  We construct two ordinary-differential-equation models of a predator feeding
adaptively on two prey types, and we evaluate the models' ability to fit data
on freshwater plankton. We model the predator's switch from one prey to the
other in two different ways: (1) smooth switching using a hyperbolic tangent
function; and (2) by incorporating a parameter that changes abruptly across the
switching boundary as a system variable that is coupled to the population
dynamics. We conduct linear stability analyses, use approximate Bayesian
computation (ABC) combined with a population Monte Carlo (PMC) method to fit
model parameters, and compare model predictions quantitatively to data for
ciliate predators and their two algal prey groups collected from Lake Constance
on the German--Swiss--Austrian border. We show that the two models fit the data
well when the smooth transition is steep, supporting the simplifying assumption
of a discontinuous prey switching behavior for this scenario. We thus conclude
that prey switching is a possible mechanistic explanation for the observed
ciliate--algae dynamics in Lake Constance in spring, but that these data cannot
distinguish between the details of prey switching that are encoded in these
different models.
