Details

Autor(en) / Beteiligte

• Rounsevell, Mark D.A.
• Arneth, Almut
• Brown, Calum
• Cheung, William W.L.
• Gimenez, Olivier
• Holman, Ian
• Leadley, Paul
• Luján, Criscely
• Mahevas, Stéphanie
• Maréchaux, Isabelle
• Pélissier, Raphaël
• Verburg, Peter H.
• Vieilledent, Ghislain
• Wintle, Brendan A.
• Shin, Yunne-Jai

Titel

Identifying uncertainties in scenarios and models of socio-ecological systems in support of decision-making

Ist Teil von

• One earth (Cambridge, Mass.), 2021-07, Vol.4 (7), p.967-985

Ort / Verlag

Elsevier Inc

Erscheinungsjahr

2021

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• There are many sources of uncertainty in scenarios and models of socio-ecological systems, and understanding these uncertainties is critical in supporting informed decision-making about the management of natural resources. Here, we review uncertainty across the steps needed to create socio-ecological scenarios, from narrative storylines to the representation of human and biological processes in models and the estimation of scenario and model parameters. We find that socio-ecological scenarios and models would benefit from moving away from “stylized” approaches that do not consider a wide range of direct drivers and their dependency on indirect drivers. Indeed, a greater focus on the social phenomena is fundamental in understanding the functioning of nature on a human-dominated planet. There is no panacea for dealing with uncertainty, but several approaches to evaluating uncertainty are still not routinely applied in scenario modeling, and this is becoming increasingly unacceptable. However, it is important to avoid uncertainties becoming an excuse for inaction in decision-making when facing environmental challenges. [Display omitted] Decision-makers are faced with many uncertainties within the scenarios and models that they use to explore the future relationships between people and nature. In this paper, we explore the full range of these uncertainties and propose solutions for their better understanding and quantification in support of decision-making. We argue that uncertainties should not preclude policy action but rather should be seen as a key contribution to robust decision-making.