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Earth System Dynamics An interactive open-access journal of the European Geosciences Union
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Volume 9, issue 2 | Copyright

Special issue: Social dynamics and planetary boundaries in Earth system...

Earth Syst. Dynam., 9, 895-914, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Review article 26 Jun 2018

Review article | 26 Jun 2018

Modelling feedbacks between human and natural processes in the land system

Derek T. Robinson1, Alan Di Vittorio2, Peter Alexander3,4, Almut Arneth5, C. Michael Barton6, Daniel G. Brown7, Albert Kettner8, Carsten Lemmen9, Brian C. O'Neill10, Marco Janssen11, Thomas A. M. Pugh12,13, Sam S. Rabin5, Mark Rounsevell3,5, James P. Syvitski14, Isaac Ullah15, and Peter H. Verburg16 Derek T. Robinson et al.
  • 1Department of Geography and Environmental Management, University of Waterloo, Waterloo, Ontario, Canada
  • 2Climate and Environmental Sciences Department, Lawrence Berkley National Laboratory, Berkeley, California, USA
  • 3School of Geosciences, University of Edinburgh, Drummond Street, Edinburgh, EH8 9XP, UK
  • 4Land Economy and Environment Research, SRUC, West Mains Road, Edinburgh, EH9 3JG, UK
  • 5Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research – Atmospheric Environmental Research (IMK-IFU), Garmisch-Partenkirchen, Germany
  • 6School of Human Evolution & Social Change and Center for Social Dynamics and Complexity, Arizona State University, Tempe, Arizona, USA
  • 7School of Environmental and Forest Sciences, University of Washington, Seattle, Washington, USA
  • 8Dartmouth Flood Observatory,  Community Surface Dynamics Modeling System, Institute of Arctic and Alpine Research, University of Colorado, Boulder, Colorado, USA
  • 9Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany
  • 10National Center for Atmospheric Research, Boulder, Colorado, USA
  • 11School of Sustainability, Arizona State University, Tempe, Arizona, USA
  • 12School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
  • 13Birmingham Institute of Forest Research, University of Birmingham, Birmingham, UK
  • 14Community Surface Dynamics Modeling System, University of Colorado, Boulder, Colorado, USA
  • 15Department of Anthropology, San Diego State University, San Diego, California, USA
  • 16Environmental Geography Group, Institute for Environmental Studies, VU University Amsterdam, Amsterdam, the Netherlands

Abstract. The unprecedented use of Earth's resources by humans, in combination with increasing natural variability in natural processes over the past century, is affecting the evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g. climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. Our understanding of these interactions and feedback between human and natural systems has been formalized through a variety of modelling approaches. However, a common conceptual framework or set of guidelines to model human–natural-system feedbacks is lacking. The presented research lays out a conceptual framework that includes representing model coupling configuration in combination with the frequency of interaction and coordination of communication between coupled models. Four different approaches used to couple representations of the human and natural system are presented in relation to this framework, which vary in the processes represented and in the scale of their application. From the development and experience associated with the four models of coupled human–natural systems, the following eight lessons were identified that if taken into account by future coupled human–natural-systems model developments may increase their success: (1) leverage the power of sensitivity analysis with models, (2) remember modelling is an iterative process, (3) create a common language, (4) make code open-access, (5) ensure consistency, (6) reconcile spatio-temporal mismatch, (7) construct homogeneous units, and (8) incorporating feedback increases non-linearity and variability. Following a discussion of feedbacks, a way forward to expedite model coupling and increase the longevity and interoperability of models is given, which suggests the use of a wrapper container software, a standardized applications programming interface (API), the incorporation of standard names, the mitigation of sunk costs by creating interfaces to multiple coupling frameworks, and the adoption of reproducible workflow environments to wire the pieces together.

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Short summary
Understanding the complexity behind the rapid use of Earth’s resources requires modelling approaches that couple human and natural systems. We propose a framework that comprises the configuration, frequency of interaction, and coordination of communication between models along with eight lessons as guidelines to increase the success of coupled human–natural systems modelling initiatives. We also suggest a way to expedite model coupling and increase the longevity and interoperability of models.
Understanding the complexity behind the rapid use of Earth’s resources requires modelling...