Evaluating consumptive and nonconsumptive predator effects on prey density using field time-series data.

Area of Science:

• Ecology
• Aquatic Ecology
• Invasive Species Research

Background:

• Predation impacts prey abundance through consumptive (CEs) and nonconsumptive effects (NCEs).
• Distinguishing CEs from NCEs and quantifying their effects on prey populations is challenging with traditional time-series methods.
• Predictive models require accurate parameter estimates of predator-prey dynamics.

Purpose of the Study:

• To quantify the impact of the invasive predator Bythotrephes longimanus on the prey Daphnia mendotae in Lake Michigan.
• To differentiate between consumptive and nonconsumptive effects of B. longimanus on D. mendotae population dynamics.
• To utilize state-space models (SSMs) for robust analysis of ecological time-series data and parameter estimation.

Main Methods:

• Employed state-space models (SSMs) to analyze seasonal time-series data (1994-2012) of B. longimanus and D. mendotae in Lake Michigan.
• Utilized iterated filtering, a maximum-likelihood-based optimization method, to fit mechanistic models within the SSM framework.
• Accounted for ecological data challenges including nonlinearities, measurement error, and irregular sampling intervals.

Main Results:

• Bythotrephes longimanus significantly impacts Daphnia mendotae population dynamics.
• Estimated a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density due to B. longimanus.
• The observed effects are most consistent with nonconsumptive effects, specifically reduced birth rates.

Conclusions:

• State-space models provide a powerful tool for elucidating predator-prey mechanisms and estimating demographic parameters from survey data.
• Invasive B. longimanus exerts substantial control over D. mendotae populations in Lake Michigan, primarily via NCEs.
• Parameter estimates from this study can inform predictive models assessing future impacts under scenarios like climate change.