IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v222y2011i1p210-218.html
   My bibliography  Save this article

Theoretical considerations on the combined use of System Dynamics and individual-based modeling in ecology

Author

Listed:
  • Vincenot, Christian Ernest
  • Giannino, Francesco
  • Rietkerk, Max
  • Moriya, Kazuyuki
  • Mazzoleni, Stefano

Abstract

Modeling could be summed up as the task of reproducing the structure and imitating the behavior of complex real-life systems with components interacting with one another at different scales. In many disciplines of ecology, System Dynamics and more recently Individual-Based modeling have emerged as the major tools to support this task. These techniques have usually been considered until now as exclusive alternatives instead of synergistic tools. The present paper starts by presenting the two approaches, and compares them to identify their strong and weak points depending on the type of components constituting the system under consideration. Then we isolate a class of systems difficult or in some cases impossible to model dynamically using any of these approaches alone, because of conceptual limitations. We further point out the usefulness of merging the two paradigms inside of a hybrid modeling framework to handle this class of systems, and present what we consider as the elementary combination patterns of System Dynamics and Individual-Based modeling. Since the power of this promising approach has been unexplored in most fields of ecology, we suggest some possible applications illustrating its usefulness.

Suggested Citation

  • Vincenot, Christian Ernest & Giannino, Francesco & Rietkerk, Max & Moriya, Kazuyuki & Mazzoleni, Stefano, 2011. "Theoretical considerations on the combined use of System Dynamics and individual-based modeling in ecology," Ecological Modelling, Elsevier, vol. 222(1), pages 210-218.
  • Handle: RePEc:eee:ecomod:v:222:y:2011:i:1:p:210-218
    DOI: 10.1016/j.ecolmodel.2010.09.029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380010005004
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2010.09.029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Esposito, S. & Incerti, G. & Giannino, F. & Russo, D. & Mazzoleni, S., 2010. "Integrated modelling of foraging behaviour, energy budget and memory properties," Ecological Modelling, Elsevier, vol. 221(9), pages 1283-1291.
    2. Bald, J. & Sinquin, A. & Borja, A. & Caill-Milly, N. & Duclercq, B. & Dang, C. & de Montaudouin, X., 2009. "A system dynamics model for the management of the Manila clam, Ruditapes philippinarum (Adams and Reeve, 1850) in the Bay of Arcachon (France)," Ecological Modelling, Elsevier, vol. 220(21), pages 2828-2837.
    3. Hazhir Rahmandad & John Sterman, 2008. "Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models," Management Science, INFORMS, vol. 54(5), pages 998-1014, May.
    4. Kramer-Schadt, Stephanie & Revilla, Eloy & Wiegand, Thorsten & Grimm, Volker, 2007. "Patterns for parameters in simulation models," Ecological Modelling, Elsevier, vol. 204(3), pages 553-556.
    5. Okuyama, Toshinori, 2009. "Local interactions between predators and prey call into question commonly used functional responses," Ecological Modelling, Elsevier, vol. 220(9), pages 1182-1188.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wallentin, Gudrun & Neuwirth, Christian, 2017. "Dynamic hybrid modelling: Switching between AB and SD designs of a predator-prey model," Ecological Modelling, Elsevier, vol. 345(C), pages 165-175.
    2. Wallentin, Gudrun, 2017. "Spatial simulation: A spatial perspective on individual-based ecology—a review," Ecological Modelling, Elsevier, vol. 350(C), pages 30-41.
    3. Yang, Tianxiang & Jing, Dong & Wang, Shoubing, 2015. "Applying and exploring a new modeling approach of functional connectivity regarding ecological network: A case study on the dynamic lines of space syntax," Ecological Modelling, Elsevier, vol. 318(C), pages 126-137.
    4. MISURACA Gianluca & BARCEVICIUS Egidijus & CODAGNONE Cristiano, 2020. "Exploring Digital Government transformation in the EU – Understanding public sector innovation in a data-driven society," JRC Research Reports JRC121548, Joint Research Centre.
    5. Pires, Marcelo A. & Crokidakis, Nuno & Duarte Queirós, Sílvio M., 2022. "Randomness in ecology: The role of complexity on the Allee effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    6. Justin Pence & Zahra Mohaghegh, 2020. "A Discourse on the Incorporation of Organizational Factors into Probabilistic Risk Assessment: Key Questions and Categorical Review," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1183-1211, June.
    7. Khamdamov, T., 2022. "A brief overview of the evolution of computer simulations in economic research," Journal of the New Economic Association, New Economic Association, vol. 54(2), pages 189-207.
    8. Laperrière, Vincent & Brugger, Katharina & Rubel, Franz, 2016. "Cross-scale modeling of a vector-borne disease, from the individual to the metapopulation: The seasonal dynamics of sylvatic plague in Kazakhstan," Ecological Modelling, Elsevier, vol. 342(C), pages 34-48.
    9. Lacitignola, Deborah & Diele, Fasma & Marangi, Carmela, 2015. "Dynamical scenarios from a two-patch predator–prey system with human control – Implications for the conservation of the wolf in the Alta Murgia National Park," Ecological Modelling, Elsevier, vol. 316(C), pages 28-40.
    10. Marilleau, Nicolas & Lang, Christophe & Giraudoux, Patrick, 2018. "Coupling agent-based with equation-based models to study spatially explicit megapopulation dynamics," Ecological Modelling, Elsevier, vol. 384(C), pages 34-42.
    11. Zhao, Xiaodong & Zhang, Hongjian & Tao, Xiaolei, 2013. "Predicting the short-time-scale variability of chlorophyll a in the Elbe River using a Lagrangian-based multi-criterion analog model," Ecological Modelling, Elsevier, vol. 250(C), pages 279-286.
    12. Dianat, Fateme & Khodakarami, Vahid & Hosseini, Seyed-Hossein & Shakouri G, Hamed, 2022. "Combining game theory concepts and system dynamics for evaluating renewable electricity development in fossil-fuel-rich countries in the Middle East and North Africa," Renewable Energy, Elsevier, vol. 190(C), pages 805-821.
    13. Zhang, Z. & Lu, W.X. & Zhao, Y. & Song, W.B., 2014. "Development tendency analysis and evaluation of the water ecological carrying capacity in the Siping area of Jilin Province in China based on system dynamics and analytic hierarchy process," Ecological Modelling, Elsevier, vol. 275(C), pages 9-21.
    14. Nguyen, Le Khanh Ngan & Howick, Susan & Megiddo, Itamar, 2024. "A framework for conceptualising hybrid system dynamics and agent-based simulation models," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1153-1166.
    15. Grimm, Volker & Berger, Uta, 2016. "Structural realism, emergence, and predictions in next-generation ecological modelling: Synthesis from a special issue," Ecological Modelling, Elsevier, vol. 326(C), pages 177-187.
    16. Wang, Jidong & Wu, Jiahui & Che, Yanbo, 2019. "Agent and system dynamics-based hybrid modeling and simulation for multilateral bidding in electricity market," Energy, Elsevier, vol. 180(C), pages 444-456.
    17. Qianjin Dong & Xu Zhang & Yalin Chen & Debin Fang, 2019. "Dynamic Management of a Water Resources-Socioeconomic-Environmental System Based on Feedbacks Using System Dynamics," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(6), pages 2093-2108, April.
    18. Kasimova, R.G. & Obnosov, Yu.V. & Baksht, F.B. & Kacimov, A.R., 2013. "Optimal shape of an anthill dome: Bejan's constructal law revisited," Ecological Modelling, Elsevier, vol. 250(C), pages 384-390.
    19. An, Li & Grimm, Volker & Sullivan, Abigail & Turner II, B.L. & Malleson, Nicolas & Heppenstall, Alison & Vincenot, Christian & Robinson, Derek & Ye, Xinyue & Liu, Jianguo & Lindkvist, Emilie & Tang, W, 2021. "Challenges, tasks, and opportunities in modeling agent-based complex systems," Ecological Modelling, Elsevier, vol. 457(C).
    20. Lewe, J.-H. & Hivin, L.F. & Mavris, D.N., 2014. "A multi-paradigm approach to system dynamics modeling of intercity transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 188-202.
    21. Zhihe Chen & Shuai Wei, 2014. "Application of System Dynamics to Water Security Research," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 287-300, January.
    22. Giovanni Improta & Giuseppe Converso & Teresa Murino & Mosè Gallo & Antonietta Perrone & Maria Romano, 2019. "Analytic Hierarchy Process (AHP) in Dynamic Configuration as a Tool for Health Technology Assessment (HTA): The Case of Biosensing Optoelectronics in Oncology," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1533-1550, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Okuyama, Toshinori, 2011. "Individual variation in prey choice in a predator–prey community," Theoretical Population Biology, Elsevier, vol. 79(3), pages 64-69.
    2. Lewe, J.-H. & Hivin, L.F. & Mavris, D.N., 2014. "A multi-paradigm approach to system dynamics modeling of intercity transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 188-202.
    3. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    4. Ellinas, Christos & Allan, Neil & Johansson, Anders, 2016. "Project systemic risk: Application examples of a network model," International Journal of Production Economics, Elsevier, vol. 182(C), pages 50-62.
    5. Cowan, Kelly R. & Daim, Tugrul U., 2011. "Review of technology acquisition and adoption research in the energy sector," Technology in Society, Elsevier, vol. 33(3), pages 183-199.
    6. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.
    7. Nguyen, Le Khanh Ngan & Howick, Susan & Megiddo, Itamar, 2024. "A framework for conceptualising hybrid system dynamics and agent-based simulation models," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1153-1166.
    8. Jiapeng Qu & Zelin Liu & Zhenggang Guo & Yikang Li & Huakun Zhou, 2021. "A System Dynamics Model for Assessing the Efficacy of Lethal Control for Sustainable Management of Ochotona curzoniae on Tibetan Plateau," Sustainability, MDPI, vol. 13(2), pages 1-11, January.
    9. Santos, Mário & Bastos, Rita & Cabral, João Alexandre, 2013. "Converting conventional ecological datasets in dynamic and dynamic spatially explicit simulations: Current advances and future applications of the Stochastic Dynamic Methodology (StDM)," Ecological Modelling, Elsevier, vol. 258(C), pages 91-100.
    10. Wouter Vermeer & Otto Koppius & Peter Vervest, 2018. "The Radiation-Transmission-Reception (RTR) model of propagation: Implications for the effectiveness of network interventions," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-21, December.
    11. Lei Xu & Ronggui Ding & Lei Wang, 2022. "How to facilitate knowledge diffusion in collaborative innovation projects by adjusting network density and project roles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1353-1379, March.
    12. Jan Kwakkel & Willem Auping, 2021. "Reaction: A commentary on Lustick and Tetlock (2021)," Futures & Foresight Science, John Wiley & Sons, vol. 3(2), June.
    13. Tesfatsion, Leigh, 2017. "Modeling Economic Systems as Locally-Constructive Sequential Games," ISU General Staff Papers 201704300700001022, Iowa State University, Department of Economics.
    14. Abedi, Vahideh Sadat, 2019. "Compartmental diffusion modeling: Describing customer heterogeneity & communication network to support decisions for new product introductions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    15. Lixin Zhou & Jie Lin & Yanfeng Li & Zhenyu Zhang, 2020. "Innovation Diffusion of Mobile Applications in Social Networks: A Multi-Agent System," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    16. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
    17. Teglio, Andrea, 2020. "On the typicality of the representative agent," MPRA Paper 105407, University Library of Munich, Germany.
    18. Rixen, Martin & Weigand, Jürgen, 2014. "Agent-based simulation of policy induced diffusion of smart meters," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 153-167.
    19. Yu Zhao & Shaopeng Wei & Yu Guo & Qing Yang & Xingyan Chen & Qing Li & Fuzhen Zhuang & Ji Liu & Gang Kou, 2022. "Combining Intra-Risk and Contagion Risk for Enterprise Bankruptcy Prediction Using Graph Neural Networks," Papers 2202.03874, arXiv.org, revised Jul 2022.
    20. Hai-hua Hu & Jun Lin & Wen-tian Cui, 2015. "Intervention Strategies and the Diffusion of Collective Behavior," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-16.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:222:y:2011:i:1:p:210-218. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.