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Resilience in landscape exploitation systems

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  • Fletcher, C.S.
  • Hilbert, David W.

Abstract

A generic model is developed that describes the broad properties of land-exploitation systems from hunting-gathering societies to modern, intensive agriculture. The framework includes social, economic and ecological drivers of change, going beyond the concept of “sustainability” to establish a paradigm of “resilient exploitation” that calculates the capacity of landscape exploitation systems to survive in uncertain and variable human and natural environments. The model is highly aggregated, consisting of two state variables: (1) human-made capital and labour (H) and (2) natural capital (N). Depending on the parameters, the model displays a single non-trivial equilibrium, two equilibria, or stable limit cycles. Our analysis focuses on the strategies that exploiters employ, through varying their investment in H, and how this affects resilience of the system. We measure resilience as the size of the basin of attraction near a desirable equilibrium and the return time following small perturbations. Four general strategies are analysed and discussed using grazing systems as a particular example: (1) constant stocking rate, (2) maintaining grass stock, (3) constant utilization rate, and (4) a non-linear, compound strategy.

Suggested Citation

  • Fletcher, C.S. & Hilbert, David W., 2007. "Resilience in landscape exploitation systems," Ecological Modelling, Elsevier, vol. 201(3), pages 440-452.
  • Handle: RePEc:eee:ecomod:v:201:y:2007:i:3:p:440-452
    DOI: 10.1016/j.ecolmodel.2006.10.011
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    1. Helena Kahiluoto & Janne Kaseva, 2016. "No Evidence of Trade-Off between Farm Efficiency and Resilience: Dependence of Resource-Use Efficiency on Land-Use Diversity," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-16, September.
    2. A J Higgins & C J Miller & A A Archer & T Ton & C S Fletcher & R R J McAllister, 2010. "Challenges of operations research practice in agricultural value chains," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(6), pages 964-973, June.
    3. Dardonville, Manon & Urruty, Nicolas & Bockstaller, Christian & Therond, Olivier, 2020. "Influence of diversity and intensification level on vulnerability, resilience and robustness of agricultural systems," Agricultural Systems, Elsevier, vol. 184(C).
    4. Rasch, Sebastian & Heckelei, Thomas & Storm, Hugo & Oomen, Roelof & Naumann, Christiane, 2017. "Multi-scale resilience of a communal rangeland system in South Africa," Ecological Economics, Elsevier, vol. 131(C), pages 129-138.
    5. Korhonen, Jouni & Snäkin, Juha-Pekka, 2015. "Quantifying the relationship of resilience and eco-efficiency in complex adaptive energy systems," Ecological Economics, Elsevier, vol. 120(C), pages 83-92.
    6. Jonathan Köhler & Fjalar de Haan & Georg Holtz & Klaus Kubeczko & Enayat Moallemi & George Papachristos & Emile Chappin, 2018. "Modelling Sustainability Transitions: An Assessment of Approaches and Challenges," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(1), pages 1-8.
    7. Shana M. Sundstrom & Craig R. Allen & David G. Angeler, 2020. "Scaling and discontinuities in the global economy," Journal of Evolutionary Economics, Springer, vol. 30(2), pages 319-345, April.
    8. Cai, Y.P. & Huang, G.H. & Tan, Q. & Chen, B., 2011. "Identification of optimal strategies for improving eco-resilience to floods in ecologically vulnerable regions of a wetland," Ecological Modelling, Elsevier, vol. 222(2), pages 360-369.

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