Ecology in Mare Pentium: an individualbased spatio-temporal model for fish with adapted behaviour
A conceptual approach to study spatial movements of ®sh using an individual-based neural network genetic algorithm model is presented. Arti®cial neural networks, where the weights are adapted using a genetic algorithm, are applied to evolve individual movement behaviour in a spatially heterogeneous...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Text |
| Language: | English |
| Published: |
1998
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| Subjects: | |
| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.323.9391 http://www.bio.uib.no/modelling/papers/Huse_1998_Ecology_in_Mare_Pentium.pdf |
| Summary: | A conceptual approach to study spatial movements of ®sh using an individual-based neural network genetic algorithm model is presented. Arti®cial neural networks, where the weights are adapted using a genetic algorithm, are applied to evolve individual movement behaviour in a spatially heterogeneous and seasonal environment. A 2D physical model (for the Barents Sea) creates monthly temperature ®elds, which again are used to calculate zooplankton production and predation pressure. Daily ®sh movement is controlled by reactive or predictive mechanisms. Reactive movement governs search for local optimal habitats, whereas predictive control enables adaptation to seasonal changes. Levels of growth and predation pressure at the time of decision are used to assess whether to apply reactive or predictive movement control. To make the model realistic on a large scale, each of the individuals are scaled up to represent a clone of one million siblings acting and growing synchronously. The ®sh lives for up to two years, and may reproduce in its second year. In order to spawn it has to be at the designated spawning area in the south-western part of the lattice in January. During spawning it produces a number of offspring in proportion to its body size. The ``genetic constitution' ' of offspring (the weights of the synapses in the neural networks) is a mix of their ``mother's' ' and a randomly picked member of the population. The model is able to solve the problem of navigating in a heterogeneous and seasonal environment. The movement of the arti®cial ®sh follows a seasonal pattern, typical for migrating pelagic ®sh stocks. During summer and autumn the distribution |
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