Among-individual variation in the swimming behaviour of the amphipod Gammarus pulex under dark and light conditions

In recent years, considerable computational advancements have been made allowing automated analysis of behavioural endpoints using video cameras. However, the results of such analyses are often confounded by a large variation among individuals, making it problematic to derive endpoints that allow distinguishing treatment effects in behavioural studies. In this study, we quantitatively analysed the effects of light conditions on the swimming behaviour of the freshwater amphipod Gammarus pulex by high-throughput tracking, and attempted to unravel among individual variation using size and sex. For this, we developed the R-package Kinematics, allowing for the rapid and reproducible analysis of the swimming behaviour (speed, acceleration, thigmotaxis, curvature and startle response) of G. pulex, as well as any other organism. Our results show a considerable amount of variation among individuals (standard deviation ranging between 5 and 115 % of the average swimming behaviour). The factors size and sex and the interaction between the two only explained a minor part of this found variation. Additionally, our study is the first to quantify the startle response in G. pulex after the light is switched on, and study the variability of this response between individuals. To analyse this startle response, we established two metrics: 1) startle response magnitude (the drop in swimming velocity directly after the light switches on), and 2) startle response duration (the time it takes to recover from the drop in swimming velocity to average swimming speed). Almost 80 % of the individuals showed a clear startle response and, therefore, these metrics demonstrate a great potential for usage in behavioural studies. The findings of this study are important for the development of appropriate experimental set-ups for behavioural experiments with G. pulex.

Automated summary

In recent years, considerable advancements in computational technology have allowed for automated analysis of behavioral endpoints using video cameras. However, the results often suffer from high variation among individuals, making it difficult to accurately determine treatment effects. In this study, the effects of light conditions on the swimming behavior of Gammarus pulex were quantitatively analyzed using high-throughput tracking. The results showed significant individual variation, with size and sex explaining only a small portion of this variation.