Data from: Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data

Determining the degree to which predation affects prey abundance in
natural communities constitutes a key goal of ecological research.
Predators can affect prey through both consumptive effects (CEs) and
nonconsumptive effects (NCEs), although the contributions of each
mechanism to the density of prey populations remain largely hypothetical
in most systems. Common statistical methods applied to time series data
cannot elucidate the mechanisms responsible for hypothesized predator
effects on prey density (e.g., differentiate CEs from NCEs), nor provide
parameters for predictive models. State space models (SSMs) applied to
time series data offer a way to meet these goals. Here, we employ SSMs to
assess effects of an invasive predatory zooplankter, Bythotrephes
longimanus, on an important prey species, Daphnia mendotae, in Lake
Michigan. We fit mechanistic models in a SSM framework to seasonal time
series (1994-2012) using a recently developed, maximum likelihood-based
optimization method, iterated filtering, which can overcome challenges in
ecological data (e.g. nonlinearities, measurement error, and irregular
sampling intervals). Our results indicate that B. longimanus strongly
influences D. mendotae dynamics, with mean annual peak densities of B.
longimanus observed in Lake Michigan estimated to cause a 61% reduction in
D. mendotae population growth rate and a 59% reduction in peak biomass
density. Further, the mechanism underlying the B. longimanus effect is
most consistent with an NCE via reduced birth rates. The SSM approach also
provided estimates for key biological parameters (e.g., demographic rates)
and the contribution of dynamic stochasticity and measurement error. Our
study therefore highlights the utility of SSMs to enhance inference for
species interactions from time series data. In particular, our findings
provide evidence derived directly from survey data that the invasive
zooplankter B. longimanus is affecting zooplankton demographics and offer
parameter estimates needed to inform predictive models that explore the
effect of B. longimanus under different scenarios such as climate change.