Modeling flight activity and population dynamics of the pine engraver, Ips pini, in the Great Lakes region: effects of weather and predators over short time scales

Abstract

Ascertaining the relative effects of factors such as weather and predation on population dynamics, and determining the time scales on which they operate, is important to our understanding of basic ecology and pest management. In this study, we sampled the pine engraver Ips pini (Say) (Coleoptera: Scolytidae) and its predominant predators Thanasimus dubius (F.) (Coleoptera: Cleridae) and Platysoma cylindrica (Paykull) (Coleoptera: Histeridae) in red pine plantations in Wisconsin, USA, over 2 years. We sampled both the prey and predators using flight traps baited with the synthetic aggregation pheromone of I. pini. Flight models were constructed using weather variables (temperature and precipitation), counts of bark beetles and their predators, and temporal variables to incorporate possible effects of seasonality. The number of I. pini per weekly collection period was temperature dependent and decreased with the number of predators, specifically T. dubius in 2001 and P. cylindrica in 2002. The number of predators captured each week was also weather dependent. The predators had similar seasonal phenologies, and the number of each predator species was positively correlated with the other. Including a term for the number of prey did not improve the model fits for either predator for either year. Our results suggest that exogenous weather factors strongly affect the flight activity of I. pini, but that its abundance is also affected by direct density‐dependent processes acting over weekly time scales. Adult predation during both colonization and dispersal are likely processes yielding these dynamics.

Daily activity and flight behaviour of adults of Capnodis tenebrionis (Coleoptera: Buprestidae)

“…Temperature is also important in determining the flight activity of Ips pines (Say) (Coleoptera: Scolytidae). Indeed, the number of Ips pines collected weekly is temperaturedependent (Aukema et al, 2005), and in spring in Anthonomus pomorum flight activity of overwintered weevils is also temperature dependent (Duan et al, 1998). Obviously other factors, affect the flight activity of C. tenebrionis, and as in Lobesia botrana Den.…”

Assessing forest vulnerability and the potential distribution of pine beetles under current and future climate scenarios in the Interior West of the US

“…For example, several studies on Ips engravers (Ips spp.) have demonstrated that colder temperatures disrupt egg development (Jonsson et al, 2009) and synchronized flight activities (Aukema et al, 2005), while extended winters reduce the number of successful broods in a given year (Anderbrant, 1989). Similar studies on mountain pine beetles have found that cold temperatures cause significant mortality for emerging adults in the spring (Amman, 1973) and late larval stages in early fall and late winter (Carrol and Safranyik, 2004).…”

“…Other studies suggest that infestations are a function of more complex abiotic and biotic relationships between bark beetles and their hosts. These include reproductive and dispersal opportunities for bark beetles (Aukema et al, 2005;Roberston et al, 2009), transport and infection by fungi and other pathogens (Adams et al, 2008;Bleiker et al, 2009), predation and competition of bark beetles Schlyter and Anderbrant, 1993), fire (Breece et al, 2008;Fettig et al, 2008), and management practices (Waring and Pitman, 1985;Hayes et al, 2008). Although the results of these studies help us better understand local dynamics between bark beetles and their hosts, they are difficult to apply across large spatial or temporal scales.…”

Predisposition to bark beetle attack by root herbivores and associated pathogens: Roles in forest decline, gap formation, and persistence of endemic bark beetle populations

“…Values included temperature minimum, maximum, and means, as well as measures of precipitation. Six different seasons were defined depending on known phenologies of the system (e.g., when Ips begin flying or when drought stress begins to accumulate; Aukema et al, 2005). For each of these seasons, summary weather variables were created such as total precipitation, number of days with no rain, average and maximum temperatures, and heating days (sum of the daily maximum temperatures).…”