Climate Change Impact Modelling Needs to Include Cross-Sectoral Interactions. Harrison, P. A., Dunford, R. W., Holman, I. P., & Rounsevell, M. D. A. 6(9):885–890.
Climate Change Impact Modelling Needs to Include Cross-Sectoral Interactions [link]Paper  doi  abstract   bibtex   
Climate change impact assessments often apply models of individual sectors such as agriculture, forestry and water use without considering interactions between these sectors. This is likely to lead to misrepresentation of impacts, and consequently to poor decisions about climate adaptation. However, no published research assesses the differences between impacts simulated by single-sector and integrated models. Here we compare 14 indicators derived from a set of impact models run within single-sector and integrated frameworks across a range of climate and socio-economic scenarios in Europe. We show that single-sector studies misrepresent the spatial pattern, direction and magnitude of most impacts because they omit the complex interdependencies within human and environmental systems. The discrepancies are particularly pronounced for indicators such as food production and water exploitation, which are highly influenced by other sectors through changes in demand, land suitability and resource competition. Furthermore, the discrepancies are greater under different socio-economic scenarios than different climate scenarios, and at the sub-regional rather than Europe-wide scale. [Excerpt: Sub-regional model outcomes differences] [\n] [...] [\n] The integrated model run shows greater water exploitation values across river basins in much of southern, central and eastern Europe than the single-sector model runs, due to a simulated increase in irrigation, which becomes profitable due to the pressure of meeting food demand with a higher population and reduced imports. However, the spatial distribution of food production varies between the single-sector and integrated model runs. The single-sector runs show higher levels of irrigated food production in much of Spain and central to eastern Europe, whereas in the integrated run food production increases to a greater extent in Fennoscandia, where irrigation is not needed but climate conditions have improved sufficiently to support more agricultural production. This leads to both a reduction in forest cover in northern Europe, as forests are converted to agriculture, and an increase in forest production in areas where food production has decreased. In southern Spain, this reduced need for irrigation leads to less water exploitation compared to the single-sector model outputs. [...]
@article{harrisonClimateChangeImpact2016,
  title = {Climate Change Impact Modelling Needs to Include Cross-Sectoral Interactions},
  author = {Harrison, Paula A. and Dunford, Robert W. and Holman, Ian P. and Rounsevell, Mark D. A.},
  date = {2016-05},
  journaltitle = {Nature Climate Change},
  volume = {6},
  pages = {885--890},
  issn = {1758-678X},
  doi = {10.1038/nclimate3039},
  url = {https://doi.org/10.1038/nclimate3039},
  abstract = {Climate change impact assessments often apply models of individual sectors such as agriculture, forestry and water use without considering interactions between these sectors. This is likely to lead to misrepresentation of impacts, and consequently to poor decisions about climate adaptation. However, no published research assesses the differences between impacts simulated by single-sector and integrated models. Here we compare 14 indicators derived from a set of impact models run within single-sector and integrated frameworks across a range of climate and socio-economic scenarios in Europe. We show that single-sector studies misrepresent the spatial pattern, direction and magnitude of most impacts because they omit the complex interdependencies within human and environmental systems. The discrepancies are particularly pronounced for indicators such as food production and water exploitation, which are highly influenced by other sectors through changes in demand, land suitability and resource competition. Furthermore, the discrepancies are greater under different socio-economic scenarios than different climate scenarios, and at the sub-regional rather than Europe-wide scale.

[Excerpt: Sub-regional model outcomes differences]

[\textbackslash n] [...]

[\textbackslash n] The integrated model run shows greater water exploitation values across river basins in much of southern, central and eastern Europe than the single-sector model runs, due to a simulated increase in irrigation, which becomes profitable due to the pressure of meeting food demand with a higher population and reduced imports. However, the spatial distribution of food production varies between the single-sector and integrated model runs. The single-sector runs show higher levels of irrigated food production in much of Spain and central to eastern Europe, whereas in the integrated run food production increases to a greater extent in Fennoscandia, where irrigation is not needed but climate conditions have improved sufficiently to support more agricultural production. This leads to both a reduction in forest cover in northern Europe, as forests are converted to agriculture, and an increase in forest production in areas where food production has decreased. In southern Spain, this reduced need for irrigation leads to less water exploitation compared to the single-sector model outputs. [...]},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14055125,~to-add-doi-URL,agricultural-resources,biodiversity,climate-change,cross-disciplinary-perspective,forest-resources,integrated-natural-resources-modelling-and-management,integration-techniques,modelling,transdisciplinary-research,uncertainty-propagation,water-resources,wide-scale-transdisciplinary-modelling-for-environment},
  number = {9}
}
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