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Title: Modelling feedbacks between human and natural processes in the land system

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 ifmore » 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.« less
Authors:
ORCiD logo [1] ; ORCiD logo [2] ; ORCiD logo [3] ;  [4] ; ORCiD logo [5] ;  [6] ;  [7] ; ORCiD logo [8] ; ORCiD logo [9] ;  [10] ;  [11] ; ORCiD logo [4] ;  [12] ;  [13] ;  [14] ;  [15]
  1. Univ. of Waterloo, ON (Canada). Dept. of Geography and Environmental Management
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Climate and Environmental Sciences Dept.
  3. Univ. of Edinburgh, Scotland (United Kingdom). School of Geosciences; Scotland's Rural College (SRUC), Edinburgh (United Kingdom). Land Economy and Environment Research
  4. Karlsruhe Inst. of Technology (KIT) Garmisch-Partenkirchen (Germany). Inst. of Meteorology and Climate Research – Atmospheric Environmental Research (IMK-IFU)
  5. Arizona State Univ., Tempe, AZ (United States). School of Human Evolution & Social Change and Center for Social Dynamics and Complexity
  6. Univ. of Washington, Seattle, WA (United States). School of Environmental and Forest Sciences
  7. Univ. of Colorado, Boulder, CO (United States). Dartmouth Flood Observatory, Community Surface Dynamics Modeling System, Inst. of Arctic and Alpine Research
  8. Helmholtz-Zentrum Geesthacht, Geesthacht (Germany). Inst. of Coastal Research
  9. National Center for Atmospheric Research, Boulder, CO (United States)
  10. Arizona State Univ., Tempe, AZ (United States). School of Sustainability
  11. Univ. of Birmingham (United Kingdom). School of Geography, Earth and Environmental Sciences, and Birmingham Inst. of Forest Research
  12. Univ. of Edinburgh, Scotland (United Kingdom). School of Geosciences; Karlsruhe Inst. of Technology (KIT) Garmisch-Partenkirchen (Germany). Inst. of Meteorology and Climate Research – Atmospheric Environmental Research (IMK-IFU)
  13. Univ. of Colorado, Boulder, CO (United States). Community Surface Dynamics Modeling System
  14. San Diego State Univ., San Diego, CA (United States). Dept. of Anthropology
  15. Vrije Univ., Amsterdam (Netherlands). Inst. for Environmental Studies
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
Earth System Dynamics (Online)
Additional Journal Information:
Journal Name: Earth System Dynamics (Online); Journal Volume: 9; Journal Issue: 2; Journal ID: ISSN 2190-4987
Publisher:
European Geosciences Union
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23). Climate and Environmental Sciences Division
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES
OSTI Identifier:
1476517

Robinson, Derek T., Di Vittorio, Alan, Alexander, Peter, Arneth, Almut, Barton, C. Michael, Brown, Daniel G., Kettner, Albert, Lemmen, Carsten, O'Neill, Brian C., Janssen, Marco, Pugh, Thomas A. M., Rabin, Sam S., Rounsevell, Mark, Syvitski, James P., Ullah, Isaac, and Verburg, Peter H.. Modelling feedbacks between human and natural processes in the land system. United States: N. p., Web. doi:10.5194/esd-9-895-2018.
Robinson, Derek T., Di Vittorio, Alan, Alexander, Peter, Arneth, Almut, Barton, C. Michael, Brown, Daniel G., Kettner, Albert, Lemmen, Carsten, O'Neill, Brian C., Janssen, Marco, Pugh, Thomas A. M., Rabin, Sam S., Rounsevell, Mark, Syvitski, James P., Ullah, Isaac, & Verburg, Peter H.. Modelling feedbacks between human and natural processes in the land system. United States. doi:10.5194/esd-9-895-2018.
Robinson, Derek T., Di Vittorio, Alan, Alexander, Peter, Arneth, Almut, Barton, C. Michael, Brown, Daniel G., Kettner, Albert, Lemmen, Carsten, O'Neill, Brian C., Janssen, Marco, Pugh, Thomas A. M., Rabin, Sam S., Rounsevell, Mark, Syvitski, James P., Ullah, Isaac, and Verburg, Peter H.. 2018. "Modelling feedbacks between human and natural processes in the land system". United States. doi:10.5194/esd-9-895-2018. https://www.osti.gov/servlets/purl/1476517.
@article{osti_1476517,
title = {Modelling feedbacks between human and natural processes in the land system},
author = {Robinson, Derek T. and Di Vittorio, Alan and Alexander, Peter and Arneth, Almut and Barton, C. Michael and Brown, Daniel G. and Kettner, Albert and Lemmen, Carsten and O'Neill, Brian C. and Janssen, Marco and Pugh, Thomas A. M. and Rabin, Sam S. and Rounsevell, Mark and Syvitski, James P. and Ullah, Isaac and Verburg, Peter H.},
abstractNote = {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.},
doi = {10.5194/esd-9-895-2018},
journal = {Earth System Dynamics (Online)},
number = 2,
volume = 9,
place = {United States},
year = {2018},
month = {1}
}