Modelling the dynamics of white cypress pine Callitris glaucophylla woodlands in inland south-eastern Australia

• Published in: Ecological modelling Vol. 211; no. 1; pp. 11 - 24
• Main Authors: Ross, Karen A., Bedward, Michael, Ellis, Murray V., Deane, Andrew, Simpson, Christopher C., Bradstock, Ross A.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 24.02.2008; Elsevier
• Subjects: Animal, plant and microbial ecology; Biological and medical sciences; Callitris; Callitris glaucophylla; Cupressus; Density-dependence; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Methods and techniques (sampling, tagging, trapping, modelling...); Simulation model; Site productivity; Stand processes; Thinning; Woodland dynamics; Australia; Oceania; South Australia; Site productivity; Stand processes; Woodland dynamics; Thinning; Callitris; Simulation model; Density-dependence; Productivity; Modeling; Woodland; Dynamics; Softwood forest tree; Density dependence
• ISSN: 0304-3800; 1872-7026
• DOI: 10.1016/j.ecolmodel.2007.08.012

White cypress pine Callitris glaucophylla is an important native tree widespread in heavily cleared savanna woodlands of the south-east Australian wheat-sheep belt. C. glaucophylla woodlands have been the focus of vigorous debate regarding their structure and dynamics during Aboriginal times and following European settlement, and the causes of structural changes are poorly understood. Management of contemporary woodland remnants is therefore controversial, and has so far lacked a predictive, process-based approach. We sought to determine whether a simple process model with recruitment, growth and survival mediated by rainfall and competition, could accurately simulate medium-term dynamics of C. glaucophylla woodlands in which fire has typically been excluded. Model parameters were optimised using reference data from 6- to 36-year silvicultural trials in central-western New South Wales (NSW). Predictions of the calibrated model compared favourably to actual growth, survival and recruitment of C. glaucophylla in the reference data, as well as in an independent dataset not used in optimisation. We tested whether remaining differences between predictions and actual data were related to variation in site productivity (a function of moisture availability as influenced by soil and landscape factors not modelled). Growth was overestimated in low-productivity sites and underestimated in high-productivity sites. Growth predictions were improved by using site-specific expected maximum heights to reflect site productivity. We also tested whether the model and parameter set produce dynamics consistent with those observed over the last half century. Modelled growth, survival, recruitment and competition processes were consistent with data and observations in previous studies on historical dynamics and stand behaviour of C. glaucophylla. The model has a wide range of potential applications for understanding past and predicting future stand dynamics. To illustrate an application of the model to thinning, a strategy currently being implemented to manage tree densities in inland NSW, we compared predicted stand structures in simulations of different thinning treatments. The simulations showed that without careful manipulation of existing canopy cover, stands can re-fill to pre-thinning densities within relatively short periods of time.