Modelling the consequence of glacier retreat on mixotrophic nanoflagellate bacterivory: a Bayesian approach

Abstract

Mixotrophic nanoflagellate bacterivory is affected by light; however, in glacially influenced lakes, glacial clay may also interfere with prey uptake. Mechanistic models based on prior quantitative hypotheses and tested with field data are useful for predicting these predator–prey interactions under a changing climate. We modelled the effect of glacial particles on the bacterivory of mixotrophic nanoflagellates, the dominant phytoplankton in mountain lakes in the North Patagonian Andes. Our model equation is based on the classical Michaelis–Menten formulation and Platt's photosynthesis–irradiance curve to account for the interference by glacial particles and the effect of light intensity, respectively. Bayesian inference was applied to estimate model parameters using data from field bacterivory experiments. Light experiments (LE) were performed in lakes with different levels of light penetration without clay particles, while clay experiments (CE) were performed with an experimental gradient of glacial clay concentration at constant light intensity. The LE showed a non‐monotonic effect of light intensity and the CE revealed an exponential negative effect of clay concentration. The obtained model was tested with two independent experiments carried out in a turbid proglacial lake. Our proposed mechanistic model successfully predicted the combined effect of light availability and particle interference on the mixotrophic nanoflagellate–bacteria relationship. The model demonstrated that the effect of light is dampened as clay concentration increases.