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Kikuchi, D. W.

Publications and source records attributed to Kikuchi, D. W..

3 recordsLinked to original sources

Bumble bees that follow a stricter routine innovate less: Foraging behaviors, environmental complexity, and how they relate to novel problem solving

The ability of animals to innovate - solve novel problems - can shape their ecology and evolution. Here we investigate how individual traits and environmental complexity relate to successful solving of a novel problem. We presented foraging bumble bees (Bombus impatiens) with artificial flowers of not-previously-encountered shapes and recorded the bees latency to access nectar. We measured individual foraging traits across multiple trips with simple flowers that did not require innovation, and bees were foraging either in a simple or complex environment (cluttered flight arena). Bees in complex environments took longer to find and were less likely to land on novel flowers, indicating that environmental complexity may take up cognitive resources and make search more difficult. However, we did not find an effect of environmental treatment on the ability or time to access reward in novel flowers once bees had landed on them. In contrast, behavioral traits significantly predicted how quickly bees solved novel flowers. In particular, overall foraging tempo as well as routine formation, i.e. how much bees followed a fixed route on known flowers, predicted innovation - faster bees innovated faster, and bees with more repetitive foraging sequences were slower to solve the novel tasks. Overall, while the degree of evolutionary novelty in tasks or solutions is always hard to evaluate, our findings demonstrate that environment and individual traits may affect innovation in different ways. Individuals in simple environments may be more likely to detect, and individuals that are generally faster and have a lower tendency to develop fixed routines may be more likely to solve, novel tasks.

animal behavior and cognition↗

Evolution of individual variation in a competitive trait: a theoretical analysis

When competitive traits are costly, negative frequency-dependence can maintain genetic variance. Most theoretical studies examining this question assume binary polymorphisms, yet most trait variation in wild populations is continuous. We propose that continuous trait variation can result from continuous variation in resource quality and that the shape of the resource distribution determines trait maintenance. We used an individual-based model to test which conditions favour the stable maintenance of variation and which cause temporal fluctuations in trait values. This approach, inspired by contrasting outcomes of previous studies, clearly showed the decisive role played by the shape of resource distributions. Under extreme conditions, like the absence of resource variation or with very scarce resources for weak competitors, traits evolved to a single non-competitive or highly competitive strategy, respectively. Some distributions led to strong temporal fluctuations on trait values, whereas others led to the maintenance of large standing variation in competitive traits together with stable mean trait values. Our results thus explain the contradicting outcomes of previous theoretical studies and at the same time provide hypotheses to explain the maintenance of genetic variation and individual differences. We also suggest how the proposed effects of resource variation on trait maintenance can be tested empirically.

evolutionary biology↗

Socially transmitted innovations in dynamic predator-prey systems

Individual behavioral variation is common, yet often we do not know how it is maintained. A potential explanation is that some behaviors must be acquired rather than genetically inherited. We investigate the social transmission of behavioral innovations, which can be key for the success of predator species, especially in contexts where environmental changes take place. We examine innovation in two classic predator-prey models. We assume that innovations increase predator attack rates or conversion efficiencies, or that innovations reduce predator mortality or prey handling time. We find that a common outcome of innovations is the destabilization of the system. Destabilizing effects include increasing oscillations or limit cycles. If either of these outcomes increases the risk of extinction, innovations that benefit individual predators may not have positive long-term effects on predator populations. Furthermore, as populations cycle, innovative individuals can be nearly eliminated, maintaining temporal behavioral variability. The destabilizing effects of behavioral innovations on predator-prey dynamics could have implications for biological invasions, urban populations, endangered species, and, more broadly, the maintenance of behavioral polymorphisms.

animal behavior and cognition↗