The role of timing in the heat shock effects on a prey-predator system
How abiotic factors affect individual species is now a well-studied topic, but their effects on interacting species can be harder to determine. In prey-predator systems, for example, an altered abiotic factor can affect both species directly, while also affecting how they interact with each other. Moreover, if the abiotic effects and species interactions are not constant through time, but instead have discrete events, the timing of abiotic effects and species interactions may become important. One such discrete abiotic effect associated with climate change is the increase of heat shocks (short-term large increases in temperature). This study investigates the role of timing in relation to how those heat shocks affect a prey-predator system. Using a controlled environment, we tested how the timing of a heat shock (increase temperature from 26C to 38C for 4 hours) affects successful attack and reproduction of a parasitoid wasp (Aphidius ervi) attacking its host, the pea aphid (Acyrthosiphon pisum). We tested three time treatments: 1) heat shock before wasp lays eggs within hosts, 2) heat shock while the wasp is foraging, and 3) heat shock after the wasp has attacked hosts. Our response variable is the successful production of new wasps in the pupal stage (mummies).
Our results showed that the heat shock had the largest effect when it occurred while wasps were actively foraging; a heat shock during this time resulted in very few new wasps. When heat shocks were applied 3 days before or after the foraging, mummy production was only slightly lower than the control treatments where everything was kept at a constant temperature. These results show the potential importance of timing when considering the effects of an altered abiotic factor, especially when considering relatively discrete events. This may change how we see and studied this relations in the past, adding another factor that should be taken into account. Moreover, this could have great importance when modelling and predicting the effects of abiotic factors through time.