Understanding consumptive (CE) and non-consumptive effects (NCE) of predators on prey in natural systems is a challenge. Many studies have approached this challenge by using results of laboratory experiments (e.g. on predation rates or behavior) to parameterize dynamical models. Confounding factors (e.g., seasonality and spatial structure) present in the field, together with measurement/process error can limit the extent of such inferences. Here we applied a state-space model with spatial structure to 16-year field data (1994-2003, 2007-2012), as a complementary approach, to understanding the influences of a predator, Bythotrephes longimanus, on an important zooplankton species, Daphnia mendotae, in Lake Michigan. Through this approach, we used time-series data to estimate parameters of a dynamic model including the magnitude of process and measurement error. Our previous work showed that Bythotrephes influences Daphnia dynamics. Here we explore mechanisms that drive the effects of Bythotrephes on Daphnia. Specifically, our goals are to: 1) evaluate if the Bythotrephes effect is due to CE or NCE, 2) evaluate if, and to what extent, temperature influences CE and NCE; 3) estimate if and how temperature affects the seasonality of Daphnia dynamics; 4) explore the utility of state-space models via iterated filtering for addressing this type of problem.
Results/Conclusions
Our results showed that physical factors and Bythotrephes abundance as well as both process and measurement errors influenced observed Daphnia dynamics. We estimated that that temperature differences between the surface and deeper level of the lake had a large influence on the NCE of Bythotrephes on the biomass density of Daphnia during the migration process of Daphnia from the surface to the deeper lake. Temperature also largely explains the Daphnia seasonality (and variation in it) among the 16 years in Lake Michigan. Including spatial structure in the state-space model allowed us to differentiate and estimate the influences of multiple factors including physical factors (e.g., temperature) and predation (e.g., NCE and CE) on the zooplankton production in a Great Lakes system. Our study demonstrates that temperature largely influences the NCE and plays an important role in shaping zooplankton production. This suggests potential influences of climate change on Great Lake systems, which may be a future direction for this work.