Analysis of climate change risks in support of policymakers to set effective adaptation policies requires an innovative yet rigorous approach towards integrated modelling (IM) of social-ecological systems (SES). Despite continuous advances, IM still faces various challenges that span through both unresolved methodological issues as well as data requirements. On the methodological side, significant improvements have been made for better understanding the dynamics of complex social and ecological systems, but still, the literature and proposed solutions are fragmented. This paper explores available modelling approaches suitable for long-term analysis of SES for supporting climate change adaptation (CCA). It proposes their classification into seven groups, identifies their main strengths and limitations, and lists current data sources of greatest interest. Upon that synthesis, the paper identifies directions for orienting the development of innovative IM, for improved analysis and management of socio-economic systems, thus providing better foundations for effective CCA.

Integrated modelling of social-ecological systems for climate change adaptation

Carlo Giupponi;Stefano Balbi;Fabio Cian;Animesh K. Gain;Arthur Hrast Essenfelder;Vahid Mojtahed;
2022

Abstract

Analysis of climate change risks in support of policymakers to set effective adaptation policies requires an innovative yet rigorous approach towards integrated modelling (IM) of social-ecological systems (SES). Despite continuous advances, IM still faces various challenges that span through both unresolved methodological issues as well as data requirements. On the methodological side, significant improvements have been made for better understanding the dynamics of complex social and ecological systems, but still, the literature and proposed solutions are fragmented. This paper explores available modelling approaches suitable for long-term analysis of SES for supporting climate change adaptation (CCA). It proposes their classification into seven groups, identifies their main strengths and limitations, and lists current data sources of greatest interest. Upon that synthesis, the paper identifies directions for orienting the development of innovative IM, for improved analysis and management of socio-economic systems, thus providing better foundations for effective CCA.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10278/3751142
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