When complex movement yields simple dispersal: behavioural heterogeneity, spatial spread and parasitism in groups of micro-wasps

Abstract

Background Understanding how behavioural dynamics, inter-individual variability and individual interactions scale-up to shape the spatial spread and dispersal of animal populations is a major challenge in ecology. For biocontrol agents, such as the microscopic Trichogramma parasitic wasps, an understanding of movement strategies is also critical to predict pest-suppression performance in the field. Methods We experimentally studied the spatial propagation of groups of parasitoids and their patterns of parasitism. We investigated whether population spread is density-dependent, how it is affected by the presence of hosts, and whether the spatial distribution of parasitism (dispersal kernel) can be predicted from the observed spread of individuals. Using a novel experimental device and high-throughput imaging techniques, we continuously tracked the spatial spread of groups of parasitoids over large temporal and spatial scales (8 h; and 6 m, ca. 12,000 body lengths). We could thus study how population density, the presence of hosts and their spatial distribution impacted the rate of population spread, the spatial distribution of individuals during population expansion, the overall rate of parasitism and the dispersal kernel (position of parasitism events). Results Higher population density accelerated population spread, but only transiently: the rate of spread reverted to low values after 4 h, in a “tortoise-hare” effect. Interestingly, the presence of hosts suppressed this transiency and permitted a sustained high rate of population spread. Importantly, we found that population spread did not obey classical diffusion, but involved dynamical switches between resident and explorer movement modes. Population distribution was therefore not Gaussian, though surprisingly the distribution of parasitism (dispersal kernel) was. Conclusions Even homogenous asexual groups of insects develop behavioural heterogeneities over a few hours, and the latter control patterns of population spread. Behavioural switching between resident and explorer states determined population distribution, density-dependence and dispersal. A simple Gaussian dispersal kernel did not reflect classical diffusion, but rather the interplay of several non-linearities at individual level. These results highlight the need to take into account behaviour and inter-individual heterogeneity to understand population spread in animals.

MoveR: an R package for easy processing and analysis of animal video-tracking data

“…Finally, MoveR can be useful for conservation purposes by, for instance, helping to better understand how environmental or social factors affect movements and predict the dispersion of invasive populations (i.e., progression front) [24] or biocontrol agents (i.e., pest-suppression performance) [65] through video-phenotyping methods.…”

Study methodology impacts density-dependent dispersal observations: a systematic review

“…Numerous species of migrating animals, such as salmon [ 42 ] and salamanders [ 122 ], will alternate between movement away from a breeding site and aggregation as they return to it, with correlated changes in their density. Alternatively, density may have no perceivable effect on dispersive movements (e.g., [ 51 ]), or its effect on dispersal may vary according to a density ‘threshold’ (e.g., [ 7 , 33 , 78 ]) or even appear to be temporary (e.g., [ 17 ]). Individual assemblages may therefore be linked to different types of density-dependent dispersal: positive, negative, neutral, and even non-linear [ 41 ].…”