Animals must make crucial decisions during their lifetime. The most common decisions that animals make are foraging decisions. Many species must decide where to forage and how to get there on a daily basis. Despite the immense importance of foraging, our understanding of how animals make foraging decisions under natural conditions is very limited. A major obstacle hindering our ability to study decision processes in the wild is lack of data. Studying decision-making in the field is extremely challenging, because it requires not only monitoring an animal’s movement, but also monitoring its foraging and its interactions with other individuals. This becomes extremely difficult when studying a small animal like a lizard, a song-bird or a bat. The main goal of this ERC project is to develop methods to bridge this knowledge gap and to use these methods to study several fundamental aspects of foraging decision-making, using bats as models.
Our environment is changing today more rapidly than ever, mostly due to human activity. Most animals suffer from this situation; many do not survive it. Only a better understanding of how animals behave in their natural environment, and of their basic needs, will allow developing conservation plans to help them survive. There are numerous examples of conservation plans that failed because of a lack of understanding of the species actual needs.
The first step toward reaching our goal was technological – we aimed to develop miniature tags that can be mounted even on small bats and include several sensors: GPS, accelerometers that allow inferring different behaviors such as flying vs. hanging and a microphone that allows monitoring foraging and interactions with other bats based on recording sound and specifically bat-echolocation. This step has been completed, and we are now using these new tags to study foraging decision-making focusing on four main questions (Work Packages):
1) Social decision-making (in fruitbats) - how does living in a colony assist foraging.
2) Spatial decision-making - we aim to compare the movement and behavior of bats that rely on predictable food, like fruit, and bats that rely on unpredictable food like insects.
3) Flexible decision-making – how animals change their decisions when original decisions turn out to be wrong.
4) Developing a computational frame-work that can explain some of these aspects of decision making.