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Stability Analysis of Harvesting Strategies in a Cellular Automata Based Predator-Prey Model

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Cellular Automata (ACRI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4173))

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Abstract

The stability properties of different harvesting strategies are an important aspect of predator-prey system. Most of the previous studies applied a non-spatial approach such as Lotka-Volterra model. In this paper, a stochastic cellular automata based predator-prey model (EcoCA) was developed and verified by the classical Lotka-Volterra model. The EcoCA was then used to investigate the statistical stabilities of different harvesting strategies of the predator-prey complex. Four groups of numerical experiments have been conducted: (1) no harvesting, (2) harvesting prey only, (3) harvesting predator only and (4) harvesting prey and predator jointly. Two harvesting methods, constant quota versus constant effort, are examined for each group. The effects of harvesting criterion are studied as well, which imposes a limit of population density when execute a harvest. The simulation results showed that constant effort leads to statistically more stable behaviors than constant quota. The joint harvesting of prey and predator with a reasonable constant effort can improve system stability and increase the total yields. In addition, it once again confirmed that space places a significant role in the stability properties of the predation and harvesting system, which indicates the importance to use spatially explicit model in conservation ecology.

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© 2006 Springer-Verlag Berlin Heidelberg

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Chen, Q., Mao, J., Li, W. (2006). Stability Analysis of Harvesting Strategies in a Cellular Automata Based Predator-Prey Model. In: El Yacoubi, S., Chopard, B., Bandini, S. (eds) Cellular Automata. ACRI 2006. Lecture Notes in Computer Science, vol 4173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861201_32

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  • DOI: https://doi.org/10.1007/11861201_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40929-8

  • Online ISBN: 978-3-540-40932-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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