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Fusing and disaggregating models, data and analysis tools for a dynamic science–society interface

E. C. Rowe, D. G. Wright, N. Bertrand and S. Reis
Geological Society, London, Special Publications, 408, 235-244, 23 June 2014, https://doi.org/10.1144/SP408.1
E. C. Rowe
1Centre for Ecology & Hydrology, Environment Centre Wales, Deiniol Road, Bangor, LL57 2UW, UK
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D. G. Wright
2Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK
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N. Bertrand
2Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK
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S. Reis
3Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK
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Abstract

Society requires rapid, most-probable predictions for specific and/or multifaceted questions related to environmental and geological science. In principle, models that encapsulate disciplinary knowledge are useful tools for making predictions and testing theory, but academic rewards favour disciplinary specialism and a proliferation of often insufficiently tested models. Decision makers have to assess the quality and robustness of predictions for complex environmental issues, and may prefer a model that performs accurately in a case study to a more parsimonious and generalizable model. Predictive ecosystem models tend to grow, as more processes are considered, even when a simpler model may be more appropriate and give results that are easier to interpret within a policy-relevant timeframe. Model fusion provides a practical way to combine knowledge from different disciplines, but can accelerate model growth. How then can we facilitate the evolution of useful predictive models? Coherent design is essential. When combining models it is often necessary to resolve overlapping scope, so tools need to allow for the disaggregation of model implementations as well as their fusion. Modelling software and integration frameworks can help resolve technical constraints, but to make models useful and used it is essential to involve stakeholders in their design and interpretation.

  • © The Geological Society of London 2017
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Geological Society, London, Special Publications: 408 (1)
Geological Society, London, Special Publications
Volume 408
2017
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Fusing and disaggregating models, data and analysis tools for a dynamic science–society interface

E. C. Rowe, D. G. Wright, N. Bertrand and S. Reis
Geological Society, London, Special Publications, 408, 235-244, 23 June 2014, https://doi.org/10.1144/SP408.1
E. C. Rowe
1Centre for Ecology & Hydrology, Environment Centre Wales, Deiniol Road, Bangor, LL57 2UW, UK
  • Find this author on Google Scholar
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  • Search for this author on this site
  • For correspondence: [email protected]
D. G. Wright
2Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
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N. Bertrand
2Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK
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S. Reis
3Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK
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Fusing and disaggregating models, data and analysis tools for a dynamic science–society interface

E. C. Rowe, D. G. Wright, N. Bertrand and S. Reis
Geological Society, London, Special Publications, 408, 235-244, 23 June 2014, https://doi.org/10.1144/SP408.1
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