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Bio-inspired modelling as a practical tool to manage giant panda population dynamics in captivity

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Abstract

The highly endangered giant panda (Ailuropoda melanoleuca) is the world’s most widely recognised conservation icon. Population dynamics models can get on track to a healthy population for giant pandas, and assess its development over time. This paper proposes a new way to study population dynamics of giant pandas in captivity by means of membrane computing, a bio-inspired computational paradigm based on processing multisets of objects within a cell structure, following a series of evolution rules. This framework is used to model the intrinsically stochastic real-life evolution processes of giant pandas, based on pedigree data. This is the first attempt to collect and analyse so complete source, and to investigate population dynamics of giant pandas based on them. Pedigree data consisting of the number of giant panda individuals per age are provided by Chengdu Research Base of Giant Panda Breeding of China. A special simulator has been developed to assist in the design and formal verification of the mathematical model presented. Particularly, the model feasibility, effectiveness, soundness and robustness have been validated by the simulator, which also enables decision-making based on the simulation results of conducted virtual experiments.

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (61672437 and 61972324) and Sichuan Science and Technology Program (2022YFG0181). We also acknowledge the support of the research project TIN2017-89842-P (MABICAP), co-financed by Ministerio de Economía, Industria y Competitividad (MINECO) of Spain, through the Agencia Estatal de Investigación (AEI) and by Fondo Europeo de Desarrollo Regional (FEDER) of the European Union.

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Authors and Affiliations

  1. School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 611756, China

    Haina Rong & Yingying Duan

  2. Research Group on Natural Computing, Department of Computer Science and Artificial Intelligence, University of Sevilla, 41012, Sevilla, Spain

    Luis Valencia-Cabrera & Mario J. Pérez-Jiménez

  3. School of Automation, Chengdu University of Information Technology, Chengdu, 610225, China

    Gexiang Zhang

  4. Chengdu Research Base of Giant Panda Breeding, Chengdu, 610081, China

    Dunwu Qi

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  1. Haina Rong
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  2. Yingying Duan
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  3. Luis Valencia-Cabrera
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  6. Mario J. Pérez-Jiménez
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Correspondence to Gexiang Zhang.

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Rong, H., Duan, Y., Valencia-Cabrera, L. et al. Bio-inspired modelling as a practical tool to manage giant panda population dynamics in captivity. Nat Comput 22, 133–147 (2023). https://doi.org/10.1007/s11047-022-09903-4

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