Pine invasions are becoming increasingly widespread and problematic in the Southern Hemisphere. Pines can reduce soil organic matter and microbial biomass, decrease native biodiversity, and alter fire and hydrological regimes. Pinus contorta (lodgepole pine), one of the most invasive species of pines, has been planted extensively in the Chilean Patagonia and has recently begun to escape plantations. The effect of microsite on P. contorta establishment in Chile has been investigated but information concerning factors determining large scale patterns of invasion is lacking. To examine the drivers of P. contorta invasion, 10 m wide belt transects were established perpendicular to the plantation edge extending into non-invaded areas. Within the transects basal diameter, number of cones, and presence of herbivory were recorded for all P. contorta individuals. An age-diameter relationship was constructed and ages of all measured trees were calculated to determine spread rate and age structure.
Results/Conclusions
P. contorta has spread at a mean rate of 62.5 m/yr. The spread has not been constant. For the first five years of invasion the rate averaged 22.4 m/yr. The subsequent five years had a similar spread rate but between the two periods there was one year of rapid spread (327.0 m/yr). Another jump in spread was seen seven years later. The timing of the episodic spread coincides with approximate time to reproduction for the trees in the invasion front (5-7 years). A probability of occurrence map for P. contorta was constructed. Slope, aspect, elevation, distance to plantation, and vegetation cover type all contributed significantly to predicting P. contorta occurrence. Probability of occurrence decreased with distance from the plantation. Areas covered with native Nothofagus antarctica or N. pumilio forests were significantly less likely to be invaded than areas occupied by steppe vegetation. The probability of occurrence was highest on western facing slopes. A simulation model to project invasions into the future was created using probability of occurrence combined with data on population dynamics and dispersal. Information on where invasions are likely to occur and what factors drive the invasions will help determine the ultimate impact of P. contorta invasions on indigenous ecosystems.