Landscape structure influences tree density patterns in fragmented woodlands in semi-arid eastern Australia.

Landscape and local-scale influences are important drivers of plant community structure. However, their relative contribution and the degree to which they interact remain unclear. We quantified the extent to which landscape structure, within-patch habitat and their confounding effects determine post-clearing tree densities and composition in agricultural landscapes in eastern subtropical Australia. Landscape structure (incorporating habitat fragmentation and loss) and within-patch (site) features were quantified for 60 remnant patches of Eucalyptus populnea (Myrtaceae) woodland. Tree density and species for three ecological maturity classes (regeneration, early maturity, late maturity) and local site features were assessed in one 100 × 10 m plot per patch. All but one landscape characteristic was determined within a 1.3-km radius of plots; Euclidean nearest neighbour distance was measured inside a 5-km radius. Variation in tree density and composition for each maturity class was partitioned into independent landscape, independent site and joint effects of landscape and site features using redundancy analysis. Independent site effects explained more variation in regeneration density and composition than pure landscape effects; significant predictors were the proportion of early and late maturity trees at a site, rainfall and the associated interaction. Conversely, landscape structure explained greater variation in early and late maturity tree density and composition than site predictors. Area of remnant native vegetation within a landscape and patch characteristics (area, shape, edge contrast) were significant predictors of early maturity tree density. However, 31% of the explained variation in early mature tree differences represented confounding influences of landscape and local variables. We suggest that within-patch characteristics are important in influencing semi-arid woodland tree regeneration. However, independent and confounding effects of landscape structure resulting from previous vegetation clearing may have exerted a greater historical influence on older cohorts and should be accounted for when examining woodland dynamics across a broader range of environments.

Hierarchical Bayesian modelling of plant pest invasions with human-mediated dispersal

Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.