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Teaser, summary, work performed and final results

Periodic Reporting for period 2 - GPS-Bat (Foraging Decision Making in the Real World – revealed from a bat’s point of view by on-board miniature sensors)


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 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.

Work performed

We have made progress in all Work-Packages (WPs) using our recently developed miniature technology (see above).
1) WP 1 – we established our own in-house fruit-bat colony. We have published two papers related to life in this colony one describing the social network of the colony, showing that individuals maintain persistent foraging ties over long periods; and another documenting the ontogeny of social communication in the species. We are now using the data from our colony to study how interactions occurring in the colony influence foraging decision-making.
2) WP 2 - The Mexican fish-eating bat is an example of a species that relies on unpredictable food as it must find flocks of fish in the ocean. The greater mouse-eared bat on the other hand, can return night after night to the same field patch to glean beetles. A first paper comparing the movement and social behavior of these two species has been recently accepted showing that the former species searches for food in groups while the latter always moves alone.
3) WP 3 aimed to examine flexibility in decision-making, that is, to reveal how animals change their decisions based on new incoming information. During three field seasons, we have collected plentiful data on the behavior of the greater mouse-eared bat and we are now analyzing it.
4) WP 4 - We have developed a model of social foraging in bats, which we used to assess how social-movement patterns assist foraging. A paper summarizing this work has recently been submitted.

Final results

We developed several unconventional methodologies in order to enable this ERC project. As mentioned above, we have developed a miniature tag (the Vesper) that weighs less than 2gr and includes an array of sensors: GPS, a microphone (allowing to detect when a bat is attacking prey or interacting with another bat), accelerometers and physiological sensors (allowing to record ECG and EEG). We have successfully tested all of the sensors and are using them to collect data in different parts of the project. Although we developed them to study bats, these tags are currently among the smallest available, and they contain more sensors than any other commercial tag. Our tags are thus being used by many labs around the world, where they are assisting researcher to study bats, and other small animals in the wild.
Another technological achievement of this project is our in-house fruit bat colony. This colony houses wild bats that roost in our facility but are free to forage outside. It thus allows a unique opportunity to monitor an entire mammalian colony of wild animals around the clock and to document the full behavior of wild bats from birth to adulthood. Thanks to this ability, we have recently studied the dynamics of the microbiome of a wild bat colony over time, by repeatedly sampling the same individuals again and again. This would not be possible without the in-house colony. The summary of this study is now under review.
In the period left for the GPSbat project, we intend to complete the work on the four work-packages described above. In WP1, we are working on a project studying how newborn pups learn to navigate in the environment and what is the involvement of their mothers in this learning. In WP2, we aim to compare the behavior of the fish eating bats to the model we developed of searching in a group (see above). In WP3, we plan to analyze the vast data collected in order to develop a framework that explains foraging flexibility. In WP4, we are working on a model that explains why bats should always continue to echolocate when flying in a group.

Website & more info

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