10 Jul 2023
 | 10 Jul 2023

Drivers of tipping points in coupled human-environment systems

Isaiah Farahbakhsh, Chris T. Bauch, and Madhur Anand

Abstract. Mathematical models that couple human behaviour to environmental processes can offer valuable insights into how human behaviour affects various types of ecological, climate and epidemiological systems. In many coupled systems, gradual changes to the human system can lead to abrupt tipping points in the overall system, leading to desirable or undesirable new human-environment states. We review aspects of human behaviour–such as social norms and rates of social change–that drive tipping points in the modelling literature, finding that many affect the coupled system depending on the system type and initial conditions. Structural components in the human system, often represented through social networks, are discussed with many studies showing high structural complexity increases the potential for tipping points. Traditional and state-of-the-art techniques in early warning signals are introduced in relation to the human drivers discussed in previous sections. We conclude with an outline of challenges and promising future directions specific to furthering our understanding and informing policy interventions around promoting sustainability within coupled human-environment systems.

Isaiah Farahbakhsh et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1478', Anonymous Referee #1, 31 Jul 2023
    • AC1: 'Reply on RC1', Isaiah Farahbakhsh, 22 Sep 2023
  • RC2: 'Comment on egusphere-2023-1478', Anonymous Referee #2, 09 Aug 2023
    • AC2: 'Reply on RC2', Isaiah Farahbakhsh, 22 Sep 2023
  • RC3: 'Comment on egusphere-2023-1478', Anonymous Referee #3, 12 Aug 2023
    • AC3: 'Reply on RC3', Isaiah Farahbakhsh, 22 Sep 2023

Isaiah Farahbakhsh et al.

Isaiah Farahbakhsh et al.


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Short summary
Mathematical models that include interactions between humans and the environment can provide valuable information to further our understanding of tipping points. Many aspects of human behaviour such as social norms and rates of social change can affect these tipping points in ways that are often specific to the system being modelled. Higher complexity of social networks can increase the likelihood of these transitions. We discuss how data is used to predict tipping points across many systems.