Integrating forest soils information across scales: spatial prediction of soil properties under Australian forests

Quantitative spatial predictions of forest soil properties and land qualiti es can be produced using field measurements of soil layer and site properti es as response variables and the more readily available spatial environment al explanatory variables derived from digital elevation models (DEM), terra in analysis, digital climatic surfaces, and geophysical and multi-spectral remote sensing. The two sets of measurements have contrasting scales, or ge ometric support, and this raises a number of methodological issues. Use of environmental correlation for predicting soil distribution is most e ffective when an a priori pedogenic model is proposed for a region. This mo del is used to design the sampling strategy and evaluate the adequacy of av ailable soil data. Geographic positioning systems (GPS) enable accurate loc ation of field samples and correct registration with environmental coverage s (e.g. DEM, remote sensing, etc.). Field measurement should focus on fores t soil processes or land qualities that affect forest productivity and mana gement such as soil physical and chemical fertility. The final modelling ph ase extends the Limited point information to the landscape level by develop ing statistical models. A major challenge in environmental correlation modelling is to generate spa tial measures of the critical environment factors affecting soil developmen t. A second major consideration is the varying scales of process, observati on and prediction. Robust prediction requires consideration of at least thr ee levels of organisation. First is the level in question (e.g. catena); se cond is the level below which provides an insight into mechanisms (e.g. ped on); and third is the level above which provides context and significance ( e.g. watershed). Predictive relationships developed at one level may not be useful for prediction at more than one level removed. Digital elevation models provide the basis for spatial representations of t opography, climate and, thus, the majority of available environmental cover ages. The resolution of these surfaces is often coarser than that of actual soil measurement creating an inequality in scale. Causal processes control ling soil formation may not have clear surface expression in ancient landsc apes or where endogenous soil forming processes dominate; thus limiting the use of land-surface morphometry. Geophysical remote sensing is currently t he only means of obtaining comprehensive, subsurface geological information . Results from two quantitative forest soil surveys at different scales in ea stern Australia are presented. The Bago-Maragle study covers a 50,000 ha ar ea of sub-alpine eucalypt forest of southern New South Wales. The second su rvey is at a finer scale, covering two native eucalypt catchments in a gran itic landscape in south-eastern NSW. Statistical models are presented with the soil and site properties as the response variables and the various spat ial environmental coverages as the explanatory variables. (C) 2000 Elsevier Science B.V. All rights reserved.