Internal state effects on behavioral shifts in freely behaving praying mantises (Tenodera sinensis)

Top-down effects of intraspeciflic predator behavioral variation

Among-individual variation in predator traits is ubiquitous in nature. However, variation among populations in this trait variation has been seldom considered in trophic dynamics. This has left unexplored (a) to what degree does among-individual variation in predator traits regulate prey populations and (b) to what degree do these effects vary spatially. We address these questions by examining how predator among-individual variation in functional traits shapes communities across habitats of varying structural complexity, in field conditions. We manipulated Chinese mantis (Tenodera sinensis) density (six or twelve individuals) and behavioral trait variability (activity level by movement on an open field) in experimental patches of old fields with varying habitat complexity (density of plant material). Then, we quantified their impacts on lower trophic levels, specifically prey (arthropods > 4 mm) and plant biomass. Predator behavioral variability only altered prey biomass in structurally complex plots, and this effect depended on mantis density. In the plots with the highest habitat complexity and mantis density, behaviorally variable groups decreased prey biomass by 40.3%. In complex plots with low mantis densities, low levels of behavioral variability decreased prey biomass by 32.2%. Behavioral variability and low habitat complexity also changed prey community composition, namely by increasing ant biomass by 881%. Our results demonstrate that among-individual trait variation can shape species-rich prey communities. Moreover, these effects depend on both predator density and habitat complexity. Incorporating this important facet of ecological diversity revealed normally unnoticed effects of functional traits on the structure and function of food webs.

Learning modifies attention during bumblebee visual search

Abstract

The role of visual search during bee foraging is relatively understudied compared to the choices made by bees. As bees learn about rewards, we predicted that visual search would be modified to prioritise rewarding flowers. To test this, we ran an experiment testing how bee search differs in the initial and later part of training as they learn about flowers with either higher- or lower-quality rewards. We then ran an experiment to see how this prior training with reward influences their search on a subsequent task with different flowers. We used the time spent inspecting flowers as a measure of attention and found that learning increased attention to rewards and away from unrewarding flowers. Higher quality rewards led to decreased attention to non-flower regions, but lower quality rewards did not. Prior experience of lower rewards also led to more attention to higher rewards compared to unrewarding flowers and non-flower regions. Our results suggest that flowers would elicit differences in bee search behaviour depending on the sugar content of their nectar. They also demonstrate the utility of studying visual search and have important implications for understanding the pollination ecology of flowers with different qualities of reward.

Significance statement

Studies investigating how foraging bees learn about reward typically focus on the choices made by the bees. How bees deploy attention and visual search during foraging is less well studied. We analysed flight videos to characterise visual search as bees learn which flowers are rewarding. We found that learning increases the focus of bees on flower regions. We also found that the quality of the reward a flower offers influences how much bees search in non-flower areas. This means that a flower with lower reward attracts less focussed foraging compared to one with a higher reward. Since flowers do differ in floral reward, this has important implications for how focussed pollinators will be on different flowers. Our approach of looking at search behaviour and attention thus advances our understanding of the cognitive ecology of pollination.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00265-024-03432-z.