Pre‐dispersal context and presence of opposite sex modulate density dependence and sex bias of dispersal

Abstract

Density‐dependent dispersal (DDD) has been observed across taxa, and is expected to affect phenomena such as population dynamics, biological invasions, range expansions, and community assembly. However, little is known about whether the patterns of DDD are robust to changes in the environment. For example, the pre‐dispersal context could affect the physiology of organisms, which in turn could alter their DDD. Similarly, in sexually reproducing organisms, males and females might be differentially affected by the environment, with possible changes in their dispersal properties. To investigate some of these issues, we performed three independent experiments using laboratory populations of Drosophila melanogaster, which tested the effects of pre‐dispersal context, sex of the dispersers and presence of mates on DDD. A two‐patch dispersal setup was used to estimate the dispersal propensity and temporal dispersal profile of adult fruit flies. Comparing the data from two different pre‐dispersal contexts (variable and uniform pre‐dispersal adult densities), we found that longer pre‐dispersal exposure to higher densities led to stronger negative DDD in both males and females. Surprisingly, this change in DDD strength was accompanied by a switch in the direction of sex‐biased dispersal: from female‐biased dispersal at a low density to male‐biased dispersal at a high density. Moreover, we found that patterns of both density dependence and sex bias were contingent upon the interaction of males and females, as neither sex exhibited DDD in the absence of the other. Taken together, these results suggest that DDD and sex‐biased dispersal can be labile and be driven by the environmental context. Finally, we discuss the potential implications of these findings in terms of various ecological and evolutionary processes.

Sex‐biased dispersal: a review of the theory

“…While it is easy for a theoretician to 'switch off' mechanisms from operating (see Section II.2 for examples of how to block kin selection), experimental work has additionally to distinguish between plastic responses to experimental settings (e.g. Mishra et al, 2018;Van Petegem et al, 2018) and long-term evolutionary outcomes, including the potential for phylogenetic inertia (Mabry et al, 2013;Trochet et al, 2016). Theoretical papers become more helpful if they clearly state the expected patterns that would validate -or falsify -the ideas presented, and communication would improve if the idealized model outcomes were discussed against messy features of real life.…”

Mate-finding dispersal reduces local mate limitation and sex bias in dispersal

“…All these populations are outbred and maintained at large population sizes (breeding size ~2400 individuals) at uniform environmental conditions of 25 °C temperature, 24-h light and 80-90% humidity. The first population, DB4, is a descendant of the IV populations, which were wild caught in Amherst, Massachusetts, USA in 1970 (Ives 1970), and its detailed maintenance regime is available elsewhere (Sah, Salve & Dey 2013;Mishra et al 2018b). The population named DBS [DB Scarlet-eyed] comprises individuals with a scarlet eye-color mutation, maintained under similar conditions as DB4.…”

“…We used two-patch source-path-destination setups (sensu Mishra et al 2018a;Mishra et al 2018b;Tung et al 2018b) to study fly dispersal. A source container (100-mL conical glass flask) is connected to a 2-m long path (transparent plastic tube; inner diameter ~1 cm), the other end of which opens into a destination container (250-mL plastic bottle) ( Fig.…”

“…A source container (100-mL conical glass flask) is connected to a 2-m long path (transparent plastic tube; inner diameter ~1 cm), the other end of which opens into a destination container (250-mL plastic bottle) ( Fig. S1; Mishra et al 2018b). For the dispersal assays in this study, we introduced flies into the source and allowed them to disperse for 2 h. During this period, we replaced the destination container with a fresh, empty container every 15 min, with minimum possible disturbance to the rest of the setup.…”

“…In addition, we also estimated the overall temporal distribution of dispersers reaching the destination (similar to Mishra et al 2018b). For this, the number of dispersers that reached the destination during each 15-min interval was divided by the final number of successful dispersers.…”