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Agent-Based Modelling of a Simple Synthetic Rangeland Ecosystem

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Landscape Modelling and Decision Support

Part of the book series: Innovations in Landscape Research ((ILR))

Abstract

The model described in this article aims at simulating free-grazing herbivores in a rangeland landscape. The first aim of the model is to find a balance between the herbivores and the vegetation dynamics guaranteeing sustainability: maintain a healthy animal population and a green landscape. Two opposite processes threaten this equilibrium: overgrazing, leading to desertification; undergrazing leading to bush invasion. Both processes may ultimately lead to the population extinction by starving and pasture invasion by bushy vegetation. The model has been implemented with the NetLogo simulation platform (Wilensky in NetLogo, http://ccl.northwestern.edu/netlogo. Northwestern University, Evanston, IL, 1999). It comprises two types of agents: cells in a spatial grid, standing for land plots, and mobile agents, standing for herbivores (here cattle). The land plots are characterized by their colour: shades of green represent grass as a function of its growth. The herbivores are characterized by attributes like their birth date, age, previous location, destination, pathway, travelled distance, ingested feed, body weight, calving dates. At each simulation time step, the herbivores iterate the following activities: find a destination, move, graze, gain and lose weight, age and, possibly, calve or die. Model simulations can be made to check variants of rangeland landscapes comprising thousands of hectares and herbivore heads. Simulation assessment criteria are the herbage biomass, herbivore population size, individual body weights, birth and mortality rates, land-use patterns and landscape fragmentation obtained after time periods of, possibly, tens of years. We give an example of simulations of a scenario giving rise to the emergence of a “grazing lawn”, that is a highly productive rangeland with a low vegetation standing biomass capable of sustaining a high stocking rate of herbivores. As the model’s ambition is not to mimic real specific rangelands but to offer a generic simple synthetic ecosystem to check ecological hypotheses or theories, we also show how to check the Ideal Free Distribution theory based on the simulated example.

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Notes

  1. 1.

    According to the Russel and Norvig’s (2010) definition: “An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors”.

  2. 2.

    BCR, see Mayer et al. (2012); also called “Relative condition” in the Grazplan model (Freer et al. 1991).

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Acknowledgements

This work has been achieved while I was at the SELMET research unit in Montpellier (France). I am indebted towards several colleagues who provided me (often through informal discussions) with information, ideas, advices, data, documentation and suggestions which helped me to render my model more relevant. They are Olivier Bonnet, Jean-Marie Capron, Laurence Flori, Myriam Grillot, Lionel Julien, Mathieu Lesnoff, Marie-Odile Nozières, Eric Vall and Hugo Valls-Fox. However, all the modelling choices, parameter assignments, model implementation and simulations presented in this article remain of my own responsibility.

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Authors and Affiliations

  1. SELMET Cirad, Inra, Montpellier SupAgro, University of Montpellier, 34398, Montpellier, France

    François Guerrin

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  1. François Guerrin
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Correspondence to François Guerrin .

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Editors and Affiliations

  1. Research Platform Models & Simulation, Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Brandenburg, Germany

    Wilfried Mirschel

  2. Faculty of Land and Water Resources Management, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia

    Vitaly V. Terleev

  3. Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Brandenburg, Germany

    Karl-Otto Wenkel

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Guerrin, F. (2020). Agent-Based Modelling of a Simple Synthetic Rangeland Ecosystem. In: Mirschel, W., Terleev, V., Wenkel, KO. (eds) Landscape Modelling and Decision Support. Innovations in Landscape Research. Springer, Cham. https://doi.org/10.1007/978-3-030-37421-1_10

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