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Cold hardiness of Lymantria monacha and L. dispar (Lepidoptera: Erebidae) eggs to extreme winter temperatures: implications for predicting climate change impacts

Fält‐Nardmann, Julia J. J., Ruohomäki, Kai, Tikkanen, Olli‐Pekka, Neuvonen, Seppo
Ecological entomology 2018 v.43 no.4 pp. 422-430
Erebidae, Lymantria dispar, Lymantria monacha, climate change, cold, cold tolerance, eggs, forest pests, mortality, overwintering, prediction, supercooling point, temperature, winter, Finland, Germany
1. It has been predicted that temperature increases of 3.6–5.8 °C would shift the northern distribution limit of Lymantria monacha (Linnaeus) and Lymantria dispar (Linnaeus) by 500–700 km, but these predictions ignore the effects of minimum winter temperatures. It was hypothesised that winter cold can limit range expansion due to high egg mortality in cold temperatures. 2. The present study determined the supercooling points of overwintering eggs of these forest pests, and compared these with recent minimum winter temperatures in the areas of origin of three populations. Eggs from one L. monacha and one L. dispar population from the species' core distribution area in Germany were included, as well as L. monacha eggs from Finland, near the northern border of the species' distribution. 3. The median supercooling points of both species were more than 10 °C lower than the median minimum winter temperatures of their areas of origin, and the median supercooling points of Finnish and German L. monacha eggs did not differ significantly. The median supercooling point of German L. monacha eggs differed from that of German L. dispar eggs. 4. Previous literature on the topic is referenced, and translations of the old German and Russian sources are given. Based on these results, it is argued that the frequent claim that L. monacha eggs can survive cold down to −40 °C is unsupported, with a value near −30 °C being a more likely limit. 5. Winter cold alone can limit the predicted range shifts of these species to 200–300 km under 3.6–5.8 °C increase scenarios, which is less than half the value of earlier estimates.