The stability of temporally variable food webs has been relatively well studied empirically. For example, seasonally fluctuating floodplains can have higher fish production than non-fluctuating environments, with maximum production achieved from slow, smoothly rising and falling of floods. Similarly in temperate lakes, seasonally variable temperatures and corresponding species interactions should benefit the secondary production of littoral habitats and mediate the potentially destabilizing effects of nutrient input and high primary production. However, the effect of season on the productivity and stability of food webs has not been fully explored mathematically. Furthermore, the effect of periodicity on this potentially stabilizing phenomenon has not been studied. Here, we aim to develop a general theory that explores how temporal variation (e.g., seasonality, decadal events) and interaction strength structure, at various scales of time and magnitude, influence food web productivity and stability. We do this using food web models with biological attributes of temporal pulsing (e.g., migration, nutrients, foraging), and compare our results to classical food web models without the same structural attributes.
Results/Conclusions
Preliminary results indicate that moderate, periodically forced (e.g., seasonal) food webs have adapted to yield relatively strong high trophic level production. This occurs without an accompanying loss in stability as would tend to occur in classical models with this increased production. However, it appears that too frequent or infrequent signals may have a different effect, and can be destabilizing for the food web. This suggests the notion that seasonal signals aid the overall stability of food webs, but altered temporal variability due to climate change (by either changing the frequency of events or altering the magnitude of signals) may have important consequences for ecosystem resilience.