Methods in Ecology and Evolution (Aug 2024)
A wireless, remotely operable and easily customizable robotic flower system
Abstract
Abstract Understanding the complex interactions between external and internal factors that influence pollinator foraging behaviour is essential to understand ecosystem functioning, design agricultural practices or develop effective conservation strategies. However, it remains challenging to collect large and reliable data sets with reasonable personnel and workload. In this study, we present a wireless and cost‐effective robotic flower equipped with internet of things (IoT) technology that automatically offers nectar to visiting insects while monitoring visitation time and duration. The robotic flower is easy to manipulate and settings such as nectar refill rates can be remotely altered, making it ideal for field settings. The system transmits data completely wirelessly and autonomously, is mobile and easy to clean. The prototype settings allow for approximately 2 weeks of uninterrupted data collection for each battery charge. As a proof‐of‐concept application, a foraging preference dual choice experiment with bumblebees was performed. On average, more than 7000 flower visits per colony were registered daily with a set‐up consisting of 16 robotic flowers. The data show a gradual preference shift away from the pre‐trained low concentration, confirming the hypothesis of favouring sugar water with higher concentration. The robotic flower provides accurate and reliable data on insect behaviour, significantly reducing the price and/or labour costs. Although primarily designed for (bumble)bees, the system could be easily adapted for other flower‐visiting insects. The robotic flower is user‐friendly and can be easily adapted to address a wide range of research questions in pollination ecology, conservation biology, biocontrol and ecotoxicology, and allows for detailed studies on how nectar traits, flower colour and shape or pollutants affect foraging behaviour.
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