Högskolan i Skövde

In this thesis, I present both theoretical and empirical work where we have studied how humans and animals use information in situations where they need to continually update their information on the density of a resource. We have found that the amount of information, and the way the information is presented, are important factors for how well decisions are adapted to current circumstances. In an empirical study on humans, we found that humans seem to have a default idea of the distribution of a resource. This default idea seems to be plastic, i.e. it is adjusted according to incoming information. The way additional information was presented, as well as the information content, was important for how well the default idea was adjusted to current circumstances.

By using mathematical models, we have also studied whether access to information from group members, so called public information, is one of the reasons why some species live in groups. When group members aim to maximize its intake rate of food and share both information and food items found equally, and when each individual has to pay all the cost for travelling between foraging patches, the intake rate of food will decrease with increasing group size. The animals will spend a larger proportion of the time on travelling between patches and less time on foraging the larger the group size. In this case, information sharing on food density in patches is not a reason why animals live in groups.

We have also used mathematical models to study the information dynamics in a group of foraging animals that cannot both search for food and information at the same time. The animals aim to maximize their survival, and are given three behavioural choices in each time step: stay and search for food, stay and scan for information, or leave the current patch. The results show that the choice of behaviour depends on the energy reserves of the individual. An animal with low energy reserves searches for food and leaves the patch if its assessment of potential patch quality decreases to a certain level. An animal with high energy reserves chooses to stay in the patch and scan for information. In our model we assume that when one individual leaves the patch, the rest of the group also leaves. This means that it is those individuals that have low energy reserves that will make the leaving decisions for the group.

In the end, we use these theories on Bayesian foraging, information updating and decision-making in order to develop a new type of effort-based quota for sustainable fisheries management: an effort-based dynamic quota (EDQ). We show that by using information from ongoing fishing combined with fishing data from earlier years, we can reach a higher maximum sustainable yield compared to using a total allowable catch (TAC).