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Evaluating ecological resilience with global sensitivity and uncertainty analysis

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  • Perz, Stephen G.
  • Muñoz-Carpena, Rafael
  • Kiker, Gregory
  • Holt, Robert D.

Abstract

Concern about catastrophic tipping points has motivated inquiry to better understand ecosystem dynamics in the presence of human action. This requires that we confront multiple challenges in the evaluation of complex systems. One challenge is that resilience has proven difficult to quantify; another issue is that the value of model complexity relative to system complexity is disputed; and finally, local methods for assessing uncertainty are inadequate for more complex models. We address these three challenges simultaneously by proposing a means of evaluating ecological resilience via employment of global sensitivity and uncertainty analysis and comparing models of varying complexity. We suggest that probability distribution functions in output from global sensitivity and uncertainty analysis can be interpreted in terms of ball-and-cup diagrams used in systems theory to visualize ecological resilience. This permits quantification of ecological resilience in terms of the probability of whether a system will remain in a pre-existing state or shift to a different state. We outline the methods for using global sensitivity and uncertainty analysis to evaluate ecological resilience and provide examples from recent research. We highlight applications of these methods to assessment of ecosystem management options in terms of their ramifications for ecological resilience.

Suggested Citation

  • Perz, Stephen G. & Muñoz-Carpena, Rafael & Kiker, Gregory & Holt, Robert D., 2013. "Evaluating ecological resilience with global sensitivity and uncertainty analysis," Ecological Modelling, Elsevier, vol. 263(C), pages 174-186.
    • Handle: RePEc:eee:ecomod:v:263:y:2013:i:c:p:174-186
    DOI: 10.1016/j.ecolmodel.2013.04.024
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    1. Chu-Agor, M.L. & Muñoz-Carpena, R. & Kiker, G.A. & Aiello-Lammens, M.E. & Akçakaya, H.R. & Convertino, M. & Linkov, I., 2012. "Simulating the fate of Florida Snowy Plovers with sea-level rise: Exploring research and management priorities with a global uncertainty and sensitivity analysis perspective," Ecological Modelling, Elsevier, vol. 224(1), pages 33-47.
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    7. Marten Scheffer & Jordi Bascompte & William A. Brock & Victor Brovkin & Stephen R. Carpenter & Vasilis Dakos & Hermann Held & Egbert H. van Nes & Max Rietkerk & George Sugihara, 2009. "Early-warning signals for critical transitions," Nature, Nature, vol. 461(7260), pages 53-59, September.
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    2. Xu Luo & Hong S. He & Yu Liang & Jacob S. Fraser & Jialin Li, 2018. "Mitigating the Effects of Climate Change through Harvesting and Planting in Boreal Forests of Northeastern China," Sustainability, MDPI, vol. 10(10), pages 1-20, October.
    3. 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.
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    5. Isabel Banos-Gonzalez & Julia Martínez-Fernández & Miguel-Ángel Esteve-Selma & Patricia Esteve-Guirao, 2018. "Sensitivity Analysis in Socio-Ecological Models as a Tool in Environmental Policy for Sustainability," Sustainability, MDPI, vol. 10(8), pages 1-30, August.
    6. Fangzheng Li & Yinan Sun & Xiong Li & Xinhua Hao & Wanyi Li & Yun Qian & Haimeng Liu & Haiyan Sun, 2016. "Research on the Sustainable Development of Green-Space in Beijing Using the Dynamic Systems Model," Sustainability, MDPI, vol. 8(10), pages 1-17, September.
    7. Susanne Moser & Sara Meerow & James Arnott & Emily Jack-Scott, 2019. "The turbulent world of resilience: interpretations and themes for transdisciplinary dialogue," Climatic Change, Springer, vol. 153(1), pages 21-40, March.
    8. Tobon Orozco, David & Molina Guerra, Carlos & Vargas Cano, John Harvey, 2016. "Extent of Expected Pigouvian Taxes and Permits for Environmental Services in a General Equilibrium Model with a natural capital constraint," Borradores Departamento de Economía 15258, Universidad de Antioquia, CIE.
    9. Chuan Qin & Yuqing Jin & Meng Tian & Ping Ju & Shun Zhou, 2023. "Comparative Study of Global Sensitivity Analysis and Local Sensitivity Analysis in Power System Parameter Identification," Energies, MDPI, vol. 16(16), pages 1-21, August.
    10. Olaru, Doina & Purchase, Sharon, 2014. "Rethinking validation: Efficient search of the space of parameters for an agent-based model," Australasian marketing journal, Elsevier, vol. 22(1), pages 60-68.

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