Guess the impact of Ips typographus – An ecosystem modelling approach for simulating bark beetle outbreaks
Publikation/Tidskrift/Serie: Agricultural and Forest Meteorology
Spruce bark beetle outbreaks are common in Norway spruce forests following windstorm damage, due to ample availability of brood material. The realization of an outbreak depends on factors regulating theIpstypographus population dynamics, such as weather conditions and salvage cutting. In this study, we take an ecosystem modelling approach to analyse the influence of multiple environmental factors on the risk for I. typographus outbreaks. Model calculations ofI. typographus phenology and population dynamics as a function of weather and brood tree availability were developed and implemented in the LPJ-GUESS ecosystem modelling framework. The model simulations were driven by gridded climate data covering Sweden with a spatial resolution of 0.5° and a daily temporal resolution. Records on storm damage and I. typographus outbreak periods in Sweden for the period of 1960–2009 were used for model evaluation, and a sensitivity analysis was performed to examine the model behaviour. The model simulations replicated the observed pattern in outbreak frequency, being more common in southern and central Sweden than in northern Sweden. A warmer climate allowing for more than one generation per year can increase the risk for attacks on living trees. The effect of countermeasures, aiming at either reduce the availability of brood material or theI. typographus population size, is dependent on a non-linear relation between I. typographus attack density and reproductive success. The sensitivity analysis indicated a major reduction in the risk of attacks on living trees by timely salvage cutting and cutting of infested trees. Knowledge uncertainties associated with attacks on standing trees, i.e. factors influencing tree defence capacity and I. typographus reproductive success, should be further addressed.
- Physical Geography
- Forest management
- Climate change
- Risk analysis
- ISSN: 0168-1923