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Swimming is of vital importance for aquatic organisms because it determines several aspects of fitness, such as encounter rates with food, predators, and mates. Generally, rotifer swimming speed is measured by manual tracking of the swimming paths filmed in videos. Recently, an open-source package has been developed that integrates different open-source software and allows direct processing and analysis of the swimming paths of moving organisms. Here, we filmed groups of females and males of Keratella cochlearis separately and in a mixed experimental setup. We extracted movement trajectories and swimming speeds and applied the classification method random forest to assign sex to individuals of the mixed setup. Finally, we used advanced statistical methods of movement ecology, namely a hidden Markov model, to investigate swimming states of females and males. When not discriminating swimming states, females swam faster than males, while when discriminating states males swam faster. Specifically, females and males showed two main states of movement with many individuals switching between states resulting in four modes of swimming. We suggest that switching between states is related to predator avoidance. Males of K. cochlearis especially exhibited switching between turning in a restricted area and swimming over longer distances. No mating or other male-female interactions were observed. Our study elucidates the steps necessary for automatic analysis of rotifer trajectories with open-source software. Application of sophisticated software and analytical models will broaden our understanding of zooplankton ecology from the individual to the population level.
Chemostat experiments are employed to study predator-prey and other trophic interactions, frequently using phytoplankton-zooplankton systems. These experiments often use population dynamics as fingerprints of ecological and evolutionary processes, assuming that the contributions of all major actors to these dynamics are known. However, bacteria are often neglected although they are frequently present. We argue that even without external carbon input bacteria may affect the experimental outcomes depending on experimental conditions and the physiological traits of bacteria, phytoplankton, and zooplankton. Using a static carbon flux model and a dynamic simulation model, we predict the minimum and maximum impact of bacteria on phytoplankton-zooplankton population dynamics. Under bacteria-suppressing conditions, we find that the effect of bacteria is indeed negligible and their omission justified. Under bacteria-favoring conditions, however, bacteria may strongly affect average biomasses of phytoplankton and zooplankton. The population dynamics may become highly complex, which may result in wrong interpretations when inferring processes (e.g., trait changes) from population dynamic patterns without considering bacteria. We provide suggestions to reduce the bacterial impact experimentally. Besides optimizing experimental conditions (e.g., the dilution rate) the appropriate choice of the zooplankton predator is decisive. Counterintuitively, bacteria have a larger impact if the predator is not bacterivorous as high bacterial biomasses and complex population dynamics arise via competition for nutrients with the phytoplankton. Only at least partial bacterivory minimizes the impact of bacteria. Our results help to improve the design of chemostat experiments and their interpretation, and advance the study of ecological and evolutionary processes in aquatic food webs.
Global change threatens the maintenance of ecosystem functions that are shaped by the persistence and dynamics of populations. It has been shown that the persistence of species increases if they possess larger trait adaptability. Here, we investigate whether trait adaptability also affects the robustness of population dynamics of interacting species and thereby shapes the reliability of ecosystem functions that are driven by these dynamics. We model co‐adaptation in a predator–prey system as changes to predator offense and prey defense due to evolution or phenotypic plasticity. We investigate how trait adaptation affects the robustness of population dynamics against press perturbations to environmental parameters and against pulse perturbations targeting species abundances and their trait values. Robustness of population dynamics is characterized by resilience, elasticity, and resistance. In addition to employing established measures for resilience and elasticity against pulse perturbations (extinction probability and return time), we propose the warping distance as a new measure for resistance against press perturbations, which compares the shapes and amplitudes of pre‐ and post‐perturbation population dynamics. As expected, we find that the robustness of population dynamics depends on the speed of adaptation, but in nontrivial ways. Elasticity increases with speed of adaptation as the system returns more rapidly to the pre‐perturbation state. Resilience, in turn, is enhanced by intermediate speeds of adaptation, as here trait adaptation dampens biomass oscillations. The resistance of population dynamics strongly depends on the target of the press perturbation, preventing a simple relationship with the adaptation speed. In general, we find that low robustness often coincides with high amplitudes of population dynamics. Hence, amplitudes may indicate the robustness against perturbations also in other natural systems with similar dynamics. Our findings show that besides counteracting extinctions, trait adaptation indeed strongly affects the robustness of population dynamics against press and pulse perturbations.