Evidence for Predator-Prey Cycles in a Bark Beetle

The southern pine beetle, Dendroctonus frontalis Zimmermann (Coleoptera: Scolytidae), is an economically important pest of pine forests in the southern United States (Price et al. 1992). This native bark beetle is able to attack and kill living trees, typically loblolly (Pinus taeda L.) or shortleaf (Pinus echinata Mill.) pine, through a process of mass attack coordinated by pheromones emitted by the beetle (Payne 1980). During the attack process, thousands of beetles bore through the outer bark of the tree and begin constructing galleries in the phloem layer. Trees can respond to beetle attack by exuding resin from a network of ducts, but the large number of simultaneous attacks usually overcomes this defense, literally draining the resin from the tree. Oviposition and brood development then occur in the girdled (and ultimately dead) tree. Once a tree is fully colonized the attack process shifts to adjacent trees, often resulting in a cluster of freshly attacked trees, trees containing developing brood, and dead and vacated trees (Coulson 1980). These infestations can range in size from a single tree to tens of thousands, although the latter only occur in areas where no control methods are applied. Approximately six generations can be completed in a year in the southern United States (Ungerer et al. 1999). Like many other forest insect pests, D. frontalis populations are characterized by a considerable degree of fluctuation. The longest time series available are Texas Forest Service records of infestations in southeast Texas since 1958 (figure 5.la). These data suggest that the fluctuations have at least some periodic component, with major outbreaks occurring at intervals of 7-9 years (1968, 1976, 1985, and 1992). A variety of different analyses, including standard time series analysis and response surface methodology (Turchin 1990, Turchin and Taylor 1992), suggest that D.frontalis dynamics are indeed cyclic and appear governed by some kind of delayed negative feedback acting on population growth (see chapter 1). This effect can be seen by plotting the realized per-capita rate of growth (R-values) over a year against population density in the previous year (figure 5.1b).