Validation of a spatial simulation model of a spreading alien plant population.
Abstract
In this paper we describe the process of parameterizing and validating a spatial demographic model of a spreading alien plant population. The model, a spatially explicit individual-based simulation, has modest data requirements (for a spatial simulation model) in that it concentrates on simulating recruitment, dispersal, mortality and disturbance and ignores the environmental and biotic heterogeneity of the receiving environment. We tested the model using the invasion of Acacia cyclops and Pinus pinaster into fynbos, the mediterranean shrublands of South Africa, as a case study. Dispersal, recruitment and mortality data were collected for each species at six different sites. Aerial photographs from six independent sites (two sites for A. cyclops and four sites for P. pinaster) were used to reconstruct the invasion histories of the two species between 1938 and 1989. Demographic data were used to parameterize the model, and the 1938 distribution of alien plants, derived from aerial photography, was used to initialize the model. The empirically estimated indices of rate and pattern of invasion fell within the range of model predictions made at all six sites studied. The indices of rate and pattern of invasion predicted by the model did not differ significantly from the empirically estimated indices for 76% of the model data comparisons made. These analyses suggested that the model predictions are good, given the variance in parameter estimates. The proportion of grid locations where the model correctly predicted alien plant distribution was typically above 0.75 and always above 0.5 for both species. A permutation test showed that locations of invasive plants predicted by the model were significantly better than random for P. pinaster, but not always for A. cyclops; this may be because A. cyclops is bird dispersed, and its dispersal may be biased towards perch sites, whereas P. pinaster is wind dispersed. Although spatial simulation models are often more difficult to parameterize and validate than statistical or analytical models, there are situations where such effort is warranted. In this case, the validation process provides confidence to use the model as a tool for planning the control of invasive plants. In a more general sense, we believe that the approach outlined here could be used for model parameterization and validation in situations where spatial simulation models seem appropriate.