landscapes using environmental modelling, historical surveys and remnant vegetation data: a case study in the Fleurieu Peninsula, South Australia. Journal of Biogeography, 31: 787–805. doi: 10.1111/j.1365-2699.2003.01050.x
- Issue published online: 14 APR 2004
- Article first published online: 14 APR 2004
- Pre-impact vegetation;
- surveyors’ records;
- remnant vegetation;
- vegetation reconstruction;
- vegetation modelling;
- historical ecology
Aim To investigate the application of environmental modelling to reconstructive mapping of pre-impact vegetation using historical survey records and remnant vegetation data.
Location The higher elevation regions of the Fleurieu Peninsula region in South Australia were selected as a case study. The Fleurieu Peninsula is an area typical of many agricultural regions in temperate Australia that have undergone massive environmental transformation since European settlement. Around 9% of the present land cover is remnant vegetation and historical survey records from the ad 1880s exist. It is a region with strong gradients in climate and topography.
Methods Records of pre-impact vegetation distribution made in surveyors’ field notebooks were transcribed into a geographical information system and the spatial and classificatory accuracy of these records was assessed. Maps of remnant vegetation distribution were obtained. Analysis was undertaken to quantify the environmental domains of historical survey record and remnant vegetation data to selected meso-scaled climatic parameters and topo-scaled terrain-related indices at a 20 m resolution. An exploratory analytical procedure was used to quantify the probability of occurrence of vegetation types in environmental domains. Probability models spatially extended to geographical space produce maps of the probability of occurrence of vegetation types. Individual probability maps were combined to produce a pre-impact vegetation map of the region.
Results Surveyors’ field notebook records provide reliable information that is accurately locatable to levels of resolution such that the vegetation data can be spatially correlated with environmental variables generated on 20 m resolution environmental data sets. Historical survey records of vegetation were weakly correlated with the topo-scaled environmental variables but were correlated with meso-scaled climate. Remnant vegetation records similarly not only correlated to climate but also displayed stronger relationships with the topo-scaled environmental variables, particularly slope.
Main conclusions A major conclusion of this study is that multiple sources of evidence are required to reconstruct past vegetation patterns in heavily transformed region. Neither the remnant vegetation data nor historical survey records provided adequate data sets on their own to reconstruct the pre-impact vegetation of the Fleurieu Peninsula. Multiple sources of evidence provide the only means of assessing the environmental and historical representativeness of data sets. The spatial distribution of historical survey records was more environmentally representative than remnant vegetation data, which reflect biases due to land clearance. Historical survey records were also shown to be classificatory and spatially accurate, thus are suitable for quantitative spatial analyses. Analysis of different spatial vegetation data sets in an environmental modelling framework provided a rigorous means of assessing and comparing respective data sets as well as mapping their predicted distributions based on quantitative correlations. The method could be usefully applied to other regions where predictions of pre-impact vegetation cover are required.