Cold winters drive consistent and spatially synchronous 8-year population cycles of cabbage stem flea beetle.

Abstract

Population cycles have been observed in mammals as well as insects, but consistent population cycling has rarely been documented in agroecosystems and never for a beetle. We analysed the long-term population patterns of the cabbage stem flea beetle Psylliodes chrysocephala in winter oilseed rape over 50 years. Psylliodes chrysocephala larval density from 3045 winter oilseed rape fields in southern Sweden showed strong 8-year population cycles in regional mean density. Fluctuations in larval density were synchronous over time across five subregional populations. Subregional mean environmental variables explained 90.6% of the synchrony in P. chrysocephala populations at the 7-11year time-scale. The number of days below -10°C showed strong anti-phase coherence with larval densities in the 7-11year time-scale, such that more cold days resulted in low larval densities. High levels of the North Atlantic Oscillation weather system are coherent and anti-phase with cold weather in Scania, Sweden. At the field-scale, later crop planting date and more cold winter days were associated with decreased overwintering larval density. Warmer autumn temperatures, resulting in greater larval accumulated degree days early in the season, increased overwintering larval density. Despite variation in environmental conditions and crop management, 8-yearcycles persisted for cabbage stem flea beetle throughout the 50 years of data collection. Moran effects, influenced by the North Atlantic Oscillation weather patterns, are the primary drivers of this cycle and synchronicity. Insect pest data collected in commercial agriculture fields is an abundant source of long-term data. We show that an agricultural pest can have the same periodic population cycles observed in perennial and unmanaged ecosystems. This unexpected finding has implications for sustainable pest management in agriculture and shows the value of long-term pest monitoring projects as an additional source of time-series data to untangle the drivers of population cycles.