Do temperature–food interactions matter? Responses of production and its components in the model heterotrophic flagellate Oxyrrhis marina

Abstract

The consequence of interactions between temperature and food concentration for protistan population dynamics and estimates of aquatic productivity are relatively unknown, primarily because we lack adequate parameters for models. Here, using the heterotrophic flagellate Oxyrrhis marina Dujardin, we demonstrate the importance of considering temperature and food concentration in combination, to determine the responses of grazing rate, specific growth rate, cell volume, specific production and yield. Specific growth rate and cell volume responded in different ways to temperature-food concentrations: prey concentration had greatest positive effects on specific growth rate with increasing temperature, and prey concentration had greatest positive effects on cell volume with decreasing temperature. The effect of these contrasting interactions on specific production (= specific growth rate × cell carbon) was a greater response to prey concentration at intermediate temperatures.We also observed that the threshold food concentration for growth increased with increasing temperature, but yield showed no clear thermal response. By applying iterative curve-fitting to data obtained from multiple temperature-food concentration combinations, we produced phenomenological models of grazing rate, specific growth rate, and cell volume. We then compared predictions from a simple predator-prey simulation model that applied either our derived equations or a single exponential (Q 10 ) relationship to the specific growth and ingestion responses at 20°C. Considerable differences in predator and prey abundance were obtained between the 2 models. Our results demonstrate the potentially complex effects of food and temperature in combination on production parameters, and we argue that these should be considered in aquatic ecosystem simulation models.

Strain-specific functional and numerical responses are required to evaluate impacts on predator–prey dynamics

“…This supports the conclusions of Kimmance et al (2006) who indicated, also using O. marina, that temperaturedependent gross growth efficiency has non-intuitive interactions with prey abundance. Consequently, we strongly recommend that modelling efforts on population dynamics of microbial eukaryotes, at the very least, consider variable assimilation efficiency and that laboratory studies should be directed at parameterising such responses.…”

“…It may seem that the scatter of our data is high, but it is typical for estimates of functional and numerical responses of protozoa (for example, Kimmance et al, 2006), and by performing many measurements across the prey range, especially with a focus on lower prey abundances, it is possible to obtain powerful, average estimates of parameters associated with the functional and numerical responses (Montagnes and Berges, 2004). Following this procedure, we have established functional and numerical responses that reveal significant differences in their parameters (Figure 3).…”

“…Rarely is it recognised that functional and numerical responses can qualitatively differ in shape, reflecting a variable conversion efficiency with food concentration (for a detailed microbial-based review and analysis of this see Fenton et al, 2010). Further complicating the situation, models rarely appreciate that both functional and numerical responses can be uniquely altered by external factors (for example, temperature: Kimmance et al, 2006;Montagnes et al, 2008).…”

“…All cultures were maintained for 24 h at each temperature, after which prey and O. marina numbers were determined. Ingestion rate of O. marina (prey predator À 1 day À 1 ) was determined from changes in prey abundance in control containers (without O. marina) compared with experimental containers (with predators), following well-established methods that account for changes in both predator and prey abundance over the incubation (for example, Heinbokel, 1978;Kimmance et al, 2006). Specific growth rate of O. marina (r, day À 1 ) was determined as described above (Temperature responses across strains).…”

“…Both in natural and experimental systems, protozoa respond rapidly to increases in prey abundance, with shortterm increases in numbers composed of one or a few similar species that potentially drive predator-prey cycles (Montagnes, 1996;Begun et al, 2004). Furthermore, ambient temperature interacts with prey abundance to alter protozoan rate processes (for example, ingestion, growth, gross growth efficiency, predator-prey dynamics; see Weisse et al, 2002;Atkinson et al, 2003;Montagnes et al, 2003Montagnes et al, , 2008Kimmance et al, 2006). This interaction will also alter predator-prey bloom dynamics.…”